SEARCH · Search NASA

Results for “extreme drought”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts

As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human–water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023, https://doi.org/10.5880/GFZ.4.4.2023.001).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

DeepClimGAN: A High-Resolution Climate Data Generator

Earth system models (ESMs), which simulate the physics and chemistry of the global atmosphere, land, and ocean, are often used to generate future projections of climate change scenarios. These models are far too computationally inten- sive to run repeatedly, but limited sets of runs are insufficient for some important applications, like adequately sampling distribution tails to characterize extreme events. As a com- promise, emulators are substantially less expensive but may not have all of the complexity of an ESM. Here we demon- strate the use of a conditional generative adversarial network (GAN) to act as an ESM emulator. In doing so, we gain the ability to produce daily weather data that is consistent with what ESM might output over any chosen scenario. In particular, the GAN is aimed at representing a joint proba- bility distribution over space, time, and climate variables, enabling the study of correlated extreme events, such as floods, droughts, or heatwaves.

Extreme events, Machine Learning, deep learning↗

DOE OSTI2022

Using Image Processing Techniques to Identify and Quantify Spatiotemporal Carbon Cycle Extremes

Rising atmospheric carbon dioxide due to human activities through fossil fuel emissions and land use changes have increased climate extremes such as heat waves and droughts that have led to and are expected to increase the occurrence of carbon cycle extremes. Carbon cycle extremes represent large anomalies in the carbon cycle that are associated with gains or losses in carbon uptake. Carbon cycle extremes could be continuous in space and time and cross political boundaries. Here, we present a methodology to identify large spatiotemporal extremes (STEs) in the terrestrial carbon cycle using image processing tools for feature detection. We characterized the STE events based on neighborhood structures that are three-dimensional adjacency matrices for the detection of spatiotemporal manifolds of carbon cycle extremes. We found that the area affected and carbon loss during negative carbon cycle extremes were consistent with continuous neighborhood structures. In the gross primary production data we used, 100 carbon cycle STEs accounted for more than 75% of all the negative carbon cycle extremes. This paper presents a comparative analysis of the magnitude of carbon cycle STEs and attribution of those STEs to climate drivers as a function of neighborhood structures for two observational datasets and an Earth system model simulation.

Sharma, Bharat↗

DOE OSTI2025

Recent Accelerated Decadal Shift in Winter North American Temperature Patterns Under Pacific‐Atlantic Decadal Variability

Global warming and internal climate variability have changed winter temperature extreme regimes in North America, affecting droughts and wildfires in the western United States. However, how internal climate variability influences North American winter temperature extreme patterns remains poorly understood. Here, we demonstrate that the recent winter North American surface air temperature (SAT) exhibits an accelerated decadal alternation between Warm West-Cold East (WWCE) and Cold West-Warm East (CWWE) dipoles because their variations show shorter decadal periods during 1990–2022 than during 1950–1989 and are regulated by the Pacific Decadal Oscillation (PDO) variability. While the winter WWCE dipole mainly linked to North Pacific blocking events exhibited a smaller mean amplitude during 1990–2022 than 1950–1989 due to the weakened positive PDO phase during 1990–2022 under the positive phase of the Atlantic Multidecadal Oscillation (AMO), the winter CWWE showed a larger mean amplitude during 1990–2022 due to the stronger negative PDO phase than during 1950–1989. Our results further suggest that the recent rapid decadal shift of North American winter temperatures is primarily attributed to the PDO variability likely due to anthropogenic warming under the positive AMO.

Atlantic Multidecadal Oscillation↗

DOE OSTI2025

Projected evolution of droughts and human exposure in the contiguous United States under SSP5-8.5: a regional downscaling perspective

The increasingly unpredictable and extreme weather patterns under a warming climate underscore the urgency of accurate regional assessments of future drought risk. This study evaluates the projected drought evolution in the contiguous United States under the high-emission shared socioeconomic pathway 5–8.5 climate scenario for the coming decades. Using a multi-model ensemble of six Coupled Model Intercomparison Project Phase 6 global climate models combined with dynamical downscaling techniques, we analyzed near-term (2020–2039) and mid-term (2040–2059) drought patterns using the self-calibrating palmer drought severity index (ScPDSI), the standardized precipitation index (SPI-12), and the Standardized Precipitation-Evapotranspiration Index (SPEI-12). Results reveal a widespread increase in abnormally dry (D0) and moderate drought (D1) conditions, particularly in urban areas, while severe (D2), extreme (D3), and exceptional (D4) droughts are expected to become less common in many regions. Meanwhile, persistent and intensifying droughts are projected in the western and southwestern U.S., driven by long-term soil moisture deficits. The ScPDSI projects that 1.1 million urban residents will be affected by D0 conditions in 2050, while SPI-12 suggests a decrease in the total affected populations after 2040. ScPDSI indicates prolonged droughts in the West, and SPI-12 captures transient variability. Although the total drought-exposed population is expected to decrease, urban areas will continue to bear a greater burden, particularly for mild droughts (D0, D1). These findings highlight a shift toward more frequent mild droughts, fewer severe droughts, and persistent drying in the Southwest, emphasizing the need for region-specific adaptation strategies.

CMIP6↗

NASA NTRSDate not supplied

Beginning and Ending Droughts in a Warmer World

Droughts are typically caused by below-normal precipitation and typically terminate in response to high precipitation. In many regions, soil moisture is projected to decrease in a warmer world. At the same time, changes in both mean and extreme precipitation are expected as the global mean temperature increases. How will these precipitation changes interact with soil moisture changes to affect drought onset and termination? In this study, we use climate model projections from Phase Six of the Coupled Model Intercomparison Project (CMIP6) to investigate how changes in mean precipitation affect soil moisture drought in the context of future warming in the Mediterranean and Western North America. We show that the same precipitation deficits at a global warming level of 2 degrees Celsius increase the likelihood of both moderate and severe drought compared to the pre-industrial baseline. Further, we evaluate the effectiveness of a given precipitation anomaly to terminate a soil moisture drought under different warming levels. These analyses offer a better understanding of the cascading impacts of, and relationships between, precipitation, precipitation extremes, and drought termination under warmer global temperatures.

Drought↗

NASA NTRSDate not supplied

Beginning and Ending Droughts in a Warmer World

Drought↗

DOE OSTI2020

Integrating field observations and process-based modeling to predict watershed water quality under environmental perturbations

Watersheds play a critical role in supplying water resources needed for human use and ecosystem health. Understanding and predicting how, when, and where changes in the quantity and quality of water resources occur under different environmental stresses including extreme events is crucial for sustainable management of water resources under a changing environment. However, few studies have attempted to quantify or identify the factors and process interactions controlling the impact of extreme events across water-shed systems. Only few large-scale studies include coordinated monitoring and modeling efforts, which limits our ability to assess the large-scale impact of extreme events on water supply and quality. Methods are lacking to propagate uncertainty in process understanding through an integrated hydro-biogeochemical model framework and evaluate its importance, thus failing to take full advantage of the information potentially available through transformative advances in characterization technologies from high-resolution mass spectrometry to airborne and satellite-based remote sensing. There are consequent risks to our nations water security and to human and ecosystem health that may become exacerbated with the increasing frequency of extreme events that is projected for the coming decades. This paper reviews the current status of watershed science for both water quantity and quality and identifies critical gaps in our current knowledge and modeling capability in addressing the emergent needs in predicting watershed hydrologic and biogeochemical responses (i.e., water quantity and quality) under natural and anthropogenic perturbations. We highlight the need to (1) understand how environmental perturbations including extreme events like floods and droughts propagate through watershed systems and assess their short- and long-term impacts on watershed biogeochemistry, water quality and their recovery pathways; (2) develop and improve a watershed water quality model that reflects the state of scientific understanding gained from observations; and (3) construct a data-model fusion system for watershed characterization, process identification, and mechanistic model parameterization. A large base of modeling, monitoring and data capabilities have been built by various federal government agencies given the relevance of water to their critical missions. An emerging need is to build an integrated national capability for watershed water availability and quality that can address water-related missions across multiple federal agencies.

13 HYDRO ENERGY↗

DOE OSTI2023

Editorial: Advances in observations and modeling of snow, forest-snow processes and snow hydrology

Seasonal snowpack plays a pivotal role in the regional water cycle. In Western mountainous regions, where precipitation predominantly occurs as snow during winter and is limited in the summer months when water demand peaks, snowpack serves as a critical water source essential for sustaining water supply, ecosystems, agriculture, and industries. Additionally, snowpack dynamically influences extreme events, such as floods, droughts, and wildfires, through intricate land-atmosphere feedback. Nevertheless, significant knowledge gaps persist within this field due to data limitations and the complexity of the physics involved in modeling snow and snow hydrology (i.e., snow acts as a critical upstream hydrological process). Here, this research topic presents a collection of manuscripts that address some of these important research gaps.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Increased Cuticle Waxes by Overexpression of WSD1 Improves Osmotic Stress Tolerance in Arabidopsis thaliana and Camelina sativa

To ensure global food security under the changing climate, there is a strong need for developing ‘climate resilient crops’ that can thrive and produce better yields under extreme environmental conditions such as drought, salinity, and high temperature. To enhance plant productivity under the adverse conditions, we constitutively overexpressed a bifunctional wax synthase/acyl-CoA:diacylglycerol acyltransferase (WSD1) gene, which plays a critical role in wax ester synthesis in Arabidopsis stem and leaf tissues. The qRT-PCR analysis showed a strong upregulation of WSD1 transcripts by mannitol, NaCl, and abscisic acid (ABA) treatments, particularly in Arabidopsis thaliana shoots. Gas chromatography and electron microscopy analyses of Arabidopsis seedlings overexpressing WSD1 showed higher deposition of epicuticular wax crystals and increased leaf and stem wax loading in WSD1 transgenics compared to wildtype (WT) plants. WSD1 transgenics exhibited enhanced tolerance to ABA, mannitol, drought and salinity, which suggested new physiological roles for WSD1 in stress response aside from its wax synthase activity. Transgenic plants were able to recover from drought and salinity better than the WT plants. Furthermore, transgenics showed reduced cuticular transpirational rates and cuticle permeability, as well as less chlorophyll leaching than the WT. The knowledge from Arabidopsis was translated to the oilseed crop Camelina sativa (L.) Crantz. Similar to Arabidopsis, transgenic Camelina lines overexpressing WSD1 also showed enhanced tolerance to drought stress. Our results clearly show that the manipulation of cuticular waxes will be advantageous for enhancing plant productivity under a changing climate.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Comparison of Deterministic and Statistical Models for Water Quality Compliance Forecasting in the San Joaquin River Basin, California

Model selection for water quality forecasting depends on many factors including analyst expertise and cost, stakeholder involvement and expected performance. Water quality forecasting in arid river basins is especially challenging given the importance of protecting beneficial uses in these environments and the livelihood of agricultural communities. In the agriculture-dominated San Joaquin River Basin of California, real-time salinity management (RTSM) is a state-sanctioned program that helps to maximize allowable salt export while protecting existing basin beneficial uses of water supply. The RTSM strategy supplants the federal total maximum daily load (TMDL) approach that could impose fines associated with exceedances of monthly and annual salt load allocations of up to $1 million per year based on average year hydrology and salt load export limits. The essential components of the current program include the establishment of telemetered sensor networks, a web-based information system for sharing data, a basin-scale salt load assimilative capacity forecasting model and institutional entities tasked with performing weekly forecasts of river salt assimilative capacity and scheduling west-side drainage export of salt loads. Web-based information portals have been developed to share model input data and salt assimilative capacity forecasts together with increasing stakeholder awareness and involvement in water quality resource management activities in the river basin. Two modeling approaches have been developed simultaneously. The first relies on a statistical analysis of the relationship between flow and salt concentration at three compliance monitoring sites and the use of these regression relationships for forecasting. The second salt load forecasting approach is a customized application of the Watershed Analysis Risk Management Framework (WARMF), a watershed water quality simulation model that has been configured to estimate daily river salt assimilative capacity and to provide decision support for real-time salinity management at the watershed level. Analysis of the results from both model-based forecasting approaches over a period of five years shows that the regression-based forecasting model, run daily Monday to Friday each week, provided marginally better performance. However, the regression-based forecasting model assumes the same general relationship between flow and salinity which breaks down during extreme weather events such as droughts when water allocation cutbacks among stakeholders are not evenly distributed across the basin. A recent test case shows the utility of both models in dealing with an exceedance event at one compliance monitoring site recently introduced in 2020.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): organization and experimental design

Subseasonal-to-seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging, but also has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction” (LS4P) as the first international grass-roots effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land–atmosphere interactions. LS4P focuses on process understanding and predictability, and hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than 40 groups worldwide have participated in this effort, including 21 Earth system models, 9 regional climate models, and 7 data groups.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1981

Recent progress in exobiology and planetary biology

Recent work in the fields of exobiology, the study of the possible characteristics of extraterrestrial life, and planetary biology, the study of life forms as a function of planetary conditions, is reviewed. Searches conducted for life on Mars by the Viking Landers and on Titan by Voyager 1 are considered, and the origin of life on earth is considered in relation to the question of the inorganic trace elements in living systems that are required for life. The question of the origin of terrestrial life from spores carried through the interstellar medium is examined, and the unlikelihood of the survival of such spores except within meteorites or dust particles is pointed out. Studies of organic molecules present in the interstellar medium are indicated as evidence that the conditions necessary for the formation of life can exist in various locations throughout the universe. Investigations of the molecular evolution of life on earth and of life under extreme conditions of heat, cold, drought and ultraviolet radiation, and of the organic compounds found in meteorites and comets are also discussed. The importance of a mechanism of heredity, such as terrestrial DNA, to the evolution of terrestrial and possible extraterrestrial life is pointed out.

Jukes, T. H.↗

NASA NTRS2001

The Bi-Modal Pattern of the Summer Circulation Over South America

Submonthly variations in warm-season (January-February) precipitation over South America, in special over the Amazon basin, central southwest Brazil, north Argentina, and Paraguay are shown to be strongly linked to variations in the moisture entering the continent from the Atlantic ocean. Two distinct regimes of lower tropospheric winds (westerlies and easterlies) were observed in Rondonia during the Wet Season Atmospheric Mesoscale Campaign (WETAMC) component of the Large Scale Atmosphere-Biosphere Experiment in Amazonia (LBA) and the Tropical Rainfall Measuring Mission (TRMM) field campaign. The westerly (easterly) winds were associated with the strong (weak) convective activity over the South Atlantic Convergence Zone (SACZ). The whole period of this study (January-February) was divided into SACZ and NSACZ (No SACZ) events. The vertically integrated moisture fluxes over the Amazon and Prata basin from the National Aeronautics and Space Administration/Goddard Data Assimilation Office (NASA/DAO) assimilation show that during SACZ (NSACZ) event strong (weak) convergence occurred over the Amazon basin with divergence (convergence) over the Prata basin. Submonthly variations in the SACZ also can be linked to extreme climate anomalies such as droughts or flooding conditions over the Amazon and Prata basin.

Herdies, Dirceu Luis↗

NASA NTRS2018

Climate Change Impacts on Agriculture: Challenges, Opportunities, and AgMIP Frameworks for Foresight

Agricultural systems are currently undergoing rapid shifts owing to socioeconomic development, technological change, population growth, economic opportunity, evolving demand for commodities, and the need for sustainability amid global environmental change. It is not sufficient to maintain current harvest levels; rather, there is a need to rapidly increase production in light of a population growing to nearly 10 billion by mid-century and to more than 11 billion by 2100 (FAO, 2016; UN, 2016; Popkin et al., 2012). Current and future agricultural systems are additionally burdened by human-caused climate change, the result of accumulating greenhouse gas and aerosol emissions, ecological destruction, and land use changes that have altered the chemical composition of Earth’s atmosphere and trapped energy in the Earth system (IPCC, 2013; Porter et al., 2014). This increased energy has already raised average surface temperatures by approximately 1 degree Centigrade (GISTEMP Team, 2017; Hansen et al., 2010), leading early on to the term “global warming,” but this phenomenon is now more accurately referred to as “climate change” because it also modifies atmospheric circulation, adjusts regional and seasonal precipitation patterns, and shifts the distribution and characteristics of extreme events (Bindoff et al., 2013; Collins et al., 2013). Food and health systems face increasing risk owing to progressive climate change now manifesting itself as more frequent, severe extreme weather events—heat waves, droughts, and floods (IPCC, 2013). Often without warning, weather-related shocks can have catastrophic and reverberating impacts on the increasingly exposed global food system—through production, processing, distribution, retail, disposal, and waste. Simultaneously, malnutrition and ill health are arising from lack of access to nutritious food, exacerbated in crises such as food price spikes or shortages. For some countries, particularly import-dependent low-income countries, weather shocks and price spikes can lead to social unrest, famine, and migration.

Ruane, Alex C.↗

NASA NTRSDate not supplied

Airborne Observations of Aerosol Properties in Southeast Asia: Overview of Emissions, Cloud Processing, and Long Range Transport during NASA CAMP2Ex

The Southwest Monsoon represents an important synoptic scale meteorological feature that modulates precipitation throughout Southeast Asia. In addition, southwesterly flow can funnel large amounts of biomass burning aerosol into heavily populated areas throughout the Philippines, mixing with urban emissions and representing a significant air quality issue. From a climate perspective, understanding interactions between these particles and clouds has important societal ramifications through frequent extreme periods of flood and drought. Here we present airborne observations made in support of the NASA CAMP2Ex (Cloud and Aerosol Monsoonal Processes-Philippines Experiment) mission aboard the Wallops Flight Facility P-3 research aircraft, based at Clark International Airport in the Luzon region of Northern Philippines. Nineteen research flights were conducted in August-October of 2019. An extensive suite of aerosol microphysical, optical, and chemical instrumentation was deployed, along with trace gas and remote sensing measurements, to characterize aerosol emissions and their vertical/spatial variability associated with moderately convective marine cloud systems in the region. Analysis will focus on characterizing disparate aerosol sources with respect to derived chemical and optical properties relevant to global circulation modeling. For example, higher than expected mass scattering efficiencies for aged biomass burning emissions, derived from a combination of nephelometer and aerosol mass spectrometer measurements, are attributed to increased particle size and decreased density. Results will also illustrate the evolution of aerosols from Indonesian agricultural biomass burning activities into the Philippines region, in comparison with urban emissions from the megacity Manila and transported air masses from mainland Asia.

Luke David Ziemba↗

NASA NTRS2022

Quantifying Spatial Drought Propagation Potential in North America Using Complex Network Theory

Droughts have a dominant three-dimensional (3-D) spatiotemporal structure typically spanning hundreds of kilometers and often lasting for months to years. Here, we introduced a novel framework to explore the 3-D structure of the evolution of droughts based on network theory concepts. The proposed framework is applied to identify critical source regions responsible for large-scale drought onsets during 1901–2014 for the North American continent using the Standardized Precipitation Evaporation Index (SPEI). We built a spatial network connecting the drought onset timings for the North American continent. Using a spatially weighted network partitioning algorithm, the whole continent is then classified into regional spatial drought networks (RSN), where droughts are more likely to propagate within these regional systems. Finally, a customized network metric was applied to identify locations (source regions) where the drought onsets further propagate to other areas within the regional spatial network. Our results indicated that the West coast, Texas coastal region, and Southeastern Arkansas as major source regions through which atmospheric drought propagates to Western, South Central, and Eastern North America. The formation of drought source regions are due to presence of high pressure ridges and anomalous wind patterns. Furthermore, our results indicate that the drought propagation from these source regions may be due to inadequate moisture transport. The proposed framework can help to develop an early warning detection system for droughts and other spatially extensive extreme events such as heatwaves and floods.

Goutam Konapala↗

NASA NTRS2023

Evaluation of a Regional Crop Model Implementation for Sub-National Yield Assessments in Kenya

CONTEXT: Cropping system models can be used to both assess regional food security and to monitor and predict agricultural drought. Agriculture in Kenya is extremely important to both the economy and food security of the country. OBJECTIVE: This study evaluated a regional implementation of a widely used crop model, the Decision Support System for Agrotechnology Transfer (DSSAT), within a coupled modeling framework, the Regional Hydrologic Extremes Assessment System (RHEAS), over Kenya. The goal of this study was to assess the ability of RHEAS to simulate the annual variability of maize yields at the county level and evaluate the uncertainty inherent in the model and inputs. METHODS: The RHEAS system implements a stochastic ensemble approach to account for field scale variabilities in crop management practices and underlying soil and weather conditions. Satellite-derived datasets were used to evaluate the land surface component of the system and seasonally disaggregated yield for 5 years was used to assess the performance of the cropping system model. RESULTS AND CONCLUSIONS: The median correlation between RHEAS and satellite-derived soil moisture and evapotranspiration estimates were 0.78, and 0.51, respectively, indicating that the model is able to capture the key drivers of the hydrological budget. Overall, RHEAS simulated yearly yield variations with a median correlation of 0.7 with reported yields, with the best performance in the short rains season. However, across both seasons, the RHEAS model was positively biased on the order of ~1.6 MT/ha. The overall median unbiased RMSE was 0.66 MT/ha. The RHEAS system shows skill at simulating extreme departures in anomalies, and a majority of the time (62.5%) the reported yields fall within the interquartile range of the simulations. SIGNIFICANCE: One of the most important areas of improvement for the next generation of agricultural data and models is to better understand and communicate the inherent uncertainties. This is especially critical in data-limited regions. Here we present a modeling system and its implementation that begins to address these concerns. We demonstrate the ability to simulate broad trends in yields at the county level for sub-annual yields with skills that commensurate previous national/annual level studies.

Crop model↗