Estimation of wet variable’s background error information for regional model

Yanlai Zhao; Weimin Zhang; Ruihong Mo

doi:10.1117/12.2502938

9 August 2018 Estimation of wet variable’s background error information for regional model

Yanlai Zhao, Weimin Zhang, Ruihong Mo

Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018); 108063U (2018) https://doi.org/10.1117/12.2502938
Event: Tenth International Conference on Digital Image Processing (ICDIP 2018), 2018, Shanghai, China

Abstract

In order to improve the humidity analysis of the WRF model, a new multivariable balance constraint scheme has been introduced to estimate wet variable’s background error information from a series of historical forecasts. The new scheme consists of three critical procedures: physical transformation, vertical transformation and horizontal transformation. By removing the balanced part associated with other control variables, the unbalanced part of relative humidity is used as the new wet control variable. Statistical results show that relative humidity’s background error structure appears an obviously localized characterization, which has a large negative value on model high level in the vertical direction and a stable characteristic length scales about 20km in the horizontal direction.

Citation Download Citation

Yanlai Zhao, Weimin Zhang, and Ruihong Mo "Estimation of wet variable’s background error information for regional model", Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108063U (9 August 2018); https://doi.org/10.1117/12.2502938

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