Rongqian Yang Ken Mitchell, Jesse Meng, Helin Wei, George Gayno Acknowledgments to Suru Saha, Wanqiu Wang, Cathy Thiaw Environmental Modeling Center (EMC)

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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 4 th Symposium on Southwest Hydrometeorology Tucson, Arizona, September 20-21, 2007

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 Conclusions to date Ongoing and Near Future Work

CFS Land Experiments: 4 Configurations Land Experiments of T126 CFS with CFS/Noah and CFS/OSU Choice of Land Model “GR2” denotes NCEP/DOE Global Reanalysis 2 Choice of Land Initial Conditions GR2/OSU (CONTROL)GR2/OSU GLDAS/Noah GLDAS/Noah Climo CFS/NoahCFS/OSU

25-year ( ) 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 ,30, and May 1-3 –5 additional members for A) and C) configurations Initial conditions: 00Z daily from Apr 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)

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

Next 6 Frames: Precip Skill Masks: correlation 1)North America 2)Asia 3)South America

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

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

15 Members each case Caveats: A)Span of years Ops: 22-years ( ) Test: 25-years ( ) B) Apr-May Initial Dates Ops: 09-13, 19-23, Test: 24-28, 19-23, T126 CFS Noah/GLDAST126 CFS OSU/GR2 Test T126 CFS versus Ops T62 CFS: JJA Precip Correlation Ops T62CFS (OSU/GR2)

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

JJA Precip Correlation Skills over Asia Worst Noah/ GLDAS Noah/ GR2 Noah/ GLDAS Climo OSU/ GR2 Best

JJA Precip Correlation Skills South America Best OSU/ GR2 Noah/ GR2 Noah/ GLDAS Noah/ GLDAS Climo

T2m Skill Masks: Correlation Next 2 frames

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

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

200 Mb Height Skill Mask: Correlation Next 2 frames

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

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

SST Skill Masks: Correlation Next 2 frames

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

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

Summer Case Studies 1 - Wet U.S. Southwest Monsoon: Wet U.S. Southwest Monsoon: widespread U.S. summer drought central U.S. flooding One frame for each case above: JJA CONUS precip anomaly : forecast and observed

1999 JJA Mean Precip Anomaly w Different LSM/ICs Noah/GLDASNoah/GR2Noah/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

90 JJA Mean Precip Anomaly w Different LSM/ICs Noah/GLDAS Noah/GR2Noah/GLDAS Climo OSU/GR2 Observed Climo Wet Southwest U.S. Monsoon Case 2: 1990 Noah/GLDAS is the best and Noah/GR2 is the worst

88 JJA Mean Precip Anomaly w Different LSM/ICs Noah/GLDASNoah/GR2Noah/GLDAS Climo OSU/GR2ObservedClimo U.S. Major Drought Year: 1988 OSU/GR2 performs the best, Noah/GLDAS is not good

93 JJA Mean Precip Anomaly w Different LSM/ICs Noah/GLDASNoah/GR2Noah/GLDAS Climo OSU/GR2Observed Climo U.S. Major Flood Year : 1993 Noah/GLDAS is the best and Noah/GR2 is the worst

Soil Moisture: Comparing GLDAS/Noah and GR2 initial states

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 ~ ) May 1 st Climatology 01 May 1999 Anomaly GLDAS/Noah GR2/OSU

Top: observed 90-day Precipitation Anomaly (mm) valid 30 April 99 Bottom: Climatology GLDAS/Noah (top) versus GR2/OSU (bottom) 2-meter soil moisture (% volume) May 1 st Climatology 01 May 1999 Anomaly 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) GLDAS/Noah GR2/OSU

Monthly Time Series ( ) of Area-mean Illinois 2-meter Soil Moisture [mm]: Observations (black), GLDAS/Noah (purple), GR2/OSU (green) Total Anomaly Climatology 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)

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.

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

Thank you for your attention !