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NASA NTRS2024

Characterizing the 2019-2021 Drought in La Plata River Basin With GLDAS and SMAP

Study region The La Plata River Basin (LPRB) is an area of interest, as there was a significant drought event from 2019 to 2021. With the LPRB being the second largest river basin in South America, this drought affected all aspects of life for over 100 million people who inhabit this area. Study focus In this study, we utilized satellite and model datasets to examine spatial and temporal variability of hydrological anomalies throughout the basin before and during the drought event. These variable anomalies, such as precipitation and groundwater, are derived from the Global Land Data Assimilation System (GLDAS). Additionally, the Soil Moisture Active Passive (SMAP) observations were used in the spatial and temporal analysis of the drought. The water loss was calculated using the Mann-Kendall test to assess the changes in anomalies for the terrestrial water storage throughout the basin and subbasins. New hydrological insights for the region The main insight from this study is the agreement of the GLDAS anomalies with the SMAP data throughout the drought. The variable anomalies all decreased and showed alignment with the downscaled 1 km SMAP which shows alignment with the trends from in-situ observations. It was also found that the Upper Parana subbasin lost the most water over the drought period. These products improve understanding of the spatial variability within the entire basin and facilitate understanding of droughts and resources to assist in the future management of water resources.

La Plata Basin↗

DOE OSTI2023

Impact of Drought on Ecohydrology of Southern California Grassland and Shrubland

Abstract Through their rooting profiles and water demands, plants affect the distribution of water in the soil profile. Simultaneously, soil water content controls plant development and interactions within and between plant communities. These plant-soil water feedbacks might vary across plant communities with different rooting depths and species composition. In semiarid environments, understanding these differences will be essential to predict how ecosystems will respond to drought, which may become more frequent and severe with climate change. In this study, we tested how plant-soil water feedbacks responded to drought in two contrasting ecosystem types—grassland and shrubland—in the coastal foothills of southern California. During years 5–8 of an ongoing precipitation manipulation experiment, we measured changes in plant communities and soil moisture up to 2 m depth. We observed different water use patterns in grassland and shrubland communities with distinct plant functional types and water use strategies. Drought treatment did not affect perennial, deep-rooted shrubs because they could access deep soil water pools. However, mid-rooted shrubs were sensitive to drought and experienced decreased productivity and die-off. As a result, water content actually increased with drought at soil depths from 50–150 cm. In grassland, biomass production by annual species, including annual grasses and forbs, declined with drought, resulting in lower water uptake from the surface soil layer. An opportunistic “live fast, die young“ life strategy allowed these species to recover quickly once water availability increased. Our results show how drought interacts with plant community composition to affect the soil water balance of semiarid ecosystems, information that could be integrated into global scale models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Exploring drought-responsive crucial genes in Sorghum

Drought severely affects global food production. Sorghum is a typical drought-resistant model crop. Based on RNA-seq data for Sorghum with multiple time points and the gray correlation coefficient, this paper firstly selects candidate genes via mean variance test and constructs weighted gene differential co-expression networks (WGDCNs); then, based on guilt-by-rewiring principle, the WGDCNs and the hidden Markov random field model, drought-responsive crucial genes are identified for five developmental stages respectively. Enrichment and sequence alignment analysis reveal that the screened genes may play critical functional roles in drought responsiveness. A multilayer differential co-expression network for the screened genes reveals that Sorghum is very sensitive to pre-flowering drought. Furthermore, a crucial gene regulatory module is established, which regulates drought responsiveness via plant hormone signal transduction, MAPK cascades, and transcriptional regulations. The proposed method can well excavate crucial genes through RNA-seq data, which have implications in breeding of new varieties with improved drought tolerance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Identification of beneficial and detrimental bacteria impacting sorghum responses to drought using multi-scale and multi-system microbiome comparisons

Abstract Drought is a major abiotic stress limiting agricultural productivity. Previous field-level experiments have demonstrated that drought decreases microbiome diversity in the root and rhizosphere. How these changes ultimately affect plant health remains elusive. Toward this end, we combined reductionist, transitional and ecological approaches, applied to the staple cereal crop sorghum to identify key root-associated microbes that robustly affect drought-stressed plant phenotypes. Fifty-three Arabidopsis-associated bacteria were applied to sorghum seeds and their effect on root growth was monitored. Two Arthrobacter strains caused root growth inhibition (RGI) in Arabidopsis and sorghum. In the context of synthetic communities, Variovorax strains were able to protect plants from Arthrobacter-caused RGI. As a transitional system, high-throughput phenotyping was used to test the synthetic communities. During drought stress, plants colonized by Arthrobacter had reduced growth and leaf water content. Plants colonized by both Arthrobacter and Variovorax performed as well or better than control plants. In parallel, we performed a field trial wherein sorghum was evaluated across drought conditions. By incorporating data on soil properties into the microbiome analysis, we accounted for experimental noise with a novel method and were able to observe the negative correlation between the abundance of Arthrobacter and plant growth. Having validated this approach, we cross-referenced datasets from the high-throughput phenotyping and field experiments and report a list of bacteria with high confidence that positively associated with plant growth under drought stress. In conclusion, a three-tiered experimental system successfully spanned the lab-to-field gap and identified beneficial and deleterious bacterial strains for sorghum under drought.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Increasing impacts of extreme droughts on vegetation productivity under climate change

Terrestrial gross primary production (GPP) is the basis of food production and vegetation growth globally1 and plays a critical role in regulating atmospheric CO2 through its impact on ecosystem carbon balance. Even though higher CO2 concentrations in future decades can increase GPP2, low soil water availability, heat stress and disturbances associated with droughts could reduce the benefits of such CO2 fertilization. Here we analysed outputs of 13 Earth system models to show an increasingly stronger impact on GPP by extreme droughts than by mild and moderate droughts over the twenty-first century. Due to a dramatic increase in the frequency of extreme droughts, the magnitude of globally averaged reductions in GPP associated with extreme droughts was projected to be nearly tripled by the last quarter of this century (2075–2099) relative to that of the historical period (1850–1999) under both high and intermediate GHG emission scenarios. By contrast, the magnitude of GPP reduction associated with mild and moderate droughts was not projected to increase substantially. Our analysis indicates a high risk of extreme droughts to the global carbon cycle with atmospheric warming; however, this risk can be potentially mitigated by positive anomalies of GPP associated with favourable environmental conditions.

Xu, Chonggang↗

DOE OSTI2023

Increased drought and extreme events over continental United States under high emissions scenario

The frequency, severity, and extent of climate extremes in future will have an impact on human well-being, ecosystems, and the effectiveness of emissions mitigation and carbon sequestration strategies. The specific objectives of this study were to downscale climate data for US weather stations and analyze future trends in meteorological drought and temperature extremes over continental United States (CONUS). We used data from 4161 weather stations across the CONUS to downscale future precipitation projections from three Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase Six (CMIP6), specifically for the high emission scenario SSP5 8.5. Comparing historic observations with climate model projections revealed a significant bias in total annual precipitation days and total precipitation amounts. The average number of annual precipitation days across CONUS was projected to be 205 ± 26, 184 ± 33, and 181 ± 25 days in the BCC, CanESM, and UKESM models, respectively, compared to 91 ± 24 days in the observed data. Analyzing the duration of drought periods in different ecoregions of CONUS showed an increase in the number of drought months in the future (2023–2052) compared to the historical period (1989–2018). The analysis of precipitation and temperature changes in various ecoregions of CONUS revealed an increased frequency of droughts in the future, along with longer durations of warm spells. Eastern temperate forests and the Great Plains, which encompass the majority of CONUS agricultural lands, are projected to experience higher drought counts in the future. Drought projections show an increasing trend in future drought occurrences due to rising temperatures and changes in precipitation patterns. Our high-resolution climate projections can inform policy makers about the hotspots and their anticipated future trajectories.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Time for a drought experiment: Do you know your plants’ water status?

Abstract Drought stress is an increasing concern because of climate change and increasing demands on water for agriculture. There are still many unknowns about how plants sense and respond to water limitation, including which genes and cellular mechanisms are impactful for ecology and crop improvement in drought-prone environments. A better understanding of plant drought resistance will require integration of several research disciplines. A common set of parameters to describe plant water status and quantify drought severity can enhance data interpretation and research integration across the research disciplines involved in understanding drought resistance and would be especially useful in integrating the flood of genomic data being generated in drought studies. Water potential (ψw) is a physical measure of the free energy status of water that, along with related physiological measurements, allows unambiguous description of plant water status that can apply across various soil types and environmental conditions. ψw and related physiological parameters can be measured with relatively modest investment in equipment and effort. Thus, we propose that increased use of ψw as a fundamental descriptor of plant water status can enhance the insight gained from many drought-related experiments and facilitate data integration and sharing across laboratories and research disciplines.

Juenger, Thomas E. (ORCID:0000000195509288)↗

NASA NTRS1999

The Impact of Surface Boundary Forcing on Simulation of the 1998 Summer Drought Over the US Midwest Using Factor Separation Technique

The factor separation (FS) technique has been utilized to evaluate quantitatively the impact of surface boundary forcings on simulation of the 1988 summer drought over the Midwestern part of the U.S. The four surface boundary forcings used are: (1)Sea Surface Temperature (SST), (2) soil moisture, (3) snow cover, and (4) sea ice. The Goddard Earth Observing System(GEOS) General Circulation Model (GCM) is used to simulate the 1988 U.S. drought. A series of sixteen simulations are performed with climatological and real 1988 surface boundary conditions. The major single and mutual synergistic factors/impacts are analyzed. The results show that SST and soil moisture are the major single pro-drought factors. The couple synergistic effect of SST and soil moisture is the major anti-drought factor. The triple synergistic impact of SST, soil moisture, and snow cover is the strongest pro-drought impact and is, therefore, the main contributor to the generation of the drought. The impact of the snow cover and sea ice anomalies for June 1988 on the drought is significant only when combined with the SST and soil moisture anomalies.

Stein, Uri↗

NASA NTRS2010

Integrating Enhanced Grace Terrestrial Water Storage Data Into the U.S. and North American Drought Monitors

NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations nf the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including ground water. The U.S. and North American Drought Monitors are two of the premier drought monitoring products available to decision-makers for assessing and minimizing drought impacts, but they rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors hy filling this observational gap. Horizontal, vertical and temporal disaggregation of the coarse-resolution GRACE TWS data has been accomplished by assimilating GRACE TWS anomalies into the Catchment Land Surface Model using ensemble Kalman smoother. The Drought Monitors combine several short-term and long-term drought indices and indicators expressed in percentiles as a reference to their historical frequency of occurrence for the location and time of year in question. To be consistent, we are in the process of generating a climatology of estimated soil moisture and ground water based on m 60-year Catchment model simulation which will subsequently be used to convert seven years of GRACE assimilated fields into soil moisture and groundwater percentiles. for systematic incorporation into the objective blends that constitute Drought Monitor baselines. At this stage we provide a preliminary evaluation of GRACE assimilated Catchment model output against independent datasets including soil moisture observations from Aqua AMSR-E and groundwater level observations from the U.S. Geological Survey's Groundwater Climate Response Network.

Housborg, Rasmus↗

NASA NTRS2012

Drought Monitoring for 3 North American Case Studies Based on the North American Land Data Assimilation System (NLDAS)

Both NLDAS Phase 1 (1996-2007) and Phase 2 (1979-present) datasets have been evaluated against in situ observational datasets, and NLDAS forcings and outputs are used by a wide variety of users. Drought indices and drought monitoring from NLDAS were recently examined by Mo et al. (2010) and Sheffield et al. (2010). In this poster, we will present results analyzing NLDAS Phase 2 forcings and outputs for 3 North American Case studies being analyzed as part of the NOAA MAPP Drought Task Force: (1) Western US drought (1998- 2004); (2) plains/southeast US drought (2006-2007); and (3) Current Texas-Mexico drought (2011-). We will examine percentiles of soil moisture consistent with the NLDAS drought monitor.

Peters-Lidard, Christa D.↗

NASA NTRS2012

Workshop on the Development of an Experimental Global Drought Information System (GDIS): Overview of Workshop Goals

Among the key recommendations of a recent WCRP Workshop on Drought Predictability and Prediction in a Changing Climate is the development of an experimental global drought information system (GDIS). The timeliness of such an effort is evidenced by the wide aITay of relevant ongoing national and international (as well as regional and continental scale) efforts to provide drought information, including the US and North American drought monitors, and various integrating activities such as GEO and the Global Drought Portal. The workshop will review current capabilities and needs, and focus on the steps necessary to develop a GDIS that will build upon the extensive worldwide investments that have already been made in developing drought monitoring (including new space-based observations), drought risk management, and climate prediction capahilities.

Schubert, Siegfried↗

NASA NTRS2015

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles describing future climate conditions. Component 3: Assimilation using LSMs CHIRPS rainfall observations (component 1) and bootstrapped forecast ensembles (component 2) can be combined using LSMs to predict soil moisture deficits. We evaluate the skill such a system in East Africa, and demonstrate results for 2013.

Funk, Chris↗

NASA NTRS2015

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

Funk, Chris↗

NASA NTRS2016

Amazon Forests Response to Droughts: A Perspective from the MAIAC Product

Amazon forests experienced two severe droughts at the beginning of the 21st century: one in 2005 and the other in 2010. How Amazon forests responded to these droughts is critical for the future of the Earth's climate system. It is only possible to assess Amazon forests' response to the droughts in large areal extent through satellite remote sensing. Here, we used the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI) data to assess Amazon forests' response to droughts, and compared the results with those from the standard (Collection 5 and Collection 6) MODIS VI data. Overall, the MAIAC data reveal more realistic Amazon forests inter-annual greenness dynamics than the standard MODIS data. Our results from the MAIAC data suggest that: (1) the droughts decreased the greenness (i.e., photosynthetic activity) of Amazon forests; (2) the Amazon wet season precipitation reduction induced by El Niño events could also lead to reduced photosynthetic activity of Amazon forests; and (3) in the subsequent year after the water stresses, the greenness of Amazon forests recovered from the preceding decreases. However, as previous research shows droughts cause Amazon forests to reduce investment in tissue maintenance and defense, it is not clear whether the photosynthesis of Amazon forests will continue to recover after future water stresses, because of the accumulated damages caused by the droughts.

remote sensing↗

NASA NTRS2018

Simulation and Prediction of Warm Season Drought in North America

This presentation presents our recent work on model simulation and prediction of warm season drought in North America. The emphasis will be on the contribution from the leading modes of subseasonal atmospheric circulation variability, which are often present in the form of stationary Rossby waves. Here we take advantage of the results from observations, reanalyses, and simulations and reforecasts performed using the NASA Goddard Earth Observing System (GEOS-5) atmospheric and coupled General Circulation Model (GCM). Our results show that stationary Rossby waves play a key role in Northern Hemisphere (NH) atmospheric circulation and surface meteorology variability on subseasonal timescales. In particular, such waves have been crucial to the development of recent short-term warm season heat waves and droughts over North America (e.g. the 1988, 1998, and 2012 summer droughts) and northern Eurasia (e.g., the 2003 summer heat wave over Europe and the 2010 summer drought and heat wave over Russia). Through an investigation of the physical processes by which these waves lead to the development of warm season drought in North America, it is further found that these waves can serve as a potential source of drought predictability. In order to properly represent their effect and exploit this source of predictability, a model needs to correctly simulate the Northern Hemisphere (NH) mean jet streams and be able to predict the sources of these waves. Given the NASA GEOS-5 AGCM deficiency in simulating the NH jet streams and tropical convection during boreal summer, an approach has been developed to artificially remove much of model mean biases, which leads to considerable improvement in model simulation and prediction of stationary Rossby waves and drought development in North America. Our study points to the need to identify key model biases that limit model simulation and prediction of regional climate extremes, and diagnose the origin of these biases so as to inform modeling group for model improvement.

Rossby Waves↗

NASA NTRS2019

Land–Atmosphere Feedbacks Exacerbate Concurrent Soil Drought and Atmospheric Aridity

Compound extremes such as cooccurring soil drought (low soil moisture) and atmospheric aridity (high vapor pressure deficit) can be disastrous for natural and societal systems. Soil drought and atmospheric aridity are 2 main physiological stressors driving widespread vegetation mortality and reduced terrestrial carbon uptake. Here, we empirically demonstrate that strong negative coupling between soil moisture and vapor pressure deficit occurs globally, indicating high probability of cooccurring soil drought and atmospheric aridity. Using the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we further show that concurrent soil drought and atmospheric aridity are greatly exacerbated by land– atmosphere feedbacks. The feedback of soil drought on the atmosphere is largely responsible for enabling atmospheric aridity extremes. In addition, the soil moisture–precipitation feedback acts to amplify precipitation and soil moisture deficits in most regions. CMIP5 models further show that the frequency of concurrent soil drought and atmospheric aridity enhanced by land–atmosphere feedbacks is projected to increase in the 21st century. Importantly, land– atmosphere feedbacks will greatly increase the intensity of both soil drought and atmospheric aridity beyond that expected from changes in mean climate alone.

Compound extreme events↗

NASA NTRS2019

Increasing Impacts of Extreme Droughts on Vegetation Productivity Under Climate Change

Terrestrial gross primary production (GPP) is the basis of vegetation growth and food production globally and plays a critical role in regulating atmospheric CO2 through its impact on ecosystem carbon balance. Even though higher CO2 concentrations in future decades can increase GPP, low soil water availability, heat stress and disturbances associated with droughts could reduce the benefits of such CO2 fertilization. Here we analysed outputs of 13 Earth system models to show an increasingly stronger impact on GPP by extreme droughts than by mild and moderate droughts over the twenty-first century. Due to a dramatic increase in the frequency of extreme droughts, the magnitude of globally averaged reductions in GPP associated with extreme droughts was projected to be nearly tripled by the last quarter of this century (2075-2099) relative to that of the historical period (1850-1999) under both high and intermediate GHG emission scenarios. By contrast, the magnitude of GPP reductions associated with mild and moderate droughts was not projected to increase substantially. Our analysis indicates a high risk of extreme droughts to the global carbon cycle with atmospheric warming; however, this risk can be potentially mitigated by positive anomalies of GPP associated with favourable environmental conditions.

Xu, Chonggang↗

NASA NTRS2020

Groundwater Drought: Environmental Controls and Monitoring

Arising from a long-term deficit of precipitation, groundwater drought often lags meteorological drought by months to years, depending on climate and subsurface hydrogeological conditions. Due to the paucity of in situ groundwater data in many parts of the world, global monitoring of groundwater storage variations and drought may be best achieved using satellite observations and/or groundwater time series simulated by hydrological models. The Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow On (GRACE-FO) missions have greatly benefitted the modeling and monitoring of groundwater storage changes and drought at the global scale. In this chapter, we first review environmental controls on the temporal variability of groundwater using in situ data. We then describe an approach that infuses GRACE and GRACE-FO observations into a land surface model for assessing groundwater storage changes and drought globally. We also discuss characteristics of simulated groundwater drought and the limitations of current groundwater drought monitoring approaches.

Bailing Li↗