Dynamical Downscaling of CCSM Using WRF Yang Gao

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Dynamical Downscaling of CCSM Using WRF Yang Gao 1, Joshua S. Fu 1, Yun-Fat

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 2 Oak of Tennessee, USA Ridge National Laboratory, USA 9 th Annual CMAS Conference, Chapel Hill, North Carolina October 11, 2010

Motivation n The Community Earth System Model (CESM) is being used to simulate IPCC

Motivation n The Community Earth System Model (CESM) is being used to simulate IPCC AR 5 scenarios. n To study climate change on regional and local scales, downscaling becomes an important technique to link global and regional models. n There are high uncertainties in regional climate downscaling. Different sensitivity cases are needed to optimize the regional climate simulations.

Linkage from Global model to Regional Model Community Earth System Model Regional Climate Model

Linkage from Global model to Regional Model Community Earth System Model Regional Climate Model CESM 1. 0 WRF 3. 2. 1 Community Atmosphere Model (CAM) Community Land Model (CLM) (D 1) Ocean component (POP) Community Sea Ice Model (CSIM) (D 2) 36 km by 36 km CONUS 1 degree by 1 degree D 1: 12 km by 12 km domain 3 hourly resolution D 2: 4 km by 4 km Eastern US domain

Global and Regional Model Configurations Most of the physics schemes are different in CESM

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

Sensitivity Scenarios 1. 3. 5 -day overlapping run segments in January, April, July and

Sensitivity Scenarios 1. 3. 5 -day overlapping run segments in January, April, July and October in 2002 2. Typical Analysis Nudging vs. No nudging 3. 4. Horizontal wind components (U and V) in all layers Temperature (T) and Water vapor mixing ratio (Q) above the PBL 5. 2) Scheme options comparison: 6. CAM/CAM vs. RRTMG/RRTMG for shortwave/longwave radiation 7. WRF: CAM 3 (A spectral-band scheme used in the NCAR Community Atmosphere Model (CAM 3. 0) for climate simulations. ) 8. CESM (CAM 4): (Parameterizations of shortwave and longwave Radiation in CAM 3 and CAM 4 are the same)

Initial condition integrity CESM (Temperature) METGRID (Relative Humidity) CCSM (Skin T) METGRID (Wind Vector)

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

Comparison between CESM and WRF We mainly focus on the following parameters comparison on

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)

Temperature at 2 meters Overall, temperature with RRTMG rw/lw radiation scheme and with nudging

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 2 m temperature from CESM

Correlation between temperature bias and temperature There is high relationship between the temperature and

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.

Specific Humidity at 2 meters CAM and RRTMG schemes perform similar with each other.

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.

Wind Speed bias at 10 meters Most of the cases, wind speed has negative

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.

Wind direction bias at 10 meters Overall, nudging case has much lower bias than

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.

Precipitation bias Small bias in January, April and October. In July, WRF predicts more

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

Comparison of WRF output with observational data Climate data may not represent a specific

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.

Comparison between MADIS and WRF OUTPUT Wind Speed at 10 meters Mean obs Mean

Comparison between MADIS and WRF OUTPUT Wind Speed at 10 meters Mean obs Mean prd Bias Wind Direction at 10 meters 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.

Comparison between MADIS and WRF OUTPUT Temperature at 2 meters Mean obs Mean prd

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.

Summary • Overall, nudging case performs better than no nudging case. • RRTMG radiation

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.

Future work Downscaling from CESM to WRF for 12 km by 12 km CONUS

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

Thanks for your attention! Questions?

Thanks for your attention! Questions?