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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 NTRS2000

Uncertainties in Remote Sensing of Aerosol Radiative Forcing

The role of aerosol forcing remains one of the largest uncertainties in estimating man's impact on the global climate system. One school of thought suggests that remote sensing by satellite sensors will provide the data necessary to narrow these uncertainties. Much effort has gone into the development of new satellite sensors specifically designed to retrieve aerosol loading and some information about the sizes of the aerosols. These next generation remote sensing instruments (EOS-MODIS, EOS-MISR, POLDER, ATSR) will provide unprecedented accuracy in the retrieval of aerosol loading. Although the new generation of sensors has excellent accuracy compared to the heritage instruments of the past, they still have measurement limitations. In clean, pristine regions the absolute magnitude of the uncertainty in the aerosol retrieval becomes comparable in magnitude to the signal itself. If much of the aerosol forcing is occurring at very low magnitudes of aerosol concentrations, satellite remote sensing will miss it. This study attempts to quantify remote sensing limitations due to the accuracy limits of the retrieval algorithms. We use a combination of numerical aerosol transport models, ground-based AERONET data and ISCCP cloud climatology to determine how much of the forcing occurs in regions too clean to determine from satellite retrievals. This study is not an intercomparison of global transport models. It is not an estimation of global aerosol forcing. This study is an exercise to determine whether satellite remote sensing can live up to our high expectations.

Remer, L.↗
NASA NTRS1993

Estimation of solar backscatter ultraviolet albedo using ground-based Umkehr measurements

A retrieval method was developed to estimate the solar backscatter ultraviolet (SBUV) satellite albedo for the ozone profiler wavelengths using ground-based ultraviolet measurements. For the present investigation the Umkehr was used as the ground-based ultraviolet measurement. Simulated SBUV data and Umkehr data theoretically computed from a priori ozone profiles observed by the SAGE II satellite were used to develop the retrieval algorithm and to test its capability. The test indicated that albedos for the SBUV ozone profiler wavelengths should allow estimates to a precision of +/- 5 percent or better, depending on the accuracy of the ultraviolet measurement. Retrievals using actual Umkehr observations were also performed to provide a preliminary look at the magnitude and annual variation of retrieved albedos. A case study was performed, comparing retrieved albedos with SBUV-measured albedos. The SBUV albedo change was seen to be approximately twice as large as the albedo changes estimated by the Umkehr method. Results of the investigation suggest that the method of estimation may be useful for determining the drift rate of the SBUV calibration.

Deluisi, John J.↗
NASA NTRS1996

U.S. Participation in the GOME and SCIAMACHY Projects

This report summarizes research done under NASA Grant NAGW-2541 from April 1, 1996 through March 31, 1997. The research performed during this reporting period includes development and maintenance of scientific software for the GOME retrieval algorithms, consultation on operational software development for GOME, consultation and development for SCIAMACHY near-real-time (NRT) and off-line (OL) data products, and development of infrared line-by-line atmospheric modeling and retrieval capability for SCIAMACHY. SAO also continues to participate in GOME validation studies, to the limit that can be accomplished at the present level of funding. The Global Ozone Monitoring Experiment was successfully launched on the ERS-2 satellite on April 20, 1995, and remains working in normal fashion. SCIAMACHY is currently in instrument characterization. The first two European ozone monitoring instruments (OMI), to fly on the Metop series of operational meteorological satellites being planned by Eumetsat, have been selected to be GOME-type instruments (the first, in fact, will be the refurbished GOME flight spare). K. Chance is the U.S. member of the OMI Users Advisory Group.

Chance, K. V.↗
NASA NTRS2004

Evaluation and Application of Satellite-Based Latent Heating Profile Estimation Methods

In recent years, methods for estimating atmospheric latent heating vertical structure from both passive and active microwave remote sensing have matured to the point where quantitative evaluation of these methods is the next logical step. Two approaches for heating algorithm evaluation are proposed: First, application of heating algorithms to synthetic data, based upon cloud-resolving model simulations, can be used to test the internal consistency of heating estimates in the absence of systematic errors in physical assumptions. Second, comparisons of satellite-retrieved vertical heating structures to independent ground-based estimates, such as rawinsonde-derived analyses of heating, provide an additional test. The two approaches are complementary, since systematic errors in heating indicated by the second approach may be confirmed by the first. A passive microwave and combined passive/active microwave heating retrieval algorithm are evaluated using the described approaches. In general, the passive microwave algorithm heating profile estimates are subject to biases due to the limited vertical heating structure information contained in the passive microwave observations. These biases may be partly overcome by including more environment-specific a priori information into the algorithm s database of candidate solution profiles. The combined passive/active microwave algorithm utilizes the much higher-resolution vertical structure information provided by spaceborne radar data to produce less biased estimates; however, the global spatio-temporal sampling by spaceborne radar is limited. In the present study, the passive/active microwave algorithm is used to construct a more physically-consistent and environment-specific set of candidate solution profiles for the passive microwave algorithm and to help evaluate errors in the passive algorithm s heating estimates. Although satellite estimates of latent heating are based upon instantaneous, footprint- scale data, suppression of random errors requires averaging to at least half-degree resolution. Analysis of mesoscale and larger space-time scale phenomena based upon passive and passive/active microwave heating estimates from TRMM, SSMI, and AMSR data will be presented at the conference.

Olson, William S.↗
NASA NTRS2007

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for constraining the use of the passive retrieval data in models and for improving the accuracy of the retrievals.

Nguyen, L.↗
NASA NTRSDate not supplied

An Oveview of TROPESS Data Products and Services at the NASA GES DISC

The TRopospheric Ozone and Precursors from Earth System Sounding (TROPESS) project generates Earth System Data Records (ESDRs) of ozone, and other atmospheric constituents (CH4,CO, H2O, HDO, NH3, PAN and temperature) by processing data from multiple satellites through a common retrieval algorithm and ground data system. Satellite Level-1B input data used in generating the TROPESS L2 data products include CrIS NOAA-20 (JPSS-1), CrIS SNPP, AIRS Aqua, OMI Aura, and TROPOMI S5P. The common retrieval framework is known as the MUlti-SpEctra, MUlti-SpEcies, Multi-SEnsors (MUSES) science data processing system (MUSES-SDPS). Several of the TROPESS data products are now available from the NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) for users to download. In this presentation we provide an overview of the various TROPESS data products. These data products can be divided into the following Forward Stream types: Standard Products, Summary Products, and Full-Archival Products. Standard Products are for users that are doing full analysis with avenging kernel and covariance corresponding to retrieved vertical profiles. Summary products have a smaller file size and are more convenient for first-look and rapid analysis, include total and partial columns, as well as column averaging kernels. The Full-Archival Products will contain all information used in creating the data. TROPESS also creates Special Products, provided on an as-needed and as-available basis to support NASA field missions and individual-investigator requests over specific regions. Eventually, TROPESS will also produce and deliver a set of Reanalysis Stream products. Data at the GES DISC are being transitioned into the "Cloud". This will allow users with "Cloud” access to perform data analysis directly on the data without downloading the data to their system. Services, such as subsetting and data visualization, will also be provided for TROPESS data products at the GES DISC.

James Johnson↗
NASA NTRS1984

Retrieval of ocean surface parameters from the scanning multifrequency microwave radiometer (SMMR) on the Nimbus-7 satellite

Sea-surface temperature retrievals have been tested on 2 months of Nimbus-7 scanning multichannel microwave radiometer data. Using the prelaunch versions of the instrument calibration and geophysical parameter retrieval algorithms the initial results were poor. Improved algorithms produced substantially better results. It appears that at least for the night-Southern Hemisphere portion of the Nimbus-7 orbit, a rms measurement accuracy of 1.45 C has been achieved. Similar tests with wind speed retrievals yield an accuracy of 2.7 m/s rms with no substantial differences between day and night measurements but limited by availability of surface observations to the Northern Hemisphere. Moreover, it appears that the retrieved wind speed is more nearly related to the square of the wind observed at the surface than to the wind itself.

Wilheit, T. T., Jr.↗
NASA NTRS1997

Synthetic Data for Testing TRMM Radar Algorithms

Test data are required to test algorithms for the TRMM Precipitation Radar. These data are needed to test the design of the computer codes under development for the operational phase of the mission, and also to test and evaluate alternative or improved precipitation retrieval algorithms. Over a number of years we have developed and used a 3-dimensional radar model for simulating spaceborne precipitation radars. We have adapted this code to produce data files as close as possible to the TRMM file specifications. In this paper, we will describe the model as it is currently implemented, and show some samples of the synthetic data sets.

Jones, Jeffrey A.↗
NASA NTRS2012

Cloud Height Retrieval with Oxygen A and B Bands for the Deep Space Climate Observatory (DSCOVR) Mission

Planned to fly in 2014, the Deep Space Climate Observatory (DSCOVR) would see the whole sunlit half of the Earth from the L 1 Lagrangian point and would provide simultaneous data on cloud and aerosol properties with its Earth Polychromatic Imaging Camera (EPIC). EPIC images the Earth on a 2Kx2K CCD array, which gives a horizontal resolution of about 10 km at nadir. A filter-wheel provides consecutive images in 10 spectral channels ranging from the UV to the near-IR, including the oxygen A and B bands. This paper presents a study of retrieving cloud height with EPIC's oxygen A and B bands. As the first step, we analyzed the effect of cloud optical and geometrical properties, sun-view geometry, and surface type on the cloud height determination. Second, we developed two cloud height retrieval algorithms that are based on the Mixed Lambertian-Equivalent Reflectivity (MLER) concept: one utilizes the absolute radiances at the Oxygen A and B bands and the other uses the radiance ratios between the absorption and reference channels of the two bands. Third, we applied the algorithms to the simulated EPIC data and to the data from SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) observations. Results show that oxygen A and B bands complement each other: A band is better suited for retrievals over ocean, while B band is better over vegetated land due to a much darker surface. Improvements to the MLER model, including corrections to surface contribution and photon path inside clouds, will also be discussed.

Yang, Yuekui↗
NASA NTRS2015

Comparison of Ozone Retrievals from the Pandora Spectrometer System and Dobson Spectrophotometer in Boulder, Colorado

A comparison of retrieved total column ozone (TCO) amounts between the Pandora #34 spectrometer system and the Dobson #061 spectrophotometer from direct-sun observations was performed on the roof of the Boulder, Colorado, NOAA building. This paper, part of an ongoing study, covers a 1-year period starting on 17 December 2013. Both the standard Dobson and Pandora TCO retrievals required a correction, TCO(sub corr) = TCO (1 + C(T)), using a monthly varying effective ozone temperature, T(sub E), derived from a temperature and ozone profile climatology. The correction is used to remove a seasonal difference caused by using a fixed temperature in each retrieval algorithm. The respective corrections C(T(sub E)) are C(sub Pandora) = 0.00333(T(sub E) - 225) and C(sub Dobson) = -0.0013(T(sub E) - 226.7) per degree K. After the applied corrections removed most of the seasonal retrieval dependence on ozone temperature, TCO agreement between the instruments was within 1% for clear-sky conditions. For clear-sky observations, both co-located instruments tracked the day-to-day variation in total column ozone amounts with a correlation of r(exp 2) = 0.97 and an average offset of 1.1 +/- 5.8 DU. In addition, the Pandora TCO data showed 0.3% annual average agreement with satellite overpass data from AURA/OMI (Ozone Monitoring Instrument) and 1% annual average offset with Suomi-NPP/OMPS (Suomi National Polar-orbiting Partnership, the nadir viewing portion of the Ozone Mapper Profiler Suite).

Herman, J.↗
NASA NTRS1988

Relations between VAS physical retrievals and their first guess input

The Smith (1983) physical retrieval algorithm, which is designed to yield mesoscale soundings through a blending of first-guess limited fine mesh-derived profiles with VISSR Atmospheric Sounder (VAS) detected radiance data by means of an inversion of the radiative transfer equation, yields retrievals that may be better related to ground truth data than the guess profiles at some levels. At other levels, the first-guess profiles were slightly superior to the retrievals. Correlation functions related to the window and midtropospheric temperature channels indicate that magnitudes and orientations of retrieval gradients were intermediate to those of the guess data and brightness temperatures.

Beven, John L.↗
NASA NTRS2001

Satellite-Based Stratospheric and Tropospheric Measurements: Determination of Global Ozone and other Trace Species

This report summarizes research done under NASA Grant NAG5-3461 from November 1, 1996 through December 31, 2000. The research performed during this reporting period includes development and maintenance of scientific software for the GOME retrieval algorithms, consultation on operational software development for GOME, sensitivity and instrument studies to help finalize the definition of the SCIAMACHY instrument, leading the development of the SCIAMACHY Scientific Requirements Document for Data and Algorithm Development, consultation and development for SCIAMACHY near-real-time (NRT) and off-line (OL) data products, radiative transfer model development for utilization in GOME, SCIAMACHY and other programs, development of infrared line-by-line atmospheric modeling and retrieval capability for SCIAMACHY, and participation in GOME and SCIAMACHY validation studies. The Global Ozone Monitoring Experiment was successfully launched on the ERS-2 satellite on April 20, 1995, and remains working in normal fashion. SCIAMACHY is currently planned for launch in late 2001 on the ESA Envisat satellite. Three GOME-2 instruments are now scheduled to fly on the Metop series of operational meteorological satellites (Eumetsat). K. Chance is a member of the reconstituted GOME Scientific Advisory Group, which will guide the GOME-2 program as well as the continuing ERS-2 GOME program.

Chance, K. V.↗
NASA NTRS2012

Recent Advances in Improvement of Forecast Skill and Understanding Climate Processes Using AIRS Version-5 Products

AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. These observations, covering the period September 2002 until the present, have been analyzed using the AIRS Science Team Version-5 retrieval algorithm. AIRS is a high spectral resolution infrared grating spectrometer with spect,ral coverage from 650 per centimeter extending to 2660 per centimeter, with low noise and a spectral resolving power of 2400. A brief overview of the AIRS Version-5 retrieval procedure will be presented, including the AIRS channels used in different steps in the retrieval process. Many researchers have used these products to make significant advances in both climate and weather applications. Recent significant results of these experiments will be presented, including results showing that 1) assimilation of AIRS Quality Controlled temperature profiles into a General Circulation Model (GCM) significantly improves the ability to predict storm tracks of intense precipitation events; and 2) anomaly time-series of Outgoing Longwave Radiation (OLR) computed using AIRS sounding products closely match those determined from the CERES instrument, and furthermore explain that the phenomenon that global and especially tropical mean OLR have been decreasing since September 2002 is a result of El Nino/La Nina oscillations during this period.

Susskind, Joel↗
NASA NTRS2019

First Steps in the Creation of a Joint MISR/MODIS Ocean Color Atmospheric Correction Algorithm

We are creating a new algorithm that combines observations from MISR and MODIS (both on the NASA Terra spacecraft) to improve atmospheric correction and coverage for ocean color data products. The algorithm utilizes information rich, multi-angle MISR observations for atmospheric correction, applied to MODIS. Our goal is to produce atmospherically corrected Remote Sensing Reflectance from MODIS with enhanced coverage and accuracy, for input to downstream bio-optical ocean parameter retrieval algorithms.An important aspect of this work is the utilization of multi-angle views of the reflected ocean surface sun glint. Usually, such observations are avoided, since the intensity of the glint overwhelms any contribution from the ocean body. However, MISR's multi-angle observations see varying degrees of glint, which means they can be used to better determine aerosol optical properties (Kaufman et al., 2002, Ottaviani et al., 2013), and to identify surface wind speeds that govern the glint pattern. The latter could be utilized to replace the wind speeds taken from ancillary sources that are currently used to conservatively mask potential glint contamination in MODIS observations.To assess this capability, and to identify the appropriate parameterization, we present an analysis using the Generalized Nonlinear Retrieval Analysis (GENRA, Vukicevic et al., 2009) information content assessment. This technique is also easily modified to act as a Bayesian retrieval algorithm, for which initial results are discussed. Finally, we describe the status of integrating MISR data into the processing capabilities of the Ocean Biology Processing Group (OBPG) at NASA, and show the first ocean color vicarious calibration (Franz et al., 2007) of the MISR instrument.

Knobelspiesse, Kirk↗
NASA NTRSDate not supplied

A Modeling and Simulation Study for the GeoXO Atmospheric Composition Instrument (ACX): System Level SO2 and O3 Retrieval Performance as a Function of SNR

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral UV/visible atmospheric composition instrument in geostationary orbit slated for operations by the early 2030s. Trace gas retrievals provide critical information about our Earth’s system as it relates to both natural and anthropogenic activity. This work focused on the impacts of the signal-to-noise ratio (SNR) on the retrieval uncertainty of SO2 and O3. An end-to-end physics-based imaging system and scene modeling and simulation framework was developed to assess instrument performance considerations in support of the planned GeoXO atmospheric composition instrument (ACX). The framework is composed of three primary components: 1) simulated at-sensor radiance via radiative transfer models of a known atmospheric composition, 2) a noise model driven by previous and planned sensor specifications, and 3) a physical retrieval algorithm. In this analysis, the tropospheric concentrations of SO2 and O3 in the atmospheric column were varied in the boundary layer (0-3 km) and at an elevation of 5 km with a thickness of 1-2 km; the uncertainty in retrieval was studied for various SNR levels for multiple viewing geometries and solar zenith angles. This effort supports the development of the GeoXO ACX instrument by providing a simulated ACX performance assessment of the system-level retrieval performance as a function of SNR, particularly with respect to the wavelength range of interest (approximately 305 – 340 nm) for SO2 and O3 trace gas retrievals.

Monica Cook↗
NASA NTRS1984

NROSS scatterometer - An instrument for global oceanic wind observations

One of the instruments - the NROSS scatterometer or SCATT - to be launched on the Navy Remote Ocean Sensing System spacecraft in 1989 is discussed. To determine wind speed and direction that SCATT will measure the ocean normalized radar cross section (NRCS) by illuminating the ocean's surface with microwave pulses and measuring the return signal power. A wind retrieval algorithm is used to compute the wind speed and direction from the measured NRCS. Winds over at least 90 percent of the global, ice-free ocean will be observed at least once every two days. For NASA users, the system will retrieve winds with an accuracy of plus or minus 2 m/s or 10 percent whichever is greater, for wind speeds ranging from 3 to 30 m/s.

Li, F.↗
NASA NTRS2006

The Continuous Monitoring of Desert Dust using an Infrared-based Dust Detection and Retrieval Method

Airborne dust and sand are significant aerosol sources that can impact the atmospheric and surface radiation budgets. Because airborne dust affects visibility and air quality, it is desirable to monitor the location and concentrations of this aerosol for transportation and public health. Although aerosol retrievals have been derived for many years using visible and near-infrared reflectance measurements from satellites, the detection and quantification of dust from these channels is problematic over bright surfaces, or when dust concentrations are large. In addition, aerosol retrievals from polar orbiting satellites lack the ability to monitor the progression and sources of dust storms. As a complement to current aerosol dust retrieval algorithms, multi-spectral thermal infrared (8-12 micron) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat-8 Spinning Enhanced Visible and Infrared Imager (SEVIRI) are used in the development of a prototype dust detection method and dust property retrieval that can monitor the progress of Saharan dust fields continuously, both night and day. The dust detection method is incorporated into the processing of CERES (Clouds and the Earth s Radiant Energy System) aerosol retrievals to produce dust property retrievals. Both MODIS (from Terra and Aqua) and SEVERI data are used to develop the method.

Duda, David P.↗
NASA NTRS2008

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

Molnar, Gyula↗