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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Extratropical Cloud Feedback Constrained by Cloud Sources and Sinks in Cyclones

Constraining cloud feedback in global climate models (GCMs) using observations is important for establishing accurate predictions of future climate. Uncertainty in shortwave cloud feedback (SW FB ) dominates uncertainty in total cloud feedback. Recent studies show a shift toward more positive extratropical SW FB in the latest generations of GCMs leading to the emergence of very high equilibrium climate sensitivity (ECS). In this study, we use precipitation efficiency and albedo susceptibility to constrain liquid water path (LWP) response to warming and SW FB in the Southern Ocean (SO; 50°–80°S). We analyze precipitation in extratropical cyclones (ECs) to learn about extratropical condensed water sink processes, combined with observations of clouds and moisture convergence, and use the analysis to better understand and constrain SW FB . We utilize a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model, version 6 (CAM6), to provide a constraint on SW FB based on observations from Clouds and the Earth’s Radiant Energy System (CERES) and Multisensor Advanced Climatology of LWP (MAC-LWP). We apply Gaussian process regression to emulate the model response to all parameters perturbed in the PPE. Confronting the emulator output with observations provides a new estimated response of Earth to global warming. Furthermore, our new estimates of SO LWP reduce the PPE range by 66%–72%, which results in a shortwave cloud radiative effect estimated range that is 27%–34% less than the PPE range. Observations suggest a more positive SO SW FB than the Community Earth System Model, version 2 (CESM2), and consequently do not reject the high climate sensitivity GCMs emerging from the Coupled Model Intercomparison Project phase 6 (CMIP6).

Atmosphere↗
NASA NTRS2020

Large-Scale Influences on Atmospheric River–Induced Extreme Precipitation Events Along the Coast of Washington State

Transient, narrow plumes of strong water vapor transport, referred to as Atmospheric Rivers (ARs) are responsible for much of the precipitation along the west coast of the United States. Along the coast of Oregon and Washington, the most intense cool season precipitation events are almost always induced by an AR and can result in detrimental impacts on society due to mudslides and flooding. It is therefore important to understand the large scale influence on extreme AR events so that they can be accurately predicted on timescales ranging from numerical weather prediction to seasonal forecasts. Here, characteristics of ARs that result in observed extreme precipitation events are compared to typical ARs on the coast of Washington State using data from the Modern Era Retrospective analysis for Research and Applications, Version 2. In addition to more intense water vapor transport, notable differences in the synoptic scale forcing are present during extreme precipitation events that are not present during typical AR events. In particular, an anomalously deep low pressure system is stationed to the west in the Gulf of Alaska, alongside a jet streak overhead. Attention will also be given to subseasonal and seasonal teleconnection patterns that are known to influence the weather in the Pacific Northwest of the United States. While little influence can be seen from the phase of the El Nino Southern Oscillation, Pacific Decadal Oscillation, and Pacific North American Pattern, the Madden Julian Oscillation (MJO) can play a role in determining the strength of precipitation associated with in AR on the Washington Coast. Lastly, interactions between the MJO and other teleconnection patterns will be explored to determine key features that should be investigated when making subseasonal predictions for AR activity and the associated precipitation in the Pacific Northwest.

Collow, Allison↗
DOE OSTI2020

AmeriFlux US-LS1 San Pedro River Lewis Springs Sacaton Grassland

This is the AmeriFlux version of the carbon flux data for the site US-LS1 San Pedro River Lewis Springs Sacaton Grassland. Site Description - This is a riparian grassland located along an old alluvial terrace along the banks of the entrenched San Pedro River in southeastern Arizona. Site climate is semiarid with monsoonal (Jul-Sep) rainfall. The grasses access groundwater (depth of 2-4 m)from an alluvial aquifer recharged elsewhere. Site water balance is not closed and ET greatly exceeds precipitation. The perennial bunchgrasses use both rainfall, groundwater and occasional flood water. This groundwater-using ecosystem is far more ebulliant and productive than the upland vegetation around it (shrublands and grasslands) outside of the San Pedro River corridor.

Scott, Russell↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-LS1 San Pedro River Lewis Springs Sacaton Grassland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-LS1 San Pedro River Lewis Springs Sacaton Grassland. This is the FLUXNET version of the carbon flux data for the site US-LS1 San Pedro River Lewis Springs Sacaton Grassland produced by applying the standard ONEFlux (1F) software. Site Description - This is a riparian grassland located along an old alluvial terrace along the banks of the entrenched San Pedro River in southeastern Arizona. Site climate is semiarid with monsoonal (Jul-Sep) rainfall. The grasses access groundwater (depth of 2-4 m)from an alluvial aquifer recharged elsewhere. Site water balance is not closed and ET greatly exceeds precipitation. The perennial bunchgrasses use both rainfall, groundwater and occasional flood water. This groundwater-using ecosystem is far more ebulliant and productive than the upland vegetation around it (shrublands and grasslands) outside of the San Pedro River corridor.

Scott, Russell [USDA-ARS]↗
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↗
DOE OSTI2020

Contrasting phase changes of precipitation annual cycle between land and ocean under global warming

The annual cycle of precipitation is a fundamental aspect of the water cycle with global ramification. Climate warming induces a robust phase delay1-5 in zonal mean tropical precipitation concomitant with an amplitude enhancement6-8. Here, we find a large land ocean contrast in the phase response of precipitation annual cycle, with a phase delay over land and a phase advance over ocean as climate warms. The phase delay over land is mainly attributed to the increase in the effective heat capacity of the atmosphere, while the phase advance over ocean is associated with a precipitation shift from land to ocean during the peak rainy season. Through the energetic constraint, this precipitation shift is closely related to the opposite changes in the amplitude of surface temperature annual cycle between land and ocean, both as consequences of basic climate feedback processes under global warming: weakening of the summer trade wind over the tropical ocean increases the surface temperature seasonal amplitude through evaporation, while an increase of the atmospheric effective heat capacity and surface cooling feedback induces opposite temperature amplitude changes over the tropical land. The opposite precipitation phase changes between land and ocean will have myriad implications for terrestrial/marine ecosystems and human activities.

Song, Fengfei↗
NASA NTRS2008

Potential Application of Airborne Passive Microwave Observations for Monitoring Inland Flooding Caused by Tropical Cyclones

Inland flooding from tropical cyclones can be a significant factor in storm-related deaths in the United States and other countries. Information collected during NASA tropical cyclone field studies suggest surface water and flooding induced by tropical cyclone precipitation can be detected and therefore monitored using passive microwave airborne radiometers. In particular, the 10.7 GHz frequency of the NASA Advanced Microwave Precipitation Radiometer (AMPR) flown on the NASA ER-2 has demonstrated high resolution detection of anomalous surface water and flooding in numerous situations. This presentation will highlight the analysis of three cases utilizing primarily satellite and airborne radiometer data. Radiometer data from the 1998 Third Convection and Moisture Experiment (CAMEX-3) are utilized to detect surface water during landfalling Hurricane Georges in both the Dominican Republic and Louisiana. A third case is landfalling Tropical Storm Gert in Eastern Mexico during the Tropical Cloud Systems and Processes (TCSP) experiment in 2005. AMPR data are compared to topographic data and vegetation indices to evaluate the significance of the surface water signature visible in the 10.7 GHz information. The results of this study suggest the benefit of an aircraft 10 GHz radiometer to provide real-time observations of surface water conditions as part of a multi-sensor flood monitoring network.

Hood, Robbie E.↗
NASA NTRS1983

A meteorologically-driven yield reduction model for spring and winter wheat

A yield reduction model for spring and winter wheat was developed for large-area crop condition assessment. Reductions are expressed in percentage from a base yield and are calculated on a daily basis. The algorithm contains two integral components: a two-layer soil water budget model and a crop calendar routine. Yield reductions associated with hot, dry winds (Sukhovey) and soil moisture stress are determined. Input variables include evapotranspiration, maximum temperature and precipitation; subsequently crop-stage, available water holding percentage and stress duration are evaluated. No specific base yield is required and may be selected by the user; however, it may be generally characterized as the maximum likely to be produced commercially at a location.

Ravet, F. W.↗
DOE OSTI2021

Evaluation of Subseasonal-to-Seasonal (S2S) precipitation forecast from the North American Multi-Model ensemble phase II (NMME-2) over the contiguous U.S.

The second phase of the North America Multi-Model Ensemble (NMME-2) provides globally available Subseasonal-to-Seasonal (S2S) precipitation forecasts with a daily resolution. The S2S precipitation forecasts are getting increasing attention for their potentials in providing hydrometeorological forcing information for water resources planning at an extended range. However, the forecast skills of many existing S2S forecast products will significantly decrease when the lead time increases, hindering their applicability for watershed-scale hydrologic modeling. Therefore, forecast validation and large-scale evaluation are of great importance for water resources planning and hydrological applications. In this study, we comprehensively evaluate the S2S precipitation forecasts from the NMME-2 dataset over the contiguous United States (CONUS) and during the study period from 1982 to 2011. Three aspects of precipitation forecast capabilities are compared and analyzed: bias, skill scores, and the ability to predict extreme precipitation events. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) is used as ground truth reference. Differs from other regional forecast validation study, we further examined and analyzed the dependences of NMME-2 precipitation forecast skills according to different seasonality, geographical locations, and lead times. Results show that the forecast biases are not sensitive to lead times but are seasonally dependent of all NMME-2 models. Overestimations are found in the Western U.S. in cooler seasons while underestimations are observed in the central regions of the U.S. in warmer seasons. The forecast skill of all individual NMME-2 models generally decreases as increases of lead times. The simple model averaging (SMA) of five NMME-2 models demonstrates a higher forecast skill than any individual NMME-2 models. Spatially, the highest forecast skill scores are observed at coastal areas in the Western U.S. with an one-week lead time. As compared to the historical resampled forecasts, NMME-2 also shows better performance in predicting extreme precipitation events above 99% percentiles and below 1% percentiles with higher probability of detections and lower false alarm ratios. Finally, the obtained results suggest the great potentials of NMME-2 precipitation forecasts in assisting ensemble hydrologic forecasts at the S2S scale over the CONUS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Radon Isotopes and Stable Water Isotopes from Coal Creek Watershed, Colorado (2021)

The radon isotope and stable water isotope data for Coal Creek Watershed, Colorado, consists of d2H, d18O, and 222Rn values from samples collected at 8 stream location along Coal Creek, samples from 7 groundwater springs within the watershed, and precipitation isotope samples collected by Next Generation Water Observing System (NGWOS) from a collector within the watershed. All stream and spring samples were collected between June and October, 2021, and precipitation isotope samples were collected between November 2020 and September 2021. These data were collected to evaluate how groundwater contributions to Coal Creek originating from a fractured hillslope and alluvial fan respond to summer monsoon rains and seasonal drying. Understanding of groundwater-surface water interactions in montane systems in critical for the future of water availability in the Western US as groundwater contributions are expected to become more important for sustaining summer stream flows. This data package contains: (1) a csv of all radon samples; (2) a csv of all stream and spring isotope samples; (3) a csv of precipitation isotope samples; and (4) a csv of locations for each sampling site. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Clumped isotope constraints on changes in latest Pleistocene hydroclimate in the northwestern Great Basin: Lake Surprise, California

Abstract During the Last Glacial Maximum (LGM) and subsequent deglaciation, the Great Basin in the southwestern United States was covered by numerous extensive closed-basin lakes, in stark contrast with the predominately arid climate observed today. This transition from lakes in the Late Pleistocene to modern aridity implies large changes in the regional water balance. Whether these changes were driven by increased precipitation rates due to changes in atmospheric dynamics, decreased evaporation rates resulting from temperature depression and summer insolation changes, or some combination of the two remains uncertain. The factors contributing to these large-scale changes in hydroclimate are critical to resolve, given that this region is poised to undergo future anthropogenic-forced climate changes with large uncertainties in model simulations for the 21st century. Furthermore, there are ambiguous constraints on the magnitude and even the sign of changes in key hydroclimate variables between the Last Glacial Maximum and the present day in both proxy reconstructions and climate model analyses of the region. Here we report thermodynamically derived estimates of changes in temperature, precipitation, and evaporation rates, as well as the isotopic composition of lake water, using clumped isotope data from an ancient lake in the northwestern Great Basin, Lake Surprise (California). Compared to modern climate, mean annual air temperature at Lake Surprise was 4.7 °C lower during the Last Glacial Maximum, with decreased evaporation rates and similar precipitation rates to modern. During the mid-deglacial period, the growth of Lake Surprise implied that the lake hydrologic budget briefly departed from steady state. Our reconstructions indicate that this growth took place rapidly, while the subsequent lake regression took place over several thousand years. Using models for precipitation and evaporation constrained from clumped isotope results, we determine that the disappearance of Lake Surprise coincided with a moderate increase in lake temperature, along with increasing evaporation rates outpacing increasing precipitation rates. Concomitant analysis of proxy data and climate model simulations for the Last Glacial Maximum are used to provide a robust means to understand past climate change, and by extension, predict how current hydroclimates may respond to expected future climate forcings. We suggest that an expansion of this analysis to more basins across a larger spatial scale could provide valuable insight into proposed climate forcings, and aid in climate model process depiction. Ultimately, our analysis highlights the importance of temperature-driven evaporation as a mechanism for lake growth and retreat in this region.

Geology↗
DOE OSTI2022

Stable carbon isotope values of syndepositional carbonate spherules and micrite record spatial and temporal changes in photosynthesis intensity

Marine and lacustrine carbonate minerals preserve carbon cycle information, and their stable carbon isotope values (δ 13 C) are frequently used to infer and reconstruct paleoenvironmental changes. However, multiple processes can influence the δ 13 C values of bulk carbonates, confounding the interpretation of these values in terms of conditions at the time of mineral precipitation. Co-existing carbonate forms may represent different environmental conditions, yet few studies have analyzed δ 13 C values of syndepositional carbonate grains of varying morphologies to investigate their origins. Here, we combine stable isotope analyses, metagenomics, and geochemical modeling to interpret δ 13 C values of syndepositional carbonate spherules (>500 μm) and fine-grained micrite (<63 μm) from a ~1600-year-long sediment record of a hypersaline lake located on the coral atoll of Kiritimati, Republic of Kiribati (1.9°N, 157.4°W). Petrographic, mineralogic, and stable isotope results suggest that both carbonate fractions precipitate in situ with minor diagenetic alterations. The δ 13 C values of spherules are high compared to the syndepositional micrite and cannot be explained by mineral differences or external perturbations, suggesting a role for local biological processes. We use geochemical modeling to test the hypothesis that the spherules form in the surface microbial mat during peak diurnal photosynthesis when the δ 13 C value of dissolved inorganic carbon is elevated. In contrast, we hypothesize that the micrite may precipitate more continuously in the water as well as in sub-surface, heterotrophic layers of the microbial mat. Both metagenome and geochemical model results support a critical role for photosynthesis in influencing carbonate δ 13 C values. The down-core spherule–micrite offset in δ 13 C values also aligns with total organic carbon values, suggesting that the difference in the δ13C values of spherules and micrite may be a more robust, inorganic indicator of variability in productivity and local biological processes through time than the δ 13 C values of individual carbonate forms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Lagrangian and Eulerian Supersaturation Statistics in Turbulent Cloudy Rayleigh–Bénard Convection: Applications for LES Subgrid Modeling

Abstract Turbulent fluctuations of scalar and velocity fields are critical for cloud microphysical processes, e.g., droplet activation and size distribution evolution, and can therefore influence cloud radiative forcing and precipitation formation. Lagrangian and Eulerian water vapor, temperature, and supersaturation statistics are investigated in direct numerical simulations (DNS) of turbulent Rayleigh–Bénard convection in the Pi Convection Cloud Chamber to provide a foundation for parameterizing subgrid-scale fluctuations in atmospheric models. A subgrid model for water vapor and temperature variances and covariance and supersaturation variance is proposed, valid for both clear and cloudy conditions. Evaluation of phase change contributions through an a priori test using DNS data shows good performance of the model. Supersaturation is a nonlinear function of temperature and water vapor, and relative external fluxes of water vapor and heat (e.g., during entrainment-mixing and phase change) influence turbulent supersaturation fluctuations. Although supersaturation has autocorrelation and structure functions similar to the independent scalars (temperature and water vapor), the autocorrelation time scale of supersaturation differs. Relative scalar fluxes in DNS without cloud make supersaturation PDFs less skewed than the adiabatic case, where they are highly negatively skewed. However, droplet condensation changes the PDF shape response: it becomes positively skewed for the adiabatic case and negatively skewed when the sidewall relative fluxes are large. Condensation also increases correlations between water vapor and temperature in the presence of relative scalar fluxes but decreases correlations for the adiabatic case. These changes in correlation suppress supersaturation variability for the nonadiabatic cases and increase it for the adiabatic case. Implications of this work for subgrid microphysics modeling using a Lagrangian stochastic scheme are also discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Automation is all you need: Faster Earth system models with AI/ML

Focal Area: Data acquisition and assimilation enabled by machine learning (ML), artificial intelligence (AI) and advanced methods. Science Challenge: Tropical cyclones can in- duce extreme water cycle events through dramatic precipitation and storm surge. More reliable models of intensity will translate into better prediction of the impact of extreme events in large scale Earth systems simulations. We demonstrate and describe AI/ML methodologies for rapid assimilation of new, in situ data products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Trustworthy AI for Extreme Event Prediction and Understanding

Our transformational science question is: can we revolutionize both the prediction and understanding of extreme events through trustworthy AI? Our use-cases include extreme weather such as tornadoes and hail as well as water-based events including extreme precipitation, compound flooding, harmful algal blooms, and sea turtle cold stunnings and nest inundations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Vertical Aerosol Profiling during SAIL (VAPS) Field Campaign Report

To more fully address the science goals of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s Surface Atmosphere Integrated Field Laboratory (SAIL) campaign, particularly the key science question of “How strongly do aerosols affect the surface energy and water balance by altering clouds, precipitation, and surface albedo, and how do these impacts vary seasonally?”, our campaign added instrumentation to planned tethered balloon system (TBS) flights in May and July of 2022. A key aspect of aerosol-cloud interactions is understanding cloud condensation nuclei (CCN) and ice nucleating particle (INP) populations, and how they vary seasonally and spatially. Because the interactions between aerosols and clouds is the target of this work, vertical distributions are particularly important to evaluate. Measurements of aerosol at ground level, below-cloud, and in-cloud will allow a better understanding of the airmasses that are feeding cloud-active particles into low- and mid-level clouds. Measurements of INP and aerosol populations often differ between the ground and aloft, with relationships that likely depend on regional and seasonal. Because of this, collocated measurements of aerosol, CCN, and INP, across different seasons, are crucial to reducing uncertainties in relationships between ground-level and cloud-base aerosol populations. Our campaign added online measurements of CCN using a compact CCN counter and offline filter collections for measurement of INP populations to the SAIL campaign TBS flights in May and July of 2022. The CCN instrument, the CloudPuck, flew and successfully collected data for a total of eight flights across both campaign periods. The IcePuck flew for most flights during the same period. Both instruments have continued to be used for other campaign requests in the SAIL domain. Analysis of this data was proposed through a concurrent DOE Atmospheric System Research (ASR) project submission, which was not funded in 2022. A similar proposal, which would involve analysis of the samples and data collected from this campaign, has been resubmitted in 2023 but a funding decision has not yet been made. If the proposal is again declined, we will seek other resources to ensure that this data can be analyzed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Cost-optimal selection of pH control for mineral scaling prevention in high recovery reverse osmosis desalination

Conference proceedings for Foundations of Computer Aided Process Design (FOCAPD) 2024 that details a cost optimization model for pH control to prevent mineral scaling in high recovery reverse osmosis. This work applies a framework for incorporating detailed water chemistry predictions such as precipitation, pH change, and mineral scaling tendencies with process-scale optimization. It demonstrates that the acid choice for pH control can have a significant impact on pretreatment costs.

Amusat, Oluwamayowa↗