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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 NTRS2006

Mission Operations Insights

The mission description Polar Operational Environmental Satellites (POES): I) Collect and disseminate worldwide meteorological and environmental data: a) Provide day and night information (AVHRR): 1) cloud cover distribution and type; 2) cloud top temperature; 3) Moisture patterns and ice/snow melt. b) Provide vertical temperature and moisture profiles of atmospheres (HIRS, AMSU, MHS. c) Measure global ozone distribution and solar UV radiation (SBUV). d) Measure proton, electro, and charged particle density to provide solar storm warnings (SEM). d) Collect environmental data (DCS): 1) Stationary platforms in remote locations; 2) Free floating platforms on buoys, balloons, migratory animals. II) Provide Search and Rescue capabilities (SARR, SARP): a) Detection and relay of distress signals. b) Has saved thousands of lives around the world.

Littman, Dave↗
NASA NTRS1998

Ice-shelf Dynamics Near the Front of Filchner-Ronne Ice Shelf, Antarctica, Revealed by SAR Interferometry: Model/Interferogram Comparison

We compare Earth Remote Sensing (ERS) satellite synthetic-aperture radar (SAR) interferograms with artificial interferograms constructed using output of a finite-element ice-shelf flow model to study the dynamics of Filchner-Ronne Ice Shelf (FRIS) near Hemmen Ice Rise (HIR) where the iceberg-calving front itersects Berkener Island (BI).

Ice-shelf Filchner-Ronne Antarctica SAR Interferom↗
NASA NTRS2006

A Quick Method for Estimating Vehicle Characteristics Appropriate for Continuous Thrust Round Trip Missions Within the Solar System

A simple method of estimating vehicle parameters appropriate for interplanetary travel can provide a useful tool for evaluating the suitability of particular propulsion systems to various space missions. Although detailed mission analyses for interplanetary travel can be quite complex, it is possible to derive hirly simple correlations which will provide reasonable trip time estimates to the planets. In the present work, it is assumed that a constant thrust propulsion system propels a spacecraft on a round trip mission having equidistant outbound and inbound legs in which the spacecraft accelerates during the first portion of each leg of the journey and decelerates during the last portion of each leg of the journey. Comparisons are made with numerical calculations from low thrust trajectory codes to estimate the range of applicability of the simplified correlations.

Emrich, Bill↗
NASA NTRS2006

Introduction to MODIS Cloud Products

The Earth's radiative energy balance and hydrological cycle are fundamentally coupled with the distribution and properties of clouds. Therefore, the ability to remotely infer cloud properties and their variation in space and time is crucial for establishing climatologies as a reference for validation of present-day climate models and in assessing future climate change. Remote cloud observations also provide data sets useful for testing and improving cloud model physics, and for assimilation into numerical weather prediction models. The MODerate Resolution Imaging Spectroradiometer (MODIS) imagers on the Terra and Aqua Earth Observing System (EOS) platforms provide the capability for globally retrieving these properties using passive solar reflectance and infrared techniques. In addition to providing measurements similar to those offered on a suite of historical operational weather platforms such as the Advanced Very High Resolution Radiometer (AVHRR), the High-resolution Infrared Radiation Sounder (HIRS), and the Geostationary Operational Environmental Satellite (GOES), MODIS provides additional spectral and/or spatial resolution in key atmospheric bands, along with on-board calibration, to expand the capability for global cloud property retrievals. The core MODIS operational cloud products include cloud top pressure, thermodynamic phase, optical thickness, particle size, and water path, and are derived globally at spatial resolutions of either 1- or 5-km (referred to as Level-2 or pixel-level products). In addition, the MODIS atmosphere team (collectively providing cloud, aerosol, and clear sky products) produces a combined gridded product (referred to as Level-3) aggregated to a 1 equal-angle grid, available for daily, eight-day, and monthly time periods. The wealth of information available from these products provides critical information for climate studies as well as the continuation and improved understanding of existing satellite-based cloud climatologies derived from heritage instruments. This chapter provides an overview of the MODIS Level-2 and -3 operational cloud products.

Baum, Bryan A.↗
NASA NTRS2005

Re-Examination of the Observed Decadal Variability of Earth Radiation Budget Using Altitude-Corrected ERBE/ERBS Nonscanner WFOV Data

This paper gives an update on the observed decadal variability of Earth Radiation Budget using the latest altitude-corrected Earth Radiation Budget Experiment (ERBE)/Earth Radiation Budget Satellite (ERBS) Nonscanner Wide Field of View (WFOV) instrument Edition3 dataset. The effects of the altitude correction are to modify the original reported decadal changes in tropical mean (20N to 20S) longwave (LW), shortwave (SW), and net radiation between the 1980s and the 1990s from 3.1/-2.4/-0.7 to 1.6/-3.0/1.4 Wm(sup -2) respectively. In addition, a small SW instrument drift over the 15-year period was discovered during the validation of the WFOV Edition3 dataset. A correction was developed and applied to the Edition3 dataset at the data user level to produce the WFOV Edition3_Rev1 dataset. With this final correction, the ERBS Nonscanner observed decadal changes in tropical mean LW, SW, and net radiation between the 1980s and the 1990s now stand at 0.7/-2.1/1.4 Wm(sup -2), respectively, which are similar to the observed decadal changes in the HIRS Pathfinder OLR and the ISCCP FD record; but disagree with the AVHRR Pathfinder ERB record. Furthermore, the observed interannual variability of near-global ERBS WFOV Edition3_Rev1 net radiation is found to be remarkably consistent with the latest ocean heat storage record for the overlapping time period of 1993 to 1999. Both data sets show variations of roughly 1.5 Wm(sup -2) in planetary net heat balance during the 1990s.

Wong, Takmeng↗
NASA NTRS2007

Summary of Terra and Aqua MODIS On-orbit Calibration and Characterization Results

The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's EOS Terra spacecraft has been in operation for more than seven years since its launch in December 1999 and the MODIS onboard Aqua spacecraft has been in operation for more than 4.5 years since its launch in May 2002. Compared to its heritage sensors, such as AVHRR, CZCS, SeaWiFS, HIRS, and Landsat TM, the MODIS instrument was developed with improved spectral and spatial resolutions, and temporal scale or global coverage frequency. The two MODIS instruments are nearly identical with each collecting data in 36 spectral bands: 20 reflective solar bands (RSB) with center wavelengths from 0.41 to 2.2jm and 16 thermal emissive bands (TEB) from 3.7 to 4.4 microns. MODIS makes the Earth view observations with a scan angle range of +/-55 degree relative to instrument nadir and at three nadir spatial resolutions: 0.25km for bands 1-2.05km for bands 3-7, and 1km for bands 8-36, thus enabling complete global coverage of the Earth in less than 2 days. Both Terra and Aqua MODIS observations have been routinely used to generate a broad range of science data products that are widely distributed and extensively applied for the studies of the Earth's land, oceans, and atmosphere and for the monitoring of climate and environmental changes. It is obvious that the MODIS science data product quality strongly relies on sensor on-orbit performance and its capability of continuously tracking sensor response changes over time. Because of this, each MODIS was built with a comprehensive set of on-board calibrators (OBC) that include a solar diffuser (SD) for the RSB calibration, a blackbody (BB) for the TEB calibration, and a spectro-radiometric calibration assembly (SRCA) for the spatial (RSB and TEB) and spectral (RSB only) characterization. Most importantly, extensive and dedicated sensor calibration and characterization efforts have been constantly made by the MODIS Characterization Support Team (MCST) at NASA/GSFC. In this presentation, we will provide an overview of MODIS sensor operations since 1aunh and the onorbit calibration and characterization methodologies with emphasis on the differences between Terra and Aqua MODIS characteristics. We will summarize both Terra and Aqua MODIS onorbit calibration and characterization results, including their RSB and TEB detector noise characterization, the sensor response changes, and the corrections to the optics degradation. In addition to radiometric calibration performance, we will illustrate both sensors' spectral and spatial characterization results in terms of their band-to-band registrations and spectral band center wavelength shifts.

Xiong, X.↗
NASA NTRS2008

Evaluation and Assimilation of Cloud Cleared Radiances for AIRS in GEOS-5

The use of clear (cloud-free) channels for AIRS in GEOS-5 had shown positive impact on forecast skills in both hemispheres. However, improvements in forecast skills due to the assimilation of AIRS data are less impressive since the number of assimilated channels from AIRS is much larger than that from other Infrared sounders such as HIRS-3 onboard NOAA 15-17 satellites. This limitation of AIRS radiance data to improve the forecast skill is mainly due to the fact that channels capable of peaking below clouds are not used in the assimilation and yet those have highest vertical resolving capability of AIRS instrument are concentrated in the lower troposphere. On average, the percentage of AIRS footprints completely clear for all channels is less than 10%. The percentage of assimilated AIRS channel radiances however ranges from 100% for channels peaking in the upper stratosphere, above the cloud, to no more that 5% in the lower atmosphere due to cloud contamination. Our current ability to model and predict clouds accurately in global model, and to fully characterize and parameterize optical properties of cloud particles in radiative transfer model are the two major obstacles prohibiting us to use cloudy radiance directly in the assimilation. To further improve forecast skill using AIRS data, we ought to use the channels peaking below the clouds in the troposphere, which can be accomplished by assimilating cloud-cleared radiance. The cloud-cleared radiance data for AIRS used in this study were obtained from optimal cloud clearing procedures developed by researchers at CIMSS of University of Wisconsin at Madison to retrieve clear column radiances for all AIRS channels by collocating multi-band MODIS IR clear radiance observations with the AIRS cloudy radiances on a single footprint basis. Two adjacent AIRS cloudy footprints are used to retrieve one AIRS cloud-cleared radiance spectrum and no background information (first guess) is needed. To assimilate the cloud-cleared radiance data, the errors of the cloud-cleared radiances need to be addressed. The details of convolving AIRS radiances with MODIS spectral response function and comparison with MODIS-measured cloud-free radiance will be presented. The range of errors of cloud-cleared radiances for AIRS using collocated MODIS clear and near-by AIRS clear data will be shown. The NASA. global data assimilation model, GEOS-5, is used to evaluate and assimilate the cloud-cleared radiance for AIRS. The residues between the cloud-cleared brightness temperature and the simulated brightness temperature from background (i.e., OMFs) will be investigated. The quality control procedures will be documented based on error estimation and the OMFs. Finally, the impacts between assimilation of clear channel radiances and cloud-cleared radiances will be addressed.

Liu, Hui-chun↗
NASA NTRS2014

Status of the NASA GMAO Observing System Simulation Experiment

An Observing System Simulation Experiment (OSSE) is a pure modeling study used when actual observations are too expensive or difficult to obtain. OSSEs are valuable tools for determining the potential impact of new observing systems on numerical weather forecasts and for evaluation of data assimilation systems (DAS). An OSSE has been developed at the NASA Global Modeling and Assimilation Office (GMAO, Errico et al 2013). The GMAO OSSE uses a 13-month integration of the European Centre for Medium- Range Weather Forecasts 2005 operational model at T511/L91 resolution for the Nature Run (NR). Synthetic observations have been updated so that they are based on real observations during the summer of 2013. The emulated observation types include AMSU-A, MHS, IASI, AIRS, and HIRS4 radiance data, GPS-RO, and conventional types including aircraft, rawinsonde, profiler, surface, and satellite winds. The synthetic satellite wind observations are colocated with the NR cloud fields, and the rawinsondes are advected during ascent using the NR wind fields. Data counts for the synthetic observations are matched as closely as possible to real data counts, as shown in Figure 2. Errors are added to the synthetic observations to emulate representativeness and instrument errors. The synthetic errors are calibrated so that the statistics of observation innovation and analysis increments in the OSSE are similar to the same statistics for assimilation of real observations, in an iterative method described by Errico et al (2013). The standard deviations of observation minus forecast (xo-H(xb)) are compared for the OSSE and real data in Figure 3. The synthetic errors include both random, uncorrelated errors, and an additional correlated error component for some observational types. Vertically correlated errors are included for conventional sounding data and GPS-RO, and channel correlated errors are introduced to AIRS and IASI (Figure 4). HIRS, AMSU-A, and MHS have a component of horizontally correlated error. The forecast model used by the GMAO OSSE is the Goddard Earth Observing System Model, Version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) DAS. The model version has been updated to v. 5.13.3, corresponding to the current operational model. Forecasts are run on a cube-sphere grid with 180 points along each edge of the cube (approximately 0.5 degree horizontal resolution) with 72 vertical levels. The DAS is cycled at 6-hour intervals, with 240 hour forecasts launched daily at 0000 UTC. Evaluation of the forecasting skill for July and August is currently underway. Prior versions of the GMAO OSSE have been found to have greater forecasting skill than real world forecasts. It is anticipated that similar forecast skill will be found in the updated OSSE.

OSSE↗
NASA NTRS2013

Inter-Calibration and Concatenation of Climate Quality Infrared Cloudy Radiances from Multiple Instruments

A change in climate is not likely captured from any single instrument, since no single instrument can span decades of time. Therefore, to detect signals of global climate change, observations from many instruments on different platforms have to be concatenated. This requires careful and detailed consideration of instrumental differences such as footprint size, diurnal cycle of observations, and relative biases in the spectral brightness temperatures. Furthermore, a common basic assumption is that the data quality is independent of the observed scene and therefore can be determined using clear scene data. However, as will be demonstrated, this is not necessarily a valid assumption as the globe is mostly cloudy. In this study we highlight challenges in inter-calibration and concatenation of infrared radiances from multiple instruments by focusing on the analysis of deep convective or anvil clouds. TRMM/VIRS is potentially useful instrument to make correction for observational differences in the local time and foot print sizes, and thus could be applied retroactively to vintage instruments such as AIRS, IASI, IRIS, AVHRR, and HIRS. As the first step, in this study, we investigate and discuss to what extent AIRS and VIRS agree in capturing deep cloudy radiances at the same local time. The analysis also includes comparisons with one year observations from CrIS. It was found that the instruments show calibration differences of about 1K under deep cloudy scenes that can vary as a function of land type and local time of observation. The sensitivity of footprint size, view angle, and spectral band-pass differences cannot fully explain the observed differences. The observed discrepancies can be considered as a measure of the magnitude of issues which will arise in the comparison of legacy data with current data.

cloudy radiance↗
NASA NTRS2016

NASA/GEWEX Surface Radiation Budget: Integrated Data Product With Reprocessed Radiance, Cloud, and Meteorology Inputs, and New Surface Albedo Treatment

The NASA/GEWEX Surface Radiation Budget (SRB) project produces shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-near present time period. Spatial resolution is 1 degree. The current release 3.0 (available at gewex-srb.larc.nasa.gov) uses the International Satellite Cloud Climatology Project (ISCCP) DX product for pixel level radiance and cloud information. This product is subsampled to 30 km. ISCCP is currently recalibrating and recomputing their entire data series, to be released as the H product, at 10km resolution. The ninefold increase in pixel number will allow SRB a higher resolution gridded product (e.g. 0.5 degree), as well as the production of pixel-level fluxes. In addition to the input data improvements, several important algorithm improvements have been made. Most notable has been the adaptation of Angular Distribution Models (ADMs) from CERES to improve the initial calculation of shortwave TOA fluxes, from which the surface flux calculations follow. Other key input improvements include a detailed aerosol history using the Max Planck Institut Aerosol Climatology (MAC), temperature and moisture profiles from HIRS, and new topography, surface type, and snow/ice. Here we present results for the improved GEWEX Shortwave and Longwave algorithm (GSW and GLW) with new ISCCP data, the various other improved input data sets and the incorporation of many additional internal SRB model improvements. As of the time of abstract submission, results from 2007 have been produced with ISCCP H availability the limiting factor. More SRB data will be produced as ISCCP reprocessing continues. The SRB data produced will be released as part of the Release 4.0 Integrated Product, recognizing the interdependence of the radiative fluxes with other GEWEX products providing estimates of the Earth's global water and energy cycle (I.e., ISCCP, SeaFlux, LandFlux, NVAP, etc.).

Cox, Stephen J.↗
NASA NTRS2018

Orbital Variations and Impacts on Observations from SNPP, NOAA 18-20, and AQUA Sun-Synchronous Satellites

The AQUA, SNPP, and NOAA 18-20 PM sun-synchronous satellites were designed with similar local time, local solarzenith angles, and overlapping temporal coverage. Although the satellites are expected to have fixed local equator-crossing time, during the satellite lifetime, the equator-crossing times of these satellites drift. For NOAA 18-19, the driftin equator-crossing time is significant (few hours) and no correction has been done over the lifetime. For SNPP andAQUA, correction in the orbital inclination angle was periodically performed to maintain the equator-crossing timearound the designed value. The impact of systematic drift of the local observation time during the satellite life cycle canbe significant and should be accounted for when using multi-year time series of satellite products in long-termenvironmental studies. In this paper, the equator-crossing time drift of AQUA, SNPP, and NOAA 18-20, the correctionof SNPP and AQUA equator-crossing time via orbital inclination angle change, and the consequent local solar zenithangle variation are evaluated. The impact of such drift on low-latitude mean brightness temperature trend derived fromthe similar ~11 μm thermal emissive channel of AQUA MODIS CH31, SNPP Visible Infrared Imaging RadiometerSuite (VIIRS) CH15 and NOAA 18-19 HIRS CH08 are analyzed. The drift in the mean brightness temperature measuredby these sensors is combined as a function of local time and analyzed using diurnal cycle analysis. The mean brightnesstemperature drift for SNPP VIIRS is reconciled within the context of much larger temperature drift of NOAA 18-19.

Shao, Xi↗
NASA NTRSDate not supplied

TPSAS-NF1676L-31179-DND

This presentation will brief the GEWEX Radiation Panel on the progress and results of the GEWEX SRB project during the last year toward production and assessment of the Release 4.0 data set. First, an update is presented regarding SRB Release 4.0 "Integrated Product" that produces consistent with GEWEX projects estimating land and ocean latent and sensible heat fluxes. Changes from the Release 3/3.1 data products to Release 4 are reviewed both for key inputs (such as the ISCCP HXS, the nn-HIRS, Land and Sea surface temperatures) and key algorithm changes. Differences between the old and new input properties are assessed and flux sensitivities to those inputs are summarized. Sample radiative flux data products are presented and compared against the previous version for span of the production run, currently from 1998 through 2012. These fluxes are also compared to surface measurements (i.e., BSRN) and CERES (Clouds and Earth's Radiant Energy System) data products both in terms of bulk statistics and also time series variability. Lastly, the plans for continued processing, archival, assessment and research and will be presented to the panel for discussion and feedback.

Paul W Stackhouse, Jr↗