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At least 145 records · Page 8

A satellite technique for quantitatively mapping rainfall rates over the oceans

A theoretical model for calculating microwave radiative transfer in raining atmospheres is developed. These calculations are compared with microwave brightness temperatures at a wavelength of 1.55 cm measured by the Electrically Scanning Microwave Radiometer (ESMR) on the Nimbus-5 satellite and rain rates derived from WSR-57 meteorological radar measurements. A specially designed ground-based verification experiment was also performed, wherein upward-viewing microwave brightness temperature measurements at wavelengths of 1.55 and 0.81 cm were compared with directly measured rain rates. It is shown that, over ocean areas, brightness temperature measurements from ESMR may be interpreted in terms of rain rate with about an accuracy of a factor of 2 over the range 1 to 25 mm/hr rain rate.

Wilheit, T. T.↗

Cumulative slant path rain attenuation associated with COMSTAR beacon at 28.56 GHz for Wallops Island, Virginia

Yearly, monthly, and time of day fade statistics are presented and characterized. A 19.04 GHz yearly fade distribution, corresponding to a second COMSTAR beacon frequency, is predicted using the concept of effective path length, disdrometer, and rain rate results. The yearly attenuation and rain rate distributions follow with good approximation log normal variations for most fade and rain rate levels. Attenuations were exceeded for the longest and shortest periods of times for all fades in August and February, respectively. The eight hour time period showing the maximum and minimum number of minutes over the year for which fades exceeded 12 db were approximately between 1600 to 2400, and 0400 to 1200 hours, respectively. In employing the predictive method for obtaining the 19.04 GHz fade distribution, it is demonstrated theoretically that the ratio of attenuations at two frequencies is minimally dependent of raindrop size distribution providing these frequencies are not widely separated.

Goldhirsh, J.↗

Effects of Nonuniform Beam Filling on Rainfall Retrieval for the TRMM Precipitation Radar

The Tropical Rainfall Measuring Mission (TRMM) will carry the first spaceborne radar for rainfall observation. Because the TRMM Precipitation Radar (PR) footprint size of 4.3 km is greater than the scale of some convective rainfall events, there is concern that nonuniform filling of the PR antenna beam may bias the retrieved rain-rate profile. The authors investigate this effect theoretically and then observationally using data from the NASA Jet Propulsion Laboratory Airborne Rain Mapping Radar (ARMAR), acquired during Tropical Oceans Global Atmosphere Coupled Ocean Atmosphere Response Experiment in early 1993. The authors' observational approach is to simulate TRMM PR data using the ARMAR data and compare the radar observables and retrieved rain rate from the simulated PR data with those corresponding to the high-resolution radar measurements. The authors find that the path-integrated attenuation and the resulting path-averaged rain rate are underestimated. The reflectivity and rain rate near the top of the rainfall column are overestimated. The near-surface reflectivity can be overestimated or underestimated, with a mean error very close to zero. The near-surface rain rate, however, is usually underestimated, sometimes severely.

Durden, Stephen L.↗

A TRMM Rainfall Estimation Method Applicable to Land Areas

Utilizing multi-spectral, dual-polarization Special Sensor Microwave Imager (SSM/I) radiometer measurements, we have developed in this study a method to retrieve average rain rate, R(sub f(sub R)), in a mesoscale grid box of 2deg x 3deg over land. The key parameter of this method is the fractional rain area, f(sub R), in that grid box, which is determined with the help of a threshold on the 85 GHz scattering depression 0 deduced from the SSM/I data. In order to demonstrate the usefulness of this method, nine-months of R(sub f(sub R))are retrieved from SSM/I data over three grid boxes in the Northeastern United States. These retrievals are then compared with the corresponding ground-truth-average rain rate, R(sub g), deduced from 15-minute rain gauges. Based on nine months of rain rate retrievals over three grid boxes, we find that R(sub f(sub R)can explain about 64 % of the variance contained in R(sub g). A similar evaluation of the grid-box-average rain rates R(sub GSCAT) and R(sub SRL), given by the NASA/GSCAT and NOAA/SRL rain retrieval algorithms, is performed. This evaluation reveals that R(sub GSCAT) and R(sub SRL) can explain only about 42 % of the variance contained in R(sub g). In our method, a threshold on the 85 GHz scattering depression is used primarily to determine the fractional rain area in a mesoscale grid box. Quantitative information pertaining to the 85 GHz scattering depression in the grid box is disregarded. In the NASA/GSCAT and NOAA/SRL methods on the other hand, this quantitative information is included. Based on the performance of all three methods, we infer that the magnitude of the scattering depression is a poor indicator of rain rate. Furthermore, from maps based on the observations made by SSM/I on land and ocean we find that there is a significant redundancy in the information content of the SSM/I multi-spectral observations. This leads us to infer that observations of SSM/I at 19 and 37 GHz add only marginal information to that given by 85 GHz scattering depression. As with other methods, the area-average rain retrieval method developed in this study needs tuning with radar and/or rain gauge observations. In the TRMM mission, the microwave radiometer rain retrieval algorithm can be tuned with TRMM radar observations. Since the radiometer has about 3.5 times wider spatial coverage compared to the radar in the TRMM mission, such an algorithm can be useful to extend geographically the rain information provided by the TRMM Precipitation Radar.

Prabhakara, C.↗

Communications Link Characterization Experiment (CLCE) technical data report, volume 2

The results are presented of the long term rain rate statistical analysis and the investigation of determining the worst month statistical from the measured attenuation data caused by precipitation. The rain rate statistics cover a period of 11 months from July of 1974 to May of 1975 for measurements taken at the NASA, Rosman station. The rain rate statistical analysis is a continuation of the analysis of the rain rate data accumulated for the ATS-6 Millimeter Wave Progation Experiment. The statistical characteristics of the rain rate data through December of 1974 is also presented for the above experiment.

Source record↗

TRMM Precipitation Radar and Microwave Imager Observations of Convective and Stratiform Rain and Their Theoretical Implications

Theoretical models of radiative transfer are developed to simulate the 85 GHz brightness temperature, T85, observed by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer as a function of rain rate. These simulations are performed separately over regions of convective and stratiform rain. For the purpose of constructing vertical profiles of hydrometeors in these regions, guidance is taken from TRMM Precipitation Radar (PR) observations, and from recent investigations of LDR and Z(sub DR) measurements made by land-based polarimetric radars. We find that for a given rain rate, the extinction in 85 GHz due to hydrometeors above the freezing level is relatively weak in convective regions compared to that in stratiform regions. The hydrometeor profile above the freezing level responsible for this weak extinction in convective regions is inferred, from LDR and Z(sub DR) observations and theoretical considerations, to contain two layers: 1) a layer of two km thickness with mixed phase particles, liquid drops and graupel, directly above the freezing level, and 2) a layer of graupel extending from the top of the mixed-phase layer to the cloud top. Strong extinction in the stratiform regions is inferred to result from slowly-falling, low-density ice aggregates (snow) above the freezing level. These theoretical results are consistent with T85 measured by TMI and the rain rate deduced from PR for convective and stratiform rain regions. On the basis of this study we infer that the accuracy of the rain rate sensed by TMI depends critically on the specification of the convective or stratiform nature of the rain.

Prabhakara, C.↗

Passive microwave remote sensing of rainfall with SSM/I: Algorithm development and implementation

A physically based algorithm sensitive to emission and scattering is used to estimate rainfall using the Special Sensor Microwave/Imager (SSM/I). The algorithm is derived from radiative transfer calculations through an atmospheric cloud model specifying vertical distributions of ice and liquid hydrometeors as a function of rain rate. The algorithm is structured in two parts: SSM/I brightness temperatures are screened to detect rainfall and are then used in rain-rate calculation. The screening process distinguishes between nonraining background conditions and emission and scattering associated with hydrometeors. Thermometric temperature and polarization thresholds determined from the radiative transfer calculations are used to detect rain, whereas the rain-rate calculation is based on a linear function fit to a linear combination of channels. Separate calculations for ocean and land account for different background conditions. The rain-rate calculation is constructed to respond to both emission and scattering, reduce extraneous atmospheric and surface effects, and to correct for beam filling. The resulting SSM/I rain-rate estimates are compared to three precipitation radars as well as to a dynamically simulated rainfall event. Global estimates from the SSM/I algorithm are also compared to continental and shipboard measurements over a 4-month period. The algorithm is found to accurately describe both localized instantaneous rainfall events and global monthly patterns over both land and ovean. Over land the 4-month mean difference between SSM/I and the Global Precipitation Climatology Center continental rain gauge database is less than 10%. Over the ocean, the mean difference between SSM/I and the Legates and Willmott global shipboard rain gauge climatology is less than 20%.

Ferriday, James G.↗

A simple rain attenuation model for earth-space radio links operating at 10-35 GHz

The simple attenuation model has been improved from an earlier version and now includes the effect of wave polarization. The model is for the prediction of rain attenuation statistics on earth-space communication links operating in the 10-35 GHz band. Simple calculations produce attenuation values as a function of average rain rate. These together with rain rate statistics (either measured or predicted) can be used to predict annual rain attenuation statistics. In this paper model predictions are compared to measured data from a data base of 62 experiments performed in the U.S., Europe, and Japan. Comparisons are also made to predictions from other models.

Stutzman, W. L.↗

The Effect of Rain on Air-Water Gas Exchange

The relationship between gas transfer velocity and rain rate was investigated at NASA's Rain-Sea Interaction Facility (RSIF) using several SF, evasion experiments. During each experiment, a water tank below the rain simulator was supersaturated with SF6, a synthetic gas, and the gas transfer velocities were calculated from the measured decrease in SF6 concentration with time. The results from experiments with IS different rain rates (7 to 10 mm/h) and 1 of 2 drop sizes (2.8 or 4.2 mm diameter) confirm a significant and systematic enhancement of air-water gas exchange by rainfall. The gas transfer velocities derived from our experiment were related to the kinetic energy flux calculated from the rain rate and drop size. The relationship obtained for mono-dropsize rain at the RSIF was extrapolated to natural rain using the kinetic energy flux of natural rain calculated from the Marshall-Palmer raindrop size distribution. Results of laboratory experiments at RSIF were compared to field observations made during a tropical rainstorm in Miami, Florida and show good agreement between laboratory and field data.

Ho, David T.↗

The beam filling error in the Nimbus 5 electronically scanning microwave radiometer observations of Global Atlantic Tropical Experiment rainfall

A comparison of rain rates retrieved from the Nimbus 5 electronically scanning microwave radiometer brightness temperatures and observed from shipboard radars during the Global Atlantic Tropical Experiment (GATE) phase I shows that the beam filling error is the major source of discrepancy between the two. When averaged over a large scene (the GATE radar array, 400 km in diameter), the beam filling error is quite stable, being 50 percent of the observed rain rate. This suggests the simple procedure of multiplying retrieved rain rates by 2 (correction factor). A statistical model of the beam filling error is developed by envisioning an idealized instrument field-of-view that encompasses an entire gamma distribution of rain rates. A modeled correction factor near 2 is found for rain rate and temperature characteristics consistent with GATE conditions. The statistical model also suggests that the correction factor varies from 1.5 to 2.5 for suppressed to enhanced tropical convective regimes, and decreases to 1.5 as the freezing level and average depth of the rain column decreases to 2.5 km.

Short, David A.↗

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part II: Evaluation of Estimates Using Independent Data

Rainfall rate estimates from spaceborne microwave radiometers are generally accepted as reliable by a majority of the atmospheric science community. One of the Tropical Rainfall Measuring Mission (TRMM) facility rain-rate algorithms is based upon passive microwave observations from the TRMM Microwave Imager (TMI). In Part I of this series, improvements of the TMI algorithm that are required to introduce latent heating as an additional algorithm product are described. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, 0.5 deg. -resolution estimates of surface rain rate over ocean from the improved TMI algorithm are well correlated with independent radar estimates (r approx. 0.88 over the Tropics), but bias reduction is the most significant improvement over earlier algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly 2.5 -resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data is limited, TMI-estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain-rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with (a) additional contextual information brought to the estimation problem and/or (b) physically consistent and representative databases supporting the algorithm. A model of the random error in instantaneous 0.5 deg. -resolution rain-rate estimates appears to be consistent with the levels of error determined from TMI comparisons with collocated radar. Error model modifications for nonraining situations will be required, however. Sampling error represents only a portion of the total error in monthly 2.5 -resolution TMI estimates; the remaining error is attributed to random and systematic algorithm errors arising from the physical inconsistency and/or nonrepresentativeness of cloud-resolving-model-simulated profiles that support the algorithm.

Yang, Song↗

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Evaluation of Estimates Using Independent Data - Part 2

Rainfall rate estimates from space-borne k&ents are generally accepted as reliable by a majority of the atmospheric science commu&y. One-of the Tropical Rainfall Measuring Mission (TRh4M) facility rain rate algorithms is based upon passive microwave observations fiom the TRMM Microwave Imager (TMI). Part I of this study describes improvements in the TMI algorithm that are required to introduce cloud latent heating and drying as additional algorithm products. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, OP5resolution estimates of surface rain rate over ocean fiom the improved TMI algorithm are well correlated with independent radar estimates (r approx. 0.88 over the Tropics), but bias reduction is the most significant improvement over forerunning algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm, and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly, 2.5 deg. -resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data are limited, TMI estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with: (a) additional contextual information brought to the estimation problem, and/or; (b) physically-consistent and representative databases supporting the algorithm. A model of the random error in instantaneous, 0.5 deg-resolution rain rate estimates appears to be consistent with the levels of error determined from TMI comparisons to collocated radar. Error model modifications for non-raining situations will be required, however. Sampling error appears to represent only a fraction of the total error in monthly, 2S0-resolution TMI estimates; the remaining error is attributed to physical inconsistency or non-representativeness of cloud-resolving model simulated profiles supporting the algorithm.

Yang, Song↗

Oceanic rain retrievals from satellite passive 37 GHz scattering measurements

A technique for estimating the effect of scattering on the average brightness temperature, T(B), is examined. This scattering method is based on the relation observed over land between the SMMR T(B) and radar-derived rain rate. The scattering algorithm was evaluated and a comparison of radar and SMMR images reveals a correlation between radar-reflectivity-derived rates and the SMMR rain rates. The limitations of the scattering technique are discussed. Graphs and images displaying the application of the scattering algorithm are presented.

Spencer, Roy W.↗

A satellite infrared technique to estimate tropical convective and stratiform rainfall

A new method of estimating both convective and stratiform precipitation from satellite infrared data is described. This technique defines convective cores and assigns rain rate and rain area to these features based on the infrared brightness temperature and the cloud model approach of Adler and Mack (1984). The method was tested for four south Florida cases during the second Florida Area Cumulus Experiment, and the results are presented and compared with three other satellite rain estimation schemes.

Adler, Robert F.↗

Passive microwave retrievals of rainfall and rain system structure

Consideration is given to the development of algorithms for the Tropical Rainfall Measuring Mission to retrieve rain and rain vertical structure from passive microwave radiometry. The self-consistency approach for surface rain rate retrieval of Kummerow et al. (1989) is applied to microwave brightness temperature data from the Cooperative Huntsville Meteorological Experiment (Dodge et al., 1986). Because the algorithm simultaneously retrieves rainfall rate and rain system structure, it is suggested that the algorithm can be used to overcome the problem of the dependence of brightness temperatures on the vertical profile of hydrometeors.

Kummerow, Christian↗

Nested rain cell contour statistics derived from radar measurements in the mid-Atlantic coast of the United States

During a period spanning more than 5 years, a series of low elevation rain radar measurements encompassing 17 rain days were systematically executed in the mid-Atlantic coast of the United States. Drop size distribution measurements with a nearby disdrometer were also acquired during 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 developed algorithms to the radar and disdrometer data, 'core' values of rain intensities and nested families of rain rate isopleths enveloping them were identified and their equi-circle diameters were statistically analyzed.

Goldhirsh, Julius↗

Assistant for Analyzing Tropical-Rain-Mapping Radar Data

A document is defined that describes an approach for a Tropical Rain Mapping Radar Data System (TDS). TDS is composed of software and hardware elements incorporating a two-frequency spaceborne radar system for measuring tropical precipitation. The TDS would be used primarily in generating data products for scientific investigations. The most novel part of the TDS would be expert-system software to aid in the selection of algorithms for converting raw radar-return data into such primary observables as rain rate, path-integrated rain rate, and surface backscatter. The expert-system approach would address the issue that selection of algorithms for processing the data requires a significant amount of preprocessing, non-intuitive reasoning, and heuristic application, making it infeasible, in many cases, to select the proper algorithm in real time. In the TDS, tentative selections would be made to enable conversions in real time. The expert system would remove straightforwardly convertible data from further consideration, and would examine ambiguous data, performing analysis in depth to determine which algorithms to select. Conversions performed by these algorithms, presumed to be correct, would be compared with the corresponding real-time conversions. Incorrect real-time conversions would be updated using the correct conversions.

James, Mark↗

Regional Variability in Convection and Rain Retrievals from the TRMM Microwave Imager (TMI)

Precipitation Radar (PR) on board the TRMM satellite shows that the average height of 30 dBz in convective rain areas of the tropics varies significantly from one region to the other. When the convection is weak this height is shallow and when convection is strong this height extends deeper into the troposphere. The brightness temperature (Tb) measured by the microwave radiometer by itself does not reflect this nature of convection satisfactorily. Radiative transfer simulations of Tbs reveal that this could be due to the variations in the vertical distribution of optically active water and ice hydrometeors and their density, shape, and size. These variations are not coupled uniquely to the strength of the convective updrafts, and as a result the Tbs do not reflect properly the convective strength indicated by PR. Because of this deficiency in the Tbs the rain rate deduced from them differs from that of PR. For this reason, to improve the estimation of rain rate we have developed an empirical method. In this method a parameter based on the areal extent of the Tbs that exceed a certain magnitude is included along with the Tbs. Rain rate deduced with this approach is better correlated with that of PR when compared to the current Version 5 operational algorithm. The percentage of rain volume as a function of rain rate, for a given region of 5deg lat. X 5deg long. over a period of three months, deduced from this method, is also in better agreement with that of the PR.

Prabhakara, C.↗