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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Role of Leaf Area Changes Within Plant CO 2 Physiological Impacts on the Global Hydrological Cycle

Rising atmospheric CO 2 concentrations enhance greenhouse warming and drive changes to plant physiology, leading to innumerable climate impacts. This study explores the impacts of plant responses on hydrological cycling at 2x preindustrial CO 2 concentrations by analyzing simulations that isolate plant physiological effects using the Community Earth System Model versions 1 and 2. We find that leaf area growth increases canopy evaporation, which offsets transpiration declines, and dampens changes in global mean evapotranspiration, precipitation, and runoff in a CESM2 experiment with dynamic leaf area. These leaf area impacts are also evident in the differences between CESM1 and CESM2, with CESM2 better capturing observed leaf area magnitudes but potentially overestimating leaf area-CO 2 sensitivity, highlighting the importance of plant CO 2 physiology on hydrological cycle changes and the need to improve its representation in climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Spatial and temporal variability of tritium in precipitation within South Africa and it's bearing on hydrological studies

Tritium, the radioactive isotope of hydrogen, has been used to understand groundwater recharge processes for decades. The current variation of tritium in the atmosphere is largely attributed to stratospheric production and fall out rates as well as global circulation phenomena controlling the hydrological cycle. Global controls on the variability in atmospheric tritium activity are poorly suited to explain local variation and tritium activities in precipitation are often assumed to be uniform over both local and regional catchments and watersheds. This assumption can result in both over and under estimation of modern recharge within an aquifer when using tritium as the recharge proxy. In order to minimize the inherent prediction residuals associated with tritium based recharge investigations, the variability of tritium in precipitation was modelled from 127 spatial precipitation samples taken over a two year period, combined with a 76 precipitation sample group-set taken over a one year period in a single location. Precipitation events were traced backward in time, from the point of collection, using HYSPLIT modelling to ascertain the origins of moisture content as well as the altitudes of moisture origin reached along the particle track. Tritium activities, collected over a one year period in Paarl, range from 0.45 to 4.16 TU and have a mean of 1.59 TU. Spatial storm events in the Western Cape in 2017 and 2018 had a range from 0 to 2.2 and 0.37 to 3.27 TU, respectively, with mean activities of 1.18 (n = 34) and 1.25 TU (n = 32). Both storm events had similar tritium variability (σ = 0.5 n = 35 and 0.48 n = 32). Regional precipitation events had the largest range of tritium activities (0.55–12.2 TU). Although not all tritium activities can be explained by interrogating the water mass origin, this study suggests that approximately 90% of events can be completely or partially attributed to the origin of the water mass. The variability of tritium, both spatially and temporally, was higher than expected, confirming that when uniform tritium inputs are used, the groundwater system would provide inaccurate modern recharge estimates. Higher spatial resolution of tritium variation in precipitation for a particular region will improve our ability to relate tritium activities in groundwater to local precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Historical sensible-heat-flux variations key to predicting future hydrologic sensitivity

Under anthropogenic climate change (CC), the global hydrological cycle intensifies at a rate known as hydrologic sensitivity (HS). Global climate models (GCMs) exhibit substantial uncertainty in HS. Past work suggests that another form of HS, derived from internal climate variability (IV), is useful for constraining this uncertainty. However, these two forms of HS are weakly related. Here we show that decomposing HS under both CC and IV, based on the global energy budget, provides insight into the likely range of future HS. We find that sensible heat exchange between the atmosphere and ocean is not accounted for in the atmospheric energy budget under IV, masking the connection between HS under IV and CC. Removing this term, a closer relationship emerges. We use observations in conjunction with this relationship to suggest an upward shift in the likely range of future HS (66% confidence interval: 2.00–2.36 W m -2 K -1

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effects of Improved Simulation of Precipitation on Evapotranspiration and Its Partitioning Over Land

Evapotranspiration (ET) is a key component of the global hydrological cycle, which is strongly modulated by the occurrence of different rainfall intensities. Global climate models (GCMs) commonly suffer from “too much light rain” and a negative bias in the ratio of transpiration (T) to ET (T/ET). It is unclear whether these biases are related. Here, in this work, we show that with the improved simulation of probability density functions of rainfall intensity by suppressing light-rain occurrence using a stochastic convection parameterization in the NCAR CESM1.2, the canopy T increases in tropical forests while evaporation from canopy interception and bare soil decreases. The simulated T/ET is increased by 2.5% globally and up to 8% regionally, primarily attributable to reduced fraction of wet leaves due to less frequent light rain despite its weak intensity. These results imply that excessive light rain is an important cause of the negative T/ET bias in GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Numerical Water Tracers in the Atmospheric Component of the Energy Exascale Earth System Model: Implementation and Changes in Moisture Origin

Numerical water tracers are implemented in the Energy Exascale Earth System Model version 2. Simulations performed with the water‐tag‐enabled model for both pre‐industrial and future greenhouse gas concentrations reveal a marked increase in the role of mid‐latitude and southern subtropical regions as exporters of atmospheric moisture—to the extratropical upper troposphere and the tropical free troposphere. For the latter, the northward shift of the Intertropical Convergence Zone increases cross‐hemispheric transport of subtropical water vapor to the Northern Hemisphere. In the polar regions, most of the lower tropospheric moistening instead arises from increases in local evaporation. These findings illustrate the utility of the water tags, underscore critical changes in global hydrologic cycle, and provide insight into atmospheric dynamics under future climate scenarios. For applications when a global grid is desired, we additionally propose a novel statistical reconstruction, based on copula modeling, of the joint distribution of origin of water vapor, which reduces the number of tracers from order $\mathcal{O}\left({n}^{2}\right)$to order $\mathcal{O}(n)$, substantially ameliorating the considerable computational cost of water tracers. This statistical reconstruction is particularly beneficial to the interpretation of the relationship between latitude and longitude of origin of moisture over the tropical oceans and in the lower troposphere over land.

copula modeling↗
DOE OSTI2023

Another Year of Record Heat for the Oceans

Abstract Changes in ocean heat content (OHC), salinity, and stratification provide critical indicators for changes in Earth’s energy and water cycles. These cycles have been profoundly altered due to the emission of greenhouse gasses and other anthropogenic substances by human activities, driving pervasive changes in Earth’s climate system. In 2022, the world’s oceans, as given by OHC, were again the hottest in the historical record and exceeded the previous 2021 record maximum. According to IAP/CAS data, the 0–2000 m OHC in 2022 exceeded that of 2021 by 10.9 ± 8.3 ZJ (1 Zetta Joules = 10 21 Joules); and according to NCEI/NOAA data, by 9.1 ± 8.7 ZJ. Among seven regions, four basins (the North Pacific, North Atlantic, the Mediterranean Sea, and southern oceans) recorded their highest OHC since the 1950s. The salinity-contrast index, a quantification of the “salty gets saltier—fresh gets fresher” pattern, also reached its highest level on record in 2022, implying continued amplification of the global hydrological cycle. Regional OHC and salinity changes in 2022 were dominated by a strong La Niña event. Global upper-ocean stratification continued its increasing trend and was among the top seven in 2022.

Meteorology & Atmospheric Sciences↗
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↗
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↗
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↗
DOE OSTI2022

Characteristics and Variability of Winter Northern Pacific Atmospheric River Flavors

Abstract Atmospheric rivers (ARs) are intensive poleward moisture transport events that are essential to the global hydrological cycle and are often linked to extreme weather events. We categorize the winter North Pacific ARs into two “flavors”: wind‐dominated (windy ARs) and moisture‐dominated (wet ARs) using 40 years of hourly data from fifth generation of the European Centre for Medium‐Range Weather Forecasts Interim Reanalysis. We compare the differences between windy ARs and wet ARs including the lifecycle characteristics (such as genesis locations and changes of meteorological elements through the lifecycle), overall AR frequency, landfall impacts, and variability. The windy ARs are more likely to occur in the midlatitudes, while wet ARs are more active in the subtropics. Windy ARs are associated with intensive surface pressure lows, where the strong pressure gradient can support the strong wind within ARs. Due to larger size and longer lifetime, wet ARs are more likely to produce more precipitation over a lifecycle. By scaling the landfalling ARs, we show that wet ARs dominate the high‐category ARs (Category 4 and 5) with higher spatial frequency and more precipitation, and windy ARs have higher contributions in the lower AR categories especially over British Columbia. Windy ARs are modulated by El Niño Southern Oscillation (ENSO) teleconnections via the anomalous geopotential height and extended subtropical jet. Wet ARs are affected by the anomalous sea surface temperature over the midlatitudes related to ENSO. Sensitivity analysis with an alternate AR detection algorithm shows consistent results on AR flavors but with disagreement on the amplitude.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Description and Evaluation of a New Deep Convective Cloud Model Considering In-cloud Inhomogeneity

Convections still need to be parameterized in general circulation models (GCMs) in the coming decades. Performances of GCMs are significantly influenced by the convection schemes used. In contrast to most conventional cloud models that ignore in-cloud inhomogeneities, a new convective cloud model explicitly considering in-cloud inhomogeneities is developed. The new model adopts a single bulk plume approach, but divides the plume into a series of interacting sub-plumes in order to mimic the transition from the plume core to its edges. We implemented the new cloud model in NCAR Community Atmosphere Model version 5.0 (CAM5) and evaluated its performance. Single-column tests show a stronger mass flux profile and low-level detrainment with the new model. In global simulations, the long-lasting wet bias in the tropical free troposphere of CAM5 is alleviated. Spatial pattern and intensity distribution of precipitation is improved, but the global hydrological cycle is slightly over-enhanced. The diurnal cycle of tropical precipitation is also better captured though the precipitation peak still occurs earlier than the observations and the amplitude of the cycle tends to weaken. MJO simulation is slightly improved with the new scheme. In addition, the new cloud model generated more tropical cyclones, in better agreement with observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Mesoscale Convective Systems Represented in High Resolution E3SMv2 and Impact of New Cloud and Convection Parameterizations

Mesoscale convective systems (MCSs) play an important role in modulating the global hydrological cycle, general circulation, and radiative energy budget. In this study, we evaluate MCS simulations in the second version of U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv2). E3SMv2 atmosphere model (EAMv2) is run at the uniform 0.25? horizontal resolution. We track MCSs consistently in the model and observations using the PyFLEXTRKR algorithm, which defines MCS based on both cloud-top brightness temperature (Tb) and surface precipitation. Results from using Tb only to define MCS, commonly used in previous studies, are also discussed. Furthermore, sensitivity experiments are performed to examine the impact of new cloud and convection parameterizations developed for EAMv3 on simulated MCSs. Our results show that EAMv2 simulated MCS precipitation is largely underestimated in the tropics and contiguous United States. This is mainly attributed to the underestimated precipitation intensity in EAMv2. In contrast, the simulated MCS frequency becomes more comparable to observations if MCSs are defined only based on cloud-top Tb. The Tb-based MCS tracking method, however, includes many cloud systems with very weak precipitation which conflicts with the MCS definition. This result illustrates the importance of accounting for precipitation in evaluating simulated MCSs. We also find that the new physics parameterizations help increase the relative contribution of convective precipitation to total precipitation in the tropics, but the simulated MCS properties are generally not improved. This suggests that simulating MCSs will remain a challenge for the next version of E3SM.

Zhang, Meng↗
DOE OSTI2023

Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System

Seasonal variability of the global hydrologic cycle directly impacts human activities, including hazard assessment and mitigation, agricultural decisions, and water resources management. This is particularly true across the High Mountain Asia (HMA) region, where availability of water resources can change depending on local seasonality of the hydrologic cycle. Forecasting the atmospheric states and surface conditions, including hydrometeorologically relevant variables, at subseasonal-to-seasonal (S2S) lead times of weeks to months is an area of active research and development. NASA's Goddard Earth Observing System (GEOS) S2S prediction system has been developed with this research goal in mind. Here, we benchmark the forecast skill of GEOS-S2S (version 2) hydrometeorological forecasts at 1–3-month lead times in the HMA region, including a portion of the Indian subcontinent, during the retrospective forecast period, 1981–2016. To assess forecast skill, we evaluate 2 m air temperature, total precipitation, fractional snow cover, snow water equivalent, surface soil moisture, and terrestrial water storage forecasts against the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and independent reanalysis data, satellite observations, and data fusion products. Anomaly correlation is highest when the forecasts are evaluated against MERRA-2 and particularly in variables with long memory in the climate system, likely due to the similar initial conditions and model architecture used in GEOS-S2S and MERRA-2. When compared to MERRA-2, results for the 1-month forecast skill range from an anomaly correlation of R anom =0.18 for precipitation to R anom =0.62 for soil moisture. Anomaly correlations are consistently lower when forecasts are evaluated against independent observations; results for the 1-month forecast skill range from R anom =0.13 for snow water equivalent to R anom =0.24 for fractional snow cover. We find that, generally, hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system's ability to forecast HMA hydrometeorology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Extratropical shortwave cloud feedbacks in the context of the global circulation and hydrological cycle

Shortwave (SW) cloud feedback ($SW_{FB}$) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs participating in the sixth assessment report exceed 5K, above the fifth assessment report ‘likely’ maximum (4.5K) due to extratropical $SW_{FB}$’s that are more positive than those simulated in the previous generation of GCMs. Here we show that across 57 GCMs Southern Ocean $SW_{FB}$ can be predicted from the sensitivity of column-integrated liquid water mass (LWP) to moisture convergence and to surface temperature. In this work, the response of LWP to moisture convergence and the response of albedo to LWP anti-correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean-state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean $SW_{FB}$— inconsistent with extreme ECS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Estimating snow cover from high-resolution satellite imagery by thresholding blue wavelengths

We report the extent and duration of snow cover, a critical component of the hydrologic cycle and the global climate system, is expected to shift dramatically under climate change. Therefore, developing high-resolution assessments of snow cover change is crucial for estimating the impact of changing snow cover on watershed and ecosystems processes in cold regions. Remote sensing tools provide a powerful method for mapping snow-covered area (SCA) across a landscape. The most common method for estimating SCA utilizes the normalized difference snow index (NDSI), which relies on spectral measurements in the shortwave-infrared wavelengths (SWIR). NDSI can effectively estimate catchment- to regional-scale SCA, but it cannot be used to assess fine-scale SCA because of current limitations on the spatial resolution of satellite-derived SWIR measurements. Here, we map SCA using a threshold of blue wavelengths and high-resolution satellite imagery. The thresholding method, which we call the Blue Snow Threshold algorithm (BST), has previously been used with digital camera imagery. We refine and automate the algorithm for use with cloud-free high-resolution satellite imagery and find that the BST can be used to assess fine-scale SCA. For validation, we compared BST-derived estimates of SCA to a) airborne lidar surveys, b) Landsat fractional SCA, and c) snow disappearance dates from Snow Telemetry (SNOTEL) stations. When compared to airborne lidar surveys of SCA, the BST predicted SCA had a range of F-scores between 0.81 and 0.94 in four study areas in California and Colorado. We also found general agreement between SCA and snow disappearance at multiple SNOTEL sites across the western United States. Given the relatively recent availability of high-resolution satellite imagery with spectral measurements in the visible wavelengths but lacking in SWIR, the BST offers a reliable and easy-to-apply tool for examining fine-scale snow-related processes.

54 ENVIRONMENTAL SCIENCES↗