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Task 1.1: Support for the WRFVar component of the CWB operational system

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Task 1.1: Support for the WRFVar component of the CWB operational system

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  1. 2010 CWB Project Annual ReviewPrincipal Investigator:Y-H. Kuo1,2Y.-R. Guo1 (WRF-Var lead)H. Liu3 (WRF-EnKF lead)J. Braun2 (Ground-based GPS lead)Fei Chen4 and Mike Barlage4(HRLDAS)Jim Bresch1 (WRF lead)CWB Visitors: Ya-Ting Tsai, Eric Chiang, Elmy Chen, Ling-Feng Hsiao, Mei-Yu Chang, Chi Pan1NCAR/MMM, 2UCAR/COSMIC, 3CISL/iMage, and 4NCAR/RAL1 December 2010

  2. Task 1: Support for the WRFVar component of the CWB operational system (OP2) and the improvement of the performance of WRFVar V3 (Y.-R. Guo, Ted Iwabuchi, Pei-Yu Chen, Eric Chiang, Ya-Ting Tsai, Mei-Hsin Chen)

  3. Task 1.1: Support for the WRFVar component of the CWB operational system • Frequent exchange of progress through the e-mails and teleconference between CWB and UCAR. Many problems were discussed and solved including CV3 BE tests, EC bogus data assimilation, GPSRO assimilation, and GSI system, etc. One interesting item is that most of the GPSPW data in NCEP prepBUFR data files are from Taiwan: • Staff visits between CWB and UCAR: • From CWB to UCAR:Elmy Chen, Eric Chiang, Chi Pan, Ling-Feng Hsiao, Der-Song Chen, J.-S. Hong, and C.-T. Fong • From UCAR to CWB: Yong-Run Guo • The main activities: • Exchange progresses reports for the 2010 project for both CWB and UCAR • CWB presentations on WRFVar • Discussion with CWB staff.

  4. Task 1.2: Improve the performance of WRFVar V3 • 1.2.1 Implementation of outer-loops with CV3 BES • Single obs --- GPSRO tests with CV3 BES and 5 outer-loops: • REF = 10 Nunit, ERR= 2.5 Nunit, Location = (111, 64,20), η = 0.55, h = 4.86km km Out# Int#. J Jb Jo 1 0.100E-01 0 8.000 0.000 8.000 0.000 1 0.100E-01 1 3.699 1.989 1.711 0.000 2 0.100E-01 0 3.704 1.989 1.715 0.000 2 0.100E-01 1 3.704 1.973 1.731 0.000 2 0.100E-01 2 3.704 1.979 1.725 0.000 3 0.100E-01 0 3.704 1.979 1.725 0.000 3 0.100E-01 1 3.704 1.978 1.726 0.000 3 0.100E-01 2 3.704 1.978 1.726 0.000 4 0.100E-01 0 3.704 1.978 1.726 0.000 4 0.100E-01 1 3.704 1.978 1.726 0.000 4 0.100E-01 2 3.704 1.978 1.726 0.000 5 0.100E-01 0 3.704 1.978 1.726 0.000 5 0.100E-01 1 3.704 1.978 1.726 0.000 5 0.100E-01 2 3.704 1.978 1.726 0.000 After the 3rd outer-loop, J, Jb, and Jo are not changed. Anomaly correlation for 4 experiments verified against NCEP analyses. • Eric Chang conducted two-week (2009121712Z to 2009122912Z) period tests for 4 experiments: 1) CV3, 2) CV3-TUNE, 3) CV3-TUNE+OUTER-LOOP, and 4) CV3-TUNE+DFI. Degraded results were obtained with the CV3-TUNE+OUTER-LOOP (without variable tuning factors for different outer-loops).

  5. Task 1.2 Improve the performance of WRFVar V3 (Cont.) • 1.2.2 Tuning for CV3 BES • Conducted literature reviews on CV3 BES: e.g. Purser et al. (2003) • Reviewed the CV3 related code in WRFVar and GSI BE codes: rdgstat_reg.f90, prewgt_reg.f90, berrorf90, etc. • Setup of CV3 BES in WRFVar: “da_setup_be_ncep_gfs.inc” • Utilization of CV3 BE in WRFVar: “da_transform_vtox.inc” • Develop the code for the different outer-loops with the variable tuning factors. • In the setup CV3 stage, there are 3 steps: • read in BE file and transfer to 3-D WRF grid; • compute the filter coefficients based the specified parameters; • Scale the vertical and horizontal scale-lengths based on the factors, and normalized the standard deviation. • The tuning factors are only related to step 3). • Single GPSREF test was conducted with the new codes, which was posted on the web page on 17 October 2010: • http://box.mmm.ucar.edu/people/guo/individual_guo/CWB/CWB_Project_2010.html

  6. Task 1.2 Improve the performance of WRFVar V3 (Cont.) 1.2.2 Tuning for CV3 BE The formulation for normalization of the standard deviation is where σnorm_k isthe normalized standard deviation and will be used in the transformation of the control variables. σk is the input standard deviation, as1 is the tuning factor for standard deviation, hlk is the tuned horizontal scale-length, vk,k depends on the tuned vertical scale-length, Mfac is the map factor, and Samp is a factor by which the amplitude at the second sweep is normalized. Sampis determined by the filter characteristics. The subscript k denotes the model level k. So the normalized standard deviation σnorm_k will be obtained by the combined effect from all tuning factors (as1) for variance, (as2) for horizontal and (as3) vertical scale-lengths. Caution must be taken to set the proper tuning factors to get reasonable increments from each of the outer-loops.

  7. Task 1.2 Improve the performance of WRFVar V3 (Cont.) 1.2.3 Technical consultation on improving the utilization of operationally available observations Eric Chiang and Yong-Run Guo worked together to carefully review the WRFVar surface data (U10, V10, T2, and Q2) assimilation code: da_sfc_wtq.inc and WRF code: module_sf_sfclay/SFCLAY1D. We made the WRFVar code consistent with the WRF code, and developed the corresponding tangent-linear and adjoint codes, which passed correctness checks. From the case (2009060818Z) study and whole month (June 2009) tests, the results showed minor but positive impact. Task 1.3: Improve the GPSRO data assimilation for CWB regional application Main problems: High level (above 10km) GPSREF data caused significant GPSREF and moisture increments at low levels (below 2km); Systematic positive bias of GPSREF (O-B) above 10km at low latitudes.

  8. Task 1.3: Improve the GPSRO data assimilation for CWB regional application Main problems: High level (above 10km) GPSREF data caused significant GPSREF and moisture increments at low levels (below 2km); Systematic positive bias of GPSREF (O-B) above 10km at low latitudes. Problem 1: Cross section plot of refractivity increments with real COSMIC refractivity data assimilation (point near 20oN and 150oE) for the 18 UTC 8 June 8 2009 case. Horizontal and vertical axes show model grid number for the east-west direction and vertical direction, respectively. Note that the refractivity profile below 6 km is rejected due to QC, but significant increments still occur in the lower levels.

  9. Problem 2: O-B statistics of absolute refractivity between COSMIC (O) and NCEP GFS (B) for CWB test period from 00Z of April 24, 2010 to 18Z of Mar 9 2010. The left and right panels show standard deviation and biases. The red curve is for the original WRFVar code, green curve is for the modified one, and the blue curve is for an additional modification using logarithmic vertical interpolation of refractivity. • Problem 1 is solved by ignoring the P-perturbation in TL/AD code • Problem 2 is solved by converting geometric height of the GPSREF data to geopotential height. • Updated code has been passed to CWB, and results are improved.

  10. Task 1.4: Training and technical consultation • 1.4.1 Consultation on CWB ZTD data assimilation • Yating Tsai, CWB, conducted a set of the experiments for a SoWMEX period, 2008060100~2008060600 with OP211, CV3-CTRL, CV3-PWV, CV3-ZTD, CV5-PWV, and CV5-ZTD. UCAR staff reviewed and discussed the results with CWB staff. Preliminary conclusions: • Ground-based data assimilation has a positive impact on the short-range QPF. • PWV assimilation performs better than ZTD assimilation • CV5 performs better than CV3 because CV3 BES have not been tuned for the 5-km domain3, but CV5 has the special BES for 5-km domain3. • Yating Tsai proposed a new strategy for ZTD assimilation with a one-way nested approach. With this ZTD assimilation, the PW in near and over Taiwan is increased, and the short-term rainfall forecast is also improved. • Based on these preliminary positive results, and a good GPS receiver network available in Taiwan, we suggest that CWB consider operational use of the GPSPW/ZTD data in NWP.

  11. 1.4.2 Provide guidance to CWB visitors at UCAR • Eric Chiang: surface observation operator: da_sfc_wtq.inc • Elmy Chen: • ported the OP211 system to the NCAR IBM (bluefire.ucar.edu) • NCAR IBM: power6, xlf version 12 compiler • CWB IBM : power5, xlf version 10 compiler • After 3 days of cycling the differences are significant. • EC-bogus experiment • GPSRO tests • Ling-Feng Hsiao: discussions to further improve 3DVAR in TWRF. (Variable tuning factors in CV3 outer-loops.

  12. 1.4.3 Technical consultation on general data assimilation issues Conducted experiments using WRFVar and GSI with identical observations from the NCEP prepBUFR file for conventional data and the BUFR file for GPSRO at 2009060818Z. Only 40% of the GPSRO data is assimilated by GSI as compared to WRFVar. The wind analysis is not sensitive to the GPSRO data, or the assimilation system (WRFVar or GSI), but the temperature and moisture are very sensitive to the GPSRO data used, and the assimilation system used. Our experiences in running GSI were provided to CWB staff (Eric Chiang).

  13. 1.4.4 Provide WRFVar training course at CWB: 3 presentations WRFVar code development: Tangent linear and adjoint code WRFVar code development: Observation operators for GPSRO, GPSZTD, and surface observations, 2-m T, Q, 10-m wind, and Psfc Formulation for wrf_to_xb and xa_to_wrf: Diagnose the pressure and geopotential height All of the presentations have been posted on the web site, and passed to CWB.

  14. Task 1: Support for the WRFVar component of the CWB operational system (OP2) and the improvement of the performance of WRFVar V3

  15. Task 2 Task 2: Test and Develop WRF/DART Ensemble Data Assimilation System for Typhoon Forecasts (Hui Liu, Jeff Anderson, and Yun-Tien Lin)

  16. Task 2.1: Modify and test WRF/DART to run in CWB’s 6-hour cycling operation • Only observations within +/-1.5 hour of analysis times are used and compared with use of all of the observations within each analysis time. • Tested various ensemble adaptive inflations for the new 6-hourly observation sets; Optimal values of 0.6/0.6/0.9 are found. • Tested sensitivity of various horizontal and vertical localizations. 1200km and 5km cutoff is determined for CWB domain. • Fixed analysis update to surface vertical velocity near high terrain, which may cause model blow-up in long period assimilation. • Point observations (PILOT, and radiosonde) near TC center (within 250 km) are excluded because of model representativeness errors. • Tuned observation error of SATEM thickness. Longer spin-up period (3-5 days) is needed for adaptive inflation for cold start. • The track and intensity of the analyses are reasonable (around 50km at later stages of the typhoons).

  17. Task 2.2: Detailed evaluation of WRF/DART performance for SOWMEX and 2008 December case • Assimilation experiments with COSMIC data for SOWMEX and 2008 December period have finished successfully. The runs shows that the new system is stable. • The RMS errors of WRF/DART analyses are comparable to NCEP analyses. • Did an extra assimilation run using all of the observations within every 6-hour analysis time window (+/- 3 hours) for SOWMEX period. The results show that the analyses and 6-hour forecasts RMS errors against radiosondes temperature and winds are very close.

  18. 2.2 Detailed evaluation of WRF/DART performance for SOWMEX Analyses and Forecasts RMSE Score CWB staff compared the DART and 3dvar analyses and forecasts against NCEP analyses for SOWMEX period. Results shows that WRF/DART analyses and forecasts are comparable to 3dvar.

  19. Task 2.2: Detailed evaluation of WRF/DART performance for SOWMEX and 2008 December case •Did assimilation experiments with/without COSMIC data for SOWMEX case. It is found that use of COSMIC data reduces water bias and RMS errors against radiosondes. The wind RMS error and bias in the upper troposphere are reduced by use of GPS data. • 48-hour ensemble forecasts are initialized from June 4 00Z. Use of COSMIC data increases rainfall over Taiwan area. • Developed an ensemble histogram tool against observations for evaluation of ensemble forecasts. The new version of obs_diag.f90 now can output histogram distribution for every observation types and any time interval and at the specified vertical layers. The histogram output is in netcdf format and can be viewed using “ncview” command. • A matlab script is also developed to make the rank histogram plots.

  20. 48-hour forecast of accumulated rainfall (mm) ( 00Z 4-6, June, 2008)

  21. Task 2.3: WRF/DART training and suport • Developed extensive training material on WRF/DART for CWB. • UCAR staff visited CWB April 11-24, 2010 and gave 3-day training on WRF/DART theory at CWB. • UCAR staff reviewed and revised the near real-time procedures and scripts for CWB operations with CWB staff at CWB. The scripts to generate the ensemble initial and boundary conditions are revised • Many communications with CWB staff on WRF/DART related questions and issues. •

  22. Task 2 Task 2: Test and Develop WRF/DART Ensemble Data Assimilation System for Typhoon Forecasts

  23. Task 3: Support and Improvement of Water Vapor Retrievals using CWB GPS Networks (John Braun)

  24. Task 3: Development and Support of GPS Water Vapor Remote Sensing Techniques at CWB Final Report • Reprocess TiMREX/SOWMEX period with improved processing strategy and uncertainty parameters. • Documentation for surface meteorology interpolation program (SmosGrd.pl). • Complete sub-task 2 (uncertainty parameter in ZTD/PW estimates). • Implement 2hr observation sessions in hourly processing.

  25. 2010 Accomplishments • Transitioned to taccop6g/taccop5g processing machines. • Test 1 – 6 h processing strategies. • Made multiple adjustments to processing schemes • Improved ZTD/PW retrievals. • TIMREX Reprocessing • Implemented improved processing strategy and uncertainty parameters to processing of TIMREX results • Documentation of surface meteorology interpolation program (SmosGrd.pl). • Improve uncertainty characteristics in PW estimates.

  26. Improvements of Hourly Processing • Objectives: • Tune hourly processing strategy so that hourly data products approach quality of daily products and implement these improvements into the operational strategy • Actions: • Tested session lengths between 1 and 6 hours to determine if increased observational length improves ZTD/PW retrievals. • Outcomes • Improvements implemented in current processing system • Near real-time ZTD/PW products should agree with daily products to ~2mm (PW) rms. • As an example, the Jan/Feb coordinate results are 2mm North/East and ~5mm Up. In August these are closer to 3mm/5mm/12mm

  27. Task 3: Support and Improvement of Water Vapor Retrievals using CWB GPS Networks

  28. Task 4: Support the Installation and Testing of the UCAR High-Resolution Land Data Assimilation System (HRLDAS) (Mike Barlage, Fei Chen, and Chia-Ling Tsai) 28

  29. Task 4.1 Up-to-date HRLDAS system with one-week testing • HRLDAS updated to be consistent with WRF v3.1 • Simulations completed over operational domains for a 17-day period beginning 15 May 2008 and ending 31 May 2008 • Major differences due to snow model changes and soil infiltration • CWB should see only small effects after upgrade to v3.1 • Additionally, CWB requested and was delivered HRLDAS consistent with WRF v3.2 and a single point driver for the Noah land surface model 29

  30. Task 4.2: Retrospective testing and parameter improvement Comparison to Taiwan observations • From university collaborators, CWB provided flux tower and soil observations at several sites: Puli, Chiayi (rice and urban), Taipei • Flux tower data at all sites had errors, namely unrealistic magnitudes and inability to close energy balance • Sites do have quality soil temperature data for significant periods. • Ran two-week simulation to compare to observations. Red and black lines are the observed soil temperatures • Blue, green, purple and orange lines are the model soil temperature at 5cm, 25cm, 70cm and 150cm. • After a short spin-up the top-layer model compares well to observations • Also have extended processing of MODIS satellite LAI/fPAR globally ºC 30

  31. Task 4: Support the Installation and Testing of the UCAR High-Resolution Land Data Assimilation System (HRLDAS) 31

  32. Task 5: Improvement of WRF model operational performance (Jim Bresch, Priscilla Mooney, Wei Wang, Bao-Jao Chen, Ya-Ting Tsai, Mei-Yu Chang, Chung-Han Lin, and Jing-Shan Hong) 32

  33. Task 5.1: Investigate the improvement of model QPF via enhancements to PBL and convective parameterization schemes. CWB selected the Kain-Fritsch cumulus parameterization for use in WRF, but its performance in the 45-km domain was not good. Domain-averaged errors 2-week SoWMEX WRF test period on domain1 by Bao-Jao Chen 850 hPa KF GD 500 hPa warm bias 300 hPa

  34. Task 5.1: Investigate the improvement of model QPF via enhancements to PBL and convective parameterization schemes. The warm bias is mostly over the ocean where there is an excess of light rainfall. Solution: Modify the convective trigger function following Ma and Tan (2009) Parcel temperature perturbation was made a function of temperature and moisture advection rather than vertical velocity.

  35. 850 hPa 850 hPa 6-h 24-h Blue areas are where the new trigger run is cooler than the standard KF run.

  36. New trigger has the desired effect of reducing areas of light rainfall without altering location of stronger systems.

  37. no fake vortex fake vortex In general, typhoon forecasts are little-changed with the new KF trigger, but slightly weaker and slightly slower. The new trigger does not produce a fake vortex (just a weak trough). New trigger function was testing in CWB’s TWRF with favorable results.

  38. Task 5.2: Assist CWB with testing of 20-km grid Mei-Yu vortex spin-up experiments initialized 00 UTC 2 May 2010

  39. Intense vortex spins up as in operational cycling run. No vortex when initialized with NCEP GFS

  40. Task 5.3: Consult and advise CWB on the operational WRF model and provide assistance to CWB visitors to UCAR. • - Modified post-processing programs ripdp and n2d64 to improve calculation of geopotential height • Investigated geopotential initialization in program real. Results show that errors introduced in real are small. • Provided nested DFI code to CWB visitor, Ya-Ting Tsai and assisted testing.

  41. 2008060100 SINGLENESTING NDOWN 700hpa Geopotential height NoDA NoDFI NoDA DFI DA DFI

  42. Task 5.3: Consult and advise CWB on the operational WRF model and provide assistance to CWB visitors to UCAR. • Provided guidance to CWB visitor, Mei-Yu Chang, on testing PBL and convective modifications to WRF

  43. Task 5: Improvement of WRF model operational performance 43

  44. Task 6: Continued interaction on WRF modeling and data assimilation system (Y.-R. Guo and Jim Bresch) • The web pages for the 2010 UCAR/CWB project were established and updated regularly. • http://www.mmm.ucar.edu/people/guo/individual_guo/CWB/CWB_Project_2010.html • This includes: • Code for WRFVar 3.1 • Shell scripts for end-to-end testing • Radiance data assimilation script • Links to WRF code page • A password-protected web page was maintained at NCAR for the review meeting’s slides • http://box.mmm.ucar.edu/individual/bresch/cwb/sep10 • The CWB WRF code web page was maintained at NCAR/MMM • http://box.mmm.ucar.edu/individual/bresch/cwb/2010/ • Data file exchanges between UCAR and CWB use the CWB ftp site: 163.29.179.171 • Teleconferences were held regularly throughout the year. 12 March, 5 May, 18 June, 20 August, and 15 November, 2010 • Yong-Run Guo, Hui Liu, and Jim Bresch from UCAR visited CWB during 2010. • Jim Bresch, NCAR, visited CWB from 1 June to 15 June 2009 for several WRF tasks and again from 1 December to 10 December for the annual review and WRF tasks.

  45. Task 6: Continued • Beginning in mid-2010 monthly progress reports were provided by UCAR to CWB • CWB visitors to UCAR were described earlier 45

  46. Task 6: Continued interaction on WRF modeling and data assimilation system 46

  47. End Thank you