Javascript must be enabled to continue!
Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya
View through CrossRef
Abstract. 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.
Title: Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central
Himalaya
Description:
Abstract.
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.
Related Results
Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya
Effects of spatial resolution on WRF v3.8.1 simulated meteorology over the central Himalaya
Abstract. The sensitive ecosystem of the central Himalayan (CH) region, which is experiencing
enhanced stress from anthropogenic forcing, requires adequate atmospheric
observations...
Seasonal prediction of Indian summer monsoon using WRF: A dynamical downscaling perspective
Seasonal prediction of Indian summer monsoon using WRF: A dynamical downscaling perspective
Abstract
Seasonal forecasting of the Indian summer monsoon by dynamically downscaling the CFSv2 output using a high resolution WRF model over the hindcast period of 1982–20...
Coupling the high-complexity land surface model ACASA to the mesoscale model WRF
Coupling the high-complexity land surface model ACASA to the mesoscale model WRF
Abstract. In this study, the Weather Research and Forecasting (WRF) model is coupled with the Advanced Canopy–Atmosphere–Soil Algorithm (ACASA), a high-complexity land surface mode...
Coupling the high complexity land surface model ACASA to the mesoscale model WRF
Coupling the high complexity land surface model ACASA to the mesoscale model WRF
Abstract. In this study, the Weather Research and Forecasting Model (WRF) is coupled with the Advanced Canopy–Atmosphere–Soil Algorithm (ACASA), a high complexity land surface mode...
Slow exhumation of the Greater Himalaya in the Yadong region, the transition between the Central and Eastern Himalaya, during the Late Neogene
Slow exhumation of the Greater Himalaya in the Yadong region, the transition between the Central and Eastern Himalaya, during the Late Neogene
The Yadong area, at the geographic boundary between the Central and Eastern Himalaya, contains the largest along-strike structural discontinuity in the Himalaya. We conducted zirco...
[RETRACTED] Keanu Reeves CBD Gummies v1
[RETRACTED] Keanu Reeves CBD Gummies v1
[RETRACTED]Keanu Reeves CBD Gummies ==❱❱ Huge Discounts:[HURRY UP ] Absolute Keanu Reeves CBD Gummies (Available)Order Online Only!! ❰❰= https://www.facebook.com/Keanu-Reeves-CBD-G...
Climate-driven late Quaternary fan surface abandonment in the NW Himalaya
Climate-driven late Quaternary fan surface abandonment in the NW Himalaya
ABSTRACT
We defined the timing of surface abandonment for 10 alluvial and debris-flow fans across contrasting climatic settings in the NW Himalaya of northern India ...
Future climate change of stability indices for the Iberian Peninsula
Future climate change of stability indices for the Iberian Peninsula
ABSTRACTStability indices evaluate the atmospheric instability which is a basic and precursor ingredient needed for storms to develop. In this study, we evaluated changes of some a...

