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Assimilation of Doppler Weather Radar Radial Velocity and Reflectivity Observations in WRF-3DVAR System for Short-Range Forecasting of Convective Storms

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Abstract

In this paper the impact of Doppler weather radar (DWR) reflectivity and radial velocity observations for the short range forecasting of a tropical storm and associated rainfall event have been examined. Doppler radar observations of a tropical storm case that occurred during 29–30 October 2006 from SHARDWR (13.6° N, 80.2° E) are assimilated in the WRF 3DVAR system. The observation operator for radar reflectivity and radial velocity is included within latest version of WRF 3DVAR system. Keeping all model physics the same, three experiments were conducted at a horizontal resolution of 30 km. In the control experiment (CTRL), NCEP Final Analysis (FNL) interpolated to the model grid was used as the initial condition for 48-h free forecast. In the second experiment (NODWR), 6-h assimilation cycles have been carried out using all conventional (radiosonde and surface data) and non-conventional (satellite) observations from the Global Telecommunication System (GTS). The third experiment (DWR) is the same as the second, except Doppler radar radial velocity and reflectivity observations are also used in the assimilation cycle. Continuous 6-h assimilation cycle employed in the WRF-3DVAR system shows positive impact on the rainfall forecast. Assimilation of DWR data creates several small scale features near the storm centre. Additional sensitivity experiments were conducted to study the individual impact of reflectivity and radial velocity in the assimilation cycle. Radar data assimilation with reflectivity alone produced large analysis response on both thermodynamical and dynamical fields. However, radial velocity assimilation impacted only on dynamical fields. Analysis increments with radar reflectivity and radial velocity produce adjustments in both dynamical and thermodynamical fields. Verification of QPF skill shows that radar data assimilation has a considerable impact on the short range precipitation forecast. Improvement of the QPF skill with radar data assimilation is more clearly seen in the heavy rainfall (for thresholds >7 mm) event than light rainfall (for thresholds of 1 and 3 mm). The spatial pattern of rainfall is well simulated by the DWR experiment and is comparable to TRMM observations.

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Acknowledgments

The authors are thankful to the Director, Indian Institute of Tropical Meteorology for providing necessary facilities to carry out this work. We also thank program manager, IITM HPC facility to carry out assimilation and forecast experiments in the HPC facility. We would like to thank the National Center for Atmospheric Research (NCAR), USA, in particular, Dr. Dale Barker for his immense assistance provided on the Mesoscale 3-DVAR assimilation system and to Dr. Mitch Moncrief for many stimulating discussions. Thanks are also due to the NCEP/FNL data provided by the Data Support Section (DSS) of the Scientific Computing Division at NCAR. The authors would like to acknowledge GSFC/NASA for making the TRMM data available in their web site. Authors are thankful to anonymous reviewers for comments and suggestions which helped improve the manuscript.

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  1. Climate and Global Modeling Division, Indian Institute of Tropical Meteorology, Pashan, Pune, 411008, India

    S. Abhilash & A. K. Sahai

  2. Department of Atmospheric Sciences, Cochin University of Science and Technology, Cochin, 682016, India

    K. Mohankumar

  3. National Centre for Medium Range Weather Forecasting, Ministry of Earth Sciences, Noida, India

    John P. George & Someshwar Das

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  1. S. Abhilash
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Abhilash, S., Sahai, A.K., Mohankumar, K. et al. Assimilation of Doppler Weather Radar Radial Velocity and Reflectivity Observations in WRF-3DVAR System for Short-Range Forecasting of Convective Storms. Pure Appl. Geophys. 169, 2047–2070 (2012). https://doi.org/10.1007/s00024-012-0462-z

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