Jaydeep Singh

Jaydeep Singh
Aryabhatta Research Institute of Observational Sciences | ARIES · Atmospheric Division

Master of Science

About

11
Publications
5,092
Reads
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77
Citations
Citations since 2017
11 Research Items
77 Citations
20172018201920202021202220230510152025
20172018201920202021202220230510152025
20172018201920202021202220230510152025
20172018201920202021202220230510152025
Introduction
Mountain Meteorology, Boundary Layer dynamics and Pollution transport, Atmospheric Modelling
Additional affiliations
September 2017 - September 2019
Aryabhatta Research Institute of Observational Sciences
Position
  • Fellow

Publications

Publications (11)
Article
Full-text available
The goal of this study is to investigate the impact of high-resolution SRTM and Corine Land Cover on the number of cloud-ground lightning flashes and their spatial distribution simulated by a numerical weather-prediction model. Two lightning episodes were selected: (1) over a non-complex terrain and (2) over a complex terrain, the Alps. Significant...
Article
The atmospheric turbulence characteristics such as energy dissipation rate (ε), eddy diffusivity (K), and refractive index structure parameter (Cn²), which are inevitable to understand the vertical mixing and transport of pollutants, momentum, and energy, are least explored over the Himalayan region owing to the unavailability of observations. Here...
Article
Full-text available
The genesis, dynamics, and impacts of a severe dust storm over the central Himalaya during June 13–17, 2018 have been investigated using in situ measurements, satellite data, and model reanalysis. A low-pressure system over northern India and prevalence of strong winds (∼20 ms−1) triggered the dust storm leading to poor visibility conditions and fi...
Article
Full-text available
The sensitive ecosystem of the central Himalayan (CH) region, which is experiencing enhanced stress from anthropogenic forcing, requires adequate atmospheric observations and an improved representation of the Himalaya in the models. However, the accuracy of atmospheric models remains limited in this region due to highly complex mountainous topograp...
Article
Measurements of equivalent black carbon (EBC) aerosols are presented for the first time from a high-altitude station Ranichauri (30°18′ N, 78°24′ E; 2200 m amsl) in the lesser Himalaya during January-December 2016. The influences of meteorology, fire emissions and transport, on [EBC] variations have been investigated here. The daily mean values of...
Article
Full-text available
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 deli...
Article
Clouds and precipitation are closely associated with each other, and a baseline understanding of such meteorological parameters on various scales including their regional climatology is essentially needed. The present article deals with the annual and seasonal distribution of different forms of precipitation (liquid, solid and drizzle) and their as...
Article
Full-text available
Elevated ozone (O3) pollution is observed every spring over the Northern Indian region including the Himalayan foothills, with a maximum typically in the month of May. However, studies investigating influences of photochemistry and dynamics in the valleys of Central Himalaya are limited. Here, in situ surface O3 observations conducted at Dehradun (...
Article
Full-text available
The variations in the ambient concentrations of particulate matter (SPM and PM10) and gaseous pollutants (SO2 and NO2) at Clock tower (CT), Raipur Road (RR) and Inter State Bus Terminal (ISBT) station in Dehradun city, Uttarakhand, India are analysed for the period of 2011‒ 2014. Mean concentrations are observed to be higher during pre-monsoon seas...

Questions

Question (1)
Question
WRF is a mesoscale model fully compressible and non-hydrostatic (optional: hydrostatic for calculation) and the order truncation error is a major source of uncertainty during the model calculation. So reducing this error we always approach higher-order accuracy methods. In WRF-ARW there are the methods: RK2 and RK3 available but not RK4 which has higher accuracy.

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