<p><b>kavulich@ucar.edu</b> 2014-10-17 11:34:21 -0600 (Fri, 17 Oct 2014)</p><p>Chapter 6: A couple gen_be and other updates<br>
</p><hr noshade><pre><font color="gray">Modified: trunk/wrf/UsersGuide/Chapter_6.tex
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--- trunk/wrf/UsersGuide/Chapter_6.tex        2014-10-09 16:25:44 UTC (rev 516)
+++ trunk/wrf/UsersGuide/Chapter_6.tex        2014-10-17 17:34:21 UTC (rev 517)
@@ -1536,12 +1536,12 @@
%CHECK THE VARIABLES USED IN THIS SECTION!!!!
%%%%%%%%%%%%
-Users have three choices for background error covariance (BE) to use with WRFDA. We call them CV3, CV5, and CV6. With CV3 and CV5, the background errors are applied to the same set of the control variables: stream function ($\psi'$), unbalanced potential velocity ($\chi'$), unbalanced temperature ($T'$), unbalanced surface pressure ($ps'$), and pseudo-relative-humidity ($q'$). However, for CV6 the moisture control variable is the unbalanced part of pseudo-relative-humidity. With CV3, the control variables are in physical space, while with CV5 and CV6, the control variables are in eigenvector space. The major difference between these two categories of BE is the vertical covariance: CV3 uses a vertical recursive filter to model the vertical covariance while CV5 and CV6 use an empirical orthogonal function (EOF) to represent the vertical covariance. The recursive filters to model the horizontal covariance are also different between the three BE methods. We have not conducted a
systematic comparison of analyses based on these BE methods. However, CV3 (a BE file provided with our WRFDA system) is a global BE and can be used for any regional domain, while CV5 and CV6 BE’s are domain-dependent, which should be generated based on the forecast data from that particular domain. We can not give a recommendation of any BE method being the \textit{best}; the impact on analysis will likely vary on a case-by-case basis.
+Users have three choices for background error covariance (BE) to use with WRFDA. We call them CV3, CV5, and CV6. With CV3 and CV5, the background errors are applied to the same set of the control variables: stream function ($\psi'$), unbalanced potential velocity ($\chi_u'$), unbalanced temperature ($T_u'$), unbalanced surface pressure ($ps_u'$), and pseudo-relative-humidity ($q'$). However, for CV6 the moisture control variable is the unbalanced part of pseudo-relative-humidity. With CV3, the control variables are in physical space, while with CV5 and CV6, the control variables are in eigenvector space. The major difference between these two categories of BE is the vertical covariance: CV3 uses a vertical recursive filter to model the vertical covariance while CV5 and CV6 use empirical orthogonal functions (EOF) to represent the vertical covariance. The recursive filters to model the horizontal covariance are also different between the three BE methods. We have not conducte
d a systematic comparison of analyses based on these BE methods. However, CV3 (a BE file provided with our WRFDA system) is a global BE and can be used for any regional domain, while CV5 and CV6 BE’s are domain-dependent, which should be generated based on the forecast data from that particular domain. We can not give a recommendation of any BE method being the \textit{best}; the impact on analysis will likely vary on a case-by-case basis.
\subsection{CV3}
\label{wrfda-be-cv3}
-CV3 is the NCEP background error covariance. It is estimated in grid space by what has become known as the NMC method (Parrish and Derber 1992\footnote{CORRECT THIS DAMN CITATION Ban, J., X. Zhang, and X.-Y. Huang,2014: The impact of assimilating NCEP Stage IV Precipitation on analyses and short-range forecasts in WRFDA 4D-Var. \textit{Wea. Forecasting}, under revision.}) . The statistics are estimated with the differences between 24- and 48-hour GFS forecasts with T170 resolution (POSSIBLY INCLUDE FOOTNOTE ABOUT T-NUMBER HERE), valid at the same time of day for 357 consecutive cases over a period of one year. Both the amplitudes and the scales of the background error have to be tuned to represent the forecast error in the estimated fields. The statistics that project multivariate relations among variables are also derived from the NMC method.
+CV3 is the NCEP background error covariance. It is estimated in grid space by what has become known as the NMC method (Parrish and Derber 1992\footnote{Parrish, David F., and John C. Derber, 1992: \href{http://journals.ametsoc.org/doi/abs/10.1175/1520-0493\%281992\%29120\%3C1747\%3ATNMCSS\%3E2.0.CO\%3B2}{The National Meteorological Center's Spectral Statistical-Interpolation Analysis System}. \textit{Mon. Wea Rev.}, \textbf{120}, 1747</font>
<font color="gray">d 1763.}). The statistics are estimated with the differences between 24- and 48-hour GFS forecasts with T170 resolution\footnote{T-170 indicates that the global spectral model uses 170 waves and triangular truncation; this corresponds to approximately 1-degree resolution.}, valid at the same time of day for 357 consecutive cases over a period of one year. Both the amplitudes and the scales of the background error have to be tuned to represent the forecast error in the estimated fields. The statistics that project multivariate relations among variables are also derived from the NMC method.
The variance of each variable, and the variance of its second derivative, are used to estimate its horizontal scales. For example, the horizontal scales of the stream function can be estimated from the variance of the vorticity and stream function.
@@ -1570,20 +1570,28 @@
%%%%% PERHAPS INCLUDE SCRIPT IN SOURCE CODE, ALONG WITH README?????
-A small example dataset consisting of only three forecasts can be found at \url{http://www.mmm.ucar.edu/wrf/users/wrfda/download/testdata.html}. When you untar the \texttt{gen\_be\_forecasts\_20080205.tar.gz} file you will find three directories:
+A small example dataset consisting of only three forecasts can be found at \url{http://www.mmm.ucar.edu/wrf/users/wrfda/download/testdata.html}. When you untar the \texttt{gen\_be\_forecasts\_20080205.tar.gz} file you will find a "fc" directory with a number of sub-directories:
\scriptsize\begin{verbatim}
- >ls -al
+ >ls -al fc/
-THIS PART NEEDS TO BE FIXED WHEN YOU GET BACK TO WORK
+total 52
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020300
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020312
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020400
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020412
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020500
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020512
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020600
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020612
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020700
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020712
+drwxr-xr-x 2 users 4096 Aug 25 16:54 2008020800
--rw-r--r-- 1 users 11556492 2008020512/wrfout_d01_2008-02-06_00:00:00
--rw-r--r-- 1 users 11556492 2008020600/wrfout_d01_2008-02-06_12:00:00
--rw-r--r-- 1 users 11556492 2008020612/wrfout_d01_2008-02-07_00:00:00
\end{verbatim}
</font>
<font color="gray">ormalsize
-In the above example, only a 24-hour period (12Z 05 Feb to 12Z 06 Feb 2008) of forecasts, initialized every 12 hours, is supplied to estimate forecast error covariance. It is only for demonstration; it should not be used for actual research applications. The minimum number of forecasts required depends on the application, number of grid points, etc., but should almost always be more than a 3-week period of forecasts. Four weeks or more of forecasts are typically recommended for the NMC method.
+In the above example, only a 5-day period (00Z 03 Feb to 00Z 08 Feb 2008) of forecasts, initialized every 12 hours, is supplied to estimate forecast error covariance. It is only for demonstration; it should not be used for actual research applications. The minimum number of forecasts required depends on the application, number of grid points, etc., but should almost always be more than a 3-week period of forecasts. Four weeks or more of forecasts are typically recommended for the NMC method.
Describe gen\_be\_wrapper.ksh in this paragraph. Perhaps reference a readme file.
@@ -1607,6 +1615,8 @@
\textbf{Note:} \texttt{START\_DATE} and \texttt{END\_DATE} are the valid dates for the \emph{perturbations}, not the forecast start dates. In other words, and as shown in the example above, when you have 24-hour and 12-hour forecasts initialized at 2008020512, through 2008020612, the first and final forecast difference valid dates are 2008020612 and 2008020700, respectively.
+In each directory there are 24 hours of forecast outputs in 6-hour intervals. Therefore, users can try
+
%%%%%%%%%%%
%VERIFY ALL OF THIS!!! I think the dates are wrong!!!
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Modified: trunk/wrf/UsersGuide/users_guide_chap6.doc
===================================================================
--- trunk/wrf/UsersGuide/users_guide_chap6.doc        2014-10-09 16:25:44 UTC (rev 516)
+++ trunk/wrf/UsersGuide/users_guide_chap6.doc        2014-10-17 17:34:21 UTC (rev 517)
@@ -1,4 +1,5 @@
-ࡱ >