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

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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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Page 1: 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.

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

Page 2: 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.

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.

Page 3: 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.

Linkage from Global model to Regional Model

Community Earth System Model

CESM 1.0

Regional Climate Model

WRF 3.2.1

36 km by 36km CONUS

D1: 12 km by 12km domain

D2: 4km by 4km Eastern US domain

Community Land Model

(CLM)

Community Atmosphere Model (CAM)

Community Sea Ice Model

(CSIM)Ocean component

(POP)

1 degree by 1 degree

3 hourly resolution

(D1)(D2)

Page 4: 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.

Global and Regional Model Configurations

Most of the physics schemes are different in CESM and WRF except radiation scheme

Page 5: 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.

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)

Sensitivity Scenarios

Page 6: 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.

CESM (Temperature) METGRID

Time: 2002-04-01-00:00

Patterns and Spatial distribution are similar

CCSM (Skin T) METGRID

(Relative Humidity) (Wind Vector)

Initial condition integrity

Page 7: 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.

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)

Page 8: 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.

Temperature at 2 meters

Dashed time series represent 2m temperature from CESM

Overall, temperature with RRTMG rw/lw radiation scheme and with nudging has lower bias than the other two cases.

Page 9: 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.

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.

Page 10: 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.

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.

Page 11: 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.

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.

Page 12: 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.

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.

Page 13: 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.

Precipitation bias

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

Page 14: 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.

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.

Page 15: 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.

Wind Speed at 10 meters

Mean obs Mean prd Bias

Comparison between MADIS and WRF OUTPUT

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.

Wind Direction at 10 meters

Mean obs Mean prd Bias

Page 16: 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.

Mean obs Mean prd BiasSpecific humidity at 2 meters

Comparison between MADIS and WRF OUTPUT

The bias of temperature and specific humidity ranges from -2 to 2 degree and -1 to 1 g/kg, respectively.

Mean obs Mean prd BiasTemperature at 2 meters

Page 17: 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.

• 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.

Summary

Page 18: 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.

Downscaling from CESM to WRF for12km by 12km CONUS domain and 4km by 4km Eastern US domain

Chemistry Downscaling from CESM to CMAQ

Future work

Page 19: 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.

Thanks for your attention!

Questions?


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