data=importdata('C:\Data\AMMA\AMMA_SEP08\AMMA_filter_final.txt'); data2=importdata('C:\Data\AMMA\AMMA_SEP08\AMMA_flux_10uf.txt'); % This file inclueds the GOMECC data filtered for reldir, rain, lagtime, % std(O3>3), delta O3ppb>3, filterchange, calibration, count drop. There % fore the column O3ppb is for each filter copied and filtered values set % to NaN jd=data(:,1); %julianday sp=data(:,2); %ship speed u=data(:,3); %wind speed reldir=data(:,4); % relative wind direction rain=data(:,5); %NaN=rain>5 lag=data(:,6); % lagtime O3ppb_o=data(:,7); %O3ppb deltaO3_o=data(:,8); O3std_o=data(:,9); O3ppb=data(:,10); %O3ppb deltaO3=data(:,11); O3std=data(:,12); sp2=data(:,13); sig_u=data(:,14); sig_h=data(:,15); hand=data(:,16); total_o=data(:,17); %total filter crosscorr without lag total=data(:,18); %total filter constant lagtime without lag slowO3=data2(:,52); O3mean=data2(:,50); z=O3mean; jj=find(isnan(lag)); lag(jj)=1; total_o(jj)=NaN; ii=find(isnan(reldir)); reldir(ii)=2; z(ii)=NaN; gg=find(isnan(deltaO3_o)); delta_o(gg)=3; z(gg)=NaN; gg2=find(isnan(deltaO3)); delta(gg2)=3; hh=find(isnan(O3std_o)); std_o(hh)=4; z(hh)=NaN; hh2=find(isnan(O3std)); std(hh2)=4; ff=find(O3ppb_o>100 | O3ppb_o<5); total_o(ff)=NaN; ff2=find(O3ppb>100 | O3ppb<5); z(ff2)=NaN; total(ff2)=NaN; ij=find(isnan(u)); u(ij)=10; z(ij)=NaN; kk=find(isnan(rain)); rain(kk)=11; z(kk)=NaN; ok=find(isfinite(z)); z(ok)=0; figure;plot(jd(kk),rain(kk),'y.') ;hold on; plot(jd(ij),u(ij),'c.');plot(jd(dd),cali(dd),'g.');plot(jd(ss),countdrop(ss),'r.'); plot(jd(tt),miss(tt),'k.');plot(jd(ff2),ppb5(ff2),'m.');plot(jd(ll),filter(ll),'y.');plot(jd(hh2),std(hh2),'c.'); plot(jd(gg2),delta(gg2),'g.');plot(jd(ii),reldir(ii),'r.');plot(jd(jj),lag(jj),'m.');plot(jd(ok),z(ok),'.'); xlabel('day of year');axis([190 220 0 12]); legend('11:rain (19)','10:wind speed (23)','9:calibration (96)', '8:count drop (95)', '7:missing data (497)', '6:O3<5ppb,>80ppb (205)', '5:filter change (30)','4:std O3 (270)', '3:delta O3 (449)','2:relative wind direction (552)' , '1:lagtime (1480)','0:remainig data (2131)'); ylabel('filter No.'); l=find(isnan(total)); figure;plot(jd(l),O3mean(l),'.');hold on;plot(jd,total,'r.'); xlabel('Day of Year'); ylabel('[O3]/ppb');title('blue: eliminated, red: remainig; excluding lag time filter'); axis([190 220 -1 90]) k=find(isnan(total_o)); figure;plot(jd(k),O3mean(k),'.');hold on;plot(jd,total_o,'r.'); xlabel('Day of Year'); ylabel('[O3]/ppb');title('blue: eliminated, red: remainig; including lag time filter'); axis([190 220 -1 90]) %j=find(isfinite(total_o)); %i=find(isnan(total_o)); %figure;plot(jd(i),slowO3(i),'.');hold on;plot(jd(j),slowO3(j),'r.'); %xlabel('Day of Year'); ylabel('[O3]/ppb');title('slowO3;blue: eliminated, red: remainig; excluding lag time filter'); %axis([190 220 -1 90]) %figure;plot(jd,O3ppb,'.');hold on;plot(jd,slowO3,'.r') %xlabel('Day of Year'); ylabel('[O3]/ppb'); %title('red:O3 ML8810, blue: O3 FRCI'); %axis([190 220 -1 90]) %Fluxes and deposition velocity jday=data2(:,1); utrue=data2(:,3); urel=data2(:,5); Tair=data2(:,9); SST=data2(:,33); lagtime=data2(:,43); % lagtime between w and O3 calculated by crosscovriance, 10 min lagtime O3w_o=data2(:,44); % w'O3' calculated with crosscovariance, 10 min lagtime, no webb correction O3mean_o=data2(:,45); % mean O3 concentration cross (ppb) O3dev_o=data2(:,46); % stdev ozone cross (ppb) O3w=data2(:,47); % O3'w' with constant lagtime of 5.1 s, and function cov, no webb correction O3mean=data2(:,48); % mean O3 concentration constant lagtime (ppb) O3dev=data2(:,49); % stdev ozone constant lagtime (ppb) Vd_o=data2(:,50); % deposition velocity 10 min lagtime (cm/s) [vdO3E,r_buz]=BuzoriusCorrection(Vd_o,urel,0.4); Vd_o=vdO3E; Vd=data2(:,51); % deposition velocity 5.1s lagtime (cm/s) [vdO3E,r_buz]=BuzoriusCorrection(Vd,urel,0.4); Vd=vdO3E; slowO3=data2(:,54); lat=data2(:,23); lon=data2(:,24); map; %excluding lag time filter %const p=find(isfinite(total)); y=find(Vd(p)>2 | Vd(p)<-2); Vdmean=mean(Vd(p(y))) Vdmedian=median(Vd(p(y))) ij=find(Vd(p(y))>0); Vdmean2=mean(Vd(p(y(ij)))) Vdmedian2=median(Vd(p(y(ij)))) figure; plot(jday(p(y)),Vd(p(y)),'.');title('Vd constant lag time excluding lag time filter'); xlabel('Day of Year');ylabel('Vd (cm*s-1)'); %Histogram x=-5:0.005:5; figure;hist(Vd(p(y)),x);title('Vd constant lag time excluding lag time filter'); xlabel('Vd / cm*s-1'); ylabel('Number of Data Points'); hold on; plot([mean(Vd(p(y))) mean(Vd(p(y)))],[0 190], 'r') %cross p=find(isfinite(z)); Vdmean_o=mean(Vd_o(p)) Vdmedian_o=median(Vd_o(p)) ij=find(Vd_o(p)>0); Vdmean_o2=mean(Vd_o(p(ij))) Vdmedian_o2=median(Vd_o(p(ij))) figure; plot(jday(p),Vd_o(p),'.'); xlabel('Day of Year');ylabel('Vd / cm*s-1');title('Vd cross correl including lag time filter'); %Histogram x=-5:0.005:5; figure;hist(Vd_o(p),x); xlabel('Vd / cm*s-1'); ylabel('Number of Data Points');title('Vd cross correl including lag time filter'); hold on; plot([mean(Vd_o(p)) mean(Vd_o(p))],[0 190], 'r') % With lagtime filter lag=data(:,6); i=find(isnan(lag)); total(i)=NaN; g=find(isfinite(total)); Vdmean3=mean(Vd(g)) Vdmedian3=median(Vd(g)) ij=find(Vd(g)>0); Vdmean4=mean(Vd(g(ij))) Vdmedian4=median(Vd(g(ij))) figure; plot(jday(g),Vd(g),'.'); xlabel('Day of Year');ylabel('Vd / cm*s-1');title('Vd const lag time including lag time filter'); %Histogramm data filtered x=-5:0.005:5; figure;hist(Vd(g),x); xlabel('Vd / cm*s-1'); ylabel('Number of Data Points');title('Vd constant lag time including lag time filter'); hold on; plot([mean(Vd(p)) mean(Vd(p))],[0 190], 'r') %cross incl lag time filter total(i)=NaN; g=find(isfinite(total_o)); Vdmean_o3=mean(Vd_o(g)) Vdmedian_o3=median(Vd_o(g)) ij=find(Vd_o(g)>0); Vdmean_o4=mean(Vd_o(g(ij))) Vdmedian_o4=median(Vd_o(g(ij))) figure; plot(jday(g),Vd_o(g),'.'); xlabel('Day of Year');ylabel('Vd / cm*s-1');title('Vd cross correl including lag time filter'); %Histogramm data filtered x=-5:0.005:5; figure;hist(Vd_o(g),x); xlabel('Vd / cm*s-1'); ylabel('Number of Data Points');title('Vd cross correl including lag time filter'); hold on; plot([mean(Vd_o(p)) mean(Vd_o(p))],[0 190], 'r')