Sensitivity of spatial resolution on Weather Research and Forecasting (WRF v3.8.1) simulated meteorology over the central Himalaya
Date & Time :
Auditorium and zoom
The Himalayan region is one of the most complex and fragile geographical systems globally and has paramount importance for the climatic implications and air composition at regional to global scales. Due to the topographically complex region and very sensitive to climate change, the frequency of severe disastrous events such as cloud bursts, heavy rainfall, temperature extremities have increased during the last few decades, and the increment will remain constant as shown by future projections. Unfortunately, the lack of an observational network covering the Himalaya and foothills with sufficient spatio-temporal density inhibits understanding the governing physical and dynamical processes. The atmospheric models play an important role in filling the gap of spare observations; however, many sources of uncertainty limit the performance of the atmospheric models. Mountain systems, rapidly changing land cover, and the low altitude valleys often lie within a grid box of typical global climate models, and therefore, the model results can drift significantly from observations. Focusing on these aspects, I will present the investigation results of the effects of spatial resolution on simulated meteorology over the central Himalaya by using the state of art model Weather and Research Forecasting (WRF). The investigation highlights the need for high-resolution modeling to represent the topographic induces features and improved simulations of the climate variability over the mountainous region. This work is the part of my Ph.D. thesis entitled “Observational and modeling studies on meteorology over the Central Himalaya.” Further, I will briefly summarize the other completed and ongoing thesis-related work.
About Speaker :
Jaydeep Singh is a Ph.D. student at ARIES. This seminar forms a part of his annual evaluation.