Homework 0

Part I: Due Thursday (Jan 24).

(a)

(b)

(c)

(d)

(e)

FIG. 1: In order to see how well each of 12 individual CMIP5 long-term current-climate "historical" global model simulations capture the precipitation spatial patterns over Florida, for the years 1901-2005, using the GPCC v5 observational precipitation (rain-gauge-based) data set as reference, two-dimensional scatter plots are created, for the region of Florida, of the two-dimensional spatial correlation coefficient versus the two-dimensional spatial centered root-mean-square (RMS) difference, in units of mm / day, plotted for each model, for each of the four seasons, and for the entire year. In addition, the 1961-2005 CanCM4, 1948-2006 NOAA CPC v1, 1998-2009 TRMM 3B42 v6, and the 1901-2005 mean of the CMIP5 models are also plotted.

plot_CMIP5_GPCC_sea_rain_1901_2005_CorrCoef_vs_RMScDiff_MPO524.m

• Details
• Download
• 5 KB

clear;
 
mod_var_names={'CCSM4';'CNRM_CM5';'GFDL_CM3';'GISS_E2_H';'GISS_E2_R';'HadCM3';'HadGEM2_CC';...
'HadGEM2_ES';'IPSL_CM5B_LR';'MPI_ESM_P';'NorESM1_M';'NorESM1_ME'};
 
CMIP5_pr_map=zeros(15,4,360,720);
 
for mod=1:12
    CMIP5_pr_map(mod,:,:,:)=importdata([char(mod_var_names(mod,1)),'_h_1901_2005_sea_maps_reg.mat']);
end
CMIP5_pr_map(13,:,:,:)=importdata('CanCM4_h_1961_2005_sea_maps_reg.mat');
CMIP5_pr_map(14,:,:,:)=importdata('CPC_1948_2006_sea_maps_reg.mat');
CMIP5_pr_map(15,:,:,:)=importdata('f3B42_1998_2009_sea_maps_reg.mat');
 
CMIP5_pr_map=CMIP5_pr_map(:,:,119:125,185:200);
 
CMIP5_pr_map2=zeros(15,5,7,16);
CMIP5_pr_map2(:,1:4,:,:)=CMIP5_pr_map;
CMIP5_pr_map2(:,5,:,:)=nanmean(CMIP5_pr_map,2);
CMIP5_pr_map=CMIP5_pr_map2;
 
CMIP5_pr_map2=zeros(16,5,7,16);
CMIP5_pr_map2(1:15,:,:,:)=CMIP5_pr_map;
CMIP5_pr_map2(16,:,:,:)=nanmean(CMIP5_pr_map(1:12,:,:,:),1);
CMIP5_pr_map=CMIP5_pr_map2;
 
clear CMIP5_pr_map2;
 
load GPCC_FL_LSmask.mat;
for mod=1:16
    for sea=1:5
        CMIP5_pr_map(mod,sea,:,:)=squeeze(CMIP5_pr_map(mod,sea,:,:)).*FL_mask;
    end
end
 
GPCC_pr_map=importdata('GPCC_1901_2005_sea_maps.mat');
GPCC_pr_map=GPCC_pr_map(:,119:125,185:200);
GPCC_pr_map2=zeros(5,7,16);
GPCC_pr_map2(1:4,:,:)=GPCC_pr_map;
GPCC_pr_map2(5,:,:)=nanmean(GPCC_pr_map,1);
GPCC_pr_map=GPCC_pr_map2;
clear GPCC_pr_map2;
 
for sea=1:5
    GPCC_pr_map(sea,:,:)=squeeze(GPCC_pr_map(sea,:,:)).*FL_mask;
end
 
CMIP5_pr_map_c=zeros(16,5,7,16);
for mod=1:16
    for sea=1:5
        gmean=squeeze(nanmean(nanmean(CMIP5_pr_map(mod,sea,:,:))));
        CMIP5_pr_map_c(mod,sea,:,:)=squeeze(CMIP5_pr_map(mod,sea,:,:)) - gmean;
    end
end
 
GPCC_pr_map_c=zeros(5,7,16);
for sea=1:5
    gmean=squeeze(nanmean(nanmean(GPCC_pr_map(sea,:,:))));
    GPCC_pr_map_c(sea,:,:)=squeeze(GPCC_pr_map(sea,:,:)) - gmean;
end
 
cdiff=zeros(16,5,7,16);
for mod=1:16
    cdiff(mod,:,:,:)=squeeze(CMIP5_pr_map_c(mod,:,:,:)) - GPCC_pr_map_c;
end
 
cdiffcdiff=cdiff.*cdiff;
 
RMScdiff=squeeze(sqrt(nanmean(nanmean(cdiffcdiff,4),3)));
 
CMIP5_GPCC_corr=zeros(16,5);
for sea=1:5
    GPCC_vect=reshape(squeeze(GPCC_pr_map(sea,:,:)).',7*16,1);
    ind=isnan(GPCC_vect);
    GPCC_vect(ind)=[];
    for mod=1:16
        CMIP5_vect=reshape(squeeze(CMIP5_pr_map(mod,sea,:,:)).',7*16,1);
        CMIP5_vect(ind)=[];
 
        CMIP5_GPCC_corr(mod,sea)=corr2(CMIP5_vect,GPCC_vect);
 
        if mod==14
            CMIP5_vect2=CMIP5_vect;
            ind2=isnan(CMIP5_vect2);
            CMIP5_vect2(ind2)=[];
 
            GPCC_vect2=GPCC_vect;
            GPCC_vect2(ind2)=[];
 
            CMIP5_GPCC_corr(mod,sea)=corr2(CMIP5_vect2,GPCC_vect2);
        end
    end
end
 
sea_labels={'DJF ';'MAM ';'JJA ';'SON ';''};
 
mod_labels={'CCSM4';'CNRM-CM5';'GFDL-CM3';'GISS-E2-H';...
    'GISS-E2-R';'HadCM3';'HadGEM2-CC';'HadGEM2-ES';'IPSL-CM5B-LR';...
    'MPI-ESM-P';'NorESM1-M';'NorESM1-ME';'CanCM4';'CPC';'3B42v6';...
    'CMIP5 Mean'};
 
legend_labels=cat(1,mod_labels(1:12,1),...
    {'CanCM4 (1961-2005)';'NOAA CPC (1948-2006)';'TRMM 3B42v6 (1998-2009)';'CMIP5 Mean'});
 
xtick=0:0.17:1.7;
ytick=-1:0.2:1;
limx=[0 1.7];
limy=[-1 1];
 
ColorSet = colorcube(17);
 
k=1;
 
for sea=1:5
    % Create figure
    figure('Name',[char(sea_labels(sea,1)),'1901-2005 precip'],'Color',[1 1 1],'Position',[0 40 1920 964]);
    set(gcf,'PaperPositionMode','auto');
    % Create axes
    set(gca,'YDir','normal','XTick',xtick,'YTick',ytick,'Layer','top','FontSize',18);
    % Uncomment the following line to preserve the X-limits of the axes
    xlim(limx);
    % Uncomment the following line to preserve the Y-limits of the axes
    ylim(limy);
 
    box('on');
    hold('all');
    grid('on');
 
    % Create image
    dy=0.05;
    for mod=1:16
        scatter(RMScdiff(mod,sea),CMIP5_GPCC_corr(mod,sea),110,ColorSet(mod,:),'filled');
        text(RMScdiff(mod,sea),CMIP5_GPCC_corr(mod,sea) + dy,char(mod_labels(mod,1)),...
            'FontSize',16,'Color',ColorSet(mod,:),'FontWeight','bold');
    end
    % Create title
    title({'Florida Rainfall',[char(sea_labels(sea,1)),'1901-2005'],'CMIP5 Models vs. GPCC v5 Obs.'},'FontSize',32);
    % Create xlabel
    xlabel('Centered RMS Differennce (mm/day)','FontSize',24,'FontWeight','bold');
    % Create ylabel
    ylabel('Correlation Coefficient','FontSize',24,'FontWeight','bold');
    % Create legend
    legend(legend_labels,'Location','EastOutside','FontSize',16,'FontWeight','bold');
 
    saveas(gcf,['MPO524\HW0_ptI_fig',int2str(k),'.jpg']);
    k=k+1;
end