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A Global Dataset of Palmer Drought Severity Index for 1870–2002: Relationship with Soil Moisture and Effects of Surface Warming
Abstract
A monthly dataset of Palmer Drought Severity Index (PDSI) from 1870 to 2002 is derived using historical precipitation and temperature data for global land areas on a 2.58 grid. Over Illinois, Mongolia, and parts of China and the former Soviet Union, where soil moisture data are available, the PDSI is significantly correlated (r 5 0.5 to 0.7) with observed soil moisture content within the top 1-m depth during warm-season months. The strongest correlation is in late summer and autumn, and the weakest correlation is in spring, when snowmelt plays an important role. Basin-averaged annual PDSI covary closely (r 5 0.6 to 0.8) with streamflow for seven of world's largest rivers and several smaller rivers examined. The results suggest that the PDSI is a good proxy of both surface moisture conditions and streamflow. An empirical orthogonal function (EOF) analysis of the PDSI reveals a fairly linear trend resulting from trends in precipitation and surface temperature and an El Nino- Southern Oscillation (ENSO)-induced mode of mostly interannual variations as the two leading patterns. The global very dry areas, defined as PDSI ,2 3.0, have more than doubled since the 1970s, with a large jump in the early 1980s due to an ENSO-induced precipitation decrease and a subsequent expansion primarily due to surface warming, while global very wet areas (PDSI .1 3.0) declined slightly during the 1980s. Together, the global land areas in either very dry or very wet conditions have increased from ;20% to 38% since 1972, with surface warming as the primary cause after the mid-1980s. These results provide observational evidence for the increasing risk of droughts as anthropogenic global warming progresses and produces both increased temperatures and increased drying.
... The early section of chronologies was truncated with the threshold of 0.85 in expressed population signal (EPS) to denote sufficient strength of the signal for use in paleoclimate reconstruction. [32] in the northeastern Qinghai-Tibetan Plateau. ...
... Meteorological data of 10 stations (ZD, NQ, QML, YS, SQ, QSH, DR, MD, XH, and HN), which were nearby the sampling sites selected to compose the regional chronology and covering a common period as long as possible, were standardized and averaged to illustrate the general climatic characteristics in the study area ( Figure 2). Palmer Drought Severity Index (PDSI) data spanning the instrumental period were extracted from a globally gridded PDSI database [32] for the four relevant grid points ( Figure 1). PDSI data for the four grids (35 • -37.5 • N, 100 • -102.5 • E and 32.5 • -35 • N, 95 • -102.5 • E) were standardized and averaged to represent the regional moisture conditions. ...
... Meteorological data of 10 stations (ZD, NQ, QML, YS, SQ, QSH, DR, MD, XH, and HN), which were nearby the sampling sites selected to compose the regional chronology and covering a common period (1961-2008) as long as possible, were standardized and averaged to illustrate the general climatic characteristics in the study area ( Figure 2). Palmer Drought Severity Index (PDSI) data spanning the instrumental period were extracted from a globally gridded PDSI database [32] for the four relevant grid points ( Figure 1). PDSI data for the four grids (35°-37.5° ...
The climate in the source region of the Yangtze River, Yellow River, and Mekong River is of great research interest because of its sensitivity to global change and its importance in regulating water resources to densely populated and vast areas downstream. A five-century long record of spring (May–June) for the Palmer Drought Severity Index (PDSI) was reconstructed for this region using tree-ring width chronologies of Qilian juniper (Juniperus przewalskii Kom.) from five high-elevation sites. The reconstruction explained 46% variance in the PDSI during the instrumental period 1955–2005. The reconstructed PDSI showed that the occurrence of dry extremes became frequent during the last century relative to the previous four centuries. The standard deviation of the reconstructed PDSI in the 100-year window showed that the recent century held apparent high values of standard deviation in the long-term context. Sustained droughts occurred in periods 1582–1631, 1737–1757, 1772–1791, 1869–1891, 1916–1939, and 1952–1982, whereas relatively wet intervals were observed in 1505–1527, 1543–1564, 1712–1736, 1792–1816, 1852–1868, 1892–1915, and 1983–2008. Notably, in the context of the past five centuries, the study region showed an increased inter-annual variability in the recent century, suggesting an intensified hydroclimatic activity possibly associated with global warming. Moreover, through diagnostic analysis of atmospheric circulation, we found that the negative phase East Asian–Pacific teleconnection pattern may be likely to trigger drought in the study region.
... Less-than-normal water vapor supply and warmer-than-normal temperature are the key factors for a drought (Dai et al., 2004;Briffa et al., 2009;Vicente-Serrano et al., 2010;Jiménez-Muñoz et al., 2016;Drumond et al., 2019Stojanovic et al., 2018Herrera-Estrada et al., 2019;Ding and Gao, 2020;Yuan et al., 2022;Wen et al., 2023). The less-than-normal water vapor supply contributes to the less-than-normal precipitation, resulting in water shortage and drought Stojanovic et al., 2018;Drumond et al., 2019;Herrera-Estrada et al., 2019;Ding and Gao, 2020;Yuan and Yang, 2020;Wen et al., 2023). ...
... It is more difficult for air to reach saturation at higher temperatures; therefore, precipitation is reduced Tu and Lu, 2020;Yuan et al., 2022). Higher temperatures also enhance surface evaporation and dry out soils, contributing to the drought (Dai et al., 2004;Vicente-Serrano et al., 2010;Vicente-Serrano et al., 2014;Jiménez-Muñoz et al., 2016;Ding and Gao, 2020;Wen et al., 2023). ...
... Apart from the contribution of water vapor supply, the more intense and longer droughts observed over many regions are closely linked to warmer temperatures (Dai et al., 2004;Briffa et al., 2009;Vicente-Serrano et al., 2010;Dai, 2011;Vicente-Serrano et al., 2014;Huang et al., 2016;Guan et al., 2019). There is evidence that severe drought events in SWC have been associated with high temperatures Qin et al., 2015;Ding and Gao, 2020;Liu et al., 2022;Wen et al., 2023), such as the droughts that occurred in summer 2009 to spring 2010 and in spring 2021. ...
... D ROUGHT is a prolonged period of low moisture in soil, air, and vegetation that can have far-reaching economic, social, and environmental consequences [1], [2]. In recent years, many studies have highlighted the increase in both the frequency and intensity of droughts [3], [4], which have attracted attention from researchers and policymakers [2]. Drought can result in water scarcity, reduced crop yields, and increased food prices, posing a threat to environmental sustainability, socioeconomic stability, and human society [5]. ...
... Drought can result in water scarcity, reduced crop yields, and increased food prices, posing a threat to environmental sustainability, socioeconomic stability, and human society [5]. Agriculture has been particularly susceptible to drought, which is caused by the effects of climate change (CC) [3], [4]; therefore, monitoring the severity and trend of drought is necessary for establishing early warning systems and supporting irrigation management in the context of CC [6], [7], [9], [9]. ...
Drought, a destructive natural disaster, poses a significant threat to vulnerable areas worldwide. Its occurrence in Taiwan brings up concerns, particularly for vital sectors such as the high-end semiconductor chip industry. Many satellite-based indexes have been developed to monitor the drought. The Temperature-Vegetation Dryness Index (TVDI), a commonly-used drought index, uses an empirical simplification of Land Surface Temperature (LST) and Fractional Vegetation Cover (FVC). The newly-developed Temperature-Soil Moisture Dryness Index (TMDI) using the LST–Normalized Difference Latent Heat Index (NDLI) space is regarded as an alternative to TVDI due to its improved ability in vegetation-sparse areas. This article presents advancements in the TMDI utilizing the novel Fractional Surface Water Availability (FSWA) derived from the NDLI, with an emphasis on enhanced edge selection in the LST–FSWA trapezoidal space for observing drought states. An effective method has been used to select the dry and wet edges within this trapezoid. The ability of the indexes was evaluated using indicators, including the Surface Energy Balance Algorithm for Land (SEBAL)-based Crop Water Stress Index (CWSI) and evapotranspiration (ET), Gross Primary Productivity (GPP), and in-situ precipitation. The results show high correlations (r) between the TVDI and both CWSI and ET, with r values of 0.85 and -0.83, respectively. The TMDI reveals even stronger relationships with CWSI (r = 0.93) and ET (r = -0.94) and is more sensitive than individual variables (FVC, FSWA, and LST) and TVDI. It also indicates a high correlation between the TVDI and GPP (r = -0.69), while the TMDI displays a higher correlation with GPP (r = -0.75). Based on the spatiotemporal analysis, the TMDI was spatially well-matched with CWSI and GPP across most of the study area. Compared to other indexes, the TMDI exhibits the highest sensitivity to precipitation (r = -0.60). By leveraging the CWSI classification, a new TMDI threshold is proposed to assess drought status in south-western Taiwan during the fourth quarter of the years 2014 to 2021. Overall, the TMDI accurately captures spatiotemporal variations in drought status, providing valuable insights for irrigation managers to effectively manage limited water resources.
... Meanwhile, the snowpack that serves as a key component of the water supply was only 38% of the past years' average on 1 April 2022, a time when it should have been its deepest (California Department of Water Resources, 2022b). Although moisture deficiency constitutes an important prerequisite for drought (Dai, 2011;Diffenbaugh et al., 2015), the warmer temperatures greatly exacerbate California's drought by enhancing evapotranspiration demand and depleting available soil moisture (Allen & Anderson, 2018;Cook et al., 2014;Dai et al., 2004;Diffenbaugh et al., 2015;Easterling et al., 2007;Kew et al., 2021;Rind et al., 1990;Trenberth et al., 2014). January through August 2022 ranks California's fifth warmest year, following 2021s warmest summer on record (Becker, 2022). ...
... Alternatively, both PDSI_detrended, which removes the warming trend, and SPI, which only incorporates precipitation changes, have an insignificant tendency in future periods. The downward trend of PDSI is likely a result of enhanced evapotranspiration under future warming (Dai et al., 2004), which is in line with those found in other research (Bonsal et al., 2013;Im et al., 2012). Such results indicate that the warming temperature plays a key role in exacerbating future droughts, substantiating the effectiveness of PDSI in understanding the warming effect in a changing climate. ...
So‐called hot droughts are seen as one of the very foreseeable extremes amid the faster‐than‐expected pace of global warming. In particular, the western part of North America has been pummeled by severe droughts due to a lack of precipitation as well as record‐breaking hot temperatures. This study assesses the joint return period of drought severity and duration using the COordinated Regional Climate Downscaling EXperiment‐COmmon Regional Experiment (CORDEX‐CORE) simulations over the California domain. Six dynamically downscaled simulations with 25 km resolution are analyzed for the historical (1956–2005) and future (2050–2099) periods, whose warming sensitivities differ based on three global climate models (GCMs) driving two regional climate models (RCMs). Our focus is on estimating the joint probabilities of the drought duration and severity constructed from multiple drought indices such as the Palmer Drought Severity Index (PDSI) (with original temperature (PDSI) and its detrended counterpart (PDSI_detrended)) and Standardized Precipitation Index (SPI). Under the RCP8.5 scenario, an unprecedented level of droughts in terms of both duration and severity is likely to emerge only when the drought is characterized by PDSI. A comparison of PDSI and PDSI_detrended explicitly reveals that the occurrence of severe and prolonged droughts is mainly attributed to the warming trend of temperature. Both PDSI_detrended and SPI, which do not incorporate the warming effect explicitly, barely differentiate the joint distributions from the historical and future simulations. Unlike the PDSI based on water budget, the SPI, based on solely accumulated precipitation, shows a loosely coupled joint structure between the severity and duration of droughts, with marked differences in their marginal distributions.
... The higher the value of Palmer Drought Severity Index (PDSI), the stronger the humidity (Dai et al., 2004). The more cloud cover there is, the greater the rainfall probability, so our reconstruction series is positively correlated with both indices over a wide range (Figure 4d,e). ...
... Among them, the correlation between the reconstructed soil moisture and regional PDSI is the highest (r = 0.5-0.6 in Figure 4d), in agreement with a previous study showing that PDSI and soil moisture 0-1 m are significantly correlated in Northeast China (Dai et al., 2004). This is because the calculation of PDSI considers the available water capacity of the soil, precipitation, and potential evapotranspiration, which is used in agriculture as an index to measure the relationship between water supply and demand (Palmer, 1965) and is used as a proxy for soil moisture in many studies (Cook et al., 2015). ...
Permafrost is one of the essential carbon pools in the world. Due to limited studies on historical soil moisture changes and the coupling relationship between soil moisture and temperature in permafrost regions, significant uncertainty exists in the carbon loss in permafrost predicted by different models under global warming scenarios. Based on the tree‐ring width chronology of Pinus sylvestris var. mongholica Litv. growing in the southern edge of the Eurasian continuous permafrost zone, we reconstructed the summer (June–September) 0–1 m soil moisture variations from 1705 to 2009, which could explain 45.6% of the variance in the observed soil moisture. Overall, local precipitation and temperature exhibited statistically significant positive feedback ( p < 0.001) to soil moisture before the 1950s, indicating that the warm/humid climate pattern was conducive to soil moisture conservation before the Anthropocene Epoch. However, the effect of temperature on soil moisture has shifted suddenly to negative since the 1950s, implying that the positive soil moisture‐temperature relationship during the past three centuries has been disrupted by the unprecedented warming in the Modern Warm Period. Furthermore, we found that the temporal relationship of the soil moisture‐temperature (15‐year sliding correlation) in the study area is negatively regulated by the global mean temperature variations ( p < 0.01). The regime shift between soil moisture and temperature might be attributed to the superimposed influence of natural and anthropogenic factors since the 1950s. Although the warming leads to the melting of the permafrost layer, and thus the increase in soil moisture content, the enhanced evapotranspiration caused by warming up results in more water loss and drier soil. This study provides historical evidence of shifted soil moisture‐temperature coupling in the permafrost zone, warning that soil moisture in the permafrost region may further decline under global warming scenarios, thereby affecting vegetation growth and forest carbon sequestration potential.
... We conducted temperature (in degrees Celsius) and precipitation (in millimeters) extractions in Google Earth Engine (Gorelick et al., 2017). We examined the PDSI (Dai, 2011a;Palmer, 1965), which is an index of atmospheric moisture conditions (Dai et al., 2004), to assess whether drought conditions influenced fawn:doe ratios. Moisture conditions range from −10 indicating extreme dryness to 10 indicating extreme wetness where values <−3 indicate extreme drought (Dai, 2011b). ...
... We calculated mean and SD during the one and two months pre-and post-parturition, and during the previous breeding season (fall), for each subpopulation. A recognized limitation to the PDSI is that it generally is not effective at measuring drought on a time scale <12 months (Dai & Zhao, 2017), although there is some indication that it can respond quickly to changes in soil moisture (Dai et al., 2004). ...
Recruitment is one of the fundamental drivers of ungulate population dynamics. Recruitment of neonates into an ungulate population can be influenced by a wide range of abiotic, biotic, and anthropogenic factors. Our objective was to examine which environmental variables most influenced pronghorn ( Antilocapra americana ) fawn recruitment, as measured by fawn:doe ratios, across six subpopulations in Idaho spanning 35 years (1984–2018) of herd composition surveys. Using a retrospective analysis, we examined the influence of precipitation, minimum and maximum temperatures, Palmer drought severity, normalized difference vegetation index (NDVI), vegetation, and elevation across five biological time periods of interest (one and two months pre‐parturition, one and two months post‐parturition, and breeding). Environmental factors, especially the variance in the greenness of vegetation (i.e., NDVI) during the two months post‐parturition (during lactation), were the main drivers of fawn recruitment for subpopulations occupying mountain valleys. Pronghorn fawn recruitment in these mountain valleys was dependent on the condition of the lactating female as influenced by the quality of vegetation, which would subsequently influence fawn growth rates. In contrast, pronghorn recruitment at lower elevations was driven by several environmental variables (i.e., NDVI, drought severity, minimum and maximum temperatures, forb, and grass cover) during the month pre‐parturition. Environmental variables at lower elevations were influencing the condition of the female during gestation which, if favorable, would result in higher birth weights and subsequent increased fawn survival. At intermediate elevation sites, results were mixed with fawn recruitment at one site influenced by low temperatures, which could induce hypothermia in fawns, while recruitment at the other site was influenced by drought severity during gestation (two months pre‐parturition). Influence of these environmental variables was also related to the timing of pronghorn arriving at the high elevation sites (i.e., arriving just prior to fawning); hence, effects were predominantly post‐parturition. In contrast, low elevation sites either had resident pronghorn or earlier arrival; thereby, effects on fawn recruitment were mostly from pre‐parturition variables. Given the range of environmental factors influencing pronghorn subpopulations, managers will need to consider the timing, intensity, and variability of environmental conditions as conditions were spatially and temporally explicit.
... Along with climate change, drought is one of the most complex environmental threats, and it can considerably influence world security, food production, inland water bodies, ecosystem, society, and the financial system (Dai et al., 2004;Koohi et al., 2021;Piniewski et al., 2022;Tian et al., 2020;Wilhite, 2000). Drought could have different definitions in different parts of the world due to the different intrinsic values of water in different societies and regions. ...
... Drought could have different definitions in different parts of the world due to the different intrinsic values of water in different societies and regions. In the worst case, drought can have an adverse effect on daily life; at the same time, in other regions, it could limit recreational activities or maritime transportation (Dai et al., 2004;Harisuseno, 2020;Tian et al., 2020). The description of drought can be divided into various types, including meteorological, hydrological, agricultural, and socioeconomic, based on its influence (Crausbay et al., 2017). ...
In this study, the accuracy of two satellite-based datasets is evaluated. The evaluation includes monthly precipitation estimates, spatial detection of precipitation, and drought monitoring against a regional gridded dataset spanning 2007-2019. A study area covering Poland and parts of the neighboring countries in Central Europe was selected for this evaluation. The Standardized Precipitation Index (SPI) at multi-time scales was employed to monitor meteorological (SPI-3), agricultural (SPI-6, SPI-9), and hydrological (SPI-12) droughts over the study region. This study selected PERSIANN-CDR as a top-down precipitation dataset and SM2RAIN-ASCAT as a bottom-up dataset. According to the results, both datasets exhibit good accuracy for precipitation estimations, but PERSIANN-CDR shows higher accuracy based on the R (coefficient of correlation) and KGE (Kling-Gupta Efficiency) performance indicators. However, SM2RAIN-ASCAT has a lower bias according to PBIAS(%) (percent bias). The reference dataset indicates that the study area experienced dry conditions over 50% of the months. Specifically, based on the reference dataset, 12 (SPI-6) and 16 (SPI-9) severe agricultural droughts were detected. Twenty-four severe agricultural drought events were identified via SPI-6, while the longer SPI window (SPI-9) demonstrated that PERSIANN-CDR assessed 20 severe droughts over the study area. SM2RAIN-ASCAT detected 11 severe agricultural droughts via SPI-6 and SPI-9. Furthermore, based on SPI-12, the reference dataset identified 75 hydrological droughts, while the top-down dataset indicated a lower number of hydrological droughts (67 events) than the reference dataset over the studied period. In contrast, the bottom-up dataset detected 84 hydrological droughts. The spatial distribution of severe meteorological droughts showed a clear pattern with predominant occurrence in eastern parts (Vistula River Basin), as shown by the reference dataset, while this pattern changed for agricultural and hydrological droughts (Odra River Basin). Additionally, the results reveal that meteorological drought does not have a similar spatial distribution to agricultural and hydrological droughts.
... Furthermore, the underlying premise of much academic work in this field is that climate change causes resource scarcity and this scarcity can lead to conflict due to its effects on key aspects of society such as income, food, and capabilities to cope (Koubi, 2019). Although a correlation between drought and conflict has been observed (Dai et al., 2004), for example, a deeper understanding of the mechanisms driving this relationship is necessary to assess the impact of climate change on future conflicts and the relationship of resource scarcity to these dynamics. Research on the Sudan, for example, has found that converging dynamics of resource abundance, militarized state power and global political economic forces may have a much greater explanatory power for the presence of potential conflict and impacts of environmental degradation than mere resource scarcity alone (Selby & Hoffmann, 2012). ...
This Final Report was authored by Dr Erin K. McFee as a consultant for the International Organization for Migration (IOM) within the framework of the IOM project “Increasing the knowledge base on community cohesion and mobility dynamics in the context of climate change and environmental degradation through a selected country-based case study within the Middle East & North Africa (MENA) region”. Dr Amy Krauss, Jonathan R.ders, Connor Christensen and Nicholas Rogers conducted supporting research under the guidance of the study author.
... Daily climate data, including precipitation (PPT), maximum temperature (T max ), and maximum vapor pressure deficit (VPD max ) were obtained from PRISM Climate Group at 4 km resolution (Oregon State University; Daly et al., 2008); and monthly self-calibrated Palmer Drought Severity Index (sc-PDSI) data were obtained separately for the same pixels (WestWide Drought Tracker; Abatzoglou et al., 2017;Palmer, 1965). PDSI is a commonlyused drought index that has shown strong correlations with measured growing season soil moisture content (Dai, 2011;Dai et al., 2004;Wang et al., 2015), and its self-calibrated variant (sc-PDSI) accounts for differences in climate regime among pixels to facilitate site comparisons (Wells et al., 2004). Depth to groundwater (DTG) was calculated for each site based on groundwater elevation data from nearby wells obtained from the California Department of Water Resources' California Statewide Groundwater Elevation Monitoring online portal (CDWR SGMA Data Viewer, 2020), as described in Williams et al. (2022). ...
Drought‐induced groundwater decline and warming associated with climate change are primary threats to dryland riparian woodlands. We used the extreme 2012–2019 drought in southern California as a natural experiment to assess how differences in water‐use strategies and groundwater dependence may influence the drought susceptibility of dryland riparian tree species with overlapping distributions. We analyzed tree‐ring stable carbon and oxygen isotopes collected from two cottonwood species (Populus trichocarpa and P. fremontii) along the semi‐arid Santa Clara River. We also modeled tree source water δ¹⁸O composition to compare with observed source water δ¹⁸O within the floodplain to infer patterns of groundwater reliance. Our results suggest that both species functioned as facultative phreatophytes that used shallow soil moisture when available but ultimately relied on groundwater to maintain physiological function during drought. We also observed apparent species differences in water‐use strategies and groundwater dependence related to their regional distributions. P. fremontii was constrained to more arid river segments and ostensibly used a greater proportion of groundwater to satisfy higher evaporative demand. P. fremontii maintained ∆¹³C at pre‐drought levels up until the peak of the drought, when trees experienced a precipitous decline in ∆¹³C. This response pattern suggests that trees prioritized maintaining photosynthetic processes over hydraulic safety, until a critical point. In contrast, P. trichocarpa showed a more gradual and sustained reduction in ∆¹³C, indicating that drought conditions induced stomatal closure and higher water use efficiency. This strategy may confer drought avoidance for P. trichocarpa while increasing its susceptibility to anticipated climate warming.
... The self-calibrating Palmer Drought Severity Index based on the Penman-Monteith equation for PET (scPDSIpm) 33 incorporates both antecedent and current water supply (P) and demand (PET) to quantify the cumulative departure of surface water balance 34 . By considering these factors, it has been widely used in analyzing hydroclimatic variations over global land 21,29,35,36 . From the perspective of water balance, it remains uncertain whether the weak positive increase in dryland P following tropical eruptions, as indicated by previous study 32 , will lead to significant hydroclimatic responses in drylands. ...
Drylands are highly vulnerable to climate change due to their fragile ecosystems and limited ability to adapt. In contrast to the global drying after tropical volcanic eruptions shown previously, we demonstrate that large tropical volcanic eruptions can induce significant two-year hydroclimatic wetting over drylands by employing the last millennium simulations. During this wetting period, which extends from the first to the third boreal winter after the eruption, several hydroclimatic indicators, such as self-calibrating Palmer Drought Severity Index based on the Penman-Monteith equation for potential evapotranspiration (scPDSIpm), standard precipitation evapotranspiration index (SPEI), aridity index (AI), top-10cm soil moisture (SM 10cm ), and leaf area index (LAI), show significant positive anomalies over most drylands. The primary contribution to the wetting response is the potential evapotranspiration (PET) reduction resulting from dryland surface cooling and reduced solar radiation, as well as a weak contribution from increased precipitation. The latter is due to the wind convergence into drylands caused by slower tropical cooling compared to drylands. The wetting response of drylands to volcanic eruptions also demonstrates some benefits over the global hydrological slowdown resulting from stratospheric aerosol injection, which replicates the cooling effects of volcanic eruptions to address global warming.
... Climate-growth relationship: The primary climatic data for the study region, such as temperature and precipitation, collected from the weather station that the Pakistan Meteorological Department (PMD) established and ran. On the contrary, the DTR and PDSI data were collected from the closest gridded data (Dai et al., 2004). The data series spanning 55 years (AD 1967(AD -2021 was complete, with no missing values. ...
Climate change has severely affected the moist and dry temperate forests of Hindu Kush region, northern Pakistan, specifically impacting the distribution and growth of the west Himalayan fir, known as Abies pindrow. This species, an important representative of the area, is facing significant abiotic stress as a result of rising temperatures and shifting precipitation patterns. We determined whether there is any correlation between the variability of Abies pindrow tree rings and the corresponding variability of the climate factors in the Hindu Kush region. Sixty-three tree ring cores were collected from thirty-one trees of Abies pindrow and developed a tree ring width chronology (AD 1666-2022) for the Dir Upper, Hindu Kush region, northern Pakistan. Radial growth was correlated with climate factors such as temperature, precipitation, Diurnal temperature range (DTR), and Palmer drought severity index (PDSI) in order to identify the major limiting factor for the tree's growth. Precipitation was found to be the most important and driving element influencing the tree growth of Abies pindrow. Precipitation from January to May and winter-spring precipitation had shown significant correlations (p≤0.05) with the radial growth of Abies pindrow. These findings suggest that the sum of precipitation during these periods greatly influences the growth of Abies pindrow. In contrast, temperature does not appear to have a strong impact on radial growth. Other factors, such as DTR and PDSI, have shown weak or insignificant correlations with Tree-Ring Width (TRW), except for a significant negative association between August DTR and TRW. The study findings suggested that the growth of Abies pindrow in the study area was more sensitive to precipitation rather than temperature, DTR, and PDSI. These results highlighted the importance of further dendroclimatological research and climate reconstruction utilizing the tree-ring chronology developed in this study. Such investigations can provide valuable insights into the past climate variations and help understand the long-term ecological dynamics of Abies pindrow forests.
... Because drought is a severe escalator, this natural disaster causes significant losses worldwide (Esfahanian et al., 2017;Gillette, 1950;Jahangir et al., 2013;Wilhite, 2000;Wilhite, 2014). From 1970From -2000, the drought rate increased by 30% worldwide (Dai et al., 2004); in 1960, drought caused up to 40 billion USD of damage, and in 1980 it caused up to 120 billion USD of damage (Domeisen, 1995). In Australia, from 1993Australia, from -2006, the incidence of drought increased by an average of 20% per year (Henry et al., 2007) and had periods of loss of up to 3 billion Australian dollars (ABARES, 2012). ...
The aim of this study is to propose priority strategies for agricultural development amidst drought in Ninh Thuan province, Vietnam. In the context of drought, the agricultural sector faces significant challenges due to the impact of both natural and socioeconomic factors. In order to conduct this research and propose effective strategies, the study utilized the SWOT analysis model via the TOWS matrix, delineating 15 strategies to pinpoint the most fitting approach for the agricultural sector. The study quantified and ranked factors within the SWOT analysis and prioritized strategies using the Fuzzy Analytic Network Process (FANP). The outcomes identified advantageous strategies for agricultural production, emphasizing the evaluation and identification of drought while focusing on market development for economically valuable agricultural products based on primary crops. The step-by-step application of these prioritized strategies aims to contribute to the sustainable development of agricultural production in Ninh Thuan province and facilitate the utilization of a multi-criteria decision-making model in resource and environmental management.
... Although the effects of global warming on droughts are not immediate, it is expected that when droughts occur, they may happen more quickly and intensely [5]. In this context, the frequency, extent, and duration of droughts are all showing an increasing trend [6][7][8]. This poses a significant threat Water 2024, 16, 766 2 of 22 to global agriculture, water resources, ecological and environmental security, and social sustainable development. ...
Poyang Lake, the largest freshwater lake in China, is an important regional water resource and a landmark ecosystem. In recent years, it has experienced a period of prolonged drought. Using appropriate drought indices to describe the drought characteristics of the Poyang Lake Basin (PLB) is of great practical significance in the face of severe drought situations. This article explores the applicability of four drought indices (including the precipitation anomaly index (PJP), standardized precipitation index (SPI), China Z-index (CPZI), and standardized precipitation evapotranspiration index (SPEI)) based on historical facts. A systematic study was conducted on the spatiotemporal evolution patterns of meteorological drought in the PLB based on the optimal drought index. The results show that SPI is more suitable for the description of drought characteristics in the PLB. Meteorological droughts occur frequently in the summer and autumn in the PLB, with the frequency of mild drought being 17.29% and 16.88%, respectively. The impact range of severe drought or worse reached 22.19% and 28.33% of the entire basin, respectively. The probability of drought occurrence in the PLB shows an increasing trend in spring, while in most areas, it shows a decreasing trend in other seasons, with only a slight increase in the upper reaches of the Ganjiang River (UGR). One of the important factors influencing drought in the PLB is atmospheric circulation. The abnormal variation of the Western Pacific Subtropical High was one of the key factors contributing to the severe drought in the PLB in 2022. This study is based on a long-term series of meteorological data and selects the drought index for the PLB. It describes the spatiotemporal distribution characteristics and evolution patterns of drought and investigates the developmental path and influencing factors of drought in typical years. This study provides a reliable scientific basis for similar watershed water resource management.
... was derived from theDai et al. (2004) 2.5 • x 2.5 • monthly gridded data set (central point: 38 • 45'S and 71 • 15'W). To assess the relationships between ENSO variability and the Araucaria tree-ring parameters evaluated in this study, we utilized the sea surface temperatures (SSTs) from El Niño-3 region provided by ESRL/NOAA (https://psl.noaa.gov/gcos_wgsp/Timeseries/Nino3/, ...
Blue intensity (BI) has emerged as an inexpensive and relatively simple method for obtaining a proxy for relative wood density, and it has been successfully tested on several conifer species in Europe, North America, Asia and Australasia. Despite international efforts to promote the use of these methods worldwide, BI chronologies developed for native South American species have not yet been published. The possibility of developing BI chronologies in Araucaria araucana, an emblematic conifer of northern Patagonia, began to be explored some years ago. However, as it has been reported in other species, the wood anatomy of Araucaria presents several difficulties for obtaining robust BI common signals between samples. Therefore, we conducted this study to assess various methods for determining BI parameters based on the degree of common signal between trees in the chronology and their correlation with climatic factors. In this study, we demonstrated the feasibility of developing reliable BI chronologies from a site within the Araucaria range in Argentina by analysing the sensitivity to changes in the width of the measurement window. Although replicating measurements within the same core improved the classical statistic used to quantify the expressed population signal in a chronology (i.e. EPS), the results obtained here show that the chronologies developed using different methods were practically identical. Furthermore, our results revealed different climate signals expressed by both earlywood (EWBI) and latewood (LWBI) BI records, corresponding to the current spring and summer, respectively. In addition, soil water availability was significantly associated with wood density variation. Therefore, the climatic and environmental information provided by BI measurements in Araucaria complements what is already known from ring width (RW) and thus highlights its potential for use in future climate and ecological reconstructions.
... Agricultural drought results from low soil moisture (Zhang et al., 2021), and socioeconomic drought encompasses the impacts on society and the economy (Wang et al., 2022a(Wang et al., , 2022b. While these drought indices can describe meteorological factors affecting drought, they struggle to objectively quantify the temporal and spatial characteristics of drought evolution (Dai et al., 2004;Vicente-Serrano et al., 2011). Furthermore, they fail to consider the impact of water and heat stress on vegetation growth, and insufficiently incorporate information regarding land cover and vegetation of the underlying surface. ...
... There are multiple indices available that offer diverse perspectives in characterizing drought conditions 4,8,12,13 . Commonly used indices include the Palmer Drought Severity Index (PDSI), the self-calibrating Palmer Drought Severity Index (scPDSI), and the Standardized Precipitation Index (SPI) [14][15][16] . However, the PDSI and scPDSI have issues with fixed timescales, inadequate data-related calibration, and limited spatial comparability 17 . ...
The future state of drought in China under climate change remains uncertain. This study investigates drought events, focusing on the region of China, using simulations from five global climate models (GCMs) under three Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, and SSP5-8.5) participating in the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b). The daily Standardized Precipitation Evapotranspiration Index (SPEI) is employed to analyze drought severity, duration, and frequency over three future periods. Evaluation of the GCMs’ simulations against observational data indicates their effectiveness in capturing historical climatic change across China. The rapid increase in CO 2 concentration under high-emission scenarios in the mid- and late-future century (2040–2070 and 2071–2100) substantially influences vegetation behavior via regulation on leaf stomata and canopy structure. This regulation decelerates the increase in potential evapotranspiration, thereby mitigating the sharp rise in future drought occurrences in China. These findings offer valuable insights for policymakers and stakeholders to develop strategies and measures for mitigating and adapting to future drought conditions in China.
... We also find that the spatial extent of drylands changed due to alterations in the aridity index (i.e., P/PET) caused by climate change, which is associated with modifications in precipitation, temperature, and potential evapotranspiration (PET). Moreover, using Palmer Drought Severity Index (PDSI), Dai et al. (2004) showed that very dry areas (PDSI < − 3.0) have increased by more than double of its size around the world since the 1970s, with a significant increase in the early 1980s due to precipitation decreases caused by ENSO and later because of surface warming. Expansion of dryland can alter the hydrological water budget between land and atmosphere, making life more miserable (Wang et al., 2012;D'Odorico and Bhattachan, 2012). ...
... The Empirical Orthogonal Function (EOF) method is a statistical decomposition approach that extracts useful information by reducing dimensionality [120][121][122][123] . It is widely used for the identification of dominant spatiotemporal patterns of geophysical variables, especially in the field of global change 121,[124][125][126] . A set of EOF for a specific variable or data-set with m observations at n stations (giving an m × n matrix X), can be denoted as: ...
Droughts or floods are usually attributed to precipitation deficits or surpluses, both of which may become more frequent and severe under continued global warming. Concurring large-scale droughts in the Southwest and flooding in the Southeast of China in recent decades have attracted considerable attention, but their causes and interrelations are not well understood. Here, we examine spatiotemporal changes in hydrometeorological variables and investigate the mechanism underlying contrasting soil dryness/wetness patterns over a 54-year period (1965–2018) across a representative mega-watershed in South China—the West River Basin. We demonstrate that increasing rainfall intensity leads to severe drying upstream with decreases in soil water storage, water yield, and baseflow, versus increases therein downstream. Our study highlights a simultaneous occurrence of increased drought and flooding risks due to contrasting interactions between rainfall intensification and topography across the river basin, implying increasingly vulnerable water and food security under continued climate change.
... Examples of operational SMA products used in large-scale drought monitoring systems are the ones included in the Global Drought In practice, because soil moisture observations are sparsely distributed and available over too short of a record to capture climate variability, the soil moisture values that are used in drought monitoring are often retrieved through indirect methods, including physically based hydrological or land surface models, and remote sensing data (Cammalleri et al., 2017). Additional tools for identifying soil moisture droughts, in the absence of specific information on soil moisture conditions, include indices that are based on a simplified water balance, such as the Palmer drought severity index (Dai et al., 2004), or meteorological drought indices that are computed at appropriated aggregation time scales, such as the Standardized Precipitation Index (SPI, McKee et al., 1993) and the Standardized Precipitation Evapotranspiration Index (SPEI, Vicente-Serrano et al., 2010). ...
The Standardized Precipitation Index (SPI) is the most commonly used index for detecting and characterizing meteorological droughts, and it is also extensively used as a proxy variable for Soil Moisture Anomalies (SMA) for the purpose of monitoring agricultural drought in absence of long-term soil moisture observations. However, the potential capability of SPI to warn of the time-lagged soil water deficit - following the well-known “drought cascade” effect - is often overlooked in agricultural drought studies. In this research, a time-lagged correlation analysis is used to evaluate the relationship between the SMA dataset, generated as part of the Global Drought Observatory of the EUs Copernicus Emergency Management Service, and a set of SPIs derived from the ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts. The possibility to achieve an optimal agreement between SPI and SMA that also preserves the early warning skills of SPI is evaluated. The results suggest that if only the correlation between SPI and SMA is considered, the maximum agreement is usually obtained with a zero lead time (almost 80% of the cases), with SPI-3 representing the best option in about 40% of the grid cells at global scale. By also accounting for the benefits of a positive lead time, short accumulation periods tend to be favored, with SPI-1 being the optimal choice in about half of the cases, and 10 to 20 days lead time in more than 90% of the grid cells is achieved without any significant reduction in either correlation or skill in drought extreme detection.
... Profile soil moisture (PSM), which refers to the soil water content in the whole soil layer, is the key variable in ecological, agricultural, and hydrological systems since it controls the major processes related to biological interaction, vegetation growth, and runoff generation [1][2][3]. In recent years, abundant studies have been conducted to investigate the temporal change in PSM based on in situ soil moisture datasets or other long time-series soil moisture datasets, but less attention is paid to its spatial distribution during a specific time period [4][5][6][7][8][9][10]. The spatial heterogeneity of PSM, which refers to the uneven distribution and complexity of data in space, helps develop refined partitioned management strategies in ecological, agricultural, and hydrological fields. ...
Profile soil moisture (PSM), the soil water content in the whole soil layer, directly controls the major processes related to biological interaction, vegetation growth, and runoff generation. Its spatial heterogeneity, which refers to the uneven distribution and complexity in space, influences refined spatial management and decision-making in ecological, agricultural, and hydrological systems. Satellite instruments and hydrological models are two important sources of spatial information on PSM, but there is still a gap in understanding their potential mechanisms that affect spatial heterogeneity. This study is designed to identify the spatial heterogeneity and the driving factors of two PSM datasets; one is preprocessed from a satellite product (European Space Agency Climate Change Initiative, ESA CCI), and the other is simulated from a distributed hydrological model (the DEM-based distributed rainfall-runoff model, DDRM). Three catchments with different climate conditions were chosen as the study area. By considering the scale dependence of spatial heterogeneity, the profile saturation degree (PSD) datasets from different sources (shown as ESA CCI PSD and DDRM PSD, respectively) during 2017 that are matched in terms of spatial scale and physical properties were acquired first based on the calibration data from 2014–2016, and then the spatial heterogeneity of the PSD from different sources was identified by using spatial statistical analysis and the semi-variogram method, followed by the geographic detector method, to investigate the driving factors. The results indicate that (1) ESA CCI and DDRM PSD are similar for seasonal changes and are overall consistent and locally different in terms of the spatial variations in catchment with different climate conditions; (2) based on spatial statistical analysis, the spatial heterogeneity of PSD reduces after spatial rescaling; at the same spatial scale, DDRM PSD shows higher spatial heterogeneity than ESA CCI PSD, and the low-flow period shows higher spatial heterogeneity than the high-flow period; (3) based on the semi-variogram method, both ESA CCI and DDRM PSD show strong spatial heterogeneity in most cases, in which the proportion of C/(C0 + C) is higher than 0.75, and the spatial data in the low-flow period mostly show larger spatial heterogeneity, in which the proportion is higher than 0.9; the spatial heterogeneity of PSD is higher in the semi-arid catchment; (4) the first three driving factors of the spatial heterogeneity of both ESA CCI and DDRM PSD are DEM, precipitation, and soil type in most cases, contributing more than 50% to spatial heterogeneity; (5) precipitation contributes most to ESA CCI PSD in the low-flow period, and there is no obvious high contribution of precipitation to DDRM PSD. The research provides insights into the spatial heterogeneity of PSM, which helps develop refined modeling and spatial management strategies for soil moisture in ecological, agricultural, and hydrological fields.
... As one of the most widely used meteorological drought indices, the Palmer Drought Severity Index (PDSI) (Palmer 1965) estimates relative dryness from temperature and precipitation measurements (Dai et al. 2004;Sheffield et al. 2012). To facilitate comparisons of drought conditions across diverse climate conditions, the self-calibrated PDSI dynamically calculates parameters according to local climate instead of using empirical constants (Wells et al. 2004). ...
Among the global monsoon systems, the Asian summer monsoon (ASM) reaches the furthest north into eastern Asia and separates it into the monsoon- and westerlies-dominated regions. Paleoclimate studies revealed different hydroclimate patterns between the monsoon- and westerlies-dominated regions at glacial-interglacial and centennial timescales. The monsoon-westerlies boundaries are difficult to be quantified with the instrumental data. Herein, a monsoon-westerlies dipole pattern was identified by empirical orthogonal function (EOF) analysis of the Palmer Drought Severity Index (PDSI) for the 1900–2018 period on interdecadal timescales. This dipole pattern showed significant correlations with variations of the monsoon-related western Pacific sea surface temperature (SST) and the westerlies-related North Atlantic Oscillation (NAO). We then reconstructed the dipole pattern back to 1511 by tree rings, which was consistent with the reconstructed NAO at interdecadal timescale. Our reconstruction revealed long-term changes of monsoon-westerlies boundaries and provided evidence of their linkages with the NAO. Apart from anthropogenic forcing, climate internal variability also play a critical role in modulations of the dipole mode between ASM and westerlies at interdecadal timescale.
... We extracted the monthly climatic data (average, minimum and maximum temperature, and average precipitation) of each year for each site. We also used the monthly Palmer Drought Severity Index (PDSI; Palmer 1965) dataset updated by (Dai et al., 2004). It is a standardized index that generally spans − 10 (dry) to +10 (wet). ...
... Similar results have been found in previous studies. For example, Dai et al. [64] reported that the PDSI in most areas of China showed a significant correlation with soil moisture at a depth of 1 m. Mika et al. [65] showed that the correlation between soil moisture and the PDSI in the Great Hungarian Plain from November to April was higher than that in May to October. ...
Drought is a natural disaster with severe global agricultural and economic impacts. Accurate drought indices are needed for improved assessment and monitoring; however, most existing drought indices poorly represent agricultural drought due to complex interactions among meteorological factors, crop and soil conditions. Here, we compute an integrated drought condition index (IDCI) based on the 3-month standardized precipitation evapotranspiration index (SPEI3), vegetation cover index (VCI) and soil moisture condition index (SMCI). We apply the IDCI to monitoring agricultural drought in Xinjiang, China. After regional evaluations with soil moisture, precipitation and air temperature observations, as well as with the scaled crop yields index, the IDCI was used to describe spatiotemporal changes in regional drought in Xinjiang during 2000–2018, revealing adverse impacts on crop yield (beet, wheat and vegetables). The IDCI is strongly correlated with observed soil moisture and performs better than SMCI, VCI or SPEI3, demonstrating that the IDCI is suitable for agricultural drought monitoring. The most severe drought occurred in the spring to autumn of 2008. Droughts before 2008 were more serious than those after 2008, in terms of both severity and frequency. Droughts in northern, southern and eastern Xinjiang, as well as in the Tianshan Mountains, were generally increasing before 2008 and then weakened after 2008.
... The Prediction maps of the probability of occurrence for plots. Dai et al., 2004;Amani et al., 2017). For sufficient soil moisture, precipitation is the main factor (Tromp-van Meerveld and McDonnell, 2006;Molina-Moral et al., 2022), however, microrelief across sites and amount of vegetation on the sites also have a large impact on soil moisture. ...
Three-dimensional (3D) mapping and unmanned aerial vehicles (UAVs) are essential components of the future development of forestry technology. Regeneration of forest stands must be ensured according to the law in the required quality and species composition. Forest management focuses on the optimization of economic costs and quality-assured seedlings. Predicting the suitability of the plots’ environment for natural forest regeneration can contribute to better strategic planning and save time and money by reducing manual work. Although the savings may be considered negligible on small forested plots, they are significant for large cleared areas, such as those harvested after large beetle infestations or strong windstorms, which are increasingly common in European forests. We present a methodology based on spatial analysis and 3D mapping to study the microrelief and surrounding of recently cleared areas. We collected data on four plots in the spring and autumn of a single year after the harvest of four Norway spruce [Picea abies (L.) Karst.] stands near Radlice, Czechia using a multirotor Phantom 4 Pro UAV with a red, green, blue (RGB) camera. We used RGB imagery to compute microrelief data at a very high spatial resolution and the surrounding forest stands after harvesting. We used the microrelief data to estimate the amount of water accumulation and incoming solar radiation across the sites. Based on presence data of newly-established seedlings, we used linear mixed effects models to create a suitability map for each site. Model variables included topographic wetness index, solar area radiation, fencing, type of soil preparation, and distance to the nearest mature forest edge. The topographic wetness index and fencing had strong positive influence on seedling establishment, while solar radiation had a negative influence. Our proposed methodology could be used to predict spontaneous regeneration on cleared harvest areas, or it can estimate how much area is suitable for regeneration, which can lead to important investment decisions.
... Constructing a drought index is an effective method for analysing drought, and choosing an objective and reasonable drought index can effectively assess the drought situation in different regions [7][8][9]. Drought indices include the standardized precipitation index (SPI) [10], the Palmer Drought Severity Index (PDSI) [11], the Precipitation anomaly (Pa) [12], and the Standardized Precipitation Evapotranspiration Index (SPEI) [13]. SPI, based on station precipitation, is favoured by many because of the ease of access to the required rainfall information and the simplicity of the calculation [14,15], and has been widely used in research for identifying drought events in different regions [16], evaluating drought indicators [17], analysing the intensity of drought [18], analysing the frequency of drought [19], identifying drought-prone areas [20], as well as monitoring and evaluating drought [21]. ...
Drought refers to a meteorological disaster that results in insufficient soil moisture due to a long-term lack of rainfall and disrupts the moisture balance of crops. Yinshanbeilu in Inner Mongolia is an arid and semi-arid region, and the onset of drought and its subsequent transmission is a key challenge in water resource management. This study takes Yinshanbeilu as the study area, analyses the changing characteristics of multi-timescale drought from 1971 to 2020 based on the Standardised Precipitation Index (SPI), and analyses the stochasticity and stability of the drought by using a cloud model. Finally, the cross-wavelet transform method and Pearson’s test are used to explore the correlation between atmospheric circulation factors, PRE and PET, and drought. The results indicate that (1) on the annual scale, the frequency of drought in Yinshanbeilu mainly ranges from 22% to 28%, with a high frequency of light droughts, a low frequency of severe droughts, a high frequency of droughts in the east and west, and a low frequency of droughts in the north and south; on the seasonal scale, the frequency of droughts in winter is the highest, with a rate of 34.6%, and the lowest frequency of droughts is in autumn, with a rate of 28.3%. (2) There is a decreasing trend in Entropy (En) and Hyper-Entropy (He), and an increasing trend in Expectation (Ex) for the inter-annual SPI-12 cloud model. Spatially, Ex and He are negatively correlated, while En and He are positively correlated. The inter-annual variation in cloud eigenvalues is greater than the inter-site variation, so the cloud model better reflects the spatial stochasticity and stability of regional inter-annual SPI. For the seasonal-scale SPI-3 cloud model, Ex is smaller in all seasons, En is also smaller, and He is larger. (3) Sunspot, PRE (precipitation), and PET (Potential Evapotranspiration) are all positively correlated with SPI and have the highest correlation. This study reveals the characteristics and causes of variations of drought in Yinshanbeilu, which can be applied to future research areas related to regional drought risk management.
... Soil moisture, as a critical parameter characterizing global land surface hydrological cycles, has extensive applications in various fields, such as hydrology [1,2], meteorology [3,4], climatology [5,6], and water resource management [7,8]. It serves as a crucial state variable in the climate system, governing the exchange of water, energy, and carbon fluxes between the land surface and the atmosphere. ...
Soil moisture (SM), as a crucial input variable of land surface processes, plays a pivotal role in the global hydrological cycle. The aim of this paper is to examine the spatiotemporal variability in SM in the Heihe River Basin using all-weather land surface temperature (LST) and reanalysis land surface data. Initially, we downscaled and generated daily 1 km all-weather SM data (2020) for the Heihe River Basin. Subsequently, we investigated the spatial and temporal patterns of SM using geostatistical and time stability methods. The driving forces of the monthly SM were studied using the optimal parameter-based geographical detector (OPGD) model. The results indicate that the monthly mean values of the downscaled SM data range from 0.115 to 0.146, with a consistently lower SM content and suitable temporal stability throughout the year. Geostatistical analysis revealed that months with a higher SM level exhibit larger random errors and higher variability. Driving analysis based on the factor detector demonstrated that in months with a lower SM level, the q values of each driving factor are relatively small, and the primary driving factors are land cover and elevation. Conversely, in months with a higher SM level, the q values for each driving factor are larger, and the primary driving factors are the normalized difference vegetation index and LST. Furthermore, interaction detector analysis suggested that the spatiotemporal variation in SM is not influenced by a single driving factor but is the result of the interaction among multiple driving factors, with most interactions enhancing the combined effect of two factors.
... Thanks to the Senegal River, flood recession agriculture was developed in this area, but it subsequently showed its limitations and demonstrated the fragility of this ecosystem. This was particularly true during the droughts that hit the region around [1969][1970], which resulted in a shortening of the rainy season (Ali 2004;Hubert et al. 2007;Sow 2007;Abrate et al. 2013;Faye 2013;Bodian et al. 2016a, b), a drastic decrease in river flows and a cessation of flow in some stretches (Nicholson et al. 2000;Chappell and Agnew 2004;Dai et al. 2004). This downward trend in rainfall is an irregular and unpredictable phenomenon with disastrous consequences for yields (Gnamou-Petauton 2010;Nechifor and Winning 2019). ...
In the Senegal River delta, the expansion of irrigated land to meet the growing food demands, combined with the effects of climate change will lead to an increasing in the demand for agriculture water. Hence, it is essential to assess the agricultural water requirements of main crops in order to optimize the management of water resources and contribute to sustainable development in the delta. This study aims to evaluate the irrigation water requirements of the main crops of the Senegal river Delta. The determination of irrigation water requirements is based on the Penman–Monteith method, crop coefficient of the main crops, and irrigation efficiency. Data from NASA’s Prediction of Worldwide Energy Resources was used to calculate reference evapotranspiration. The spatial analysis of the crop water requirements was carried out using the inverse distance weighting method. The results showed that irrigation water requirements vary according to season, sowing date, and variety. In the hot dry season, the 115- and 125-day cycle Sahel varieties have irrigation water requirements ranging from 12,823 to 16,634 m³/ha. For the 150-day cycle varieties sown in the warm season, water requirements vary from 15,191 to 19,996 m³/ha. During the cold season, onions have irrigation water requirements that vary from 10,891 to 13,166 m³/ha. For tomato, they range from 8460 to 10,418 m³/ha. Irrigation water requirements increase gradually from the northwest to the northeast of the delta for all seasons and crops. This study could contribute to the development of strategies for optimizing irrigation water management based on sowing dates and crops.
... Therefore, for WTA and WTSA zones, ISA% is negatively correlated with LST. Pre-season precipitation predominates in plant growth (Dai et al., 2004), and soil water availability governs the SOS (Los et al., 2001;Zhang et al., 2005), making SOS start around the rainy season in arid climates (Chesson et al., 2004;Du et al., 2020). There are two explanations for the latitudinal symmetry of SOS in the rural-urban ecosystem, one according to the chilling requirement and the other based on the sensitivity to spring temperature. ...
A R T I C L E I N F O Keywords: Spring vegetation phenology urbanization urban heat island effect climates rural-urban ecosystem A B S T R A C T Cities have been considered ideal surrogates for evaluating ecological responses to climate warming. Although research has revealed that the urban heat island effect is not the only determinant that drives the rural-urban difference in spring phenology, limited attempts further explore the effect of complex interactions between urbanization and climates on the start of the season (SOS). Here, we employed the percentage of impervious surface area as an indicator of urbanization levels, incorporating the urban heat island (UHI) effect and climates to decipher the multiple effects on the temporal shift in SOS. Our results suggest that urbanization, the UHI effect, and climates jointly drive the phenological timing in cities. The SOS is highly linearly correlated with urbanization levels and UHI effects (p<0.001) in the zones with warm and humid climates, whereas relatively warmer, cooler, or arid climates break down the linearity. Geographically, the SOS is north-south symmetrical for the rural-urban ecosystem at the national scale, which initiates at the mid-latitudes (around 30 • N, 67.58 DOY ± 2.23 days) first and then towards the low (around 20 • N, 105.25 DOY ± 1.31 days) and high-latitudes (45 • N, 123.01 DOY ± 1.45 days). Chilling accumulation and spring temperature jointly contribute to this phenomenon. As the UHI effect is similar to the projected global warming in the future, understanding the phenological responses to urbanization in various climates is insightful for evaluating the impact of future warming on plants' phenological behavior in the global ecosystem.
... Besides the extreme indices mentioned above, there are other indices applied for characterization of hydro-climatic extremes. For instance, SPI (Standardized Precipitation Index), SPEI (Standardized Precipitation Evapotranspiration Index), PDSI (Palmer Drought Severity Index) and MSDI (Multivariate Standardized Drought Index) (Hayes et al., 1999;Dai et al., 2004;Vicente-Serrano et al., 2010;Hao and Aghakouchak, 2014) are used to depict meteorological droughts (pluvials). Among these indexes, SPI is one of most widely used for investigation of meteorological droughts (pluvials) because of its simplicity and flexibility of different time scales (Farahmand and Aghakouchak, 2015). ...
Study region: Headwater regions of Hei River basin, located in the northeast of Tibetan Plateau. Study focus: Hydro-climatic extremes analysis for historical (1971-2015) and future (2024-2100) period. New hydrological insights for the region: Remarkable climate change has been observed in high mountain areas, which may result in more frequent hydro-climatic extremes. Investigating hydro-climatic extremes variations is important for mitigating hydro-climatic disasters and implementing water resource management. Warm extremes present an increasing trend in frequency and magnitude for historical and future period, while the cold extremes show a decreasing trend in the study area. Meanwhile, frequency and amount of precipitation extremes present an increasing trend for historical and future period. As a result, the intensity of meteorological and hydrological droughts show decreasing trends while floods present an increasing trend, indicating a certain drought relief in the study area. But future occurrence of extreme droughts or floods will increase. Moreover, floods for different return periods will rise with different change rate under different scenarios (SSP 1-2.6, SSP 2-4.5, SSP 3-7.0 and SSP 5-8.5). Therefore, extreme floods or droughts risks should not be underestimated and need be addressed accordingly. The findings highlight the importance of adaptive strategies to cope with more frequent hydro-climatic extremes under climate change.
... In order to quantitatively analyze the evolution law of hydrologic drought, scholars put forward various drought indexes. For example, standardized runoff index (SRI) (Shukla et al. 2008), streamflow drought index (SDI) (Nalbantis et al. 2009;Tabari et al. 2013), the Palmer drought severity index (PDSI) (Dai et al. 2004), standardized streamflow index (SSI) (Huang et al. 2017). The standardized runoff index (SRI) is based on the SPI theory proposed by McKee et al. (1993) and replaces the precipitation in SPI calculation with the runoff, which is widely used in hydrological drought research at home and abroad because of its simple structure, easy data acquisition and convenient calculation. ...
Under the background of global warming and human activities, drought occurs frequently in the Shaying River Basin (SYRB). It is particularly important for agriculture and water resources management to comprehensively evaluate the evolution of hydrological drought in the river basin. In this study, we used the nonparametric standardized runoff index (NSRI) to investigate the temporal characteristics of hydrological drought in the SYRB from 1956 to 2013. The duration and severity of hydrological drought events were identified based on run theory, and the copula functions with the highest goodness of fit were used to investigate the drought return period. In addition, the double cumulative curve method was used to analyze the main causes of hydrological drought in the SYRB. The results indicated that: (1) From 1957 to 2013, the drought showed an increasing trend in the upper, middle and lower reaches of the SYRB, with frequent alternations of droughts, and the trend characteristic of drought was different in each subzone; (2) the frequency of drought decreased from upstream to downstream, but the duration and severity of drought increased; (3) Frank-copula was considered to be the best fitting two-dimensional copula function in the SYRB and the most severe drought lasted for 25 months, with drought severity of 11.485, and drought return period of 42.14 years; (4) human activities were the main reason for the decrease of runoff in the SYRB and the dominant factor for the intensification of hydrological drought in the basin.
... Deficit rainfall for a prolonged time affects the growth and survival of trees which leads to a severe outbreak of insects in forest areas (Netherer and Schopf 2010a, b). It has been found by Dai et al. (2004) that drought-like conditions have tend to increase since the mid-1950s in the land areas of the Northern Hemisphere. Under the conditions of drought stress, more infections tend to develop. ...
Climate change has impacted the whole world in the form of global warming, greenhouse effect, polar ice cap melting and so on. The temperature of the earth has risen at an unprecedented rate at about 1°C within a century, and half of it has just risen in the late 1900s. Climate change impacts every organism on the earth in a different manner starting from smaller organisms to higher-order mammals. Maximum and immediate alterations are seen in insects that are highly sensible to even a slight change in temperature or climate. Due to global shift in climate, the insects and their invasions have started moving poleward, leading a threat to indigenous crops with no access to biological control. Therefore, entomopathogenesis, as a vocation, is gaining momentum, where microbes are being implied to combat the deleterious effects of the insect pests. The most important organisms that are used as entomopathogens include fungi, bacteria, viruses, nematodes and protozoans. In this chapter, we focus on climate change, its impact on insects and its pathogens and various well-known entomopathogens that are currently being employed to reduce the pest population.
... Wang et al., 2019), and soil behavior and physical properties (Lal & Shukla, 2004) affords its importance in agriculture and hydrology (Songara & Patel, 2022) where it can serve as an indicator of climate change-related risks (viz., droughts and floods). Hence, the accurate quantification and monitoring of the spatiotemporal variations of surface SM are essential for many climate-related studies, such as flood and drought predictions (Dai et al., 2004) and for informing efficient agricultural and land management practices (AbdelRahman et al., 2021). ...
Soil moisture (SM) is a fundamental constituent of the terrestrial environment and the hydrological cycle. Owing to its significant influence on catchment hydrological responses, it can be utilized as an indicator of floods and droughts to aid early warning systems. This study aimed to develop a field-scale method to estimate SM using parametric and machine learning-based methods to compare whether advanced artificial intelligence methods can give similar results as traditional methods. Considering this, monthly observed SM data (from the top 10 cm), environmental covariates, and remotely sensed data from March 2019 to July 2021 for the Cathedral Peak Research Catchments VI and IX in South Africa were obtained. From the 241 observations obtained across 12 sites, 160 (∼66%) were used for model training, while the remaining 81 (∼34%) were used for model testing. Employing 10-fold cross-validation, the individual machine learning models (viz., support vector machine [SVM], random forest (RF), k-nearest neighbor, classification and regression trees [Rpart], and generalized linear model) displayed a satisfactory performance (R2 = 0.52–0.79; root mean square error = 3.79–5.80). In the validation phase, the RF model displayed a superior performance, followed by the SVM. Subsequent SM estimation using the hybrid model produced satisfactory results in training (R2 = 0.90) and testing (R2 = 0.45). The results obtained from this study can aid in predicting SM variations in catchments with limited monitoring. Furthermore, this model can be applied in drought monitoring, forecasting, and informing agricultural management practices.
... The Intergovernmental Panel on Climate Change (IPCC) (e.g., IPCC, 2012) and Coumou and Rahmstorf (2012) emphasize that climate change will lead to a higher intensity and frequency of multi-year droughts in many parts of the world. Multi-year droughts are already prevalent in many parts of the globe (Dai et al., 2004;Nicholls, 2004) and their implications are more complex in comparison to a single-year drought. 1 Table 1 In this paper we estimate the causal impact of subsequent droughts on the revenues of farmers in Ethiopia factoring in their adaptive capacity. We use household panel data collected in 2004 (used as baseline), 2014 and 2015, on household revenue (per hectare) from primary food crops (wheat, barley, maize, sorghum, millet, and teff), based on national-level prices from 2001 as our dependent variable. ...
We estimate the impact of subsequent droughts on the revenues of farmers in Ethiopia factoring in their adaptive capacity. We find that after the first drought, there is no significant difference in the revenue of the farmers who experienced a drought, as compared to those who did not. However, there is a loss in revenue after the second drought, specifically for those farmers that are endowed with less assets. This finding underscores that a rise in the frequency of extreme events and shocks can potentially have significant local distributional implications, with wealth as a major distinguishing factor.
... We propose incorporating realistic vegetation 75 restrictions into existing PET methods, while not increasing much cost and uncertainty caused by additional data sources and complex formulations. Then we use independent soil moisture observations (Dai, Trenberth, & Qian, 2004) from satellite to evaluate the drought depictions by various forms of PET approaches across different temporal scales. The evaluation against observed soil moisture allows the direct diagnosis of the most sensitive surface characteristics and the most effective approach for drought quantification (Vicente-80 Serrano et al., 2012). ...
Atmospheric evaporative demand is a key metric for monitoring agricultural drought. The existing ways of estimating evaporative demand in drought indices do not faithfully represent the constraints of land surface characteristics and become less accurate over non-uniform land surfaces. This study proposes incorporating surface vegetation characteristics, such as vegetation dynamics data, aerodynamic and physiological parameters, into existing potential evapotranspiration (PET) methods. This approach is implemented over the Continental United States (CONUS) for the period of 1981–2017 and is tested in a recently developed drought index the Standardized Precipitation Evapotranspiration Index (SPEI). We show that activating realistic maximum surface and aerodynamic conductance could improve prediction of soil moisture dynamics and drought impacts by 29 % on average compared to the widely used simple methods, especially effective in the forests and humid regions. Surface characteristics that have a strong influence on the performance of the SPEI are mainly driven by leaf area index (LAI). Our approach only requires the minimum amount of ancillary data, while permitting both historical reconstruction and real-time forecast of drought. This offers a physically meaningful, yet easy-to-implement way to account for the vegetation control in drought indices.
Drought is one of the most devastating natural disasters, and its consequences affect various human and environmental aspects. In both arid and semi-arid regions, the impact of drought poses direct threats to livelihoods and socio-economic activities. For drought mitigation purposes, spatially accurate predictions of the areas to be affected are essential. By utilising an Artificial Neural Network (ANN) within a Geographic Information Systems (GIS) environment, this research aimed to project drought severity across Oman throughout the twenty-first century. Drought severity during the rainy season (DJF) was characterised using the Standardized Precipitation Evapotranspiration Index (SPEI) calculated for February at a three-month timescale. SPEI was computed based on the monthly data for a set of climatic variables (i.e. maximum and minimum air temperatures, total precipitation, wind speed, relative humidity) derived from the climate forecast system reanalysis (CFSR) dataset at a grid interval of 0.25° for the period between 1998 and 2012. The ANN model was forced with drought classes (i.e. mild, moderate, severe, extreme, and very extreme) employed as a dependent variable, while a wide spectrum of climatic (e.g., air temperature, precipitation, wind speed), topographical (e.g., elevation, aspect) and geographical (e.g., distance to coasts, vegetation cover) variables were used as independent variables. For consistency in projecting drought changes, the dependent and independent variables were re-gridded to a common grid interval (0.25 °C) using a spline interpolation algorithm. Our findings show that the ANN model provided a realistic simulation of drought occurrence incorporating the relevant climatic, topographical and geographic parameters across Oman. Regarding the projected spatial patterns of drought, the northern parts of the study area (e.g., North and South Al-Batinah governorates) are exposed to the severe and extreme intensification of drought, whilst predominately medium and low levels of droughts are expected to occur across the south and south-west areas of Oman. In a water-scarce region like Oman, the results of this study could have particular policy implications, specifically in terms of management of water resources, food production, agriculture, water supply, hydropower energy and biodiversity, amongst others. The projected changes in drought occurrence in Oman make it necessary to develop effective national initiatives to mitigate the impacts of drought and to build society's capacity for drought preparedness.
Graphical abstract
A better understanding of the relative roles of internal climate variability and external contributions, from both natural (solar, volcanic) and anthropogenic greenhouse gas forcing, is important to better project future hydrologic changes. Changes in the evaporative demand play a central role in this context, particularly in tropical areas characterized by high precipitation seasonality, such as the tropical savannah and semi-desertic biomes. Here we present a set of geochemical proxies in speleothems from a well-ventilated cave located in central-eastern Brazil which shows that the evaporative demand is no longer being met by precipitation, leading to a hydrological deficit. A marked change in the hydrologic balance in central-eastern Brazil, caused by a severe warming trend, can be identified, starting in the 1970s. Our findings show that the current aridity has no analog over the last 720 years. A detection and attribution study indicates that this trend is mostly driven by anthropogenic forcing and cannot be explained by natural factors alone. These results reinforce the premise of a severe long-term drought in the subtropics of eastern South America that will likely be further exacerbated in the future given its apparent connection to increased greenhouse gas emissions.
Soil moisture (SM) is an important component for many applications in agriculture, hydrology, meteorology, and ecology. In past decades, passive/active microwave sensors onboard Earth observation satellites are utilized to obtain SM estimates from radiometer or radar observations. In this study, the Soil Moisture and Ocean Salinity (SMOS) Level 3 daily SM retrievals at 25‐km spatial resolution between 2010 and 2021 were downscaled through an apparent thermal inertia principle‐based algorithm. The 1‐km downscaled SMOS SM retrievals were validated by in situ measurements from 635 sites of 19 SM networks in the world, which were acquired from the International Soil Moisture Network and Texas Soil Observation Network. Additionally, the validation results of the SMOS SM products were compared with those of the Soil Moisture Active Passive (SMAP) global Level 2 enhanced SM products at 1‐km downscaled and original 9‐km resolution in 2015–2021. It shows that the downscaled SMOS SM data have an overall improved accuracy and outperform the coarse‐resolution 25‐km data, with a lower unbiased Root Mean Squared Error of 0.114 m ³ /m ³ on average.
Drought monitoring is crucial for assessing and mitigating the impacts of water scarcity on various sectors and ecosystems. Although traditional drought monitoring relies on soil moisture data, remote sensing technology has have significantly augmented the capabilities for drought monitoring. This study aims to evaluate the accuracy and applicability of two temperature vegetation drought indices (TVDI), TVDI NDVI and TVDI EVI , constructed using the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) vegetation indices for drought monitoring. Using Guangdong Province as a case, enhanced versions of these indices, developed through Savitzky–Golay filtering and terrain correction were employed. Additionally, Pearson correlation analysis and F-tests were utilized to determine the suitability of the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) in correlation with TVDI NDVI and TVDI EVI . The results show that TVDI NDVI had more meteorological stations passing both significance test levels ( P < 0.001 and P < 0.05) compared to TVDI EVI , and the average Pearson’R correlation coefficient was slightly higher than that of TVDI EVI , indicating that TVDI NDVI responded better to drought in Guangdong Province. Our conclusion reveals that drought-prone regions in Guangdong Province are concentrated in the Leizhou Peninsula in southern Guangdong and the Pearl River Delta in central Guangdong. We also analyzed the phenomenon of winter-spring drought in Guangdong Province over the past 20 years. The area coverage of different drought levels was as follows: mild drought accounted for 42% to 64.6%, moderate drought accounted for 6.96% to 27.92%, and severe drought accounted for 0.002% to 1.84%. In 2003, the winter-spring drought in the entire province was the most severe, with a drought coverage rate of up to 84.2%, while in 2009, the drought area coverage was the lowest, at 49.02%. This study offers valuable insights the applicability of TVDI, and presents a viable methodology for drought monitoring in Guangdong Province, underlining its significance to agriculture, environmental conservation, and socio-economic facets in the region.
Resumo Os impactos das secas variam dependendo da sua intensidade, duração e recorrência, além do estado de desenvolvimento e da capacidade de enfrentamento das regiões e dos países. A seca pode ser dividida em três categorias principais: meteorológica, hidrológica e agrícola. A mitigação eficaz dos impactos da seca é possível por meio de um sistema de monitoramento eficiente. Como a seca é um evento multi-fatorial, a análise de múltiplos índices de diferentes classes auxilia no seu monitoramento. Este estudo visa preencher uma lacuna na pesquisa ao avaliar os três tipos de seca por meio de índices em regiões semiáridas, visando melhorar o monitoramento e a gestão dessas condições. Esse trabalhoa analisa o comportamento de sete índices de seca, SPI, SPEI, EDDI, RDIst, SRI, VHI e NDVI. Estes foram calculados para a bacia do alto jaguaribe por meio de uma janela móvel de tempo e por meio de uma discretização temporal, tanto para a escala de 3 como de 12 meses. Foram utilizadas como métricas de análise o valor de informação mútua e correlação de Pearson entre os índices. Os resultados dos índices metereológicos SPI, SPEI e RDIst apresentaram elevada correlação tanto na análise linear como não-linear. EDDI apresentou um comportamento diferente dos outros índices metereológicos. Contudo, O EDDI-12 mostrou maior informação mútua do que o NDVI, sugerindo um alarme precoce para a seca da vegetação em escalas mais amplas. Este estudo analisa a propagação de seca através da correlação entre índices de escala 3 meses e o SPI-3 para fevereiro-março-abril. Os resultados mostram a propagação de seca, com maiores correlações dos índices de vegetação (VHI e NDVI) e hidrológico (SRI) em março-abril-maio, e os índices meteorológicos (RDIst e SPEI) com as maiores correlações em fevereiro-março-abril.
The historical rise of irrigation has profoundly mitigated the effect of drought on agriculture in many parts of the United States. While irrigation directly alters soil moisture, meteorological drought indices ignore the effects of irrigation, since they are often based on simple water balance models that neglect the irrigation input. Reanalyses also largely neglect irrigation. Other approaches estimate the evaporative fraction (EF), which is correlated with soil moisture under water-limited conditions typical of droughts, with lower values corresponding to drier soils. However, those approaches require satellite observations of land surface temperature, meaning they cannot be used to study droughts prior to the satellite era. Here, we use a recent theory of land–atmosphere coupling—surface flux equilibrium (SFE) theory—to estimate EF from readily available observations of near-surface air temperature and specific humidity with long historical records. In contrast to EF estimated from a reanalysis that largely neglects irrigation, the SFE-predicted EF is greater at irrigated sites than at nonirrigated sites during droughts, and its historical trends are typically consistent with the spatial distribution of irrigation growth. Two sites at which SFE-predicted EF unexpectedly rises in the absence of changes in irrigation can be explained by increased flooding due to human interventions unrelated to irrigation (river engineering and the expansion of fish hatcheries). This work introduces a new method for quantifying agricultural drought prior to the satellite era. It can be used to provide insight into the role of irrigation in mitigating drought in the United States over the twentieth century.
Significance Statement
Irrigation grew profoundly in the United States over the twentieth century, increasing the resilience of American agriculture to drought. Yet observational records of agricultural drought, and its response to irrigation, are limited to the satellite era. Here, we show that a common measure of agricultural drought (the evaporative fraction, EF) can be estimated using widespread weather data, extending the agricultural drought record decades further back in time. We show that EF estimated using our approach is both sensitive and specific to the occurrence of irrigation, unlike an alternative derived from a reanalysis.
As global temperatures rise, droughts are becoming more frequent and severe. To predict how drought might affect plant communities, ecologists have traditionally designed experiments with controlled watering regimes and rainout shelters. Both treatments have proven effective for simulating soil drought. However, neither are designed to directly modify atmospheric drought.
Here, we detail the efficacy of a silica gel atmospheric drought treatment in outdoor mesocosms with and without a cooccurring soil drought treatment. At California State University, Los Angeles, we monitored relative humidity (RH), temperature, and vapor pressure deficit (VPD) every 10 minutes for five months in a bare-ground experiment featuring mesocosms treated with soil drought (reduced watering) and/or atmospheric drought (silica packets suspended 12 cm above soil).
We found that silica packets dehumidified these microclimates most effectively (-5% RH) when combined with reduced soil water, regardless of the ambient humidity levels of the surrounding air. Further, packets increased microclimate VPD most effectively (+0.4 kPa) when combined with reduced soil water and ambient air temperatures above 20°C. Finally, packets simulated atmospheric drought most consistently when replaced within three days of deployment.
Our results demonstrate the use of silica packets as effective dehumidification agents in outdoor drought experiments. We emphasize that incorporating atmospheric drought in existing soil drought experiments can improve our understandings of the ecological impacts of drought.
Crop water stress and drought status can be indicat-ed through soil moisture (SM). SM-related factors, such as water availability, vegetation state, and temperature, can be inferred by Normalized Difference Latent Heat Index (NDLI), Normalized Difference Vegetation Index (NDVI), and Land Surface Temper-ature (LST), respectively. This study presents a new Surface Wa-ter Availability and Temperature (SWAT) index that utilizes remotely-sensed data to monitor crop water stress and drought status. The Euclidean distance method was used to analyze the three-dimensional (3D) scatterplots of NDLI, NDVI, and LST to define the SWAT. Subsequently, the SWAT and two drought indices, including the Temperature-Vegetation Dryness Index (TVDI) and Temperature-Soil Moisture Dryness Index (TMDI), were used to determine the spatial signatures of droughts in Tai-wan from 2013 to 2020. These drought signatures were evaluated and compared against corresponding assessments from various indicators, including the in-situ SM, TVDI, TMDI, Crop Water Stress Index (CWSI), and Net Primary Productivity (NPP). The results show that the TVDI and TMDI were negatively correlated with the in-situ SM, with the highest correlation coefficient (r) of −0.53 and −0.67, respectively. The SWAT was found to be even more correlated to the SM (–0.79 ≤ r ≤ –0.49, p < 0.01) and exhib-ited more sensitive and stable than other single indices (NDVI, NDLI, and LST) and integrated indices (TVDI and TMDI). Ac-cording to the spatial observation, the SWAT index was closely related to CWSI (r = 0.77, p < 0.01). Moreover, the SWAT was in line with NPP (r = −0.79, p < 0.01) and more sensitive to drought than the TVDI and TMDI. Furthermore, the SWAT was highly correlated with the TVDI, TMDI, CWSI, and NPP in most agri-cultural regions in Taiwan. Overall, the SWAT is proven to be a satellite index effectively describing agricultural drought stress.
Erosion is a concern due to environmental degradation, loss of valuable cropland, increased sediment loads in aquatic systems, and reduced reservoir capacity. To manage erosion, riparian forest buffers and bendway weirs were installed in the Little Blue River, Kansas, during years 2002–2010. To illustrate land cover changes associated with management for upland and streambank erosion, indicated through terrestrial land gains, particularly of permanent tree cover relative to short‐lived crop cover, we digitized 1 m orthoimagery. For the pretreatment interval of 1991–2002, we digitized streambank edges to approximate change in river area. Due to river dynamics, for the 2002 and 2014 interval before and after treatment, we used land ownership parcels as fixed locations to assess changes in land area and land classes for 24 treated and 24 untreated parcels, each parcel group totaling 1575 ha. We appraised two extents of the unified streambank for both years and all land in parcels rather than isolating the river from the surrounding watershed. During 1991 to 2002, treated land parcels lost terrestrial land, whereas untreated land parcels gained land. During 2002–2014, treated land had greater river and crop cover, and less tree cover than untreated land. For the entire extent, with similar trends for the unified streambank extent, by 2014, treated parcels gained 27.3 ha of terrestrial land compared to 4.6 ha gained by untreated parcels. Gains occurred in tree cover and losses in river water and sediments cover. In treated parcels crop cover decreased, whereas in untreated parcels crop cover increased. Streamflows decreased over time, likely contributing to streambank stability. Despite lack of documented cost‐share agreements, in untreated parcels, landowners managed land by increasing tree cover to protect soil from erosion. All measurements were consistent with erosion followed by management for erosion through terrestrial land gains of tree cover.
Changes in the global water cycle can cause major environmental and socioeconomic impacts. As the average global temperature increases, it is generally expected that the air will become drier and that evaporation from terrestrial water bodies will increase. Paradoxically, terrestrial observations over the past 50 years show the reverse. Here, we show that the decrease in evaporation is consistent with what one would expect from the observed large and widespread decreases in sunlight resulting from increasing cloud coverage and aerosol concentration.
The Common Land Model (CLM) was developed for community use by a
grassroots collaboration of scientists who have an interest in making a
general land model available for public use and further development. The
major model characteristics include enough unevenly spaced layers to
adequately represent soil temperature and soil moisture, and a
multilayer parameterization of snow processes; an explicit treatment of
the mass of liquid water and ice water and their phase change within the
snow and soil system; a runoff parameterization following the TOPMODEL
concept; a canopy photosynthesis-conductance model that describes the
simultaneous transfer of CO2 and water vapor into and out of
vegetation; and a tiled treatment of the subgrid fraction of energy and
water balance. CLM has been extensively evaluated in offline mode and
coupling runs with the NCAR Community Climate Model (CCM3). The results
of two offline runs, presented as examples, are compared with
observations and with the simulation of three other land models [the
Biosphere-Atmosphere Transfer Scheme (BATS), Bonan's Land Surface Model
(LSM), and the 1994 version of the Chinese Academy of Sciences Institute
of Atmospheric Physics LSM (IAP94)].
Twentieth century trends of precipitation are examined by a variety of methods to more fully describe how precipitation has changed or varied. Since 1910, precipitation has increased by about 10% across the contiguous United States. The increase in precipitation is reflected primarily in the heavy and extreme daily precipitation events. For example, over half (53%) of the total increase of precipitation is due to positive trends in the upper 10 percentiles of the precipitation distribution. These trends are highly significant, both practically and statistically. The increase has arisen for two reasons. First, an increase in the frequency of days with precipitation ]6 days (100 yr)1[ has occurred for all categories of precipitation amount. Second, for the extremely heavy precipitation events, an increase in the intensity of the events is also significantly contributing (about half) to the precipitation increase. As a result, there is a significant trend in much of the United States of the highest daily year-month precipitation amount, but with no systematic national trend of the median precipitation amount.These data suggest that the precipitation regimes in the United States are changing disproportionately across the precipitation distribution. The proportion of total precipitation derived from extreme and heavy events is increasing relative to more moderate events. These changes have an impact on the area of the United States affected by a much above-normal (upper 10 percentile) proportion of precipitation derived from very heavy precipitation events, for example, daily precipitation events exceeding 50.8 mm (2 in.).
Instrumental Palmer Drought Severity Indexes (PDSI) averaged over the western United States and Great Plains document three major decadal moisture regimes during the twentieth century: the early twentieth-century pluvial, the Dust Bowl drought, and the 1950s drought. Tree-ring reconstructed PDSI for the contiguous Unites States replicates these three twentieth-century moisture regimes, and have been used to search for possible analogs over the past 500 yr. The early twentieth-century wet regime from 1905 to 1917 appears to have been the wettest episode across the West since A.D. 1500, but similar pluvials occurred in the nineteenth, seventeenth, and sixteenth centuries. The Dust Bowl drought (1929-40) was most severe over the northern Plains to the northern Rockies. No close analogs are found for the full severity and geographical focus of the Dust Bowl drought over the past 500 yr. The 1950s drought (1946-56) was concentrated over the Southwest and was replicated by some 12 droughts of similar spatial coverage and duration over the past 500 yr. One of these analogs, the sixteenth-century mega-drought, was also focused over the Southwest and appears to have surpassed the Dust Bowl drought in coverage, duration, and severity.
This study is an extensive revision of the Climatic Research Unit (CRU) land station temperature database that is used to produce a gridbox dataset of 5° latitude × 5° longitude temperature anomalies. The new database comprises 5159 station records, of which 4167 have enough data for the 1961-90 period to calculate or estimate the necessary averages. Apart from the increase in station numbers compared to the earlier study in 1994, many station records have had their data replaced by newly homogenized series that have been produced by several recent studies. New versions of all the gridded datasets currently available on the CRU Web site (www.cru.uea.ac.uk) have been developed. This includes combinations with marine (sea surface temperature anomalies) data over the oceans and versions with adjustment of the variance of individual gridbox series to remove the effects of changing station numbers through time.Hemispheric and global temperature averages for land areas developed with the new dataset differ slightly from those developed in 1994. Possible reasons for the differences between the new and the earlier analysis and those from the National Climatic Data Center and the Goddard Institute for Space Studies are discussed. Differences are greatest over the Southern Hemisphere and at the beginnings and ends of each time series and relate to gridbox sizes and data availability. The rate of annual warming for global land areas over the 1901-2000 period is estimated by least squares to be 0.07°C decade1 (significant at better than the 99.9% level). Warming is not continuous but occurs principally over two periods (about 1920-45 and since 1975). Annual temperature series for the seven continents and the Arctic all show significant warming over the twentieth century, with significant (95%) warming for 1920-44 for North America, the Arctic, Africa, and South America, and all continents except Australia and the Antarctic since 1977. Cooling is significant during the intervening period (1945-76) for North America, the Arctic, and Africa.
The Palmer Drought Severity Index (PDSI) was calculated globally using gridded monthly air temperature and precipitation. From 1900 to 1995, there are large multi- year to decadal variations in the percentage areas in severe drought (PDSI< 3:0) and severe moisture surplus (PDSI > +3:0) over many land areas while secular trends are small. Since the late 1970s, however, there have been some in- creases in the combined percentage areas in severe drought and severe moisture surplus, resulting from increases in ei- ther the drought area (e.g., over the Sahel, eastern Asia and southern Africa) or both the drought and wet areas (e.g., over the U.S. and Europe). Although the high per- centages of the dry and wet areas in the recent decades are not unprecedented during this century (except the Sahel), the recent changes are closely relate to the shift in El Ni~ no - Southern Oscillation (ENSO) towards more warm events since the late 1970s and coincide with record high global mean temperatures. Moreover, for any given value of ENSO indices, the PDSI anomalies tend to be larger than would be expected from previous records. These changes are qualita- tively consistent with those expected from increased green- house gases in the atmosphere.
The development of a 2° lat × 3° long grid of summer
drought reconstructions for the continental United States estimated from
a dense network of annual tree-ring chronologies is described. The
drought metric used is the Palmer Drought Severity Index (PDSI). The
number of grid points is 154 and the reconstructions cover the common
period 1700-1978. In producing this grid, an automated gridpoint
regression method called `point-by-point regression' was developed and
tested. In so doing, a near-optimal global solution was found for its
implementation. The reconstructions have been thoroughly tested for
validity using PDSI data not used in regression modeling. In general,
most of the gridpoint estimates of drought pass the verification tests
used. In addition, the spatial features of drought in the United States
have been faithfully recorded in the reconstructions even though the
method of reconstruction is not explicitly spatial in its design.The
drought reconstructions show that the 1930s `Dust Bowl' drought was the
most severe such event to strike the United States since 1700. Other
more local droughts are also revealed in the regional patterns of
drought obtained by rotated principal component analysis. These
reconstructions are located on a NOAA Web site at the World Data
Center-A in Boulder, Colorado, and can be freely downloaded from there.
An update is given of the global correlation and regression patterns of sea level pressure associated with the Southern Oscillation, based upon the reanalyses from the National Centers for Environmental Prediction-National Center for Atmospheric Research for 1958-98, a period independent of that of early work. Features over the oceans are better defined than was previously possible and most features prove to be robust, although climate changes such as the 1976 climate shift have evidently altered some important relationships, such as those with Southeast Asia. Associated surface temperature patterns are also shown over the same interval and reveal striking symmetry about the equator. For El Nino, the patterns emphasize the associated broad warming over the tropical central and eastern Pacific, as well as along the west coast of the Americas extending into high latitudes of the Pacific in both hemispheres, and cooling in the central North and South Pacific. Precipitation patterns associated with the Southern Oscillation are given based upon the post-1979 period to include satellite data over the oceans, which emphasizes that the main changes are for a global redistribution of precipitation, so that solely land-based perspectives are biased. While annual mean patterns reveal much of the geographic structure associated with the Southern Oscillation, important seasonal variations are present, especially for sea level pressure and pre- cipitation.
Regular measurements of solar radiation carried out in the network of
actinometric stations of the former Soviet Union (FSU) have shown a
decreasing tendency in the time series of direct and global solar
radiation during last decades. A statistically significant decrease has
been found in 60% of the time series of global radiation annual totals
obtained from 160 actinometric stations. Three large areas, where this
decrease exceeded 2% per 10 years, were found (in the European part of
the FSU, in West Siberia, and in the Far East). As the main reason for
changes in solar radiation, increased cloudiness and atmospheric
turbidity are considered. A more detailed analysis of long-term changes
in radiation budget components obtained from two stations situated in
rather different conditions (Moscow Meteorological Observatory in a
large town and Tõravere Actinometric Station in a rural area)
allows us to point out the influence of a large town as a source of air
pollution on the radiation transfer in the atmosphere, as well as on
cloudiness and air temperature.
Composite temperature and precipitation anomalies during various stages
of an event in the Southern Oscillation (SO) have been computed for
several hundred stations across the globe. Large regions of coherent,
significant signals are shown to exist for both extremes of the SO, with
warm event signals generally opposite to those during cold events. In
addition, during the year preceding the development of an event in the
SO (year 1), climatic anomalies tend to be opposite to those during the
following year (year 0). This confirms that the biennial tendency of the
SO over the Pacific/Indian ocean sectors is also present in more remote
regions with climatic signals related to the SO. Many of the signals are
consistent enough from event to event to be useful for extended range
forecasting purposes.
The Palmer Drought Severity Index (PDSI) is routinely made available by
NOAA for operational use, and it has also been calculated across the
United States on a historical basis back to 1895 (Karl et al., 1983).
Traditionally, the coefficients used in the calculation of the PDSI have
been based on an anomalously hot and dry period across much of the
United States (1931-60). By changing the base period used to calibrate
the coefficients, the magnitude and the sign of the PDSI change
significantly in many areas of the United States. Often the changes are
larger than those that occur when the potential evapotranspiration is
forced to a constant equal to the long-term monthly mean potential
evapotranspiration. This sensitivity to base period calibration has
important implications in the interpretation of operational or hindcast
values of the PDSI for forest fire danger and other applications. The
less frequently used Palmer moisture anomaly index (Z-index) is much
less sensitive to changes in the calibration periods, and also has some
desirable characteristics which may make it preferable to the PDSI for
some agricultural and forest fire applications, i.e., it is more
responsive to short-term moisture anomalies.
Observed decreases in pan evaporation over most of the United Stares and the former USSR during the post-WWII period, if interpreted as a decrease in actual evaporation, are at odds with increases in temperature and precipitation over many regions of these two countries. Using parallel observations of actual and Dan evaporation at six Russian, one Latvian, and one U.S, experimental sites, we recalibrate trends in pan evaporation to make them more representative of actual evaporation changes. After applying this transformation, pan evaporation time series over southern Russia and most of the United States reveal an increasing trend in actual evaporation during the past forty years.
A synthesis of available data for the Mississippi River basin (area 3x10(6) km(2)) reveals an upward trend in evaporation during recent decades, driven primarily by increases in precipitation and secondarily by human water use. A cloud-related decrease in surface net radiation appears to have accompanied the precipitation trend. Resultant evaporative and radiative cooling of the land and lower atmosphere quantitatively explains downward trends in observed pan evaporation. These cooling tendencies also reconcile the observed regional atmospheric cooling with the anticipated regional "greenhouse warming." If recent high levels of precipitation (which correlate with the North Atlantic Oscillation) are mainly caused by an internal climatic fluctuation, an eventual return to normal precipitation could reveal heretofore-unrealized warming in the basin. If, instead, they are caused by some unidentified forcing that will continue to grow in the future, then continued intensification of water cycling and suppression of warming in the basin could result.
Pan evaporation, an indicator of potential evaporation, has decreased during the last several decades in many parts of the world. This trend is contrary to the expectation that global warming will be accompanied by an increase in terrestrial evaporation, known as the pan evaporation paradox. In this paper we present an analysis of changes in the spatial patterns of pan evaporation in China based on data from 85 weather stations from 1955 to 2000. We found that pan evaporation decreased in China from 1955 to 2000. The decrease was statistically significant in all of China's eight climatic regions except northeast China. We also found that the decrease in solar irradiance was most likely the driving force for the reduced pan evaporation in China. However, unlike in other areas of the world, in China the decrease in solar irradiance was not always accompanied by an increase in cloud cover and precipitation. Therefore we speculate that aerosols may play a critical role in the decrease of solar irradiance in China. By subdividing China into eight climatic regions, we found that the rate of decrease in pan evaporation was highest in the northwest and lowest in the southwest. Although changes in solar irradiance are the main cause of decreasing pan evaporation, water conditions influence the sensitivity of pan evaporation to the change in solar irradiance in comparing the eight climatic regions. Thus the spatial trends of pan evaporation differ from those of solar irradiance among these regions.
Observed decreases in pan evaporation over most of the United States and the former USSR during the post-WWII period, if interpreted as a decrease in actual evaporation, are at odds with increases in temperature and precipitation over many regions of these two countries. Using parallel observations of actual and pan evaporation at six Russian, one Latvian, and one U.S. experimental sites, we recalibrate trends in pan evaporation to make them more representative of actual evaporation changes. After applying this transformation, pan evaporation time series over southern Russia and most of the United States reveal an increasing trend in actual evaporation during the past forty years.
Over the contiguous United States, precipitation, temperature, streamflow, and heavy and very heavy precipitation have increased during the twentieth century. In the east, high streamflow has increased as well. Soil wetness (as described by the Keetch-Byram Drought index) has increased over the northern and eastern regions of the United States, but in the southwestern quadrant of the country soil dryness has increased, making the region more susceptible to forest fires. In addition to these changes during the past 50 yr, increases in evaporation, near-surface humidity, total cloud cover, and low stratiform and cumulonimbus clouds have been observed. Snow cover has diminished earlier in the year in the west, and a decrease in near-surface wind speed has also occurred in many areas. Much of the increase in heavy and very heavy precipitation has occurred during the past three decades.
Ten years of soil moisture measurements (biweekly from March through September and monthly during winter) within the top 1 m of soil at 17 grass-covered sites across Illinois are analyzed to provide a climatology of soil moisture for this important Midwest agricultural region. Soil moisture measurements were obtained with neutron probes that were calibrated for each site. Measurement errors are dependent upon the volumetric water content with errors less than 20 percent when soil moisture is above 0 percent of soil volume. Single point errors in moisture measurements from the top 1 m of soil range from 6 percent to 13 percent when volumetric soil moisture is 30 percent of soil volume. The average depletion in moisture between winter and summer over the 10-year period for the top 2 m of soil in Illinois was 72.3 mm. Three-quarters of this decrease occurred above 0.5 m and only 5 percent occurred between the 1.0-m and 2.0-m depths. The average moisture decrease between winter and summer during a wet year (1985) and a drought year (1988) in the top 2 m of soil was 64 percent and 204 percent of the average for the 10-year period, respectively. Seasonal means in soil moisture averaged for the state show the effects of different seasons and soil types on soil moisture. In the winter and spring a latitudinal gradient exists with the wetter soils in the southern part of the state. During summer and autumn there is a longitudinal gradient with the wetter soils in the eastern half of the state. The longitudinal gradient is closely associated with the depth of loess deposits.
The El Niño-Southern Oscillation (ENSO) system orchestrates a well-documented suite of climate anomalies worldwide. The details of ENSO's extratropical influence vary among events, but this variability has not been described or diagnosed beyond the past few decades, and previous descriptions have looked at inter-event differences rather than decadal patterns. We use a new tree-ring based drought reconstruction for the continental U.S. and instrumental ENSO indices to document systematic decadal changes in the U.S. drought-ENSO relationship since the late 19th century. Significant ENSO-drought correlation occurs consistently in the southwest U.S., but the strength of penetration of moisture anomalies into the continent varies substantially. The most striking change over the past 130 years is the initiation of a “bipolar” ENSO-drought signature around 1920, producing opposite-sign moisture anomalies in the southwest and mid-Atlantic states. Shifts in teleconnection patterns coincide with variations in the strength of ENSO and in a North Pacific mode.
The spatial structure of asymmetries in sea surface temperature (SST) and surface air temperature (SAT) between average El Niño and La Niña events is considered. It is demonstrated that in historical SST and SAT reconstructions, the anomaly spatial pattern that changes sign between El Niño and La Niña events (the ``linear'' signal) strongly resembles that of principal component analysis (PCA) mode 1, while that which does not change sign (the ``nonlinear'' signal) resembles the pattern of PCA mode 2. The linear and nonlinear patterns also strongly resemble the standard deviation and skewness fields, respectively. Furthermore, temporal subsampling of long (130 yr) SST reconstructions suggests that the magnitude of the nonlinear signal and its similarity to PCA mode 2 are functions of the strength of ENSO, as measured by the standard deviation of the PCA mode-1 time series. Finally, it is found that of several coupled general circulation models (GCMs) considered, the spatial and temporal structure of the El Niño La Niña asymmetry is captured only by the GFDL R30 model, despite large biases in its covariance structure.
Worsening drought, water restrictions, and wildfires have been widely featured in news reports across North America during recent years. Area burned by wildfire was at unprecedented levels in the United States in the summer of 2002, and devastating wildfires in California were in the news just a few months ago. Drought is not only gripping parts of North America, but also parts of Northern Africa and other regions worldwide, serving as a reminder of society's vulnerability to drought and its enormous economic impact.
But what is the full range of past drought variability, as revealed by paleoclimate data? What role might droughts associated with abrupt climate change play? Are droughts likely to become more frequent, longer, or more extensive as we move into the future with global warming?
ABSTRACT This paper describes the initial work,toward the production of monthly,global (land and ocean) analyses of precipitation for an extended period from 1948 to the present. Called the precipitation reconstruction (PREC), the global analyses are defined by interpolation of gauge observations over land (PREC/L) and by EOF recon- struction of historical observations over ocean (PREC/O). This paper documents,the creation of the land com- ponent of the analyses (PREC/L) on a 2.58 latitude/longitude grid for 1948‐2000. These analyses are derived from gauge,observations from over 17 000 stations collected in the Global Historical Climatology Network (GHCN), version 2, and the Climate Anomaly Monitoring System (CAMS) datasets. To determine the most suitable objective analysis procedure for gridding, the analyses generated by four published objective analysis techniques [those of Cressman, Barnes, and Shepard, and the optimal interpolation (OI) method of Gandin] were compared. The evaluation demonstrated,two crucial points: 1) better results are obtained when,interpolating anomalies rather than the precipitation totals, and 2) the OI analysis procedure provided the most accurate and stable analyses among the four algorithms that were tested. Based on these results, the OI technique was used to create monthly,gridded analyses of precipitation over the global land areas for the 53-yr period from 1948 to 2000. In addition, some diagnostic investigations of the seasonal and interannual variability of large-scale precipitation over the global land areas are presented. The mean,distribution and annual cycle of precipitation observed in the PREC/L showed good agreement with those in several published gauge-based datasets, and the anomaly,patterns associated with ENSO resemble,those found in previous studies. The gauge-based dataset (PREC/L) will be updated on a quasi-real-time basis and is available online (ftp.ncep.noaa.gov/pub/precip/50- yr).
We investigate the “typical” global and large-scale regional precipitation patterns that are associated with the El Nino/Southern Oscillation (ENSO). Monthly precipitation time series from over 1700 stations are analyzed using an empirical method designed to identify regions of the globe that have precipitation variations associated with ENSO. Monthly mean ranked precipitation composites are computed over idealized 2-year ENSO episodes for all stations that include data for at least five ENSOs. The amplitude and phase of the Arm harmonic fitted to the 24-month composite values are plotted in the form of a vector for each station. When plotted on a global map, these vectors reveal both the regions of spatially coherent ENSO-related precipitation and the phase of this signal in relation to the evolution of the composite episode. Time cries of precipitation for the coherent regions identified in the harmonic vector map are examined to determine the magnitudes of the ENSO-related precipitation and th...
Two theoretical approaches to evaporation from saturated surfaces are outlined, the first being on an aerodynamic basis in which evaporation is regarded as due to turbulent transport of vapour by a process of eddy diffusion, and the second being on an energy basis in which evaporation is regarded as one of the ways of degrading incoming radiation. Neither approach is new, but a combination is suggested that eliminates the parameter measured with most difficulty-surface temperature-and provides for the first time an opportunity to make theoretical estimates of evaporation rates from standard meteorological data, estimates that can be retrospective. Experimental work to test these theories shows that the aerodynamic approach is not adequate and an empirical expression, previously obtained in America, is a better description of evaporation from open water. The energy balance is found to be quite successful. Evaporation rates from wet bare soil and from turf with an adequate supply of water are obtained as fractions of that from open water, the fraction for turf showing a seasonal change attributed to the annual cycle of length of daylight. Finally, the experimental results are applied to data published elsewhere and it is shown that a satisfactory account can be given of open water evaporation at four widely spaced sites in America and Europe, the results for bare soil receive a reasonable check in India, and application of the results for turf shows good agreement with estimates of evaporation from catchment areas in the British Isles.
Although there have been many analyses of El Niño/Southern Oscillation (ENSO) induced precipitation anomalies, global patterns from these analyses remain incomplete. Here we combine recent satellite estimates of oceanic precipitation and historical rain-gauge records to derive a global climatology of ENSO-induced precipitation anomalies using empirical orthogonal function (EOF) analyses. The patterns suggest that the re-arrangement of convection centers of the Walker circulation during ENSO events induces large precipitation anomalies in the tropics, while associated changes in the monsoon systems (through the Hadley cell) over the Pacific, Indian and Atlantic Oceans, and their interactions with midlatitude westerlies generate coherent anomaly patterns over the extratropics. Our results can be used to evaluate climate models and forecast ENSO-induced precipitation anomalies.
The authors have analyzed global station data and created a gridded dataset of monthly precipitation for the period of 1900-88. Statistical analyses suggest that discontinuities associated with instrumental errors are large for many high-latitude station records, although they are unlikely to be significant for the majority of the stations. The first leading EOF in global precipitation fields is an ENSO-related pattern, concentrating mostly in the low latitudes. The second leading EOF depicts a linear increasing trend (;2.4 mm decade21) in global precipitation fields during the period of 1900-88. Consistent with the zonal precipitation trends identified in previous analyses, the EOF trend is seen as a long-term increase mostly in North America, mid- to high-latitude Eurasia, Argentina, and Australia. The spatial patterns of the trend EOF and the rate of increase are generally consistent with those of the precipitation changes in increasing CO 2 GCM experiments. The North Atlantic oscillation (NAO) accounts for ;10% of December-February precipitation variance over North Atlantic surrounding regions. The mode suggests that during high-NAO-index winters, precipitation is above normal in northern (.508N) Europe, the eastern United States, northern Africa, and the Mediterranean, while below-normal precipitation occurs in southern Europe, eastern Canada, and western Greenland. Wet and dry months of one standard deviation occur at probabilities close to those of a normal distribution in midlatitudes. In the subtropics, the mean interval between two extreme events is longer. The monthly wet and dry events seldom (probability , 5%) last longer than 2 months. ENSO is the single largest cause of global extreme precipitation events. Consistent with the upward trend in global precipitation, globally, the averaged mean interval between two dry months increased by ;28% from 1900-44 to 1945-88. The percentage of wet areas over the United States has more than doubled (from ;12% to .24%) since the 1970s, while the percentage of dry areas has decreased by a similar amount since the 1940s. Severe droughts and floods comparable to the 1988 drought and 1993 flood in the Midwest have occurred 2-9 times in each of several other regions of the world during this century.
Worldwide, economic damages attributed to natural disasters tripled from the 1960s (US$40 billion) to the 1980s (US$120 billion) (Domeisen 1995). The 1990s have witnessed a continued escalation of economic damages, reaching US$400 billion through 1996 (Carol-wicz 1996). Between 1992 and 1996, losses associated with natural disasters in the United States averaged US$54.2 billion per week (Carolwicz 1996). The economic, social, and environmental costs and losses associated with drought are also increasing dramatically, although it is difficult to quantify this trend precisely because of the lack of reliable historical estimates of losses. White and Haas estimated in 1975 that the average annual crop losses associated with drought in the Great Plains region of the United States were about US$700 million. In 1995, the US Federal Emergency Management Agency (FEMA) estimated annual losses attributable to drought at US$6-8 billion (FEMA 1995).
The tendency for more frequent El Niño events and fewer La Niña events since the late 1970's has been linked to decadal changes in climate throughout the Pacific basin. Aspects of the most recent warming in the tropical Pacific from 1990 to 1995, which are connected to but not synonymous with El Niño, are unprecedented in the climate record of the past 113 years. There is a distinction between El Niño (EN), the Southern Oscillation (SO) in the atmosphere, and ENSO, where the two are strongly linked, that emerges clearly on decadal time scales. In the traditional El Niño region, sea surface temperature anomalies (SSTAs) have waxed and waned, while SSTAs in the central equatorial Pacific, which are better linked to the SO, remained positive from 1990 to June 1995. We carry out several statistical tests to assess the likelihood that the recent behavior of the SO is part of a natural decadal-timescale variation. One test fits an autoregressive-moving average (ARMA) model to a measure of the SO given by the first hundred years of the pressures at Darwin, Australia, beginning in 1882. Both the recent trend for more ENSO events since 1976 and the prolonged 1990-1995 ENSO event are unexpected given the previous record, with a probability of occurrence about once in 2,000 years. This opens up the possibility that the ENSO changes may be partly caused by the observed increases in greenhouse gases.
A standardized global data set of soil horizon thicknesses and textures (particle size distributions) has been compiled from the Food and Agriculture Organization of the United Nations/United Nations Educational, Scientific, and Cultural Organization (FAO/UNESCO) Soil Map of the World, Vols. 2–10 [1971–1981]. This data set was developed for use by the improved land-surface hydrology parameterization designed by Abramopoulos et al. [1988] for the Goddard Institute for Space Studies General Circulation Model II (GISS GCM). The data set specifies the top and bottom depths and the percent abundance of sand, silt, and clay of individual soil horizons in each of the 106 soil types cataloged for nine continental divisions. When combined with the World Soil Data File [Zobler, 1986], the result is a l°×l° global data set of variations in physical properties throughout the soil profile. These properties are important in the determination of water storage in individual soil horizons and exchange of water with the lower atmosphere within global climate models. We have used these data sets, in conjunction with the Matthews [1983] global vegetation data set and texture-based estimates of available soil moisture, to calculate the global distributions of soil profile thickness, potential storage of water in the soil profile, potential storage of water in the root zone, and potential storage of water derived from soil texture. Comparisons with the water-holding capacities used in the GISS Model II show that our derived values for potential storage of water are consistently larger than those previously used in the GISS GCM. Preliminary analyses suggest that incorporation of this data set into the GISS GCM has improved the model's performance by including more realistic variability in land surface properties.
Annual and monthly mean values of continental freshwater discharge into the oceans are estimated at 18 resolution using several methods. The most accurate estimate is based on streamflow data from the world's largest 921 rivers, supplemented with estimates of discharge from unmonitored areas based on the ratios of runoff and drainage area between the unmonitored and monitored regions. Simulations using a river transport model (RTM) forced by a runoff field were used to derive the river mouth outflow from the farthest downstream gauge records. Separate estimates are also made using RTM simulations forced by three different runoff fields: 1) based on observed streamflow and a water balance model, and from estimates of precipitation P minus evaporation E computed as residuals from the atmospheric moisture budget using atmospheric reanalyses from 2) the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) and 3) the European Centre for Medium-Range Weather Forecasts (ECMWF). Compared with previous estimates, improvements are made in extending observed discharge downstream to the river mouth, in accounting for the unmonitored streamflow, in discharging runoff at correct locations, and in providing an annual cycle of continental discharge. The use of river mouth outflow increases the global continental discharge by ;19% compared with unadjusted streamflow from the farthest downstream stations. The river-based estimate of global continental discharge presented here is 37 288 6 662 km3 yr21, which is ;7.6% of global P or 35% of terrestrial P. While this number is comparable to earlier estimates, its partitioning into individual oceans and its latitudinal distribution differ from earlier studies. The peak discharges into the Arctic, the Pacific, and global oceans occur in June, versus May for the Atlantic and August for the Indian Oceans. Snow accumulation and melt are shown to have large effects on the annual cycle of discharge into all ocean basins except for the Indian Ocean and the Med- iterranean and Black Seas. The discharge and its latitudinal distribution implied by the observation-based runoff and the ECMWF reanalysis-based P-E agree well with the river-based estimates, whereas the discharge implied by the NCEP-NCAR reanalysis-based P-E has a negative bias.
ABSTRACT The Climate System Model, a coupled global climate model without ‘‘flux adjustments’’ recently developed at the National Center for Atmospheric Research, was used to simulate the twentieth-century climate using historical greenhouse,gas and sulfate aerosol forcing. This simulation was,extended,through the twenty-first century under two newly developed scenarios, a business-as-usual case (ACACIA-BAU, CO2 710 ppmv in 2100) and a CO2 stabilization case (STA550, CO 2 540 ppmv in 2100). Here we compare the simulated and observed twentieth-century climate, and then describe the simulated climates for the twenty-first century. The model,simulates the spatial and temporal,variations of the twentieth-century climate reasonably well. These include the rapid rise in global and zonal mean surface temperatures since the late 1970s, the precipitation increases over northern mid- and high-latitude land areas, ENSO-induced precipitation anomalies, and Pole‐ midlatitude oscillations (such as the North Atlantic oscillation) in sea level pressure fields. The model,has a cold bias (28‐68C) in surface air temperature over land, overestimates of cloudiness (by 10%‐30%) over land, and underestimates,of marine stratus clouds to the west of North and South America and Africa. The projected global surface warming,from the 1990s to the 2090s is ;1.98C under the BAU scenario and ;1.58C under the STA550 scenario. In both cases, the midstratosphere cools due to the increase in CO 2, whereas the lower stratosphere warms in response to recovery of the ozone layer. As in other coupled models, the surface warming,is largest at winter high latitudes ($5.08C from the 1990s to the 2090s) and smallest (;1.08C) over the southern oceans, and is larger over land areas than ocean areas. Globally averaged precipitation increases by ;3.5% (3.0%) from the 1990s to the 2090s in the BAU (STA550) case. In the BAU case, large precipitation increases (up to 50%) occur over northern mid- and high latitudes and over India and the Arabian Peninsula. Marked differences occur between,the BAU and STA550 regional precipitation changes resulting from inter- decadal variability. Surface evaporation increases at all latitudes except for 60 8‐908S. Water vapor from increased tropical evaporation is transported into mid- and high latitudes and returned to the surface through increased precipitation there. Changes in soil moisture content are small (within 63%). Total cloud cover changes little, although there is an upward,shift of midlevel clouds. Surface diurnal temperature range decreases by about 0.28‐ 0.58C over most land areas. The 2‐8-day synoptic storm activity decreases (by up to 10%) at low latitudes and over midlatitude oceans, but increases over Eurasia and Canada. The cores of subtropical jets move slightly up- and equatorward. Associated with reduced latitudinal temperature gradients over mid- and high latitudes, the wintertime Ferrel cell weakens (by 10%‐15%). The Hadley circulation also weakens (by ;10%), partly due to
From a societal, weather, and climate perspective, precipitation
intensity, duration, frequency, and phase are as much of concern as
total amounts, as these factors determine the disposition of
precipitation once it hits the ground and how much runs off. At the
extremes of precipitation incidence are the events that give rise to
floods and droughts, whose changes in occurrence and severity have an
enormous impact on the environment and society. Hence, advancing
understanding and the ability to model and predict the character of
precipitation is vital but requires new approaches to examining data and
models. Various mechanisms, storms and so forth, exist to bring about
precipitation. Because the rate of precipitation, conditional on when it
falls, greatly exceeds the rate of replenishment of moisture by surface
evaporation, most precipitation comes from moisture already in the
atmosphere at the time the storm begins, and transport of moisture by
the storm-scale circulation into the storm is vital. Hence, the
intensity of precipitation depends on available moisture, especially for
heavy events. As climate warms, the amount of moisture in the
atmosphere, which is governed by the Clausius- Clapeyron equation, is
expected to rise much faster than the total precipitation amount, which
is governed by the surface heat budget through evaporation. This implies
that the main changes to be experienced are in the character of
precipitation: increases in intensity must be offset by decreases in
duration or frequency of events. The timing, duration, and intensity of
precipitation can be systematically explored via the diurnal cycle,
whose correct simulation in models remains an unsolved challenge of
vital importance in global climate change. Typical problems include the
premature initiation of convection, and precipitation events that are
too light and too frequent. These challenges in observations, modeling,
and understanding precipitation changes are being taken up in the NCAR
"Water Cycle Across Scales" initiative, which will exploit the diurnal
cycle as a test bed for a hierarchy of models to promote improvements in
models.*The National Center for Atmospheric Research is sponsored by the
National Science Foundation
Recent developments in the study of moisture and heat fields in the soil
are applied to the problem of evaporation from bare soil surfaces. Most
of the analysis is confined to steady conditions, but it definitely
suggests that there are three phases to the desiccation of a given soil
profile:1. So long as the soil is sufficiently moist, the evaporation
rate, E, is indistinguishable from that from a saturated surface,
E3.2. At intermediate moisture contents, E is independent of
E3 and depends only on the soil-moisture distribution.3. When
the surface layers of the soil are sufficiently dry, E is sensitive to
the heat flux in the soil, and a negative correlation between E and
E3 may follow.The first and second of these correspond to the
well-known constant and falling rate phases of the `isothermal' drying
of initially saturated soils and other porous media, which thus receive
quantitative physical explanation. There is experimental evidence of the
existence of the third phase also.Other results of the article include
:1. Development of a (steady state) mode1 of the energy balance at
imperfectly evaporating surfaces (E < E3). This leads to a
simplified but suggestive approach to the microclimate of bare soils.2.
Analysis of the spatial distribution of evaporation sites within the
soil.3. Analysis of the modification of the energy balance which results
from the location of evaporation sites within the soil rather than at
the surface.
The Common Land Model (CLM) has recently been developed through a
grass-roots collaboration of scientists who have an interest in making a
general land model available for public use. Its major components
include: (1) Ten prognostic layers in the soil temperature and soil
moisture, with a free drainage and a zero heat flux as the bottom
boundary conditions; (2) A comprehensive parameterization of snow
processes with up to 5 snow layers depending on the total snow depth;
(3) Prognostic equations for mass of liquid water and ice water within
soil / snow, and explicit treatment of phase changes within soil / snow;
(4) Runoff is parameterized from the lowlands in terms of precipitation
incident on wet areas and a base flow using ideas from TOPMODEL; (5)
Incorporation of a realistic canopy photosynthesis-conductance model to
describe the simultaneous transfer of CO2 and water vapor into and out
of vegetation, respectively. (6) Its interface with the atmospheric
model is characterized by a tiled treatment of subgrid fraction of
energy and water balance; (7) Global vegetation cover database derived
from satellite AVHRR; Global soil data with vertical profile from
IGBP-DIS; and Global survey data for root vertical distribution; (8) The
code is based on FORTRAN90. The model has been extensively evaluated in
offline tests, land-atmosphere coupled simulations, and in data
assimilation. In the presentation, we will discuss the model as well as
its offline tests using long observational time series from six
different sites: Valdai (grassland), Cabauw (grassland), Hapex-Mobilhy
(crop), Amazonian (rainforest), FIFE (grassland) and Tucson
(semi-desert).
Indices for objectively quantifying the severity of meteorological,
agricultural, and hydrological forms of drought are discussed. Indices
for each drought form are judged according to six weighted evaluation
criteria: robustness, tractability, transparency, sophistication,
extendability, and dimensionality. The indices considered most promising
for succinctly summarizing drought severity are computed for two climate
divisions in Oregon for 24 water years, 1976-99. The assessment
determined that the most valuable indices for characterizing
meteorological, hydrological, and agricultural droughts are rainfall
deciles, total water deficit, and computed soil moisture, respectively.
A unique dataset of soil moisture in the upper 1-m soil layer at sites
with natural plant cover in the Soviet Union is compared to simulations
of soil moisture for the present climate by the Geophysical Fluid
Dynamics Laboratory, Oregon State University, and United Kingdom
Meteorological Office general circulation models. It is found that the
present-day soil moisture regime is not well simulated by these
models.Delworth and Manabe's hypothesis that the spectrum of time
variations in soil moisture in the upper 1-m layer corresponds to a
first-order Markov process with a decay time of the correlation function
equal to the ratio of field capacity to potential evapotranspiration is
empirically confirmed with this dataset.Analysis of measurement data
over the 1972-1985 period reveals that the long-term trends of soil
moisture north of 50°N are mainly due to increasing precipitation
during this period of the same scale (1-3 cm/10 yr). The seasonal
structure does not correspond to the `summer continental desiccation'
scenario predicted by some climate models.
Observed decreases in pan evaporation over most of the United States and the former USSR during the post-WWII period, if interpreted as a decrease in actual evaporation, are at odds with increases in temperature and precipitation over many regions of these two countries. Using parallel observations of actual and pan evaporation at six Russian, one Latvian, and one U.S. experimental sites, we recalibrate trends in pan evaporation to make them more representative of actual evaporation changes. After applying this transformation, pan evaporation time series over southern Russia and most of the United States reveal an increasing trend in actual evaporation during the past forty years.
This study analysed and modified (where necessary) the properties of three drought indices: the Palmer drought severity index (PDSI), the Bhalme–Mooley index (BMI) and the standardized precipitation index (SPI). We modified the original PDSI's recursive formula, potential runoff, and Z index, which produced more realistic results than the original PDSI (designed for the USA) for East Africa. We improved the SPI by first using a plotting position formula designed for the Pearson type III (P3) distribution to transform the ‘smoothed’ precipitation data into non-exceedance probabilities, which we then transformed into standard P3 variates by the regional flood index method. The modified SPI depicted East Africa's drought conditions more accurately than the original SPI. Using the three indices and East Africa as a case example, we identified eight assessment criteria to determine the most appropriate index for detecting drought events on a regional basis. BMI produced results that are highly correlated to those of the modified PDSI, which suggested that precipitation alone could explain most of the variability of East African droughts. Furthermore, among the three indices, SPI is more appropriate for monitoring East African droughts because it is more easily adapted to the local climate, has modest data requirements, can be computed at almost any time scale, provides relatively consistent power spectra spatially, has no theoretical upper or lower bounds, and is easy to interpret. Copyright © 2003 Royal Meteorological Society
D rought is a recurring phenomena that has plagued civilization throughout history. It af-fects natural habitats, ecosystems, and many economic and social sectors, from the foundation of civilization—agriculture—to transportation, urban water supply, and the modern complex industries. The wide variety of sectors affected by drought, its diverse geographical and temporal distribution, and the demand placed on water supply by human-use systems make it difficult to develop a single definition of drought. The American Meteorological Society (1997) groups drought definitions and types into four cat-egories: meteorological or climatological, agricul-tural, hydrological, and socioeconomic. A prolonged (e.g., of several months or years duration) meteoro-logical drought—the atmospheric conditions result-ing in the absence or reduction of precipitation—can develop quickly and end abruptly (in some cases, the transition can occur almost literally overnight). Short-term (i.e., a few weeks duration) dryness in the surface layers (root zone), which occurs at a critical time during the growing season, can result in an ag-ricultural drought that severely reduces crop yields, even though deeper soil levels may be saturated. Hot temperatures, low relative humidity, and desiccating winds often add to the impact of the lack of rainfall (Condra 1944). The onset of an agricultural drought may lag that of a meteorological drought, depending on the prior moisture status of the surface soil lay-ers. Precipitation deficits over a prolonged period that affect surface or subsurface water supply, thus reducing streamflow, groundwater, reservoir, and lake levels, will result in a hydrological drought, which will persist long after a meteorological drought has ended. Socioeconomic drought associates the supply and demand of some economic good with elements of meteorological, agricultural, and hydrological In final form 12 February 2002 Knowing the history of drought index development helps take the confusion out of the complex issues of drought monitoring, drought impacts, and drought definitions.