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NASA NTRS2000

Magnitude, Duration, and Geographic Coherence of Interannual Anomalies of the Great Plains Low-Level Jet

The Great Plains region of the United States is characterized by some of the world's most frequent and regular occurrences of a nocturnal low-level jet (LLJ). While this southerly jet is generally confined to the lowest kilometer of the atmosphere, it may cover a substantial region of the Great Plains and reach wind speed maxima of 20 m/s or more. The temporal and spatial structure of this jet has been well captured by the GEOS-1 15-year reanalysis. The jet is most evident during the warm season, May through August. The year-to-year variability of the seasonally-averaged jet structure is small relative to its diurnal or its intraseasonal variability and is comparable in magnitude to the seasonal variability for the mean climatology. The interannual variance maximum is located to the east of both the jet maximum and the seasonal variance maximum and seems to be related to a biennial oscillation which occurs for the first six years of the reanalysis period. There is a second maximum which is free of this oscillation, which is located at the same latitude but further south in the Gulf of Mexico. Interannual anomalies seem to have a duration of about three weeks and spatial coherences about ten degrees wide. Meridional velocity anomalies for the drought year 1988 and the flood year 1993 are large, but their impacts on the hydrological cycle may be as sensitive to their eastward location as to their magnitudes.

Helfand, H. Mark↗

NASA NTRS2008

Space-based Ornithology-Studying Bird Migration and Environmental Change in North America

Natural fluctuations in the availability of critical stopover sites coupled with anthropogenic destruction of wetlands, land-use change, and anticipated losses due to climate change present migratory birds with a formidable challenge. We have developed an individual-based, spatially explicit bird migration model that simulates the migration routes, timing and energy budgets of individual birds under dynamic weather and land surface conditions. Our model incorporates biophysical constraints, individual bird energy status, bird behavior, and flight aerodynamics. We model the speed, direction, and timing of individual birds moving through a user specified Lagrangian grid. The model incorporates environmental properties including wind speed and direction, topography, dynamic hydrologic properties of the landscape, and environmental suitability. The model is driven by important variables estimated from satellite observations of the land surface, by data assimilation products from weather and climate models, and biological field data. We illustrate the use of the model to study the impact of both short- and long-term environmental variatios, e.g. climate, drought, anthropogenic, on migration timing (phenology), spatial pattern, and fitness (survival and reproductive success). We present several theoretical simulations of the spring migration of Pectoral Sandpiper (Calidris melanotos) in North America with emphasis on the Central flyway from the Gulf of Mexico to Alaska.

Smith, James↗

NASA NTRS2016

Biomass Burning, Land-Cover Change, and the Hydrological Cycle in Northern Sub-Saharan Africa

The Northern Sub-Saharan African (NSSA) region, which accounts for 20%-25%of the global carbon emissions from biomass burning, also suffers from frequent drought episodes and other disruptions to the hydrological cycle whose adverse societal impacts have been widely reported during the last several decades. This paper presents a conceptual framework of the NSSA regional climate system components that may be linked to biomass burning, as well as detailed analyses of a variety of satellite data for 2001-2014 in conjunction with relevant model-assimilated variables. Satellite fire detections in NSSA show that the vast majority (greater than 75%) occurs in the savanna and woody savanna land-cover types. Starting in the 2006-2007 burning season through the end of the analyzed data in 2014, peak burning activity showed a net decrease of 2-7% /yr in different parts of NSSA, especially in the savanna regions. However, fire distribution shows appreciable coincidence with land-cover change. Although there is variable mutual exchange of different land cover types, during 2003-2013, cropland increased at an estimated rate of 0.28% /yr of the total NSSA land area, with most of it (0.18% /yr) coming from savanna.During the last decade, conversion to croplands increased in some areas classified as forests and wetlands, posing a threat to these vital and vulnerable ecosystems. Seasonal peak burning is anti-correlated with annual water-cycle indicators such as precipitation, soil moisture, vegetation greenness, and evapotranspiration, except in humid West Africa (5 deg-10 deg latitude),where this anti-correlation occurs exclusively in the dry season and burning virtually stops when monthly mean precipitation reaches 4 mm/d. These results provide observational evidence of changes in land-cover and hydrological variables that are consistent with feedbacks from biomass burning in NSSA, and encourage more synergistic modeling and observational studies that can elaborate this feedback mechanism.

biomass burning↗

NASA NTRS2023

Pacific Northwest Health & Air Quality: Monitoring Trends in Air Quality During a Drought Case Study to Improve Public Health Response to Drought Threats

Recent studies have documented a correlation between air quality and drought in the United States, which has been linked with increased aerosols including airborne particulate matter (PM) during drought conditions. This study partnered with local health departments to evaluate trends in air quality in the Pacific Northwest during the evolution of drought conditions using aerosol optical depth (AOD) observations collected by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellites. These satellite data were analyzed in conjunction with ground-based PM2.5 and PM10 data sourced from the Environmental Protection Agency (EPA)’s network of ground-based monitors and the Standardized Precipitation Evapotranspiration Index (SPEI) drought index. Based on recommendations by local health departments, this study examined air quality trends between 2015 and 2022 in 12 counties within Oregon and Washington that reflected diversity in population density, drought exposure, rural and urban status, and data availability from EPA monitors. Overall, results indicated variation in relationships among drought, satellite, and ground-based air quality data across the study area. This study did not control for the impact of wildfire events on air quality and also did not investigate shorter SPEI aggregation periods, both of which are avenues for future research. This project supplemented research into links between drought and human health and provided health departments with an objective foundation from which they can communicate public health risks to local communities.

Abby Sgan↗

NASA NTRS2021

Daily Precipitation Frequency Distributions Impacts on Land-Surface Simulations of CONUS

Many precipitation-driven data products from land data assimilation systems support assessments of droughts, floods, and other societally-relevant land-surface processes.The accumulated precipitation used as input to these products has a significant impacton water budgets; however, the effects of daily distribution of precipitation on theseproducts are not well known. A comparison of the Integrated Multi-satellite Retrievalsfor GPM (IMERG) and Climate Hazards Group InfraRed Precipitation with Stationsversion 2 (CHIRPS2) rainfall products over the continentalUnited States (CONUS) wasperformed to quantify the impacts of the daily distributionof precipitation on biases anderrors in soil moisture, runoff, and evapotranspiration (ET). Since the total accumulatedprecipitation between the IMERG and CHIRPS product differed, a third precipitationproduct, CHIRPS-to-IMERG (CHtoIM), was produced that usedCHIRPS2 accumulatedprecipitation totals and the daily precipitation frequency distribution of IMERG. Thisnew product supported a controlled analysis of the impact ofprecipitation frequencydistribution on simulated hydrological fields. The CHtoIM had higher occurrences ofprecipitation in the 0–5 mm day−1range, with a lower occurrence of dry days, whichdecreased soil moisture and surface runoff in the land-surface model. The surface soillayer had a tendency to reach saturation more often in the CHIRPS2 simulations, wherethe number of moderate to heavy precipitation days (>5mm day−1) was increased. Usingthe blended CHtoIM product as input reduced errors in surface soil moisture by 5–15%when compared to Soil Moisture Active/Passive (SMAP) data.Similarly, ET errors werealso slightly decreased (∼2%) when compared to SSEBop data. Moderate changes indaily precipitation distributions had a quantifiable impact on soil moisture, runoff, andET. These changes usually improved the model when compared to other modeled andobservational datasets, but the magnitude of the improvements varied by region andtime of year.

Daniel P Sarmiento↗

NASA NTRS2007

Use of AIRS, OMI, MLS, and TES Data in Assessing Forest Ecosystem Exposure to Ozone

Ground-level ozone at high levels poses health threats to exposed flora and fauna, including negative impacts to human health. While concern is common regarding depletion of ozone in the stratosphere, portions of the urban and rural United States periodically have high ambient levels of tropospheric ozone on the ground. Ozone pollution can cause a variety of impacts to susceptible vegetation (e.g., Ponderosa and Jeffrey pine species in the southwestern United States), such as stunted growth, alteration of growth form, needle or leaf chlorosis, and impaired ability to withstand drought-induced water stress. In addition, Southern Californian forests with high ozone exposures have been recently subject to multiyear droughts that have led to extensive forest overstory mortality from insect outbreaks and increased incidence of wildfires. Residual forests in these impacted areas may be more vulnerable to high ozone exposures and to other forest threats than ever before. NASA sensors collect a wealth of atmospheric data that have been used recently for mapping and monitoring regional tropospheric ozone levels. AIRS (Atmospheric Infrared Sounder), OMI (Ozone Monitoring Instrument), MLS (Microwave Limb Sounder), and TES (Tropospheric Emission Spectrometer) data could be used to assess forest ecosystem exposure to ozone. Such NASA data hold promise for providing better or at least complementary synoptic information on ground-level ozone levels that Federal agency partners can use to assess forest health trends and to mitigate the threats as needed in compliance with Federal laws and mandates. NASA data products on ozone concentrations may be able to aid applications of DSTs (decision support tools) adopted by the USDA FS (U.S. Department of Agriculture Forest Service) and by the NPS (National Park Service), such as the Ozone Calculator, in which ground ozone estimates are employed to assess ozone impacts to forested vegetation.

Spruce, Joseph P.↗

NASA NTRS2019

Quantifying Contributions of Land Carbon Fluxes Variability and Atmospheric Transport Variability to Atmospheric CO2 Variability

Much of the uncertainty in predicting variations in greenhouse gases originates in the complex dynamics of the land ecosystem and the atmosphere. To reduce the uncertainties, it is useful to decouple the contributions of land carbon fluxes and atmospheric transport to atmospheric carbon variability. Here we isolate these contributions using a version of the NASA GEOS model that couples carbon, energy and water cycles between the land and the atmosphere. Our current study is a follow-on to a preliminary analysis that suggested that an extreme event (e.g., imposed drought) in a free running AGCM simulation affects atmospheric CO2 more through its impact on atmospheric transport than through a modification of land carbon fluxes. In order to more carefully isolate the effects of the land carbon variability and atmospheric transport variability on atmospheric CO2 variability, we conducted two coupled-AGCM simulations in replay mode, a mode that forces the model's evolution of weather to match that of the MERRA-2 reanalysis. In the control simulation, the land carbon fluxes and the atmospheric CO2 concentrations, as well as the meteorology, are simulated over 2001-2015. We compute the climatological seasonal cycles of net land carbon production from this control simulation and then prescribe, in a second simulation, these climatological carbon fluxes to the atmosphere in the same replay mode. By comparing the atmospheric CO2 variability produced in the two simulations, we fully isolate the part of this variability associated with land surface fluxes. Relative contributions of land flux variability and atmospheric transport variability to CO2 variability are quantified both on a regional basis and as a function of height into the atmosphere to support interpretation of both ground-based and satellite observations.

Lee, Eunjee↗

NASA NTRS2015

Sensitivity of Water Scarcity Events to ENSO-Driven Climate Variability at the Global Scale

Globally, freshwater shortage is one of the most dangerous risks for society. Changing hydro-climatic and socioeconomic conditions have aggravated water scarcity over the past decades. A wide range of studies show that water scarcity will intensify in the future, as a result of both increased consumptive water use and, in some regions, climate change. Although it is well-known that El Niño- Southern Oscillation (ENSO) affects patterns of precipitation and drought at global and regional scales, little attention has yet been paid to the impacts of climate variability on water scarcity conditions, despite its importance for adaptation planning. Therefore, we present the first global-scale sensitivity assessment of water scarcity to ENSO, the most dominant signal of climate variability. We show that over the time period 1961-2010, both water availability and water scarcity conditions are significantly correlated with ENSO-driven climate variability over a large proportion of the global land area (> 28.1 %); an area inhabited by more than 31.4% of the global population. We also found, however, that climate variability alone is often not enough to trigger the actual incidence of water scarcity events. The sensitivity of a region to water scarcity events, expressed in terms of land area or population exposed, is determined by both hydro-climatic and socioeconomic conditions. Currently, the population actually impacted by water scarcity events consists of 39.6% (CTA: consumption-to-availability ratio) and 41.1% (WCI: water crowding index) of the global population, whilst only 11.4% (CTA) and 15.9% (WCI) of the global population is at the same time living in areas sensitive to ENSO-driven climate variability. These results are contrasted, however, by differences in growth rates found under changing socioeconomic conditions, which are relatively high in regions exposed to water scarcity events. Given the correlations found between ENSO and water availability and scarcity conditions, and the relative developments of water scarcity impacts under changing socioeconomic conditions, we suggest that there is potential for ENSO-based adaptation and risk reduction that could be facilitated by more research on this emerging topic.

risk↗

NASA NTRS2020

Comparison of Vertical Surface Deformation Estimates Derived From Space-Based Gravimetry, Ground-Based GPS, and Model-Based Hydrologic Loading Over Snow-Dominated Watersheds in the United States

Spatiotemporal variability in Earth's terrestrial water storage (TWS) causes changes in surface deformation. The potential for using ground-based Global Positioning System (GPS) vertical displacement observations for estimating TWS is explored through a comparison of vertical displacements derived from space-based gravimetric retrievals, ground-based GPS, and model-based hydrologic estimates. The study presented here focuses on two snow-dominated basins in the Western United States for the years 2003–2016. Seasonal variations are observed in the vertical displacements derived from all three data sets, and the variation is coherent with the changes in hydrologic loading. Good consistency is observed between any two of the three data sets with gravimetric retrievals and hydrologic model estimates providing the highest level of agreement (i.e., all examined stations with correlation coefficient R > 0.70). Vertical displacements derived from gravimetric retrievals and ground-based GPS yielded R > 0.70 for more than 89% of the stations. In addition, it is found that both GPS-derived and space-based, gravimetry-derived vertical displacements clearly reflected the impact of climate variation (i.e., heavy precipitation during 2010–2011 winter followed by prolonged drought). Vertical displacements derived from the hydrologic model highlighted the relatively large precipitation convergence phase during late 2010 to early 2011 at some stations but not the prolonged drought that followed. The results indicate that ground-based GPS observations of vertical displacement have the capability to capture variations in TWS changes, which can be systematically merged in conjunction with Gravity Recovery and Climate Experiment (GRACE) into a land surface model to improve TWS estimates in a follow-up study.

Gaohong Yin↗

NASA NTRS2020

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high‐resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED‐2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED‐2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

Marcos Longo↗

NASA NTRS2012

Overview of US AID-World Bank-NASA Collaboration to Address Water Management Issues in the MENA Region

The World Bank, USAID and NASA have recently established a joint project to study multiple issues pertaining to water related applications in the Middle East North Africa (MENA) region. The main concentration of the project is on utilization of remote sensing data and hydrological models to address crop irrigation and mapping, flood mapping and forecasting, evapotranspiration and drought problems prevalent in this large geographic area. Additional emphases are placed on understanding the climate impact on these areas as well. Per IPCC 2007 report, by the end of this century MENA region is projected to experience an increase of 3 C to 5 C rise in mean temperatures and a 20% decline in precipitation. This poses a serious problem for this geographic zone especially when majority of the hydrological consumption is for the agriculture sector and the remaining amount is for domestic consumption. The remote sensing data from space is one of the best ways to study such complex issues and further feed into the decision support systems. NASA's fleet of Earth Observing satellites offer a great vantage point from space to look at the globe and provide vital signs necessary to maintain healthy and sustainable ecosystem. These observations generate multiple products such as soil moisture, global precipitation, aerosols, cloud cover, normalized difference vegetation index, land cover/use, ocean altimetry, ocean salinity, sea surface winds, sea surface temperature, ozone and atmospheric gases, ice and snow measurements, and many more. All of the data products, models and research results are distributed-via the Internet freely through out the world. This project will utilize several NASA models such as global Land Data Assimilation System (LDAS) to generate hydrological states and fluxes in near real time. These LDAS products will then be further compared with other NASA satellite observations (MODIS, VIIRS, TRMM, etc.) and other discrete models to compare and optimize evapotranspiration, soil moisture and crop irrigation, droUght assessment and water balance. The floods being a critical disaster in many of the MENA countries, NASA's global flood mapping and modeling framework (CREST) will be customized for country specific needs and delivered to the remote sensing organizations for their future use. Finally, capacity building is a critical part of this project and NASA will assist in this effort as well.

Habib, Shahid↗

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 NTRS2011

Predicting Regional Drought on Sub-Seasonal to Decadal Time Scales

Drought occurs on a wide range of time scales, and within a variety of different types of regional climates. It is driven foremost by an extended period of reduced precipitation, but it is the impacts on such quantities as soil moisture, streamflow and crop yields that are often most important from a users perspective. While recognizing that different users have different needs for drought information, it is nevertheless important to understand that progress in predicting drought and satisfying such user needs, largely hinges on our ability to improve predictions of precipitation. This talk reviews our current understanding of the physical mechanisms that drive precipitation variations on subseasonal to decadal time scales, and the implications for predictability and prediction skill. Examples are given highlighting the phenomena and mechanisms controlling precipitation on monthly (e.g., stationary Rossby waves, soil moisture), seasonal (ENSO) and decadal time scales (PD~ and AMO).

Schubert, Siegfried↗

NASA NTRS1998

NASA's Earth Observing System: The Transition from Climate Monitoring to Climate Change Prediction

Earth's 4.5 billion year history is a study in change. Natural geological forces have been rearranging the surface features and climatic conditions of our planet since its beginning. There is scientific evidence that some of these natural changes have not only led to mass extinctions of species (e.g., dinosaurs), but have also severely impacted human civilizations. For instance, there is evidence that a relatively sudden climate change caused a 300-year drought that contributed to the downfall of Akkadia, one of the most powerful empires in the Middle-East region around 2200 BC. More recently, the "little ice age" from 1200-1400 AD forced the Vikings to abandon Greenland when temperatures there dropped by about 1.5 C, rendering it too difficult to grow enough crops to sustain the population. Today, there is compelling scientific evidence that human activities have attained the magnitude of a geological force and are speeding up the rate of global change. For example, carbon dioxide levels have risen 30 percent since the industrial revolution and about 40 percent of the world's land surface has been transformed by humans. We don't understand the cause-and-effect relationships among Earth's land, ocean, and atmosphere well enough to predict what, if any, impacts these rapid changes will have on future climate conditions. We need to make many measurements all over the world, over a long period of time, in order to assemble the information needed to construct accurate computer models that will enable us to forecast climate change. In 1988, the Earth System Sciences Committee, sponsored by NASA, issued a report calling for an integrated, long-term strategy for measuring the vital signs of Earth's climate system. The report urged that the measurements must all be intimately coupled with focused process studies, they must facilitate development of Earth system models, and they must be stored in an information system that ensures open access to consistent, long-term data. This committee emphasized that the only feasible way to collect these consistent, long-term data is through the use of space-based Earth "remote sensors" (instruments that can measure from a distance things like temperature).

King, Michael D.↗

NASA NTRS2010

Possible Influences of Air Pollution, Dust and Sandstorms on the Indian Monsoon

In Asian monsoon countries, such as China and India, human health and safety problems caused by air pollution are becoming increasingly serious, due to the increased loading of atmospheric pollutants from waste gas emissions and from rising energy demand associated with the rapid pace of industrialization and modernization. Meanwhile, uneven distribution of monsoon rain associated with flash floods or prolonged drought, has caused major loss of human life and damage to crops and.property with devastating societal impacts. Historically, air-pollution and monsoons research are treated as separate problems. However recent studies have suggested that the two problems may be intrinsically linked and need to be studied jointly. Fundamentally, aerosols can affect precipitation through radiative effects cif suspended particles in the atmosphere (direct effect) and/or by interfering and changing: the cloud and precipitation formation processes (indirect effect). Based on their optical properties, aerosols can be classified into two types.: those that absorb solar radiation, and those that do not. Both types of aerosols scatter sunlight and reduce the amount of solar radiation from reaching the Earth's surface, causing it to cool. The surface cooling increases atmospheric stability and reduces convection potential, Absorbing aerosols, however, in addition to cooling the surface, can heat the atmosphere. The heating of the atmosphere may reduce the amount of low clouds by increased evaporation in cloud drops. The heating, however, may induce rising motion, enhance low-level moisture, convergence and, hence, increases rainfall, The latent heating from enhanced rainfall may excite feedback processes in the large-scale circulation, further amplify.the initial response to aerosol heating and producing more rain. Additionally, aerosols can increase the concentration of cloud condensation nuclei (CCN), increase cloud amount and decrease coalescence and collision rates, leading to reduced precipitation. However, in the presence of increasing moist and warm air, the reduced coalescence/collision may lead to supercooled drops at higher altitudes where ice precipitation falls and melts. The latent heat release from freezing aloft and melting below implies greater upward heat transport in polluted clouds and invigorate deep convection. In this way, aerosols may lead to increased local convection. Hence, depending on the ambient large-scale conditions and dynamical feedback processes, aerosols' effect on precipitation can be positive, negative or mixed. In the Asian monsoon and adjacent regions, the aerosol forcing and responses of the water cycle are even more complex, Both direct and indirect effects may take place locally and simultaneously, interacting with each other. in addition to local effects, monsoon rainfall may be affected by aerosols transported from other regions and intensified through large-scale circulation and moisture feedback. Thus, dust transported by the large-scale circulation from the adjacent deserts to northern India may affect rainfall over the Bay of Bengal; sulphate and black carbon front industrial pollution in central, southern China and northern India may affect the rainfall regime over the Korean peninsula and Japan; organic and black carbon front biomass burning from Indo-China may modulate the pre-monsoon rainfall regime over southern China and coastal regions, contributing to variability in differential heating and cooling of the atmosphere and to the land-sea thermal contrast. During the pre-monsoon season and monsoon breaks, it has been suggested that radiative forcing by absorbing aerosols have nearly the same order of magnitude as the forcing due to latent heating from convection and surface fluxes. The magnitude of the total aerosol radiative cooling due to sulphates and soot is of the order of 20-40 W/m2 over the Asian monsoon land region in the pre-monsoon season, compared to about 1-2 W/m2 for global warng. However, the combined forcing at the surface and in the atmosphere, including all species. if aerosols, and details of aerosol mixing, and impacts on the energy and water cycles in the monsoon land regions, are not well known.

Lau, William K. M.↗

NASA NTRS2022

Interactive Biogenic Emissions and Drought Stress Effects on Atmospheric Composition in NASA GISS ModelE

Drought is a hydroclimatic extreme that causes perturbations to the terrestrial biosphere and acts as a stressor on vegetation, affecting emissions patterns. During severe drought, isoprene emissions are reduced. In this paper, we focus on capturing this reduction signal by implementing a new percentile isoprene drought stress (y d ) algorithm in NASA GISS ModelE based on the MEGAN3 (Model of Emissions of Gases and Aerosols from Nature Version 3) approach as a function of a photosynthetic parameter (V c,max ) and water stress (β). Four global transient simulations from 2003–2013 are used to demonstrate the effect without y d (Default_ModelE) and with online y d (DroughtStress_ModelE). DroughtStress_ModelE is evaluated against the observed isoprene measurements at the Missouri Ozarks AmeriFlux (MOFLUX) site during the 2012 severe drought where improvements in the correlation coefficient indicate it is a suitable drought stress parameterization to capture the reduction signal during severe drought. The application of y d globally leads to a decadal average reduction of ∼ 2.7 %, which is equivalent to ∼14.6 Tg yr -1 of isoprene. The changes have larger impacts in regions such as the southeastern US. DroughtStress_ModelE is validated using the satellite ΩHCHO column from the Ozone Monitoring Instrument (OMI) and surface O 3 observations across regions of the US to examine the effect of drought on atmospheric composition. It was found that the inclusion of isoprene drought stress reduced the overestimation of ΩHCHO in Default_ModelE during the 2007 and 2011 southeastern US droughts and led to improvements in simulated O 3 during drought periods. We conclude that isoprene drought stress should be tuned on a model-by-model basis because the variables used in the parameterization responses are relative to the land surface model hydrology scheme (LSM) and the effects of y d application could be larger than seen here due to ModelE not having large biases of isoprene during severe drought.

drought stress effects↗

NASA NTRS2015

Relative Impacts of Mitigation, Temperature, and Precipitation on 21st-Century Megadrought Risk in the American Southwest

Megadroughts are comparable in severity to the worst droughts of the 20th century but are of much longer duration. A megadrought in the American Southwest would impose unprecedented stress on the limited water resources of the area, making it critical to evaluate future risks not only under different climate change mitigation scenarios but also for different aspects of regional hydroclimate. We find that changes in the mean hydroclimate state, rather than its variability, determine megadrought risk in the American Southwest. Estimates of megadrought probabilities based on precipitation alone tend to underestimate risk. Furthermore, business-as-usual emissions of greenhouse gases will drive regional warming and drying, regardless of large precipitation uncertainties. We find that regional temperature increases alone push megadrought risk above 70, 90, or 99% by the end of the century, even if precipitation increases moderately, does not change, or decreases, respectively. Although each possibility is supported by some climate model simulations, the latter is the most common outcome for the American Southwest in Coupled Model Intercomparison 5 generation models. An aggressive reduction in global greenhouse gas emissions cuts megadrought risks nearly in half.

risk↗

NASA NTRS2011

The International Summer School on Land Cover Change and Hydroclimate of the La Plata Basin

The La Plata Basin (LPB) in southern South America has been subject to land cover and land use changes (LCLUCs) since colonial times and with an accelerated rate in the last decades and over extensive areas. The work of Ameghino even suggested that there were relations between those land use changes and the frequency of droughts and floods in the region. Despite this early knowledge, not much is known of the potential impacts of LCLUC on the hydroclimate of the La Plata basin. Besides, over the last century much of the La Plata Basin has had a reported increase in precipitation and heavy rains, and these changes along with an increase in population growth - have resulted in more adverse effects from flooding. To draw attention to these issues, during two weeks in November 2009 the International Summer School on Land Cover Change and Hydroclimate of the La Plata Basin was organized at the grounds of the Itaip Hydropower Plant in Brazil. The school was the result of the combination of interests between the La Plata Basin Regional Hydroclimate Project, the Inter-American Institute for Global Change Research (IAI), and the International Hydroinformatics Center (IHC) in Itaip . LPB is an umbrella project endorsed by the Global Energy and Water Cycle Experiment (GEWEX) and the Climate Prediction and Variability (CLIVAR), both of the World Climate Research Programme (WCRP). LPB has made a priority to train young scientists and promote interdisciplinary collaborations in areas related to Climate, Hydrology, Ecology and Agriculture. The IAI, with a similar agenda, was a natural partner to develop this Summer School, which in turn benefited from Itaipu s interest in relating with the scientific community of neighboring countries. The choice of location (Itaip Technological Park) was made so that participants could relate research usually done at academic institutions to applications and operations at one of the largest hydropower plants in the world. The school was attended by 45 advanced graduate students and young scientists with different backgrounds from seven countries, including less technically advanced ones in the region..

Berbery, Ernesto Hugo↗