<p><b>xinzhang</b> 2009-06-29 09:52:51 -0600 (Mon, 29 Jun 2009)</p><p>Update Chap6 for V3.1.1 release<br>
</p><hr noshade><pre><font color="gray">Modified: trunk/wrf/UsersGuide/users_guide_chap6.doc
===================================================================
--- trunk/wrf/UsersGuide/users_guide_chap6.doc 2009-06-29 15:46:18 UTC (rev 196)
+++ trunk/wrf/UsersGuide/users_guide_chap6.doc 2009-06-29 15:52:51 UTC (rev 197)
@@ -1,7 +1,7 @@
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+ࡱ
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Introduction
Data assimilation is the technique by which observations are combined with a NWP product (the first guess or background forecast) and their respective error statistics to provide an improved estimate (the analysis) of the atmospheric (or oceanic, Jovian, whatever) state. Variational (Var) data assimilation achieves this through the iterative minimization of a prescribed cost (or penalty) function. Differences between the analysis and observations/first guess are penalized (damped) according to their perceived error. The difference between three-dimensional (3D-Var) and four-dimensional (4D-Var) data assimilation is the use of a numerical forecast model in the latter.
-MMM Division of NCAR supports a unified (global/regional, multi-model, 3/4D-Var) model-space variational data assimilation system (WRF-Var) for use by NCAR staff and collaborators, and is also freely available to the general community, together with further documentation, test results, plans et
c., from the WRF-Var web-page HYPERLINK "http://www.mmm.ucar.edu/wrf/users/wrfda/Docs/user_guide_V3.1/users_guide_chap6.htm" http://www.mmm.ucar.edu/wrf/users/wrfda/Docs/user_guide_V3.1/users_guide_chap6.htm.
+MMM Division of NCAR supports a unified (global/regional, multi-model, 3/4D-Var) model-space variational data assimilation system (WRF-Var) for use by NCAR staff and collaborators, and is also freely available to the general community, together with further documentation, test results, plans etc., from the WRF-Var web-page HYPERLINK "http://www.mmm.ucar.edu/wrf/users/wrfda/Docs/user_guide_V3.1/users_guide_chap6.htm" http://www.mmm.ucar.edu/wrf/users/wrfda/Docs/user_guide_V3.1.1/users_guide_chap6.htm.
Various components of the WRF-Var system are shown in blue in the sketch below, together with their relationship with rest of the WRF system.
xb: first guess either from previous WRF forecast or from WPS/real output.
@@ -172,7 +172,7 @@
You should see wrfplus.exe
Running Observation Preprocessor (OBSPROC)
-The OBSPROC program reads observations in LITTLE_R format (a legendary ASCII format, in use since MM5 era). Please refer to the documentation at HYPERLINK "http://www.mmm.ucar.edu/mm5/mm5v3/data/how_to_get_rawdata.html" http://www.mmm.ucar.edu/mm5/mm5v3/data/how_to_get_rawdata.html for LITTLE_R format description. For your applications, you will have to prepare your own observation files. Please see HYPERLINK "http://www.mmm.ucar.edu/mm5/mm5v3/data/free_data.html" http://www.mmm.ucar.edu/mm5/mm5v3/data/free_data.html for the sources of some freely available observations and the program for converting the observations to LITTLE_R format. Because the raw observation data files could be in any of formats, such as ASCII, BUFR, PREPBUFR, MADIS, HDF, etc. Further more, for each of formats, there may be the different versions. To make WRF-Var system as general as possible, the L
ITTLE_R format ASCII file was adopted as an intermediate observation data format for WRF-Var system. Some extensions were made in the LITTLE_R format for WRF-Var applications. More complete description of LITTLE_R format and conventional observation data sources for WRF-Var could be found from the web page: HYPERLINK "http://www.mmm.ucar.edu/wrf/users/wrfda/Tutorials/2009_Jan/tutorial_presentation_winter_2009.html" http://www.mmm.ucar.edu/wrf/users/wrfda/Tutorials/2009_Jan/tutorial_presentation_winter_2009.html by click Observation Pre-processing. The conversion of the user-specific-source data to the LITTLE_R format observation data file is a users task.
+The OBSPROC program reads observations in LITTLE_R format (a legendary ASCII format, in use since MM5 era). Please refer to the documentation at HYPERLINK "http://www.mmm.ucar.edu/mm5/mm5v3/data/how_to_get_rawdata.html" http://www.mmm.ucar.edu/mm5/mm5v3/data/how_to_get_rawdata.html for LITT
LE_R format description. For your applications, you will hav!
e to pre
pare your own observation files. Please see HYPERLINK "http://www.mmm.ucar.edu/mm5/mm5v3/data/free_data.html" http://www.mmm.ucar.edu/mm5/mm5v3/data/free_data.html for the sources of some freely available observations and the program for converting the observations to LITTLE_R format. Because the raw observation data files could be in any of formats, such as ASCII, BUFR, PREPBUFR, MADIS, HDF, etc. Further more, for each of formats, there may be the different versions. To make WRF-Var system as general as possible, the LITTLE_R format ASCII file was adopted as an intermediate observation data format for WRF-Var system. Some extensions were made in the LITTLE_R format for WRF-Var applications. More complete description of LITTLE_R format and conventional observation data sources for WRF-Var could be found from the web page: HYPERLINK "http://www.mmm.ucar.edu/wrf/users/wrfda/Tutorials/2009_Jan/tutorial_presentation_winter_2009.html" http://www.mmm.uc
ar.edu/wrf/users/wrfda/Tutorials/2009_Jan/tutorial_presentation_winter_2009.html by clicking Observation Pre-processing. The conversion of the user-specific-source data to the LITTLE_R format observation data file is a users task.
The purposes of OBSPROC are:
Remove observations outside the time range and domain (horizontal and top).
Re-order and merge duplicate (in time and location) data reports.
@@ -1101,10 +1101,10 @@
-WRF-ARW V3: Users Guide 6- PAGE 4
+WRF-ARW V3: Users Guide 6- PAGE 14
-WRF-ARW V3: Users Guide 6- PAGE 7
+WRF-ARW V3: Users Guide 6- PAGE 15
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