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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

Climate↗
NASA NTRS2015

Evaluation of Radar Vegetation Indices for Vegetation Water Content Estimation Using Data from a Ground-Based SMAP Simulator

Vegetation water content (VWC) is an important component of microwave soil moisture retrieval algorithms. This paper aims to estimate VWC using L band active and passive radar/radiometer datasets obtained from a NASA ground-based Soil Moisture Active Passive (SMAP) simulator known as ComRAD (Combined Radar/Radiometer). Several approaches to derive vegetation information from radar and radiometer data such as HH, HV, VV, Microwave Polarization Difference Index (MPDI), HH/VV ratio, HV/(HH+VV), HV/(HH+HV+VV) and Radar Vegetation Index (RVI) are tested for VWC estimation through a generalized linear model (GLM). The overall analysis indicates that HV radar backscattering could be used for VWC content estimation with highest performance followed by HH, VV, MPDI, RVI, and other ratios.

soil moisture↗
DOE OSTI2023

TRACER CLAMPS1 AERI TROPoe Retrievals

These files contain 24 hour periods of retrieved thermodynamic profiles derived from observations collected by the CLAMPS1 Atmospheric Emitted Radiance Interferometer (AERI). The TROPoe algorithm is a python equivalent to the AERIoe algorithm (see Turner and Loehnert 2014; Turner and Blumberg 2019). These data were collected during the TRACER-CUBIC project. Due to issues with the CLAMPS1 microwave radiometer, only retrievals that used AERI data are available.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Quantifying Global Uncertainties in a Simple Microwave Rainfall Algorithm

While a large number of methods exist in the literature for retrieving rainfall from passive microwave brightness temperatures, little has been written about the quantitative assessment of the expected uncertainties in these rainfall products at various time and space scales. The latter is the result of two factors: sparse validation sites over most of the world's oceans, and algorithm sensitivities to rainfall regimes that cause inconsistencies against validation data collected at different locations. To make progress in this area, a simple probabilistic algorithm is developed. The algorithm uses an a priori database constructed from the Tropical Rainfall Measuring Mission (TRMM) radar data coupled with radiative transfer computations. Unlike efforts designed to improve rainfall products, this algorithm takes a step backward in order to focus on uncertainties. In addition to inversion uncertainties, the construction of the algorithm allows errors resulting from incorrect databases, incomplete databases, and time- and space-varying databases to be examined. These are quantified. Results show that the simple algorithm reduces errors introduced by imperfect knowledge of precipitation radar (PR) rain by a factor of 4 relative to an algorithm that is tuned to the PR rainfall. Database completeness does not introduce any additional uncertainty at the global scale, while climatologically distinct space/time domains add approximately 25% uncertainty that cannot be detected by a radiometer alone. Of this value, 20% is attributed to changes in cloud morphology and microphysics, while 5% is a result of changes in the rain/no-rain thresholds. All but 2%-3% of this variability can be accounted for by considering the implicit assumptions in the algorithm. Additional uncertainties introduced by the details of the algorithm formulation are not quantified in this study because of the need for independent measurements that are beyond the scope of this paper. A validation strategy for these errors is outlined.

Kummerow, Christian↗
NASA NTRS1995

Ground-based microwave monitoring of middle atmosphere ozone: Comparison to lidar and Stratospheric and Gas Experiment 2 satellite observations

A dedicated ground-based microwave radiometer was in operation to monitor the middle atmospheric ozone concentration at Table Mountain Facility (TMF) of the Jet Propulsion Laboratory (JPL), California (34.4 deg N, 117.7 deg W) from July 1989 to June 1992, as a part of the Network for Detection of Stratospheric Change. Ozone profiles from 56 to 0.04 mbar (approximately 20 - 70 km) were retrieved from the microwave data. The focus in this paper is to validate the microwave ozone observations from 56 to 1 mbar by comparing the results from a JPL ground-based lidar located at the same site and from the Stratospheric Aerosol and Gas Experiment 2 (SAGE 2) satellite overpasses within 1000 km of TMF and to examine the ability of these instruments to detect short-term, seasonal, and annual variations in ozone. The profile comparison results show that the mean differences of microwave ozone from lidar and SAGE 2 are about 5% or less and the root-mean-square scatter about the mean is mainly from the precision of the instruments. A correlation analysis of ozone time series suggests highly significant correlations up to 2.4 mbar between lidar and microwave measurements and up to 1 mbar between SAGE 2 and microwave. The short-term and seasonal variation of the ozone profile seen in the microwave measurements is shown to be consistent with the observations of lidar and SAGE 2, and the interannual variation of ozone appears to be detectable within an accuracy of a few percent with the microwave instrument.

Tsou, J. J.↗
NASA NTRS2022

Assimilation of GPM-retrieved Ocean Surface Meteorology Data for Two Snowstorm Events during ICE-POP 2018

As a component of the National Aeronautics and Space Administration (NASA) Weather Focus Area and Global Precipitation Measurement (GPM) Ground Validation participation in the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field research and forecast demonstration programs, hourly ocean surface meteorology properties were retrieved from the GPM microwave observations for January – March 2018. In this study, the retrieved ocean surface meteorological products – 2-m temperature, 2-m specific humidity, and 10-m wind speed were assimilated into a regional numerical weather prediction (NWP) framework to explore the application of these observations for two heavy snowfall events during the ICE-POP 2018: 27-28 February, and 7-8 March 2018. The Weather Research and Forecasting (WRF) model and the community Gridpoint Statistical Interpolation (GSI) were used to conduct high resolution simulations and data assimilation experiments. The results indicate that the data assimilation has a large influence on surface thermodynamic and wind fields in the model initial condition for both events. With cycled data assimilation, significantly positive influence of the retrieved surface observation was found for the March case with improved quantitative precipitation forecast and reduced error in temperature forecast. A slightly smaller yet positive impact was also found in the forecast of the February case.

assimilation↗
DOE OSTI2021

Droplet Number Concentration Value-Added Product

The ndrop_mfrsr value-added product (VAP) provides an estimate of the cloud droplet number concentration of overcast water clouds retrieved from cloud optical depth from the multi-filter rotating shadowband radiometer (MFRSR) instrument and liquid water path (LWP) retrieved from the microwave radiometer (MWR). When cloud layer information is available from vertically pointing lidar and radars in the Active Remote Sensing of Clouds (ARSCL) product, the VAP also provides estimates of the adiabatic LWP and an adiabatic parameter (beta) that indicates how divergent the LWP is from the adiabatic case. quality control (QC) flags (qc_drop_number_conc), an uncertainty estimate (drop_number_conc_toterr), and a cloud layer type flag (cloud_base_type) are useful indicators of the quality and accuracy of any given value of the retrieval. Examples of these major input and output variables are given in sample plots in section 6.0.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

Water Vapor Profile Retrievals from the HIRS/MSU Satellite Sounder

The objective of this research is to develop a method for the retrieval of atmospheric water vapor profiles within the context of the GLAS physically based retrieval scheme. The GLAS retrieval method is currently capable of producing accurate atmospheric temperature retrievals as well as cloud fields and retrieved surface properties such as temperature and microwave emissivity. In the GLAS retrieval scheme, the water vapor field used in the computation of the atmospheric transmittance functions is obtained from a 6 hour forecast and is not modified in the retrieval process. Improved estimates of the water vapor field, in addition to being in themselves variables of meteorological interest, may, therefore, result in improved estimates of the other retrieved parameters obtained from the system.

Reuter, D.↗
NASA NTRS1998

Evaluation of Terms in the Water Vapor Budget Using Airborne Dial and In Situ Measurements from the Southern Great Plans 1997 Experiment

The Southern Great Plains (SGP97) field experiment was conducted in Oklahoma during June and July 1997 primarily to validate soil moisture retrieval algorithms using microwave radiometer measurements from aircraft as well as in situ surface measurements. One important objective of the SGP97 experiment plan was to examine the effect of soil moisture on the evolution of the atmospheric boundary layer (ABL) and clouds over the Southern Great Plains during the warm season. To support boundary layer studies during SGP97. the NASA Langley Research Center's Lidar Atmospheric Sensing Experiment (LASE) was flown on a NASA-P3 aircraft in conjunction with the Electronically Scanned Thinned Array Radiometer (ESTAR). The LASE instrument is an airborne, downward-looking differential absorption lidar (DIAL) system capable of measuring water vapor concentration as well as aerosol backscatter with high horizontal and vertical resolution in the ABL. Here, we will demonstrate how the LASE data can be used to determine water vapor statistics and most of the water vapor budget terms in the ABL. This information can then be related to spatial variations in soil moisture and the surface energy budget. The extensive surface and aircraft in situ measurements conducted during SGP97 provide information on the ABL that cannot be retrieved from the LASE data alone and also offer an excellent opportunity to validate the remote water vapor budget measurements with LASE.

Senff, Christoph J.↗
NASA NTRS1993

Comparison of remote sensing measurements with a two-scale polarimetric emission and scattering model for sea surfaces

Recently, it has been observed that the brightness temperatures of sea surfaces correlate with the azimuth angle of the ocean wind vector, indicating that ocean wind direction can not only be retrieved from the microwave backscatter, but also from the brightness temperature measurements. In this paper, comparison of the theoretical result calculated from a two-scale emission and scattering model with the Seasat and SSM/I model functions and aircraft measurements is presented and potential applications of microwave polarimetry are discussed. In our two-scale model, the modified reflectivities of large scale surfaces are calculated by extending the small perturbation method to the second order for small scale perturbation with anisotropic directional spectrum. It was found that the modified reflectivities derived from the second-order scattered field agree excellently well with the results obtained from a Monte Carlo simulation technique which numerically calculates the polarimetric reflectivities of one-dimensional random rough surfaces with a power-law spectrum. Without the second-order correction, the modified reflectivities of the rough surfaces are significantly over-estimated and sign errors are observed in the third and fourth Stokes parameters for thermal emissions. The surface spectrum parameters and two-scale cutoff are selected so that the calculated scattering and emission signatures agree with the reported model functions for Seasat and SSM/I. Subsequently, the polarimetric signatures of sea surfaces are illustrated to indicate the possibility of reducing the number of azimuthal looks required for spaceborne sensors in the remote sensing of ocean wind by using the polarimetric information. Furthermore, it is found that contrary to the dependence of backscattering coefficients on incidence angles, polarimetric brightness temperatures display a stronger wind direction dependence in the near nadir-looking direction than away from nadir. Finally, we discuss the potential of a single-look polarimetric radiometer for wind retrieval.

Yueh, S. H.↗
NASA NTRS1997

Passive Microwave Algorithms for Sea Ice Concentration: A Comparison of Two Techniques

The most comprehensive large-scale characterization of the global sea ice cover so far has been provided by satellite passive microwave data. Accurate retrieval of ice concentrations from these data is important because of the sensitivity of surface flux(e.g. heat, salt, and water) calculations to small change in the amount of open water (leads and polynyas) within the polar ice packs. Two algorithms that have been used for deriving ice concentrations from multichannel data are compared. One is the NASA Team algorithm and the other is the Bootstrap algorithm, both of which were developed at NASA's Goddard Space Flight Center. The two algorithms use different channel combinations, reference brightness temperatures, weather filters, and techniques. Analyses are made to evaluate the sensitivity of algorithm results to variations of emissivity and temperature with space and time. To assess the difference in the performance of the two algorithms, analyses were performed with data from both hemispheres and for all seasons. The results show only small differences in the central Arctic in but larger disagreements in the seasonal regions and in summer. In some ares in the Antarctic, the Bootstrap technique show ice concentrations higher than those of the Team algorithm by as much as 25%; whereas, in other areas, it shows ice concentrations lower by as much as 30%. The The differences in the results are caused by temperature effects, emissivity effects, and tie point differences. The Team and the Bootstrap results were compared with available Landsat, advanced very high resolution radiometer (AVHRR) and synthetic aperture radar (SAR) data. AVHRR, Landsat, and SAR data sets all yield higher concentrations than the passive microwave algorithms. Inconsistencies among results suggest the need for further validation studies.

Comiso, Josefino C.↗
NASA NTRS1990

Comparison of SSM/I measurements to numerically-simulated cloud and precipitation during ERICA

These investigations focused essentially on the macroscale organization of cloud and precipitation which occurred during the 4th Intensive Observing Period (IOP-4) of the Experiment for Rapidly Intensifying Cyclones over the Atlantic (ERICA). This experiment, held off the East Coast of the United States and Canada during the winter of 1989, documented several episodes of rapid cyclonic storm development. Also playing a major role as validation and ground truth in these studies are Special Sensor Microwave Imager (SSM/I) retrievals of precipitable water, total liquid water and ice, generated by other Marshall Space Flight Center (MSFC) supported investigations. Model simulations produced to date suggest that, while the large-scale atmospheric dynamics was an essential driving mechanism, the role of condensation was crucial in facilitating the exceptionally rapid spinup of the cyclone and the low surface pressure. A model simulation of the precipitation rate at the time of most rapid storm intensification is shown in the accompanying figure. Heavier precipitation rates in the crescent shaped region are associated with deep convection along the leading edge of a dry intrusion behind the surface low. The majority of precipitation in the stratiform region to the northeast involved the production of ice with deposition from vapor to ice being the dominant process of growth. Some small amount of mixed phase cloudiness was present. Model condensate distributions matched well with SSM/I observations. The accompanying SSM/I imagery which delineates areas of large (greater than several hundred micron effective radius) precipitating ice over the ocean suggests that the model has done well in capturing the essential mechanisms responsible for the horizontal distribution of precipitation.

Robertson, Franklin R.↗
NASA NTRS1999

TRMM-Based Merged Precipitation Analyses

This paper describes results of using Tropical Rainfall Measuring Mission (TRMM) information as the key calibration tool in a merged analysis on a 1X1 latitude/longitude monthly scale based on multiple satellite sources and raingauge analyses. The TRMM-based product is compared with surface-based validation data sets and the community-based 20-year Global Precipitation Climatology Project (GPCP)monthly analyses. The TRMM-based merged analysis uses the TRMM information to calibrate the estimates from SSM/I and geosynchronous IR observations and merges those estimates together with the TRMM and gauge information to produce accurate rainfall estimates with the increased sampling provided by the combined satellite information. This TRMM merged analysis uses the combined instrument (Precipitation Radar [PR] and TRMM Microwave Imager [TMI]) retrieval of Haddad as the TRMM estimate with which to calibrate the other satellite estimates. This TRMM Combined instrument (TCI) estimate is shown to produce very similar absolute values to the other main TRMM products. The TRMM and other satellites merged analysis compares favorably to the atoll data set of Morrissey for the months of 1998 with a very small positive bias of 2%. However, comparison with the preliminary results from the TRMM ground validation radar information at Kwajalein atoll in the western Pacific Ocean shows a 26% positive bias. Therefore, absolute magnitudes from TRMM and/or the ground validation need to be treated with care at this point. A month by month comparison of the TRMM merged analysis and the GPCP analysis indicates very similar patterns, but with subtle differences in magnitude. Focusing on the Pacific Ocean ITCZ one can see the TRMM-based estimates having higher peak values and lower values in the ITCZ periphery. These attributes also show up in the statistics, where GPCP>TRMM at low values (below 10 mm/d) and TRMM>GPCP at high values (greater than 15 mm/d). Integrated over the 37N-37S belt for all of 1998 the TRMM value is 3.1 mm/day compared to 2.9 mm/day for GPCP, with the results when confined to ocean being 3.3 and 3.0, respectively. Therefore, TRMM has approximately 10% higher tropical oceanic precipitation than GPCP. Examples of TRMM monthly fields in analysis of geographic and temporal variations will also be discussed. Results for 1998 indicate that TRMM has a different ratio of western Pacific to eastern Pacific rainfall than GPCP, perhaps indicating that TRMM's ability to discern the vertical structure of the rain may lead to better estimates in the eastern Pacific. In addition the rainfall anomalies associated with the '98-'99 ENSO event are shown to be larger with the TRMM results as compared to the GPCP analyses.

Adler, Robert↗