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Overview %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%

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Présentation au sujet: "Overview %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%"— Transcription de la présentation:

1 Overview %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%%%%%% %%%%%%%

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4 %nakedsoftware.org opensource license, copyright 2010 stephane.poirier@oifii.org % %developed by Stephane Poirier, M.Sc. Optical Physics, Remote Sensing Application Software Developer (1991-2010) % %this function is part of oifii.org's ar\sp\ Microwave- derived 30-year Canada-Alaska Daily Temperature and Snowcover Databases library % %this function is part of oifii.org's ar\sp\'this folder' application (lauched with ar\sp\'this file'.m) %oifii.org's ar\sp\affiche_carte application is part of the oifii.org's ar\sp set of applications which %may also contain similar variant versions of this function with identical filename. % %A geophysical research paper about this work has been submitted in June 2009 for publication in JGR-Atmosphere %Royer, A. and Poirier S., Surface temperature spatial and temporal variations in North America from homogenized %satellite SMMR-SSM/I microwave measurements and reanalysis for 1979-2008, Journal of Geophysical Research - Atmosphere, %Submitted June 2009, http://www.oifii.org/tsatdb/Royer- Poirier_Microwave-derived-daily-surface- temperature_JGR2009JD012760_R2.pdf % %This study's database can be downloaded from the author web site at: %http://www.oifii.org/tsatdb/Royer-Poirier_Microwave-derived- daily-surface-temperature-db_1979-2008.zip % %this function is used to display the raw microwave raster data (NSIDC's SMMR and SSMI satellite, ref. nsidc.org) % %usage: % 20yymmmdd % %version 0.0, 20yymmmdd, spi, initial function draft % %nakedsoftware.org opensource license, copyright 2010 stephane.poirier@oifii.org

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7 function [r,err,p95,p99]=corr_montec(X,Y) % Function [r,err,p95,p99]=corr_montec(X,Y) % Renvoie la correlation 'r' entre 2 series X et Y, et la probabilité 'err' % que cette correlation ne soit pas significative, en tenant compte % de l'autocorrélation de rang 1 dans chacune des 2 séries % (test de Monte-Carlo avec génération de séries xx et yy de meme % autocorrélation que X et Y). % 'r95' et 'r99' renvoient également les seuils de signification à 95 et 99% % % N.F. % modifié P.C. 27/09/05 % % http://www.u- bourgogne.fr/climatologie/data/Matlab/corr_montec.m r=corrcoef([X Y]); r=r(1,2); autocor=corrcoef([X(1:(length(X)-1)) X(2:length(X))]); autocorx=autocor(2,1); autocor=corrcoef([Y(1:(length(Y)-1)) Y(2:length(Y))]); autocory=autocor(2,1); an=length(X); mm=200; xx=zeros(an,mm); xx(1,:)=randn(1,mm); yy=zeros(an,mm); yy(1,:)=randn(1,mm); for i=2:an; xx(i,:)=autocorx*xx(i-1,:)+(1-autocorx)*randn(1,mm); yy(i,:)=autocory*yy(i-1,:)+(1-autocory)*randn(1,mm); end; rr=corrcoef([xx yy]); rr=rr(1:mm,mm+1:mm*2); rr=reshape(rr,mm*mm,1); %clf; hist(rr) i=find(abs(rr)>abs(r)); err=length(i)/(mm*mm); p95=prctile(abs(rr),95); p99=prctile(abs(rr),99);


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