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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Using TRMM Data To Understand Interannual Variations In the Tropical Water Balance

A significant element of the science rationale for TRMM centered on assembling rainfall data needed to validate climate models-- climatological estimates of precipitation, its spatial and temporal variability, and vertical modes of latent heat release. Since the launch of TRMM, a great interest in the science community has emerged for quantifying interannual variability (IAV) of precipitation and its relationship to sea-surface temperature (SST) changes. The fact that TRMM has sampled one strong warm/ cold ENSO couplet, together with the prospect for a mission lifetime approaching ten years, has bolstered this interest in these longer time scales. Variability on a regional basis as well as for the tropics as a whole is of concern. Our analysis of TRMM results so far has shown surprising lack of concordance between various algorithms in quantifying IAV of precipitation. The first objective of this talk is to quantify the sensitivity of tropical precipitation to changes in SSTs. We analyze performance of the 3A11, 3A25, and 3B31 algorithms and investigate their relationship to scattering-- based algorithms constructed from SSM/I and TRMM 85 kHz data. The physical basis for the differences (and similarities) in depicting tropical oceanic and land rainfall will be discussed. We argue that scattering-based estimates of variability constitute a useful upper bound for precipitation variations. These results lead to the second question addressed in this talk-- How do TRMM precipitation / SST sensitivities compare to estimates of oceanic evaporation and what are the implications of these uncertainties in determining interannual changes in large-scale moisture transport? We summarize results of an analysis performed using COADS data supplemented by SSM/I estimates of near-surface variables to assess evaporation sensitivity to SST. The response of near 5 W sq m/K is compared to various TRMM precipitation sensitivities. Implied moisture convergence over the tropics and its sensitivity to errors of these algorithms is discussed.

Robertson, Franklin R.↗
DOE OSTI2024

Training the next generation of researchers in exploring cloud dynamics and microphysics using millimeter-wavelength radars

Millimeter-wavelength radars, with their ability to collect observations and high spatiotemporal resolution, have become cornerstone instruments for investigating cloud and precipitation microphysics and dynamics in the last two decades. Since the1990s the US Department of Energy Atmospheric Radiation Measurement (ARM) program has invested in mm-wavelength radar technology progressively adding scanning capability, additional frequencies and polarimetric capability. In addition, atmospheric observatories including those technologies have been operated overseas. Those technologies have enhanced our understanding of cloud and precipitation processes. Only a few universities operate those instruments and use them for educational purposes. The central role of mm- wavelength radars and their role will be further highlighted in the next decade. NASA and other international space agencies are planning to launch millimeter-wavelength (i.e., Ku, Ka, W, G- bands) Doppler radar in space to improve our understanding of cloud and precipitation formation, evolution and their impacts on global climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Calibration and Validation of the SAIL Radar

Calibration of a weather radar is not a simple process, as is well described and documented in several articles (Chandrasekar, V, L Baldini, N Bharadwaj, and PL Smith. 2015. "Calibration procedures for global precipitation-measurement ground-validation radars." URSI Radio Science Bulletin 2015(355): 45–73, https://10.23919/URSIRSB.2015.7909473.). Direct hardware-based characterization is called calibration whereas indirect check with other sources such as disdrometer, or comparison with other radars or indirect means, is called validation. The validation process has its own measurement error and the comparison should fall within its limit. In the following we describe calibration and validation processes for the SAIL radar. Based on the comparison of calibration and validation, an addition of 2 dB is suggested for the SAIL radar observations, with a nuanced Z dr calibration correction, as presented. If a fixed Z dr calibration is preferred, a bias addition of 0.5 dB is suggested.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Evaluation of geophysical parameters measured by the Nimbus-7 microwave radiometer for the TOGA Heat Exchange Project

The data distributed by the National Space Science Data Center on the Geophysical parameters of precipitable water, sea surface temperature, and surface-level wind speed, measured by the Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus-7, are evaluated with in situ measurements between Jan. 1980 and Oct. 1983 over the tropical oceans. In tracking annual cycles and the 1982-83 E1 Nino/Southern Oscillation episode, the radiometer measurements are coherent with sea surface temperatures and surface-level wind speeds measured at equatorial buoys and with precipitable water derived from radiosonde soundings at tropical island stations. However, there are differences between SMMR and in situ measurements. Corrections based on radiosonde and ship data were derived supplementing correction formulae suggested in the databook. This study is the initial evaluation of the data for quantitative description of the 1982-83 E1 Nino/Southern Oscillation episode. It paves the way for determination of the ocean-atmosphere moisture and latent heat exchanges, a priority of the Tropical Ocean and Global Atmosphere (TOGA) Heat Exchange Program.

Liu, W. Timothy↗
NASA NTRS2003

NASA's Scientific Agenda for GPM Mission

The objectives of the Global Precipitation Measurement (GPM) Mission are to: 1) Understand the horizontal and vertical structure of rainfall, its macro- and micro-physical nature, and its associated latent heating, 2) Train and calibrate retrieval algorithms for constellation radiometers, 3) Provide sufficient global sampling to significantly reduce uncertainties in short-term rainfall accumulations, and 4) Extend scientific and societal applications. The GPM mission design consists of a core satellite, constellation satellties, precipitation validation sites for error characterization, and a precipitation processing center. This viewgraph presentation profiles the science goals of the mission, and its capability for producing climate data and weather predictions.

Smith, Eric A.↗
NASA NTRS2022

Shoshone River Water Resources: Assessing Sediment Inputs into the Shoshone River in Wyoming to Determine Areas for Protection and Restoration Practices

In 2016, a routine repair operation at the Willwood Dam released tons of built-up sediment into the Shoshone River, polluting the river and negatively impacting the ecosystem. This release greatly affected the communities that rely on the river for farming, recreation, and tourism. In partnership with the Wyoming Department of Environmental Quality (WYDEQ), Shoshone River Partners, and the United States Geological Survey (USGS) Wyoming–Montana Water Science Center, this project utilized satellite imagery and precipitation data to examine turbidity patterns in the Shoshone River between the Buffalo Bill Dam and the Willwood Dam. We used PlanetScope satellite images to assess changes in surface reflectance of the river in response to precipitation events and Global Precipitation Measurement (GPM) Integrated Multi-Spectral Retrieval (IMERG) precipitation data to estimate the lag time between rainfall events and increased turbidity. The National Land Cover Dataset (2019) was used to identify the main land cover types within each sub-basin. The end products included a turbidity analysis, land cover analysis, and precipitation analysis that provided the partners with a better understanding of sediment dynamics in the river. The results demonstrated the feasibility of using PlanetScope data to examine turbidity spatially along small rivers. Sediment plumes from tributaries were visually identified for multiple high turbidity events, and we calibrated an equation that translated reflectance to turbidity, accurately representing plume extent. Inconsistent spectral quality of PlanetScope data, however, limited our ability to assess the relative sediment contribution of the tributaries.

tributaries↗
NASA NTRSDate not supplied

Integrated Multi-Satellite Retrievals for GPM (IMERG)

The Integrated Multi-satellitE Retrievals for GPM (IMERG) product from the U.S. Science Team of the NASA-JAXA Global Precipitation Measurement (GPM) mission provides global satellite precipitation estimates for a wide range of scientific research and societal applications. By adopting a constellation approach using low-Earth orbit passive microwave and geosynchronous-orbit infrared observations from domestic and international partners, IMERG is able to achieve a high resolution of 0.1° every half-hour globally, with three Runs to cater to applications with different latency requirements. With the completion of the reprocessing of the latest version, IMERG V07 now provides improved global satellite precipitation estimates for a period of more than 20 years. This presentation summarizes background on retrievals, the IMERG algorithm, and access to the data. As well, it showcases select results from the data, which might give participants ideas about how they can analyze the data themselves. The presentation ends with a prospectus for the timeline for the upcoming Version 08 and provides a list of references.

IMERG↗
NASA NTRS2021

The Global Satellite Precipitation Constellation: Current Status and Future Requirements

To address the need to map precipitation on a global scale a collection of satellites carrying passive microwave (PMW) radiometers has grown over the last 20 years to form a constellation of about 10-12 sensors at any one time. Over the same period, a broad range of science and user communities has become increasingly dependent on the precipitation products provided by these sensors. The constellation presently consists of both conical and cross-track scanning precipitation-capable multi-channel instruments, many of which are beyond their operational and design lifetime but continue to operate through the cooperation of the responsible agencies. The Group on Earth Observations and the Coordinating Group for Meteorological Satellites (CGMS), among other groups, have raised the issue of how a robust, future precipitation constellation should be constructed. The key issues of current and future requirements for the mapping of global precipitation from satellite sensors can be summarised as providing: 1) sufficiently fine spatial resolutions to capture precipitation-scale systems and reduce the beam-filling effects of the observations; 2) a wide channel diversity for each sensor to cover the range of precipitation types, characteristics and intensities observed across the globe; 3) an observation interval that provides temporal sampling commensurate with the variability of precipitation; and 4) precipitation radars and radiometers in low inclination orbit to provide a consistent calibration source, as demonstrated by the first two spaceborne radar/radiometer combinations on the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) mission Core Observatory (CO). These issues are critical in determining the direction of future constellation requirements, while preserving the continuity of the existing constellation necessary for long-term climate-scale studies.

Precipitation↗
NASA NTRSDate not supplied

Open-Source Science-led Development of the Atmosphere Observing System (AOS) Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David Giles↗
NASA NTRSDate not supplied

Open-Source Science-led Development of the AOS Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David M. Giles↗
NASA NTRSDate not supplied

NASA's Decadal Survey Observing System for Aerosols, Clouds, Convection, and Precipitation (ACCP): The Atmosphere Observing System

The observing system to be described today arose from NASA’s recent Earth Science Decadal Survey. In 2018, NASA funded a 2.5-year study to identify key science requirements and potential architecture solutions to address 2 of the 5 decadal survey recommended designated observables: aerosols and clouds, convection, and precipitation (or ACCP). A set of architectures was recommended to NASA HQ earlier this year, leading to a new mission that we have named the Atmosphere Observing System, or AOS, although that name may eventually change. In this presentation, when I refer to ACCP, I am speaking about the recent 2-year study and when I refer to AOS I am speaking of the new mission currently in its mission concept development phase. I will provide some background on the decadal survey and how it led to the ACCP and AOS goals. I will describe the architecture that was recommended to NASA HQ and summarize current activities as we work toward our mission concept review next spring.

Scott A. Braun↗
DOE OSTI2025

A stress-sensitive precipitate nucleation model beyond classical nucleation theory

The dynamic evolution of precipitates and second phases dictates the strength and stability of most engineering alloys. By design, or as a consequence of thermo-mechanical aging, engineering metals and alloys often form precipitates of second phases when subjecting to diverse thermal and mechanical loads. Precipitation is governed by several factors, including the alloy’s composition, processing/operating temperature, and stresses — either as a result of external loads or from residual stresses. However, state-of-the-art models for precipitate nucleation (i.e., classical nucleation theory) typically lacks consistent method to capture the effects of externally applied and/or internal stresses on nucleation; thereby severely limiting the applicability of these models to complex materials systems and to representative loading scenarios. Here, in this work, we extend upon classical nucleation theory to account for the effect of stresses on precipitation kinetics and thermodynamics. This is achieved via the use of an Eshelbian micromechanics framework keeping track of (i) the stress build up resulting from second phase formation as a function of mechanical load and, (ii) the effects of dislocations on precipitate formation. This new model is applied to σ precipitate in Fe–Cr binary alloys and M 23 C 6 precipitate in 316H stainless steel (SS). Simulations demonstrate the important role of both the remotely applied loads and dislocation pile ups on precipitate nucleation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Future Changes in Midwest Extreme Precipitation Depend on Storm Type

Midwestern U.S. extreme precipitation is associated with multiple storm types including mesoscale convective systems (MCSs) and/or training thunderstorms, tropical cyclone (TC) remnants, and winter storms. Anthropogenic warming is expected to increase climatological precipitation globally, however, there may be little correspondence with regional storm-based changes. Furthermore, uncertainty remains in precipitation-temperature scaling due to use of convective parameterization in most global models. In this study, we investigated historically impactful extreme precipitation events from multiple types of Midwest storms using the Weather Research and Forecasting model at convection-permitting resolution. We simulated five-member ensembles of historical hindcasts and experiments representing the storms in the future using the pseudo-global warming method. We found that future precipitation changes depend on storm type, with increases near Clausius-Clapeyron (CC) for winter storms, no consensus for MCSs and/or training thunderstorms, and sub-CC increases for TC remnants. This research highlights the importance of considering storm type in future extreme precipitation projections.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Open-Source Science-Driven Development of the Science Data System (SDS) for Earth System Observatory (ESO) Atmospheric Missions

The NASA Earth System Observatory (ESO) atmospheric missions will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The Science Data System (SDS) will deploy the adaptive processing system (APS) developed within the Cloud to manage the research and operational processing of ESO atmospheric mission orbital and suborbital sensors and curate these data for near real-time and collection reprocessing and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage and distribution. Further, the SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The SDS follows NASA’s commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the SDS system components will be developed with open-source concepts including components of APS itself as well as ESO atmospheric mission algorithms. This presentation describes the framework of the SDS and its integral part in facilitating OSS within the ESO atmospheric missions.

David M. Giles↗
NASA NTRSDate not supplied

Science Performance Comparison Between a Spaceborne HSRL and CALIOP

NASA operates airborne and spaceborne lidar systems to answer aerosol and cloud related science questions. NASA Langley Research Center has extensive experience operating lidar systems in both regimes. These include High Spectral Resolution Lidar (HSRL) systems, which have been operating on airborne systems,and CALIOP, the spaceborne elastic backscatter lidar system on board CALIPSO. In support of NASA’s ACCP Study Plan to address the Aerosol (A) and Cloud, Convection, and Precipitation (CCP) Designated Observables called out in the 2017 Earth Science Decadal Survey, LaRC is using lidar simulation tools to evaluate the performance of spaceborne systems using both the HSRL and elastic backscatter techniques. The LaRC high-fidelity simulator tool models both HSRL and elastic backscatter lidar systems by modeling the effects of the instrument specifications and producing backscatter signals generated from molecules, aerosols, clouds, ocean surface, and ocean subsurface. It derives the solar background signals from the scene specific aerosol and cloud characteristics, surface type, and sun elevation. The tool models both random and systematic uncertainties in the retrieved geophysical parameters. In this study, we will present simulated results that compare and contrast the performance of spaceborne HSRL systems to the performance of CALIOP. As recommended by the Decadal Study, ACCP is seeking advances over performance that has been achieved by A-Train. This study will provide a description of the HSRL and elastic backscatter techniques and demonstrate how and why the performance of these HSRL systems exceeds the performance of CALIOP.

Kathleen A Powell↗
NASA NTRS2018

Global Precipitation Measurement (GPM): Unified Precipitation Estimation From Space

Global Precipitation Measurement (GPM) is an international satellite mission that uses measurements from an advanced radar/radiometer system on a Core Observatory as reference standards to unify and advance precipitation estimates through a constellation of research and operational microwave sensors. GPM is a science mission focusing on a key component of the Earth's water and energy cycle, delivering near real-time observations of precipitation for monitoring severe weather events, freshwater resources, and other societal applications. This work presents the GPM mission design, together with descriptions of sensor characteristics, inter-satellite calibration, retrieval methodologies, ground validation activities, and societal applications.

satellite↗
NASA NTRSDate not supplied

Open Science Approach to Analyze Climate-Crop Relationships in the US Leveraging GES DISC and Galaxy Workflows

Understanding the intricate relationship between climate variability and agricultural production is crucial for ensuring food security. This study investigates the impact of climate parameters, such as temperature, precipitation, and soil moisture, on major US crop yields. Adopting an open science approach, the study analyzes the impact of climate on agricultural production in the United States. The Galaxy workflow engine serves as the primary tool for integrating climate data from the Goddard Earth Sciences Data and Information Services Center (GES DISC), retrieved via the Giovanni system, with yield statistics from the United States Department of Agriculture’s National Agricultural Statistics Service (USDA NASS). Extensions for reading, preprocessing, and analyzing external data have been developed, enabling the creation of workflows within the Galaxy platform. The development of a reproducible workflow allows for the calculation of seasonal climate averages, which are then assessed for their correlation with crop yields. This methodology ensures the replicability of the research, promoting transparency and collaboration in the scientific community. Correlational and regression analyses have been applied to different sub-zones and crops. The findings from this research offer valuable insights into the relationship between climate parameters and crop yields. These insights contribute to a deeper understanding of climate-crop relationships, providing a solid foundation for informed decision-making in the agricultural sector. The high correlation values indicate a significant relationship between climate parameters and crop yields, underscoring the importance of considering climate factors in agricultural planning and policymaking. This research also exemplifies the power of open science in advancing our understanding of complex environmental and agricultural phenomena. By leveraging open data and services, it provides a robust and replicable framework for future studies in this critical field.

Open science↗