/
plot_TEMP_horizons.m
3745 lines (2976 loc) · 145 KB
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plot_TEMP_horizons.m
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% Generate analysis/plots for Temperature impacts paper
clearvars -except S;
close all; clc;
RELOAD=1;
if RELOAD==1
load(append('data','/','S9.mat'))%load('S9.mat'); # Request the data files from the authors
end
cd RCP
[ti, Tmax, Tmean, Tmin]=temperatureProjectionsCMIP5();
cd ..
QC={S.QC};
ID=find(strcmp(QC,'Everything seems ok.'));
% remove some stations manually
ID(strcmp({S(ID).name}','THORNBROUGH'))=[];
ID(strcmp({S(ID).name}','Buckskin Joe'))=[];
ID(strcmp({S(ID).name}','Saint Elmo'))=[];
ID(strcmp({S(ID).name}','WAPELLO'))=[];
ID(strcmp({S(ID).name}','HYDEN 4 E'))=[];
ID(strcmp({S(ID).name}','ANDERSON 3W'))=[];
ID(strcmp({S(ID).name}','AVA 6NW'))=[];
ID(strcmp({S(ID).name}','JOPLIN 24 N'))=[];
ID(strcmp({S(ID).name}','PARKS SPRING RCH'))=[];
ID(strcmp({S(ID).name}','CHARLOTTE'))=[];
ID(strcmp({S(ID).name}','MT. PLEASANT'))=[];
ID(strcmp({S(ID).name}','Swift Creek'))=[];
ID(strcmp({S(ID).name}','LAC VIEUX DESERT'))=[];
ID([S(ID).yearsWithData]<=50)=[];
len=length(ID);
% Stations of interests
cities={'USW00022521','Honolulu'
'USW00023272','San Francisco'
'USW00024233','Seattle'
'USW00025309','Juneau'
'USW00013960','Dallas'
'USW00094846','Chicago'
'USW00014739','Boston'
'USW00013743','Washington D.C.'
};
ID_cities=[];
for i =1:size(cities,1)
ID_cities(end+1)=find(strcmp({S(ID).id},cities{i,1}));
end
ri=1/3;
% anonymous functions to work with GEV data
F=@(x,mu,sig,k) gevcdf(x,k,sig,mu); % Cumulative probablity distribution function
E=@(x,mu,sig,k) 1-F(x,mu,sig,k); % exceedance probablity function
E_inc=@(x,mu,sig,k,SLR) E(x,mu+SLR,sig,k)./E(x,mu,sig,k); % factor of increase in exceedance of probability
x_inv=@(E,mu,sig,k) gevinv(1-E,k,sig,mu); % calculate event level x based on exceedace probability
Tr=@(x,mu,sig,k) ri./E(x,mu,sig,k); % return period
x_Tr=@(yr,mu,sig,k) gevinv(1-(ri./yr),k,sig,mu); % calculate event level x based on return period
Tr_pct_red=@(TR,mu,sig,k,SLR) (TR-Tr(x_Tr(TR,mu,sig,k),mu+SLR,sig,k))./TR; % calculate the percent reduction in return period
DT=@(mu,sig,k) x_Tr(50,mu,sig,k)-x_Tr(1,mu,sig,k); % difference in temperature level between 50-year and 1-year event
DeltaT_50yr_1yr=NaN(len,1);
DeltaT_1yr_SUMTEMP=NaN(len,1);
for i=1:len
DeltaT_50yr_1yr(i)=DT(S(ID(i)).mu,S(ID(i)).sigma,S(ID(i)).k);
DeltaT_1yr_SUMTEMP(i)=x_Tr(1,S(ID(i)).mu,S(ID(i)).sigma,S(ID(i)).k)-S(ID(i)).summer_avg;
end
% % solve for sigma as a function of K and DWL
mu=40;
k=(-1:0.02:1)';
DTi=(0.01:0.1:50)';
[K,DTi]=meshgrid(k,DTi);
[m,n]=size(K);
SIG=NaN(m,n);
for i=1:m
for j=1:n
SIG(i,j)=fzero(@(sig) DT(mu,sig*(sig>0)+1e-6,K(i,j))-DTi(i,j),[1e-5 1000]);
end
end
% pcolor(K,DTi,SIG); shading flat;
% contour(K,DTi,SIG); shading flat;
%% Computing local projections + high-end and low-end projections
% Mohsen has prepared the following mat file.
% load('/Users/ali/Downloads/T_kelvin_monthly_2000_2300.mat')
% load('/Users/ali/Downloads/T_kelvin_annual_2000_2100.mat')
% load('data/T_kelvin_annual_2000_2300_fixed.mat')
% T_proj_local = struct;
% T_proj_local.lat = Lat;
% T_proj_local.lon = Lon - 180;
% T_proj_local.TR = T_kelvin - repmat(T_kelvin(:,:,1), [1 1 size(T_kelvin, 3)]);
%
% % T_proj_local.time_start = datenum(2000,6,30);
% % T_proj_local.time_end = datenum(2100,6,30);
% % T_proj_local.time = linspace(T_proj_local.time_start, T_proj_local.time_end, 101);
%
% T_proj_local.time_start = datenum(2000,6,30);
% T_proj_local.time_end = datenum(2300,6,30);
% T_proj_local.time = linspace(T_proj_local.time_start, T_proj_local.time_end, 301);
%
% save('Data/T_proj_local.mat', 'T_proj_local');
load('Data/T_proj_local.mat');
% load('Data/full-run.mat')
cd RCP
[ti, Tmax, Tmean, Tmin]=temperatureProjectionsCMIP5();
cd ..
[b,a] = butter(4,0.01,'low');
Tmin=filtfilt(b,a,Tmin);
Tmean=filtfilt(b,a,Tmean);
Tmax=filtfilt(b,a,Tmax);
Tmin(1:250) = interp1([1 250],[Tmin(1) Tmin(250)],1:1:250,'spline');
Tmax(1:250) = interp1([1 250],[Tmax(1) Tmax(250)],1:1:250,'spline');
Tmin(1:9) = Tmin(9)*ones(9,1);
ti_int = linspace(T_proj_local.time_start, T_proj_local.time_end, size(T_proj_local.TR, 3));
Tmax_ratio = 1+interp1(ti, (Tmax-Tmean)./Tmean, ti_int,'linear', 'extrap');
Tmin_ratio = 1+interp1(ti, (Tmin-Tmean)./Tmean, ti_int,'linear', 'extrap');
Tmin_ratio(Tmin_ratio<0.01) = 0.01;
Tmean_int = interp1(ti, Tmean, ti_int);
[X,Y] = meshgrid(T_proj_local.lat, T_proj_local.lon);
T_mean_stations = NaN(len,301);
T_low_stations = NaN(len,301);
T_high_stations = NaN(len,301);
for i=1:len
id=ID(i);
i
% https://stackoverflow.com/questions/32481804/find-the-nearest-point-to-x-y-coordinates-on-mesh-matlab
d = (S(id).lat-X).^2+(S(id).lon-Y).^2;
[~, ind] = min(d(:));
% resultX = X(ind) %// use that index to obtain the result
% resultY = Y(ind)
[ind_r, ind_c] = ind2sub(size(X), ind);
% X(ind_r, ind_c)
% Y(ind_r, ind_c)
% The Temperature projection linked to the location:
Ttmp = reshape(T_proj_local.TR(ind_r, ind_c, :), 1, []);
Ttmp2 = Ttmp;
% N=30;
% Ttmp2=[flipud(Ttmp(1:N)), Ttmp, flipud(Ttmp(end-N:end))];
% [b,a] = butter(2,0.02,'low');
[b,a] = butter(4,0.01,'low'); %0.01
Tsmooth=filtfilt(b,a,Ttmp2);
% Tsmooth=Tsmooth(N+1:end-N-1);
Tsmooth_shift = 0 - Tsmooth(1);
Tsmooth = Tsmooth + Tsmooth_shift;
% figure(13)
% plot(Ttmp2); hold on
% plot(Tsmooth)
% plot(Tsmooth); hold on
% drawnow
% for ii = 1:301
% if Tsmooth(ii)<0
% pause(1)
% break
% end
% end
S(id).TR_raw = reshape(T_proj_local.TR(ind_r, ind_c, :), 1, []);
S(id).TR_smooth = Tsmooth;
% S(id).TR = S(id).TR_raw + Tsmooth_shift;
S(id).TR = Tsmooth;
assert(~any(isnan(S(id).TR)))
% S(id).TR_high_end = S(id).TR.*(1+Tmax_ratio);
% S(id).TR_low_end = S(id).TR.*(1+Tmin_ratio);
S(id).TR_high_end = S(id).TR.*(Tmax_ratio);
S(id).TR_low_end = S(id).TR.*(Tmin_ratio);
S(id).TR_scenario = [S(ID(i)).TR_low_end', S(ID(i)).TR', S(ID(i)).TR_high_end'];
S(id).ti = ti_int;
T_mean_stations(i,:) = S(id).TR;
T_low_stations(i,:) = S(id).TR.*(Tmin_ratio);
T_high_stations(i,:) = S(id).TR.*(Tmax_ratio);
end
% ssss = 1050;
% figure(14)
% plot(T_mean_stations(ssss,:),'-k'); hold on
% plot(T_low_stations(ssss,:),'-b');
% plot(T_high_stations(ssss,:),'-r');
% Tmean_local = reshape(mean(mean(T_proj_local.TR, 1,'omitnan'),2,'omitnan'), 1, []);
% Tmean_local = interp1(ti_int, Tmean_local, ti);
% Global projections: mean-max-min
% figure;
% plot(ti, Tmean); hold on;
% plot(ti_int, Tmean_int.*(1+Tmax_ratio));
% plot(ti_int, Tmean_int.*(1+Tmin_ratio));
% datetick('x','keeplimits','keepticks');
% legend('Tmean','Tmax_comp. by ratio','Tmin comp. by ratio')
% % axis([datenum(2000,1,1) datenum(2100,1,1) 0 6]);
% axis([datenum(2000,1,1) datenum(2300,1,15) 0 16]);
%
% % Local projection:
% figure; hold on;
% plot(T_proj_local.time, S(id).TR);
% plot(T_proj_local.time, S(id).TR_smooth);
% plot(T_proj_local.time, S(id).TR_high_end);
% plot(T_proj_local.time, S(id).TR_low_end);
%
% datetick('x','keeplimits','keepticks');
% legend('Local TR', 'Local TR smooth', 'Local High-end TR', 'Local Low-end TR')
%% Calculations for ENSO vs. nonstationary GEV parameters
load('ENSO_ONI.mat');
ENSO_thresh = 0.833; %threshold to choose ENSO years based on ENSO index value (0.833 is the 0.5*std(ONI) value)
ENSO_yr = [];
ENSO_index = [];
for ff = 1:size(ENSO_ONI,1)
if max(ENSO_ONI(ff,2:end)) > ENSO_thresh
ENSO_yr = [ENSO_yr ENSO_ONI(ff,1)];
ENSO_index = [ENSO_index max(ENSO_ONI(ff,2:end))];
end
end
% ENSO_yr = [1952 1958 1964 1966 1969 1973 1983 1987 1988 1992 1995 1998 2003 2010 2016];
% ENSO_index = [1.2 1.8 1.4 2 1.1 2.1 2.2 1.2 1.7 1.7 1.1 2.4 1.3 1.6 2.6]; %ONI
NS_groups = [4 5 6 7 8 9]; %number of time periods for nonstationary analysis
start_yr = 1951;
end_yr = 2017;
max_events = 3; %top n maxima per year
for k = 1:length(NS_groups)
NS_yr_lim = floor(linspace(start_yr,end_yr,NS_groups(k)+1));
ENSO_index_avg = NaN(1,NS_groups(k));
yearss = NaN(2,NS_groups(k));
yearss_label = cell(1,NS_groups(k));
for pp = 1:NS_groups(k)
t_1 = datenum(append('01-Jun-',num2str(NS_yr_lim(pp))),'dd-mmm-yyyy');
t_2 = datenum(append('01-Jun-',num2str(NS_yr_lim(pp+1))),'dd-mmm-yyyy');
bin = [];
for jj = 1:length(ENSO_yr)
t_t = datenum(append('01-Jan-',num2str(ENSO_yr(jj))),'dd-mmm-yyyy');
if t_t>t_1 && t_t<t_2
bin = [bin ENSO_index(jj)];
end
end
ENSO_index_avg(1,pp) = nanmean(bin);
Yearss(1,pp) = NS_yr_lim(pp);
Yearss(2,pp) = NS_yr_lim(pp+1);
yearss_label(1,pp) = cellstr(append(num2str(nanmean(bin),'%.3f'),' ','(',num2str(NS_yr_lim(pp)),'-',num2str(NS_yr_lim(pp+1)),')'));
end
mu_st = NaN(1,len);
sigma_st = NaN(1,len);
k_st = NaN(1,len);
mu_nonst = NaN(NS_groups(k),len);
sigma_nonst = NaN(NS_groups(k),len);
k_nonst = NaN(NS_groups(k),len);
for i = 1:len
[k i]
max_temps = [];
max_times = [];
for j = 1:size(S(ID(i)).h_events,1)
[bin_h,ind] = sort(S(ID(i)).h_events(j,:),'descend');
bin_t = S(ID(i)).t_events(j,:);
bin_t = bin_t(ind);
max_temps = [max_temps bin_h(1:max_events)];
max_times = [max_times bin_t(1:max_events)];
end
parmhat = gevfit(max_temps);
mu_st(i) = parmhat(3);
sigma_st(i) = parmhat(2);
k_st(i) = parmhat(1);
for ii = 1:NS_groups(k)
t_1 = datenum(append('01-Jun-',num2str(NS_yr_lim(ii))),'dd-mmm-yyyy');
t_2 = datenum(append('01-Jun-',num2str(NS_yr_lim(ii+1))),'dd-mmm-yyyy');
ind2 = find(max_times>=t_1 & max_times<=t_2);
max_temps_NS = max_temps(ind2);
max_times_NS = max_times(ind2);
if length(max_temps_NS) > floor(0.5*(NS_yr_lim(ii+1)-NS_yr_lim(ii)))
parmhat = gevfit(max_temps_NS);
mu_nonst(ii,i) = parmhat(3);
sigma_nonst(ii,i) = parmhat(2);
k_nonst(ii,i) = parmhat(1);
end
end
end
mu_dev = mu_nonst-repmat(mu_st,NS_groups(k),1);
sigma_dev = sigma_nonst-repmat(sigma_st,NS_groups(k),1);
k_dev = k_nonst-repmat(k_st,NS_groups(k),1);
[ENSO_index_avg,ind4] = sort(ENSO_index_avg,'ascend');
yearss_label = yearss_label(ind4);
mu_dev = mu_dev(ind4,:);
sigma_dev = sigma_dev(ind4,:);
k_dev = k_dev(ind4,:);
if k ==1
x_starts = 0.12;
y_starts = 0.78;
x_len = 0.79;
y_len = 0.12;
ONI = [];
for iii = 1:size(ENSO_ONI,1)
ONI = [ONI ENSO_ONI(iii,2:end)];
end
figure(111);
set(gcf,'PaperpositionMode','auto','Position',[100 50 1000 1000],'color','w');
subplot('Position',[x_starts y_starts x_len y_len]); hold on; box on;
plot(ENSO_ONI(1,1):1/12:ENSO_ONI(end,1)+1-1/12,ONI,'k');
xx = ENSO_ONI(1,1):1/12:ENSO_ONI(end,1)+1-1/12;
yy = ONI;
xx = interp1(1:length(xx),xx,1:0.1:length(xx));
yy = interp1(1:length(yy),yy,1:0.1:length(yy));
idxp = yy>=0;
area(xx(idxp),yy(idxp),'FaceColor',[0.8500 0.3250 0.0980]);
idxn = yy<=0;
area(xx(idxn),yy(idxn),'FaceColor',[0 0.4470 0.7410]);
yline(std(ONI),'--','color',[0.4940 0.1840 0.5560],'linewidth',1);
yline(-std(ONI),'--','color',[0.4940 0.1840 0.5560],'linewidth',1);
area(xx,std(ONI)*ones(size(xx)),'FaceColor','w','edgeColor','none','FaceAlpha',0.7);
area(xx,-std(ONI)*ones(size(xx)),'FaceColor','w','edgeColor','none','FaceAlpha',0.7);
xlabel('Year'); xlim([1950 2017]);
ylabel('ONI'); ylim([-2.75 2.75]);
set(gca,'FontSize',12,'FontName','Constantia');
legend('','El Niño event','La Niña event','\pm \sigma_{ONI}','','','','Location','southwest','FontSize',10,'Box','on','orientation','horizontal');
title('The evolution of ENSO (1950-2017)','FontSize',16,'FontName','Constantia');
annotation(gcf,'textbox',...
[0.120000000000001 0.904221311475419 0.020999999999999 0.0220081967213137],...
'VerticalAlignment','middle',...
'String','A',...
'Interpreter','none',...
'HorizontalAlignment','center',...
'FontWeight','bold',...
'FontSize',18,...
'FontName','Nomada Incise',...
'FitBoxToText','off',...
'BackgroundColor',[0.8 0.8 0.8]);
end
xlims = [1.44 1.63; 1.35 1.85; 1.35 2.06; 1.04 2.06; 1.04 2.06; 0.84 2.23];
subplot(4,2,k+2); hold on; box on; grid on
boxplot(k_dev',ENSO_index_avg,'Positions',ENSO_index_avg,'PlotStyle','compact');
hh = findobj(gcf,'tag','Outliers');
set(hh,'MarkerSize',0.000001);
medlinreg = polyfit(ENSO_index_avg,nanmedian(k_dev'),1);
medlinval = polyval(medlinreg,ENSO_index_avg);
plot(ENSO_index_avg,medlinval,'--','color',[0.8500 0.3250 0.0980],'linewidth',2)
% xlabel('$\overline{ONI}$','Interpreter','latex');
xlim(xlims(k,:))
xticks(ENSO_index_avg);
xticklabels(string(yearss_label)); xtickangle(20)
ylabel('$\Delta$k','Interpreter','latex');
ylim([-0.69 0.69])
set(gca,'FontSize',12,'FontName','Constantia');
title(append('$\Delta$k vs. $\overline{ONI}$ [','y=',num2str(medlinreg(1),'%.3f'),'x+(',num2str(medlinreg(2),'%.3f'),')]'),'FontSize',15,'Interpreter','latex');
labelsss = {'A','B','C','D','E','F','G'};
x_sepp = 0.458;
y_sepp = 0.223;
annotation(gcf,'textbox',...
[0.131000000000001+(mod(k+1,2))*x_sepp 0.69364754098361-floor((k-1)/2)*y_sepp 0.0209999999999992 0.0220081967213137],...
'VerticalAlignment','middle',...
'String',string(labelsss(k+1)),...
'Interpreter','none',...
'HorizontalAlignment','center',...
'FontWeight','bold',...
'FontSize',18,...
'FontName','Nomada Incise',...
'FitBoxToText','off',...
'BackgroundColor',[0.8 0.8 0.8]);
annotation(gcf,'textbox',...
[0.171+(mod(k+1,2))*x_sepp 0.517418032786886-floor((k-1)/2)*y_sepp 0.282 0.0256147540983606],...
'VerticalAlignment','middle',...
'String','$\overline{ONI}$ (Period)',...
'Interpreter','latex',...
'HorizontalAlignment','center',...
'FontSize',12,...
'FitBoxToText','off',...
'EdgeColor','none');
end
exportgraphics(gcf,'figures/ENSO_effect_on_k.png','Resolution',300)
%%
stop
%% clustering
Nclusters=4;
mu=[S(ID).mu]; sigma=[S(ID).sigma]; k=[S(ID).k];
MHHW=[S(ID).summer_avg];
RECLUSTER=0;
if RECLUSTER==1
idx = kmeans([((mu-nanmean(mu))/nanstd(mu))' ((sigma-nanmean(sigma))/nanstd(sigma))'...
((k-nanmean(k))/nanstd(k))'],Nclusters,'MaxIter',1000);
save('clusters.mat','idx');
else
load(fullfile('data', 'clusters.mat'));
end
% color based on cluster
cmap=[0 255 0; ...
255 0 0; ...
0.9290*255 0.6940*255 0.1250*255; ...
135 206 250; ...
]/255;
% cmap=[0.4660 0.6740 0.1880; ...
% 0.6350 0.0780 0.1840; ...
% 0.9290 0.6940 0.1250; ...
% 0 0.4470 0.7410; ...
% ];
FontName = 'Alverata';
% figure(10);
% scatter3([S(ID).mu],[S(ID).sigma],[S(ID).k],30*ones(length([S(ID).lon]),1),idx,'filled');
% xlabel('mu');
% ylabel('sigma');
% zlabel('k');
% colormap(cmap);
%cmap=colormap(jet(Nclusters));
han1=figure(1); set(han1,'PaperpositionMode','auto','Position',[200 100 1000 800],'color','w'); hold on; box on;
subplot('position',[0.056 0.49 0.542 0.451666666666667]);
hold on;
geoshow('landareas.shp','FaceColor',[0.6 0.6 0.6],'EdgeColor',[0.6 0.6 0.6]); box on; axis equal
% axis equal; axis tight; box on; shading flat; hold on
% scatter([S(ID).longitude],[S(ID).latitude],30*ones(length([S(ID).longitude]),1),idx,'filled');
% scatter([S(ID).longitude],[S(ID).latitude],30*ones(length([S(ID).longitude]),1),[S(ID).mu],'filled');
%scatter([S(ID).lon],[S(ID).lat],30*ones(length([S(ID).lon]),1),[S(ID).mu],'filled');
scatter([S(ID).lon],[S(ID).lat],30*ones(length([S(ID).lon]),1),idx,'filled');
axis([-180 -60 0 80]);
colormap(cmap);
set(gca,'FontSize',14,'FontName',FontName);
title('North America climate stations','FontSize',18);
% Borders: https://www.mathworks.com/matlabcentral/fileexchange/50390-borders
cd borders_v2/borders
borders('countries','k','nomap','linewidth',0.25)
cd ../..
id=find(strcmp({S(ID).id}','USW00094846')); % station of interest - Chicago
han1=plot(S(ID(id)).lon,S(ID(id)).lat,'ko'); set(han1,'LineWidth',2)
annotation(gcf,'textarrow',[0.443 0.467],[0.795 0.735],...
'String',{'Chicago'},'FontName',FontName);
%
% annotation(gcf,'textbox',[0.175 0.6 0.128 0.0524999999999999],...
% 'String',{'GEV model details','shown in panel B'},...
% 'FitBoxToText','off','FontSize',9,'linestyle','none','color',[0.6 0.6 0.6]);
% annotation(gcf,'arrow',[0.181 0.159],[0.635 0.615],'color',[0.6 0.6 0.6]);
% SUBPLOT B
subplot('position',[0.68 0.485 0.3 0.455]); hold on; box on;
axis([ri 100 20 50])
set(gca,'FontSize',14,'Xscale','log','FontName',FontName);
S(ID(id)).h_max=sort(reshape(S(ID(id)).h_events(:,1:3),[],1),'descend');
Nmax=length(S(ID(id)).h_max);
% max=S(ID(id)).yearsWithData*3;
% Plot results
P1=(0.001:0.001:1)'; E1=1-P1;
E_data=linspace(1/(Nmax+1),Nmax/(Nmax+1),Nmax)';
P_data=1-E_data;
ri=1/3;
%Tr_data=S(ID(id)).ri./E_data;
Tr_data=ri./E_data;
%ri=S.ri;
Tr1=(0.01:0.01:150)';
han1=plot(Tr_data,S(ID(id)).h_max,'o');set(han1,'MarkerFaceColor',[255 0 0]/255,'MarkerEdgeColor',[255 0 0]/255,'MarkerSize',5);
han1=plot(Tr1,x_Tr(Tr1,mu(id),sigma(id),k(id)),'b'); set(han1,'LineWidth',2);
GW=x_Tr(50,mu(id),sigma(id),k(id))-x_Tr(1,mu(id),sigma(id),k(id)); % ???? Is this how we get global warming?
han1=plot(Tr1,x_Tr(Tr1,mu(id)+GW,sigma(id),k(id)),'r');
set(han1,'LineWidth',2);
plot([0.1 100],[x_Tr(50,mu(id),sigma(id),k(id)) x_Tr(50,mu(id),sigma(id),k(id))],'k--');
%plot([1 1],[0 2],'k--');
annotation(gcf,'arrow',[0.738 0.738], [0.72 0.792],'LineWidth',2);
% annotation(gcf,'arrow',[0.737 0.737], [0.61118 0.71878],'LineWidth',2);
%annotation(gcf,'textbox',[0.701 0.62875 0.045 0.03875],'String',{'GW'},'FitBoxToText','off','FontWeight','bold','LineStyle','none');
annotation(gcf,'textbox',[0.702 0.726 0.045 0.0387],'String',{'TR'},'FitBoxToText','off','FontWeight','bold','LineStyle','none','FontSize',16,'FontName',FontName);
%
annotation(gcf,'arrow',[0.734 0.734],[0.60155 0.67495],'LineWidth',2);
annotation(gcf,'textbox',[0.698 0.61377 0.045 0.0387],'String',{'TR'},'FitBoxToText','off','FontWeight','bold','LineStyle','none','FontSize',16,'FontName',FontName);
han1=plot([0.1 100],[MHHW(id)+GW MHHW(id)+GW],'r--'); set(han1,'LineWidth',2);
TR=[1 50];
for ii=1:length(TR)
han1=plot(TR(ii),x_Tr(TR(ii),mu(id),sigma(id),k(id)),'kx'); set(han1,'MarkerSize',10,'LineWidth',2);
end
%han1 = text(.79,.81, 'ali'); set(han1, 'FontSize', 16)
han1=text(2.77223050497508, 35.1557987627863,[num2str(TR(1)),'-yr event = ',num2str(x_Tr(TR(1),mu(id),sigma(id),k(id)),3),' \circC']); set(han1,'FontSize',16,'FontName',FontName);
han1=text(1.221, 46.737 ,[num2str(TR(2)),'-yr event = ',num2str(x_Tr(TR(2),mu(id),sigma(id),k(id)),3), ' \circC']); set(han1,'FontSize',16,'FontName',FontName);
annotation(gcf,'arrow',[0.8832 0.938],[0.87142 0.80125]);
annotation(gcf,'arrow',[0.787 0.748],[0.715 0.71625]);
xlabel('Return period [years]');
ylabel('Extreme temperature [\circC]');
set(gca,'FontSize',14,'Xscale','log','FontName',FontName);
title('GEV model for Chicago, Illinois','FontSize',18)
han1=plot([0.1 100],[MHHW(id) MHHW(id)],'k--'); set(han1,'LineWidth',2);
% han1=text(1.3,MHHW(id)+0.04,['GW = ',num2str(MHHW(id),3),' m']); set(han1,'FontSize',16);
han1=text(1.7241, 28.4955,['MST = ',num2str(MHHW(id),3),' \circC']); set(han1,'FontSize',16,'FontName',FontName);
han1=legend('Temperature data','GEV model','GEV model + TR'); set(han1,'location','southeast','FontSize',16);
axis([ri 100 20 50])
%axis([ri 100 ylim])
width=0.24;
height=1.25*width;
xsep=0.09;
% SUBPLOT C
subplot('position',[0.085-0.01 0.11 width height]); hold on; box on;
for i=1:Nclusters
han1=plot(mu(idx==i),sigma(idx==i),'o');set(han1,'MarkerFaceColor',cmap(i,:),'MarkerSize',8,'MarkerEdgeColor','k');
end
set(gca,'FontSize',14,'FontName',FontName)
xlabel('\mu','FontSize',18);
ylabel('\sigma','FontSize',18);
axis([10 50 0.5 3.5])
subplot('position',[0.085+(width+xsep)-0.01 0.11 width height]); hold on; box on;
for i=1:Nclusters
han1=plot(mu(idx==i),k(idx==i),'o');set(han1,'MarkerFaceColor',cmap(i,:),'MarkerSize',8,'MarkerEdgeColor','k');
end
set(gca,'FontSize',14,'FontName',FontName)
xlabel('\mu','FontSize',18);
ylabel('$k$','Interpreter','latex','FontSize',18);
axis([10 50 -0.5 0.21])
subplot('position',[0.085+2*(width+xsep)-0.01 0.11 width height]); hold on; box on;
for i=1:Nclusters
han1=plot(sigma(idx==i),k(idx==i),'o');set(han1,'MarkerFaceColor',cmap(i,:),'MarkerSize',8,'MarkerEdgeColor','k');
end
set(gca,'FontSize',14,'FontName',FontName)
xlabel('\sigma','FontSize',18);
ylabel('$k$','Interpreter','latex','FontSize',18);
axis([0.5 3.5 -0.5 0.21])
xticks([0.5:0.5:3.5])
annotation(gcf,'textbox',...
[0.0630000000000006 0.49875 0.0349999999999997 0.04375],...
'VerticalAlignment','middle',...
'String','A',...
'Interpreter','none',...
'HorizontalAlignment','center',...
'FontWeight','bold',...
'FontSize',30,...
'FontName','Nomada Incise',...
'FitBoxToText','off',...
'BackgroundColor',[0.8 0.8 0.8]);
annotation(gcf,'textbox',...
[0.687000000000001 0.49875 0.0349999999999997 0.04375],...
'VerticalAlignment','middle',...
'String','B',...
'Interpreter','none',...
'HorizontalAlignment','center',...
'FontWeight','bold',...
'FontSize',30,...
'FontName','Nomada Incise',...
'FitBoxToText','off',...
'BackgroundColor',[0.8 0.8 0.8]);
annotation(gcf,'textbox',...
[0.0920000000000008-0.01 0.11875 0.0349999999999995 0.0437499999999998],...
'VerticalAlignment','middle',...
'String','C',...
'Interpreter','none',...
'HorizontalAlignment','center',...
'FontWeight','bold',...
'FontSize',30,...
'FontName','Nomada Incise',...
'FitBoxToText','off',...
'BackgroundColor',[0.8 0.8 0.8]);
annotation(gcf,'textbox',...
[0.422000000000001-0.01 0.11875 0.0349999999999995 0.0437499999999998],...
'VerticalAlignment','middle',...
'String','D',...
'Interpreter','none',...
'HorizontalAlignment','center',...
'FontWeight','bold',...
'FontSize',30,...
'FontName','Nomada Incise',...
'FitBoxToText','off',...
'BackgroundColor',[0.8 0.8 0.8]);
annotation(gcf,'textbox',...
[0.752000000000001-0.01 0.11875 0.0349999999999996 0.0437499999999998],...
'VerticalAlignment','middle',...
'String','E',...
'Interpreter','none',...
'HorizontalAlignment','center',...
'FontWeight','bold',...
'FontSize',30,...
'FontName','Nomada Incise',...
'FitBoxToText','off',...
'BackgroundColor',[0.8 0.8 0.8]);
% print(gcf,'figures/Figure1_clusters.jpg','-djpeg','-r300');
exportgraphics(gcf,'figures/Figure2.png','Resolution',300)
% exportgraphics(gcf,'figures/test2.png','Resolution',300)
%% Plot Delta tempereture (Figure 2)
han1=figure(2); set(han1,'PaperpositionMode','auto','Position',[200 100 1000 500],'color','w');
subplot('position',[0.07 0.11 0.47 .82]); hold on; box on;
han1=plot([S(ID).k],DeltaT_50yr_1yr,'ko'); set(han1,'linewidth',2);
scatter([S(ID).k],DeltaT_50yr_1yr,40,[S(ID).sigma],'o','filled');
%caxis([0 4]);
caxis([0.5 3.5]);
colormap(flipud(jet));
han1=colorbar; set(han1,'visible','off')
% tmp=linspace(0.4,3.2,5); % BUG: has to be flipped
tmp=flip(linspace(0.4,3.2,5));
% contour(K,DTi,SIG,[6.4 3.2 1.6 0.8 0.4],'k--')
contour(K,DTi,SIG,tmp,'k--') % original
text(-0.1101, 10.213,['$\sigma =' num2str(tmp(1)) ' $'],'Interpreter','latex','Rotation',65,'FontSize',14,'color','k');
text(-0.0249, 10.154,['$\sigma =' num2str(tmp(2)) ' $'],'Interpreter','latex','Rotation',65,'FontSize',14,'color','k');
text(0.0817, 10.21,['$\sigma =' num2str(tmp(3)) ' $'],'Interpreter','latex','Rotation',65,'FontSize',14,'color','k');
text(0.1788, 8.4287,['$\sigma =' num2str(tmp(4)) ' $'],'Interpreter','latex','Rotation',62,'FontSize',14,'color','k');
text(0.1288, 2.7215,['$\sigma =' num2str(tmp(5)) ' $'],'Interpreter','latex','Rotation',35,'FontSize',14,'color','k');
LABELS=1;
if LABELS
i = ID_cities;
han1=plot([S(ID(i)).k],DeltaT_50yr_1yr(i),'ko'); set(han1,'linewidth',2);
% annotation(gcf,'textarrow',[0.213 0.161],[0.138 0.196],...
% 'String',{'Honolulu'});
% annotation(gcf,'textarrow',[0.233 0.266],[0.568 0.484],...
% 'String',{'San Francisco'});
% annotation(gcf,'textarrow',[0.182 0.222],[0.5 0.408],...
% 'String',{'Seattle'});
% annotation(gcf,'textarrow',[0.146 0.237],[0.426 0.364],...
% 'String',{'Juneau'});
% annotation(gcf,'textarrow',[0.297 0.24],[0.164 0.31],...
% 'String',{'Dallas'});
% annotation(gcf,'textarrow',[0.399 0.313],[0.408 0.398],...
% 'String',{'Chicago'});
% annotation(gcf,'textarrow',[0.354 0.26],[0.186 0.312],...
% 'String',{'Boston'});
% annotation(gcf,'textarrow',[0.358 0.271],[0.368 0.338],...
% 'String',{'Washington D.C.'});
annotation(gcf,'textarrow',[0.213 0.161],[0.138 0.196],...
'String',{'Honolulu'},'FontName',FontName);
annotation(gcf,'textarrow',[0.233 0.275],[0.568 0.48],...
'String',{'San Francisco'},'FontName',FontName);
annotation(gcf,'textarrow',[0.182 0.23],[0.5 0.406],...
'String',{'Seattle'},'FontName',FontName);
annotation(gcf,'textarrow',[0.146 0.243],[0.426 0.366],...
'String',{'Juneau'},'FontName',FontName);
annotation(gcf,'textarrow',[0.297 0.249],[0.164 0.308],...
'String',{'Dallas'},'FontName',FontName);
annotation(gcf,'textarrow',[0.399 0.322],[0.408 0.398],...
'String',{'Chicago'},'FontName',FontName);
annotation(gcf,'textarrow',[0.354 0.268],[0.186 0.316],...
'String',{'Boston'},'FontName',FontName);
annotation(gcf,'textarrow',[0.358 0.28],[0.368 0.338],...
'String',{'Washington D.C.'},'FontName',FontName);
end
axis([-0.55 .25 0 14]); % The next plot has to have the same axis
xlabel('$k$','FontSize',14,'interpreter','latex');
ylabel(['\DeltaT [\circC]'],'FontSize',14);
set(gca,'FontSize',14,'XTick',[-1:0.25:1],'FontName',FontName);
title('50-yr event \rightarrow 1-yr event','FontSize',18);
% Right subplot
subplot('position',[0.49 0.11 0.49 .82]); hold on; box on;
han1=plot([S(ID).k],DeltaT_1yr_SUMTEMP,'ko'); set(han1,'linewidth',2);
han2=scatter([S(ID).k],DeltaT_1yr_SUMTEMP,40,[S(ID).sigma],'o','filled');
caxis([0.5 3.5]); colormap(flipud(jet)); colorbar;
if LABELS
i = ID_cities;
% hax = [S(ID(i)).k]
% hay = DeltaT_1yr_SUMTEMP(i)
han1=plot([S(ID(i)).k],DeltaT_1yr_SUMTEMP(i),'ko'); set(han1,'linewidth',2)
% annotation(gcf,'textarrow',[0.615990099009901 0.597990099009901],...
% [0.186227180527383 0.240227180527383],'String',{'Honolulu'});
% annotation(gcf,'textarrow',[0.807445544554456 0.721782178217822],...
% [0.862170385395538 0.908722109533469],'String',{'San Francisco'});
% annotation(gcf,'textarrow',[0.603960396039604 0.664009900990099],...
% [0.860040567951318 0.721079107505071],'String',{'Seattle'});
% annotation(gcf,'textarrow',[0.804980198019802 0.694980198019802],...
% [0.746908722109533 0.654908722109533],'String',{'Juneau'});
% annotation(gcf,'textarrow',[0.586 0.672],...
% [0.384511156186613 0.428511156186613],'String',{'Dallas'});
% annotation(gcf,'textarrow',[0.824990099009901 0.757990099009901],...
% [0.604766734279919 0.560766734279919],'String',{'Chicago'});
% annotation(gcf,'textarrow',[0.577990099009901 0.692990099009901],...
% [0.556908722109533 0.630908722109533],'String',{'Boston'});
% annotation(gcf,'textarrow',[0.8 0.715],...
% [0.241379310344828 0.478653144016227],'String',{'Washington D.C.'});
annotation(gcf,'textarrow',[0.615990099009901-0.015 0.6-0.015],...
[0.186227180527383 0.24],'String',{'Honolulu'},'FontName',FontName);
annotation(gcf,'textarrow',[0.807445544554456-0.015 0.731-0.015],...
[0.862170385395538 0.906],'String',{'San Francisco'},'FontName',FontName);
annotation(gcf,'textarrow',[0.603960396039604-0.015 0.673-0.015],...
[0.860040567951318 0.718],'String',{'Seattle'},'FontName',FontName);
annotation(gcf,'textarrow',[0.555 0.674],[0.626 0.65],'String',{'Juneau'},'FontName',FontName);
annotation(gcf,'textarrow',[0.586-0.015 0.679-0.015],...
[0.384511156186613 0.43],'String',{'Dallas'},'FontName',FontName);
annotation(gcf,'textarrow',[0.824990099009901-0.015 0.766-0.015],...
[0.604766734279919 0.56],'String',{'Chicago'},'FontName',FontName);
annotation(gcf,'textarrow',[0.802 0.698],[0.718 0.65],'String',{'Boston'},'FontName',FontName);
annotation(gcf,'textarrow',[0.8-0.019 0.724-0.019],...
[0.241379310344828 0.48],'String',{'Washington D.C.'},'FontName',FontName);
end
axis([-0.55 .25 0 14]); % BUG: This has to be the same the other subplot
% axis([-0.55 .25 0 12]);
xlabel('$k$','FontSize',14,'interpreter','latex'); set(gca,'FontSize',14,'XTick',[-1:0.25:1],'FontName',FontName);
set(gca,'YTickLabel',[]);
title('1-yr event \rightarrow MST','FontSize',18,'FontName',FontName);
annotation(gcf,'textbox',[0.924 0.924 0.03 0.078],'String',{'$\sigma$'},...
'LineStyle','none','Interpreter','latex','FontSize',20,'FitBoxToText','off');
annotation(gcf,'textbox',[0.935000000000001 0.922 0.0549999999999993 0.078],'String',{' [\circ C]'},...
'LineStyle','none','FontSize',16,'FitBoxToText','off','FontName',FontName);
annotation(gcf,'textbox',...
[0.0780000000000012 0.842750000000002 0.0349999999999995 0.07125],...
'VerticalAlignment','middle',...
'String','A',...
'Interpreter','none',...
'HorizontalAlignment','center',...
'FontWeight','bold',...
'FontSize',30,...
'FontName','Nomada Incise',...
'FitBoxToText','off',...
'BackgroundColor',[0.8 0.8 0.8]);
annotation(gcf,'textbox',...
[0.498000000000001 0.842750000000003 0.0349999999999996 0.07125],...
'VerticalAlignment','middle',...
'String','B',...
'Interpreter','none',...
'HorizontalAlignment','center',...
'FontWeight','bold',...
'FontSize',30,...
'FontName','Nomada Incise',...
'FitBoxToText','off',...
'BackgroundColor',[0.8 0.8 0.8]);
% print(gcf,'figures/Figure2_delta_temperature.jpg','-djpeg','-r300');
exportgraphics(gcf,'figures/Figure3.png','Resolution',300)
% exportgraphics(gcf,'figures/test2.png','Resolution',300)
% -------------------------------------------------------------------------
% Statistics:
% hist(DeltaT_50yr_1yr)
ftemp = @(x) sum(DeltaT_50yr_1yr<x & DeltaT_50yr_1yr>0)/length(DeltaT_50yr_1yr)*100
f_time_to_get_temp = @(x) datetime(ti(find( Tmean > x, 1 )),'ConvertFrom','datenum')
%plot(1:.1:10,ftemp(1:0.1:10))
disp(['50yr becoming y1' string(ftemp(5)), '% of stations'])
disp(['50yr becoming y1' string(ftemp(6.5)), '% of stations'])
disp(['DT of two plots - average:' string(mean(DeltaT_1yr_SUMTEMP))])
disp(['DT of two plots - standard deviation:' string(std(DeltaT_1yr_SUMTEMP))])
sum(DeltaT_1yr_SUMTEMP<5)/length(DeltaT_50yr_1yr)*100
% histogram(DeltaT_1yr_SUMTEMP-DeltaT_50yr_1yr)
%% plot temperature rise horizons plot - Figure 3
TIME1=NaN(len,1);
TIME2=NaN(len,1);
TIME1_max=NaN(len,1);
TIME1_min=NaN(len,1);
TIME2_max=NaN(len,1);
TIME2_min=NaN(len,1);
% RCP={'RCP 2.6','RCP 4.5','RCP 6.0','RCP 8.5'};
s=4;
% s=1; % RCP 8.5
% s=2; % RCP 4.5
% s=3; % RCP 2.6
% TEMP=0:20;
% REMOVE=15;
% RCPt(end-REMOVE:end)=[];
% RCPTEMP(end-REMOVE:end,:)=[];
%TIMEEX=interp1(RCPTEMP(:,s), RCPt,TEMP,'linear','extrap');
% TIMEEX=interp1(Tmean, ti,TEMP,'linear','extrap'); % NEW Commented
% if 1
% figure;
% plot(ti,Tmax,'-b.')%,TIME1,TEMP,'ro');
% stop
% end
for i=1:len
% find the times when SLR is the same as the Delta water level
% TIME1(i)=interp1(RCPTEMP(:,s), RCPt,DeltaT_50yr_1yr(i),'linear','extrap');
% TIME1(i)=interp1(Tmean, ti, DeltaT_50yr_1yr(i),'linear','extrap');
% TIME1_max(i)=interp1(Tmin, ti, DeltaT_50yr_1yr(i),'linear','extrap');
% TIME1_min(i)=interp1(Tmax, ti, DeltaT_50yr_1yr(i),'linear','extrap');
% NEW changes: using local projections:
TIME1(i)=interp1(S(ID(i)).TR, T_proj_local.time, DeltaT_50yr_1yr(i),'linear','extrap');
TIME1_max(i)=interp1(S(ID(i)).TR_low_end, T_proj_local.time, DeltaT_50yr_1yr(i),'linear','extrap');
TIME1_min(i)=interp1(S(ID(i)).TR_high_end, T_proj_local.time, DeltaT_50yr_1yr(i),'linear','extrap');
% TIME2(i)=interp1(Tmean, ti,DeltaT_1yr_SUMTEMP(i),'linear','extrap');
% NEW change: using local projections
TIME2(i)=interp1(S(ID(i)).TR, T_proj_local.time,DeltaT_1yr_SUMTEMP(i),'linear','extrap');
% figure
% plot(TIMEEX, TEMP,'r-',RCPt,RCPTEMP(:,s),'b-',TIME1(i),DeltaT_50yr_1yr(i),'ro',[datenum(2000,1,1) datenum(2150,1,1)],[DeltaT_50yr_1yr(i) DeltaT_50yr_1yr(i)],'k--',[TIME1(i) TIME1(i)],[-1 7],'k--'); datetick('x','keeplimits');
%
% stop
%
end
% Plot time horizon
YLIM1=datenum(2000,1,1);
YLIM2=datenum(2300,1,1);
han1=figure(3); set(han1,'PaperpositionMode','auto','Position',[200 100 1000 500],'color','w');
subplot('position',[0.07 0.11 0.41 .82]); hold on; box on;
%contour(K,TIME,SIG,[0.02 0.05 0.1 0.2],'k--');
han1=scatter([S(ID).k],TIME1,40,[S(ID).sigma],'o','filled');
%caxis([0 4]); colormap(jet); %colorbar;
caxis([0.5 3.5]); colormap(flipud(jet)); %colorbar;
yneg = abs(TIME1-TIME1_min);
ypos = abs(TIME1-TIME1_max);
xneg = zeros(size(TIME1));
xpos = zeros(size(TIME1));
ERRORBARS=0;
if ERRORBARS==1
han1=errorbar([S(ID).k],TIME1,yneg,ypos,xneg,xpos,'.k'); set(han1,'color',[0.666 0.666 0.666])
end
han1=plot([S(ID).k],TIME1,'ko'); set(han1,'linewidth',2);
han1=scatter([S(ID).k],TIME1,40,[S(ID).sigma],'o','filled');
% caxis([0 0.2]); colormap(jet); %colorbar;
axis([-0.55 .25 YLIM1 YLIM2]);
LABELS=1;
if LABELS
han1=plot([S(ID(ID_cities)).k],TIME1(ID_cities),'ko'); set(han1,'linewidth',2);
% ADD labels
% a=axis;
% p=han1.Parent.Position;
% x=@(x) (x-a(1))/(a(2)-a(1))-p(1);
% y=@(y) (y-a(3))/(a(4)-a(3))-p(2);
annotation(gcf,'textarrow',[0.197 0.163],[0.16 0.194],'String',cities(1,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.242 0.275],[0.538 0.414],'String',cities(2,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.148 0.229],[0.42 0.314],'String',cities(3,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.181 0.246],[0.482 0.352],'String',cities(4,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.279 0.247],[0.172 0.282],'String',cities(5,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.415 0.32],[0.442 0.354],'String',cities(6,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.33 0.266],[0.18 0.306],'String',cities(7,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.364 0.279],[0.272 0.34],'String',cities(8,2),'FontName',FontName);
end
set(gca,'FontSize',14,'XTick',[-1:0.25:1],'YTick',datenum(2000:25:2300,1,1),'FontName',FontName);
datetick('y','keeplimits','keepticks');
xlabel('$k$','FontSize',14,'interpreter','latex','interpreter','latex'); ylabel('Year','FontSize',14);
title('50-yr event \rightarrow 1-yr event','FontSize',18);
subplot('position',[0.49 0.11 0.5 .82]); hold on; box on;
han1=scatter([S(ID).k],TIME2,40,[S(ID).sigma],'o','filled');
% caxis([0 0.2]); colormap(jet); colorbar;
% yneg = abs(TIME2-TIME2_min);
% ypos = abs(TIME2-TIME2_max);
%
% xneg = zeros(size(TIME2));
% xpos = zeros(size(TIME2));
%
% ERRORBARS=1;
% if ERRORBARS;
% han1=errorbar([S(ID).k],TIME2,yneg,ypos,xneg,xpos,'.k'); set(han1,'color',[0.666 0.666 0.666])
% end
han1=plot([S(ID).k],TIME2,'ko'); set(han1,'linewidth',2);
han1=scatter([S(ID).k],TIME2,40,[S(ID).sigma],'o','filled');
%caxis([0 4]); colormap(jet); colorbar;
caxis([0.5 3.5]); colormap(flipud(jet)); colorbar;
% axis([-0.55 .25 YLIM1 YLIM2]);
xlabel('$k$','FontSize',14,'interpreter','latex');
set(gca,'FontSize',14,'XTick',[-1:0.25:1],'YTick',datenum(2000:25:2300,1,1),'FontName',FontName);
if LABELS
i = ID_cities;
han1=plot([S(ID(i)).k],TIME2(i),'ko'); set(han1,'linewidth',2);
% ADD labels
% a=axis;
% p=han1.Parent.Position;
% x=@(x) (x-a(1))/(a(2)-a(1))-p(1);
% y=@(y) (y-a(3))/(a(4)-a(3))-p(2);
% annotation(gcf,'textarrow',[0.65 0.632],[0.228 0.282],'String',cities(1,2));
% % annotation(gcf,'textarrow',[0.276 0.301],[0.616 0.536],'String',cities(2,2));
% % annotation(gcf,'textarrow',[0.22 0.252],[0.486 0.44],'String',cities(3,2));
% annotation(gcf,'textarrow',[0.633 0.704],[0.842 0.886],'String',cities(4,2));
% annotation(gcf,'textarrow',[0.621 0.698],[0.398 0.476],'String',cities(5,2));
% annotation(gcf,'textarrow',[0.84 0.773],[0.69 0.646],'String',cities(6,2));
% annotation(gcf,'textarrow',[0.796 0.727],[0.882 0.862],'String',cities(7,2));
% annotation(gcf,'textarrow',[0.817 0.734],[0.244 0.536],'String',cities(8,2));
annotation(gcf,'textarrow',[0.605 0.587],[0.174 0.228],'String',cities(1,2),'FontName',FontName);
% annotation(gcf,'textarrow',[0.276 0.301],[0.616 0.536],'String',cities(2,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.592 0.661],[0.658 0.53],'String',cities(3,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.639 0.681],[0.768 0.54],'String',cities(4,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.582 0.669],[0.334 0.38],'String',cities(5,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.84 0.757000000000001],[0.48 0.44],'String',cities(6,2),'FontName',FontName);
annotation(gcf,'textarrow',[0.791 0.701],[0.606 0.546],'String',cities(7,2),'FontName',FontName);