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Simulation of radiance and progress in Joint OSSEs

This study evaluates the impact of simulated vs. real Radiosonde Observations Balloon (RAOB) data in calibration experiments using various satellite and conventional data sources. Initial results show the importance of accurate RAOB data in improving simulated radiance. Experts handling radiance data and Radiative Transfer Model (RTM) development are crucial for successful calibration. Tools like CRTM 2.0 enhance efficiency, while data experts are needed for processing Nature Run data and DBL91 simulations. Collaboration and data exchange among projects are key for handling large data sets efficiently.

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Simulation of radiance and progress in Joint OSSEs

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  1. Simulation of radiance and progress in Joint OSSEs April 30 2010

  2. Calibration experiments at NCEP and ESRL,Initial results Data used HIRS,AIRS,AMSU,MSU by GMAO GOES by NESDIS Conventional data by NCEP ESRL: May 2007 GSI NCEP: Dec 2009 GSI

  3. V200 Time series of RMSE between two experiment Zonally averaged between 20N-80N Simulated RAOB have more impact than real RAOB Purple + : Real_ESRL_CTL & REAL_ESRL_noraob Orange Open Circle: Real_CTL & REAL_CTL (May) Green Closed circle: Real_CTL & REAL_noraob Darkblue open square: Real_CTL &REAL_noraobwin Light blue closed square: Sim_CTL & Sim_noraob Magenta closed square: Sim_CTL & Sim_noraobwin

  4. Successful calibration RAOB data denial Comments?? Globally averaged RSME The simulated data impact increase with added error

  5. 200hPa V RMSE from CTL 6 hourly Averaged between 7/20-7/31 REAL different Initial condition Simulated no RAOB REAL no raob Simulated no raob wind Real no raob wind Simulated RAOB need more error

  6. Flexible Radiance data Simulation strategies at NCEP Experts for data handling and experts of RTM are different people. • Content of DBL91 • Nature Run data at foot print • 91 level 3-D data (12 Variables) • 2-D data (71 Variables) • Climatological data • All information to simulate Radiances DBL91 The DBL91 also used for development of RTM. DBL91 can be processed for other sampling such as GMAO sampling DBL91 can be processed for new observation It is an option whether DBL91 to be saved and exchange among various project, or DBL91 to be treated as temporary file produced in simulation process. This depends on size of DBL91 compare to the Nature Run. 6

  7. Nature Run (grib1 reduced Gaussian) 91 level 3-D data (12 Variables) 2-D data (71 Variables) Climatological data Observation template Geometry Location Mask Need complete NR (3.5TB) Random access to grib1 data Need Data Experts Decoding grib1 Horizontal Interpolation DBL91 Need large cpu Need Radiation experts Need Data Experts but this will be small program Running Simulation program (RTM) Post Processing (Add mask for channel, Packing to BUFR) Simulated Radiance Data 7

  8. A few issues (by Michiko) 1. Radiance and Brightness temperature IASI was saved and analyzed as scaled radiance. All other data are saved and analyzed as brightness temperature (BT) Kleespies code was written for radiance data. BT need to be converted to radiance and convert back to BT after error is added. CRTM has utility for these conversion, 2. Templates are made based on both 2005 and 2009 observing systems. We need to do calibration using 2005 data but 2009 template which include IASI, metop, and GPS data may be better for OSSE. 3. Sample scripts uses CRTM 1.2.2. Now CRTM 2.0 is available. The results may not change much but CRTM 2.0 is much efficient and some memory leak problem are fixed. Switching from 1.2.2 to 2.0 require some change in codes.

  9. A few issues (by Michiko) cont. 4. Simulation is done for each instrument and each satellite separately. amsua_n15 amsua_n16 amsua_n17 This make simulation much easier as CRTM coefficients are prepared this way and simulation can be processed as “do” loop. These files have to be combined to one file for amsua, for example, for GSI scripts using “combbufr”. This is easy and fast process requires one line in scripts. Otherwise we have to change GSI scripts in several location. (GMAO code simulate each instrument type, such as amsua, amsub,hirs2, hirs3 etc and search coefficient files within the code) 5. AMSUA on AQUA Channel number saved is combined channel number of other aqua instruments and should not be used or need to be fixed. GSI does not use channel number saved in the data.

  10. A few activities 1. Error data for AQUA Tom Kleespies contacted Tom Pagano of JPL 2. ESRL is working on calibration using new correlated error by Ron Errico. 3. ESRL is looking into vortex relocation in GSI script They may be able to generate simulated tc_vitals files. 4. Setting up DWL test code for GSI

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