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Dynamical Downscaling of CCSM Using WRF

Dynamical Downscaling of CCSM Using WRF. Yang Gao 1 , Joshua S. Fu 1 , Yun-Fat Lam 1 , John Drake 1 , Kate Evans 2 1 University of Tennessee, USA 2 Oak Ridge National Laboratory, USA. 9th Annual CMAS Conference, Chapel Hill, North Carolina October 11, 2010.

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Dynamical Downscaling of CCSM Using WRF

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  1. Dynamical Downscaling of CCSM Using WRF Yang Gao1, Joshua S. Fu1, Yun-Fat Lam1, John Drake1, Kate Evans2 1University of Tennessee, USA 2Oak Ridge National Laboratory, USA 9th Annual CMAS Conference, Chapel Hill, North Carolina October 11, 2010

  2. Motivation • The Community Earth System Model (CESM) is being used to simulate IPCC AR5 scenarios. • To study climate change on regional and local scales, downscaling becomes an important technique to link global and regional models. • There are high uncertainties in regional climate downscaling. Different sensitivity cases are needed to optimize the regional climate simulations.

  3. Community Atmosphere Model (CAM) Community Land Model (CLM) Community Sea Ice Model (CSIM) Ocean component (POP) Linkage from Global model to Regional Model Community Earth System Model CESM 1.0 Regional Climate Model WRF 3.2.1 (D2) (D1) 36 km by 36km CONUS D1: 12 km by 12km domain D2: 4km by 4km Eastern US domain 1 degree by 1 degree 3 hourly resolution

  4. Global and Regional Model Configurations Most of the physics schemes are different in CESM and WRF except radiation scheme

  5. Sensitivity Scenarios • 3.5-day overlapping run segments in January, April, July and October in 2002 • Typical Analysis Nudging vs. No nudging • Horizontal wind components (U and V) in all layers • Temperature (T) and Water vapor mixing ratio (Q) above the PBL • 2) Scheme options comparison: • CAM/CAM vs. RRTMG/RRTMG for shortwave/longwave radiation • WRF: CAM 3 (A spectral-band scheme used in the NCAR Community Atmosphere Model (CAM 3.0) for climate simulations.) • CESM (CAM4): (Parameterizations of shortwave and longwave Radiation in CAM3 and CAM4 are the same)

  6. Initial condition integrity CCSM (Skin T) METGRID CESM (Temperature) METGRID (Relative Humidity) (Wind Vector) Patterns and Spatial distribution are similar Time: 2002-04-01-00:00

  7. Comparison between CESM and WRF We mainly focus on the following parameters comparison on the surface layer: 10 m Wind speed*, 10 m Wind direction*, 2 m temperature, 2 m specific humidity and precipitation (*Note: CESM does not output 10 meters wind speed and wind direction, so the lowest model layer (around 60 m) values are used for the comparison)

  8. Temperature at 2 meters Overall, temperature with RRTMG rw/lw radiation scheme and with nudging has lower bias than the other two cases. Dashed time series represent 2m temperature from CESM

  9. Correlation between temperature bias and temperature There is high relationship between the temperature and the bias. Bias tends to change from positive to negative when the temperature from CESM increases.

  10. Specific Humidity at 2 meters CAM and RRTMG schemes perform similar with each other. Nudging performs better for most of the sub-region than no nudging case. The biases are mainly ranging from -2 to 2 g/kg.

  11. Wind Speed bias at 10 meters Most of the cases, wind speed has negative bias. The two radiation schemes have quite similar performance on wind speed.

  12. Wind direction bias at 10 meters Overall, nudging case has much lower bias than no nudging for wind direction. Radiation schemes does not have much impact on the wind directions.

  13. Precipitation bias Small bias in January, April and October. In July, WRF predicts more precipitation than CESM.

  14. Comparison of WRF output with observational data Climate data may not represent a specific year. We try to evaluate how far the WRF downscaling simulations compared with Meteorological Assimilation Data Ingest System (MADIS) observational data. Overall, RRTMG radiation scheme with nudging performs better than the other two cases, so we only compare WRF output with observational data for the RRTMG/NUDGING case.

  15. Comparison between MADIS and WRF OUTPUT Wind Speed at 10 meters Wind Direction at 10 meters Mean obs Mean prd Bias Mean obs Mean prd Bias Compared with observational data, the biases of wind speeds are within 2 m/s for most of the sub-region. Wind direction is also comparable with observational data.

  16. Comparison between MADIS and WRF OUTPUT Temperature at 2 meters Mean obs Mean prd Bias Specific humidity at 2 meters Mean obs Mean prd Bias The bias of temperature and specific humidity ranges from -2 to 2 degree and -1 to 1 g/kg, respectively.

  17. Summary • Overall, nudging case performs better than no nudging case. • RRTMG radiation scheme with nudging case shows the lowest bias for temperature compared with CAM radiation scheme and no nudging case. • There is high relationship between the temperature and the bias. Bias tends to change from positive to negative when the temperature from CESM increases. • WRF simulations driven by CESM are comparable to the observational data, and the range of biases for temperature, wind speed, specific humidity are from -2 to 2 degrees , from 1 to 2 m/s and from-1 to 1 g/kg, respectively.

  18. Future work Downscaling from CESM to WRF for12km by 12km CONUS domain and 4km by 4km Eastern US domain Chemistry Downscaling from CESM to CMAQ

  19. Thanks for your attention! Questions?

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