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闲着没事,画画图,AO和NAO是两种不同的现象,但是它们又有着很大的关联,下面用Matlab处理了一下(数据来自:http://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/ao.shtml#current)
程序如下:
%-------------AO and NAO Index data----------------
%----------------Created by 猛牛, Apr 22, 2012------------------------
clear;clf;clc;
load monthly.ao.index.b50.current.ascii
load norm.nao.monthly.b5001.current.ascii
AO=monthly_ao_index_b50_current;
NAO=norm_nao_monthly_b5001_current;
AO_p=AO(637:744,3); %-------Time: 2003 to 2011------
NAO_p=NAO(637:744,3);
A_index1=find(AO_p>0);
AO_positive=AO_p(AO_p>0);
A_index2=find(AO_p<0);
AO_negtive=AO_p(AO_p<0);
up=0;
for i=1:length(AO_p)
up=up+(AO_p(i)-mean(AO_p))*(NAO_p(i)-mean(NAO_p));
end
down_1=0;down_2=0;
for i=1:length(AO_p)
down_1=down_1+(AO_p(i)-mean(AO_p))^2;
down_2=down_2+(NAO_p(i)-mean(NAO_p))^2;
end
r=up/(sqrt(down_1*down_2)); %-----Caculate the correlation coefficient-----
t=abs(r*sqrt(length(AO_p)-2)/sqrt(1-r^2)); %-----t-test------
bb=bar(A_index1,AO_positive,'b');
hold on
cc=bar(A_index2,AO_negtive,'r');
plot(NAO_p,'k','linewidth',2);
set(gca,'xtick',[1,13,25,37,49,61,73,85,97],'xticklabel',...
{'2003-Jan','2004-Jan','2005-Jan','2006-Jan','2007-Jan','2008-Jan','2009-Jan','2010-Jan','2011-Jan'},'xlim',[1 110],'fontsize',16);
set(gca,'ylim',[-4.5 3],'fontsize',16);
xlabel('Year(Monthly mean)','FontSize',21);
ylabel('AO and NAO Index','FontSize',21);
set(gca,'XColor','k','YColor','k','linewidth',2);
text(3,-3,strcat('Correlation Coefficient R:',num2str(r)),'color','g','fontsize',16,'fontweight','bold');
legend('AO-Positive','AO-Negtive','NAO',3);
legend('boxoff');
title('AO and NAO Index','FontSize',23);
saveas(gcf,strcat('AO and NAO Index(Monthly mean)','.emf'));
成图如下:
可以看出AO和NAO的密切关系,相关系数达到0.68888,通过了显著水平0.05的检验。
PS:不是做气象的,欢迎讨论与批评指正 :)
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