<p><b>guo</b> 2007-02-14 10:25:50 -0700 (Wed, 14 Feb 2007)</p><p></p><hr noshade><pre><font color="gray">Modified: trunk/wrfvar/technote/obs.tex
===================================================================
--- trunk/wrfvar/technote/obs.tex 2007-02-13 20:38:34 UTC (rev 48)
+++ trunk/wrfvar/technote/obs.tex 2007-02-14 17:25:50 UTC (rev 49)
@@ -4,7 +4,129 @@
Guo, Rizvi
\section{Observation Preprocessing}
+In general, the observation processing system can be separated into 3 modules: 1) the decoder module to convert the observations in a variety of format from the external sources to a decoder format file, i.e. LITTLE\_R format here; 2) the 3DVAR\_OBSPROC module to perform the functions for which the first guess field information is not required; and 3) the WRFVar observation processing module to perform the functions for which the first guess field information is required. In this section, only the second one, 3DVAR\_OBSPROC, is discussed. The first one, the decoder module development, is the user's responsibility, and the third one, WRFVar observation processing such as innovation calculation, background check, etc., is included in the WRFVar code (\ref{xx}). The observation preprocessor program, 3DVAR\_OBSPROC, is coded with the Fortran-90.
+The observation preprocessing, 3DVAR\_OBSPROC, provides the "conventional" observations ${\it{Y^o}}$ for ingest into WRF-Var. Here the "conventional" observations include not only the synoptic data, such as TEMP, SYNOP, etc., but also some of the retrievals from satellite measurements, such as SATEM, QuikSCAT, AIRS, Ground-based GPSPW(ZTD), and Space-born GPS refractivity, and SSMI, etc. Currently, the 3DVAR\_OBSPROC supports 21 types of observations, each type is assigned with the WMO code as listed in the table 5.1. The 2-digit codes are standard WMO code, and the 3-digit codes are the expansion in 3DVAR\_OBSPROC.
+
+\begin{table}[t]
+\begin{center}
+\vspace*{2mm}
+\caption{
+WMO code for each type of observations
+}
+\label{tab:wmocode}
+\vspace*{3mm}
+\begin{tabular}{| l | l | l | l |}
+\hline
+No. &Name & WMO code & observations \\
+\hline
+1 & SYNOP & 12, 14 & SYNOP, SYNOP MOBIL \\
+\hline
+2 & SHIP & 13 & SHIP \\
+\hline
+3 & METAR & 15, 16 & METAR, SPECT \\
+\hline
+4 & buoy & 18, 19 & BUOY \\
+\hline
+5 & PILOT & 32, 33, 34 & PILOT, PILOT SHIP, PILOL MOBIL \\
+\hline
+6 & TEMP & 35, 36, 37, 38 & TEMP, TEMP SHIP, TEMP DROP, TEMP MOBIL \\
+\hline
+7 & AMDAR & 42 & AMDAR \\
+\hline
+8 & SATEM & 86 & SATEM \\
+\hline
+9 & SATOB & 88 & SATOB (MODIS polar AMV or Geostationary AMV) \\
+\hline
+10 & AIREP & 96, 97 & AIREP \\
+\hline
+11 & GPSPW & 111 & Ground-based GPS PW (Precipitable Water) \\
+\hline
+12 & GPSZD & 114 & Ground-based GPS ZTD (Zenith Total Delay) \\
+\hline
+13 & SSMT1 & 121 & SSMT1 (temperature) \\
+\hline
+14 & SSMT2 & 122 & SSMT2 (humidity) \\
+\hline
+15 & SSMI & 125 & SSMI retrievals (PW ans surface wind speed) \\
+\hline
+16 & SSMI & 126 & SSMI Tb (brightness temperature) \\
+\hline
+17 & TOVS & 131 & TOVS soundings \\
+\hline
+18 & PROFL & 132 & Profilers wind \\
+\hline
+19 & AIRSRET & 133 & AIRS retrieved soundings \\
+\hline
+20 & BOGUS & 135 & Bogus soundings \\
+\hline
+21 & QSCAT & 281 & QuikSCAT ocean surface wind \\
+\hline
+\end{tabular}
+\end{center}
+\vspace*{-5mm}
+\end{table}
+
+
+\subsection{Input files}
+The 3DVAR\_OBSPROC requires three input files: 1) namelist.3dvar\_obs; 2) LITTLE\_R observation data file (\ref{ascii}); 3) observation error statistics file; and 4) ${\it{prebufr}}$ table file.
+
+The {\it{namelist.3dvar\_obs}} file provides the necessary information to 3DVAR\_OBSPROC program, which contains nine records (see Appendix ). The most important informations are the LITTLE\_R observation filename, analysis time window, geographic location, and the analysis domain setting, etc. In this new released version of 3DVAR\_OBSPROC, an additional namelist-record, ${\it{record9}}$, indicates the format to the processed observation output file: prebufr, ascii, or both. Users must carefully edit this {\it{namelist.3dvar\_obs}} file to meet the requirements of the applications prior to run 3DVAR\_OBSPROC.
+
+The observation data file to input 3DVAR\_OBSPROC must be in LITTLE\_R format. The LITTLE\_R file is a report-based ascii file, all observation reports can be merged together, in any order, to form a LITTLE\_R file. A complete description of LITTLE\_R format can be found from $${http://www.mmm.ucar.edu/mm5/documents/MM5\_tut\_Web\_notes/OA/OA.htm}$$ in section 6.12. In this 3DVar application, the ground-based GPS PW (precipitable water) is included in end of the header record. Optionally, if there are 7-channel SSMI brightness temperature available, they should be included in end part of the header record after GPS PW.
+
+The LITTLE\_R file is easy to be manipulated by hand, for example, add or remove certain reports from a LITTLE\_R file to identify the impacts of those reports. However, the size of the ascii file is too large for some of the remote sensing data, thus it is hard to be transferred.
+
+Currently except the Radar and satellite radiance data, the space-born GPS Radio-Occultation observation in BUFR format, SSMI brightness temperature in HDF format, etc., can also be converted to LITTLE\_R format data and processed by 3DVAR\_OBSPROC (\ref{GPSRO}).
+
+The observation error statistics file, ${\it{obserr.txt}}$, provided by our preprocessor includes the error specifications for 15 types of observations: SYNOP, SHIP, BUOY, METAR, PILOT, PROFILER, SOUND, SATEM, SATOB, AIREP, SSMI, AIRS, TOVS, SSMT1, and SSMT2, for the different observed parameters. For some types of observations, such as GPS PW (\ref{GPSPW}) and QuikSCAT sea surface wind (\ref{ascii}), the observation errors may be available from the LITTLE\_R file. If not available, a default observation errors will be assigned by 3DVAR\_OBSPROC.
+
+The ${\it{prebufr\ table\ file}}$ provided by 3DVAR\_OBSPROC is used to write out a ${\it{prebufr}}$ format observation file (\ref{bufr}). When a new type of observation is introduced, this table file must be edited, otherwise that new type of observation will not be contained in the prebufr observation file although it is included in the ascii observation file.
+
+\subsection{Tasks of Observation processing}
+
+\begin{itemize}
+
+\item
+Read the namelist file and the LITTLE\_R observation data file and screen the observations
+
+\vspace*{2mm}
+During the reading stage, the reports outside the target domain and the specific time window are all filtered out. The domain and time window information are provided by the namelist file.
+
+For a report, the data are read in level by level. Any data read in outside the range of -888888.0 to 888888.0 are regarded as the missing data. If both of pressure and height are missing, the data at the level are not ingested. If the both pressure and height are within the range and with good quality flags, a very grossly check against the reference height (Appendix ) is applied to the reported height. When $|(Ref\_height(p)-height)| > 12000 m$, the data at this level will be screened out, not ingested. For instance, the pressure and height are the values of 1000.0 Pa and 0.0 m, respectively, with good quality flags of 0. These values are within the meaningful range, but they are definitely inconsistent each other, the data at this level must be thrown away. Because the code used the ${\it{pointer/link}}$ structure, the new coming level data will be inserted into a linked list of measurements in decreasing order of pressure value. If the new coming pressure level has!
already existed, the new and existed data will be merged together. Note that here this merging procedure was performed within a coming observation report.
+
+Moreover, the observation errors for ground-based GPS PW(ZTD), are got in this reading stage from its quality flag field in LITTLE\_R file.
+
+\item
+Sort and the duplication check of the observations
+
+\vspace*{2mm}
+To prepare the sort and duplication check of the observations, the pressure need to be recovered if it is missing at certain levels. Basically, this is done under two situations: (1) if both of pressure and height can be found at the levels above and below the missing level, $p1$, $p2$ and $h1$, $h2$, then from data at these two levels, the mean temperature, $T_m$, between them can be computed and
+
+\begin{equation}
+%$$
+BB=-\frac{RT_m}{g}=\frac{h2-h1}{log(p2/p1)}
+%$$
+\end{equation}
+
+based on the hydrostatic assumption, the pressure, $p$, at the level, $h$, will be obtained as
+
+\begin{equation}
+p=p1\times{Exp}\left\{\frac{h-h1}{BB}\right\}
+\end{equation}
+
+
+(2) if the pressure and height are available at only one level, either above or below the missing level, the pressure, $p$, at the missing level could still be recovered by using the one set of known $p$ and $h$ with the help of the reference atmospheric state.
+
+Next, all observation reports are sorted by using a recursive subroutine
+based on platform (WMO code), location, ID, and name. This will make the
+duplication check easier and faster.
+
+
+
+
+\end{itemize}
+
\section{Observation Quality Control}
\section{Observation Data Formats}
@@ -15,5 +137,6 @@
\subsection{ASCII format}
\label{ascii}
+
\section{First Guess at Appropriate Time}
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