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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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NASA NTRS2020

NASA Global Satellite and Model Data Products and Services for Tropical Meteorology and Climatology

Satellite remote sensing and model data play an important role in research and applications of tropical meteorology and climatology over vast, data sparse oceans and remote continents. Since the first weather satellite was launched by NASA in 1960, a large collection of NASA's Earth science data is freely available to the research and application communities around the world, significantly improving our overall understanding of the Earth system and environment. Established in the mid-80s, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), located in Maryland, USA, is a data archive center for multidisciplinary, satellite and model assimilation data products. As one of the 12 NASA data centers in Earth Sciences, GES DISC hosts several important NASA satellite missions for tropical meteorology and climatology such as the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM) mission and the Modern-Era Retrospective analysis for Research and Applications (MERRA). Over the years, GES DISC has developed data services to facilitate data discovery, access, distribution, analysis and visualization, including Giovanni, an online analysis and visualization tool without the need to download data and software. Despite many efforts for improving data access, still quite a number of challenges remain, such as finding datasets and services for a specific research topic or project, especially for inexperienced users or users outside the remote sensing community. In this article, we list and describe major NASA satellite remote sensing and model datasets and services for tropical meteorology and climatology along with examples of using the data and services, in hope that may help users better utilize the information in their research and applications.

tropical meteorology and climatology, data, servic↗
NASA NTRS1998

Prototype Local Data Integration System and Central Florida Data Deficiency

This report describes the Applied Meteorology Unit's (AMU) task on the Local Data Integration System (LDIS) and central Florida data deficiency. The objectives of the task are to identify all existing meteorological data sources within 250 km of the Kennedy Space Center (KSC) and the Eastern Range at Cape Canaveral Air Station (CCAS), identify and configure an appropriate LDIS to integrate these data, and implement a working prototype to be used for limited case studies and data non-incorporation (DNI) experiments. The ultimate goal for running LDIS is to generate products that may enhance weather nowcasts and short-range (less than 6 h) forecasts issued in support of the 45th Weather Squadron (45 WS), Spaceflight Meteorology Group (SMG), and the Melbourne National Weather Service (NWS MLB) operational requirements. The LDIS has the potential to provide added value for nowcasts and short term forecasts for two reasons. First, it incorporates all data operationally available in east central Florida. Second, it is run at finer spatial and temporal resolutions than current national-scale operational models. In combination with a suitable visualization tool, LDIS may provide users with a more complete and comprehensive understanding of evolving fine-scale weather features than could be developed by individually examining the disparate data sets over the same area and time. The utility of LDIS depends largely on the reliability and availability of observational data. Therefore, it is important to document all existing meteorological data sources around central Florida that can be incorporated by it. Several factors contribute to the data density and coverage over east central Florida including the level in the atmosphere, distance from KSC/CCAS, time, and prevailing weather. The central Florida mesonet consists of existing surface meteorological and hydrological data available from the Tampa NWS and data servers at Miami and Jacksonville. However the utility of these data for operational use is limited, mainly because there are relatively few additional meteorological observations within 50 km of KSC/CCAS to supplement existing METAR and KSC/CCAS tower reports.

Manobianco, John↗
DOE OSTI2019

Panama Land Model (CLM/ELM) Site Drivers

This data package contains meteorological and surface data at the Barro Colorado Island (BCI) and Bosque Protector San Lorenzo (Fort Sherman) NGEE Tropics sites in Panama. Data has been converted into formats usable by the land-models driving the Functionally-Assembled Terrestrial Ecosystem Simulator (FATES). Surface datasets are model release dependent and may have to be re-processed for later versions of the model. Current surface datasets based off of "<>_16pfts_Irrig_CMIP6_simyr2000_c170824.nc" See the README_ngeet_lm_driver text file in the attached zip file for detailed descriptions of the included data files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Ground-based All-sky Mid-infrared and Visible Imagery for Purposes of Characterizing Cloud Properties

This paper describes the All Sky Infrared Visible Analyzer (ASIVA), a multi-purpose visible and infrared sky imaging and analysis instrument whose primary functionality is to provide radiometrically calibrated imagery in the mid-infrared (mid-IR) atmospheric window. This functionality enables the determination of diurnal hemispherical cloud fraction (HCF) and estimates of sky/cloud temperature from which one can derive estimates of cloud emissivity and cloud height. This paper describes the calibration methods and performance of the ASIVA instrument with particular emphasis on data products being developed for the meteorological community. Data presented here were collected during a field campaign conducted at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Climate Research Facility from May 21 to July 27, 2009. The purpose of this campaign was to determine the efficacy of IR technology in providing reliable nighttime HCF data. Significant progress has been made in the analysis of the campaign data over the past several years and the ASIVA has proven to be an excellent instrument for determining HCF as well as several other important cloud properties.

analyzer↗
NASA NTRS2013

The Hyperspectral Infrared Imager (HyspIRI) Public Health and Air Quality Applications

The neglected tropical diseases (NTDs), a group of chronic, debilitating, and poverty-promoting parasitic, bacterial, and some viral and fungal infections, are among the most common causes of illness of the poorest people living in developing countries. Abiotic environmental factors are important in determining the distribution of disease-causing vectors and their life-cycles. HyspIRI observations can be merged through a Land Data Assimilation System (LDAS) be used to drive spatially-explicit ecological models of NTD vectors distribution & life cycles. Assimilations will be driven by observational data LDAS and satellite-derived meteorological forcing data, parameter datasets, and assimilation observations. HyspIRI hyperspectral measurements would provide global measurements of surface mineralogy and biotic crusts important in accessing the impact of dust in human health. HyspIRI surface thermal measurements would also help identify the variability of dust sources due to surface moisture conditions and map mineralogy.

Luvall, Jeffrey C.↗
NASA NTRS2013

The Hyperspectral Infrared Imager (HyspIRI) Public Health and Air Quality Applications

The neglected tropical diseases (NTDs), a group of chronic, debilitating, and poverty-promoting parasitic, bacterial, and some viral and fungal infections, are among the most common causes of illness of the poorest people living in developing countries. Abiotic environmental factors are important in determining the distribution of disease-causing vectors and their life-cycles. HyspIRI observations can be merged through a Land Data Assimilation System (LDAS) be used to drive spatially-explicit ecological models of NTD vectors distribution & life cycles. Assimilations will be driven by observational data LDAS and satellite-derived meteorological forcing data, parameter datasets, and assimilation observations. HyspIRI hyperspectral measurements would provide global measurements of surface mineralogy and biotic crusts important in accessing the impact of dust in human health. HyspIRI surface thermal measurements would also help identify the variability of dust sources due to surface moisture conditions and map mineralogy.

Luvall, Jeffrey C.↗
NASA NTRS2013

The Hyperspectral Infrared Imager (HyspIRI) Public Health & Air Quality Applications

The neglected tropical diseases (NTDs), a group of chronic, debilitating, and poverty-promoting parasitic, bacterial, and some viral and fungal infections, are among the most common causes of illness of the poorest people living in developing countries. Abiotic environmental factors are important in determining the distribution of disease-causing vectors and their life-cycles. HyspIRI observations can be merged through a Land Data Assimilation System (LDAS) be used to drive spatially-explicit ecological models of NTD vectors distribution & life cycles. Assimilations will be driven by observational data LDAS and satellite-derived meteorological forcing data, parameter datasets, and assimilation observations. HyspIRI hyperspectral measurements would provide global measurements of surface mineralogy and biotic crusts important in accessing the impact of dust in human health. HyspIRI surface thermal measurements would also help identify the variability of dust sources due to surface moisture conditions and map mineralogy.

Luvall, Jeffrey C.↗
NASA NTRS2014

The Hyperspectral Infrared Imager (HyspIRI) Public Health and Air Quality Applications

The neglected tropical diseases (NTDs), a group of chronic, debilitating, and poverty-promoting parasitic, bacterial, and some viral and fungal infections, are among the most common causes of illness of the poorest people living in developing countries. Abiotic environmental factors are important in determining the distribution of disease-causing vectors and their life-cycles. HyspIRI observations can be merged through a Land Data Assimilation System (LDAS) be used to drive spatially-explicit ecological models of NTD vectors distribution and life cycles. Assimilations will be driven by observational data LDAS and satellite-derived meteorological forcing data, parameter datasets, and assimilation observations. HyspIRI hyperspectral measurements would provide global measurements of surface mineralogy and biotic crusts important in accessing the impact of dust in human health. HyspIRI surface thermal measurements would also help identify the variability of dust sources due to surface moisture conditions and map mineralogy.

Luvall, Jeffrey C.↗
DOE OSTI2012

Maximum Photovoltaic Penetration Levels on Typical Distribution Feeders: Preprint

This paper presents simulation results for a taxonomy of typical distribution feeders with various levels of photovoltaic (PV) penetration. For each of the 16 feeders simulated, the maximum PV penetration that did not result in steady-state voltage or current violation is presented for several PV location scenarios: clustered near the feeder source, clustered near the midpoint of the feeder,clustered near the end of the feeder, randomly located, and evenly distributed. In addition, the maximum level of PV is presented for single, large PV systems at each location. Maximum PV penetration was determined by requiring that feeder voltages stay within ANSI Range A and that feeder currents stay within the ranges determined by overcurrent protection devices. Simulations were run inGridLAB-D using hourly time steps over a year with randomized load profiles based on utility data and typical meteorological year weather data. For 86% of the cases simulated, maximum PV penetration was at least 30% of peak load.

14 SOLAR ENERGY↗
DOE OSTI2025

Enhancing Streamflow Reanalysis Across the Conterminous US Leveraging Multiple Gridded Precipitation Data Sets

Streamflow observations, essential for various water resource applications, are often unavailable at critical locations in need. Although different models have been proposed to enhance streamflow predictability at ungauged locations, the challenge extends beyond model fidelity. Differences in meteorologic forcing data sets, precipitation in particular, can significantly affect the accuracy of hydrologic predictions. This challenge intensifies across regions characterized by diverse hydro-climatological and geographical conditions, such as in the conterminous US (CONUS) where a single precipitation product struggles to consistently replicate observed hydrographs, particularly peak flow dynamics. To enhance streamflow predictions, we utilize a VIC-RAPID hydrologic modeling framework driven by multiple commonly used meteorological forcing data sets, such as Daymet, PRISM, ST4, AORC, and their hybrids and create multiple sets of 40-year (1980–2019) hourly, daily, and monthly streamflow reanalysis, Dayflow Version 2, for 2.7 million river reaches across the CONUS. Most forcings lead to skillful streamflow performance, except for ST4 in the mountainous west, where severe radar blockage adversely affects the accuracy. The evaluation using over 6,000 hourly stream gauges shows that hourly AORC and ST4 lead to improved annual peak flow performance over Daymet—driven streamflow (Dayflow V1), particularly in smaller basins, highlighting the value of high temporal resolution forcings in hydrologic predictions. Compared with other benchmark data sets like National Water Model V3.0, AORC-driven VIC-RAPID exhibits improved regional streamflow performance, with comparable peak flow representation. We envision that multi-forcing streamflow reanalysis data can inform regions in need of forcing data enhancement, diagnose hydrologic model performance, and benefit diverse water resource applications.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Transmission of radiometer data from the Synchronous Meteorological Satellite

The Synchronous Meteorological Satellite uses a spin scanner radiometer which generates eight visual signals and two infrared signals. These signals are multiplexed and converted into a 28-Mbps data stream. This signal is transmitted to ground by quadriphase modulation at 1686.1 MHz. On the ground, the digital signal is reconstructed to an analog signal. To conserve bandwidth, an analog-to-digital converter with a nonlinear transfer function was used for the visual signals. The size of the quantization step was made proportional to the noise output of the scanner photomultiplier tube which increases as the square root of incident light. The radiometer data transmission link was simulated on a digital computer to determine the transfer function. Some results of the simulation are shown.

Davies, R. S.↗
DOE OSTI2025

Investigating Building Energy Consumption and CO2 Emission in Phoenix Using AutoBEM and Future Typical Meteorological Year (fTMY) Weather Data

This research investigates the energy performance and CO2 emissions of each building stock across the Phoenix metropolitan area using the Automatic Building Energy Modeling (AutoBEM) framework and Model America v2 (MAv2) dataset from Oak Ridge National Laboratory (ORNL). Typical Meteorological Year (TMY) and Future Typical Meteorological Year (fTMY) files were used for AutoBEM simulation. The simulation results from TMY and fTMY were compared. It was found that a projected 10.28% increase in total CO2 emissions and a 9.30% rise in total energy consumption by 2080–2099 relative to current typical conditions. The results highlight the disparities in emissions among different building stocks and the influence of climate change on future energy demand. The findings underscore the necessity of targeted policy interventions and retrofitting strategies (eg. advanced HVAC systems, improved insulation, reflective roofing) to mitigate emissions in high-energy-use and emission-intensed buildings, particularly as climate conditions evolve. This study contributes to the growing understanding of building-sector emissions and their long-term implications under future climate scenarios.

Li, Hang [ORNL] (ORCID:0000000306001920)↗
DOE OSTI2023

Achieving Realistic Runoff in the Western United States with a Land Surface Model Forced by Dynamically Downscaled Meteorology

Abstract In this study, we calibrate a regional climate model’s (RCM) underlying land surface model (LSM). In addition to providing a realistic representation of runoff across the hydroclimatically diverse western United States, this is done to take advantage of the RCM’s ability to physically resolve meteorological forcing data in ungauged regions, and to prepare the calibrated hydrologic model for tight coupling, or the ability to represent land surface–atmosphere interactions, with the RCM. Specifically, we use a 9-km resolution meteorological forcing dataset across the western United States, from the fifth generation ECMWF Reanalysis (ERA5) downscaled by the Weather Research Forecasting (WRF) regional climate model, as an offline forcing for Noah-Multiparameterization (Noah-MP). We detail the steps involved in producing an LSM capable of accurately representing runoff, including physical parameterization selection, parameter calibration, and regionalization to ungauged basins. Based on our model evaluation from 1954 to 2021 for 586 basins with daily natural streamflow, the streamflow bias is reduced from 24.2% to 4.4%, and the median daily Nash–Sutcliffe efficiency (NSE) is improved from 0.12 to 0.36. When validating against basins with monthly natural streamflow data, we obtain a similar reduction in bias and a median monthly NSE improvement from 0.18 to 0.56. In this study, we also discover the optimal setup when using a donor-basin method to regionalize parameters to ungauged basins, which can vary by 0.06 NSE for unique designs of this regionalization method. Significance Statement This study provides useful guidance for improving a land surface model to accurately represent runoff across a spatially extensive and hydroclimatically diverse region (the western United States). The land surface model is updated to represent runoff more accurately at gauged basins, and then additionally updated for basins without observational data using a mathematical approach called the donor-basin method. We make use of a regional climate model’s reanalysis-derived meteorological data and its underlying land surface model to achieve realistic runoff. The calibrated land surface model can thus be tightly coupled in subsequent studies in a manner that should more accurately reflect runoff conditions. Findings from this study will serve as a useful reference for the atmospheric (and hydrologic) modeling communities and their ability to represent large-scale hydrology accurately.

Meteorology & Atmospheric Sciences↗
NASA NTRS1985

Application of the Man-computer Interactive Data Access System (McIDAS) to aerospace meteorology

The Man-computer Interactive Data Access System (McIDAS) considered in this paper has been in use at Marshall Space Flight Center (MSFC) since 1981. The MSFC McIDAS system is primarily employed as a research tool, taking into account rainfall estimates as deduced from Scanning Multichannel Microwave Radiometer (SMMR) data, remote sensing sensor development (MAMS), Doppler-lidar derived winds, cloud tracked winds, and analysis of lightning ground strike data. With respect to the SMMR data analysis, passive microwave satellite data are displayed on McIDAS as images. Two major research efforts are concerned with the determination of mesoscale winds. These efforts are based on a utilization of a Doppler-lidar system, and GOES multispectral imagery. It is pointed out that future plans include increased usage of the McIDAS system.

Meyer, P. J.↗
NASA NTRS1976

A combined boundary-profile and automated data-reduction and analysis system

A portable boundary-layer meteorological data-acquisition and analysis system is described which employs a small tethered balloon and a programmable calculator. The system is capable of measuring pressure, wet- and dry-bulb temperature, wind speed, and temperature fluctuations as a function of height and time. Other quantities, which can be calculated in terms of these, can also be made available in real time. All quantities, measured and calculated, can be printed, plotted, and stored on magnetic tape in the field during the data-acquisition phase of an experiment.

Deloach, R.↗
NASA NTRS2009

A Climate-Data Record of the "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

We are developing a climate-data record (CDR of daily "clear-sky" ice-surface temperature (IST) of the Greenland Ice Sheet, from 1982 to the present using Advanced Very High Resolution Radiometer (AVHRR) (1982 - present) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data (2000 - present) at a resolution of approximately 5 km. The CDR will be continued in the National Polar-orbiting Operational Environmental Satellite System Visible/Infrared Imager Radiometer Suite era. Two algorithms remain under consideration. One algorithm under consideration is based on the split-window technique used in the Polar Pathfinder dataset (Fowler et al., 2000 & 21007). Another algorithm under consideration, developed by Comiso (2006), uses a single channel of AVHRR data (channel 4) in conjunction with meteorological-station data to account for atmospheric effects and drift between AVHRR instruments. Known issues being addressed in the production of the CDR are: tune-series bias caused by cloud cover (surface temperatures can be different under clouds vs. clear areas) and cross-calibration in the overlap period between AVHRR instruments, and between AVHRR and MODIS instruments. Because of uncertainties, mainly due to clouds (Stroeve & Steffen, 1998; Wang and Key, 2005; Hall et al., 2008 and Koenig and Hall, submitted), time-series of satellite 1S'1" do not necessarily correspond to actual surface temperatures. The CDR will be validated by comparing results with automatic-,",eather station (AWS) data and with satellite-derived surface-temperature products. Regional "clear-sky" surface temperature increases in the Arctic, measured from AVHRR infrared data, range from 0.57+/-0.02 deg C (Wang and Key, 2005) to 0.72+/-0.10 deg C (Comiso, 2006) per decade since the early 1980s. Arctic warming has important implications for ice-sheet mass balance because much of the periphery of the Greenland Ice Sheet is already near 0 deg C during the melt season, and is thus vulnerable to rapid melting if temperatures continue to increase. References

Hall, D. K.↗