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13
Atmospheric latent heating distributions in the Tropics derived from satellite passive microwave radiometer measurements
- J. Appl. Meteor
, 1999
"... A method for the remote sensing of three-dimensional latent heating distributions in precipitating tropical weather systems from satellite passive microwave observations is presented. In this method, cloud model sim-ulated hydrometeor/latent heating vertical profiles that have radiative characterist ..."
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A method for the remote sensing of three-dimensional latent heating distributions in precipitating tropical weather systems from satellite passive microwave observations is presented. In this method, cloud model sim-ulated hydrometeor/latent heating vertical profiles that have radiative characteristics consistent with a given set of multispectral microwave radiometric observations are composited to create a best estimate of the observed profile. An estimate of the areal coverage of convective precipitation within the radiometer footprint is used as an additional constraint on the contributing model profiles. This constraint leads to more definitive retrieved profiles of precipitation and latent heating in synthetic data tests. The remote sensing method is applied to Special Sensor Microwave/Imager (SSM/I) observations of tropical systems that occurred during the TOGA COARE Intensive Observing Period, and to observations of Hurricane Andrew (1992). Although instantaneous estimates of rain rates are high-biased with respect to coincident radar rain estimates, precipitation patterns are reasonably correlated with radar patterns, and composite rain rate and latent heating profiles show respectable agreement with estimates from forecast models and heat and moisture budget calculations. Uncertainties in the remote sensing estimates of precipitation/latent heating may be partly attributed to the relatively low spatial resolution of the SSM/I and a lack of microwave sensitivity to tenuous
a: Physical and Microwave Radiative Properties of Precipitating Clouds. Part II: A Parametric ID Rain-Cloud Model for Use in Microwave Radiative Transfer Simulations
- J. Appl. Met
, 2001
"... ABSTRACT Using stringent criteria pertaining to rain-cloud optical thickness and horizontal extent, 3203 multichannel microwave observations of heavy, widespread tropical precipitation over ocean were selected from 9 months of global Special Sensor Microwave Imager (SSM/I) data. These observations ..."
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Cited by 8 (0 self)
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ABSTRACT Using stringent criteria pertaining to rain-cloud optical thickness and horizontal extent, 3203 multichannel microwave observations of heavy, widespread tropical precipitation over ocean were selected from 9 months of global Special Sensor Microwave Imager (SSM/I) data. These observations subsequently were found to be associated almost exclusively with stratiform rain areas in tropical cyclones. Because of the restrictions on optical thickness and spatial extent, the mean multichannel microwave brightness temperatures and their interchannel covariances are presumed to be determined primarily by the vertical microphysical structure of the rain clouds. The distribution of the above observations in seven-dimensional channel space is characterized concisely using principal component analysis. It is found that only three independent variables are sufficient to explain 97% of the variance in the correlation matrix. This result suggests that the radiometrically important microphysical properties of these rain clouds are strongly interdependent. The most significant eigenvector of the observation correlation matrix corresponds to variable scattering at high frequencies by ice aloft. Its spectral dependence is accurately given by 1.76 , where is the microwave frequency. This empirical result constrains the effective mean sizes of ice particles responsible for observed passive microwave scattering in rain clouds and provides a plausible empirical basis for accurately predicting the magnitude of scattering effects by ice at non-SSM/I microwave frequencies. There are also qualitative indications that this mode of brightness temperature variability is poorly correlated with surface rain rate in this study sample. The empirical results presented herein are expected to be of value for the validation and improvement of microphysical assumptions and optical parameterizations in forward microwave radiative transfer models. Companion papers describe the actual retrieval of effective rain-cloud microphysical properties from the observed multichannel radiances.
Passive microwave remote sensing of extreme weather events using NOAA-18 AMSUA and MHS
- IEEE Transactions on Geoscience and Remote Sensing
, 2007
"... Abstract—The ability to provide temperature and water-vapor soundings under extreme weather conditions, such as hurricanes, could extend the coverage of space-based measurements to critical areas and provide information that could enhance outcomes of numerical weather prediction (NWP) models and oth ..."
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Cited by 4 (0 self)
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Abstract—The ability to provide temperature and water-vapor soundings under extreme weather conditions, such as hurricanes, could extend the coverage of space-based measurements to critical areas and provide information that could enhance outcomes of numerical weather prediction (NWP) models and other storm-track forecasting models, which, in turn, could have vital societal benefits. An NWP-independent 1D-VAR system has been devel-oped to carry out the simultaneous restitutions of atmospheric constituents and surface parameters in all weather conditions. This consistent treatment of all components that have an impact on the measurements allows an optimal information-content extrac-tion. This study focuses on the data from the NOAA-18 satellite (AMSUA and MHS sounders). The retrieval of the precipitating and nonprecipitating cloud parameters is done in a profile form, taking advantage of the natural correlations that do exist between the different parameters and across the vertical layers. Stability and the problem’s ill-posed nature are the two classical issues facing this type of retrieval. The use of empirically orthogonal-function decomposition leads to a dramatic stabilization of the problem. The main goal of this inversion system is to be able to retrieve independently, with a high-enough accuracy and under all conditions, the temperature and water-vapor profiles, which are still the two main prognostic variables in numerical weather forecast models. Validation of these parameters in different con-ditions is undertaken in this paper by comparing the case-by-case retrievals with GPS-dropsondes data and NWP analyses in and around a hurricane. High temporal and spatial variabilities of the atmosphere are shown to present a challenge to any attempt to val-idate the microwave remote-sensing retrievals in meteorologically active areas. Index Terms—Atmospheric sounding, data assimilation, drop-sonde, hurricane, microwave remote sensing, retrieval algorithm. I.
Quantifying global uncertainties in a simple microwave rainfall algorithm
- J. Atmos. Oceanic Technol
, 2006
"... 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 uncer-tainties in these rainfall products at various time and space scales. The latter is the resu ..."
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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 uncer-tainties 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. 1.
Observation and Interpretation of Microwave Cloud Signatures over the Arctic Ocean during Winter
, 2001
"... An analysis of satellite microwave brightness temperatures at 85 GHz (37 GHz) shows that these temperatures sometimes vary by more than 30 K (15 K) within 1 or 2 days at a single location over Arctic sea ice. This variation can be seen in horizontal brightness temperature distributions with spatial ..."
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An analysis of satellite microwave brightness temperatures at 85 GHz (37 GHz) shows that these temperatures sometimes vary by more than 30 K (15 K) within 1 or 2 days at a single location over Arctic sea ice. This variation can be seen in horizontal brightness temperature distributions with spatial scales of hundreds of kilometers, as well as in brightness temperature time series observed at a single location. Analysis of satellite observations during winter shows that such brightness temperature warming frequently occurs in the Arctic Ocean, particularly in regions over which low pressure systems often pass. By comparing the observed microwave brightness temperature warming with ground-based measurements of geophysical variables collected during the Surface Heat Budget of the Arctic (SHEBA) experiment and with numerical prediction model analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF), it is found that brightness temperature anomalies are significantly correlated with clouds and precipitation. This finding raises the possibility of using satellite microwave data to estimate cloud liquid water path and precipitation in the Arctic. Factors contributing to the brightness temperature warming were examined, and it was found that the primary contributors to the observed warming were cloud liquid water and surface temperature change. 1.
CORRECTING FOR PRECIPITATION EFFECTS IN SATELLITE-BASED PASSIVE MICROWAVE TROPICAL CYCLONE INTENSITY ESTIMATES
, 2005
"... Public reporting burden for this collection of Information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments ..."
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Public reporting burden for this collection of Information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this
CORRECTING FOR PRECIPITATION EFFECTS IN SATELLITE-BASED PASSIVE MICROWAVE TROPICAL CYCLONE INTENSITY ESTIMATES
, 2005
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HARRIS AND FOUFOULA-GEORGIOU: CLOUD MODEL DOWNSCALING
"... Subgrid variability and stochastic downscaling of modeled clouds: Effects on radiative transfer computations for rainfall retrieval ..."
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Subgrid variability and stochastic downscaling of modeled clouds: Effects on radiative transfer computations for rainfall retrieval
Product PR-OBS-1 Precipitation rate at ground by MW conical scanners INDEX
, 2011
"... Algorithm Theoretical Baseline Document (ATBD) for product H01 – PR‐OBS‐1 Precipitation rate at ground by MW conical scanners Version: 1.1 ..."
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Algorithm Theoretical Baseline Document (ATBD) for product H01 – PR‐OBS‐1 Precipitation rate at ground by MW conical scanners Version: 1.1
