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Drought and teleconnection and drought monitoring

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  • Water and Environment Consulting
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... Even though the drought has a massive impact on society, quantifying drought characteristics (intensity, magnitude, duration, and spatial extent), predicting and mitigating drought are difficult tasks among the climate community (Vicente-Serrano et al. 2016). Droughts are considered to be the most complex and least-understood natural hazard, interrelated with many different processes such as land-based processes (e.g., precipitation, evaporation rates, soil moisture current, runoff (Spinoni et al. 2017;Dai 2011)), atmospheric processes (monsoon circulations, atmospheric evaporative demand) (Vicente-Serrano et al. 2020;Zhang and Zhou 2015;Lin and Shelton 2020), and ocean processes (teleconnection with sea surface temperatures) (Dai 2011;Spinoni et al. 2017;Abiy et al. 2019). Due to its complexity, there is no acceptable universal approach to defining, monitoring, or quantifying drought characteristics, the spatial and temporal extent, up to date (Quiring 2009). ...
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The Gravity Recovery and Climate Experiment (GRACE) twin satellites observe time variations in Earth's gravity field which yield valuable information about changes in terrestrial water storage (TWS). GRACE is characterized by low spatial (>150,000 km2) and temporal (>10 days) resolution but has the unique ability to sense water stored at all levels (including groundwater) systematically and continuously. The GRACE Data Assimilation System (DAS), based on the Catchment Land Surface Model (CLSM), enhances the value of the GRACE water storage data by enabling spatial and temporal downscaling and vertical decomposition into moisture components (i.e., groundwater, soil moisture, and snow), which individually are more useful for scientific applications. In this study, GRACE DAS was applied to North America, and GRACE-based drought indicators were developed as part of a larger effort to investigate the possibility of more comprehensive and objective identification of drought conditions by integrating spatially, temporally, and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors. Previously, the drought monitors lacked objective information on deep soil moisture and groundwater conditions, which are useful indicators of drought. Extensive data sets of groundwater storage from U.S. Geological Survey monitoring wells and soil moisture from the Soil Climate Analysis Network were used to assess improvements in the hydrological modeling skill resulting from the assimilation of GRACE TWS data. The results point toward modest, but statistically significant, improvements in the hydrological modeling skill across major parts of the United States, highlighting the potential value of a GRACE-assimilated water storage field for improving drought detection. © 2012. American Geophysical Union.
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Seasonal climate anomalies over North America exhibit rather large variability between years characterized by the same ENSO phase. This lack of consistency reduces potential statistically based ENSO-related climate predictability. The authors show that the North Pacific oscillation (NPO) exerts a modulating effect on ENSO teleconnections. Sea level pressure (SLP) data over the North Pacific, North America, and the North Atlantic and daily rainfall records in the contiguous United States are used to demonstrate that typical ENSO signals tend to be stronger and more stable during preferred phases of the NPO. Typical El Niño patterns (e.g., low pressure over the northeastern Pacific, dry northwest, and wet southwest, etc.) are strong and consistent only during the high phase of the NPO, which is associated with an anomalously cold northwestern Pacific. The generally reversed SLP and precipitation patterns during La Niña winters are consistent only during the low NPO phase. Climatic anomalies tend to be weak and spatially incoherent during low NPO-El Niño and high NPO-La Niña winters. These results suggest that confidence in ENSO-based long-range climate forecasts for North America should reflect interdecadal climatic anomalies in the North Pacific.
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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.
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The Palmer Drought Severity Index (PDSI) has been calculated for about 30 years as a means of providing a single measure of meteorological drought severity. It was intended to retrospectively look at wet and dry conditions using water balance techniques. The Standardized Precipitation Index (SPI) is a probability index that was developed to give a better representation of abnormal wetness and dryness than the Palmer indices. Before the user community will accept the SPI as an alternative to the Palmer indices, a standard method must be developed for computing the index. Standardization is necessary so that all users of the index will have a common basis for both spatial and temporal comparison of index values. If different probability distributions and models are used to describe an observed series of precipitation, then different SPI values may be obtained. This article describes the effect on the SPI values computed from different probability models as well as the effects on dry event characteristics. It is concluded that the Pearson Type III distribution is the `best' universal model, and that the reliability of the SPI is sample size dependent. It is also concluded that because of data limitations, SPIs with time scales longer than 24 months may be unreliable. An internet link is provided that will allow users to access Fortran 77 source code for calculating the SPI.
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The standardized precipitation evapotranspiration index (SPEI) was developed in 2010 and has been used in an increasing number of climatology and hydrology studies. The objective of this article is to describe computing options that provide flexible and robust use of the SPEI. In particular, we present methods for estimating the parameters of the log-logistic distribution for obtaining standardized values, methods for computing reference evapotranspiration (ET0), and weighting kernels used for calculation of the SPEI at different time scales. We discuss the use of alternative ET0 and actual evapotranspiration (ETa) methods and different options on the resulting SPEI series by use of observational and global gridded data. The results indicate that the equation used to calculate ET0 can have a significant effect on the SPEI in some regions of the world. Although the original formulation of the SPEI was based on plotting-positions Probability Weighted Moment (PWM), we now recommend use of unbiased PWM for model fitting. Finally, we present new software tools for computation and analysis of SPEI series, an updated global gridded database, and a real-time drought-monitoring system.
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A new global index used operational satellite remote sensing as primary inputs and enhances near real-time drought monitoring and mitigation efforts. A DSI algorithm was developed using satellite-derived ET, PET, and NDVI products to detect and monitor droughts on a global basis. The DSI algorithm was developed to overcome several limitations and to exploit the relative volume of operational satellite records and associated vegetation indicators. The input datasets and the DSI model were introduced and DSI patterns and anomalies in relation to alternative global PDSI information and documented regional drought events. The MODIS operational net primary production (NPP) product was used as an indicator of vegetation productivity changes under documented severe droughts in the Amazon, Europe, and Russia, and to evaluate corresponding DSI- and PDSI-based vegetation drought responses.
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This study examines the sensitivity of the climate system to volcanic aerosol forcing in the third climate configuration of the Met Office Unified Model (HadCM3). The main test case was based on the 1880s when there were several volcanic eruptions, the well-known Krakatau being the largest. These eruptions increased atmospheric aerosol concentrations and induced a period of global cooling surface temperatures. In this study, an ensemble of HadCM3 has been integrated with the standard set of radiative forcings and aerosols from the Intergovernmental Panel on Climate Change Fourth Assessment Report simulations, from 1860 to present. A second ensemble removes the volcanic aerosols from 1880 to 1899. The all-forcings ensemble shows an attributable 1.2-Sv (1 Sv = 10 6-3 s -1) increase in the Atlantic meridional overturning circulation (AMOC) at 45°N-with a 0.04-PW increase in meridional heat transport at 40°N and increased northern Atlantic SSTs-starting around 1894, approximately 11 years after the first eruption, and lasting a further 10 years at least. The mechanisms responsible are traced to the Arctic, with suppression of the global water cycle (high-latitude precipitation), which leads to an increase in upper-level Arctic and Greenland Sea salinities. This then leads to increased convection in the Greenland-Iceland-Norwegian (GIN) Seas, enhanced Denmark Strait overflows, and AMOC changes with density anomalies traceable southward along the western Atlantic boundary. The authors investigate whether a similar response to the Pinatubo eruption in 1991 could still be ongoing, but do not find strong evidence.
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The existing remote sensing drought indices were mainly derived from optical and infrared bands, and have been widely used in monitoring agricultural drought; however, their application in monitoring meteorological drought was limited. This study proposes a new multi-sensor microwave remote sensing drought index, the Microwave Integrated Drought Index (MIDI), for monitoring short-term drought, especially the meteorological drought over semi-arid regions, by integrating three variables: Tropical Rainfall Measuring Mission (TRMM) derived precipitation, Advanced Microwave Scanning Radiometer for EOS (AMSR-E) derived soil moisture, and AMSR-E derived land surface temperature. Each variable was linearly scaled from 0 to 1 for each pixel based on absolute minimum and maximum values over time to relatively monitor drought. Pearson correlation analyses were performed between remote sensing drought indices and scale-dependent Standardized Precipitation Index (SPI) during the growing season (April to October) from 2003 to 2010 to assess the capability of remotely sensed drought indices over three bioclimate regions in northern China. The results showed that MIDI with proper weights of three components outperformed individual remote sensing drought indices and other combined microwave drought indices in monitoring drought. It nearly possessed the best correlations with different time scale SPI; meanwhile it showed the highest correlation with 1-month SPI, and then decreased as SPI time scale increased, suggesting that the MIDI was a very reliable index in monitoring meteorological drought. Furthermore, similar spatial patterns and temporal changes were found between MIDI and 1- or 3-month SPI in monitoring drought. Therefore, the MIDI was recommended to be the optimum drought index, in monitoring short-term drought, especially for meteorological drought over cropland and grassland across northern China or similar regions globally with the ability to work in all weather conditions.
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Drought is a complex phenomenon that is difficult to accurately describe because its definition is both spatially variant and context dependent. Decision makers in local, state, and federal agencies commonly use operational drought definitions that are based on specific drought index thresholds to trigger water conservation measures and determine levels of drought assistance. Unfortunately, many state drought plans utilize operational drought definitions that are derived subjectively and therefore may not be appropriate for triggering drought responses. This paper presents an objective methodology for establishing operational drought definitions. The advantages of this methodology are demonstrated by calculating meteorological drought thresholds for the Palmer drought severity index, the standardized precipitation index, and percent of normal precipitation using both station and climate division data from Texas. Results indicate that using subjectively derived operational drought definitions may lead to over- or underestimating true drought severity. Therefore, it is more appropriate to use an objective location-specific method for defining operational drought thresholds.
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From the 344 state climate divisions in the conterminous United States, nine distinct regions of warm-season drought variability are identified using Principal Components Analysis. The drought metric used is the Palmer Hydrological Drought Index for the period 1895–2008. The focus of this paper is multidecadal drought variability in the Southeast (SEUS) and eastern Gulf South (EGS) regions of the U.S.A., areas in which the low-frequency forcing mechanisms of warm-season drought are still poorly understood. Low-frequency drought variability in the SEUS and EGS is associated with smoothed indexed time series of major ocean-atmosphere circulation features, including two indices of spatiotemporal variability in the North Atlantic Subtropical Anticyclone (Bermuda High). Long-term warm-season drought conditions are significantly out-of-phase between the two regions. Multidecadal regimes of above- and below-average moisture in the SEUS and EGS are closely associated with slow variability in sea surface temperatures in the North Atlantic, and with the summer mean position and mean strength of the Bermuda High. Multivariate linear regression indicates that 82–92% of the low-frequency variability in warm-season moisture is explained by two of the three leading Principal Components of low-frequency variability in the climate indices. The findings are important for water resource managers and water-intensive industries in the SEUS and EGS. The associations identified in the paper are valuable for enhanced drought preparedness and forecasting in the study area, and potentially for global models of coupled ocean-atmosphere variability.
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Recent research has highlighted the persistence of multi-decadal epochs of enhanced/reduced flood risk across New South Wales (NSW), Australia. Recent climatological studies have also revealed multi-decadal variability in the modulation of the magnitude of El Niño/Southern Oscillation (ENSO) impacts. In this paper, the variability of flood risk across NSW is analysed with respect to the observed modulation of ENSO event magnitude. This is achieved through the use of a simple index of regional flood risk. The results indicate that cold ENSO events (La Niña) are the dominant drivers of elevated flood risk. An analysis of multi-decadal modulation of flood risk is achieved using the inter-decadal Pacific Oscillation (IPO) index. The analysis reveals that IPO modulation of ENSO events leads to multi-decadal epochs of elevated flood risk, however this modulation appears to affect not only the magnitude of individual ENSO events, but also the frequency of their occurrence. This dual modulation of ENSO processes has the effect of reducing and elevating flood risk on multi-decadal timescales. These results have marked implications for achieving robust flood frequency analysis as well as providing a strong example of the role of natural climate variability.
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The Pacific Decadal Oscillation (PDO) is a large-scale climate system feature that influences the surface climate and hydrology of western North America. In this paper, we review the literature describing the PDO and demonstrate its effects on temperature, precipitation, snowfall, glacier mass balance, and streamflow with a focus on western Canada, and particularly British Columbia. We review how the PDO index was developed and discuss other North Pacific climate patterns that resemble the PDO. The impacts of PDO on glacier mass balance and streamflow from retrospective studies are also reviewed and illustrated with specific examples from BC. We assess the current state of knowledge regarding the PDO and provide a critical assessment of its use in hydroclimatology. This information should provide insight on the sensitivity of projects to climatic variability. © 2010 Canadian Water Resources Association and Environment Canada.
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Hurricanes result in considerable damage in the United States. Previous work has shown that Atlantic hurricane landfalls in the United States have a strong relationship with the El Niño-Southern Oscillation phenomena. This paper compares the historical record of La Niña and El Niño events defined by eastern Pacific sea surface temperature with a dataset of hurricane losses normalized to 1997 values. A significant relationship is found between the ENSO cycle and U.S. hurricane losses, with La Niña years exhibiting much more damage. Used appropriately, this relationship is of potential value to decision makers who are able to manage risk based on probabilistic information.
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Linkages between tropical Pacific Ocean monthly climatic variables and the Upper Colorado River basin (UCRB) hydroclimatic variations from 1909 to 1998 are analyzed at interseasonal timescales. A study of the changes in these linkages through the years and their relationship to the Pacific Decadal Oscillation (PDO) is also investigated. Tropical Pacific climate variations were represented by atmospheric/oceanic ENSO indicators. For the UCRB, warm season (April-September) streamflow totals at Lee's Ferry, Arizona, and precipitation averages at different periods (cold season: October-March; warm season: April-September; and annual: October-September) were used to study the UCRB's response to tropical Pacific climatic forcing. A basinwide ENSO signature was found in the significant correlations between warm season precipitation in the UCRB and warm season SST averages from the Niño-3 region in most of the stations around the UCRB. This link is more evident during the warm phase of ENSO (El Niño), which is associated with an increase in warm season precipitation. The analysis also showed a link between June to November ENSO conditions and cold season precipitation variations contained in a principal component representing the high-elevation precipitation stations, which are the main source of streamflow. However, the amplitude and coherence of the cold season ENSO signal is significantly smaller compared to the general precipitation variations found in stations around the UCRB. Only when very few stations in the high elevations are considered is the ENSO signal in cold season precipitation in the basin revealed. Interdecadal hydroclimatic variations in the UCRB related to possible PDO influences were also investigated. There are significant shifts in the mean of UCRB's moisture-controlled variables (precipitation and streamflow) coincident with the PDO shifts, suggesting a connection between the two processes. It has been suggested in other studies that this connection could be expressed as a modulation on the predominance of each ENSO phase; that is, strong and consistent winter El Niño (La Niña) patterns are associated with the positive (negative) phase of the PDO. In the UCRB this apparent modulation seems to be accompanied by a general change in the sign of the correlation between ENSO indicators and cold season precipitation in most stations of the basin around 1932/33. From 1909 to 1932 the basin has a predominantly cold season ENSO response characteristic of the northwestern United States (drier than normal associated with tropical SST warming and vice versa); from 1933 to 1998 the response of the basin is predominantly typical of the southwestern United States during winter (wetter than normal associated with tropical SST warming and vice versa). This apparent correlation sign reversal is suggested to be related to interdecadal changes in the boundary of the north-south bipolar response characteristic of the ENSO signal in the western United States during winter.
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A parametric water balance model was developed based on statistical averaging of the main hydrological processes. The model has a two-layer structure with both a physical and statistical basis for the model parameters. It was developed to fill a need for models with a small number of parameters and of intermediate complexity between a one-parameter simple bucket and more complex hydrologically oriented models with many parameters such as the Sacramento model. The focus was to improve the representation of runoff relative to the simple bucket without introducing the full complexity of the Sacramento model. The model was designed to operate over a range of time steps to facilitate coupling to an atmospheric model. The model can be used for catchment scale simulations in hydrological applications and for simple representation of runoff in coupled atmospheric/hydrological models. An important role for the simple water balance (SWB) model is to assist in understanding how much complexity in representing land surface processes is needed and can be supported with available data to estimate model parameters. The model is tested using rainfall, runoff, and surface meteorological data for three catchments from different climate regimes. Model performance is compared to performance of a simple bucket model, the Sacramento model, and the Oregon State University land surface model. Finally, a series of tests were conducted to evaluate the sensitivity of SWB performance when it is operated at time steps different from the time step for which it was calibrated.
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Some physical causes of United States drought are outlined. Among the associated factors is subsidence, either in the upper level as or to the south of strong jets, or sometimes under prevailing northerly components of upper level flow. These conditions are engendered by abnormal forms of the atmosphere's general circulation. Causative factors vary in kind and degree according to area, so that droughts over the Far West differ from those of the Great Plains or the East. Examples of each of these are shown as well as treatment of a rapidly developing drought.
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The surface-water-supply index (SWSI) was introduced in Colorado in the early 1980s as a better indicator of water availability in the western United States than is the Palmer drought index. Similar indexes have been subsequently developed in Oregon and Montana. These indexes have found great usefulness in drought monitoring and in triggering specific drought-related activities by state governments. Two conceptual weaknesses exist in the current SWSIs: (1) Subjective assignment of values to coefficients; and (2) obscured statistical properties of the index. Revisions to overcome these weaknesses include a specific definition of surface-water-supply, use of streamflow volume forecasts, and appropriate handling of data to achieve the desired statistical properties of the index. It is also suggested that indexes for individual hydrologic components be developed to provide supporting information to the SWSI. An example of the development of the revised SWSI is given for the Flathead River basin in Montana.
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A number of recent studies have reported an ENSO-like EOF mode in the global sea surface temperature (SST) field, whose time variability is marked by an abrupt change toward a warmer tropical eastern Pacific and a colder extratropical central North Pacific in 1976-77. The present study compares this pattern with the structure of the interannual variability associated with the ENSO cycle and documents its time history back to 1900. The analysis is primarily based on the leading EOFs of the SST anomaly and ''anomaly deviation'' fields in various domains and the associated expansion coefficient (or principal component) time series, which are used to construct global regression maps of SST, sea level pressure (SLP), and a number of related variables. The use of ''anomaly deviations'' (i.e., departures of local SST anomalies from the concurrent global-mean SST anomaly) reduces the influence of global-mean SST trends upon the structure of the EOFs and their expansion coefficient time series. An important auxiliary time series used in this study is a ''Southern Oscillation index'' based on marine surface observations. By means of several different analysis techniques, the time variability of the leading EOF of the global SST field is separated into two components: one identified with the ''ENSO cycle-related'' variability on the inter- annual timescale, and the other a linearly independent ''residual'' comprising all the interdecadal variability in the record. The two components exhibit rather similar spatial signatures in the global SST, SLP, and wind stress fields. The SST signature in the residual variability is less equatorially confined in the eastern Pacific and it is relatively more prominent over the extratropical North Pacific. The corresponding SLP signature is also stronger over the extratropical North Pacific, and its counterpart in the cold season 500-mb height field more closely resembles the PNA pattern. The amplitude time series of the ENSO-like pattern in the residual variability reflects the above-mentioned shift in 1976-77, as well as a number of other prominent features, including a shift of opposite polarity during the 1940s.
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