Global Moupfouma rain CDF prediction model
%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
%
%Inputs
%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)
%OUTPUTS
%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 (https://www.mathworks.com/matlabcentral/fileexchange/20254-global-moupfouma-rain-cdf-prediction-model), MATLAB Central File Exchange. Retrieved .
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Version | Published | Release Notes | |
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1.1.1 | Inputs include now a target p (scalar or vector).
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1.1.0.1 | description changes |
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1.1.0.0 | Clarified usage of interpolated P/3011 results. Outputs now include raw data and interpolated data.
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1.0.0.0 | implementation issues: precende problem on Pg line and change of opeartor in the tropical part of u |