Abstract
Abstract. Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15–18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor–Yamada–Janjic PBL and Betts–Miller–Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme compared to the simple Slab model. To analyse the effect of model grid spacing, two sets of downscaling ratios – (i) 1 : 3, global to regional (G2R) scale and (ii) 1 : 9, global to convection-permitting scale (G2C) – are employed. Results indicate that a higher downscaling ratio (G2C) causes higher variability and consequently large errors in the simulations. Therefore, G2R is adopted as a suitable choice for simulating heavy rainfall event in the present case study. Further, the WRF-simulated rainfall is found to exhibit less bias when compared with the NCEP FiNaL (FNL) reanalysis data.
Highlights
Indian summer monsoon rainfall (ISMR) is often associated with very heavy (124.5 to 244.4 mm day−1) to extremely heavy rainfall (Indian Meteorological Department, Terminologies and Glossary; http:// imd.gov.in/section/nhac/termglossary.pdf), during June to September months
The ability of the Weather Research and Forecasting (WRF) model configuration to simulate an extreme rainfall event is evaluated by comparing the simulated rainfall with the observations through indices such as scale error (SE), which is the ratio of standard deviation of model simulations to the observed standard deviation, and coefficient of variation (CV) in addition to Mean absolute error (MAE), root mean square error (RMSE) and β
The main focus of this paper is to provide a general guideline for setting up the WRF model configuration to simulate heavy rainfall events
Summary
Indian summer monsoon rainfall (ISMR) is often associated with very heavy (124.5 to 244.4 mm day−1) to extremely heavy (more than 244.5 mm day−1) rainfall (Indian Meteorological Department, Terminologies and Glossary; http:// imd.gov.in/section/nhac/termglossary.pdf), during June to September months. The conclusions regarding which CU scheme performs best would be intimately tied to the choice of the MP or land surface options considered in conducting the numerical experiments With this perspective, this paper seeks to assess the sensitivity of the WRF model in predicting heavy to extremely heavy rainfall episodes over the Ganga Basin in the foothills of the Himalayas. The monsoon low provided the moisture feed and the upper-level westerly trough provided the divergence to lift the moisture This whole system eventually led to an unanticipated heavy rainfall during 15–18 June 2013 in the Kedarnath valley and adjoining areas in the state of Uttarakhand, India (Kotal et al, 2014; Ray et al, 2014; Chevuturi and Dimri, 2016; Rajesh et al, 2016). The region is of social, cultural and economic importance to India, further making this study necessary
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