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Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya


Pozzer,  Andrea
Atmospheric Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

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Singh, J., Singh, N., Ojha, N., Sharma, A., Pozzer, A., Kumar, N. K., et al. (2020). Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya. Geoscientific Model Development Discussions, 13. doi:10.5194/gmd-2020-12.

Cite as: http://hdl.handle.net/21.11116/0000-0007-6518-D
The sensitive and fragile ecosystem of the central Himalayan (CH) region, experiencing enhanced anthropogenic pressure, requires adequate atmospheric observations and an improved representation of Himalaya in the models. However, the accuracies of atmospheric models remain limited here due to highly complex mountainous topography. This article delineates the effects of spatial resolution on the modeled meteorology and dynamics over the CH by combining the WRF (Weather Research and Forecasting) model with the GVAX (Ganges Valley Aerosol Experiment) observations during the summer monsoon. WRF simulation is performed over a domain (d01) encompassing northern India at 15 km × 15 km resolution, and two nests: d02 (5 km × 5 km) and d03 (1 km × 1 km) centered over CH with boundary conditions from respective parent domains. WRF simulations reveal higher variability in meteorology e.g. Relative Humidity (RH = 71.4–93.3 %), Wind speed (WS = 1.6–3.1 ms−1), as compared to the ERA Interim reanalysis (RH = 79.4–85.0, and WS = 1.3–2.3 ms−1) over the northern India owing to higher resolution. WRF simulated temporal evolution of meteorological profiles is seen to be in agreement with the balloon-borne measurements with stronger correlations aloft (r = 0.44–0.92), than those in the lower troposphere (r = 0.27–0.48). However, the model overestimates temperature (warm bias by 2.8 °C) and underestimates RH (dry bias by 7.6 %) at surface in the d01. Model results show a significant improvement in d03 (P = 827.6 hPa, T = 19.8 °C, RH = 90.2 %) and are closer to the GVAX observations (P = 801.3, T = 19.5, RH = 94.5 %). Temporal variations in near surface P, T and RH are also reproduced by WRF d03 to an extent (r > 0.5). A sensitivity simulation incorporating the feedback from nested domain demonstrated improvements in simulated P, T and RH over CH. Our study shows the WRF model set up at finer spatial resolution can significantly reduce the biases in simulated meteorology and such an improved representation of CH can be adopted through domain feedback into regional-scale simulations. Interestingly, WRF simulates a dominant easterly wind component at 1 km × 1 km resolution (d03), which was missing in the coarse simulations; however, a frequent southeastward wind component remained underestimated. Model simulation implementing a high resolution (3 s) topography input (SRTM) improved the prediction of wind directions, nevertheless, further improvements are required to better reproduce the observed local-scale dynamics over the CH.