Global Moupfouma rain CDF prediction model

implementation of the Moupfouma-Martin rainfall rate CDF model, as per Electronic Letters paper Vol.29, No.17, Aug. 1993
Updated 14 Apr 2020

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%Function implementing the Global Moupfouma-Martin model,
%As per Electronic Letters paper "Point Rainfall rate cumulative
%distribution valid at various locations"
%F. Moupfouma and L. Martin, EL, Vol.29, No.17, Aug. 1993
%Rzz1: Rain rate value exceeded 0.01% of the time
%p : target probability, percentage. Scalar or vector
%Climzone: string: either 'tropical' or 'temperate'
%A coarse classification is used (Temperate, Tropical)
%Rgp : rainfall rate for target p values (scalar/vector)
%[R p] are a cumulative distribution function useful for telecom system
%ADDITIONAL OUTPUTS [in strict order]
%Pi : varargout{1}, reference P vector from P.311
%Ri : varargout{2}, rainfall rate in mm/hr corresponding to Pi
%Rg : varargout{3}, rainfall rate vector 2:0.25:400 use to compute the initial P(R) distribution
%Pg : varargout{4}, vector of probabilities of experiencing R>Rg, following the model's formulation
%Remarks : Rgp is interpolated from [Rg,Pg]
%Release date : Apr.14.2020. v 1.1.1
%Example of usage: Compute three values of rainfall rate, for 1%, 0.1% and 0.01%, for a site with R_0.01% = 110 mm/hr in a tropical location.
% [R]=Global_Moupfouma(110,[1 0.1 0.01],'tropical');
% R = 7.1236 39.6510 110.0000

Cite As

luis emiliani (2024). Global Moupfouma rain CDF prediction model (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2015a
Compatible with any release
Platform Compatibility
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Version Published Release Notes

Inputs include now a target p (scalar or vector).
Optional outputs include interpolated P(R) and original reference P(R)

description changes

Clarified usage of interpolated P/3011 results. Outputs now include raw data and interpolated data.
full call returns all P and R options,.

implementation issues: precende problem on Pg line and change of opeartor in the tropical part of u