Earth Interactions

Published by American Geophysical Union
Online ISSN: 1087-3562
Publications
Article
"Understory fires" that burn the floor of standing forests are one of the most important types of forest impoverishment in the Amazon, especially during the severe droughts of El Nino Southern Oscillation (ENSO) episodes. However, we are aware of no estimates of the areal extent of these fires for the Brazilian Amazon and, hence, of their contribution to Amazon carbon fluxes to the atmosphere. We calculated the area of forest understory fires for the Brazilian Amazon region during an El Nino (1998) and a non El Nino (1995) year based on forest fire scars mapped with satellite images for three locations in eastern and southern Amazon, where deforestation is concentrated. The three study sites represented a gradient of both forest types and dry season severity. The burning scar maps were used to determine how the percentage of forest that burned varied with distance from agricultural clearings. These spatial functions were then applied to similar forest/climate combinations outside of the study sites to derive an initial estimate for the Brazilian Amazon. Ninety-one percent of the forest area that burned in the study sites was within the first kilometer of a clearing for the non ENSO year and within the first four kilometers for the ENSO year. The area of forest burned by understory forest fire during the severe drought (ENSO) year (3.9 millions of hectares) was 13 times greater than the area burned during the average rainfall year (0.2 million hectares), and twice the area of annual deforestation rate. Dense forest was, proportionally, the forest area most affected by understory fires during the El Nino year, while understory fires were concentrated in transitional forests during the year of average rainfall. Our estimate of aboveground tree biomass killed by fire ranged from 0.06 Pg to 0.38 Pg during the ENSO and from 0,004 Pg to 0,024 Pg during the non ENSO.
 
Article
This article promotes the hypothesis that the massive demographic collapse of the native populations of the Americas triggered by the European colonization brought about the abandonment of large expanses of agricultural fields soon recovered by forests, which in due turn fixed atmospheric CO<sub>2</sub> in significant quantities. This hypothesis is supported by measurements of atmospheric CO<sub>2</sub> levels in ice cores from Law Dome, Antarctica. Changing the focus from paleoclimate to global population dynamics and using the same causal chain, the measured drop in historic atmospheric CO<sub>2</sub> levels can also be looked upon as further, strong evidence for the postconquest demographic collapse of the Americas.
 
Article
Urban heat islands (UHIs) are caused by the heat-retaining properties of surfaces usually found in urban cities like asphalt and concrete. The UHI can typically be observed on the evening TV weather map as warmer temperatures over the downtown of major cities and cooler temperatures in the suburbs and surrounding rural areas. The UHI has now become a widely acknowledged, observed, and researched phenomenon because of its broad environmental and societal implications. Interest in the UHI will intensify in the future as existing urban areas expand and rural areas urbanize. By the year 2025, more than 60% of the world s population will live in cities, with higher percentages expected in developed nations. The urban growth rate in the United States, for example, is estimated to be 12.5%, and the recent 2000 Census found that more than 80% of the population currently lives in urban areas. Furthermore, the U.S. population is not only growing but is tending to concentrate more in urban areas within the environmentally sensitive coastal zones. Urban growth creates unique and often contentious issues for policymakers related to land use zoning, transportation planning, agricultural production, housing and development, pollution, and natural resources protection. Urban expansion and its associated TJHIs also have measurable impacts on weather and climate processes. The UHI has been documented to affect local and regional temperature, wind patterns, and air quality
 
Initial and boundary conditions for the convection simulations of this paper.
Article
The potential effects of continental crust on mantle convection are explored using threedimensional numerical simulations. The simulations model the coupling between a thin, deformable layer of chemically buoyant crust and a deep layer of thermally convecting and chemically dense mantle. Simulations begin with a crustal layer embedded within the upper thermal boundary layer of a mantle convection roll in a 1x1x1 domain. Convective stresses cause crust to thicken above a sheet-like mantle downwelling. For mild convective vigor an initial crustal thickness variation is required to induce three-dimensional mantle instability below the zone of thickening. Instability is characterised by the formation of local drip-like thermals that exist within the large-scale thermal roll associated with crustal thickening. In terms of surface effects, the drips cause significant deviations from local Airy compensation. After initial thickening, the crustal accumulation that forms serves as an ...
 
Article
Using the Coupled Model Intercomparison Project phase 3 (CMIP3) general circulation models (GCMs), projections of a range of climate extremes are explored for the western Pacific. These projections include the 1-in-20-yr return levels and a selection of climate indices for minimum temperature, maximum temperature, and precipitation, and they are compared to corresponding mean projections for the Special Report on Emission Scenarios (SRES) A2 scenario during 2081-2100. Models are evaluated per variable based on their ability to simulate current extremes, as well as the overall daily distribution. Using the standardized evaluation scores for each variable, models are divided into four subsets where ensemble variability is calculated to measure model uncertainty and biases are calculated in respect to the multimodel ensemble (MME). Results show that higher uncertainty in projections of climate extremes exists when compared to the mean, even in those subsets consisting of higher-skilled models. Higher uncertainty exists for precipitation projections than for temperature, and biases and uncertainties in the 1-in-20-yr precipitation events are an order of magnitude higher than the corresponding mean. Poorer performing models exhibit a cooler bias in the mean and 1-in- 20-yr return levels for maximum and minimum temperature, and ensemble variability is low among all subsets of mean minimum temperature, especially the lower-skilled subsets. Higher-skilled models project 1-in-20-yr precipitation return levels that are more intense than in the MME. The frequency of temperature extremes increase dramatically; however, this is explained by the underpinning small temperature range of the region. Although some systematic biases occur in the higher- and lower-skilled models and omitting the poorer performers is recommended, great care should be exercised when interpreting the reduction of uncertainty because the ensemble variability among the remaining models is comparable and in some cases greater than the MME. Such results should be treated on a case-by-case basis.
 
Article
In this study, the authors provide a global assessment of the performance of different drought indices for monitoring drought impacts on several hydrological, agricultural, and ecological response variables. For this purpose, they compare the performance of several drought indices [the standardized precipitation index (SPI); four versions of the Palmer drought severity index (PDSI); and the standardized precipitation evapotranspiration index (SPEI)] to predict changes in streamflow, soil moisture, forest growth, and crop yield. The authors found a superior capability of the SPEI and the SPI drought indices, which are calculated on different time scales than the Palmer indices to capture the drought impacts on the aforementioned hydrological, agricultural, and ecological variables. They detected small differences in the comparative performance of the SPI and the SPEI indices, but the SPEI was the drought index that best captured the responses of the assessed variables to drought in summer, the season in which more drought-related impacts are recorded and in which drought monitoring is critical. Hence, the SPEI shows improved capability to identify drought impacts as compared with the SPI. In conclusion, it seems reasonable to recommend the use of the SPEI if the responses of the variables of interest to drought are not known a priori.
 
Article
With the growing demands for food and biofuel, new technologies and crop management systems are being used to increase productivity and minimize land-use impacts. In this context, estimates of productivity and the impacts of agriculture management practices are becoming increasingly important. Numerical models that describe the soil-surface-atmosphere interactions for natural and agricultural ecosystems are important tools to explore the impacts of these agronomical technologies and their environmental impacts. However, these models need to be validated by considering the different soil and environmental conditions before they can be widely applied. The processbased terrestrial agricultural version of the Integrated Biosphere Simulator (IBIS) model (Agro-IBIS) has only been calibrated and validated for North American sites. Here, the authors validate the Agro-IBIS results for an experimental soybean site in southern Brazil. At this site, soybean was grown under two different management systems: no tillage (NT) and conventional tillage (CT). The model results were evaluated against micrometeorological, soil condition, and biomass observations made during the soybean growing season. The leaf area index (LAI) was underestimated, approaching the values obtained in the CT crop system, with higher error in the leaf senescence period. The model shows higher skill for daily averages and the diurnal cycle of the energy balance components in the period of high LAI. The soil temperature and moisture were robustly simulated, although the latter is best correlated with the observations made at the CT field. The ecosystem respiration is highly underestimated, causing an overestimation of the cumulative net ecosystem exchange (NEE), particularly at the end of the crop cycle.
 
Article
The current Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)-based broadband albedomodel requires shortwave infrared bands 5 (2.145-2.185 nm), 6 (2.185-2.225 nm), 8 (2.295-2.365 nm), and 9 (2.360-2.430 nm) and visible/near-infrared bands 1 (0.52-0.60 nm) and 3 (0.78-0.86 nm). However, because of sensor irregularities at high temperatures, shortwave infrared wavelengths are not recorded in the ASTER data acquired after April 2008. Therefore, this study seeks to evaluate the performance of artificial neural networks (ANN) in estimating surface albedo using visible/nearinfrared bands available in the data obtained after April 2008. It also compares the outcomes with the results of multiple linear regression (MLR) modeling. First, the most influential spectral bands used in the current model as well as band 2 (0.63-0.69 nm) (which is also available after April 2008 in the visible/nearinfrared part) were determined by a primary analysis of the data acquired before April 2008. Then, multiple linear regression and ANN models were developed by using bands with a relatively high level of contribution. The results showed that bands 1 and 3 were the most important spectral ones for estimating albedo where land cover consisted of soil and vegetation. These two bands were used as the study input, and the albedo (estimated through a model that utilized bands 1, 3, 5, 6, 8, and 9) served as a target to remodel albedo. Because of its high collinearity with band 1, band 2 was identified less effectively by MLR as well as ANN. The study confirmed that a combination of bands 1 and 3, which are available in the current ASTER data, could be modeled through ANN and MLR to estimate surface albedo. However, because of its higher accuracy, ANN method was superior to MLR in developing objective functions.
 
Article
Fire influences global change and tropical ecosystems through its connection to land-cover dynamics, atmospheric composition, and the global carbon cycle. As such, the climate change community, the Brazilian government, and the Large-Scale BiosphereAtmosphere (LBA) Experiment in Amazonia are interested in the use of satellites to monitor and quantify fire occurrence throughout Brazil. Because multiple satellites and algorithms are being utilized, it is important to quantify the accuracy of the derived products. In this paper the characteristics of two fire detection algorithms are evaluated, both of which are applied to Terras Moderate Resolution Imagine Spectroradiometer (MODIS) data and with both operationally producing publicly available fire locations. The two algorithms are NASAs operational Earth Observing System (EOS) MODIS fire detection product and Brazils Instituto Nacional de Pesquisas Espaciais (INPE) algorithm. Both algorithms are compared to fire maps that are derived independently from 30-m spatial resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. A quantitative comparison is accomplished through logistic regression and error matrices. Results show that the likelihood of MODIS fire detection, for either algorithm, is a function of both the number of ASTER fire pixels within the MODIS pixel as well as the contiguity of those pixels. Both algorithms have similar omission errors and each has a fairly high likelihood of detecting relatively small fires, as observed in the ASTER data. However, INPEs commission error is roughly 3 times more than that of the EOS algorithm. Pages: 1-25
 
Article
In the Amazon basin, seasonal and interannual spectral changes measured by satellites result from anthropogenic disturbance and from the interaction between climate variation and the surface cover. Measurements of spectral change, and the characterization of that change, provide information concerning the physical processes evident at this mesoscale. A 17-yr sequence of daily Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) images were analyzed to produce a monthly record of surface spectral change encompassing El Niño-Southern Oscillation (ENSO) cycles. Monthly cloud-free composite images from daily AVHRR data were produced by linear filters that minimized the finescale spatial variance and allowed for a wide range analysis within a consistent mathematical framework. Here the use of a minimized local variance (MLV) filter that produced spatially smooth images in which major land-cover boundaries and spatial gradients are clearly represented is discussed. Changes in the configuration of these boundaries and the composition of the landscape elements they defined are described in terms of quantitative changes in landscape pattern. The time series produced with the MLV filter revealed a marked seasonal difference in the pattern of the landscape and structural differences over the length of the time series. Strikingly, the response of the region to drier El Nñio years appears to be delayed in the MLV series, the maximum response being in the year following El Niño with little or no change seen during El Niño.
 
Article
The Brazilian government annually assesses the extent of deforestation in the Legal Amazon for a variety of scientific and policy applications. Currently, the assessment requires the processing and storing of large volumes of Landsat satellite data. The potential for efficient, accurate, and less data-intensive assessment of annual deforestation using data from NASAs Moderate Resolution Imaging Spectroradiometer (MODIS) at 250-m resolution is evaluated. Landsat-derived deforestation estimates are compared to MODIS-derived estimates for six Landsat scenes with five change-detection algorithms and a variety of input dataSurface Reflectance (MOD09), Vegetation Indices (MOD13), fraction images derived from a linear mixing model, Vegetation Cover Conversion (MOD44A), and percent tree cover from the Vegetation Continuous Fields (MOD44B) product. Several algorithms generated consistently low commission errors (positive predictive value near 90%) and identified more than 80% of deforestation polygons larger than 3 ha. All methods accurately identified polygons larger than 20 ha. However, no method consistently detected a high percent of Landsat-derived deforestation area across all six scenes. Field validation in central Mato Grosso confirmed that all MODIS-derived deforestation clusters larger than three 250-m pixels were true deforestation. Application of this field-validated method to the state of Mato Grosso for 200104 highlighted a change in deforestation dynamics; the number of large clusters (>10 MODIS pixels) that were detected doubled, from 750 between August 2001 and August 2002 to over 1500 between August 2003 and August 2004. These analyses demonstrate that MODIS data are appropriate for rapid identification of the location of deforestation areas and trends in deforestation dynamics with greatly reduced storage and processing requirements compared to Landsat-derived assessments. However, the MODIS-based analyses evaluated in this study are not a replacement for high-resolution analyses that estimate the total area of deforestation and identify small clearings.. Pages: 1-22
 
Article
The Brazilian Amazon is one of the most rapidly developing agricultural frontiers in the world. The authors assess changes in cropland area and the intensification of cropping in the Brazilian agricultural frontier state of Mato Grosso using remote sensing and develop a greenhouse gas emissions budget. The most common type of intensification in this region is a shift from single-to double-cropping patterns and associated changes in management, including increased fertilization. Using the enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, the authors created a green-leaf phenology for 2001-06 that was temporally smoothed with a wavelet filter. The wavelet-smoothed green-leaf phenology was analyzed to detect cropland areas and their cropping patterns. The authors document cropland extensification and double-cropping intensification validated with field data with 85% accuracy for detecting croplands and 64% and 89% accuracy for detecting single-and double-cropping patterns, respectively. The results show that croplands more than doubled from 2001 to 2006 to cover about 100 000 km 2 and that new double-cropping intensification occurred on over 20% of croplands. Variations are seen in the annual rates of extensification and double-cropping intensification. Greenhouse gas emissions are estimated for the period 2001-06 due to conversion of natural vegetation and pastures to row-crop agriculture in Mato Grosso averaged 179 Tg CO2-e yr21, over half the typical fossil fuel emissions for the country in recent years.
 
Article
The Amazon rain forest may undergo significant change in response to future climate change. To determine the likelihood and causes of such changes, the authors analyzed the output of 24 models from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) and a dynamic vegetation model, Vegetation-Global-Atmosphere-Soil (VEGAS), driven by these climate output. Their results suggest that the core of the Amazon rain forest should remain largely stable because rainfall in the core of the basin is projected to increase in nearly all models. However, the periphery, notably the southern edge of Amazonia and farther south into central Brazil (SAB), is in danger of drying out, driven by two main processes. First, a decline in precipitation of 11% during the southern Amazonia's dry season (May-September) reduces soil moisture. Two dynamical mechanisms may explain the forecast reduction in dry season rainfall: 1) a general subtropical drying under global warming when the dry season southern Amazon basin is under the control of subtropical high pressure and 2) a stronger north-south tropical Atlantic sea surface temperature gradient and, to a lesser degree, a warmer eastern equatorial Pacific. The drying corresponds to a lengthening of the dry season by approximately 10 days. The decline in soil moisture occurs despite an increase in precipitation during the wet season, because of nonlinear responses in hydrology associated with the decline in dry season precipitation, ecosystem dynamics, and an increase in evaporative demand due to the general warming. In terms of ecosystem response, higher maintenance cost and reduced productivity under warming may also have additional adverse impact. Although the IPCC models have substantial intermodel variation in precipitation change, these latter two hydroecological effects are highly robust because of the general warming simulated by all models. As a result, when forced by these climate projections, a dynamic vegetation model VEGAS projects an enhancement of fire risk by 20%-30% in the SAB region. Fire danger reaches its peak in Amazonia during the dry season, and this danger is expected to increase primarily because of the reduction in soil moisture and the decrease in dry season rainfall. VEGAS also projects a reduction of about 0.77 in leaf area index (LAI) over the SAB region. The vegetation response may be partially mediated by the CO2 fertilization effect, because a sensitivity experiment without CO2 fertilization shows a higher 0.89 decrease in LAI. Southern Amazonia is currently under intense human influence as a result of deforestation and land-use change. Should this direct human impact continue at present rates, added pressure to the region's ecosystems from climate change may subject the region to profound changes in the twenty-first century.
 
Article
The influence of Amazonian floodplains on the hydrological, sedimentary, and biogeochemical river budget was investigated along the Vargem Grande–Óbidos reach, by applying six mixing models based on variable regional and/or variable hydrological sources. By comparing the output of many different models designed for different purposes, the nature and the magnitude of processes linking water and biogeochemical budgets of the Amazonian floodplains were clarified. This study reveals that most of the chemical baseline of the Amazon River basin is acquired before the studied 2000-km Amazonian reach. However, the tight connection between the hydrograph stage of the river and the chemical signals provides insightful information on the dynamics of its floodplains. The chemical expression of biotic and abiotic processes occurring in the Amazonian floodplains can be particularly perceived during falling waters. It appears delayed in time compared to the maximum extension of submerged area, because the alternating water circulation polarity (filling versus emptying) between the main channel and the adjacent floodplains determines delayed emptying of floodplains during falling waters. It results also in a longer time of residence in the hydrograph network, which strengthens the rate of transformation of transiting materials and solutes. Biotic and biologically mediated processes tend to accentuate changes in river water chemistry initiated upstream, in each subbasin, along river corridors, indicating that processes operating downstream prolong those from upstream (e.g., floodplains of the large tributaries). Conversely, the flood wave propagation tends to lessen the seasonal variability as a result of the water storage in the floodplains, which admixes waters of distinct origins (in time and space). The morphology of floodplains, determining the deposition and the diagenesis of the sediments as well as the variable extension of submerged areas or the chronology of floodplains storage/emptying, appears to be the main factor controlling the floodplains biogeodynamics. By coupling classical end-member mixing models (providing insight on hydrological source) with a variable regional contribution scheme, relevant information on the biogeochemical budget of the Amazonian floodplains can be achieved.
 
Article
Increase in global mean temperature and changes in rainfall amount, pattern, and distribution over the world are all indicative of climate change events. These changes alter the hydroclimatic condition of regions as well as the availability of water resources. In this study, the data generated by 14 general circulation models (GCMs) developed under the Special Report on Emissions Scenarios (SRES) A1B, A2, and B2 are downscaled and utilized to evaluate climate change impact on the hydroclimatic system of the Karaj River basin located in central Iran. The precipitation and temperature of the study region are downscaled using the change factor approach (CFA). The study analyzes future climate data, extreme changes of future climatic conditions of precipitation, and temperature. The Hydrologiska Byra ns Vattenbalansavdelning (HBV) model developed by the Swedish Meteorological and Hydrological Institute (SMHI) is used to simulate streamflow under extreme climate change conditions. Two different sources of uncertainty are investigated in this study. First, the model parameters uncertainty is analyzed with the Monte Carlo procedure, and then different datasets of GCMs projection are investigated under the climate of the twentieth-century climate simulation (20C3M). Results show the GCMs projections range can almost capture the historical records during the 1980s through 2000 for the Karaj basin. By applying the HBV model, considerable range of streamflow changes in the future can be projected that will affect the operation scheme of Karaj Reservoir. In this study, the system dynamics (SD) modeling approach is used to simulate the system behavior through time in an integrated fashion and evaluate its overall reliability in supplying water. The results of this study show that the runoff will decrease in the future under the climate change impact. This will result in more than 50% decrease in reliability of the Karaj Reservoir system under the extreme conditions. As a result, this research predicts that the Karaj Reservoir system will face more than 50% decrease in its reliability under the extreme conditions. Consequently, meeting the increasing water demands would be difficult and application of demand management strategies will be unavoidable.
 
Article
The Athabasca oil sands development in northeast Alberta, Canada, has disturbed more than 500 km2 of boreal forest through surface mining and tailings ponds development. In this paper, the authors compare the time series of temperatures and precipitation measured over oil sands and non-oil sands locations from 1994 to 2010. In addition, they analyzed the distribution of lightning strikes from 1999 to 2010. The oil sands development has not affected the number of lightning strikes or precipitation amounts but has affected the temperature regime. Over the past 17 years, the summer overnight minimum temperatures near the oil sands have increased by about 1.2°C compared to the regional average. The authors speculate that this is caused by a combination of the industrial addition of waste heat to the atmosphere above the oil sands and changing the surface type from boreal forest to open pit mines with tailings ponds.
 
Article
Atmosphere–land–ocean coupled model simulations are examined to diagnose the ability of models to simulate drought and persistent wet spells over the United States. A total of seven models are selected for this study. They are three versions of the NCEP Climate Forecast System (CFS) coupled general circulation model (CGCM) with a T382, T126, and T62 horizontal resolution; GFDL Climate Model version 2.0 (CM2.0); GFDL CM2.1; Max Planck Institute (MPI) ECHAM5; and third climate configuration of the Met Office Unified Model (HadCM3) simulations from the World Climate Research Programme (WCRP) Coupled Model Intercomparison Project phase 3 (CMIP3) experiments. Over the United States, drought and persistent wet spells are more likely to occur over the western interior region, while extreme events are less likely to persist over the eastern United States and the West Coast. For meteorological drought, which is defined by precipitation (P) deficit, the east–west contrast is well simulated by the CFS T382 and the T126 models. The HadCM3 captures the pattern but not the magnitudes of the frequency of occurrence of persistent extreme events. For agricultural drought, which is defined by soil moisture (SM) deficit, the CFS T382, CFS T126, MPI ECHAM5, and HadCM3 models capture the east–west contrast. The models that capture the west–east contrast also have a realistic P climatology and seasonal cycle. ENSO is the dominant mode that modulates P over the United States. A model needs to have the ENSO mode and capture the mean P responses to ENSO in order to simulate realistic drought. To simulate realistic agricultural drought, the model needs to capture the persistence of SM anomalies over the western region.
 
Article
The purpose of this study was to focus on how anomalies in the normalized difference vegetation index (NDVI; a proxy for soil moisture) over the Canadian Prairies can condition the convective boundary layer (CBL) so as to inhibit or facilitate thunderstorm activity while also considering the role of synoptic-scale forcing. This study focused on a census agricultural region (CAR) over central Alberta for which we had observed lightning data (proxy for thunderstorms), remotely sensed NDVI data, and in situ rawinsonde data (to quantify impacts of vegetation vigor on the CBL characteristics) for 11 summers from 1999 to 2009. The authors' data suggest that the occurrence of lightning over the study area is more likely (and is of longer duration) when storms develop in an environment in which the surface and upper-air synoptic-scale forcing are synchronized. On days when surface forcing and midtropospheric ascent are present, storms are more likely to be triggered when NDVI is much above average, compared to when NDVI is much below average. Additionally, the authors found the response of thunderstorm duration to NDVI anomalies to be asymmetric. That is, the response of lightning duration to anomalies in NDVI is marked when NDVI is below average but is not necessarily discernible when NDVI is above average. The authors propose a conceptual model, based largely on observations, that integrates all of the above findings to describe how a reduction in vegetation vigor-in response to soil moisture deficits-modulates the partitioning of available energy into sensible and latent heat fluxes at the surface, thereby modulating lifting condensation level heights, which in turn affect lightning activity.
 
Article
At the Visayas State College of Agriculture (ViSCA) on the island of Leyte in the Philippines, hydrologic and soil-loss measurements were recorded for 32 erosion events over 3 yr on three 12-m-long bare soil plots with slopes of approximately 50%, 60%, and 70%. Measurements included rainfall and runoff rates at 1-min intervals, total soil lost per event from the plot, rill details when observed after an erosion event, and soil settling-velocity characteristics. Storm events are characterized by high rainfall rates but quite low rates of runoff, because of the consistently high infiltration rate of the stable clay soil (an Oxic Dystropept). Both observation and modeling indicated that overland flow is commonly so shallow that much of the soil surface is likely to be unsubmerged. For the 70% slope plot, half the events recorded mean sediment concentrations from 100 to 570 kg m−3. A somewhat constant hydrologic lag between rainfall and runoff is used to estimate a Manning's roughness coefficient n of about 0.1 m−1/3 s, a value used to estimate velocity of overland flow. Possible effects of shallow flows and high sediment concentrations on existing erosion theory are investigated theoretically but are found to have only minor effects for the ViSCA dataset. A soil erodibility parameter β was evaluated for the data whenever rilling was recorded following an erosion event. The values of β indicate that, except for events with higher stream powers, other erosion processes in addition to overland flow could have contributed to soil loss from erosion plots in a significant number of events. Yes Yes
 
Article
A regional watershed model was developed for watersheds contributing to Long Island Sound, including the Connecticut River basin. The study region covers approximately 40 900 km(2), extending from a moderate coastal climate zone in the south to a mountainous northern New England climate zone dominated by snowmelt in the north. The input data indicate that precipitation and temperature have been increasing for the last 46 years (1961-2006) across the region. Minimum temperature has increased more than maximum temperature over the same period (1961-2006). The model simulation indicates that there was an upward trend in groundwater recharge across most of the modeled region. However, trends in increasing precipitation and groundwater recharge are not significant at the 0.05 level if the drought of 1961-67 is removed from the time series. The trend in simulated snowfall is not significant across much of the region, although there is a significant downward trend in southeast Connecticut and in central Massachusetts. To simulate future trends, two input datasets, one assuming high carbon emissions and one assuming low carbon emissions, were developed from GCM forecasts. Under both of the carbon emission scenarios, simulations indicate that historical trends will continue, with increases in groundwater recharge over much of the region and substantial snowfall decreases across Massachusetts, Connecticut, southern Vermont, and southern New Hampshire. The increases in groundwater recharge and decreases in snowfall are most pronounced for the high emission scenario.
 
Article
Because of their stochastic nature, droughts vary in space and time, and therefore quantifying droughts at different time units is important for water resources planning. The authors investigated the relationship between meteorological variables and hydrological drought properties using the Palmer hydrological drought index (PHDI). Twenty different spatial units were chosen from the unit of a climatic division to a regional unit across the United States. The relationship between meteorological variables and PHDI was investigated using a wavelet-Bayesian regression model, which enhances the modeling strength of a simple Bayesian regression model. Further, the wavelet-Bayesian regression model was tested for the predictability of global climate models (GCMs) to simulate PHDI, which will also help understand their role for downscaling purposes.
 
Article
Ocean and atmosphere reanalysis fields are used to study environmental conditions and their relation to commercial fish catch in the central Benguela upwelling zone, using both targeted and objective techniques. Composite maps and sections indicate a 10%–20% weakening of southeasterly winds, a 0.5°C warming of sea temperatures over the shelf, and changes in currents and subsurface upwelling associated with higher fish catch. During periods of high fish catch, recirculating gyres form that may aid the retention of eggs and larvae. Offshore winds contribute to poleward Ekman transport in a 50-m-deep layer within 100 km of the coast. In addition to composite analysis, the natural variability is studied by principal component analysis of wind stress, sea level, temperature, salinity, currents, and vertical motion in the period 1970–2007. Comparison of interannual time scores and fisheries data indicate that anomalous poleward winds and warmer temperatures in the Lüderitz plume, driven by an atmospheric trough in the South Atlantic, are associated with higher catch rates.
 
Foliar projective cover of tropical trees and grasses at the end of the 100-yr fully coupled spinup and prior to the deforestation branch cases. Shown are the (top left) broadleaf evergreen tropical tree, (top right) broadleaf deciduous tropical tree, (bottom left) C3 grass, and (bottom right) C4 grass.
Foliar projective cover of tropical trees and grasses at the end of 50 years of the DFC10-PT10 case. Shown are the (top left) broadleaf evergreen tropical tree, (top right) broadleaf deciduous tropical tree, (bottom left) C3 grass, and (bottom right) C4 grass.
Tree cover for the (top) broadleaf evergreen tropical tree and (bottom) broadleaf deciduous tropical tree for the (left) DFC10-PT10 and (right) DFC1-PT10 cases averaged over their respective postdeforestation periods.
Total foliar projective cover in the tropical band (308S-308N) of tropical tree types and grasses in the first 100 years of the control (solid lines), DFC1-PT10 (dashed lines), and DFC10-PT10 (dotted lines) branches.
Article
Deforestation perturbs both biophysical and carbon feedbacks on climate. However, biophysical feedbacks operate at temporally immediate and spatially focused scales and thus may be sensitive to the rate of deforestation rather than just to total forest-cover loss. Explored here is a method for simulating annual tropical deforestation in the fully coupled Community Climate System Model, version 3.0 (CCSM3) with the Dynamic Global Vegetation Model (DGVM) for testing biosphere climate sensitivity to "preservation pathways." Two deforestation curves were simulated-a 10% deforestation curve with a 10% preservation target (DFC10-PT10) versus a 1% deforestation curve with a 10% preservation target (DFC1-PT10). During active deforestation, albedo, net radiation, latent heat flux, and climate variables were compared for time dependence and sensitivity to tropical tree cover across the tropical band and the Amazon basin, central African, and Southeast Asian regions. The results demonstrated the feasibility of modeling incremental deforestation and detecting both transient and long-term impacts, although a warm/dry bias in CCSM3-DGVM and the absence of carbon feedbacks preclude definitive conclusions on the magnitude of sensitivities. The deforestation rates produced characteristic trends in biophysical variables with DFC10-PT10 resulting in rapid increase/decrease during the initial 10-30 years before leveling off, whereas DFC1-PT10 exhibits gradual changes. The rate had little effect on biophysical and climate sensitivities when averaged over tropical land but produced significant differences at a regional level. Over the long term, the rates produced dissimilar vegetation distributions, despite having the same preservation target in both cases. Overall, these results indicate that the question of rates is one worth further analysis.
 
Map of the study area of the Kapchorwa headwater chronosequence of catchments in western Kenya and its approximate location within Kenya (inset shows Kenya and its districts). The weir positions are shown by dots in each catchment. Letters indicate land-use histories of the catchments: (a) forested catchment and maize cultivation for (b) 5, (c) 10, and (d) 50 years following forest conversion. 
Daily discharge and rainfall of the Kapchorwa chronosequence of catchments in western Kenya in 2007 and 2008 for (a) forested and agricultural catchments with (b) 5, (c) 10, and (d) 50 years of cultivation. 
Cumulative flow duration curves of the Kapchorwa headwater chronosequence of catchments (average of 2007 and 2008). 
Article
Tropical Africa is affected by intense land-use change, particularly forest conversion to agricultural land. In this study, the stream discharge of four small headwater catchments located within an area of 6 km2 in western Kenya was examined for 2 years (2007 and 2008). The four catchments cover a degradation gradient ranging from intact forest to agricultural land under maize cultivation for 5, 10, and 50 years. The runoff ratio (e.g., annual catchment discharge expressed as a percentage of rainfall) increased with increasing duration of cultivation from an average of 16.0% in the forest to 32.4% in the 50-yr-old agricultural catchment. Similarly, the average runoff ratio due to the stormflow component was 0.033 in the forest and increased gradually to 0.095 with increasing duration of cultivation. The conversion from forest to agricultural land in the first 5 years caused about half of the total observed increases in runoff ratio (46.3%) and discharge in relation to rainfall (50.6%). The other half of the changes in discharge occurred later during soil degradation after forest clearing. With increasing duration of cultivation, soil bulk density ρb at a depth of 0-0.1 m increased by 46%, while soil organic carbon (SOC) concentrations and total porosity decreased by 75% and 20%, respectively. The changes in hydrological responses that occurred in the initial years after forest clearing may suggest a significant potential for improved land management in alleviating runoff and enhanced storm flow and moisture retention in agricultural watersheds.
 
Article
Poyang Lake in Jiangxi Province is the largest freshwater lake in China and is historically a region of significant floods. Maximum annual lake stage and the number of severe flood events have increased during the past few decades because of levee construction that reduced the area available for floodwater storage. The most severe floods since 1950 occurred during 1954, 1973, 1983, 1995, and 1998. Each of these floods followed El Niño events that influence the Asian monsoon and that are directly linked to rainfall in the Changjiang (Yangtze River) basin. The 1954 flood was the largest ever recorded until the 1990s. That year the peak Changjiang stage at Hukou was 21.6 m, which was 1.6 m above the previous record high. The last major flood on the Changjiang was during 1998, when the peak Changjiang stage reached 22.5 m, higher than during 1954, even though peak discharge was lower. The most severe floods, including those in 1954 and 1998, require both 1) high rainfall and tributary discharge into Poyang Lake and 2) high Changjiang discharge and stage at Hukou that backflows into the lake or slows Poyang Lake drainage. Since gauging stations were established on the Changjiang, these conditions always occurred following an El Niño.
 
Location map of the United States showing the 14 selected basins. Red triangle denotes location of stream gauge for model calibration (basins not to scale; see Table 1 for relative scales). 
Schematic of the climate change factor method as applied in this study. 
( Continued ) 
Range in 11-yr moving mean daily growing season values by emission scenario for the 14 basins. 
Article
Understanding the effects of climate change on the vegetative growing season is key to quantifying future hydrologic water budget conditions. The U. S. Geological Survey modeled changes in future growing season length at 14 basins across 11 states. Simulations for each basin were generated using five general circulation models with three emission scenarios as inputs to the Precipitation-Runoff Modeling System (PRMS). PRMS is a deterministic, distributed-parameter, watershed model developed to simulate the effects of various combinations of precipitation, climate, and land use on watershed response. PRMS was modified to include a growing season calculation in this study. The growing season was examined for trends in the total length (annual), as well as changes in the timing of onset (spring) and the end (fall) of the growing season. The results showed an increase in the annual growing season length in all 14 basins, averaging 27-47 days for the three emission scenarios. The change in the spring and fall growing season onset and end varied across the 14 basins, with larger increases in the total length of the growing season occurring in the mountainous regions and smaller increases occurring in the Midwest, Northeast, and Southeast regions. The Clear Creek basin, 1 of the 14 basins in this study, was evaluated to examine the growing season length determined by emission scenario, as compared to a growing season length fixed baseline condition. The Clear Creek basin showed substantial variation in hydrologic responses, including streamflow, as a result of growing season length determined by emission scenario.
 
Article
The international scientific community has long recognized the need for coordinated drought monitoring and response, but many factors have prevented progress in the development of a Global Drought Early Warning System (GDEWS): some of which involve administrative issues (coordinated international action and policy) while others involve scientific, technological, and logistical issues. The creation of the National Integrated Drought Information System (NIDIS) Portal within the United States provided an opportunity to take the first steps toward building the informational foundation for a GDEWS: that is, a Global Drought Information System (GDIS). At a series of workshops sponsored by the World Meteorological Organization (WMO) and Group on Earth Observations (GEO) held in Asheville, North Carolina, in April 2010, it was recommended that a modular approach be taken in the creation of a GDIS and that the NIDIS Portal serve as the foundation for the GDIS structure. Once a NIDIS-based Global Drought Monitor (GDM) Portal (GDMP) established an international drought clearinghouse, the various components of a GDIS (drought monitoring, forecasting, impacts, history, research, and education) and later a GDEWS (drought relief, recovery, and planning) could be constructed atop it. The NIDIS Portal is a web-based information system created to address drought services and early warning in the United States, including drought monitoring, forecasting, impacts, mitigation, research, and education. This portal utilizes Open Geospatial Consortium (OGC) web mapping services (WMS) to incorporate continental drought monitors into the GDMP. As of early 2012, the GDM has incorporated continental drought information for North America (North American Drought Monitor), Europe (European Drought Observatory), and Africa (African Drought Monitor developed by Princeton University); interest has been expressed by groups representing Australia and South America; and coordination with appropriate parties in Asia is also expected. Because of the range of climates across the world and the diverse nature of drought and the sectors it impacts, the construction and functioning of each continental drought monitor needs to be appropriate for the continent in question. The GDMP includes a suite of global drought indicators identified by experts and adopted by the WMO as the necessary measures to examine drought from a meteorological standpoint; these global drought indicators provide a base to assist the global integration and interpretation of the continental drought monitors. The GDMP has been included in recent updates to the GEO Work Plan and has benefited from substantial coordination with WMO on both their Global Framework for Climate Services and the National Drought Policy efforts. The GDMP is recognized as having the potential to be a major contributor to both of these activities.
 
The central Appalachian Mountains. The heavy lines portray state boundaries, and the thin lines indicate physiographic boundaries (based on Fenneman 1938; Rodgers 1970; Bailey 1999). The points represent the climate stations used to analyze precipitation regimes for the central Appalachian NF and NP lands used by Lafon and Grissino-Mayer (Lafon and Grissino-Mayer 2007) in their analysis of central Appalachian fire regimes.  
Climate stations in the central Appalachian Mountains. 
Relationship of fire activity to (a),(b) mean annual moisture balance and (c),(d) daily precipitation variability for NFs and NPs in the eastern United States. The graphs in (a),(c) portray fire activity in terms of mean annual fire density, while those in (b),(d) depict fire activity in terms of mean annual area burned. Each point on the scatterplots represents an NF or NP.  
Eastern U.S. federal lands incorporated in the study. 
Correlations of fire activity to climate variables for national forests and parks across the eastern United States. 
Article
Fire affects virtually all terrestrial ecosystems but occurs more commonly in some than in others. This paper investigates how climate, specifically the moisture regime, influences the flammability of different landscapes in the eastern United States. A previous study of spatial differences in fire regimes across the central Appalachian Mountains suggested that intra-annual precipitation variability influences fire occurrence more strongly than does total annual precipitation. The results presented here support that conclusion. The relationship of fire occurrence to moisture regime is also considered for the entire eastern United States. To do so, mean annual wildfire density and mean annual area burned were calculated for 34 national forests and parks representing the major vegetation and climatic conditions throughout the eastern forests. The relationship between fire activity and two climate variables was analyzed: mean annual moisture balance [precipitation P - potential evapotranspiration (PET)] and daily precipitation variability (coefficient of variability for daily precipitation). Fire activity is related to both climate variables but displays a stronger relationship with precipitation variability. The southeastern United States is particularly noteworthy for its high wildfire activity, which is associated with a warm, humid climate and a variable precipitation regime, which promote heavy fuel production and rapid drying of fuels.
 
Article
Located on the Bahr el Jebel in South Sudan, the Sudd is one of the largest floodplain wetlands in the world. Seasonal inundation drives the hydrologic, geomorphological, and ecological processes, and the annual flood pulse is essential to the functioning of the Sudd. Despite the importance of the flood pulse, various hydrological interventions are planned upstream of the Sudd to increase economic benefits and food security. These will not be without consequences, in particular for wetlands where the biological productivity, biodiversity, and human livelihoods are dependent on the flood pulse and both the costs and benefits need to be carefully evaluated. Many African countries still lack regional baseline information on the temporal extent, distribution, and characteristics of wetlands, making it hard to assess the consequences of development interventions. Because of political instability in Sudan and the inaccessible nature of the Sudd, recent measurements of flooding and seasonal dynamics are inadequate. Analyses of multitemporal and multisensor remote sensing datasets are presented in this paper, in order to investigate and characterize flood pulsing within the Sudd wetland over a 12-month period. Wetland area has been mapped along with dominant components of open water and flooded vegetation at five time periods over a single year. The total area of flooding (both rain and river fed) over the 12 months was 41 334 km2, with 9176 km2 of this constituting the permanent wetland. Mean annual total evaporation is shown to be higher and with narrower distribution of values from areas of open water (1718 mm) than from flooded vegetation (1641 mm). Although the exact figures require validation against ground-based measurements, the results highlight the relative differences in inundation patterns and evaporation across the Sudd.
 
Article
Large-scale environmental, social, and economic impacts of recent weather and climate extremes are raising questions about whether the frequency and intensity of these extremes have been increasing. Here, the authors evaluate trends in climate extremes during the past half century using the U.S. High Plains as a case study. A total of eight different extreme indices and the standardized precipitation index (SPI) were evaluated using daily maximum and minimum temperature and precipitation data from 207 stations and 0.258 gridded data. The 1958-2010 time period was selected to exclude the 1950s and 2011 droughts. Results show general consistency between the station data and gridded data. The annual extreme temperature range (ETR) decreased significantly (p, 0.05) in;54% of the High Plains, with a spatial mean rate of 20.78C decade21. Decreases in ETR result primarily from increases in annual lowest temperature in;63% of the stations at a mean rate of;0.98C decade21, whereas increases in annual highest temperature were much less. Approximately 43% of the stations showed increasing warm nights (Tmin90) with a spatial mean rate of 0.5% decade21. Precipitation intensity generally did not vary significantly in most grid cells and stations. Significant decreasing trends in consecutive dry days (CDD) were restricted to 21% of the stations in the northern High Plains with a spatial mean of 20.8 days decade21. Areas experiencing severe dry periods (1-month SPI, 21.5) decreased over time from 8% to 4%. The number of dry months (SPI, 0) in each year also decreased. In summary, the ETR is decreasing and low temperatures are increasing. Precipitation extremes are generally not changing in the High Plains; however, high natural climatic variability in this semiarid region makes it difficult to assess climate extremes.
 
Article
Monthly composite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor was used to reconstruct vegetation dynamics in response to climate patterns over the period 2001-05 for North America. Results imply that plant growth over extensive land areas were closely coupled to El Niño-Southern Oscillation (ENSO) effects on regional climate. Areas strongly tied to recent (2002-03) ENSO climate effects were located mainly in northwestern Canada, interior Alaska, the northern Rocky Mountains of the United States, and throughout northern Mexico. Localized variations in precipitation were detected as the predominant controllers of.
 
Article
The authors examine five recent reanalysis products [NCEP Climate Forecast System Reanalysis (CFSR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), Japanese 25-year Reanalysis Project (JRA-25), Interim ECMWF Re-Analysis (ERA-Interim), and Arctic System Reanalysis (ASR)] for 1) trends in near-surface radiation fluxes, air temperature, and humidity, which are important indicators of changes within the Arctic Ocean and also influence sea ice and ocean conditions, and 2) fidelity of these atmospheric fields and effects for an extreme event: namely, the 2007 ice retreat. An analysis of trends over the Arctic for the past decade (2000–09) shows that reanalysis solutions have large spreads, particularly for downwelling shortwave radiation. In many cases, the differences in significant trends between the five reanalysis products are comparable to the estimated trend within a particular product. These discrepancies make it difficult to establish a consensus on likely changes occurring in the Arctic solely based on results from reanalyses fields. Regarding the 2007 ice retreat event, comparisons with remotely sensed estimates of downwelling radiation observations against these reanalysis products present an ambiguity. Remotely sensed observations from a study cited herewith suggest a large increase in downwelling summertime shortwave radiation and decrease in downwelling summertime longwave radiation from 2006 and 2007. On the contrary, the reanalysis products show only small gains in summertime shortwave radiation, if any; however, all the products show increases in downwelling longwave radiation. Thus, agreement within reanalysis fields needs to be further checked against observations to assess possible biases common to all products. © 2015, Paper 19-002; 45209 words, 7 Figures, 0 Animations, 0 Tables.
 
Article
John Wesley Powell, in the nineteenth century, introduced the notion that the 100th meridian divides the North American continent into arid western regions and humid eastern regions. This concept remains firmly fixed in the national imagination. It is reexamined in terms of climate, hydrology, vegetation, land use, settlement, and the agricultural economy. It is shown there is a stark east–west gradient in aridity roughly at the 100th meridian that is well expressed in hydroclimate, soil moisture, and “potential vegetation.” The gradient arises from atmospheric circulations and moisture transports. In winter, the arid regions west of the 100th meridian are shielded from Pacific stormrelated precipitation and are too far west to benefit from Atlantic storms. In summer, the southerly flow on the western flank of the North Atlantic subtropical high has a westerly component over the western plains, bringing air from the interior southwest, but it also brings air from the Gulf of Mexico over the eastern plains, generating a west–east moisture transport and precipitation gradient. The aridity gradient is realized in soil moisture and a west-to-east transition from shortgrass to tallgrass prairie. The gradient is sharp in terms of greater fractional coverage of developed land east of the 100th meridian than to the west. Farms are fewer but larger west of the meridian, reflective of lower land productivity. Wheat and corn cultivation preferentially occur west and east of the 100th meridian, respectively. The 100th meridian is a very real arid–humid divide in the physical climate and landscape, and this has exerted a powerful influence on human settlement and agricultural development.
 
Article
The 100th meridian bisects the Great Plains of the United States and effectively divides the continent into more arid western and less arid eastern halves and is well expressed in terms of vegetation, land hydrology, crops, and the farm economy. Here, it is considered how this arid–humid divide will change in intensity and location during the current century under rising greenhouse gases. It is first shown that state-of-the-art climate models from phase 5 of the Coupled Model Intercomparison Project generally underestimate the degree of aridity of the United States and simulate an arid–humid divide that is too diffuse. These biases are traced to excessive precipitation and evapotranspiration and inadequate blocking of eastward moisture flux by the Pacific coastal ranges and Rockies. Bias-corrected future projections are developed that modify observationally based measures of aridity by the model-projected fractional changes in aridity. Aridity increases across the United States, and the aridity gradient weakens. The main contributor to the changes is rising potential evapotranspiration, while changes in precipitation working alone increase aridity across the southern and decrease across the northern United States. The ‘‘effective 100th meridian’’ moves to the east as the century progresses. In the current farm economy, farm size and percent of county under rangelands increase and percent of cropland under corn decreases as aridity increases. Statistical relations between these quantities and the biascorrected aridity projections suggest that, all else being equal (which it will not be), adjustment to changing environmental conditions would cause farm size and rangeland area to increase across the plains and percent of cropland under corn to decrease in the northern plains as the century advances.
 
Article
Season-to-season persistence of soil moisture drought varies across North America. Such interseasonal autocorrelation can have modest skill in forecasting future conditions several months in advance. Because robust instrumental observations of precipitation span less than 100 years, the temporal stability of the relationship between seasonal moisture anomalies is uncertain. The North American Seasonal Precipitation Atlas (NASPA) is a gridded network of separately reconstructed cool-season (December–April) and warm-season (May–July) precipitation series and offers new insights on the intra-annual changes in drought for up to 2000 years. Here, the NASPA precipitation reconstructions are rescaled to represent the long-term soil moisture balance during the cool season and 3-month-long atmospheric moisture during the warm season. These rescaled seasonal reconstructions are then used to quantify the frequency, magnitude, and spatial extent of cool-season drought that was relieved or reversed during the following summer months. The adjusted seasonal reconstructions reproduce the general patterns of large-scale drought amelioration and termination in the instrumental record during the twentieth century and are used to estimate relief and reversals for the most skillfully reconstructed past 500 years. Subcontinental-to-continental-scale reversals of cool-season drought in the following warm season have been rare, but the reconstructions display periods prior to the instrumental data of increased reversal probabilities for the mid-Atlantic region and the U.S. Southwest. Drought relief at the continental scale may arise in part from macroscale ocean–atmosphere processes, whereas the smaller-scale regional reversals may reflect land surface feedbacks and stochastic variability.
 
Article
Forest degradation is the long-term and gradual reduction of canopy cover due to forest fire and unsustainable logging. A critical consequence of this process is increased atmospheric carbon emissions. Although this issue is gaining attention, forest degradation in the Brazilian Amazon has not yet been properly addressed. The claim here is that this process is not constant throughout Amazonia and varies according to colonization frontiers. Moreover, the accurate characterization of degradation requires lengthy observation periods to track gradual forest changes. The forest degradation process, the associated timeframe, spatial patterns, trajectories, and extent were characterized in the context of the Amazon frontiers of the 1990s using 28 years (1984-2011) of annual Landsat images. Given the large database and the characteristic of logging and burning, this study used data mining techniques and cell approach classification to analyze the spatial patterns and to construct associated trajectories. Multitemporal analysis indicated that forest degradation in the last two decades has caused as many interannual landscape changes as have clear-cuts. In addition, selective logging, as a major aspect of forest degradation, affected a larger amount of forest land than did forest fire. Although a large proportion of logged forest was deforested in the following years, selective logging did not always precede complete deforestation. Instead, the results indicate that logged forests were abandoned for approximately 4 years before clearance. Throughout the forest degradation process, there were no recurrent forest fires, and loggers did not revisit the forest. Forest degradation mostly occurred as a result of a single selective logging event and was associated with low-intensity forest damage.
 
Article
India responded to the COVID-19 pandemic through a three-phase nationwide lockdown: 25 March - 14 April, 15 April - 3 May and 4 - 17 May, 2020. We utilized this unique opportunity to assess the impact of restrictions on the air quality of Indian cities. We conducted comprehensive statistical assessments for the Air Quality Index (AQI) and criteria pollutant concentrations for 91 cities during the lockdown phases to the preceding seven days (pre-lockdown phase 18-24March,2020) and corresponding values from the same days of the year in 2019. Both comparisons show statistically significant country-wide mean decrease in AQI (33%), PM 2.5 (36%), PM 10 (40%), NO 2 (58%), O 3 (5%), SO 2 (25%), NH 3 (28%), and CO(60%). These reductions represent a background or the lower bound of air quality burden of industrial and transportation sectors. The northern region was most impacted by the first two phases of the lockdown, while the southern region was most affectedin the last phase. The northeastern region was least affected, followed by the eastern region which also showed an increase in O3during the lockdown. Analysis of satellite retrieved Aerosol Optical Depth (AOD) shows that effects of restrictions on particulate pollution to be variable- locally confined in some areas or having a broader impact in other regions. Anomalous behavior over the eastern region suggestsa differing role of regional societal response or meteorology. The study results have policy implications as they provide the observational background values for the industrial and transportation sector’s contribution to urban pollution.
 
Article
Land surface heterogeneity affects mesoscale interactions, including the evolution of severe convection. However, its contribution to tornadogenesis is not well known. Indiana is selected as an example to present an assessment of documented tornadoes and land surface heterogeneity to better understand the spatial distribution of tornadoes. This assessment is developed using a GIS framework taking data from 1950 to 2012 and investigates the following topics: temporal analysis, effect of ENSO, antecedent rainfall linkages, population density, land use/land cover, and topography, placing them in the context of land surface heterogeneity. Spatial analysis of tornado touchdown locations reveals several spatial relationships with regard to cities, population density, land-use classification, and topography. A total of 61% of F0–F5 tornadoes and 43% of F0–F5 tornadoes in Indiana have touched down within 1 km of urban land use and land area classified as forest, respectively, suggesting the possible role of land-use surface roughness on tornado occurrences. The correlation of tornado touchdown points to population density suggests a moderate to strong relationship. A temporal analysis of tornado days shows favored time of day, months, seasons, and active tornado years. Tornado days for 1950–2012 are compared to antecedent rainfall and ENSO phases, which both show no discernible relationship with the average number of annual tornado days. Analysis of tornado touchdowns and topography does not indicate any strong relationship between tornado touchdowns and elevation. Results suggest a possible signature of land surface heterogeneity—particularly that around urban and forested land cover—in tornado climatology.
 
Article
The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks. The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output. Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.
 
Article
Recent decades have witnessed rapid urbanization and urban population growth resulting in urban sprawl of cities. This paper analyzes the spatiotemporal dynamics of the urbanization process (using remote sensing and spatial metrics) that has occurred in Delhi, the capital city of India, which is divided into nine districts. The urban patterns and processes within the nine administrative districts of the city based on raw satellite data have been taken into consideration. Area, population, patch, edge, and shape metrics along with Pearson’s chi statistics and Shannon’s entropy have been calculated. Three types of urban patterns exist in the city: 1) highly sprawled districts, namely, West, North, North East, and East; 2) medium sprawled districts, namely, North West, South, and South West; and 3) least sprawled districts—Central and New Delhi. Relative entropy, which scales Shannon’s entropy values from 0 to 1, is calculated for the districts and time spans. Its values are 0.80, 0.92, and 0.50 from 1977 to 1993, 1993 to 2006, and 2006 to 2014, respectively, indicating a high degree of urban sprawl. Parametric and nonparametric correlation tests suggest the existence of associations between built-up density and population density, area-weighted mean patch fractal dimension (AWMPFD) and areaweighted mean shape index (AWMSI), compactness index and edge density, normalized compactness index and number of patches, and AWMPFD and built-up density.
 
Article
Potential evapotranspiration (PET), the maximum evapotranspiration rate under unlimited water supply, reflects the capacity for transpiration flow and plant primary production. Numerous models have been developed to quantify PET, but there are still large uncertainties in PET estimations. In this study, the authors conducted spatially explicit estimations of daily PET from 1981 to 2010 for eight different land-cover types on the Tibetan Plateau by applying three types of PET models including a combination model (Penman–Monteith), a radiation-based model (Priestley–Taylor), and a temperature-based model (Thornthwaite). This study found that the PET estimated by Thornthwaite model (PETT) was lower than those estimated by Priestley–Taylor (PETPT) and Penman–Monteith models (PETPM). Penman– Monteith model gave the highest estimates of PET on annual and daily scales. The mean annual PET for the whole plateau estimated by these three models varied from 675.1 to 700.5mmyr⁻¹, and daily PET varied from 1.33 to 1.92mmday⁻¹. The spatial pattern of PETT did not agree with the PETPT and PETPM, while the latter two agreed well with each other. Because of different model structures and dominant meteorological drivers, the interannual variability of PET varied significantly among the models. PETPT and PETPM showed a transition around 1993 since the dominant meteorological drivers were different before and after 1993. These disagreements among different models suggested that PET models with different algorithms should be used with caution. This study provided a validation to assist those undertaking PET estimations on the Tibetan Plateau.
 
Article
Prolonged droughts and uneven monsoons have adversely affected socioeconomic and environmental conditions of Pakistan, especially of the Punjab province. Analysis of historical (1981-2010) daily minimum and maximum temperatures from five cities in semiarid Punjab, Pakistan, was carried out to evaluate spatial and temporal patterns in thermal regimes. A total of 13 climate change indices were calculated using daily minimum and maximum temperatures and analyzed for trend using RClimDex, a program written in the statistical software package R. A nonparametric Mann-Kendall test and Sen's slope estimates were used to determine the statistical significance and magnitude of a trend, respectively. Observed trends in selected indices during 1981-2010 suggest an overall warming in the region. Over the analysis period, the regionally averaged occurrence of extreme cold (10th percentile) nights and days has decreased by 23.94 nights per decade and 20.61 days per decade, respectively. Occurrence of extreme hot (90th percentile) nights and days has increased by 4.19 nights per decade and 0.92 days per decade, respectively. The number of summer days has increased by almost 3 days per decade on average at four out of the five cities. Multan was the only city where the number of summer days has declined by 5 days per decade. Regionally averaged increase in tropical nights was 8.35 nights per decade. Regional warming will dictate increased crop water requirements in this semiarid region agriculture, which is already under water-scarce conditions, especially in the Faisalabad district, where saline groundwater is not suitable for crops.
 
Article
Trends and transitions in the growing-season normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor at 250-m resolution were analyzed for the period from 2000 to 2018 to understand recent patterns of vegetation change in ecosystems of the Arctic National Wildlife Refuge (ANWR) in Alaska. Statistical analysis of changes in the NDVI time series was conducted using the breaks for additive seasonal and trend method (BFAST). This structural change analysis indicated that NDVI breakpoints and negative 18-yr trends in vegetation greenness over the years since 2000 could be explained in large part by the impacts of severe wildfires. At least one NDVI breakpoint was detected in around 20% of the MODIS pixels within both the Porcupine River and Coleen River basins of the study area. The vast majority of vegetation cover in the ANWR Brooks Range and coastal plain ecoregions was detected with no (positive or negative) growing-season NDVI trends since the year 2000. Results suggested that most negative NDVI anomalies in the 18-yr MODIS record have been associated with early spring thawing and elevated levels of surface moisture in low-elevation drainages of the northern ANWR ecoregions.
 
Article
Droughts dramatically affect plant production of global terrestrial ecosystems. To date, quantification of this impact remains a challenge because of the complex plant physiological and biochemical processes associated with drought. Here, this study incorporates a drought index into an existing process-based terrestrial ecosystem model to estimate the drought impact on global plant production for the period 2001–10. Global Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data products are used to constrain model parameters and verify themodel algorithms. The verified model is then applied to evaluate the drought impact. The study indicates that droughts will reduce GPP by 9.8 gCm-2 month-1 during the study period. On average, drought reduces GPP by 10% globally. As a result, the global GPP decreased from 106.4 to 95.9 PgC yr-1 while the global net primary production (NPP) decreased from 54.9 to 49.9 Pg C yr-1. This study revises the estimation of the global NPP and suggests that the future quantification of the global carbon budget of terrestrial ecosystems should take the drought impact into account.
 
Article
Knowledge of the spatial distribution and temporal changes of the land surface parameters at the Three Gorges Dam (TGD) region is essential to understanding the changes of hydrological processes and climate systems possibly brought by TGD. Based on accumulated observations for years from a spaceborne passive microwave radiometer, this study presents and analyzes the spatial and temporal distribution of soil moisture in the TGD region. Major drought and flood events are identified from the satellite-derived soil moisture products. Moreover, the areas around the largest freshwater lakes of China, the Dongting and Poyang Lakes, are frequently subjected to drought events, which might be partially related to the impoundment of TGD since the year 2006. Data analysis further reveals a statistically significant drying trend in May in the middle and lower reaches of the Yangtze River over the years 2003-11. These analyses indicate that water shortage becomes a realistic challenge for the once water abundant Yangtze River region, and more considerations on the possible consequences brought by climate changes are needed for the operation of TGD.
 
Article
The 2010 eruption of Eyjafjallajökull produced volcanic ash that was mostly deposited to the south and east of the volcano, with the thickest deposits closest to the eruption vents. For months following the eruption there were numerous reports of resuspended volcanic ash made by weather observers on the ground. A saltation sensor (SENSIT) and an optical particle counter (OPC) located on the southern side of Eyjafjallajökull measured posteruptive particulate matter (PM) saltation and suspension events, some of which were also observable by satellite imagery. During the autumn/winter following the eruption, visible satellite images and the SENSIT show that PM measured by the OPC was only detected when winds had a northerly component, making the source on the slopes of Eyjafjallajökull. During the largest observed events, particles >10 μ m were suspended but measured in extremely low concentrations (<1 particle per centimeter cubed). The saltation measurements, however, show high concentrations of particles >100 μ m in size during these events. During the largest events, winds were at least 5 m s ⁻¹ with a relative humidity < 70%. Ground conditions in Iceland change quickly from unfavorable to favorable for the suspension of particles. It is hypothesized that this is due to the porosity of the surface material allowing water to filter through quickly as well as the fast drying time of surface material. The high moisture content of the atmosphere and the ground do not appear to be a deterrent for large PM events to occur in Iceland.
 
Article
This study considers eastern Antilles (11°-18°N, 64°-57°W) weather and climate interactions in the context of the 2013 Christmas storm. This unseasonal event caused flash flooding in Grenada, St. Vincent, St. Lucia, Martinique, and Dominica from 24 to 25 December 2013, despite having winds ,15ms-1. The meteorological scenario and short-term forecasts are analyzed. At the low level, a convective wave propagated westward while near-equatorial upper westerly winds surged with eastward passage of a trough. The combination of tropical moisture, cyclonic vorticity, and uplift resulted in rain rates greater than 30mmh-1 and many stations reporting 200 mm. Although forecast rainfall was low and a few hours late, weather services posted flood warnings in advance. At the climate scale, the fresh Orinoco River plume brought into the region by the North Brazil Current together with solar radiation greater than 200Wm22, enabled sea temperatures to reach 28°C, and supplied convective available potential energy greater than 1800 J kg-1. Climate change model simulations are compared with reference fields and trends are analyzed in the eastern Antilles. While temperatures are set to increase, the frequency of flood events appears to decline in the future.
 
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The selection of statistical methods to evaluate data depends on study questions and characteristics of available data. In climate science, some methods are more popularly used than others; however, the use of applicable alternative methods does not invalidate study findings. Regardless of limitations, some methods like Pearson ordinary correlation are widely used in all sciences including climate and by scientists at government agencies like NOAA and the USGS. In addition, the use of the robust Student’s t test is valid for near-Gaussian distributions with high sample numbers, since it is resistant to data distribution inconsistencies. We wish to put in context the citation about our article and clarify the methods and justification for using them and to educate readers about the use of some conventional statistical tools and tests.
 
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Land-use land-cover change (LULCC) has become an important topic of research for the central United States because of the extensive conversion of the natural prairie into agricultural land, especially in the northern Great Plains. As a result, shifts in the natural climate (minimum/maximum temperature, precipitation, etc.) across the north-central United States have been observed, as noted within the Fourth National Climate Assessment (NCA4) report. Thus, it is necessary to understand how further LULCC will affect the near-surface atmosphere, the lower troposphere, and the planetary boundary layer (PBL) atmosphere over this region. The goal of this work was to investigate the utility of a new future land-use land-cover (LULC) dataset within the Weather Research and Forecasting (WRF) modeling system. The present study utilizes a modeled future land-use dataset developed by the Forecasting Scenarios of Land-Use Change (FORE-SCE) model to investigate the influence of future (2050) land use on a simulated PBL development within the WRF Model. Three primary areas of LULCC were identified within the FORE-SCE future LULC dataset across Nebraska and South Dakota. Variations in LULC between the 2005 LULC control simulation and four FORE-SCE simulations affected near-surface temperature (0.5°–1°C) and specific humidity (0.3–0.5 g kg ⁻¹ ). The differences noted in the temperature and moisture fields affected the development of the simulated PBL, leading to variations in PBL height and convective available potential energy. Overall, utilizing the FORE-SCE dataset within WRF produced notable differences relative to the control simulation over areas of LULCC represented in the FORE-SCE dataset.
 
Top-cited authors
Ruth S. Defries
  • Columbia University
Mark L Carroll
C. Dimiceli
  • University of Maryland, College Park
J. R. G. Townshend
  • University of Maryland, College Park
Marshall Shepherd
  • University of Georgia