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Assimilation of Satellite Soil Moisture Blended Products from SMOPS in NCEP Global Forecast System Weizhong Zheng 1,2 , Xiwu Zhan 3 , Jicheng Liu 4 , Michael Ek 1 , Jesse Meng 1,2 , Jiarui Dong 1,2 and Helin Wei 1,2 1 NOAA/NCEP/EMC, College Park, MD 20740 2 IMSG, Kensington, MD 20895 - PowerPoint PPT Presentation
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Assimilation of Satellite Soil Moisture Blended Products from SMOPS in NCEP Global Forecast System
Weizhong Zheng1,2, Xiwu Zhan3, Jicheng Liu4, Michael Ek1, Jesse Meng1,2, Jiarui Dong1,2 and Helin Wei1,2
1NOAA/NCEP/EMC, College Park, MD 207402IMSG, Kensington, MD 20895
3NOAA/NESDIS/STAR, College Park, MD 207404GMU, Fairfax, VA 22030
JCSDA Science Workshop, June 5-7, 2013
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OUTLINE:
ObjectiveObjective
Embed EnKF in GFSEmbed EnKF in GFS
Testing with Testing with SMOS SMSMOS SM
Testing with Testing with SMOPS Blended SMSMOPS Blended SM * Fits to SfcObs* Fits to SfcObs
* Fits to RaObs* Fits to RaObs
* Scores* Scores
* CONUS Precipitation* CONUS Precipitation
Summary and future plan Summary and future plan 2
““Online” satellite soil moisture data Online” satellite soil moisture data assimilation in NCEP GFSassimilation in NCEP GFS
Examine how satellite SM data impact Examine how satellite SM data impact NCEP GFS forecastsNCEP GFS forecasts
OBJECTIVESOBJECTIVES
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NOAA NESDIS Soil Moisture Operational Product System (SMOPS)
6-hour operational soil moisture product from the Office of Satellite and Product Operations (OSPO) of NOAA/NESDIS. Carries near real-time global gridded soil moisture products from several individual satellite sensors as well as a blended product.
Soil moisture layer from individual sensors: (AMSR-E), ASCAT, SMOS, and WindSat.
Blended product: CDF matching is used to merge all available values from above individual sensors to a common climatology, resulting in better spatial and temporal coverage.
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SMOPS Blended Product from WindSat, SMOS and ASCAT
WindSat SMOS ASCAT
Blended
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SMOS GFS_CTL
GFS_EnKF EnKF-CTL
Testing with SMOS SM (May 1 – June 17 2012): 18Z, 1-17 June 2012
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GFS_CTL
EnKF-CTL GFS_EnKF
SMOS
Testing with SMOS SM (May 1 – June 17 2012): 18Z, 1-17 June 2012
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Assimilation of Satellite Soil Moisture Blended Products from SMOPS in NCEP Global Forecast System
The simplified ensemble Kalman Filter (EnKF) was embedded in the GFS latest version to assimilate soil moisture observation.
Case: Starting from 00Z April 1–May 4, 2012. (GFS/GSI)
Experiments: CTL: Control run (without SM DA) EnKF: Sensitivity run (Daily EnKF run) And precipitation perturbation.
PRT: Perturbation size for each layer soil moisture.10
Comparison of soil moisture from SMOPS Blended 18Z, 1-30 April 2012
GFS_EnKF EnKF-CTL
GFS_CTL SMOPS
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Comparison of soil moisture from SMOPS Blended 18Z, 1-30 April 2012
SMOPS GFS_CTL
GFS_EnKF EnKF-CTL
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GFS Top Layer SM Validation GFS Top Layer SM Validation With USDA-SCAN Measurements With USDA-SCAN Measurements
1-30 of April, 20121-30 of April, 2012
East CONUS (26 sites) West CONUS (25 sites) Whole CONUS
RMSE BiasCorr-Coef
RMSE BiasCorr-Coef
RMSE BiasCorr-Coef
CTLCTL 0.135 0.046 0.565 0.124 0.033 0.448 0.129 0.040 0.508
EnKFEnKF 0.130 -0.031 0.613 0.114 -0.021 0.549 0.123 -0.031 0.587
SMOPSSMOPS 0.133 -0.055 0.601 0.098 -0.036 0.402 0.117 -0.048 0.524
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Soil moisture at 4 layers: Day 3: April 2 – May 4 2012
SM1
SM3
SM2
SM4
CTL
Diff
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Q2m
(left) and T2m
(right): Day 3: April 2 – May 4 2012
CTL
Diff
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Tmin2m
(left) and Tmax2m
(right): Day 3: April 2 – May 4 2012
Diff
CTL
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Sfc RH (%) over CONUS West and East: April 2 – May 4 2012
West East17
Sfc RH (%) RMSE over CONUS West and East: April 2 – May 4 2012
West East18
Sfc T (K) over CONUS West and East: April 2 – May 4 2012
West East19
Sfc T (K) RMSE over CONUS West and East: April 2 – May 4 2012
West East20
RH (%) Bias and RMSE over CONUS: Day 5: April 2 – May 4 2012
Bias RMSE 21
T(K) Bias and RMSE over CONUS: Day 5: April 2 – May 4 2012
RMSE Bias22
+ 0.004
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25
700 hPa
1000 hPa
+ 0.003
+ 0.003
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- 0.36
- 0.43
Bias
RMSE
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Bias RMSE
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+ 0.002
+ 0.007
NHX
SHX
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NHX SHX
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Precipitation Skill Scores over CONUS
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Summary:
The satellite soil moisture blended products from SMOPS were assimilated in NCEP GFS and the result shows as follows:
1) Improved GFS deeper layer soil moisture estimates comparing with in situ
measurements;
2) Improved GFS forecast scores and reduced its bias and root-mean-square
errors.
3) Showed some positive impact on precipitation on CONUS but not for
heavy precipitation.
Future: assimilate SMAP (remote sensing), COSMOS & other in situ
measurements. Furthermore, consider regions where soil alternates (frozen
and thawed) during the transition seasons (by CREST ongoing project).
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Thank you!
Questions?
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