%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\chapter{Aplicação do MSD}
\label{capAplicacao_do_MSD}

\section{Estrutura}
  Atualmente o MSD consiste de três tipos de diagnósticos,
 level\textunderscore1, level\textunderscore2 e level\textunderscore higher. A aplicação básica de cada diagnostico
 é da seguinte forma:

 \begin{itemize}
  \item \$var  : Este diretorio contém os dados diários de uma determinada variável
                 (e.g. olr\textunderscore av  : dados diários de olr da NOAA (AVHRR) 
                       olr\textunderscore cam : dados diários de olr do CAM) e os códigos, scripts
                 e resultados dos calculos (level\textunderscore1, level\textunderscore2).
  \item sample : arquivos template para calcular e plotar o MSD (e.g. ano: templates 
                 para calcular anomalias).
  \item csh    : scripts c-shell para calcular e plotar arquivo o MSD utilizando os arquivos
                 template (e.g. filter: script c-shell para filtragem).
  \item fig    : todas as figuras são salvas neste diretório.
 \end{itemize}
 
 Os scripts devem ser modificados para ser utilizado com outros dados

\section{Calculos e plotagem}

 A seguir vamos descrever os cálculos de cada diagnóstico

\subsection{Nível: Level\textunderscore 1} 

%! History
%! [Created] Daehyun Kim - 20May2007
%! [Revised] Daehyun Kim - 29Apr2008
%!  Can be applied to the model which has 360 day calendar
%!  leap.eq.2 => leap.eq.0 (in the c-shell script)
%
%! Description
%! This document contains descriptions for 
%%! the calculating & plotting system of level_1 MSD
%! (MJO Simulation Diagnostics).
%
%! Please visit
%! http://climate.snu.ac.kr/mjo_diagnostics/index.htm
%! to see the figures and detailed descriptions of level_1 MSD.
%
%! The upper limit directory of this system is 'msd'.
%! This document will give descriptions starting from this 
%! directory. (e.g. msd/level_1/sample/ano/ano.sh)
%
%! $var : {variable}_{source of data}
%!  (e.g. olr_av, olr_cam, u850_snu)
%
%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
%# Before the calculation & plotting

% The daily data should be located in the directory 

% msd/level_1/$var/data

% *Fortran binary data, direct access
% (e.g. msd/level_1/olr_av/data/daily.19790101_20051231.gdat)

% Example data provided are olr_av, u850_n1 and u200_n1.
% olr_av : OLR (AVHRR)
% u850_n1 : 850hPa zonal wind (NCEP1)
% u200_n1 : 200hPa zonal wind (NCEP1) 
%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

  Prévio aos cálculos e plotagem os dados diários devem ser colocados no diretório:

 \path{ msd/level_1/$var/data}

 (os dados aqui utilizados são olr\textunderscore av, u850\textunderscore n1, u200\textunderscore n1)
 \begin{itemize}
  \item olr\textunderscore av : OLR (AVHRR)
  \item u850\textunderscore n1 : 850hPa zonal wind (NCEP1)
  \item u200\textunderscore n1 : 200hPa zonal wind (NCEP1) 
 \end{itemize}
 
%
% NOW, YOU HAVE DATA IN A PROPER DIRECTORY.
% LET'S START!

\subsubsection{ Variance Maps}

 As figuras \ref{all_gif}, \ref{sum_gif} e \ref{win_gif} são um exemplo da aplicação do ``Variance maps'' para o 
 caso de anomalia diária de Outgoing Longwave Radiation (OLR). A anomalia diária é obtida subtraindo dos dados
 diários a climatología diária. Logo os dados são filtrados com filtro passa banda (20-100 dias) de Lanczos. 
 O periodo de corte associado com a frequência mais baixa (100 dias) requer 2$\times$100 + 1 pontos para ser
 adequadamente representado. Logo nos extremos da série há uma perda de informação inevitável.

 Da variância tropical (20S-20N) e considerando todas as estações do ano (veja Figura \ref{all_gif}), a intrasazonal é 
 intensa e confinada 
 na região do oceano Indico e oceano Pacífico Oeste, com um nó (ponto de mínima variabilidade) sobre o continente marítimo 
 (ilhas da Oceania). A variabilidade
 intrasazonal consegue representar até 40\% da variância total. Durante os meses de Maio-Outubro (periodo mais quente
 do hemisfério norte), a variabilidade desloca-se para o norte e aparece um pico de variabilidade sobre a América do Norte (tropical).
 a porcentagem de variabilidade mantem-se, particularmente em volta do mar da India e um outro máximo entre as ilhas de Taiwan
 e as Filipinas. Para os meses de Novembro-Abril a variabilidade mais intensa desloca-se para o Sul e a extensão zonal aumenta
 considerávelmente, chegando a ter aproximadamente 180 graus. A estrutura em torno da Australia aparenta ter 3 modos com nós
 ao nordeste e noroeste da Australia, sobre a América do Sul fica evidente um sinal forte sobre o Sudeste da América do Sul.

 As características acima descritas mudam ao se analisar ventos, seja em 850mb ou 200mb. Isto deve-se em parte que a OLR
 é associado com as nuvens as quais estão relacionadas com processos convectivos. Neste tipo de campo, os efeitos do acoplamento
 dinâmica-física são mais intensos e com isto a dispersão de informação é menor e as estruturas são mais confinadas. Os campos
 dinâmicos como o vento em 200mb, a dispersão é maior devido ao menor acoplamento com a física e a informação se espalha com mais
 facilidade.

\subsubsection{ Time Series Power Spectra}

% * Order of calculations & plotting

\begin{description}
 \item[a. aave   :] Média da área antes de calcular o espectro 
                    (de potência)
          % area averging before calculate power spectra
 \begin{description}
  \item [Calculation ::] msd/level\textunderscore 1/csh/aave/aave.sh
  \item [Results     ::] msd/level\textunderscore 1/\$var/data/\$\{region\}.[win/sum].series
               ===> série temporal da média da área %area averaged time series
 \end{description}

 \item[b. tsps   :] cálculo do espectro utilizando médias espaciais na área %calculate power spectra using area averaged data
 \begin{description}
  \item [Calculation ::] msd/level\textunderscore 1/csh/tsps/tsps.sh
  \item [Results     ::] msd/level\textunderscore 1/\$var/tsps/\$\{region\}.[win/sum]
               ===>espectro de potência % power spectra 

  \item [Plotting    ::] msd/level\textunderscore 1/csh/tsps/fig.sh
  \item [Figures     ::] msd/level\textunderscore 1/fig/tsps/\$var/\$\{region\}.[win/sum].gif
 \end{description}
\end{description}

\subsubsection{  EOFs}

% * Order of calculations & plotting

\begin{description}
 \item [a. anom   :] veja 1.a %go to 1.a

 \item [b. filter :] veja 1.b %go to 1.b

 \item [c. 5x5    :] interpola os dados 1.b para a resolução 5x5 %interpolate filtered (1.b) data to have 5'x5' resolution

 \begin{description}
  \item [Calculation ::] msd/level\textunderscore 1/csh/5x5/5x5.sh
  \item [Results     ::] msd/level\textunderscore 1/\$var/data/daily.5x5.anom.\$\{period\}.gdat
               ===> interpola anomalias (PC projetada) %interpolated anomaly data (for projected PC)
  \item [            ::] msd/level\textunderscore 1/\$var/data/daily.5x5.filt.20-100.lanz.100.\$\{period\}.gdat
               ===> interpola dados filtrados (para a EOF) %interpolated filtered data (for eof)
 \end{description}

 \item [d. eof    :] calcula as EOFs %calculate EOFs (empirical orthogonal function) 
  \begin{description}
   \item [Calculation ::] msd/level\textunderscore 1/csh/eof/eof.sh
   \item [Results     ::] msd/level\textunderscore 1/\$var/eof/[win/sum]/eof.pct
               ===> porcentagem de variância %percentage variance
   \item [          ::] msd/level\textunderscore 1/\$var/eof/[win/sum]/eof.pct.gdat
               ===> untilizado para as figuras da porcentagem de variância %used in percentage variance plotting
   \item [          ::] msd/level\textunderscore 1/\$var/eof/[win/sum]/eof.ev
               ===> eigen vectors
   \item [          ::] msd/level\textunderscore 1/\$var/eof/[win/sum]/eof.ts
               ===> série temporal da PC % PC time series
   \item [          ::] msd/level\textunderscore 1/\$var/eof/[win/sum]/eof.ts.pr
               ===> série temporal da PC projetada % projected PC time series
  \end{description}

  \item [e. pcps   :] calcula o espectro utilizando a série temporal
                      da PC projetada 
                      %calculate power spectra using projected PCs (3.b)
   \begin{description}
    \item [Calculation ::] msd/level\textunderscore 1/csh/eof/pcps.sh
    \item [Results     ::] msd/level\textunderscore 1/\$var/eof/[win/sum]/pcps.ts0[1/2/3/4/5].[win\/sum]
               ===> espectro a partir da PC projetada %power spectra from projcected PC time series

   \item [Plotting    ::] msd/level\textunderscore 1/csh/eof/fig.sh
   \item [Figures     ::] msd/level\textunderscore 1/fig/eof/\$var/eof.[win\/sum].gif
               ===> eigen vectors
   \item [           ::] msd/level\textunderscore 1/fig/eof/\$var/pct.[win/sum].gif
               ===> porcentagem de variância % percentage variance
   \item [           ::] msd/level\textunderscore 1/fig/eof/\$var/pcps.ts0[1\/2\/3\/4\/5].[win\/sum].gif
               ===> espectro de potência utilizando PCs projetadas % power spectra using projected PCs
   \end{description}
\end{description}

\subsubsection{ Lag Correlations}

% * Order of calculations & plotting

\begin{description}
 \item[a. ano    :] veja 1.a % go to 1.a

 \item[b. filter :] veja 1.b %go to 1.b

 \item[c. 5x5    :] veja 3.d % go to 3.d

 \item[d  eof    :] veja 3.d %go to 3.d

 \item[e. pcl    :] calcula correlação defasada entre PC1 e PC2 %calculate lead-lag correlation coefficients between PC1 and PC2 from 3.d

  \begin{description}
   \item[Calculation ::] msd/level\textunderscore 1/csh/pcl/pcl.sh
   \item[Results     ::] msd/level\textunderscore 1/\$var/eof/[win/sum]/pcl.llreg\textunderscore 2d.gdat
               ===> coeficientes da correlação defasada %lag correlation coefficients

   \item[Plotting    ::] msd/level\textunderscore 1/csh/pcl/fig.sh
   \item[Figures     ::] msd/level\textunderscore 1/fig/pcl/\$var/pcl.[win/sum].gif
               ===> coeficientes de correlação defasada entre PC1, PC2 e EOF 
                    %lag correlation between PC1 and PC2 from EOF
  \end{description}

 \item[ f. zm     :] médias meridionais/zonais dos dados filtrados 
                    %meridionally/zonally averaging filtered data (1.b)

   \begin{description}
    \item[Calculation ::] msd/level\textunderscore 1/csh/zm/zm.sh
    \item[Results     ::] msd/level\textunderscore 1/\$var/data/daily.filt.20$-$100.lanz.100.10S10N.\$\{period\}.gdat
               ===> média meridional (10S$-$10N) %meridionally averaged (10S$-$10N) 
    \item[          ::] msd/level\textunderscore 1/\$var/data/daily.filt.20-100.lanz.100.80E100E.\$\{period\}.gdat
               ===> média zonal (80E$-$100E) %zonally average (80E$-$100E)
    \item[          ::] msd/level\textunderscore 1/\$var/data/daily.filt.20-100.lanz.100.115E135E.\$\{period\}.gdat
               ===> média zonal (115E-135E) % zonally average (115E-135E)
   \end{description}

 \item[g. lgc    :] calculando os coeficientes de correlação defasada
                    entre séries temporais das médias (area, 2.a) e as médias
                    zonais/meridionais dos dados filtrados (4.f). 
             %calculate lead-lag correlation coefficients between
             %area averaged time series (2.a) and meridionally/zonally averaged
             %filtered data (4.f)

  \begin{description}
   \item[Calculation ::] msd/level\textunderscore 1/csh/lgc/lgc.sh
   \item[Results     ::] msd/level\textunderscore 1/\$var/lgc/east.[win\/sum].llreg\textunderscore 2d.gdat
   \item[            ===>] propagação para leste % eastward propagation
   \item[           ::] msd/level\textunderscore 1/\$var/lgc/north[1\/2].llreg\textunderscore 2d.gdat
   \item[            ===>] propagação para norte % northward propagation
                    (1 $=$ oceano Indico, 2 $=$ Pacífico oeste)
                    %(1 $=$ indian ocean, 2 $=$ western Pacific)
  
   \item[Plotting    ::] msd/level\textunderscore 1/csh/lgc/fig.sh
   \item[Figures     ::] msd/level\textunderscore 1/fig/lgc/\$var/east.[win\/sum].gif
   \item[           ::] msd/level\textunderscore 1/fig/lgc/\$var/north.[io\/wp].gif

  \end{description}
\end{description}

%! * Contact : Daehyun Kim (kim@climate.snu.ac.kr)

%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
%!!! Last updated in 26May2007 by Daehyun Kim
%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!


%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
%!!!!!!!!!!!!! MJO Simulation Diagnostics - LEVEL 2 !!!!!!!!!!!!!!
%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
%!!!!! DRAFT DRAFT DRAFT DRAFT DRAFT DRAFT DRAFT DRAFT DRAFT !!!!!
%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
%
%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
%! This is draft version of MSD calculation system.
%! Please send feedback to kim@climate.snu.ac.kr
%!  - Daehyun Kim
%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
%
%! History
%! [Created] Daehyun Kim - 25May2007
%! [Revised] Daehyun Kim - 27Sep2007
%! [Revised] Daehyun Kim - 21Apr2008
%!  Include WK99, coherence squared and phase diagram
%!  and MJO life cycle composite diagnostics
%! [Revised] Daehyun Kim - 29Apr2008
%!  Can be applied to the model which has 360 day calendar
%!  leap.eq.2 => leap.eq.0 (in the c-shell script)
%
%! Description
%! This document contains descriptions for 
%! the calculating & plotting system of level_2 MSD
%! (MJO Simulation Diagnostics).
%
%! Please visit
%! http://climate.snu.ac.kr/mjo_metrics/index.htm
%! to see the figures and detailed descriptions of level_2 MSD.
%
%! The upper limit directory of this system is 'msd'.
%! This document will give descriptions starting from this 
%! directory. (e.g. msd/level_2/sample/ano/ano.sh)
%
%! $var : {variable}_{source of data}
%!  (e.g. olr_av, olr_cam, u850_snu)
%
%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
%# Before the calculation & plotting
%
% Level 2 metrics calculation needs data from level 1 metrics.
% (e.g. daily anomaly data, daily filtered data)
% See msd/level_1/README_LEVEL_1 to know how to calculate them.
%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

\subsection{Nível: Level\textunderscore 2} 

  Nesta parte do documento descreve-se o nível level\textunderscore 2. Que inclue
 cálculos de coherencia quadrada, diagramas de fase e cíclo de vida
 da MJO como calculados em WK99

\subsubsection{ Space-Time Power spectra}

% * Order of calculations & plotting
\begin{description}
 \item[a. ano    :]  veja nível 1 % go to Level 1 - 1.a

 \item[b. zm2    :]  média meridional (10S - 10N) dos dados brutos e da anomalia %meridionally averaging (10S-10N) raw and anomaly data

 % The detailed description of each diagnostics is refered to,
  \begin{description}
   \item[Calculation ::] msd/level\textunderscore 2/csh/zm2/zm2.sh
   \item[Results     ::] msd/level\textunderscore 1/\$var/data/daily.10S10N.\$\{period\}.gdat
               ===> média meridional (10S - 10N) dos dados brutos % meridionally averaged (10S$-$10N) raw data
   \item[           ::] msd/level\textunderscore 1/\$var/data/daily.anom.10S10N.\$\{period\}.gdat
               ===> média meridional (10S - 10N) da anomalia %meridionally averaged (10S$-$10N) anomaly data
  \end{description}

 \item[ c. stps    :] calcular o espectro de potência espaço-tempo %calculate space-time power spectra

   * Para todas as estações % * all season data
  \begin{description}
   \item[Calculation ::] msd/level\textunderscore 2/csh/stps/stps.all.sh
               ===> para todas as estações (com ciclo anual) %for all season data (with annual cycle)
   \item[Results     ::] msd/level\textunderscore 2/stps/all/\$var/\$var
               ===> espectro de potência espaço-tempo utilizando dados com todas as estações do ano %space-time power spectra using all season data

   \item[Plotting    ::] msd/level\textunderscore 2/csh/stps/fig.all.sh
   \item[Figures     ::] msd/level\textunderscore 2/fig/stps/all/\$var.all.gif
  \end{description}

  * dados separados por estações do ano %* seasonally stratified data
  \begin{description}
   \item [Calculation ::] msd/level\textunderscore 2/csh/stps/stps.sea.sh
               ===> para as estações do ano (sem ciclo anual) % for seasonally stratified data (without annual cycle)
   \item [Results     ::] msd/level\textunderscore 2/stps/[win/sum]/\$var/\$var
               ===> espectro de potência espaço-tempo utilizando dados separados por estações do ano % space-time power spectra using seasonally stratified data

   \item [Plotting    ::] msd/level\textunderscore 2/csh/stps/fig.sea.sh
   \item [Figures     ::] msd/level\textunderscore 2/fig/stps/[win/sum]/\$var.[win/sum].gif
  \end{description}
 
 \item [d. filter :] filtrando anomalia diária utilizando filtro de lanczos %filtering daily anomaly using Lanczos filter

  \begin{description}
   \item [Calculation ::] msd/level\textunderscore 1/csh/filter/filter.sh
   \item [Results     ::] msd/level\textunderscore 1/\$var/data/daily.filt.20-100.lanz.100.period.gdat
               ===> filtro passa banda 20-100 dias utilizando filtro de Lanzos 201 pontos % 20-100 day filtered data using 201-points Lanczos filter
  \end{description}
 
 \item [d. var    :] calcula variância usando anomalias e dados filtrados % calculate variance using anomaly and filtered data

  \begin{description}
   \item [Calculation ::] msd/level\textunderscore 1/csh/var/var.sh
   \item [Results     ::] msd/level\textunderscore 1/\$var/var/raw.[all/win/sum].gdat
   \item [           ::] msd/level\textunderscore 1/\$var/var/fil.[all/win/sum].gdat

   \item [Plotting    ::] msd/level\textunderscore 1/csh/var/fig.sh
   \item [Figures     ::] msd/level\textunderscore 1/fig/var/\$var/all/*gif - todas as estações %all season
   \item [$\text{      }$]              msd/level\textunderscore 1/fig/var/\$var/sum/*gif - verões % summer
   \item [$\text{      }$]              msd/level\textunderscore 1/fig/var/\$var/win/*gif - invernos %winter
  \end{description}
\end{description}

\subsubsection{ Combined EOF}

% * Order of calculations & plotting


 \begin{description}

  \item [a. anom   :] veja Nível 1 ===> para olr, u850, u200 
                %go to Level 1 1.a ===> for olr, u850, u200

  \item [b. filter :] veja Nível 1 ===> para olr, u850, u200
                %go to Level 1 1.b ===> for olr, u850, u200

  \item [c. zm3    :] média meridional (15S-15N) da anomalia e dos dados filtrados % meridionally averaging (15S-15N) anomaly and filtered data
    
  \begin{description}
   \item[Calculation ::] msd/level\textunderscore 2/csh/zm3/zm3.sh
   \item[Results     ::] msd/level\textunderscore 1/\$var/data/daily.anom.15S15N.\$\{period\}.gdat
               ===> meridionally averaged (15S-15N) anomaly data
   \item[           ::] msd/level\textunderscore 1/\$var/data/daily.filt.20-100.lanz.100.10S10N.\$\{period\}.gdat
               ===> meridionally averaged (15S-15N) filtered
  \end{description}

  \item [d. ceof   :] Combined EOF

  \begin{description}
   \item[Calculation ::] msd/level\textunderscore 2/csh/ceof/ceof.sh
   \item[Results     ::] msd/level\textunderscore 2/\$var/ceof/ceof.pct
               ===> porcentagem de variância %percentage variance
   \item[           ::] msd/level\textunderscore 2/\$var/ceof/ceof.pct.gdat
               ===> utilizada em plots da porcentagem de variância %used in percentage variance plotting
   \item[           ::] msd/level\textunderscore 2/\$var/ceof/ceof.var
               ===> porcentagem de variância explicada por cada modo para cada varíavel %percentage variance explained by each mode for each variable
   \item[           ::] msd/level\textunderscore 2/\$var/ceof/ceof.ev
               ===> eigen vectors
   \item[           ::] msd/level\textunderscore 2/\$var/ceof/ceof.ts
               ===> PC time series
   \item[           ::] msd/level\textunderscore 2/\$var/ceof/ceof.ts.pr
               ===> projcected PC time series

   \end{description}
   \item[e. sp256   :] calcula o espectro de potência utilizando
            PCs; 183-dias dos dados diários são acomodados em 
            segmentos de 256-dias.
           % calculate power spectra using PCs
           % : 183-day daily data is padded onto 256-day segment

   \begin{description}
    \item[Calculation ::] msd/level\textunderscore 2/csh/ceof/sp256.sh
    \item[Results     ::] msd/level\textunderscore 2/ceof/sp256.ts0[1/2]
               ===> espectro de potência da PC1 e PC2 %power spectra from PC1 and PC2
   \end{description}

   \item[f. pcl     :] calcula correlações defasadas entre PC1 e PC2 de 2.d %calculate lead-lag correlation coefficients between PC1 and PC2 from 2.d

   \begin{description}
    \item[Calculation ::] msd/level\textunderscore 2/csh/ceof/pcl.sh
    \item[Results     ::] msd/level\textunderscore 2/ceof/pcl.llreg\textunderscore 2d.gdat
               ===> coeficientes de correlação defasada %lag correlation coefficients
   \end{description}

   \item[g. crsp    :] espectro cruzado entre PC1 e PC2 da CEOF % cross-spectra between PC1 and PC2 from CEOF

   \begin{description}
    \item[Calculation ::] msd/level\textunderscore 2/csh/ceof/crsp.sh
    \item[Results     ::] msd/level\textunderscore 2/ceof/crsp
               ===> coherência quadrado e fase entre PC1 e PC2 %coherence squared and phase between PC1 and PC2
    \item[          ::] msd/level\textunderscore 2/ceof/crsp.moch
               ===> coherência quadrado média entre 30-80 dias %coherence squared averaged between 30-80 days period

   \item[Plotting    ::] msd/level\textunderscore 2/csh/ceof/fig.sh
   \item[Figures     ::] msd/level\textunderscore 2/fig/ceof/ceof.gif
               ===> eigen vectors
  \item[            ::] msd/level\textunderscore 2/fig/ceof/pct.gif
               ===> porcentagem de variância %percentage variance
  \item[            ::] msd/level\textunderscore 2/fig/ceof/sp256.ts0[1/2].gif
               ===> espectro de potência utilizando PCs projetadas %power spectra using projected PCs
  \item[            ::] msd/level\textunderscore 2/fig/ceof/pcl.gif
               ===> correlação defasada entre PC1 e PC2 % lag correlation between PC1 and PC2
  \item[            ::] msd/level\textunderscore 2/fig/ceof/crsp.gif
               ===> coherência quadrada e fase entre PC1 e PC2 % coherence squared and phase between PC1 and PC2
  \end{description}
\end{description}

\subsubsection{ MJO Life cycle composite}

\begin{description}
% * Order of calculations & plotting

 \item[a. ceof    :] veja Nível 2 (CEOF) %go to Level 2 2. Combined EOF

 \item[b. pre\textunderscore comp:] noramalização da PC 1/2 e determina amplitudes e fase %normalize PC 1/2 and determines amplitudes and phases
 
  \begin{description} 
   \item[Calculation ::] msd/level\textunderscore 2/csh/comp/pre\textunderscore comp.sh
   \item[Results     ::] msd/level\textunderscore 2/comp/data/amp\textunderscore pha
               ===> amplitude e fase da PC 1/2 noramlizadas %amplitude and phase of normalized PC 1/2
  \end{description} 

 \item[c. comp    :] composto %composite the 2d(lon.-lat.)/3d(lon.-pressure) fields

  \begin{description}
   \item[Calculation ::] msd/level\textunderscore 2/csh/comp/comp.sea.sh
   \item[Results     ::] msd/level\textunderscore 2/comp/\$var/comp.[win/sum].gdat
   \item[            ===>] composto em 8 fases %composited data in 8 phases
                 msd/level\textunderscore 2/comp/\$var/n\textunderscore comp.[win/sum].gdat
   \item[            ===>] número de dias por cada fase (para plotagem) % number of days for each phases (for plotting)

   \item[Plotting    ::] msd/level\textunderscore 2/csh/comp/fig\textunderscore 2d.sea.sh
   \item[Figures     ::] msd/level\textunderscore 2/fig/comp/2d/comp.\$var.[win/sum].gif
   \item[            ===>] campo composto (lon-lat) % composited field (longitude-latitude)

   \item[Plotting    ::] msd/level\textunderscore 2/csh/comp/fig\textunderscore 2d.flux\textunderscore with\textunderscore olr.sea.sh
   \item[Figures     ::] msd/level\textunderscore 2/fig/comp/2d\textunderscore olr/comp.\$var.[win/sum].gif
   \item[            ===>] campo composto com contornos de OLR (lon-lat) % composited field with contoured OLR (longitude-latitude)

   \item[Plotting    ::] msd/level\textunderscore 2/csh/comp/fig\textunderscore wind.sea.sh
   \item[Figures     ::] msd/level\textunderscore 2/fig/comp/wind/comp.\$var.[win/sum].gif
   \item[            ===>] campo composto com vetores de vento (lon-lat) % composited field with wind vectors (longitude-latitude)

   \item[Plotting    ::] msd/level\textunderscore 2/csh/comp/fig\textunderscore 3d.sea.sh
   \item[Figures     ::] msd/level\textunderscore 2/fig/comp/3d/comp.\$var.[win/sum].gif
   \item[            ===>] campo composto (longitude-altura) % composited field (longitude-height)
                
  \end{description}
\end{description}

\subsubsection{ Wheeler-Kiladis diagrams}

% * Order of calculations & plotting
\begin{description}
 \item[a. anom   :] veja Nível 1 1.a ===> para olr, u50, u200 % go to Level 1 1.a ===> for olr, u850, u200

 \item[b. seg    :] faz segmentos %make segments
  \begin{description}
   \item[Calculation ::] msd/level\textunderscore 2/csh/wk99/wk99\textunderscore 1\textunderscore seg.sh
   \item[Results     ::] msd/level\textunderscore 2/wk99/\$var/data/seg96\textunderscore over60\textunderscore [sym/asy].gdat
   \item[            ===>] segmentos de 96 dias com 60 dias de overlap (campos simétricos/antisimétricos) %96 days segments with 60 days overlab (symmetric/antisymmetric)
  \end{description}

 \item[c. power  :] calcula potência %calculate power

  \begin{description}
   \item [Calculation ::] msd/level\textunderscore 2/csh/wk99/wk99\textunderscore 2\textunderscore power.sh
   \item [Results     ::] msd/level\textunderscore 2/wk99/\$var/power/power.[sym/asy].gdat
   \item [           ===>] espectro número de onda - frequência (simétrico/antisimétrico) % wavenumber-frequency power spectra (symmetric/antisymmetric)

  \end{description}
 \item[d. norm   :] normalizar a potência % normalize the power


 \begin{description}
  \item[Calculation ::] msd/level\textunderscore 2/csh/wk99/wk99\textunderscore 3\textunderscore norm.sh
  \item[Results     ::] msd/level\textunderscore 2/wk99/\$var/power/norm.[sym/asy].gdat
  \item[             ===>] espectro de potência (número de onda - frequência) normalizado  (simétrico/antisimétrico) % normalized wavenumber-frequency power spectra (symmetric/antisymmetric)
  \item[Results     ::] msd/level\textunderscore 2/wk99/\$var/power/back..gdat
  \item[             ===>]  espectro de potência background %background wavenumber-frequency power spectra

  \item[Plotting    ::] msd/level\textunderscore 2/csh/wk99/fig.sh
  \item[Figures     ::] msd/level\textunderscore 2/fig/wk99/wk99.\$var.gif
  \item[             ===>] fig. do espectro de potência normalizado % normalized wavenumber-frequency power spectra (symmetric/antisymmetric)

 \end{description}
\end{description}

\subsubsection{ 2D cross spectra between OLR and wind fields}

% * Order of calculations & plotting
\begin{description}

 \item[a. anom   :] veja Nível 1 1.a ===> para olr, u850, u200 %go to Level 1 1.a ===> for olr, u850, u200

 \item[b. seg    :] faz segmentos %make segments

  \begin{description}
   \item[Calculation ::] msd/level\textunderscore 2/csh/coh2/coh2\textunderscore 1\textunderscore seg.sh
   \item[Results     ::] msd/level\textunderscore 2/coh2/\$var/data/seg256\textunderscore over200\textunderscore sym\textunderscore asy.gdat
   \item[            ===>] segmentos de 256 dias com 20 dias de overlap %256 days segments with 200 days overlab (symmetric/antisymmetric)
  \end{description}
 \item[c. power  :] calcula potência % calculate power

 \begin{description}
  \item[Calculation ::] msd/level\textunderscore 2/csh/coh2/coh2\textunderscore 2\textunderscore power.sh
  \item[Results     ::] msd/level\textunderscore 2/coh2/\$var/power/power.[sym/asy].gdat
  \item[             ===>] espectro de potência e co-quadratura (simétrico/antisimétrico) % wavenumber-frequency power spectra and co-/quadrature- spectra (symmetric/antisymmetric)

  \item[            ::] msd/level\textunderscore 2/coh2/\$var/power/coh2.[sym/asy].gdat
  \item[             ===>] coherência (número de onda-frequência) e fase entre OLR e os campos de vento (simétrico/antisimétrico) %wavenumber-frequency coherence and phase between OLR and wind fields (symmetric/antisymmetric)

  \item[Plotting    ::] msd/level\textunderscore 2/csh/coh2/fig.sh
  \item[Figures     ::] msd/level\textunderscore 2/fig/coh2/coh2.\$var.gif
  \item[             ===>] coherência (número de onda-frequência) e fase entre OLR e os campos de vento (simétrico/antisimétrico) %wavenumber-frequency coherence and phase between OLR and wind fields (symmetric/antisymmetric)

 \end{description}
\end{description}