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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Rain rate measurement capabilities using a Seasat type radar altimeter

The combined use of a space-based radar and a radiometer for measurement of precipitation is discussed. Phenomena to exploit or overcome is surveyed. Basic measurement problems are discussed. Several active systems are proposed, including three ocean systems and two land-sea systems. Recommendations for future research are given.

Goldhirsh, J.↗
NASA NTRS1983

Satellite microwave radiances correlated with radar rain rates over land

The characteristics of upwelling microwave radiation from raindrops as measured by satellite sensors are examined. The scanning multichannel microwave radiometers on board the Nimbus 7 and Seasat satellites have the capability of quantifying the perpendicularly polarized antenna temperatures at 37, 21, 18, 10.7, and 6.6 GHz. The instruments scan the earth at a constant 50 deg angle to the surface with a footprint that varies from 20-70 km. Radar rainfall measurements have an accuracy of within 60 percent, whereas a series of test measurements using SMMR data in comparison with radar data for rainfall in the same areas showed that the microwave data depicted rainfall rates with less than 1.55 mm/h error. Details of the rainfall rate algorithms used to treat the satellite microwave data are provided, noting that the identification of rainfall rates is dependent on quantifying the amount the upwelling radiance is reduced due to rainfall.

Spencer, R. W.↗
NASA NTRS2004

Application of SeaWinds Scatterometer and TMI-SSM/I Rain Rates to Hurricane Analysis and Forecasting

Results provided by two different assimilation methodologies involving data from passive and active space-borne microwave instruments are presented. The impact of the precipitation estimates produced by the TRMM Microwave Imager (TMI) and Special Sensor Microwave/Imager (SSM/I) in a previously developed 1D variational continuous assimilation algorithm for assimilating tropical rainfall is shown on two hurricane cases. Results on the impact of the SeaWinds scatterometer on the intensity and track forecast of a mid-Atlantic hurricane are also presented. This work is the outcome of a collaborative effort between NASA and NOAA and indicates the substantial improvement in tropical cyclone forecasting that can result from the assimilation of space-based data in global atmospheric models.

Atlas, Robert↗
NASA NTRS1989

The ground truth analysis of rain gauge data for the TRMM project

As a part of the Tropical Rainfall Measuring Missioin (TRMM) ground truth program to determine the diurnal variability of the area wide rain rates, the rain rate PDFs, and their effect on the area integral algorithm, rain rate data have been collected from a network of gages located in the area near the Cape Canaveral and Kennedy Space Center, in the period beginning in September 1987. In the preliminary statistical analysis, based on the rain rates derived from the eleven gages, the seasonal diurnal rainfall and network averaged rain rates are determined. The analysis was performed in two steps: determination of the hourly and daily rain accumulations and rain rates; and computation of the fraction of hourly and daily rain rates that exceed a particular threshold, and analysis of the hourly and daily rain rate PDFs for the network. The results indicate that there are diurnal and seasonal variations in the components which determine the network rain rate PDFs.

Kowalewsky, Karen J.↗
NASA NTRS2006

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Improved Method and Uncertainties - Part 1

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5 -resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%-80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5deg resolution is relatively small (less than 6% at 5 mm day.1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%-35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%-15% at 5 mm day.1, with proportionate reductions in latent heating sampling errors.

Olson, William S.↗
NASA NTRS2004

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Method and Uncertainties - Part 1

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).

Olson, William S.↗
NASA NTRS1989

Rain attenuation measurements: Variability and data quality assessment

Year to year variations in the cumulative distributions of rain rate or rain attenuation are evident in any of the published measurements for a single propagation path that span a period of several years of observation. These variations must be described by models for the prediction of rain attenuation statistics. Now that a large measurement data base has been assembled by the International Radio Consultative Committee, the information needed to assess variability is available. On the basis of 252 sample cumulative distribution functions for the occurrence of attenuation by rain, the expected year to year variation in attenuation at a fixed probability level in the 0.1 to 0.001 percent of a year range is estimated to be 27 percent. The expected deviation from an attenuation model prediction for a single year of observations is estimated to exceed 33 percent when any of the available global rain climate model are employed to estimate the rain rate statistics. The probability distribution for the variation in attenuation or rain rate at a fixed fraction of a year is lognormal. The lognormal behavior of the variate was used to compile the statistics for variability.

Crane, Robert K.↗
NASA NTRS1989

Rain core structure statistics derived from radar and disdrometer measurements in the mid-Atlantic coast of the US

During a period spanning more than 5 years, low elevation radar measurements of rain were systematically obtained in the mid-Atlantic coast of the U.S. Drop size distribution measurements with a disdrometer were also acquired on the same rain days. The drop size data were utilized to convert the radar reflectivity factors to estimated rain rates for the respective rain days of operation. Applying high level algorithms to the rain data, core values of rain intensities were identified (peak rain rates), and families of rain rate isopleths analyzed. In particular, equicircle diameters of the family of isopleths enveloping peak rain intensities were statistically characterized. The presented results represents the analysis of two rain days, 12 radar scans, corresponding to 430 culled rain rate isopleths from an available data base of 22,000 contours, approximately 100 scans encompassing 17 rain days. The results presented show trends of the average rain rate vs. contour scale dimensions, and cumulative distributions of rain cell dimensions which belong to core families of precipitation.

Goldhirsh, Julius↗
DOE OSTI2022

How Much Attenuation Extinguishes mm-Wave Vertically Pointing Radar Return Signals?

Vertically pointing radars (VPRs) operating at millimeter wavelengths measure the power return from raindrops enabling precipitation retrievals as a function of height. However, as the rain rate increases, there are combinations of rain rate and rain path length that produce sufficient attenuation to prevent the radar from detecting raindrops all the way through rain shafts. This study explores the question: Which rain rate and path length combinations completely extinguish radar return signals for VPRs operating between 3 and 200 GHz? An important step in these simulations is converting attenuated radar reflectivity factor into radar received signal-to-noise ratio (SNR) in order to determine the range where the SNR drops below the receiver detection threshold. Configuring the simulations to mimic a U.S. Department of Energy Atmospheric Radiation Mission (ARM) W-band (95 GHz) radar deployed in Brazil, the simulation results indicate that a W-band radar could observe raindrops above 3.5 km only when the rain rate was less than approximately 4 mm h -1 . The deployed W-band radar measurements confirm the simulation results with maximum observed heights ranging between 3 and 4.5 km when a surface disdrometer measured 4 mm h -1 rain rate (based on 25-to-75 percentiles from over 25,000 W-band radar profiles). In summary, this study contributes to our understanding of how rain and atmospheric gas attenuation impacts the performance of millimeter-wave VPRs and will help with the design and configuration of multi-frequency VPRs deployed in future field campaigns.

54 ENVIRONMENTAL SCIENCES↗