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At least 703 records · Page 39

Improving Surface Soil Moisture Estimates in West Africa Through GRACE Data Assimilation

Recent annual trends of precipitation and terrestrial water storage (TWS) in West Africa have been increasing over the past decade. Despite a significant impact of soil moisture on the TWS in West Africa, there is little research on the recent spatial and temporal behaviors of surface soil moisture (SSM) along with the hydrological trends and variability in West Africa. In this study, we assimilate TWS estimates from the Gravity Recovery and Climate Experiment (GRACE) mission into the Catchment Land Surface Model (CLSM) and evaluate its impacts on SSM simulations for the years, 2002–2017. The evaluation is performed using reference datasets: the African Monsoon Multidisciplinary Analysis (AMMA) in situ soil moisture observations, three currently available microwave satellite SSM observations from the Advanced Scatterometer (ASCAT), the Soil Moisture Ocean Salinity (SMOS), and the Soil Moisture Active Passive (SMAP) satellites and also the triple collocation analysis (TCA). Overall, modeled SSM shows good agreement with the reference datasets in terms of the anomaly SSM correlations. However, both modeled and ASCAT SSM are limited in their representation of the drying rates, as observed by ground observations, SMOS and SMAP estimates. Further, GRACE data assimilation results in improved SSM simulations in the humid regions with large annual TWS variability. This study demonstrates the utility of land data assimilation to inform hydrological conditions in West Africa, where soil moisture monitoring is necessary for water resource and livestock management.

West Africa↗

Identifying Meteorological Influences on Marine Low Cloud Mesoscale Morphology Using Satellite Classifications

Marine low cloud mesoscale morphology in the southeastern Pacific Ocean is analyzed using a large dataset of machine-learning generated classifications spanning three years. Meteorological variables and cloud properties are composited 10by mesoscale cloud type, showing distinct meteorological regimes of marine low cloud organization from the tropics to the midlatitudes. The presentation of mesoscale cellular convection, with respect to geographic distribution, boundary layer structure, and large-scale environmental conditions, agrees with prior knowledge. Two tropical and subtropical cumuliform boundary layer regimes, suppressed cumulus and clustered cumulus, are studied in detail. The patterns in precipitation, circulation, column water vapor, and cloudiness are consistent with the representation of marine shallow mesoscale convective 15 self-aggregation by large eddy simulations of the boundary layer. Although they occur under similar large-scale conditions, the suppressed and clustered low cloud types are found to be well-separated by variables associated with low-level mesoscale circulation, with surface wind divergence being the clearest discriminator between them, whether reanalysis or satellite observations are used. Clustered regimes are associated with surface convergence and suppressed regimes are associated with surface divergence.

Johannes Mohrmann↗

On the Prediction of Surface Melt Over the Greenland Ice Sheet at NWP and S2S Timescales

Greenland surface melt “events” – encompassing large swaths of the ice sheet over approximately 4-10 day periods – have occurred with increasing frequency in the 21st Century. Surface processes are significant to the ice sheet’s overall contribution to sea level. In addition, the sudden onset of widespread surface melt produces hazardous conditions for researchers and for communities adjacent to the ice sheet. The mechanisms producing melt events, their associated large-scale forcing, and timescales of interest are highly variable and poorly understood. Here we examine the predictability of melt events in a numerical weather prediction system (NWP) and a subseasonal-to-seasonal system (S2S). The NASA Global Modeling and Assimilation Office forward processing (GMAO-FP) is an NWP system that incorporates an evolving, global hybrid 4D ensemble–variational (4DEnVar) data assimilation system and a state-of-the-art model that is run twice-daily with forecasts out to five and ten days. The GMAO S2S system is a hindcast-anomaly, coupled-model prediction system initialized with an atmospheric analysis, and in situ and satellite ocean data assimilation. Both systems represent ice sheet surface hydrology and snowpack processes. We examine the performance of the systems over the period 2018-2023, a span that includes approximately nine significant events, against analyses and satellite-derived melt extent. In addition to extent, we examine related conditions and their role in the melt forecast, including the onset of both omega and Rex atmospheric blocking patterns, sea surface temperatures, sea ice extent, water vapor transport, precipitation, and surface preconditioning. We further examine the tendency for false-alarm events in each system and assess reasons for the forecast performance. North Atlantic atmospheric blocking patterns leading to surface melt are well forecast by the NWP system out to around eight days, while the S2S system generally underestimates the magnitude of such events at monthly lead times. These systems suggest that while short term forecasts of ice sheet melt and melt events are relatively robust, S2S predictions of surface conditions are highly dependent on the ability of a coupled system to generate the short-term atmospheric conditions associated with surface melt events.

Richard Cullather↗

Mixed metal oxide extrudate catalyst

Methods of making a Ce0.6Zr0.4O2 supported NiMg catalyst extrudate are provided. In some aspects, the methods include preparing a ceria-zirconia solution comprising Ce(NO3)3.6H2O, ZrO(NO3)2xH2O, and water; forming a precipitate; drying and calcining the precipitate to produce a Ce0.6Zr0.4O2; adding a nickel-magnesium solution to the Ce0.6Zr0.4O2 to produce the NiMg/Ce0.6Zr0.4O2; and drying and calcining a wet extrudate of the NiMg/Ce0.6Zr0.4O2 to produce the Ce0.6Zr0.4O2 supported NiMg catalyst extrudate. Ce0.6Zr0.4O2 supported NiMg catalyst extrudates made by the methods are also provided.

36 MATERIALS SCIENCE↗

Hygroscopic cooling tower for waste water disposal

In various embodiments, the present invention relates to heat dissipation systems including a hygroscopic working fluid integrating waste water as makeup water. The present invention also relates to methods of using the same. The present invention also relates to hygroscopic cooling systems adapted to dispose of waste water by combining the waste water with a hygroscopic working fluid, precipitating impurities and evaporating the remaining water.

Martin, Christopher Lee↗

Hygroscopic cooling tower for waste water disposal

In various embodiments, the present invention relates to heat dissipation systems including a hygroscopic working fluid integrating waste water as makeup water. The present invention also relates to methods of using the same. The present invention also relates to hygroscopic cooling systems adapted to dispose of waste water by combining the waste water with a hygroscopic working fluid, precipitating impurities and evaporating the remaining water.

Martin, Christopher Lee↗

Flood Estimation under Snowmelt and Rain-on-Snow Processes in Alaska: A Military Installation Perspective

Accurate flood estimation in snow-dominated and high-latitude regions remains challenging due to complex interactions among rainfall, snowmelt, and rain-on-snow (ROS) processes, which are not captured in conventional precipitation-based intensity-duration-frequency (PREC-IDF) curves. This study evaluates the Next-Generation IDF (NG-IDF) framework, an extension of PREC-IDF that incorporates total water available for runoff (precipitation minus changes in snow water equivalent), in two contrasting Alaskan watersheds of Department of Defense (DoD) significance: the Little Chena River Basin (LCRB) in interior Alaska, a tributary of the Chena River that flows through Fort Wainwright and near Eielson Air Force Base, and the Upper Ship Creek Basin (USCB), which drains Joint Base Elmendorf-Richardson near Anchorage. Using long-term SNOTEL observations and event-based rainfall-runoff modeling, NG-IDF and PREC-IDF flood estimates were compared against observation-based flood frequency analyses. Results show that NG-IDF consistently reduces flood-estimation bias by 15–20% relative to PREC-IDF, particularly for snowmelt- and ROS-dominated events. In the interior LCRB, permafrost conditions can substantially amplify flood responses during snowmelt events, an effect not explicitly represented in standard design tools. These findings demonstrate that NG-IDF provides a more physically consistent and transferable framework for flood estimation in cold regions, with potential relevance to mission-critical DoD installation resilience. Projected increases in ROS frequency and permafrost degradation across Alaska further emphasize the need to integrate physics-based hydrologic models that explicitly represent snow and permafrost processes to enhance design resilience and operational readiness for military and other critical infrastructure.

Yan, Hongxiang (ORCID:000000022387403X)↗

Comparison of Four Strong Acids on the Precipitation Potential of Gypsum in Brines During Distillation of Pretreated, Augmented Urine

In this study, three different mineral acids were substituted for sulfuric acid (H2SO4) in the urine stabilizer solution to eliminate the excess of sulfate ions in pretreated urine and assess the impact on maximum water recovery to avoid precipitation of minerals during distillation. The study evaluated replacing 98% sulfuric acid with 85% phosphoric acid (H3PO4), 37% hydrochloric acid (HCl), or 70% nitric acid (HNO3). The effect of lowering the oxidizer concentration in the pretreatment formulation also was studied. This paper summarizes the test results, defines candidate formulations for further study, and specifies the injection masses required to stabilize urine and minimize the risk of mineral precipitation during distillation. In the first test with a brine ersatz acidified with different acids, the solubility of calcium in gypsum saturated solutions was measured. The solubility of gypsum was doubled in the brines acidified with the alternative acids compared to sulfuric acid. In a second series of tests, the alternative acid pretreatment concentrations were effective at preventing precipitation of gypsum and other minerals up to 85% water recovery from 95th-percentile pretreated, augmented urine. Based on test results, phosphoric acid is recommended as the safest alternative to sulfuric acid. It also is recommended that the injected mass concentration of chromium trioxide solution be reduced by 75% to minimize liquid resupply mass by about 50%, reduce toxicity of brines, and reduce the concentration of organic acids in distillate. The new stabilizer solution formulations and required doses to stabilize urine and prevent precipitation of minerals up to 85% water recovery are given. The formulations in this study were tested on a limited number of artificially augmented urine batches collected from employees at the Johnson Space Center (JSC). This study successfully demonstrated that the desired physical and chemical stability of pretreated urine and brines can be achieved using alternate pretreatment formulations under laboratory conditions. Additional testing and hazard assessments will be required to determine the feasibility of utilizing the proposed urine pretreatment formulations on ISS.

Muirhead, Dean↗

Congo Basin Water Balance and Terrestrial Fluxes Inferred From Satellite Observations of the Isotopic Composition of Water Vapor

Large spatio-temporal gradients in the Congo basin vegetation and rainfall are observed. However, its water-balance (evapotranspiration minus precipitation, or ET - P) is typically measured at basin-scales, limited primarily by river-discharge data, spatial resolution of terrestrial water storage measurements, and poorly constrained ET. We use observations of the isotopic composition of water vapor to quantify the spatio-temporal variability of net surface water fluxes across the Congo Basin between 2003 and 2018. These data are calibrated at basin scale using satellite gravity and total Congo river discharge measurements and then used to estimate time-varying ET - P over four quadrants representing the Congo Basin, providing first estimates of this kind for the region. We find that the multi-year record, seasonality, and interannual variability of ET - P from both the isotopes and the gravity/river discharge based estimates are consistent. Additionally, we use precipitation and gravity-based estimates with our water vapor isotope-based ET - P to calculate time and space averaged ET and net river discharge within the Congo Basin. These quadrant-scale moisture flux estimates indicate (a) substantial recycling of moisture in the Congo Basin (temporally and spatially averaged ET/P > 70%), consistent with models and visible light-based ET estimates, and (b) net river outflow is largest in the Western Congo where there are more rivers and higher flow rates. Our results confirm the importance of ET in modulating the Congo water cycle relative to other water sources.

54 ENVIRONMENTAL SCIENCES↗

Integrating LEO and GEO Observations: Toward Optimal Summertime Satellite Precipitation Retrieval

Abstract Reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for understanding the Earth’s hydrological cycle. Precipitation estimation over land and coastal regions is necessary for addressing the high degree of spatial heterogeneity of water availability and demand, and for resolving the extremes that modulate and amplify hazards such as flooding and landslides. Advancements in computation power along with unique high spatiotemporal and spectral resolution data streams from passive meteorological sensors aboard geosynchronous Earth-orbiting (GEO) and low Earth-orbiting (LEO) satellites offer exciting opportunities to retrieve information about surface precipitation phenomena using data-driven machine learning techniques. In this study, the capabilities of U-Net–like architecture are investigated to map instantaneous, summertime surface precipitation intensity at the spatial resolution of 2 km. The calibrated brightness temperature products from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) radiometer are combined with multispectral images (visible, near-infrared, and infrared bands) from the Advanced Baseline Imager (ABI) aboard the GOES-R satellites as main inputs to the U-Net–like precipitation algorithm. Total precipitable water and 2-m temperature from the Global Forecast System (GFS) model are also used as auxiliary inputs to the model. The results show that the U-Net–like algorithm can capture fine-scale patterns and intensity of surface precipitation at high spatial resolution over stratiform and convective precipitation regimes. The evaluations reveal the potential of extracting relevant, high spatial features over complex surface types such as mountainous regions and coastlines. The algorithm allows users to interpret the inputs’ importance and can serve as a starting point for further exploration of precipitation systems within the field of hydrometeorology.

Meteorology & Atmospheric Sciences↗

Where Does the Irrigation Water Go? An Estimate of the Contribution of Irrigation to Precipitation Using MERRA

Irrigation is an important human activity that may impact local and regional climate, but current climate model simulations and data assimilation systems generally do not explicitly include it. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) shows more irrigation signal in surface evapotranspiration (ET) than the Modern-Era Retrospective Analysis for Research and Applications (MERRA) because ERA-Interim adjusts soil moisture according to the observed surface temperature and humidity while MERRA has no explicit consideration of irrigation at the surface. But, when compared with the results from a hydrological model with detailed considerations of agriculture, the ET from both reanalyses show large deficiencies in capturing the impact of irrigation. Here, a back-trajectory method is used to estimate the contribution of irrigation to precipitation over local and surrounding regions, using MERRA with observation-based corrections and added irrigation-caused ET increase from the hydrological model. Results show substantial contributions of irrigation to precipitation over heavily irrigated regions in Asia, but the precipitation increase is much less than the ET increase over most areas, indicating that irrigation could lead to water deficits over these regions. For the same increase in ET, precipitation increases are larger over wetter areas where convection is more easily triggered, but the percentage increase in precipitation is similar for different areas. There are substantial regional differences in the patterns of irrigation impact, but, for all the studied regions, the highest percentage contribution to precipitation is over local land.

ERA-Interim↗

Basin Scale Estimates of Evapotranspiration Using GRACE and other Observations

Evapotranspiration is integral to studies of the Earth system, yet it is difficult to measure on regional scales. One estimation technique is a terrestrial water budget, i.e., total precipitation minus the sum of evapotranspiration and net runoff equals the change in water storage. Gravity Recovery and Climate Experiment (GRACE) satellite gravity observations are now enabling closure of this equation by providing the terrestrial water storage change. Equations are presented here for estimating evapotranspiration using observation based information, taking into account the unique nature of GRACE observations. GRACE water storage changes are first substantiated by comparing with results from a land surface model and a combined atmospheric-terrestrial water budget approach. Evapotranspiration is then estimated for 14 time periods over the Mississippi River basin and compared with output from three modeling systems. The GRACE estimates generally lay in the middle of the models and may provide skill in evaluating modeled evapotranspiration.

Rodell, M.↗

Ion Exchange Technology Development in Support of the Urine Processor Assembly

The urine processor assembly (UPA) on the International Space Station (ISS) recovers water from urine via a vacuum distillation process. The distillation occurs in a rotating distillation assembly (DA) where the urine is heated and subjected to sub-ambient pressure. As water is removed, the original organics, salts, and minerals in the urine become more concentrated and result in urine brine. Eventually, water removal will concentrate the urine brine to super saturation of individual constituents, and precipitation occurs. Under typical UPA DA operating conditions, calcium sulfate or gypsum is the first chemical to precipitate in substantial quantity. During preflight testing with ground urine, the UPA achieved 85% water recovery without precipitation. However, on ISS, it is possible that crewmember urine can be significantly more concentrated relative to urine from ground donors. As a result, gypsum precipitated in the DA when operating at water recovery rates at or near 85%, causing the failure and subsequent re14 NASA Tech Briefs, September 2013 placement of the DA. Later investigations have demonstrated that an excess of calcium and sulfate will cause precipitation at water recovery rates greater than 70%. The source of the excess calcium is likely physiological in nature, via crewmembers' bone loss, while the excess sulfate is primarily due to the sulfuric acid component of the urine pretreatment. To prevent gypsum precipitation in the UPA, the Precipitation Prevention Project (PPP) team has focused on removing the calcium ion from pretreated urine, using ion exchange resins as calcium removal agents. The selectivity and effectiveness of ion exchange resins are determined by such factors as the mobility of the liquid phase through the polymer matrix, the density of functional groups, type of functional groups bound to the matrix, and the chemical characteristics of the liquid phase (pH, oxidation potential, and ionic strength). Previous experience with ion exchange resins has demonstrated that the most effective implementation for an ion exchange resin is a cartridge, or column, in which the resin is contained. Based on the results of equilibrium and sub-scale dynamic column testing, a possible solution for mitigating the calcium precipitation issue on the ISS has been identified. From an original pool of 13 ion exchange resins, two candidates have been identified that demonstrate substantial calcium removal on the sub-scale. The dramatic reduction in resin performance from published calcium uptake demonstrates the need for thorough evaluation of resins at the low pH and strong oxidizing environment present in the UPA. Chemical variations in the influent (calcium concentrations and pretreatment dosing) appear to have a noticeable impact on the calcium capacity of the resin. Low calcium concentrations and high pretreatment dosing will likely result in a decrease in calcium capacity. Conversely, low pre trea t - ment dosing will likely result in an increase in calcium capacity. In contrast, investigations at a variety of flow rates, length-to-diameter ratios, resin volumes, and flow regimes (continuous versus pulsed) show that changes in physical parameters do not have substantial impacts on resin performance in the very low specific velocity ranges of interest. This result is particularly useful because most commercial applications at higher specific velocities do show a relatively strong relationship between flow and capacity. The lack of a strong relationship will allow more flexibility in the implementation of an ion exchange bed for flight. Verification of subscale tests with flight-scale resin beds is recommended prior to implementation in the on-orbit UPA.

Mitchell, Julie↗

Exploratory Precipitation Metrics: Spatiotemporal Characteristics, Process-Oriented, and Phenomena-Based

Abstract Precipitation sustains life and supports human activities, making its prediction one of the most societally relevant challenges in weather and climate modeling. Limitations in modeling precipitation underscore the need for diagnostics and metrics to evaluate precipitation in simulations and predictions. While routine use of basic metrics is important for documenting model skill, more sophisticated diagnostics and metrics aimed at connecting model biases to their sources and revealing precipitation characteristics relevant to how model precipitation is used are critical for improving models and their uses. This paper illustrates examples of exploratory diagnostics and metrics including 1) spatiotemporal characteristics metrics such as diurnal variability, probability of extremes, duration of dry spells, spectral characteristics, and spatiotemporal coherence of precipitation; 2) process-oriented metrics based on the rainfall–moisture coupling and temperature–water vapor environments of precipitation; and 3) phenomena-based metrics focusing on precipitation associated with weather phenomena including low pressure systems, mesoscale convective systems, frontal systems, and atmospheric rivers. Together, these diagnostics and metrics delineate the multifaceted and multiscale nature of precipitation, its relations with the environments, and its generation mechanisms. The metrics are applied to historical simulations from phases 5 and 6 of the Coupled Model Intercomparison Project. Models exhibit diverse skill as measured by the suite of metrics, with very few models consistently ranked as top or bottom performers compared to other models in multiple metrics. Analysis of model skill across metrics and models suggests possible relationships among subsets of metrics, motivating the need for more systematic analysis to understand model biases for informing model development.

54 ENVIRONMENTAL SCIENCES↗

Idaho National Laboratory Site Environmental Surveillance Program: Fourth Quarter 2022

This report for the fourth quarter of 2022 contains results from the INL Site environmental surveillance program’s monitoring of the U.S. Department of Energy’s Idaho National Laboratory (INL) Site’s Onsite, Boundary and Offsite location environment, October 1 through December 31, 2022. All sample types (media) and the sampling schedule followed during 2022 are listed in Appendix A. This report contains results for the following sample types: • Air, including particulate air filters, charcoal cartridges, and atmospheric moisture, • Quarterly composites, • Precipitation, • Drinking and surface water, • Milk, • Potatoes, • Soil, • Large game animals, • Waterfowl, and • OSLDs.

99 GENERAL AND MISCELLANEOUS↗

Kinetics of diffusional droplet growth in a liquid/liquid two-phase system

A new powerful experimental technique based on holographic observations, developed at the NASA Marshall Space Flight Center, now permits observation of small liquid droplets coarsening. This technique was developed and used for mixed-dimensional coarsening studies. Experiments were conducted on an isopycnic two-phase alloy of succinonitrile and water, annealed isothermally over a four-month period. The succinonitrile-rich droplets precipitate from a water-rich liquid matrix having a density very close to that of the droplets. The matrix and droplets, however, have different optical indices. The results of these experiments, along with the results of computer simulation based on the quasi-static diffusion approximation developed at Rensselaer are reported. These results were published recently. Copies of these papers are attached to this report.

Glickman, M. E.↗

Advances in Data Assimilation and Weather Prediction Using TRMM Observations

Understanding the Earth's climate and how it responds to climate perturbations requires knowledge of how atmospheric moisture, clouds, latent heating, the large-scale circulation and energy fluxes vary with changing climatic conditions. The physical process linking these climate elements is precipitation. Accurate knowledge of how precipitation varies in space and time and how it couples with other atmospheric variables is essential for understanding the global water and energy cycle. In recent years, TRMM data products have played a key role in advancing the field of data assimilation to provide better global analyses for climate research and numerical weather prediction. TRMM research has demonstrated the effectiveness of microwave-based rainfall and total precipitable water (TPW) observations in improving the quality of assimilated datasets and upgrading forecast skills. TRMM latent heating products have also stimulated experimentation with innovative techniques to use this type of information to improve global analyses. We discuss strategies of assimilating TRMM observations at NASA s Data Assimilation Office and present results on the impact assimilating TRMM data on the Goddard Earth Observing System (GEOS) analyses and forecast capabilities.

Atlas, Robert↗

Land surface water cycles observed with satellite sensors

Acceleration of the global water cycle may lead to increased global precipitation, faster evaporation and a consequent exacerbation of hydrologic extreme. In the U.S. national assessment of the potential consequences of climate variability and change, two GCMs (CGCM1 and HadCM2) show a large increase in precipitation in the future over the southwestern U.S. particularly during winter (Felzer and Heard, 1999). Increased precipitation potentially has important impacts on agricultural and water use in the southeast U.S. (Hatch et al., 1999) and in the central Great Plains (Nielsen, 1997). A hurricane model predicts a 40% precipitation increase for severe hurricanes affecting southeastern Florida, which provokes substantially greater flooding that could negate most of the benefits of present water-management practices in this basin (Gutowski et al., 1994). Thus, it is important to observe the hydroclimate on a continuous longterm basis to address the question of increased precipitation in the enhanced water cycle.

droughts↗