Article Type:
Research Article

Evaluations of BDA Scheme Using the Advanced Research WRF (ARW) Model

Qingnong Xiao Mesoscale and Microscale Meteorology Division, Earth and Sun Systems Laboratory, National Center for Atmospheric Research, * Boulder, Colorado

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Liqiang Chen Mesoscale and Microscale Meteorology Division, Earth and Sun Systems Laboratory, National Center for Atmospheric Research, * Boulder, Colorado, and Institute of Atmospheric Environment, China Meteorological Administration, Shenyang, China

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Xiaoyan Zhang Mesoscale and Microscale Meteorology Division, Earth and Sun Systems Laboratory, National Center for Atmospheric Research, * Boulder, Colorado

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Print Publication:
01 Mar 2009
DOI:
https://doi.org/10.1175/2008JAMC1994.1
Page(s):
680–689
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Abstract

A tropical cyclone bogus data assimilation (BDA) scheme is built in the Weather Research and Forecasting three-dimensional variational data assimilation system (WRF 3D-VAR). Experiments were conducted (21 experiments with BDA in parallel with another 21 without BDA) to assess its impacts on the predictions of seven Atlantic Ocean basin hurricanes observed in 2004 (Charley, Frances, Ivan, and Jeanne) and in 2005 (Katrina, Rita, and Wilma). In addition, its performance was compared with the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane initialization scheme in a case study of Hurricane Humberto (2007). It is indicated that hurricane initialization with the BDA technique can improve the forecast skills of track and intensity in the Advanced Research WRF (ARW). Among the three hurricane verification parameters [track, central sea level pressure (CSLP), and maximum surface wind (MSW)], BDA improves CSLP the most. The improvement of MSW is also considerable. The track has the smallest, but still noticeable, improvement. With WRF 3D-VAR, the initial vortex produced by BDA is balanced with the dynamical and statistical balance in the 3D-VAR system. It has great potential for improving the hurricane intensity forecast. The case study on Hurricane Humberto (2007) shows that BDA performs better than the GFDL bogus scheme in the ARW forecast for the case. Better definition of the initial vortex is the main reason for the advanced skill in hurricane track and intensity forecasting in this case.

Corresponding author address: Dr. Qingnong Xiao, NCAR, MMM, P.O. Box 3000, Boulder, CO 80307-3000. Email: hsiao@ucar.edu

Abstract

A tropical cyclone bogus data assimilation (BDA) scheme is built in the Weather Research and Forecasting three-dimensional variational data assimilation system (WRF 3D-VAR). Experiments were conducted (21 experiments with BDA in parallel with another 21 without BDA) to assess its impacts on the predictions of seven Atlantic Ocean basin hurricanes observed in 2004 (Charley, Frances, Ivan, and Jeanne) and in 2005 (Katrina, Rita, and Wilma). In addition, its performance was compared with the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane initialization scheme in a case study of Hurricane Humberto (2007). It is indicated that hurricane initialization with the BDA technique can improve the forecast skills of track and intensity in the Advanced Research WRF (ARW). Among the three hurricane verification parameters [track, central sea level pressure (CSLP), and maximum surface wind (MSW)], BDA improves CSLP the most. The improvement of MSW is also considerable. The track has the smallest, but still noticeable, improvement. With WRF 3D-VAR, the initial vortex produced by BDA is balanced with the dynamical and statistical balance in the 3D-VAR system. It has great potential for improving the hurricane intensity forecast. The case study on Hurricane Humberto (2007) shows that BDA performs better than the GFDL bogus scheme in the ARW forecast for the case. Better definition of the initial vortex is the main reason for the advanced skill in hurricane track and intensity forecasting in this case.

Corresponding author address: Dr. Qingnong Xiao, NCAR, MMM, P.O. Box 3000, Boulder, CO 80307-3000. Email: hsiao@ucar.edu

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Journal of Applied Meteorology and Climatology

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