Sensitivity of WRF Cloud Microphysics to Simulations of a Convective Storm Over the Nepal Himalayas
Rudra K. Shrestha1, *, Paul J. Connolly2, Martin W. Gallagher2
Identifiers and Pagination:Year: 2017
First Page: 29
Last Page: 43
Publisher Id: TOASCJ-11-29
Article History:Received Date: 13/12/2016
Revision Received Date: 16/02/2017
Acceptance Date: 10/03/2017
Electronic publication date: 30/06/2017
Collection year: 2017
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
This paper investigates sensitivity of bulk microphysical parameterization (BMP) schemes within the Weather Research and Forecasting (WRF) model to simulate a convective storm that generally evolves during pre-monsoon season (March – May) across the foothills of the Himalayas.
Four mixed-phase BMP schemes (Morrison, Lin, WDM6, and WSM6), which are parameterized with an increasing complexity from single to double moments of particle distribution to represent cloud processes, are used with an explicit convection permitting grid resolution (3 km x 3 km). Experiments are set up to simulate a convective storm that occurred in the late afternoon of 18th May 2011 and compared with i) Satellite-based tropical rainfall measuring mission (TRMM) 3B42 v7 data, and ii) Ground-based observations at Nagarkot (27.7°N, 85.5°E), Nepal.
Our results show that the simulated storm characteristics are not overly sensitive to the chosen BMP schemes. In general, all the BMP schemes produce similar rainfall characteristics and compares reasonably well with the observations across Siwalik Hills and Middle Mountains, which act as a topographic barrier to low level circulations and receive more rain. The schemes, however, show negative bias across central Nepal including the Kathmandu Valley, albeit the magnitude and spatial distribution of bias are different between the schemes. In contrast, upper level total water condensate and cloud fraction show a strong sensitivity to the BMP schemes.
Overall, the Morrison scheme, in addition to warm clouds which also predict double moment distribution of all hydrometeors in the cold-cloud processes, a dominant cloud forming process in the Himalayas, accurately represents the mechanism and outperforms the simplified schemes based on root mean square error (RMSE) analysis.