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Eta RCM Predictions of Warm Season Precipitation over North America: Sensitivity to Initial Land States and Domain Size

This presentation outlines the development of the Eta Regional Climate Model (RCM) and its predictions of warm season precipitation over North America. It explores the sensitivity of the model to initial land states and choice of domain size. The study compares the results of different experiments and provides preliminary conclusions for future work.

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Eta RCM Predictions of Warm Season Precipitation over North America: Sensitivity to Initial Land States and Domain Size

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  1. Warm Season Precipitation Predictions over North America with the Eta Regional Climate Model Model Sensitivity to Initial Land States and Choice of Domain Size The 30th Climate Diagnostic Prediction Workshop (Oct.24 - 28, 2005) State College, PA Rongqian Yang and Kenneth Mitchell Environmental Modeling Center This development is sponsored by the GAPP program of NOAA/OAR/OGP National Centers for Environmental Prediction

  2. Presentation Outline • Brief Introduction of the Eta RCM • Model Predictions using CFS Hcst data • Initial starting time (10 members from CFS, Mid April to Early May out to 6 months) • Land States from Reanalysis II and Regional Reanalysis • Big vs Small Domain • 2004 results (NAME period, Precip, 500h, T2m etc.) • Preliminary Conclusions • Future Work

  3. The Eta Regional Climate Model Development at NCEP • Developed: uses very recent version of Eta Model physics • As implemented in NCEP Regional Reanalysis • As implemented in operational NCEP Eta on 24 Jul 01 • Virtually exact match to Eta model in Regional Reanalysis (R/R) • R/R domain and grid (32-km, 45-levels, large R/R domain) • R/R Eta model physics, e.g. Noah Land Model 2.3, with 4 soil layers

  4. The Eta Regional Climate Model Development at NCEP (Cont’d) • Daily updates of several surface boundary fields • Daily CFS predicted SST (or observed 1-deg weekly Reynolds/Stokes SST ) • Satellite NDVI-based 0.15-degree monthly greenness (NESDIS) • Seasonal 1.0-deg snow-free albedo climatology (NASA) • Initial land states of soil moisture and soil temperature • Soil moist/temp from : • Regional Reanslysis • Global Reanalysis II • Snow depth: USAF operational 47-km daily global snow depth

  5. Model Prediction (Experiments) • Tests of different initial land states (GR2 or R/R) • Test with both big and small domain size • Predicted Lateral Boundary Conditions (CFS Hindcast) • Predicted SSTs (CFS Hindcast) • 10 summer members (mid-April/early May through mid-November) • Currently 2004 (summer of NAME field campaign) • 2000, 2001, 2002, and 2003 under way (to achieve 5yr model climo) • Ultimate goal is to execute 10-20 yrs

  6. The Big Domain

  7. The Small Domain

  8. Focus Issues • Model's sensitivity to initial land states • Choice of domain size • Full prediction mode (i.e. using CFS predicted LBC and SSTs) • To see if the regional model shows any skill in seasonal prediction mode, if any, where (in ensemble sense)? • Focusing on precipitation over the CONUS domain and whether the skills are better than CFS

  9. CFS Hcst RCM RCM/R2 RCM/RR CPC Analysis All missed this heavy rain Big Domain 10 Member Mean June Precipitation Just a Hint

  10. 10 Member Mean June Precipitation CFS Hcst RCM/R2 RCM/RR CPC Analysis All missed this heavy rain with small domain too Nothing Here Small Domain

  11. CFS Hcst RCM/R2 NAM RCM/RR CPC Analysis NAM: North American Monsoon Big Domain 10 Member Mean July Precipitation NAM

  12. 10 Member Mean July Precipitation CFS Hcst RCM/R2 RCM/RR CPC Analysis NAM is weaker compared to Big Domain Small Domain

  13. 10 Member Mean August Precipitation CFS Hcst RCM/R2 RCM/RR CPC Analysis Sustained NAM Big Domain

  14. 10 Member Mean August Precipitation CFS Hcst RCM/R2 RCM/RR CPC Analysis Small Domain

  15. 10 Member Mean JJA Precipitation CFS Hcst RCM/R2 RCM/RR CPC Analysis Dry in Southern Great Plains Big Domain

  16. 10 Member Mean JJA Precipitation CFS Hcst RCM/R2 RCM/RR CPC Analysis Less dry in Southern Great Plains than the results using big domain Small Domain

  17. CFS Hcst RCM/R2 RCM/RR RR Eta-RCM and CFS Temperature is somewhat warmer in central US than the RR verification Orography signatures are much better revealed in RCM than in Global CFS Big Domain 10 Member Mean June 2m Temperature

  18. 10 Member Mean June 2m Temperature CFS Hcst RCM/R2 RCM/RR RR Analysis Eta-RCM temperature is somewhat warmer than RR verification Small Domain

  19. 10 Member Mean June 500mb GPH RCM/R2 CFS Hcst RR Analysis RCM/RR GPH: Geo-potential Height 500mb GPH is low compared to RR, RCM/R2 Better Big Domain

  20. 10 Member Mean June 500mb GPH RCM/R2 CFS Hcst RR Analysis RCM/RR 500mb GPH is high compared to RR verification Small Domain

  21. Total Soil Moisture Soil T Temp GR2 cooler 0-100cm percentage of Soil Saturation 0-10 cm Soil Moisture GR2 drier Diffs in Initial Land States from One Member (April, 23) Comparison of the two Initial Land States

  22. Comparison of May Predicted Fields (Difference Fields: EtaRCM with GR2 Land States minus EtaRCM with RR Land States) Latent Heat 500mb GPH 200mb GPH Precip

  23. Comparison of Area-avgd Precipitation Timeseries (over CONUS) Area Avgd Precip is low at the beginning of integration with big domain Green: GR2 land states Yellow: R/R land states Small Domain Big Domain

  24. Other Comparisons between the two domains using GR2 and RR land states

  25. Big with R2 LS CFS Hindcast Big with R/R LS Small with R2 LS Small with R/R LS Regional Reanalysis Model Losing Kinetic Energy in May/June ? Ensemble Mean Kinetic Energy

  26. Big with R2 LS CFS Hcst Big with R/R LS Small with R2 LS Small with R/R LS R/R Small domain has the highest percentage of convective Precip Ensemble Mean Ratio of ACPCP/APCP

  27. Preliminary Conclusions • Domain size choice is crucial to model results. • Diffs caused by different land landstates is secondary. • Big Domain EtaRCM yields better results than other combinations in general. • The EtaRCM shows skills in warm season precipitation predictions (Compared to Obs and CFS hindcast, especially with features associated with NAM system), still problems? LBC errors plus physics?

  28. Future Work • More tests on different years (under way, 2000-2003). To drive the Eta-RCM, CFS hindcasts need to be re-run (saved sigma files). It takes a lot CPU time (so only 2004 finished so far). • Establishing model climatology to evaluate a relative dry/wet year with respect to model climatology. • Further testing Land states from Regional Reanalysis and its impact on warm season precipitation.

  29. Thanks to Suranjana Saha Wanqiu Wang Cathy Thiaw Jun Wang Kingtse Mo

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