%PARTE I
%Analisis de Cluster para obtener las conf sinopticas de viento cruzado
clear all
close all
cd /home/jacqueline/Documentos/Antartica/pre_proceso/Reanalisis_clusters
%Creando anomalias por metodo de cluster
load HGT500.mat %cargando la matriz de hgt (datos de reanalis)
REANALYSIS=HGT500;
clear HGT
%Cargando las fechas de los 5 fenomenos significativos
load Fecha_CW.mat
f=floor(Fecha_CW);
clear Fecha_CW
% get meteo data for 12 UTC
% WATCH OUT! be careful with how many attributes the meteo data has (lon,
% lat,level, time, etc)
REA_12Z=REANALYSIS(:,:,3:4:end); % (lon,lat,time) time 4 per day each 6h
% new time for meteo data
t_12z=floor(t(3:4:end));%deja solamente el dia
m_12z=month(t_12z);
% seasonal points for Reanalysis data, we want to get the climatology of
% each season during the last 10,5 years
% mr: monthly reanalysis
% s:summer, a:autumn, w:winter, p: springs
mr_s=[find(m_12z==12) find(m_12z==1) find(m_12z==2) ];
mr_a=[find(m_12z==3) find(m_12z==4) find(m_12z==5) ];
mr_w=[find(m_12z==6) find(m_12z==7) find(m_12z==8) ];
mr_p=[find(m_12z==9) find(m_12z==10) find(m_12z==11)];
% get seasonal variable and climatology
% Same but for events, we want to get the reanalysis data for all events
% and after that the anomalies (events - climatology)
% same but till 30 jun 2014
%f=f(f<=datenum(2014,06,30));
m_f=month(f);%FECHA DE MIS EVENTOS
% me: monthly events,
% s:summer, a:autumn, w:winter, p: springs
% e: events
me_s=[find(m_f==12)' find(m_f==1)' find(m_f==2)' ];%verano
me_a=[find(m_f==3)' find(m_f==4)' find(m_f==5)' ];%otono
me_w=[find(m_f==6)' find(m_f==7)' find(m_f==8)' ];%invierno
me_p=[find(m_f==9)' find(m_f==10)' find(m_f==11)'];%primavera
season=['s' 'a' 'w' 'p'];
%clear i p y
%eval:evaluar
for i=1:length(season)
% getting mean climatology
eval(['r_meanH_' season(i) '=nanmean(REA_12Z(:,:,mr_' season(i) '),3);']);
% getting seasonal reanalysis data
eval(['rH_' season(i) '=REA_12Z(:,:,mr_' season(i) ');']);
% getting seasonal reanalysis time
eval(['t_12z_' season(i) '=t_12z(mr_' season(i) ');']);
eval(['t1=t_12z_' season(i) ';']);
% tt: seasonal events time
eval(['tt_' season(i) '=f(me_' season(i) ');']);%me:eventos por estacion
eval(['t2=tt_' season(i) ';']);
% getting position of the events into reanalysis data time
%clear in
dbclear all
for p=1:length(t2)
in(p)=find(t1==t2(p));
end
% getting seasonal events in Reanalysis data
eval(['r_e_' season(i) '= rH_' season(i) '(:,:,in);']);
% getting anomalies
for y=1:length(t2) % length of t2 and hgt_e_season are equal
eval(['r_anomH_' season(i) '(:,:,y)= r_e_' season(i) '(:,:,y)-r_meanH_' season(i) ';']);
end
end
%las fechas de eventos+reanalisis son tt_a;tt_p;tt_s y tt_w (corrspondiente
%a primavera, otono, invierno y verano)
