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Assessment of physical parameterization schemes in WRF over national capital region of India

Increase in the extreme weather events around the world has necessitated application of numerical weather prediction (NWP) models to forecast these events and minimize consequences. Application of NWP models requires appropriate selection of physics parameterization options for close representation...

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Published in:Meteorology and atmospheric physics 2021-04, Vol.133 (2), p.399-418
Main Authors: Gunwani, Preeti, Sati, Ankur Prabhat, Mohan, Manju, Gupta, Medhavi
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description Increase in the extreme weather events around the world has necessitated application of numerical weather prediction (NWP) models to forecast these events and minimize consequences. Application of NWP models requires appropriate selection of physics parameterization options for close representation of atmospheric processes. In this study, the WRF model performance was evaluated for varying physical parameterization of surface processes in simulating meteorology with respect to varying (i) shortwave and longwave radiation schemes, (ii) planetary boundary layer (PBL) and corresponding surface layer (SL) schemes over Delhi NCR. A total of 11 simulation sets were curated with 7 PBL schemes (ACM2, GBM, UW, MYJ, SH, TEMF and BouLac), 4 surface layer schemes (Pleim-Xiu, Revised MM5, Eta and TEMF), 3 shortwave radiation schemes (Dudhia, New Goddard and RRTMG), 3 longwave radiation schemes (RRTM, New Goddard and RRTMG) and 2 land surface models (LSM) (Pleim-Xiu and Noah). Sensitivity experiments are performed at a fine resolution (1 km) with updated LULC input. Based on the sensitivity analysis, it is inferred that the simulation set which works best for the region is TEMF PBL, TEMF SL, Dudhia shortwave radiation, RRTM longwave radiation and Noah LSM schemes. The TEMF PBL scheme is designed as hybrid (local–nonlocal) scheme and thereby, with consideration of both local and nonlocal viewpoints it is noted that the near-surface meteorological parameters are depicted with greater accuracy. To further address the model biases it is important to refine the physical parameterizations schemes in the WRF model or using different bias correction and data assimilation techniques.
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subjects Aquatic Pollution
Atmospheric models
Atmospheric processes
Atmospheric Sciences
Boundary layers
Data assimilation
Data collection
Earth and Environmental Science
Earth Sciences
Extreme weather
Land surface models
Long wave radiation
Math. Appl. in Environmental Science
Meteorological parameters
Meteorological satellites
Meteorology
Model accuracy
Numerical weather forecasting
Original Paper
Parameterization
Physics
Planetary boundary layer
Radiation
Sensitivity analysis
Short wave radiation
Simulation
Surface boundary layer
Surface layers
Terrestrial Pollution
Waste Water Technology
Water Management
Water Pollution Control
Weather forecasting
title Assessment of physical parameterization schemes in WRF over national capital region of India
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