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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Nimbus-7 global cloud climatology. I - Algorithms and validation

An improved version of the Nimbus-7 cloud retrieval algorithm was validated using data from Nimbus-7 Temperature Humidity Infrared Radiometer and Total Ozone Mapping Spectrometer to determine cloudiness parameters for the globe. Quantitative validation of total cloud amount was performed by comparing the algorithm results with estimates derived from GOES images and auxiliary meteorological data. The systematic errors of the Nimbus-7 total cloud-amount algorithm, relative to the GOES-derived estimates, were found to be less than 10 percent. The random errors of daily estimates ranged between 7 and 16 percent, day or night.

Stowe, L. L.↗
NASA NTRS1994

Observation of melt onset on multiyear Arctic sea ice using the ERS 1 synthetic aperture radar

We present nearly coincident observations of backscattering from the Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and of near-surface temperature from six drifting buoys in the Beaufort Sea, showing that the onset of melting in snow on multiyear sea ice is clearly detectable in the SAR data. Melt onset is marked by a clean, steep decrease in the backscattering cross section of multiyear ice at 5.3 GHz and VV polarization. We investigate the scattering physics responsible for the signature change and find that the cross section decrease is due solely to the appearance of liquid water in the snow cover overlying the ice. A thin layer of moist snow is sufficient to cause the observed decrease. We present a prototype algorithm to estimate the date of melt onset using the ERS 1 SAR and apply the algorithm first to the SAR data for which we have corresponding buoy temperatures. The melt onset dates estimated by the SAR algorithm agree with those obtained independently from the temperature data to within 4 days or less, with the exception of one case in which temperatures oscillated about 0 C for several weeks. Lastly, we apply the algorithm to the entire ERS 1 SAR data record acquired by the Alaska SAR Facility for the Beaufort Sea north of 73 deg N during the spring of 1992, to produce a map of the dates of melt onset over an area roughly 1000 km on a side. The progression of melt onset is primarily poleward but shows a weak meridional dependence at latitudes of approximately 76 deg-77 deg N. Melting begins in the southern part of the study region on June 13 and by June 20 has progressed to the northermost part of the region.

Winebrenner, D. P.↗
NASA NTRS1999

Improved Stratospheric Temperature Retrievals for Climate Reanalysis

The Data Assimilation Office (DAO) is embarking on plans to generate a twenty year reanalysis data set of climatic atmospheric variables. One of the focus points will be in the evaluation of the dynamics of the stratosphere. The Stratospheric Sounding Unit (SSU), flown as part of the TIROS Operational Vertical Sounder (TOVS), is one of the primary stratospheric temperature sensors flown consistently throughout the reanalysis period. Seven unique sensors made the measurements over time, with individual instrument characteristics that need to be addressed. The stratospheric temperatures being assimilated across satellite platforms will profoundly impact the reanalysis dynamical fields. To attempt to quantify aspects of instrument and retrieval bias we are carefully collecting and analyzing all available information on the sensors, their instrument anomalies, forward model errors and retrieval biases. For the retrieval of stratospheric temperatures, we adapted the minimum variance approach of Jazwinski (1970) and Rodgers (1976) and applied it to the SSU soundings. In our algorithm, the state vector contains an initial guess of temperature from a model six hour forecast provided by the Goddard EOS Data Assimilation System (GEOS/DAS). This is combined with an a priori covariance matrix, a forward model parameterization, and specifications of instrument noise characteristics. A quasi-Newtonian iteration is used to obtain convergence of the retrieved state to the measurement vector. This algorithm also enables us to analyze and address the systematic errors associated with the unique characteristics of the cell pressures on the individual SSU instruments and the resolving power of the instruments to vertical gradients in the stratosphere. The preliminary results of the improved retrievals and their assimilation as well as baseline calculations of bias and rms error between the NESDIS operational product and col-located ground measurements will be presented.

Rokke, L.↗
NASA NTRS1991

An evaluation of analog and numerical techniques for unsteady heat transfer measurement with thin-film gauges in transient facilities

The importance of frequency response considerations in the use of thin-film gages for unsteady heat transfer measurements in transient facilities is considered, and methods for evaluating it are proposed. A departure frequency response function is introduced and illustrated by an existing analog circuit. A Fresnel integral temperature which possesses the essential features of the film temperature in transient facilities is introduced and is used to evaluate two numerical algorithms. Finally, criteria are proposed for the use of finite-difference algorithms for the calculation of the unsteady heat flux from a sampled temperature signal.

George, William K.↗
NASA NTRS1985

Sea surface temperature - Observations from geostationary satellites

Multispectral image data acquired from the VISSR atmospheric sounder (VAS) on the geostationary GOES satellites were used to estimate sea surface temperatures (SST). A procedure was developed to screen VAS visible and infrared data for cloud-free regions for estimation of SST from the clear infrared radiances. A data set of matches between the VAS radiances and high quality buoy estimates of SST was produced. A linear regression analysis of these matches was performed to generate an empirical algorithm relating the VAS window channel brightness temperatures to the estimates of SST recorded by NOAA fixed environment buoys. Daily maps of SST during Hurricanes Alicia (1983) and Debbie (1982) demonstrated the ability of VAS to monitor air-sea interactions at high temporal and spatial scales.

Bates, J. J.↗
NASA NTRS1993

Atmospheric electricity/meteorology analysis

This activity focuses on Lightning Imaging Sensor (LIS)/Lightning Mapper Sensor (LMS) algorithm development and applied research. Specifically we are exploring the relationships between (1) global and regional lightning activity and rainfall, and (2) storm electrical development, physics, and the role of the environment. U.S. composite radar-rainfall maps and ground strike lightning maps are used to understand lightning-rainfall relationships at the regional scale. These observations are then compared to SSM/I brightness temperatures to simulate LIS/TRMM multi-sensor algorithm data sets. These data sets are supplied to the WETNET project archive. WSR88-D (NEXRAD) data are also used as it becomes available. The results of this study allow us to examine the information content from lightning imaging sensors in low-earth and geostationary orbits. Analysis of tropical and U.S. data sets continues. A neural network/sensor fusion algorithm is being refined for objectively associating lightning and rainfall with their parent storm systems. Total lightning data from interferometers are being used in conjunction with data from the national lightning network. A 6-year lightning/rainfall climatology has been assembled for LIS sampling studies.

Goodman, Steven J.↗
NASA NTRS2013

SDR Input Power Estimation Algorithms

The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.

Nappier, Jennifer M.↗
NASA NTRS1989

Upwind-biased, point-implicit relaxation strategies for viscous, hypersonic flows

An upwind-biased point-implicit relaxation algorithm for obtaining the numerical solution to the governing equations for three-dimensional viscous hypersonic flows in chemical and thermal nonequilibrium is described. Details of the algorithm development, in the context of an 11-species two-temperature reacting gas model, are emphasized. Because of the point-implicit relaxation strategy, the algorithm remains stable at large Courant numbers without the necessity of solving large block-tridiagonal systems. Predictions for the hypersonic flow of air in chemical and thermal nonequilibrium (velocity = 8917 m/s, altitude = 78 km) over the Aeroassist Flight Experiment configuration, obtained on a multidomain grid, are discussed.

Gnoffo, Peter A.↗
NASA NTRSDate not supplied

Where IMERG Goes Next: Version 08 and Beyond

With the Version 07 (V07) Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm finalized and production initiated, the focus turns to enhancements for Version 08. These include innovations not included in V07 due to time constraints, plus issues revealed by the initial V07 products. One high priority is to evaluate and revise the schemes in V07 that rectify temporal artifacts caused by the time interpolation that fills the gaps between the various passive microwave (PMW) sensor overpasses. A second priority is to improve the homogeneity between the TRMM and GPM eras by characterizing differences between the two eras, determining the causes of these differences, and applying corrections as feasible, perhaps by enforcing spatial scale consistency (an overarching issue). Certainly, we must account for GPROF and the Combined Radar-Radiometer Algorithm converting to Machine Learning schemes in V08. Other priority topics include additional automated quality control for artifacts in the IR brightness temperatures and PMW precipitation fields, revisions to the specification algorithm for the probability of liquid precipitation, and accommodating new PMW sensors, which include the next generation of small-sats. We also consider the post-V08 landscape; the final GPM reprocessing will be restricted to fixing known code or algorithmic errors. Nonetheless, there are several data sources on the horizon to consider, including more small-sat PMW radiometers, AVHRR-based precipitation estimates (most useful in high latitudes), and the ISCCP-Next Generation and GEO-Ring projects that could provide easy access to multiple geosynchronous satellite channels and enable significantly improved algorithms compared to GEO-IR alone.

George J. Huffman↗
NASA NTRS2022

Multi-Frequency Radiometer-Based Soil Moisture Retrieval and Algorithm Parameterization Using In Situ Sites

L-band brightness temperature (TB) has been shown to provide the best sensitivity to soil moisture (SM) although C- and X-band based products offer a longer time-series from satellite-based measurements. Currently, global coverage SM is routinely produced from spaceborne measurements using all three frequency bands, but despite continued validation efforts of the products, the relative characteristics and performance of these observations have not been fully established. Therefore, this study focused on the parametrization of SM retrieval algorithms at L-, C- and X-bands using TB observations from the L-band radiometer on NASA's SM Active Passive (SMAP) mission and the C- and X-band channels of JAXA's Advanced Microwave Scanning Radiometer 2 (AMSR2) onboard the GCOM-W satellite. These can be applied in global SM retrieval algorithms using either one of the frequencies or a combination of them. The reference in situ SM data was obtained from 12 core validation sites across various land cover types around the world. The investigation highlighted the known challenges of retrieving SM from C- and X-band data compared to the higher sensitivity of the L-band data. Even with a site-specific retrieval algorithm parameterization, the mean correlation of the C- and X-band retrievals for the core validation site SM measurement were much lower than that for L-band, being 0.52 (0.54) and 0.45 (0.47) for vertical (horizontal) polarization, respectively, while for the L-band retrieval the corresponding values were 0.81 (0.77). The parameterization exercise showed that matching the C- and X-band TB measurements with an emission model was not difficult; the problem was relating the observations to SM under the influence of large roughness and vegetation effects. As a result, parameter optimization produced values for some sites that were not realistic or did not allow any practical sensitivity to SM at C- and X-band. Considering the L-band observations, the parameter optimization resulted in superior bias performance as compared to the operational SMAP product parameterization, but the sensitivity to SM changes (R and unbiased root mean square difference) did not improve markedly, or in some cases degraded at the expense of a smaller bias.

passive microwave↗
NASA NTRS2022

Flood Monitoring Using Enhanced Resolution Passive Microwave Data: A Test Case Over Bangladesh

Monitoring floods is a major issue in water resources management and risk mitigation, especially in the Global South. Optical and radar observations, even providing a fine spatial resolution, are still limited by cloud cover interaction or insufficient temporal resolution. On the other hand, passive microwave (PMW) sensors collect information on a daily frequency with minor cloud cover interaction, but they have been historically limited in terms of spatial resolution. Here, we evaluate the capability of an enhanced spatial resolution PMW dataset (3.125 km) in monitoring spatio-temporal evolution of flood events, focusing on a major flood event that occurred in October 2005 in Bangladesh. We apply an algorithm aimed to remove the seasonal variability of surface temperature from the PMW timeseries, exploiting the difference in emissivity between dry and water-covered pixels. We assess the capability of the algorithm in capturing flood evolution and extension through the comparison with quantities obtained from optical data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and water level measurements. We also compare the enhanced product with the historical coarser resolution dataset by means of a variogram-based analysis to evaluate the improvements in terms of spatial representation. Finally, we evaluate the possibility to extract the water fraction within a single pixel by using an Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) emissivity dataset and compare the estimates with MODIS-derived water fractions. Our results show that the enhanced PMW product outperforms the coarser one when compared to flood mapped from optical data based on information content, indicating that it is possible to integrate such a product into the mapping of floods at a global scale on a daily basis.

flood detection↗
NASA NTRS1994

A passive microwave technique for estimating rainfall and vertical structure information from space. Part 1: Algorithm description

This paper describes a multichannel physical approach for retrieving rainfall and vertical structure information from satellite-based passive microwave observations. The algorithm makes use of statistical inversion techniques based upon theoretically calculated relations between rainfall rates and brightness temperatures. Potential errors introduced into the theoretical calculations by the unknown vertical distribution of hydrometeors are overcome by explicity accounting for diverse hydrometeor profiles. This is accomplished by allowing for a number of different vertical distributions in the theoretical brightness temperature calculations and requiring consistency between the observed and calculated brightness temperatures. This paper will focus primarily on the theoretical aspects of the retrieval algorithm, which includes a procedure used to account for inhomogeneities of the rainfall within the satellite field of view as well as a detailed description of the algorithm as it is applied over both ocean and land surfaces. The residual error between observed and calculated brightness temperatures is found to be an important quantity in assessing the uniqueness of the solution. It is further found that the residual error is a meaningful quantity that can be used to derive expected accuracies from this retrieval technique. Examples comparing the retrieved results as well as the detailed analysis of the algorithm performance under various circumstances are the subject of a companion paper.

Kummerow, Christian↗
NASA NTRS2012

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

Tan, Bin↗
NASA NTRS1993

Effects of vertical distribution of water vapor and temperature on total column water vapor retrieval error

Results are presented of a test of the physically based total column water vapor retrieval algorithm of Wentz (1992) for sensitivity to realistic vertical distributions of temperature and water vapor. The ECMWF monthly averaged temperature and humidity fields are used to simulate the spatial pattern of systematic retrieval error of total column water vapor due to this sensitivity. The estimated systematic error is within 0.1 g/sq cm over about 70 percent of the global ocean area; systematic errors greater than 0.3 g/sq cm are expected to exist only over a few well-defined regions, about 3 percent of the global oceans, assuming that the global mean value is unbiased.

Sun, Jielun↗
NASA NTRS1985

Pattern recognition in the satellite temperature retrieval problem

Pattern recognition procedures have been developed in order to improve the first-guess fields for satellite temperature retrievals. The first procedure is used to select one or more historical radiosonde temperature profiles as analog estimates of ambient thermal structure. The second procedure is used to organize a priori data into shape-coherent pattern libraries using structural information inherent in the data itself. On the basis of independent tests of about 800 temperature retrievals, it was found that: (1) the pattern recognition techniques reduced first-guess profile errors by nearly 50 percent in comparison with traditional partitioning schemes; and (2) with regression and physical-iterative retrieval algorithms, however, the effect of pattern recognition on temperature retrieval error was insignificant. Analysis of individual retrieval errors showed that poor retrievals may outweigh the potential benefits of both pattern recognition techniques.

Thompson, O. E.↗
NASA NTRS2002

Calibration and Data Retrieval Algorithms for the NASA Langley/Ames Diode Laser Hygrometer for the NASA Trace-P Mission

This paper describes the procedures and algorithms for the laboratory calibration and the field data retrieval of the NASA Langley / Ames Diode Laser Hygrometer as implemented during the NASA Trace-P mission during February to April 2000. The calibration is based on a NIST traceable dewpoint hygrometer using relatively high humidity and short pathlength. Two water lines of widely different strengths are used to increase the dynamic range of the instrument in the course of a flight. The laboratory results are incorporated into a numerical model of the second harmonic spectrum for each of the two spectral window regions using spectroscopic parameters from the HITRAN database and other sources, allowing water vapor retrieval at upper tropospheric and lower stratospheric temperatures and humidity levels. The data retrieval algorithm is simple, numerically stable, and accurate. A comparison with other water vapor instruments on board the NASA DC-8 and ER-2 aircraft is presented.

Podolske, James R.↗
NASA NTRS1993

Atmospheric moisture measurements - A microwave radiometer-radiosonde comparison

Measurements of the thermal emission of the sky at three frequencies (20.7, 22.2, and 31.4 GHz) with the NASA/Goddard Space Flight Center Crustal Dynamics Project MW Water Vapor Radiometer are reported. These measurements are compared with brightness temperatures inferred from measurements from VAISALA radiosonde packages launched every 3 hr during the experiment period. An error analysis for the radiosonde-inferred brightness temperatures is performed under the assumption of reasonable random uncertainties for the pressure, temperature, and humidity measurements and propagation of these uncertainties through the analysis algorithm. For the assumed uncertainties, the dominant contribution to the total uncertainty comes from the temperature measurement (66-88 percent), whereas the relative humidity measurement contributes only 2-8 percent, except in the vicinity of the water vapor line, where the contribution is 10-20 percent.

England, Martin N.↗