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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Precipitation chemistry - Atmospheric loadings to the surface waters of the Indian River lagoon basin by rainfall

Rain volume and chemistry monitoring as part of the Kennedy Space Center Long Term Environmental Monitoring Program included the years 1984-1987 as part of the National Atmospheric Deposition Program. Atmospheric deposition in rainfall consisted primarily of sea salt and hydrogen ion, sulfate, nitrate, and ammonium ions. The deposition of nitrogen (a principal plant nutrient) was on the order of 200-300 metric tons per year to the surface waters.

Dreschel, Thomas W.↗
NASA NTRS1983

Possible limits on the composition of the Archaean Ocean

The potential impact of high carbon dioxide partial pressure on ocean chemistry is examined in order to investigate what constraints are imposed by the known record of chemical sedimentation through time. The evidence consists of the persistence of calcium carbonate and sulfate precipitation throughout almost the entire sedimentary rock record. A uniformitarian point of view that assumes no very great change in the conditions for the deposition of these chemical sediments. The methods of Holland (1972) are used to set limits on the composition of the water from which precipitation occurred. No inconsistencies between the sedimentary rock record and presumed higher partial pressure of carbon dioxide early in earth history, provided that high partial pressure was accompanied by a generally lower pH for seawater, higher concentrations of calcium and biocarbonate ions, and lower concentrations of carbonate and sulfate ions.

Walker, J. C. G.↗
NASA NTRS2007

Quantifying the Global Fresh Water Budget: Capabilities from Current and Future Satellite Sensors

The global water cycle is complex and its components are difficult to measure, particularly at the global scales and with the precision needed for assessing climate impacts. Recent advances in satellite observational capabilities, however, are greatly improving our knowledge of the key terms in the fresh water flux budget. Many components of the of the global water budget, e.g. precipitation, atmospheric moisture profiles, soil moisture, snow cover, sea ice are now routinely measured globally using instruments on satellites such as TRMM, AQUA, TERRA, GRACE, and ICESat, as well as on operational satellites. New techniques, many using data assimilation approaches, are providing pathways toward measuring snow water equivalent, evapotranspiration, ground water, ice mass, as well as improving the measurement quality for other components of the global water budget. This paper evaluates these current and developing satellite capabilities to observe the global fresh water budget, then looks forward to evaluate the potential for improvements that may result from future space missions as detailed by the US Decadal Survey, and operational plans. Based on these analyses, and on the goal of improved knowledge of the global fresh water budget under the effects of climate change, we suggest some priorities for the future, based on new approaches that may provide the improved measurements and the analyses needed to understand and observe the potential speed-up of the global water cycle under the effects of climate change.

Hildebrand, Peter↗
DOE OSTI2023

Arctic Mixed-Phase Cloud Base Ice Precipitation Properties During the M-PACE Field Campaign

Cloud-climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long-lived, and nearly-continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud-base properties a more appealing target for inference and evaluation of model simulations. This dataset provides a set of 25 samples from the M-PACE field campaign, all of which were retrieved using the synthesis of ARM radar and lidar measurements. The retrieved ice precipitation variables in this dataset include, among others, the ice number concentration, water content, PSD parameters, precipitation rate, mass-weighted fall velocity, vertical air motion, and effective radius, all of which are highly valuable for model evaluation and a general understanding of polar cloud sink processes. Each variable sample includes its mean value and associated uncertainty. Additional variables based on ARM measurements (liquid layer statistics, etc.) are included in this dataset as well. The retrieval algorithm and analysis of this dataset are described in Silber (JGR, 2023, https://doi.org/10.1029/2022JD038202).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Venus cloud structure and water vapor abundance from Mariner 10 observations

Observations of the Venus atmosphere with the infrared radiometer on Mariner 10 have been analyzed by Taylor (1975) in terms of the vertical distribution of opacity at wavelengths near 11 microns and 45 microns in the thermal infrared. In this paper, we discuss models of the Venus atmosphere which are consistent with the inferred opacity structure. Either a two-layer cloud structure, or a single cloud deck overlaid by a layer containing approximately 40 precipitable microns of water vapor, would have the required limb-darkening characteristics at the wavelengths of observation.

Taylor, F. W.↗
DOE OSTI2023

Insights into the relation between vertical cloud structure and dynamics of three polar lows: Observations from COMBLE

The vertical structure of three polar lows is described using profiling radar, lidar, and passive remote sensors deployed at a coastal site in northern Norway. The data were collected as part of the Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE). These data are examined in the context of satellite imagery, operational weather radar reflectivity imagery, and output from the AROME-Arctic model. A comparison to satellite images shows that AROME-Arctic captured the polar lows well. All three polar lows form in marine cold-air outbreaks and are surrounded by open-cellular convection typical of such outbreaks. Two of the lows form in a forward shear environment, and one under reverse shear. Initially, the three polar lows are comma-shaped; two of them transition to be more spirali-form at their mature stage and have mostly cloud-free warm cores. The warm cores are the result of a warm-seclusion process. All three lows have stratiform precipitation bands, marked by little cloud liquid water, and rather high surface precipitation rate. The vertical drafts and turbulence in these stratiform clouds are generally weak. In conclusion, all three lows also have convective clouds, which have stronger vertical drafts, stronger turbulence, and pockets of high liquid water content.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Convergent Hydraulic Redistribution and Groundwater Access Supported Facilitative Dependency Between Trees and Grasses in a Semi‐Arid Environment

Abstract Hydraulic redistribution is the transport of water from wet to dry soil layers, upward or downward, through plant roots. Often in savanna and woodland ecosystems, deep‐rooted trees, and shallow‐rooted grasses coexist. The degree to which these different species compete for or share soil‐water derived from precipitation or groundwater, as well as how these interactions are altered by hydraulic redistribution, is unknown. We use a multilayer canopy model and field observations to examine how the presence of deep, but tree‐root accessible, groundwater impacts seasonal patterns of hydraulic redistribution, and interaction between coexisting vegetation species in a semiarid riparian woodland (US‐CMW). Based on the simulation, trees absorb moisture at the water table (∼10 m depth) and release it in the shallow soil depth (0–3 m) during the dry pre‐monsoon season. We observed the occurrence of a new convergent hydraulic redistribution pattern during the monsoon season, where moisture is transported from both the near‐surface (0–0.5 m) and the water table to intermediate soil layers (1–5 m) through tree roots. We found that hydraulic redistribution demonstrates a growth facilitation effect at this site, supporting 49% of growing season tree transpiration and 14% of the grass transpiration. Compared to a similarly structured upland savanna without accessible groundwater, the riparian site shows an increased amount of hydraulically redistributed water and more facilitative water use between coexisting grasses and trees. These results shed light on the linkage between accessible groundwater and the role of hydraulic redistribution on the interaction between deep‐rooted and shallow‐rooted vegetation.

Lee, E.↗
NASA NTRS1995

Low-frequency variations in the atmospheric branch of the global hydrological cycle

The annual variation of the hydrological cycle is illustrated in terms of hemispheric-mean hydrological variables for the Northern and Southern Hemispheres, while the intraseasonal variations of the global hydrological cycle are illustrated with mean values over two hemispheres that form an east-west partition of the globe. This partition is defined by the 60 deg E-120 deg W great circle and was chosen so that the mean precipitation difference and the divergent water vapor transport between the two hemispheres was maximized. Two years (1979-80) of daily precipitation estimates from the Goddard Laboratory for Atmospheres an 14 years (1979-92) of upper-air data generated by the Global Data Assimilation System at the National Meteorological Center are used in making quantitative estimates of the annual and intraseasonal variations in the global hydrological cycle. The annual variations in hemispheric-mean precipitation (P-circumflex) and water vapor flux divergence (del(vector differential operator) dot Q-circumflex) for the Northern and Southern Hemispheres are comparable with amplitudes of about 0.5 approximately 0.7 mm/day. Both (P-circumflex) and (del(vector differential operator) dot Q-circumflex) vary annually in a coherent way in each hemisphere so that water vapor diverges from the winter hemisphere, where (P-circumflex) reaches its minimum, to the summer hemisphere, where (P-circumflex) attains its maximum. In fact, the hemispheric-mean divergence of water vapor flux changes sign during the annual cycle. Intraseasonal variations of hemispheric-mean precipitation mean P-tilde, evaporation mean E-tilde, and water vapor flux divergence mean del (vector differential operator) dot Q-tilde in the two hemisphres in the east-west direction are comparable with amplitudes of about 0.1 approximately 0.2 mm/day, although amplitudes in some cases exceed 0.3 mm/day. Hemispheric-mean precipitation mean P-tilde varies coherently in opposite phase for the two hemispheres, while mean del (vector differential operator) dot Q-tilde varies so that water vapor diverges from the hemisphere of maximum mean P-tilde to the hemisphere to the hemisphere of minimum mean P-tilde. Intraseasonal variations of mean P-tilde, mean E-tilde, and mean del (vector differential oprator) dot Q-tilde are in accord with the eastward propagation of the intraseasonal global divergent circulation.

Chen, Tsing-Chang↗
NASA NTRS2004

NASA Data for Water Resources Applications

Water Management Applications is one of twelve elements in the Earth Science Enterprise National Applications Program. NASA Goddard Space Flight Center is supporting the Applications Program through partnering with other organizations to use NASA project results, such as from satellite instruments and Earth system models to enhance the organizations critical needs. The focus thus far has been: 1) estimating water storage including snowpack and soil moisture, 2) modeling and predicting water fluxes such as evapotranspiration (ET), precipitation and river runoff, and 3) remote sensing of water quality, including both point source (e.g., turbidity and productivity) and non-point source (e.g., land cover conversion such as forest to agriculture yielding higher nutrient runoff). The objectives of the partnering cover three steps of: 1) Evaluation, 2) Verification and Validation, and 3) Benchmark Report. We are working with the U.S. federal agencies including the Environmental Protection Agency (EPA), the Bureau of Reclamation (USBR) and the Department of Agriculture (USDA). We are using several of their Decision Support Systems (DSS) tools. This includes the DSS support tools BASINS used by EPA, Riverware and AWARDS ET ToolBox by USBR and SWAT by USDA and EPA. Regional application sites using NASA data across the US. are currently being eliminated for the DSS tools. The current NASA data emphasized thus far are from the Land Data Assimilation Systems WAS) and MODIS satellite products. We are currently in the first two steps of evaluation and verification validation. Water Management Applications is one of twelve elements in the Earth Science Enterprise s National Applications Program. NASA Goddard Space Flight Center is supporting the Applications Program through partnering with other organizations to use NASA project results, such as from satellite instruments and Earth system models to enhance the organizations critical needs. The focus thus far has been: 1) estimating water storage including snowpack and soil moisture, 2) modeling and predicting water fluxes such as evapotranspiration (ET), precipitation and river runoff, and 3) remote sensing of water quality, including both point source (e.g., turbidity and productivity) and non-point source (e.g., land cover conversion such as forest to agriculture yielding higher nutrient runoff). The objectives of the partnering cover three steps of 1) Evaluation, 2) Verification and Validation, and 3) Benchmark Report. We are working with the U.S. federal agencies the Environmental Protection Agency (EPA), the Bureau of Reclamation (USBR) and the Department of Agriculture (USDA). We are using several of their Decision Support Systems (DSS) tools. T us includes the DSS support tools BASINS used by EPA, Riverware and AWARDS ET ToolBox by USBR and SWAT by USDA and EPA. Regional application sites using NASA data across the US. are currently being evaluated for the DSS tools. The current NASA data emphasized thus far are from the Land Data Assimilation Systems (LDAS) and MODIS satellite products. We are currently in the first two steps of evaluation and verification and validation.

Toll, David↗
DOE OSTI2021

Grizzly Development for Light Water Reactor and Advanced Reactor Applications in Fiscal Year 2021

This report summarizes work performed during Fiscal Year (FY) 2021 at Idaho National Laboratory (INL) for the U.S. Department of Energy’s Nuclear Engineering Advanced Modeling and Simulation (NEAMS) program for the Structural Materials and Chemistry Technical Area in the work package entitled “MS-21IN050106 - Structural Materials - INL.” This effort mainly focused on development and application of capabilities for engineering-scale analysis of nuclear reactor structural components in the Grizzly and BlackBear codes. These efforts include performance improvements and application of models for high-temperature component response, cluster dynamics modeling of precipitation in light water reactor pressure vessel steel, engineering-scale capability development in the areas of concrete simulation and reactor pressure vessel analysis, and preparation for and conducting an independent assessment of the adherence of these codes to software quality standards.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An Overview of ARTMIP's Tier 2 Reanalysis Intercomparison: Uncertainty in the Detection of Atmospheric Rivers and Their Associated Precipitation

Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags--binary fields indicating the presence or absence of atmospheric rivers--of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six-hourly tags in the Japanese 55-year Reanalysis (JRA-55). Due to a higher climatological mean for integrated water vapor transport in MERRA-2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. We found that the fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

An Overview of ARTMIP’s Tier 2 Reanalysis Intercomparison: Uncertainty in the Detection of Atmospheric Rivers and their Associated Precipitation

Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags--binary fields indicating the presence or absence of atmospheric rivers--of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six-hourly tags in the Japanese 55-year Reanalysis (JRA-55). Due to a higher climatological mean for integrated water vapor transport in MERRA-2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. The fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.

ARTMIP↗
DOE OSTI2023

Arctic Mixed-Phase Cloud Base Ice Precipitation Properties Over the NSA Site

Cloud-climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long-lived, and nearly continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud-base properties a more appealing target for inference and evaluation of model simulations. This data set provides more than 1800 samples of cloud-base ice precipitation properties over Utqiagvik, North Slope of Alaska, all of which were retrieved using the synthesis of ARM radar and lidar measurements. The retrieved ice precipitation variables in this data set include, among others, the ice number concentration, water content, PSD parameters, precipitation rate, mass-weighted fall velocity, vertical air motion, and effective radius, all of which are highly valuable for model evaluation and a general understanding of polar cloud sink processes. Each variable sample includes its mean value and associated uncertainty. Additional variables based on ARM measurements (liquid layer statistics, etc.) are included in this data set. The retrieval algorithm and analysis of this data set are described in Silber (JGR, 2023, https://doi.org/10.1029/2022JD038202).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Ensemble Estimation of Historical Evapotranspiration for the Conterminous U.S.

Abstract Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall‐to‐wall explanatory variable maps to generate CONUS‐wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national‐scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.

Environmental Sciences & Ecology↗
NASA NTRS1988

The causes for geographical variations in OS187/OS186 at the Cretaceous-Tertiary boundary

Researchers at Yale has approached the problem of the osmium isotopic composition of marine deposits formed in contact with both oxidized and reduced bottom waters. The measured (187) Os/(186) Os ratios of modern bulk sediment can be explained using mixing equations involving continental detrital, volcaniclastic, cosmogenic and hydrogeneous components. These studies show that sediments deposited under reducing marine conditions contain a hydrogenous component which is enriched in Re and has a radiogenic (187) Os/(186) Os ratio. The presence of such a hydrogenous component in the marine fish clay at Stevns Klint can account for the elevation of its (187) Os/(186) Os ration above the expected meteoritic value. Mass balance considerations require the Re/Os ratio of the phase precipitated from the terminal Cretaceous sea at Stevns Klint to have been about one tenth the value observed in contemporary deposits in the Black Sea, assuming Re has not been lost (or Os gained) subsequent to precipitation. In continental sections, the elevation of the (187) Os/(186) Os ratio in boundary layers may be due to precipitation from continental waters of crustally-derived radiogenic osmium either contemporaneous with the meteoritic (or mantle) osmium deposition or later during diagenesis.

Turekian, K. K.↗
DOE OSTI2020

Assessment of rainfall variability and future change in Brazil across multiple timescales

Abstract Rainfall variability change under global warming is a crucial issue that may have a substantial impact on society and the environment, as it can directly impact biodiversity, agriculture, and water resources. Observed precipitation trends and climate change projections over Brazil indicate that many sectors of society are potentially highly vulnerable to the impacts of climate change. The purpose of this study is to assess model projections of the change in rainfall variability at various temporal scales over sub‐regions of Brazil. For this, daily data from 30 CMIP5 models for historical (1900–2005) and future (2050–2100) experiments under a high‐emission scenario are used. We assess the change in precipitation variability, applying a band‐pass filter to isolate variability on daily, weekly, monthly, intra‐seasonal, and El Nino Southern Oscillation (ENSO) time scales. For historical climate, simulated precipitation is evaluated against observations to establish model reliability. The results show that models largely agree on increases in variability on all timescales in all sub‐regions, except on ENSO timescales where models do not agree on the sign of future change. Brazil will experience more rainfall variability in the future that is, drier or more frequent dry periods and wetter wet periods on daily, weekly, monthly, and intra‐seasonal timescales, even in sub‐regions where future changes in mean rainfall are currently uncertain. This may provide useful information for climate change adaptation across, for example, the agriculture and water resource sectors in Brazil.

Alves, Lincoln M.↗
DOE OSTI2021

Attribution of Snowpack Errors to Simulated Temperature and Precipitation in E3SMv1 Over the Contiguous United States

Abstract Snow water equivalent (SWE), temperature, and precipitation biases and trends are evaluated in the atmosphere‐land simulations of the Energy Exascale Earth System Model version 1 (E3SMv1) in comparison to the Community Earth System Model version 2 (CESM2) and two other models using the ground measurement‐based University of Arizona (UA) snow product. SWE, temperature, and precipitation biases are highest in magnitude in the Western contiguous United States (CONUS). SWE errors are attributed to temperature and precipitation through multiple linear regressions of normalized errors, the coefficients of which represent the sensitivities to temperature and precipitation errors. SWE errors are more sensitive to temperature errors throughout the CONUS. Model SWE and temperature trends are generally opposite from UA product trends in the Western CONUS. SWE trend errors are also attributed to temperature and precipitation trend errors using multiple linear regressions of normalized trend errors. SWE trend errors are more sensitive to those of precipitation at higher elevations (>1,500 m) in the Western CONUS in these simulations. Thus, the sensitivity to temperature and precipitation differ for SWE errors and its trend errors. Furthermore, the SWE trend errors are more sensitive to temperature and precipitation in the atmosphere‐ocean coupled simulations in which the atmosphere‐land is coupled to an active ocean model. These results suggest that both errors in simulated temperature and precipitation contribute to SWE errors.

Meteorology & Atmospheric Sciences↗