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Journal ArticleDOI

Climatologically tuned reflectivity-rain rate relations and links to area-time integrals

TLDR
In this article, an effort is made to determine relationships between reflectivity (Z) and rain rate (R) which are tuned to the local climatology, where the relation is tuned so that the probability distribution of reflectivity, P(Z), replicates that of R over some predetermined space-time climatic domain.
Abstract
An effort is made to determine relationships between reflectivity (Z) and rain rate (R) which are tuned to the local climatology. The development of such relations was motivated by the need to understand the role of precipitation in controlling general circulation and in affecting such phenomena as ENSO. Attention is given to methods of deriving such relations and how they are linked to area integral rainfall measurements. In essence, the relation is tuned so that the probability distribution of reflectivity, P(Z), replicates that of R over some predetermined space-time climatic domain. Thus, the accurate measurement of the average R over any smaller domain depends on how closely the sampled P(Z) approximates the climatic P(Z). The probability matching method used is a modification of the approach of Calheiros and Zawadzki (1987) and Rosenfeld (1980). The technique is applied to data from Germany and the eastern tropical Atlantic (GATE).

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Precipitation Estimation from Remotely Sensed Imagery Using an Artificial Neural Network Cloud Classification System

TL;DR: In this article, a satellite-based rainfall estimation algorithm, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Cloud Classification System (CCS), is described.
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Evidence from Tropical Raindrop Spectra of the Origin of Rain from Stratiform versus Convective Clouds

TL;DR: In this article, an empirical stratiform-convective classification method based on N 0 and R (rainfall rate) is presented. But, the occurrence of precipitation was found to be 74% (stratiform) and 26% (convection) but total rainfall, on the other hand, was...
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Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

TL;DR: In this article, the retrieval characteristics of passive (AMSR-E) and active (ASCAT) microwave satellite estimates are combined to produce an improved soil moisture product. But the results of the satellite-based passive and active microwave sensors have the potential to offer improved estimates of surface soil moisture at global scale.
Journal ArticleDOI

Bias reduction in short records of satellite soil moisture

TL;DR: In this paper, the cumulative distribution functions (cdf) of the satellite and model data are matched to obtain local statistics based on a one-year satellite record that are a good approximation to those that would be derived from a much longer time series.
Journal ArticleDOI

Cloud Microphysical Properties, Processes, and Rainfall Estimation Opportunities

TL;DR: In this paper, the relationship between raindrop-size distributions and radar reflectivity-rainfall rate (Z-R) relationships is revisited, this time from the combined approach of rain-forming physical processes that shape the RDSD, and a formulation of the RDP into the simplest free parameters of the rain intensity R, rainwater content W, and median volume drop diameter D0.
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