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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 NTRS2002

Assimilation Experiments of One-Dimensional Variational Analyses with GPS/MET Refractivity

The GPS/MET 1995 experiment demonstrated the feasibility of remote soundings of the Earth's atmosphere using the GPS radio occultation technique. Subsequent studies assessed the information content of such measurements. Several groups have attempted to assimilate the GPS radio occultation measurements into a global Data Assimilation System (DAS). These attempts followed in general the methodology proposed by Eyre, and range from die act four-dimensional variational assimilation of bending angles to assimilation of inverted profiles of temperature and/or humidity. We present here an hybrid approach. We attempted to take advantage of the accuracy of current, weather models to constrain one-dimensional variational analyses using GPS refractivity. Retrieved profiles of atmospheric parameters were then assimilated like other types of observations in a global DAS for issuing the next forecast period.

Poli, Paul↗
NASA NTRS2019

Advances in Space Radiation Physics and Transport

The space radiation environment is a complex mixture of particle types and energies originating from sources inside and outside of the galaxy. These environments may be modified by the heliospheric and geomagnetic conditions as well as planetary bodies and vehicle or habitat mass shielding. In low Earth orbit (LEO), the geomagnetic field deflects a portion of the galactic cosmic rays (GCR) and all but the most intense solar particle events (SPE). There are also dynamic belts of trapped electrons and protons with low to medium energy and intense particle count rates. In deep space, the GCR exposure is more severe than in LEO and varies inversely with solar activity. Unpredictable solar storms also present an acute risk to astronauts if adequate shielding is not provided. Near planetary surfaces such as the Earth, moon or Mars, secondary particles are produced when the ambient deep space radiation environment interacts with these surfaces and/or atmospheres. These secondary particles further complicate the local radiation environment and modify the associated health risks. Characterizing the radiation fields in this vast array of scenarios and environments is a challenging task and is currently accomplished with a combination of computational models and dosimetry. The computational tools include models for the ambient space radiation environment, mass shielding geometry, and atomic and nuclear interaction parameters. These models are then coupled to a radiation transport code to describe the radiation field at the location of interest within a vehicle or habitat. Many new advances in these models have been made in the last decade, and the present review article focuses on the progress and contributions made by workers and collaborators at NASA in the same time frame. Although great progress has been made, and models continue to improve, significant gaps remain and are discussed in the context of planned future missions. Of particular interest is the juxtaposition of various review committee findings regarding the accuracy and gaps of combined space radiation environment, physics, and transport models with the progress achieved over the past decade. While current models are now fully capable of characterizing radiation environments in the broad range of forecasted mission scenarios, it should be remembered that uncertainties still remain and need to be addressed.

Space radiation↗
NASA NTRS1986

Studies in geophysics: Active tectonics

Active tectonics is defined within the study as tectonic movements that are expected to occur within a future time span of concern to society. Such movements and their associated hazards include earthquakes, volcanic eruptions, and land subsidence and emergence. The entire range of geology, geophysics, and geodesy is, to some extent, pertinent to this topic. The needs for useful forecasts of tectonic activity, so that actions may be taken to mitigate hazards, call for special attention to ongoing tectonic activity. Further progress in understanding active tectonics depends on continued research. Particularly important is improvement in the accuracy of dating techniques for recent geologic materials.

Source record↗
NASA NTRS2016

Overview of the SMAP Applications and the SMAP Early Adopters Program - NASA's First Mission-Directed Outreach Effort

Satellite data provide global observations of many of the earths system processes and features. These data are valuable for developing scientific products that increase our understanding of how the earths systems are integrated. The water, energy and carbon cycle exchanges between the land and atmosphere are linked by soil moisture. NASAs Soil Moisture Active Passive (SMAP) mission provides soil moisture and freeze thaw measurements from space and allows scientists to link the water energy and carbon cycles. In order for SMAP data to be best integrated into decision support systems, the mission has engaged with the stakeholder community since 2009 and has attempted to scale the utility of the data to the thematic societal impacts of the satellite product applications. The SMAP Mission, which launched on January 31, 2015, has actively grown an Early Adopter (EA) community as part of its applications effort and worked with these EAs to demonstrate a scaled thematic impact of SMAP data product in societally relevant decision support applications. The SMAP mission provides global observations of the Earths surface soil moisture, providing high accuracy, resolution and continuous global coverage. Through the Early Adopters Program, the SMAP Applications Team will spend the next 2 years after launch documenting and evaluating the use of SMAP science products in applications related to weather forecasting, drought, agriculture productivity, floods, human health and national security.

SMAP↗
NASA NTRS2010

Objective Lightning Probability Forecasting for Kennedy Space Center and Cape Canaveral Air Force Station, Phase III

The AMU created new logistic regression equations in an effort to increase the skill of the Objective Lightning Forecast Tool developed in Phase II (Lambert 2007). One equation was created for each of five sub-seasons based on the daily lightning climatology instead of by month as was done in Phase II. The assumption was that these equations would capture the physical attributes that contribute to thunderstorm formation more so than monthly equations. However, the SS values in Section 5.3.2 showed that the Phase III equations had worse skill than the Phase II equations and, therefore, will not be transitioned into operations. The current Objective Lightning Forecast Tool developed in Phase II will continue to be used operationally in MIDDS. Three warm seasons were added to the Phase II dataset to increase the POR from 17 to 20 years (1989-2008), and data for October were included since the daily climatology showed lightning occurrence extending into that month. None of the three methods tested to determine the start of the subseason in each individual year were able to discern the start dates with consistent accuracy. Therefore, the start dates were determined by the daily climatology shown in Figure 10 and were the same in every year. The procedures used to create the predictors and develop the equations were identical to those in Phase II. The equations were made up of one to three predictors. TI and the flow regime probabilities were the top predictors followed by 1-day persistence, then VT and Ll. Each equation outperformed four other forecast methods by 7-57% using the verification dataset, but the new equations were outperformed by the Phase II equations in every sub-season. The reason for the degradation may be due to the fact that the same sub-season start dates were used in every year. It is likely there was overlap of sub-season days at the beginning and end of each defined sub-season in each individual year, which could very well affect equation performance.

Crawford, Winifred C.↗
NASA NTRS1999

Application of Lidar Winds to Data Assimilation

One of the major applications of space-based doppler wind lidar is to improve atmospheric analyses and numerical weather prediction (NWP). Since the mid 198,0's, Observing System Simulation Experiments (OSSE's) have been conducted in order to evaluate the potential impact of lidar winds on NWP. These experiments have shown tremendous potential for satellite lidar observations to improve atmospheric analyses and forecasts. In addition, the OSSE's are providing an evaluation of trade-offs in lidar design, and are currently being used to define the specific requirements for lidar winds in terms of horizontal and vertical coverage and accuracy. At the meeting the methodology for these experiments and the main results relating to proposed lidars will be presented.

Atlas, Robert↗
NASA NTRS2000

Accuracy of Modelled Stratospheric Temperatures in the Winter Arctic Vortex from Infra Red Montgolfier Long Duration Balloon Measurements

The temperature of the stratosphere has been measured in the Arctic vortex every 9-10 minutes along the trajectory of four Infra Red Montgolfier long duration balloons flown for 7 to 22 days during the winters of 1997 and 1999. From a number of comparisons to independent sensors, the accuracy of the measurements is demonstrated to be plus or minus 0.5 K during nighttime and at altitude below 28 km (10 hPa). The performances of the analyses of global meteorological models, European Center for Medium Range Weather Forecasts (ECMWF) 31 and 50 levels, United Kingdom Meteorological Office (UKMO), Data Assimilation Office (DAO), National Climatic Prediction Center (NCEP) and NCEP/NCAR reanalysis, used in photochemical simulations of ozone destruction and interpretation of satellite data, are evaluated by comparison to this large (3500 data points) and homogeneous experimental data set. Most of models, except ECMWF31 in 1999, do show a smal1 average warm bias of between 0 and 1.6 K, with deviations particularly large, up to 20 K at high altitude (5hPa) in stratospheric warming conditions in 1999. Particularly wrong was ECMWF 31 levels near its top level at 10 hPa in 1999 where temperature 25 K colder than the real atmosphere were reported. The average dispersion between models and measurements varies from plus or minus 1.0 to plus or minus 3.0 K depending on the model and the year. It is shown to be the result of three contributions. The largest is a long wave modulation likely caused by the displacement of the temperature field in the analyses compared to real atmosphere. The second is the overestimation of the vertical gradient of temperature particularly in warming conditions, which explains the increase of dispersion from 1997 to 1999. Unexpectedly, the third and smallest (plus or minus 0.6-0.7 K) is the contribution of meso and subgrid scale vertical and horizontal features associated to the vertical propagation of orographic or gravity waves. Compared to other models, the newly available ECMWF 50 levels version assimilating the high vertical resolution radiances of the space borne Advanced Microwave Sounding Unit, performs significantly better (0.03 plus or minus 1.12 K on average between 10 and 140 hPa in 1999) than other models.

Pommereau, J.-P.↗
NASA NTRS2004

Why Is Rainfall Error Analysis Requisite for Data Assimilation and Climate Modeling?

Given the large temporal and spatial variability of precipitation processes, errors in rainfall observations are difficult to quantify yet crucial to making effective use of rainfall data for improving atmospheric analysis, weather forecasting, and climate modeling. We highlight the need for developing a quantitative understanding of systematic and random errors in precipitation observations by examining explicit examples of how each type of errors can affect forecasts and analyses in global data assimilation. We characterize the error information needed from the precipitation measurement community and how it may be used to improve data usage within the general framework of analysis techniques, as well as accuracy requirements from the perspective of climate modeling and global data assimilation.

Hou, Arthur Y.↗
NASA NTRS2016

Recent Checks on the Radiometric and Spatial Calibration of AIRS In-Orbit

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002 and is currently fully operational. AIRS acquires hyperspectral infrared radiances in 2378 channels ranging in wavelength from 3.7-15.4 um with spectral resolution of better than 1200, and spatial resolution of 13.5 km with global daily coverage. The AIRS was designed to measure temperature and water vapor profiles for improvement in weather forecast and improved parameterization of climate processes. Currently the AIRS Level 1B Radiance Products are assimilated by NWP centers worldwide and have shown considerable forecast improvement. Although the calibration of AIRS (< 200 mK 3 sigma) is sufficient for data assimilation into Numerical Weather Prediction (NWP) models, long term trends of Earth’s climate require radiances with stability approaching 10 mK/year, and absolute accuracies better than 100 mK. This investigation uses views of space during roll maneuvers of the Aqua spacecraft to calibrate the mirror emission (one of the largest error sources for AIRS) and reduce the residual errors in cold scenes. We also present results of a secondary study that uses MODIS data to determine the alignment of the AIRS boresight. In this study we match AIRS and MODIS data and iterate on the assumed boresight to find the minimum difference in signal. In this way we are able to confirm the boresight projections determined shortly after launch.

Pagano, Thomas S.↗
NASA NTRS1993

A direct evaluation of the Geosat altimeter wet atmospheric range delay using very long baseline interferometry observations

The overall accuracy of the U.S. Navy Geosat altimeter wet atmospheric range delay caused by refraction through the atmosphere is directly assessed by comparing the estimates made from the DMSP Special Sensor Microwave/Imager and the U.S. Navy Fleet Numerical Ocean Center forecast model for Geosat with measurements of total zenith columnar water vapor content from four VLBI sites. The assessment is made by comparing time series of range delay from various methods at each location. To determine the importance of diurnal variation in water vapor content in noncoincident estimates, the VLBI measurements were made at 15-min intervals over a few days. The VLBI measurements showed strong diurnal variations in columnar water vapor at several sites, causing errors of the order 3 cm rms in any noncoincident measurement of the wet troposphere range delay. These errors have an effect on studies of annual and interannual changes in sea level with Geosat data.

Koblinsky, C. J.↗
NASA NTRS2000

An Assessment of Our Ability to Model the Upper Troposphere and Lower Stratosphere in Interactive Climate Models

The physics of the upper troposphere is dominated by the different phases of water, while the lower stratosphere is governed by the presence of ozone. The tropopause may be regarded as the layer which separates the regions where stratospheric and tropospheric processes dominate the physics, but it is clearly not a smooth transition level. Modelling this region in comprehensive climate models is complicated, partly because of the constraints inherent in numerical methods (such as the finite resolution used in models) and partly because of our incomplete knowledge of the physical and chemical interactions which occur (such as the phase transitions of water and the composition of aerosols). However, studies of stratospheric impacts on climate change clearly require the tropopause region to be modelled with a high degree of accuracy. This paper will examine how well we can currently model the structure and dynamics of the tropopause region; this includes some comparisons of the simulated atmospheric composition with observational estimates of these species, some studies of discrepancies between forecasts and observations in the Data Assimilation System of the Data Assimilation office, and inferences for sparsely observed quantities. The analysis will focus on meteorological quantities, physical forcing mechanisms, and the transport and interactions of trace species.

Pawson, Steven↗
NASA NTRS2003

The Aura Mission and Its Application to Climate and Air Quality

NASA's Aura satellite is scheduled to launch in the second quarter of 2004 into a polar orbit. The Aura mission is designed to collect data to address three high priority environmental science questions: (1) Is the ozone layer recovering as expected? (2) What are the sources and processes that control tropospheric pollutants? And (3) what is the quantitative impact of constituents on climate change? Aura will answer these questions by globally measuring a comprehensive set of trace gases and aerosols in the troposphere and stratosphere. Aura data will also have applications for monitoring and predicting climate and air quality parameters. Aura s observations will continue the TOMS ozone trend record and provide an assessment as to whether the Montreal Protocol is achieving its objective. Aura will measure gases and aerosols in the upper troposphere and lower stratosphere that contribute to climate forcing. These data will be of sufficient coverage, vertical resolution, and accuracy to help constrain climate models. In addition, Aura observations of tropospheric ozone and its precursors will have regional as well as intercontinental coverage, which could improve emission inventories. Near real time data will tested for local air quality forecasts in collaboration with the US's Environmental Protection UV-B forecasts from Aura ozone and cloud cover data. An overview of Aura s instruments, data products, validation, and examples of data applications will be presented.

Hilsenrath, Ernest↗
NASA NTRS2013

Requirements for a Moderate-Resolution Infrared Imaging Sounder (MIRIS)

The high cost of imaging and sounding from space warrants exploration of new methods for obtaining the required information, including changing the spectral band sets, employing new technologies and merging instruments. In some cases we must consider relaxation of the current capability. In others, we expect higher performance. In general our goal is to meet the VIIRS and CrIS requirements while providing the enhanced next generation capabilities: 1) Hyperspectral Imaging in the Vis/NIR bands, 2) High Spatial Resolution Sounding in the Infrared bands. The former will improve the accuracy of ocean color products, aerosols and water vapor, surface vegetation and geology. The latter will enable the high-impact achieved by the current suite of hyperspectral infrared sounders to be achieved by the next generation high resolution forecast models. We examine the spectral, spatial and radiometric requirements for a next generation system and technologies that can be applied from the available inventory within government and industry. A two-band grating spectrometer instrument called the Moderate-resolution Infrared Imaging Sounder (MIRIS) is conceived that, when used with the planned NASA PACE Ocean Color Instrument (OCI) will meet the vast majority of CrIS and VIIRS requirements in the all bands and provide the next generation capabilities desired. MIRIS resource requirements are modest and the Technology Readiness Level is high leading to the expectation that the cost and risk of MIRIS will be reasonable.

Atmospheric Infrared Sounder (AIRS)↗
NASA NTRS1988

A forecast of new test capabilities using Magnetic Suspension and Balance Systems

This paper outlines the potential of Magnetic Suspension and Balance System (MSBS) technology to solve existing problems related to support interference in wind tunnels. Improvement of existing test techniques and exciting new techniques are envisioned as a result of applying MSBS. These include improved data accuracy, dynamic stability testing, two-body/stores release testing, and pilot/designer-in-the-loop tests. It also discusses the use of MSBS for testing exotic configurations such as hybrid hypersonic vehicles. A new facility concept that combines features of ballistic tubes, magnetic suspension, and cryogenic tunnels is described.

Lawing, Pierce L.↗
NASA NTRS2004

Regional Assimilation of NASA Atmospheric Infrared Sounder (AIRS) Data

The NASA Short-term Prediction Research and Transition (SPORT) Center seeks to accelerate the infusion of NASA Earth Science Enterprise (ESE) observations, data assimilation and modeling research into NW S forecast operations and decision-making. The Atmospheric Infrared Sounder (AIRS), is expected to advance climate research and weather prediction into the 21 st century. It is one of six instruments onboard Aqua, a satellite that is part of NASA s Earth Observing System. AIRS, along with two partner microwave sounding instruments, represents the most advanced atmospheric sounding system ever deployed in space. The system is capable of measuring the atmospheric temperature in the troposphere with radiosonde accuracies of 1 K over 1 km-thick layers under both clear and cloudy conditions, while the accuracy of the derived moisture profiles will exceed that obtained by radiosondes. It is imperative that the scientific community is prepared to take full advantage of next-generation satellite data that will become available within the next decade. The purpose of this paper is to describe a procedure designed to optimally assimilate AIRS data at high spatial resolution over both land and ocean. The assimilation system used in this study is the Local Analysis and Prediction System (LAPS) developed at the Forecast System Laboratory used extensively around the globe. Results will focus on quality control issues associated with AIRS, optimal assimilation strategies, and the impact of the AIRS data on subsequent numerical forecasts at 12 km produced by the next generation Weather Research and Forecast (WRF) model.

Chou, Shih-Hung↗
NASA NTRS1982

User's appraisal of yield model evaluation criteria

The five major potential USDA users of AgRISTAR crop yield forecast models rated the Yield Model Development (YMD) project Test and Evaluation Criteria by the importance placed on them. These users were agreed that the "TIMELINES" and "RELIABILITY" of the forecast yields would be of major importance in determining if a proposed yield model was worthy of adoption. Although there was considerable difference of opinion as to the relative importance of the other criteria, "COST", "OBJECTIVITY", "ADEQUACY", AND "MEASURES OF ACCURACY" generally were felt to be more important that "SIMPLICITY" and "CONSISTENCY WITH SCIENTIFIC KNOWLEDGE". However, some of the comments which accompanied the ratings did indicate that several of the definitions and descriptions of the criteria were confusing.

Warren, F. B.↗
NASA NTRSDate not supplied

Medium-Range River Flood Forecasts Using a Long Short-Term Memory Network

River flooding and the impacts are a concern for decision makers throughout the United States. Accurate medium-range forecasts (~3-7 days) are critical for providing advanced outlooks to emergency management officials. Unfortunately, accurately forecasting rainfall-runoff and the subsequent rise and fall within rivers remain a challenge in hydrological modeling. While complex physical modeling systems are the standard for representing the hydrological processes, they are computationally demanding and can require extensive calibration. Further, uncertainties remain in the model parameters and input data. The use of machine learning can reduce some of the computational demand while maintaining high accuracy. Therefore, this project makes use of a Long Short-Term Memory (LSTM) network which explicitly accounts for the time-dependent nature of rainfall-runoff modeling. The developed LSTM was trained to predict river gauge height, or stage height, based on time-lagged input features which include: gauge height to initialize the model, the NASA Short-term Prediction Research and Transition Center’s instance of the Land Information System (SPoRT-LIS) relative soil moisture to describe the rainfall infiltration rate, and 6-hr Multi-Radar Multi-Sensor quantitative precipitation estimate (MRMS QPE). The developed LSTM based system is then used to produce 7-day forecasts with a 6-hr temporal resolution using three different quantitative precipitation forecasts (QPF) from the NWS’s Weather Prediction Center (WPC), the NCEP Global Forecast System (GFS) model and the National Blend of Models (NBM). This trained modeling system has been implemented as an experimental product at over 100 different rivers in collaboration with at multiple National Weather Service (NWS) Forecast Offices and River Forecast Centers (RFC) across the eastern half of the United States. The developed LSTM model achieved average Nash-Sutcliffe efficiency (NSE) 0.89 higher than the equivalent medium-range National Water Model ensemble member forecast over a 7-day forecast. In addition to the initial development and evaluation, this project has continued to expand. While the initial model was developed for precipitation dominated basins, expansion of the project has taken it to basins effected by snow melt. This presentation will provide an overview of the project with focus on recent developments on incorporating snow melt processes into the model.

Andrew T. White↗
NASA NTRS1983

The influence of the tropics on the prediction of ultralong waves. I - Tropical wind field

The effects of tropical wind data from the FGGE and tropical latent heating on numerical modeling of ultralong waves are considered in a two-part study. The model studied is the global fourth-order GLAS general circulation model, an energy-conserving format with horizontal differences calculated with fourth-order accuracy. Data assimilation experiments were performed with and without the wind data, with account taken of eastward and northward wind components, the geopotential height, and the relative humidity, all over pressure surfaces. The initial conditions were used to generate six pairs of forecasts, and the tropical wind error decreased after two days of prediction when the initial conditions contained the wind data. The deviations from the measured planetary wave data were attributed to differences in the initial rotational wind field, which varied on a three-day basis. The latent heat initial data had a five-day period and extended its influence beyond the tropical zone. The tropical heat sources sustained the tropical westerlies in the GLAS model, and removal of the tropical heat sources reversed the wind to easterlies.

Baker, W. E.↗