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DOE OSTI2025

HydroForecast Long-term: Improving hydropower’s resilience to climate change through accurate climate-scale

With hydrologic patterns and water availability across the globe shifting due to climate change, advancements in hydrologic prediction systems can help significantly reduce the uncertainties that utilities and water supply entities have in their decision making. Understanding and estimating hydrology at the climate scale is critical for managing water resources under changing climate scenarios. This project focuses on integrating state-of-the-art neural network modeling with downscaled climate projections to deliver the reliable water supply projections decades into the future to meet an urgent need from hydropower operators and water utilities. In this Phase 1 DOE SBIR proposal, we developed and validated a theory-guided neural network model, HydroForecast Long-term, for climate-scale hydrology and implemented the model within existing HydroForecast infrastructure. HydroForecast Long-term combines the most accurate streamflow modeling system with a flexible and scalable data architecture to generate water supply projections out to the year 2100. This report illustrates that we have achieved our four objectives: 1) create a prototype of HydroForecast Long-term, building the neural network prediction model, 2) build an automated data input pipeline that processes large amounts of data from the latest global temperature and precipitation climate models; 3) benchmark the accuracy of the hydrologic model over the recent two decades over a large set of diverse basins, and 4) create a set of output visuals and summary metrics informed by customer feedback that connect the data to critical decision points. This work empowers water users to make data-informed decisions supporting a resilient, renewable-powered grid and water system. The results advance the Department of Energy’s mission by addressing critical gaps in water supply planning under climate change.

13 HYDRO ENERGY↗

DOE OSTI2025

University of Miami G-band Vapor Radiometer Calibration (UMGVR_CAL) Field Campaign Report

Cold-air outbreak (CAO) clouds in the Arctic are commonly mixed-phase (MP); however, the partitioning of the amount of ice and water in CAO clouds and precipitation is not always well observed. Understanding how cloud phases partition as a function of cloud life cycle is important for predicting snowfall rates, convective life cycle, and intensity at weather timescales. The partitioning into liquid versus ice also has radiative impacts that are consequential for climate. These concerns motivated the incorporation of an airborne G-band vapor radiometer (GVR) into an National Science Foundation-supported aircraft campaign named the Cold Air outbreak Experiment in the Sub-Arctic Region (CAESAR). The GVR is an upward-pointing passive microwave radiometer using four frequencies centered around the 183.31 GHz water vapor absorption line, displaced by +- 1, 3, 7, and 14 GHz. For context, The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility operates a surface-based GVR at its North Slope of Alaska (NSA) site. The same GVR has been used previously for a field campaign in the southeast Pacific, where an offset was noticed between brightness temperatures (Tbs) measured under clear skies compared to those calculated from a radiative transfer model. To account for any calibration offsets to the Tbs, a request was made to DOE to allow the GVR to operate at ARM’s Southern Great Plains (SGP) observatory and enable comparisons between its measurements and those available at SGP. This request was granted, titled ‘UMGVR_CAL’, short for ‘UMGVR_Calibration’. From October 30 to November 10, 2023, the GVR was deployed to the ARM SGP site to take advantage of their regular, nearby radiosonde launches under clear-sky conditions. The latter were determined using the SGP total sky imagery data. The GVR brightness temperatures in these clear-sky conditions were compared to those calculated by a radiative transfer code (PAMTRA) based on the SGP radiosondes. During the campaign, four suitable clear-sky episodes could be used for the GVR calibration. While few in number, these proved to be enough to satisfy our goal.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

IA-TmG.2.0

Soil samples were collected in triplicate in the Fall of 2017 across three grassland locations having differences in historical annual precipitation. For each of the three field site soil collections, one deeply sequenced composite metagenome (> 1 terabase) was obtained and individually sequenced in replicate to provide three additional terabase metagenomes for replicate statistical comparison in addition to screening for viral soil contigs for assessing the impact of historical annual precipitation. This data package provides new knowledge of viral types, abundances, diversity, and auxiliary metabolic genes (AMGs) in grassland soils for predicting viral response to changes in their environment.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

KS-TmG.2.0

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

WA-TmG.2.0

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1990

The 1990 Western Pacific Geophysics meeting

The 1990 Western Pacific Geophysics Meeting was held in Kanazawa, Japan from 15-21 Aug. 1990. This was the first meeting of a new series of meetings for the American Geophysical Union, and it proved to be very successful in terms of the scientific program and attendance, which included over 1,000 participants. The intent of this meeting was an effort on the part of the American Geophysical Union (AGU) and several Japanese geophysical societies to gather individual Earth and space scientists at a major scientific meeting to focus on geophysical problems being studied in the western Pacific rim. The meeting was organized along the lines of a typical AGU annual meeting with some invited talks, many contributed talks, poster sessions, and with emphasis on presentations and informal discussions. The program committee consisted of scientists from both the U.S. and Japan. This meeting provided ample opportunities for U.S. and Japanese scientists to get to know each other and their works on a one-to-one basis. It was also a valuable opportunity for students studying geophysics to get together and interact with each other and with scientists from both the U.S. and Japan. There were 939 abstracts submitted to the conference and a total of 102 sessions designed as a result of the abstracts received. The topics of interest are as follows: space geodetic and observatory measurements for earthquake and tectonic studies; gravity, sea level, and vertical motion; variations in earth rotation and earth dynamics; sedimentary magnetism; global processes and precipitation; subsurface contaminant transport; U.S. Western Pacific Rim initiatives in hydrology; shelf and coastal circulation; tectonics, magmatism, and hydrothermal processes; earthquake prediction and hazard assessment; seismic wave propagation in realistic media; and dynamics and structure of plate boundaries and of the Earth's deep interior.

Source record↗

NASA NTRS2016

Building Climate Resilience at NASA Ames

NASA Ames Research Center, located at the southern end of the San Francisco Bay (SFB) estuary has identified three primary vulnerabilities to changes in climate. The Ames Climate Adaptation Science Investigator (CASI) workgroup has studied each of these challenges to operations and the potential exposure of infrastructure and employees to an increased frequency of hazards. Sea level rise inundation scenarios for the SFB Area generally refer to projected scenarios in mean sea level rather than changes in extreme tides that could occur during future storm conditions. In the Summer of 2014, high resolution 3-D mapping of the low lying portion of Ames was performed. Those data are integrated with improved sea level inundation scenarios to identify the buildings, basements and drainage systems potentially affected. We will also identify the impacts of sea level and storm surge effects on transportation to and from the Center. This information will help Center Management develop future Master Plans. Climate change will also lead to changes in temperature, storm frequency and intensity. These changes have potential impacts on localized floods and ecosystems, as well as on electricity and water availability. Over the coming decades, these changes are going to be imposed on top of ongoing land use and land cover changes, especially those deriving from continued urbanization and increase in impervious surface areas. These coupled changes have the potential to create a series of cascading impacts on ecosystems, including changes in primary productivity and disturbance of hydrological properties and increased flood risk.The majority of the electricity used at Ames is supplied by hydroelectric dams, which will be influenced by reductions in precipitation or changes in the timing or phase of precipitation which reduces snow pack. Coupled with increased demand for summertime air conditioning and other cooling needs, NASA Ames is at risk for electricity shortfalls. To assess the anticipated energy usage as climate changes, the Ames CASI team is collecting historical energy usage data from Ames facilities, historical weather data, and projected future weather parameters from the CASI Climate subgroup. This data will be incorporated into the RETScreen model to predict how energy usage at Ames will change over the coming century.

climate↗

NASA NTRS2021

Capturing the Footprints of Ground Motion in the Spatial Distribution of Rainfall-Induced Landslides

The coupled effect of earthquakes and rainfall is rarely investigated in landslide susceptibility assessments although it could be crucial to predict landslide occurrences. This is even more critical in the context of early warning systems and especially in cases of extreme precipitation regimes in post-seismic conditions, where the rock masses are already damaged due to the ground shaking. Here, we investigate this concept by accounting for the legacy of seismic ground shaking in rainfall-induced landslide (RFIL) scenarios. We do this to identify whether ground shaking plays a role in the susceptibility to post-seismic rainfall-induced landslides and to identify whether this legacy effect persists through time. With this motivation, we use binary logistic regression and examine time series of landslides associated with four earthquakes occurred in Indonesia: 2012 Sulawesi (M(sub w) = 6.3), 2016 Reuleut (M(sub w) = 6.5), 2017 Kasiguncu (M(sub w) = 6.6) and 2018 Palu (M(sub w) = 7.5) earthquakes. The dataset includes one co-seismic and three post-seismic landslide inventories for each earthquake. We use the peak ground acceleration map of the last strongest earthquake in each case as a predisposing factor of landslides representing the effect of ground shaking. We observe that, at least for the study areas under consideration and in a probabilistic context, the earthquake legacy contributes to increase the post-seismic RFIL susceptibility. This positive contribution decays through time. Specifically, we observe that ground motion is a significant predisposing factor controlling the spatial distribution of RFIL in the post-seismic period 110 days after an earthquake. We also show that this effect dissipates within 3 years at most.

Landslides↗

DOE OSTI2023

Diurnal cycle of precipitation over the tropics and central United States: intercomparison of general circulation models

Diurnal precipitation is a fundamental mode of variability that climate models have difficulty in accurately simulating. Here, in this work, the diurnal cycle of precipitation (DCP) in participating climate models from the Global Energy and Water Exchanges' DCP project is evaluated over the tropics and central United States. Common model biases such as excessive precipitation over the tropics, too frequent light-to-moderate rain, and the failure to capture propagating convection in the central United States still exist. Over the central United States, the issues of too weak rainfall intensity in climate runs is well improved in their hindcast runs with initial conditions from numerical weather prediction analyses. But the improvement is minimal over the central Amazon. Incorporating the role of the large-scale environment in convective triggering processes helps resolve the phase-locking issue in many models where precipitation often incorrectly peaks near noon due to maximum insolation over land. Allowing air parcels to be lifted above the boundary layer improves the simulation of nocturnal precipitation which is often associated with the propagation of mesoscale systems. Including convective memory in cumulus parameterizations acts to suppress light-to-moderate rain and promote intense rainfall; however, it also weakens the diurnal variability. Simply increasing model resolution (with cumulus parameterizations still used) cannot fully resolve the biases of low-resolution climate models in DCP. The hierarchy modeling framework from this study is useful for identifying the missing physics in models and testing new development of model convective processes over different convective regimes.

58 GEOSCIENCES↗

NASA NTRS2008

Accessing and Utilizing Remote Sensing Data for Vectorborne Infectious Diseases Surveillance and Modeling

Background: The transmission of vectorborne infectious diseases is often influenced by environmental, meteorological and climatic parameters, because the vector life cycle depends on these factors. For example, the geophysical parameters relevant to malaria transmission include precipitation, surface temperature, humidity, elevation, and vegetation type. Because these parameters are routinely measured by satellites, remote sensing is an important technological tool for predicting, preventing, and containing a number of vectorborne infectious diseases, such as malaria, dengue, West Nile virus, etc. Methods: A variety of NASA remote sensing data can be used for modeling vectorborne infectious disease transmission. We will discuss both the well known and less known remote sensing data, including Landsat, AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), TRMM (Tropical Rainfall Measuring Mission), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), EO-1 (Earth Observing One) ALI (Advanced Land Imager), and SIESIP (Seasonal to Interannual Earth Science Information Partner) dataset. Giovanni is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center. It provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. After remote sensing data is obtained, a variety of techniques, including generalized linear models and artificial intelligence oriented methods, t 3 can be used to model the dependency of disease transmission on these parameters. Results: The processes of accessing, visualizing and utilizing precipitation data using Giovanni, and acquiring other data at additional websites are illustrated. Malaria incidence time series for some parts of Thailand and Indonesia are used to demonstrate that malaria incidences are reasonably well modeled with generalized linear models and artificial intelligence based techniques. Conclusions: Remote sensing data relevant to the transmission of vectorborne infectious diseases can be conveniently accessed at NASA and some other websites. These data are useful for vectorborne infectious disease surveillance and modeling.

Kiang, Richard↗

NASA NTRS1996

Precipitation Recycling

The water cycle regulates and reflects natural variability in climate at the regional and global scales. Large-scale human activities that involve changes in land cover, such as tropical deforestation, are likely to modify climate through changes in the water cycle. In order to understand, and hopefully be able to predict, the extent of these potential global and regional changes, we need first to understand how the water cycle works. In the past, most of the research in hydrology focused on the land branch of the water cycle, with little attention given to the atmospheric branch. The study of precipitation recycling which is defined as the contribution of local evaporation to local precipitation, aims at understanding hydrologic processes in the atmospheric branch of the water cycle. Simply stated, any study on precipitation recycling is about how the atmospheric branch of the water cycle works, namely, what happens to water vapor molecules after they evaporate from the surface, and where will they precipitate?

Eltahir, Elfatih A. B.↗

DOE OSTI2024

Melting and solidification dynamics during laser melting of reaction-based metal matrix composites uncovered by in-situ synchrotron X-ray diffraction

Laser additive manufacturing (AM) of reaction-based metal matrix composites (MMCs) involves highly complex and non-equilibrium material transformation behavior, including melting, dissolution, precipitation, and solidification. Yet, the dynamics and interplay of these phase transformation processes remain poorly understood, posing substantial challenges in identifying the microstructure formation mechanism, and predicting and controlling the microstructure in the printed parts. Here, in this study, we performed the in-situ X-ray diffraction experiment to characterize the phase evolution dynamics of the 316L + 10 vol.%TiC system during laser melting, which provides direct and quantitative insights of the complex phase reaction and evolution dynamics under rapid heating and cooling conditions relevant to additive manufacturing of reaction-based MMCs. Further in-depth thermodynamic and kinetic calculations revealed that most of the phase evolution behavior observed in the in-situ X-ray diffraction experiment cannot be solely explained by widely used equilibrium thermodynamic models, and diffusion-controlled nonequilibrium dissolution and precipitation kinetics must be considered to elucidate the complex phase evolution behavior, including incomplete TiC dissolution, and three-step TiC precipitation. The three distinct types of precipitates generate unique hierarchical TiC micro- and nanostructures, which enhances the yield strength from 513 MPa to 877 MPa by 71 %, tensile strength from 628 MPa to 1054 MPa by 68 %, and Young's modulus from 193 GPa to 221 GPa by 14 %. The findings of our research provide the knowledge foundation for the design of unique microstructures and advanced MMC materials through laser AM.

36 MATERIALS SCIENCE↗

NASA NTRS2002

Using Clustering to Establish Climate Regimes from PCM Output

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Oglesby, Robert↗

NASA NTRS2018

Precipitating Electron Energy Flux and Characteristic Energies in Jupiter's Main Auroral Region as Measured by Juno/JEDI

The relationship between electron energy flux and the characteristic energy of electron distributions in the main auroral loss cone bridges the gap between predictions made by theory and measurements just recently available from Juno. For decades such relationships have been inferred from remote sensing observations of the Jovian aurora, primarily from the Hubble Space Telescope, and also more recently from Hisaki. However, to infer these quantities, remote sensing techniques had to assume properties of the Jovian atmospheric structure - leading to uncertainties in their profile. Juno's arrival and subsequent auroral passes have allowed us to obtain these relationships unambiguously for the first time, when the spacecraft passes through the auroral acceleration region. Using Juno /Jupiter Energetic particle Detector Instrument (JEDI), an energetic particle instrument, we present these relationships for the 30-kiloelectronvolts to 1-megaelectronvolts electron population. Observations presented here show that the electron energy flux in the loss cone is a nonlinear function of the characteristic or mean electron energy and supports both the predictions from Knight (1973, https://doi.org/10.1016/0032-0633(73)90093-7) and magnetohydrodynamic turbulence acceleration theories (e.g., Saur et al., 2003, https://doi.org/10.1029/2002GL015761). Finally, we compare the in situ analyses of Juno with remote Hisaki observations and use them to help constrain Jupiter's atmospheric profile. We find a possible solution that provides the best agreement between these data sets is an atmospheric profile that more efficiently transports the hydrocarbons to higher altitudes. If this is correct, it supports the previously published idea (e.g., Parkinson et al., 2006, https://doi.org/10.1029/2005JE002539) that precipitating electrons increase the hydrocarbon eddy diffusion coefficients in the auroral regions.

Auroral↗

NASA NTRS2002

Understanding the Global Water and Energy Cycle Through Assimilation of Precipitation-Related Observations: Lessons from TRMM and Prospects for GPM

Understanding the Earth's climate and how it responds to climate perturbations relies on what we know about how atmospheric moisture, clouds, latent heating, and the large-scale circulation vary with changing climatic conditions. The physical process that links these key climate elements is precipitation. Improving the fidelity of precipitation-related fields in global analyses is essential for gaining a better understanding of the global water and energy cycle. In recent years, research and operational use of precipitation observations derived from microwave sensors such as the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Special Sensor Microwave/Imager (SSM/I) have shown the tremendous potential of using these data to improve global modeling, data assimilation, and numerical weather prediction. We will give an overview of the benefits of assimilating TRMM and SSM/I rain rates and discuss developmental strategies for using space-based rainfall and rainfall-related observations to improve forecast models and climate datasets in preparation for the proposed multi-national Global Precipitation Mission (GPM).

Hou, Arthur↗

NASA NTRS2005

The Hurricane-Flood-Landslide Continuum

In August 2004, representatives from NOAA, NASA, the USGS, and other government agencies convened in San Juan, Puerto Rim for a workshop to discuss a proposed research project called the Hurricane-Flood-Landslide Continuum (HFLC). The essence of the HFLC is to develop and integrate tools across disciplines to enable the issuance of regional guidance products for floods and landslides associated with major tropical rain systems, with sufficient lead time that local emergency managers can protect vulnerable populations and infrastructure. All three lead agencies are independently developing precipitation-flood-debris flow forecasting technologies, and all have a history of work on natural hazards both domestically and overseas. NOM has the capability to provide tracking and prediction of storm rainfall, trajectory and landfall and is developing flood probability and magnTtude capabilities. The USGS has the capability to evaluate the ambient stability of natural and man-made landforms, to assess landslide susceptibilities for those landforms, and to establish probabilities for initiation of landslides and debris flows. Additionally, the USGS has well-developed operational capacity for real-time monitoring and reporting of streamflow across distributed networks of automated gaging stations (http://water.usgs.gov/waterwatch/). NASA has the capability to provide sophisticated algorithms for satellite remote sensing of precipitation, land use, and in the future, soil moisture. The Workshop sought to initiate discussion among three agencies regarding their specific and highly complimentary capabilities. The fundamental goal of the Workshop was to establish a framework that will leverage the strengths of each agency. Once a prototype system is developed for example, in relatively data-rich Puerto Rim, it could be adapted for use in data-poor, low-infrastructure regions such as the Dominican Republic or Haiti. This paper provides an overview of the Workshop s goals, presentations and recommendations with respect to the development of the HFLC.

Negri, Andrew J.↗

NASA NTRS1990

Global magnetic anomaly and aurora of Neptune

The large offset and tilt of Neptune's dipole magnetic field combine to create a global magnetic anomaly, analogous to but much more important than earth's South Atlantic Anomaly. Energetic particle precipitation loss within the Neptune anomaly creates 'atmospheric drift shadows' within which particle fluxes are greatly reduced. The energetic particle dropout observed by Voyager near closest approach occurred near the predicted times when Voyager passed within the atmospheric drift shadow. Extremely soft, structured bursts of ions and electrons within the drift shadow may result from plasma wave-induced pitch angle scattering of trapped particles confined near the magnetic equator. The dropout does not necessarily imply that Voyager passed through an earth-like discrete auroral zone, as earlier reported. The ion and electron fluxes observed within the dropout period correspond to particles that must precipitate to Neptune's atmosphere within the anomaly region. This anomaly precipitation can account for a major portion of the ultraviolet emissions previously identified as Neptune aurora.

Cheng, Andrew F.↗

NASA NTRS2014

Expansion of the Real-time Sport-land Information System for NOAA / National Weather Service Situational Awareness and Local Modeling Applications

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL (Jedlovec 2013; Ralph et al. 2013; Merceret et al. 2013) is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The SPoRT-LIS is currently run over a domain covering the southeastern half of the Continental United States (CONUS), with an additional experimental real-time run over the entire CONUS and surrounding portions of southern Canada and northern Mexico. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) product (Zhang et al. 2011, 2014), which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014. This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations. Section 2 gives background information on the NASA LIS and describes the realtime SPoRT-LIS configurations being compared. Section 3 presents recent work done to develop a training module on situational awareness applications of real-time SPoRT-LIS output. Comparisons between output from the two SPoRT-LIS runs are shown in Section 4, including a documentation of issues encountered in using the MRMS precipitation dataset. A summary and future work in given in Section 5, followed by acknowledgements and references.

Case, Jonathan L.↗