Indian Institute Of Technology (IIT) Roorkee, Uttarakhand
CO-Principal Investigator
Dr. Sumit Sen
Indian Institute Of Technology (IIT) Roorkee, Uttarakhand,Roorkee - Haridwar Highway, Roorkee,Uttarakhand,Haridwar-247667
Project Overview
A major source of uncertainty in forecasting high-impact weather events such as cloudbursts, extreme rainfall, tropical cyclones, the spread of forest fires, etc. is due to inaccurate parameterization of surface-atmosphere exchange processes in the weather forecast as well as climate models. An accurate and efficient parametrization of physical boundary layer processes is essential to mitigate and manage the impact of high-impact weather events through early warning systems. The high-frequency surface flux measurements, which are required for an improved understanding of surface-atmosphere exchange processes and minimizing the uncertainty in parameterizations are rare in the high-altitude Himalayan region. A number of field experiments have been carried out to develop numerous parameterization schemes consistent with the atmospheric conditions over the Indian sub-continent. Data acquired from these experiments have been frequently utilized to study the surface-atmosphere exchange processes over the Indian region. This has led to an improved understanding of boundary/surface layer features over land as well as ocean surfaces (Ramachandranan et al., 1994; Krishnan and Kunhikrishnan, 2002; Tyagi and Satyanarayana, 2012; Sharan and Srivastava, 2016; Srivastava and Sharan, 2015). However, due to a lack of observational data in the Indian Himalayan region, there is still uncertainty in the parameterization of the transfer coefficients of momentum (CD), heat (CH) and moisture (CE) during high-impact weather events. The objective of the proposed study is to generate high-quality flux observations for an improved parameterization of surface-atmosphere exchange processes (heat, momentum and moisture) in the high-altitude Himalayan region. This would help improve the numerical weather prediction models over the region vulnerable to extreme weather events such as cloudbursts, extreme precipitation, and landslides.
Source
Source
Anusandhan National Research Foundation/Science and Engineering Research Board (SERB), DST 2023-24