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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Convective and Stratiform Precipitation Processes and their Relationship to Latent Heating

The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of its formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the Tropics. Associated with this rainfall is a vast amount of heat, which is known as latent heat. It arises mainly due to the phase change of water vapor condensing into liquid droplets; three-fourths of the total heat energy available to the Earth's atmosphere comes from tropical rainfall. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. An improved convective -stratiform heating (CSH) algorithm has been developed to obtain the 3D structure of cloud heating over the Tropics based on two sources of information: 1) rainfall information, namely its amount and the fraction due to light rain intensity, observed directly from the Precipitation Radar (PR) on board the TRMM satellite and 2) synthetic cloud physics information obtained from cloud-resolving model (CRM) simulations of cloud systems. The cloud simulations provide details on cloud processes, specifically latent heating, eddy heat flux convergence and radiative heating/cooling, that. are not directly observable by satellite. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. One of the major differences between new and old algorithms is that the level of maximum cloud heating occurs 1 to 1.5 km lower in the atmosphere in the new algorithm. This can effect the structure of the implied air currents associated with the general circulation of the atmosphere in the Tropics. The new CSH algorithm will be used provide retrieved heating data to other heating algorithms to supplement their performance.

Tao, Wei-Kuo↗
NASA NTRS2010

Shallow and Deep Latent Heating Modes Over Tropical Oceans Observed with TRMM PR Spectral Latent Heating Data

The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of its formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the Tropics. Associated with this rainfall is a vast amount of heat, which is known as latent heat. It arises mainly due to the phase change of water vapor condensing into liquid droplets; three-fourths of the total heat energy available to the Earth's atmosphere comes from tropical rainfall. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. Three-dimensional distributions of latent heating estimated from Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR)utilizing the Spectral Latent Heating (SLH) algorithm are analyzed. Mass-weighted and vertically integrated latent heating averaged over the tropical oceans is estimated as approx.72.6 J/s (approx.2.51 mm/day), and that over tropical land is approx.73.7 J/s (approx.2.55 mm/day), for 30degN-30degS. It is shown that non-drizzle precipitation over tropical and subtropical oceans consists of two dominant modes of rainfall systems, deep systems and congestus. A rough estimate of shallow mode contribution against the total heating is about 46.7 % for the average tropical oceans, which is substantially larger than 23.7 % over tropical land. While cumulus congestus heating linearly correlates with the SST, deep mode is dynamically bounded by large-scale subsidence. It is notable that substantial amount of rain, as large as 2.38 mm day-1 in average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that even in the region with SST warmer than 28 oC, large-scale subsidence effectively suppresses the deep convection, remaining the heating by congestus clouds. Our results support that the entrainment of mid-to-lower-tropospheric dry air, which accompanies the large-scale subsidence is the major factor suppressing the deep convection. Therefore, representation of the realistic entrainment is very important for proper reproduction of precipitation distribution and resultant large-scale circulation.

Takayabu, Yukari N.↗
NASA NTRS1999

The Tropical Rainfall Measuring Mission: An Overview

The importance of quantitative knowledge of tropical rainfall, its associated latent heating and variability is summarized in the context of the global hydrologic cycle. Much of the tropics is covered by oceans. What land exists, is covered largely by rainforests that are only thinly populated. The only way to adequately measure the global tropical rainfall for climate and general circulation models is from space. To address these issues, the TRMM satellite was launched in Nov. 1997. It has been operating successfully ever since.

Kummerow. Christian↗
NASA NTRS2014

How Accurate is Land/Ocean Moisture Transport Variability in Reanalyses?

Quantifying the global hydrological cycle and its variability across various time scales remains a challenge to the climate community. Direct measurements of evaporation (E), evapotranspiration (ET), and precipitation (P) are not feasible on a global scale, nor is the transport of water vapor over the global oceans and sparsely populated land areas. Expanding satellite data streams have enabled development of various water (and energy) flux products, complementing reanalyses and facilitating observationally constrained modeling. But the evolution of the global observing system has produced additional complications--improvements in satellite sensor resolution and accuracy have resulted in "epochs" of observational quasi-uniformity that can adversely affect reanalysis trends. In this work we focus on vertically integrated moisture flux convergence (VMFC) variations within the period 1979 - present integrated over global land. We show that VMFC in recent reanalyses (e.g. ERA-I, NASA MERRA, NOAA CFSR and JRA55) suffers from observing system changes, though differently in each product. Land Surface Models (LSMs) forced with observations-based precipitation, radiation and near-surface meteorology share closely the interannual P-ET variations of the reanalyses associated with ENSO events. (VMFC over land and P-ET estimates are equivalent quantities since atmospheric storage changes are small on these scales.) But the long-term LSM trend over the period since 1979 is approximately one-fourth that of the reanalyses. Additional reduced observation reanalyses assimilating only surface pressure and /or specifying seasurface temperature also have a much smaller trend in P-ET like the LSMs. We explore the regional manifestation of the reanalysis P-ET / VMFC problems, particularly over land. Both principal component analysis and a simple time series changepoint analysis highlight problems associated with data poor regions such as Equatorial Africa and, for one reanalysis, the Equatorial Andes region. Onset of the availability of passive microwave Special Sensor Microwave Imager (SSMI) moisture data in July 1987 and the transition from the Microwave Sounder Unit (MSU) to an advanced version (AMSU) have significant impacts on VMFC variability. Simple accounting for these errors of leading importance results in modified reanalysis VMFC estimates that agree much better with the LSM results. Regional details of the modified reanalysis VMFC and LSM P-ET are related to changes in Pacific Decadal Variability as manifest in SST changes after the late 1990s.

Robertson, F. R.↗
NASA NTRS2000

Goddard Cumulus Ensemble (GCE) Model: Application for Understanding Preciptation Processes

The global hydrological cycle is central to climate system interactions and the key to understanding their behavior. Rainfall and its associated precipitation processes are a key link in the hydrologic cycle. Fresh water provided by tropical rainfall and its variability can exert a large impact upon the structure of the upper ocean layer. In addition, approximately two-thirds of the global rain falls in the Tropics, while the associated latent heat release accounts for about three-fourths of the total heat energy for the Earth's atmosphere. Precipitation from convective cloud systems comprises a large portion of tropical heating and rainfall. Furthermore, the vertical distribution of convective latent-heat releases modulates large-scale tropical circulations (e.g., the 30-60-day intraseasonal oscillation), which, in turn, impacts midlatitude weather through teleconnection patterns such as those associated with El Nino. Shifts in these global circulations can result in prolonged periods of droughts and floods, thereby exerting a tremendous impact upon the biosphere and human habitation. And yet, monthly rainfall over the tropical oceans is still not known within a factor of two over large (5 degrees latitude by 5 degrees longitude) areas. Hence, the Tropical Rainfall Measuring Mission (TRMM), a joint U.S./Japan space project, can provide a more accurate measurement of rainfall as well as estimate the four-dimensional structure of diabatic heating over the global tropics. The distributions of rainfall and inferred heating can be used to advance our understanding of the global energy and water cycle. In addition, this information can be used for global circulation and climate models for testing and improving their parameterizations.

Tao, Wei-Kuo↗
DOE OSTI2024

Tree water uptake patterns across the globe

Plant water uptake from the soil is a crucial element of the global hydrological cycle and essential for vegetation drought resilience. Yet, knowledge of how the distribution of water uptake depth (WUD) varies across species, climates, and seasons is scarce relative to our knowledge of aboveground plant functions. With a global literature review, we found that average WUD varied more among biomes than plant functional types (i.e. deciduous/evergreen broadleaves and conifers), illustrating the importance of the hydroclimate, especially precipitation seasonality, on WUD. By combining records of rooting depth with WUD, we observed a consistently deeper maximum rooting depth than WUD with the largest differences in arid regions – indicating that deep taproots act as lifelines while not contributing to the majority of water uptake. The most ubiquitous observation across the literature was that woody plants switch water sources to soil layers with the highest water availability within short timescales. Hence, seasonal shifts to deep soil layers occur across the globe when shallow soils are drying out, allowing continued transpiration and hydraulic safety. While there are still significant gaps in our understanding of WUD, the consistency across global ecosystems allows integration of existing knowledge into the next generation of vegetation process models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Can ERA5 Be Used to Study Mesoscale Convective System Climatological Characteristics?

Mesoscale convective systems (MCSs) produce more than half of tropical rainfall and are central to the global hydrologic cycle. As the climate warms, environments favorable for MCSs may become more common; however, limited observational records hamper understanding of how MCSs respond to variations and changes in their environments. Here, we evaluate how well MCSs are represented in ERA5, a widely used global high‐resolution reanalysis product. Using PyFLEXTRKR, which jointly tracks top‐of‐atmosphere infrared brightness temperature and surface precipitation, we identified MCSs in ERA5 and compared them with those identified in satellite observations using the same detection algorithm. This comparison analysis spans 2007–2020 using hourly data at 0.25° horizontal resolution focusing over the tropics. ERA5 reproduces observed brightness‐temperature statistics and captures the geographic distribution and seasonal and diurnal cycles of MCS cold cloud shields. However, ERA5 precipitation exhibits an intensity bias—too much light rain and too little heavy rain—which shifts the rain‐rate distribution and reduces the frequency of MCSs relative to observations. Within MCSs, ERA5 precipitation exhibits the same pattern of bias, yielding a systematic underestimation of MCS precipitation intensity. Consistent with these biases, ERA5 underestimates the contribution of MCS to tropical rainfall by 25%–34% in key regions. Overall, ERA5 is suitable for studying MCS cold cloud‐shield climatology and evolution, but precipitation‐based MCS characteristics (including event‐level precipitation features and the geospatial distribution of MCS precipitation) should be interpreted with caution. These findings clarify which aspects of MCS behavior are robustly represented in ERA5 for climatological applications.

mesoscale convection↗
NASA NTRS1988

Radar scattering and soil moisture

Research is being conducted on microwave scattering from vegetation. The objective is to develop techniques for measuring parameters of the vegetation canopy (such as biomass) needed for understanding global biogeochemical cycles and to develop techniques for correcting microwave measurements of soil moisture for the effects of the vegetation canopy. Measurements of vegetation and soil moisture are important for understanding the environment on a global scale. For example, moisture in the soil is an important, highly variable, element in the global hydrologic cycle. The hydrologic cycle, in turn, is strongly coupled to weather and climate through moisture (and energy) fluxes at the surface. The amount and distribution of vegetation is an important element in biogeochemical cycles; and knowledge of both the vegetation canopy and soil moisture is of practical importance in agricultural management. These theories are examined.

Levine, D. M.↗
NASA NTRS1992

Integration of space and in-situ observations to study atmosphere, ocean and land processes

A research investigation was conducted into the possibility of using atmospheric observations made in the past from both terrestrial and space-based platforms to create a global, coherent four dimensional analysis for the purpose of studying atmospheric, oceanic, and land surface processes relevant to climate simulation, monitoring, and change. This investigation consisted of the following tasks: (1) a mature global data assimilation system was obtained from the National Meteorological Center and modified for use on a Cray X-MP computer system; (2) atmospheric observations for the period 20 Nov. 1982 through 1 Mar. 1983, including rawinsonde soundings, aircraft-based measurements, pilot balloons, and temperature soundings from polar orbiting satellites were obtained from several sources; and (3) the global data assimilation system was used to reassimilate the atmospheric observations to produce a new atmospheric analysis which was then compared with the contemporaneous analysis. The global hydrologic cycle, including fluxes between the atmosphere and both the land and ocean surfaces, was estimated. The flux of water from the ocean surface into the atmosphere, its transport in the form of latent heat to remote regions, and its return to the surface in the form of precipitation were estimated globally. In addition, several regional budgets for selected tropical oceanic and extratropical continental areas were also done.

Shukla, J.↗
NASA NTRS2019

Online Visualization and Analysis of NASA Satellite-Based Global and Regional Precipitation Products Through Giovanni

Observational data are essential for Earth science research and applications. Traditional ground-based observations suffer from many limitations (e.g. costly deployment). As a result, data are often sparse and inconsistent, especially over vast oceans that cover nearly 71% of the Earth's surface, and for remote continents. Precipitation is one of the important physical parameters in the global hydrological cycle and other disciplines. Each year, severe floods and droughts happen in different parts of the world and cause significant damage to the economy, as well as human casualties (e.g. Hurricane Katrina, the Dust Bowl). Accurate and timely precipitation observations and predictions are important for research and applications. However, ground-based precipitation observations are quite limited, especially in remote and mountainous regions. Since the satellite era began, satellite-based precipitation products have gained popularity in Earth science research, applications, and education. Accessing satellite products can be a daunting task to many users, especially those who do not have prior experience or knowledge with satellite data. Recognizing this obstacle, the NASA Goddard Earth Sciences and Data and Information Services Center (GES DISC), home to data archives for the NASA-JAXA Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM), has developed data services including an online visualization and analysis tool, Giovanni (the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure), enabling users at different levels to access, explore, and evaluate NASA satellite-based data products without downloading either data and software, or requiring coding. Currently, global and regional precipitation products from different satellite missions (TRMM, GPM) and projects (e.g. the Modern Era Retrospective-analysis for Research and Applications Version 2 (MERRA-2), and the North American Land Data Assimilation System (NLDAS)), ranging from half-hourly to monthly temporal resolution, are available in Giovanni. There are over 1900 variables in Giovanni, covering measurements in precipitation, hydrology, atmospheric dynamics, atmospheric chemistry, etc. In this poster presentation, we will provide a live demonstration of Giovanni and its latest development, including precipitation-related variables, and new basic features such as polar projections. The session will also provide a Q&A opportunity for attendees.

Giovanni↗
DOE OSTI2022

The uncertain role of rising atmospheric CO 2 on global plant transpiration

As CO 2 concentration in the atmosphere rises, there is a need for improved physical understanding of its impact on global plant transpiration. This knowledge gap poses a major hurdle in robustly projecting changes in the global hydrologic cycle. For this reason, here we review the different processes by which atmospheric CO 2 concentration affects plant transpiration, the several uncertainties related to the complex physiological and radiative processes involved, and the knowledge gaps which need to be filled in order to improve predictions of plant transpiration. Additionally, although there is a high degree of certainty that rising CO 2 will impact plant transpiration, the exact nature of this impact remains unclear due to complex interactions between CO 2 and climate, and key aspects of plant morphology and physiology. The interplay between these factors has substantial consequences not only for future climate and global vegetation, but also for water availability needed for sustaining the productivity of terrestrial ecosystems. Future changes in global plant transpiration in response to enhanced CO 2 are expected to be driven by water availability, atmospheric evaporative demand, plant physiological processes, emergent plant disturbances related to increasing temperatures, and the modification of plant physiology and coverage. Considering the universal sensitivity of natural and agricultural systems to terrestrial water availability we argue that reliable future projections of transpiration is an issue of the highest priority, which can only be achieved by integrating monitoring and modeling efforts to improve the representation of CO 2 effects on plant transpiration in the next generation of earth system models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Global Assimilation of Multi-Sensor Snow Observations for Improved Characterization of Snow Processes

Snow conditions on the land surface are recognized to be key components of the global hydrological cycle as they play a critical role in the determination of local and regional climate. In many mid-latitude and high-latitude regions, the seasonal water storage and associated spring snowmelt dominate the local hydrology. The contribution to the runoff and moisture conditions from snow is vital in supporting agriculture and in determining water resources management practices. Consequently, accurate characterization of snow properties becomes important for both end-use applications and weather and climate research. Recently a joint effort between the u.S. Air Force and NASA has enabled a blended, multi-sensor snow product known as the AFWA NASA Snow Algorithm (ANSA). This global snow dataset has been generated by utilizing the Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) datasets. ANSA product includes estimates of snow cover extent, snow water equivalent (SWE) and SWE-derived snow depth fields. The MODIS-based products enable snow cover mappings under cloud-free conditions whereas the passive microwave data from AMSR-E provides measurements under cloudy conditions. These remotely-sensed snow observations are further augmented with the information from ground-based snow measurements through data fusion techniques. The resulting ANSA products are employed in the NASA Land Information System (LIS) data assimilation framework, which provides a comprehensive environment for integrating community land surface models, ground and satellite-based observations, and ensemble-based data assimilation tools. LIS incorporates the multisensor ANSA snow retrievals with the land surface model estimates to generate spatially and temporally continuous estimates of snow states, through data assimilation. A suite of experiments to assimilate ANSA snow cover, SWE and snow depth estimates with different land surface models in LIS are conducted and the resulting estimates of snow conditions are evaluated against a number of in-situ observational datasets, over several regions of the world. These evaluations are used to compare and contrast the advantages and disadvantages of these multi-sensor snow observations.

Kumar, Sujay↗
NASA NTRS1997

The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

Robertson, Franklin R.↗
NASA NTRS2006

A Time Series Approach for Soil Moisture Estimation

Soil moisture is a key parameter in understanding the global water cycle and in predicting natural hazards. Polarimetric radar measurements have been used for estimating soil moisture of bare surfaces. In order to estimate soil moisture accurately, the surface roughness effect must be compensated properly. In addition, these algorithms will not produce accurate results for vegetated surfaces. It is difficult to retrieve soil moisture of a vegetated surface since the radar backscattering cross section is sensitive to the vegetation structure and environmental conditions such as the ground slope. Therefore, it is necessary to develop a method to estimate the effect of the surface roughness and vegetation reliably. One way to remove the roughness effect and the vegetation contamination is to take advantage of the temporal variation of soil moisture. In order to understand the global hydrologic cycle, it is desirable to measure soil moisture with one- to two-days revisit. Using these frequent measurements, a time series approach can be implemented to improve the soil moisture retrieval accuracy.

soil moisture↗
NASA NTRS2006

The Tropospheric Wind Lidar Technology Experiment (TWiLiTE): An Airborne Direct Detection Doppler Lidar Instrument Development Program

Global measurement of tropospheric winds is a key measurement for understanding atmospheric dynamics and improving numerical weather prediction. Global wind profiles remain a high priority for the operational weather community and also for a variety of research applications including studies of the global hydrologic cycle and transport studies of aerosols and trace species. In addition to space based winds, a high altitude airborne system flown on UAV or other advanced platforms would be of great interest for studying mesoscale dynamics and hurricanes. The Tropospheric Wind Lidar Technology Experiment (TWiLiTE) project was selected in 2005 by the NASA Earth Sun Technology Office as part of the Instrument Incubator Program. TWiLiTE will leverage significant research and development investments in key technologies made in the past several years. The primary focus will be on integrating these sub-systems into a complete molecular direct detection Doppler wind lidar system designed for autonomous operation on a high altitude aircraft, such as the NASA WB57, so that the nadir viewing lidar will be able to profile winds through the full troposphere. TWiLiTE is a collaboration involving scientists and technologists from NASA Goddard, NOAA ESRL, Utah State University Space Dynamics Lab and industry partners Michigan Aerospace Corporation and Sigma Space Corporation. NASA Goddard and it's partners have been at the forefront in the development of key lidar technologies (lasers, telescopes, scanning systems, detectors and receivers) required to enable spaceborne global wind lidar measurement. The TWiLiTE integrated airborne Doppler lidar instrument will be the first demonstration of a airborne scanning direct detection Doppler lidar and will serve as a critical milestone on the path to a fixture spaceborne tropospheric wind system. The completed system will have the capability to profile winds in clear air from the aircraft altitude of 18 h to the surface with 250 m vertical resolution and less than 2 meters per second velocity accuracy. The instrument design, technologies and predicted performance will be presented.

Gentry, Bruce↗
DOE OSTI2022

Tradeoffs in forest resilience to satellite-based estimates of water and productivity losses

Climate change is expected to intensify the global hydrological cycle via increased evapotranspiration (ET). Changes in ET have important consequences for water-related ecosystem services as well as for forest productivity. Forests play a critical role in ET: active trees sequester carbon at the expense of losing water, yet if they are not active, water remains in the trees, but productivity stalls. Here, we estimated the capacity of forests to recover (resilience) from extreme water or productivity losses based on modeled ET through remote sensing methods across the conterminous USA. Results show there is a spatial tradeoff in resilience to water or productivity losses. Forests were more resilient to water loss in the drier west, and more resilient to productivity loss in the wetter east. Still, resilience was highly heterogeneous across the continent. Projections under climate change indicate both declines and increases of up to 13% in forest resilience, with broad regional trends but high spatial heterogeneity within regions. This study brings crucial satellite-based insights on how water dynamics, and consequentially productivity and water provision in forests, might be impacted by climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deciphering the incipient phases of ice-mineral interactions as a precursor of physical weathering

Atmospheric ice formation influences Earth’s global hydrological cycle and is widely studied. In contrast, the intricacies of freeze-thaw processes in natural soils, such as whether ice nucleation on mineral surfaces is affected by biological activity, needs additional insight. In-situ ice formation on unreacted grains and grains exposed to field and laboratory weathering conditions was studied at the submicron scale using an ice nucleation chamber interfaced with an environmental scanning electron microscope. We found that ice nucleation activity differed by treatment. Unreacted grains and fungal-mineral interfaces displayed ice formation along edges and fractures. Conversely, grains with mineral coatings, seemingly from biological activity, exhibited water uptake and ice nucleation on the coatings themselves. Our results suggest that in natural soils, mineral coatings can influence where and how ice forms. This ultimately affects weathering and nutrient release to the biosphere, with direct consequences for interactions between the atmosphere and geosphere.

Lybrand, Rebecca A.↗
DOE OSTI2022

Large Divergence in Tropical Hydrological Projections Caused by Model Spread in Vegetation Responses to Elevated CO 2

Increasing atmospheric CO 2 and associated global warming are expected to alter the global hydrological cycle, thereby posing widespread threats to freshwater availability. However, future hydrological projections differ greatly between models, particularly over the tropical regions. The large difference between model projections directly limits policy planning efforts, and the responsible modeling processes remain unclear. Here, we identify the primary processes accounting for model differences in tropical hydrological changes using multiple CO 2 sensitivity experiments in the Coupled Model Intercomparison Project. We show that differences in projected changes to tropical evapotranspiration, precipitation, and surface water availability mainly arise from model representations of vegetation cover and stomatal conductance responses to elevated CO 2 and associated changes in atmospheric moisture and circulation. Atmospheric responses to sea surface warming contribute additionally to the divergence in hydrological projections. Given the importance of vegetation responses to elevated CO 2 and associated atmosphere feedbacks, our results underscore the need to improve representations of the vegetation physiological response to rising CO 2 and its coupling to the atmosphere, to provide reliable tropical hydrological projections.

54 ENVIRONMENTAL SCIENCES↗