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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 19 records

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NASA NTRS1988

Effect of wet tropospheric path delays on estimation of geodetic baselines in the Gulf of California using the Global Positioning System

Surface Meteorological (SM) and Water Vapor Radiometer (WVR) measurements are used to provide an independent means of calibrating the GPS signal for the wet tropospheric path delay in a study of geodetic baseline measurements in the Gulf of California using GPS in which high tropospheric water vapor content yielded wet path delays in excess of 20 cm at zenith. Residual wet delays at zenith are estimated as constants and as first-order exponentially correlated stochastic processes. Calibration with WVR data is found to yield the best repeatabilities, with improved results possible if combined carrier phase and pseudorange data are used. Although SM measurements can introduce significant errors in baseline solutions if used with a simple atmospheric model and estimation of residual zenith delays as constants, SM calibration and stochastic estimation for residual zenith wet delays may be adequate for precise estimation of GPS baselines. For dry locations, WVRs may not be required to accurately model tropospheric effects on GPS baselines.

Tralli, David M.↗

NASA NTRS2011

Meteorological Conditions Experienced During the Orion Pad Abort Test

Presentation describes the atmosphere at launch minus one day and a forecast associated for launch. Also presented is the day of launch observations from weather balloons, the 924 MHz wind profiler, and four Surface Automatic Meteorological System (SAMS) from nearby locations. Details will be provided illustrating the terrain and atmosphere interactions that produced strong winds at the launch site and calm winds at the balloon launch facility just 3 miles away.

Teets, Edward H., Jr.↗

NASA NTRS1978

Feasibility of estimation of surface air temperature from meteorological satellite data test plan

A conceptual system designed to estimate daily surface air temperatures utilizing radiometric data obtained from polar orbiting meteorological satellites is discussed in this memorandum. The Surface Air Temperature Estimation System is an outgrowth of previous developmental and operational systems. The system represents an effort to integrate both satellite and surface meteorological observations into an operational framework which would be usable worldwide.

Phinney, D. E.↗

NASA NTRS1990

A noise assessment and prediction system

A system has been designed to provide an assessment of noise levels that result from testing activities at Aberdeen Proving Ground, Md. The system receives meteorological data from surface stations and an upper air sounding system. The data from these systems are sent to a meteorological model, which provides forecasting conditions for up to three hours from the test time. The meteorological data are then used as input into an acoustic ray trace model which projects sound level contours onto a two-dimensional display of the surrounding area. This information is sent to the meteorological office for verification, as well as the range control office, and the environmental office. To evaluate the noise level predictions, a series of microphones are located off the reservation to receive the sound and transmit this information back to the central display unit. The computer models are modular allowing for a variety of models to be utilized and tested to achieve the best agreement with data. This technique of prediction and model validation will be used to improve the noise assessment system.

Olsen, Robert O.↗

NASA NTRS1994

The integrated sounding system: Description and preliminary observations from TOGA COARE

An Integrated Sounding System (ISS) that combines state-of-the-art remote and in situ sensors into a single transportable facility has been developed jointly by the National Center for Atmospheric Research (NCAR) and the Aeronomy Laboratory of the National Oceanic and Atmospheric Administration (NOAA/AL). The instrumentation for each ISS includes a 915-MHz wind profiler, a Radio Acoustic Sounding System (RASS), an Omega-based NAVAID sounding system, and an enhanced surface meteorological station. The general philosophy behind the ISS is that the integration of various measurement systems overcomes each system's respective limitations while taking advantage of its positive attributes. The individual observing systems within the ISS provide high-level data products to a central workstation that manages and integrates these measurements. The ISS software package performs a wide range of functions: real-time data acquisition, database support, and graphical displays; data archival and communications; and operational and posttime analysis. The first deployment of the ISS consists of six sites in the western tropical Pacific--four land-based deployments and two ship-based deployments. The sites serve the Coupled Ocean-Atmosphere Response Experiment (COARE) of the Tropical Ocean and Global Atmosphere (TOGA) program and TOGA's enhanced atmospheric monitoring effort. Examples of ISS data taken during this deployment are shown in order to demonstrate the capabilities of this new sounding system and to demonstrate the performance of these in situ and remote sensing instruments in a moist tropical environment. In particular, a strong convective outflow with a pronounced impact of the atmospheric boundary layer and heat fluxes from the ocean surface was examined with a shipboard ISS. If these strong outflows commonly occur, they may prove to be an important component of the surface energy budget of the western tropical Pacific.

Parsons, David↗

NASA NTRS2018

Soil Moisture Active Passive (SMAP) Project Assessment Report for Version 4 of the L4_SM Data Product

This report provides an assessment of Version 4 of the SMAP Level 4 Surface and Root Zone Soil Moisture (L4_SM) product, released on 14 June 2018. The assessment includes comparisons of L4_SM soil moisture and temperature estimates with in situ measurements from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product, including observation-minus-forecast (O-F) brightness temperature residuals and soil moisture analysis increments.Together, the core validation site comparisons and the statistics of the assimilation diagnostics areconsidered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to upscaling errors from the point-scale to the grid-cell scale of the data product.The Version 4 L4_SM product benefits from an improved land surface modeling system and from retrospective surface meteorological forcing data that are as consistent as possible with the present-day datain terms of their climatology. Specifically, the model changes include revised parameters and parameterizations for (i) the surface energy balance, (ii) recharge from below of the model's surface excess reservoir, and (iii) the snow depletion curve. Updated ancillary inputs include improved datasets for landcover, topography, and vegetation height. The Version 4 algorithm further includes a revised approach to precipitation corrections that improves the precipitation climatology in Africa and the high-latitudes. Moreover, for system calibration the model is forced retrospectively with MERRA-2 reanalysis data, which are more consistent with the near-real time GEOS forward processing (FP) data used during the SMAP period than the retrospective GEOS data that were available for previous L4_SM versions. An analysis of the time-average surface and root zone soil moisture shows that the global pattern ofarid and humid regions is captured by the Version 4 L4_SM estimates. Owing to the changes in the landsurface modeling system, surface soil moisture is typically drier by several volumetric percent in Version 4 compared to Version 3, whereas root zone soil moisture is wetter in Version 4 in some regions and drierin others. Because of these climatological differences, the Version 3 and Version 4 products should not be combined into a single dataset for use in applications.Results from the core validation site comparisons indicate that Version 4 of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the RMSE after removal of the long-term mean difference (ubRMSE). The overall ubRMSE of the 3-hourly L4_SM dataat the 9 km scale is 0.039 m3 m-3 for surface soil moisture and 0.029 m3 m-3 for root zone soil moisture,below the 0.04 m3 m-3 requirement. The L4_SM estimates are an improvement over estimates from a model-only Nature Run version 7.2 (NRv7.2), which demonstrates the beneficial impact of the SMAP brightness temperature data. Overall, L4_SM surface and root zone soil moisture estimates are more skillful than NRv7.2 estimates, with statistically significant improvements at the 5% level for surface soil moisture R and anomaly R values. Results from comparisons of the L4_SM product to i

Reichle, Rolf H.↗

NASA NTRSDate not supplied

Using Time Series Data Products to Support ASHRAE’s Historic and Future Climate Data Needs through NASA’s POWER Web Services

To address the data needs for resilience and sustainability of building systems within ASHRAE, the NASA Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data on a long-term, global scale. Solar data from several NASA projects and meteorological data from NASA assimilation models have been reformatted and disseminated to the public via a user friendly web GIS-enabled based data portal (https://power.larc.nasa.gov) in selectable data formats, immediately amenable to key industry wide decision support tools such as EnergyPlus. Time series of potential climate conditions from downscaled climate simulations are being made available for similar statistics and formats. An emphasis is placed upon obtaining and utilizing time series data to conduct analysis of building system performance for current and planning building systems for energy savings and greenhouse gas emissions. This presentation has the learning following learning objectives for the ASHRAE community: 1) Learn how NASA POWER’s web service suite can provide supplementary solar and surface meteorological data parameters, including a discussion of uncertainty. 2) Learn how downscaled climate scenario information can be provided to evaluate potential future requirements. The presentation is part of a forum entitled, "Weather Data for Large-Scale Building Energy Modeling".

time series↗

NASA NTRS2021

A High-Resolution Land Data Assimilation System Optimized for the Western United States

The Western Land Data Assimilation System (WLDAS) is a custom instance of the NASA Land Information System that combines land surface parameters, meteorological forcing data, and satellite products within a land surface model to produce daily estimates of the water and energy budget variables for the western United States. WLDAS was configured through discussions with partners, with the goal of groundwater sustainability planning for the state of California in mind. The publicly available output dataset has a 1-km grid resolution and spans 1979–present, which makes it suitable for water resources assessments. The data are also able to contextualize the recent drought events in California. Assimilation of Leaf Area Index, which is demonstrated herein to improve simulation over agricultural areas in California, specifically in terms of evapotranspiration in irrigation regions, will be included along with other data assimilation in subsequent releases of WLDAS.

land surface modeling↗

NASA NTRS2002

Surface Temperature Assimilation in the Global Land Data Assimilation System (GLDAS)

The Global Land Data Assimilation System (GLDAS) is a global land parameterization that uses prescribed meteorology as forcing in order to determine regular gridded land surface states (temperature and moisture) and other properties (e.g. water and heat fluxes). In the present experiment, the assimilation of surface skin temperature is incorporated into the land parameterizations. The meteorological forcing was derived from the Goddard Earth Observing System (GEOS-3) Data Assimilation System (DAS) for the full year of 1998 GLDAS can use several land parameterizations, but here we use the Mosaic land surface model and the Common Land Model (CLM). TOVS surface temperature observations are assimilated into GLDAS. The TOVS observations are less frequent that observations used in previous experiments (ISCCP). The purpose of this presentation is to evaluate the impact of the TOVS assimilation on both Mosaic and CLM. We will especially consider the impact of coarse temporal observations on the assimilation and bias correction.

Bosilovich, Michael G.↗

NASA NTRS2017

NIAC Phase 1 Final Study Report on Titan Aerial Daughtercraft

Saturns giant moon Titan has become one of the most fascinating bodies in the Solar System. Even though it is a billion miles from Earth, data from the Cassini mission reveals that Titan has a very diverse, Earth-like surface, with mountains, fluvial channels, lakes, evaporite basins, plains, dunes, and seas [Lopes 2010] (Figure 1). But unlike Earth, Titans surface likely is composed of organic chemistry products derived from complex atmospheric photochemistry [Lorenz 2008]. In addition, Titan has an active meteorological system with observed storms and precipitation-induced surface darkening suggesting a hydrocarbon cycle analogous to Earths water cycle [Turtle 2011].Titan is the richest laboratory in the solar system for studying prebiotic chemistry, which makes studying its chemistry from the surface and in the atmosphere one of the most important objectives in planetary science [Decadal 2011]. The diversity of surface features on Titan related to organic solids and liquids makes long-range mobility with surface access important [Decadal 2011]. This has not been possible to date, because mission concepts have had either no mobility (landers), no surface access (balloons and airplanes), or low maturity, high risk, and/or high development costs for this environment (e,g. large, self-sufficient, long-duration helicopters). Enabling in situ mobility could revolutionize Titan exploration, similarly to the way rovers revolutionized Mars exploration. Recent progress on several fronts has suggested that small-scale rotorcraft deployed as daughtercraft from a lander or balloon mothercraft may be an effective, affordable approach to expanding Titan surface access. This includes rapid progress on autonomous navigation capabilities of such aircraft for terrestrial applications and on miniaturization, driven by the consumer mobile electronics market, of high performance of sensors, processors, and other avionics components needed for such aircraft. Chemical analysis, for example with a mass spectrometer, will be important to any Titan surface mission. Anticipating that it may be more practical to host chemical analysis instruments on a mothership than a daughtercraft, we defined system and mission concepts that deploy a small rotorcraft, termed a Titan Aerial Daughtercraft (TAD), from a lander or balloon to perform high-resolution imaging and mapping, potentially land to acquire microscopic images or other in situ measurements, and acquire samples to return to analytical instruments on the mothership. In principle, the ability to recharge batteries in TAD from a radioisotope or other long-lived power source on the mothership could enable multiple sorties. For a lander-based mission, a variety of landing sites is conceivable, including near lake margins, in dry lake beds, or in regions of plains, dunes, or putative cryovolanic or impact melt features. Such missions may require landing with greater precision than in previous missions (Huygens) and mission studies; this could also enhance the ability of TAD to reach interesting terrain from the landing site. Precision descent may also benefit balloon missions, with or without a daughtercraft, by increasing the probability that the balloon will drift over desired terrain early in its mission. Given these potential benefits, the overall concept studied here includes brief consideration of precision descent for landing or balloon deployment, followed by one or more sorties by a rotorcraft deployed from the mothership, with the ability to return to the mothership.

Saturn↗

NASA NTRS2026

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗

NASA NTRS1990

Stochastic estimation of tropospheric path delays in global positioning system geodetic measurements

Water vapor radiometric and surface meteorological measurements taken during three GPS geodetic experiments are used to calculate process noise levels for random walk and first-order Gauss-Markov temporal models of tropospheric path delays. Entire wet and combined wet and dry zenith delays at each network site are estimated simultaneously with the geodetic parameters without prior calibration. The path delays and corresponding baseline estimates are compared to those obtained with calibrated data and stochastic residual delays. In this manner, the marginal utility of a priori tropospheric calibration is assessed given the ability to estimate the path delays directly using only the GPS data. Estimation of total zenith path delays with appropriate random walk or Gauss-Markov models yields baseline repeatabilities of a few parts in 100 million. Results suggest that GPS data alone have sufficient strength to resolve centimeter-level zenith path delay fluctuations over periods of a few minutes.

Tralli, David M.↗

NASA NTRS2016

Surface Pressure Dependencies in the Geos-Chem-Adjoint System and the Impact of the GEOS-5 Surface Pressure on CO2 Model Forecast

In the GEOS-Chem Adjoint (GCA) system, the total (wet) surface pressure of the GEOS meteorology is employed as dry surface pressure, ignoring the presence of water vapor. The Jet Propulsion Laboratory (JPL) Carbon Monitoring System (CMS) research team has been evaluating the impact of the above discrepancy on the CO2 model forecast and the CO2 flux inversion. The JPL CMS research utilizes a multi-mission assimilation framework developed by the Multi-Mission Observation Operator (M2O2) research team at JPL extending the GCA system. The GCA-M2O2 framework facilitates mission-generic 3D and 4D-variational assimilations streamlining the interfaces to the satellite data products and prior emission inventories. The GCA-M2O2 framework currently integrates the GCA system version 35h and provides a dry surface pressure setup to allow the CO2 model forecast to be performed with the GEOS-5 surface pressure directly or after converting it to dry surface pressure.

Carbon Monitoring System↗

NASA NTRS2016

Surface Pressure Dependencies in the GEOS-Chem-Adjoint System and the Impact of the GEOS-5 Surface Pressure on CO2 Model Forecast

Lee, Meemong↗

NASA NTRS2018

Climate Reanalysis: Progress and Future Prospects

Reanalysis is the process whereby an unchanging data assimilation system is used to provide a consistent reprocessing of observations, typically spanning an extended segment of the historical data record. The process relies on an underlying model to combine often-disparate observations in a physically consistent manner, enabling production of gridded data sets for a broad range of applications including the study of historical weather events, preparation of climatologies, business sector development and, more recently, climate monitoring. Over the last few decades, several generations of reanalyses of the global atmosphere have been produced by various operational and research centers, focusing more or less on the period of regular conventional and satellite observations beginning in the mid to late twentieth century. There have also been successful efforts to extend atmospheric reanalyses back to the late nineteenth and early twentieth centuries, using mostly surface observations. Much progress has resulted from (and contributed to) advancements in numerical weather prediction, especially improved models and data assimilation techniques, increased computing capacity, the availability of new observation types and efforts to recover and improve the quality of historical ones. The recent extension of forecast systems that allow integrated modeling of meteorological, oceanic, land surface, and chemical variables provide the basic elements for coupled data assimilation. This has opened the door to the development of a new generation of coupled reanalyses of the Earth system, or integrated Earth system analyses (IESA). Evidence so far suggests that this approach can improve the analysis of currently uncoupled components of the Earth system, especially at their interface, and lead to increased predictability. However, extensive analysis coupling as envisioned for IESA, while progressing, still presents significant challenges. These include model biases that can be exacerbated when coupled, component systems with different physical characteristics and different spatial and temporal scales, and component observations in different media with different spatial and temporal frequencies and different latencies. Quantification of uncertainty in reanalyses is also a critical challenge and is important for expanding their utility as a tool for climate change assessment. This talk provides a brief overview of the progress of reanalysis development during recent decades, and describes remaining challenges in the progression toward coupled Earth system reanalyses.

IES↗

NASA NTRS1998

Comparison of Surface Ground Temperature from Satellite Observations and the Off-Line Land Surface GEOS Assimilation System

The surface ground temperature (Tg) is an important meteorological variable, because it represents an integrated thermal state of the land surface determined by a complex surface energy budget. Furthermore, Tg affects both the surface sensible and latent heat fluxes. Through these fluxes. the surface budget is coupled with the atmosphere above. Accurate Tg data are useful for estimating the surface radiation budget and fluxes, as well as soil moisture. Tg is not included in conventional synoptical weather station reports. Currently, satellites provide Tg estimates globally. It is necessary to carefully consider appropriate methods of using these satellite data in a data assimilation system. Recently, an Off-line Land surface GEOS Assimilation (OLGA) system was implemented at the Data Assimilation Office at NASA-GSFC. One of the goals of OLGA is to assimilate satellite-derived Tg data. Prior to the Tg assimilation, a thorough investigation of satellite- and model-derived Tg, including error estimates, is required. In this study we examine the Tg from the n Project (ISCCP DI) data and the OLGA simulations. The ISCCP data used here are 3-hourly DI data (2.5x2.5 degree resolution) for 1992 summer months (June, July, and August) and winter months (January and February). The model Tg for the same periods were generated by OLGA. The forcing data for this OLGA 1992 simulation were generated from the GEOS-1 Data Assimilation System (DAS) at Data Assimilation Office NASA-GSFC. We examine the discrepancies between ISCCP and OLGA Tg with a focus on its spatial and temporal characteristics, particularly on the diurnal cycle. The error statistics in both data sets, including bias, will be estimated. The impact of surface properties, including vegetation cover and type, topography, etc, on the discrepancies will be addressed.

Yang, R.↗

NASA NTRS2004

Characteristics of Heavy Summer Rainfall in Southwestern Taiwan in Relation to Orographic Effects

On the windward side of southwestern Taiwan, about a quarter to a half of all rainfall during mid-July through August from 1994 to 2000 came from convective systems embedded in the southwesterly monsoon flow. k this study, the causes of two heavy rainfall events (daily rainfall exceeding 100 mm day over at least three rainfall stations) observed over the slopes and/or lowlands of southwestern Taiwan were examined. Data from European Center for Medium-Range Weather Forecasts /Tropical Ocean- Global Atmosphere (EC/TOGA) analyses, the rainfall stations of the Automatic Rainfall and Meteorological Telemetry System (ARMTS) and the conventional surface stations over Taiwan, and the simulation results from a regional-scale numerical model were used to accomplish the objectives. In one event (393 mm day on 9 August 1999), heavy rainfall was observed over the windward slopes of southern Taiwan in a potentially unstable environment with very humid air around 850 hPa. The extreme accumulation was simulated and attributed to orographic lifting effects. No preexisting convection drifted in from the Taiwan Strait into western Taiwan.

Chen, Ching-Sen↗

NASA NTRS2012

Correction to "Influence of Dust and Black Carbon on the Snow Albedo in the NASA Goddard Earth Observing System Version 5 Land Surface Model"

The website information describing the forcing meteorological data used for the land surface model (LSM) simulation, which were observed at an Automated Meteorological Station CAWS) at the Sapporo District Meteorological Observatory maintained by the Japan Meteorological Agency (JMA), was missing from the text. The 1-hourly data were obtained from the website of Kisyoutoukeijouhou (Information for available JMA-observed meteorological data in the past) on the website of JMA (in Japanese) (available at: http://www.jma.go.jpijmaimenulreport.html). The measurement height information of 59.5 m for the anemometer at the Sapporo Observatory was also obtained from the website of JMA (in Japanese) (available at: http://www.jma.go.jp/jma/menu/report.html). In addition, the converted 10-m wind speed, based on the AWS/JMA data, was further converted to a 2-m wind speed prior to its use with the land model as a usual treatment of off-line Catchment simulation. Please ignore the ice absorption data on the website mentioned in paragraph [15] which was not used for our calculations (but the data on the website was mostly the same as the estimated ice absorption coefficients by the following method because they partially used the same data by Warren [1984]). We calculated the ice absorption coefficients with the method mentioned in the same paragraph, for which some of the refractive index data by Warren [1984] were used and then interpolated between wavelengths, and also mentioned in paragraph [20] for the visible (VIS) and near-infrared (NIR) ranges. The optical data we used were interpolated between wavelengths as necessary.

Yasunari, Teppei J.↗