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Impact of background error statistics on 3D-Var assimilation: case study over the Indian region

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Abstract

The quality of background error statistics (BES) is one of the key components for successful assimilation of observations in a numerical model. Considerable uncertainties and non-uniqueness exist, however, in prescribing BES; in particular, the prescription and impact of BES can also depend on the weather regime and not much is known in this regard over the Indian region. We have conducted a series of assimilation experiments using the WRF three-dimensional variational data assimilation (3D-Var) system with different BES to asses the relative improvement in model forecast due to different BES over the Indian region. The forecasted wind, temperature, and humidity are verified against NCEP analysis and conventional radiosondes, while the predicted rainfall is verified against Tropical Rainfall Measuring Mission (TRMM) observations. Using a number of parameters to quantify impact of BES, it is shown that the use of regional BES (RBES) in WRF 3D-Var significantly improves model forecast as compared to the control experiment (no assimilation) and Global BES (GBES). The use of RBES from National Meteorological Center (NMC) and ensemble perturbation (ENS) method in WRF 3D-Var produced similar impact on model forecasts except slight differences in wind speed. This study highlights the importance of domain-dependent and region-specific BES in WRF 3D-Var assimilation system; for the selected events, results obtained using RBES is found to be significantly better than GBES.

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Acknowledgments

The authors gratefully acknowledge Mesoscale and Microscale Meteorology division at the National Center for Atmospheric Research (NCAR) for access and support of WRF and its 3D-Var assimilation system. The authors also acknowledge the National Centers for Environmental Prediction (NCEP) for making analysis data available at their site. The radiosonde data were obtained from the University of Wyoming website. The ICOADS data were obtained from ftp.dss.ucar.edu. The AIRS and TRMM data were obtained from NASA websites and is gratefully acknowledged. The authors thank Dr. Dale Barker and Dr. S. R. H. Rizvi of NCAR for discussions regarding the generation of BES for WRF 3D-Var. The authors thank the anonymous reviewers for their critical and insightful comments/suggestions, which were helpful in substantially improving the presentation of the manuscript. This work was supported by a research grant from CSIR (PPD), India.

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  1. CSIR Centre for Mathematical Modelling and Computer Simulation (C-MMACS), NAL Belur Campus, Bangalore, 560037, India

    V. Rakesh & P. Goswami

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  1. V. Rakesh
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  2. P. Goswami
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Correspondence to P. Goswami.

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Rakesh, V., Goswami, P. Impact of background error statistics on 3D-Var assimilation: case study over the Indian region. Meteorol Atmos Phys 112, 63–79 (2011). https://doi.org/10.1007/s00703-011-0128-x

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