1 / 33

Rongqian Yang Ken Mitchell, Jesse Meng, Helin Wei, George Gayno Acknowledgments to Suru Saha, Wanqiu Wang, Cathy Thiaw E

Rongqian Yang Ken Mitchell, Jesse Meng, Helin Wei, George Gayno Acknowledgments to Suru Saha, Wanqiu Wang, Cathy Thiaw Environmental Modeling Center (EMC) National Centers for Environmental Prediction. Summer Season Predictions with T126 CFS Using

domani
Download Presentation

Rongqian Yang Ken Mitchell, Jesse Meng, Helin Wei, George Gayno Acknowledgments to Suru Saha, Wanqiu Wang, Cathy Thiaw E

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Rongqian Yang Ken Mitchell, Jesse Meng, Helin Wei, George Gayno Acknowledgments to Suru Saha, Wanqiu Wang, Cathy Thiaw Environmental Modeling Center (EMC) National Centers for Environmental Prediction Summer Season Predictions with T126 CFS Using Different Land Models and Different Initial Land States The 4th Symposium on Southwest Hydrometeorology Tucson, Arizona, September 20-21, 2007

  2. Outline of Presentation • Configuration of the CFS land-related experiments • CFS Skill Masks for JJA: Correlation scores • Precip • T2m • SST • 200 Mb GPH • Individual cases: • Wet U.S. Southwest Monsoon (summer 1999, summer 1990) • 1988 widespread U.S. summer drought • 1993 central U.S. flooding • Comparing GLDAS/Noah and GR2/OSU initial Soil Moisture • Conclusionsto date • Ongoing and Near Future Work

  3. Choice ofLand Model CFS/Noah CFS/OSU Choice of LandInitial Conditions GR2/OSU GR2/OSU (CONTROL) GLDAS/Noah GLDAS/Noah Climo “GR2” denotes NCEP/DOE Global Reanalysis 2 CFS Land Experiments: 4 ConfigurationsLand Experiments of T126 CFS with CFS/Noah and CFS/OSU

  4. CFS Land Related Experiments Objective:Demonstrate Impact on CFS of: A) new land model (Noah LSM vs OSU LSM)B) new land initial conditions (GLDAS vs GR2) • 25-year (1980-2004) 10-member 6-month T126 CFS runs ( GFS-OP3T3, MOM-3 ) • Four configurations of T126 CFS: • A) CFS/OSU/GR2: - OSU LSM, initial land states from GR2 (CONTROL) • B) CFS/Noah/GR2: - Noah LSM, initial land states from GR2 • C) CFS/Noah/GLDAS: - Noah LSM, initial land states from T126 GLDAS/Noah • D) CFS/Noah/GLDAS-Climo: - Noah LSM, initial land states from GLDAS/Noah climo • Initial conditions: 00Z daily from Apr 19-23 29,30, and May 1-3 • 5 additional membersfor A) and C) configurations Initial conditions: 00Z daily from Apr 24-28

  5. Verification Data Sources • Precip - CMAP (also Xie/Arkin) • T2m - GHCN/CAMS Global T2m (T126) • Heights - GR2 (200mb) • SST - OI SST (1x1 to T126)

  6. Next 6 Frames: Precip Skill Masks: correlation North America Asia South America

  7. JJA Precip Correlation Skill w Different LSMs and ICs Noah/ GLDAS Noah/ GR2 Worst OSU/ GR2 Noah/ GLDAS Climo 10 Members each case (same initial dates)

  8. 15 vs 10 mem JJA Precip Correlation Skills comparison 15 10 OSU/GR2 Noah/GLDAS 15 members results (top row) appear moderately better

  9. Test T126 CFS versus Ops T62 CFS: JJA Precip Correlation T126 CFS Noah/GLDAS T126 CFS OSU/GR2 15 Members each case Caveats: Span of years Ops: 22-years (1982-2003) Test: 25-years (1980-2004) B) Apr-May Initial Dates Ops: 09-13, 19-23, 29-03 Test: 24-28, 19-23, 29-03 Ops T62CFS (OSU/GR2)

  10. Comparison with Xie/Arkin Precip Anal as Verification Data Source (future work: will repeat with gauge-only CONUS precip analysis) Noah/GLDAS OSU/GR2 CMAP Xie/Arkin Use of two different verifying global precip analyses yields similar correlation scores

  11. JJAPrecip Correlation Skills overAsia Noah/ GLDAS Noah/ GR2 Best Worst OSU/ GR2 Noah/ GLDAS Climo

  12. JJAPrecip Correlation Skills South America Noah/ GLDAS Noah/ GR2 Best Noah/ GLDAS Climo OSU/ GR2

  13. T2m Skill Masks: Correlation Next 2 frames

  14. JJA Mean T2m Correlation Skill w Different LSM/ICs Noah/ GLDAS Noah/ GR2 Noah/ GLDAS Climo OSU/ GR2 10 Members each case (same initial dates)

  15. JJA Mean T2m Correlation Skill Comparison Ops CFS T62 April ICs Noah/ GLDAS OSU/ GR2 Good CONUS Best CONUS 10 members 10 members Ops CFS Noah/ GLDAS Climo Worst CONUS Good CONUS 15 members 10 members

  16. 200 Mb Height Skill Mask: Correlation Next 2 frames

  17. JJA Mean 200mb GPH Correlation Skill w Different LSM/ICs Noah/ GR2 Noah/ GLDAS Noah/ GLDAS Climo OSU/ GR2

  18. JJA Mean 200mb GPH Correlation Comparision Ops CFS T62 April ICs OSU/ GR2 Noah/ GLDAS Ops CFS Noah/ GLDAS Climo

  19. SST Skill Masks: Correlation Next 2 frames

  20. JJA Mean SST Correlation Skill w Different LSM/ICs Globally Noah/ GR2 Noah/ GLDAS Noah/ GLDAS Climo OSU/ GR2 10 Members each case (same initial dates)

  21. JJA Mean SST Correlation Skill Comparison Globally Ops CFS T62 April ICs Noah/ GLDAS OSU/ GR2 Ops CFS Noah/ GLDAS Climo Noah/GLDAS Climo seems best, and Noah/GLDAS not so good

  22. Summer Case Studies • 1 - Wet U.S. Southwest Monsoon: 1999 • 2 - Wet U.S. Southwest Monsoon: 1990 • 3 - 1988 widespread U.S. summer drought • 4 - 1993 central U.S. flooding • One frame for each case above: • JJA CONUSprecip anomaly: forecast and observed

  23. 1999 JJA Mean Precip Anomaly w Different LSM/ICs Noah/GLDAS Noah/GR2 Noah/GLDAS Climo OSU/GR2 Observed Climo Wet Southwest U.S. Monsoon Case 1: 1999 CFS with Noah/GLDAS performs the best, OSU/GR2 and Noah/GR2 perform poorly

  24. 90 JJAMean Precip Anomaly w Different LSM/ICs Noah/GR2 Noah/GLDAS Climo Noah/GLDAS OSU/GR2 Observed Climo Wet Southwest U.S. Monsoon Case 2: 1990 Noah/GLDAS is the best and Noah/GR2 is the worst

  25. 88 JJA Mean Precip Anomaly w Different LSM/ICs Noah/GLDAS Noah/GR2 Noah/GLDAS Climo OSU/GR2 Observed Climo U.S. Major Drought Year: 1988 OSU/GR2 performs the best, Noah/GLDAS is not good

  26. 93 JJA Mean Precip Anomaly w Different LSM/ICs Noah/GR2 Noah/GLDAS Climo Noah/GLDAS OSU/GR2 Observed Climo U.S. Major Flood Year : 1993 Noah/GLDAS is the best and Noah/GR2 is the worst

  27. Soil Moisture: Comparing GLDAS/Noah and GR2 initial states

  28. GLDAS/Noah (top row) versus GR2/OSU (bottom row)2-meter soil moisture (% volume): GLDAS/Noah values are higher Climatology (left column) is from 25-year period of ~1981-2005)May 1stClimatology01 May 1999Anomaly GLDAS/Noah GLDAS/Noah GR2/OSU GR2/OSU

  29. GLDAS/Noah (top) versus GR2/OSU (bottom)2-meter soil moisture (% volume) May 1stClimatology 01 May 1999Anomaly Top: observed 90-day Precipitation Anomaly (mm) valid 30 April 99 Bottom: Climatology GLDAS/Noah GLDAS/Noah GR2/OSU GR2/OSU Left column: GLDAS/Noah soil moisture climo is generally higher then GR2/OSU Middle column: GLDAS/Noah soil moisture anomaly pattern agrees better than that of GR2/OSU with observed precipitation anomaly (right column: top)

  30. Monthly Time Series (1985-2004) of Area-mean Illinois 2-meter Soil Moisture [mm]:Observations (black), GLDAS/Noah (purple),GR2/OSU (green) Total Climatology Anomaly The climatology of GLDAS/Noah soil moisture is higher and closer to the observed climatology than that of GR2/OSU, while the anomlies of all three show generally better agreement with each other (though some exceptions)

  31. Conclusions • Combined use of the Noah LSM with GLDAS Land States exhibits a promising indication of improving CFS summer season forecasts of precipitation, Noah with GR2 combo seems to give the poorest results. • Providing Noah LSM compatible GLDAS ICs is important • Unfortunately, the current public version of CFS scripts still uses GR2 as default land states. GLDAS Land States should be used.

  32. Ongoing/Near Future Work • Examine entire atmospheric and land water budget • Examine the soil moisture influence on seasonal predictions • Recast skill masks for same 22-year period as ops CFS hindcasts • Add more performance measures (BSS, RPSS etc) • Analyze winter-season CFS experiments with land component results • Re-run CFS/Noah with “Generation 2” of GLDAS/Noah • Investigate source of land-component impact on Pacific SST • Surface wind stress differences

  33. Thank you for your attention !

More Related