Modeling Seasonal Variation in Urban Weather in Sub-Tropical Region of Delhi
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RESEARCH ARTICLE
Modeling Seasonal Variation in Urban Weather in Sub-Tropical Region of Delhi Kshama Gupta1 • Pushplata2 • Allaka Lalitha3 • Payel Ghosh Dastidar1 • Jillela Malleswara Rao4 Praveen Thakur1 • Jai Shankar Gummapu5 • A. Senthil Kumar3
•
Received: 23 December 2019 / Accepted: 5 October 2020 Ó Indian Society of Remote Sensing 2020
Abstract Complexity and heterogeneity of urban areas lead to difficulty in urban weather simulations and climate modeling. Diversity and size of urban areas necessitate to downscale global climate models to urban scale (* hundreds of meters) and to enhance urban parameterization in the models to realistically simulate urban weather conditions. Hence, in this study, a methodology has been developed to generate multi-class urban land use land cover (LULC) by employing Resourcesat-2 LISS IV data. Weather Research and Forecast (WRF) model which is also a mesoscale numerical weather prediction and regional climate model was utilized to downscale the meteorological parameters up to 0.5 km grid resolution. Multi-class urban LULC prepared with improved urban parameters and updated Land Surface Parameters (LSPs) was ingested in model for Delhi to evaluate the model performance in three dominant seasons, i.e., summer, monsoon and winter. Evaluation of model performance with ground observation data revealed that multi-class urban LULC along with updated LSPs provided improved RMSE values of 2.31° C, 1.79 m/s and 0.94 mbar as compared to ingestion of multiclass urban LULC only (RMSE values of 3.42° C, 3.72 m/s and 1.58 mbar) for temperature at 2 m, wind speed and surface pressure, respectively. Temperature is found to be highest in summer season (38.58° C) and lowest in winter season while relative humidity is highest in monsoon season (* 88%) and lowest in summer season (* 30%). The study highlights the importance of ingestion of updated LSPs along with updated multi-class urban LULC for enhanced model performance. Keywords Urban weather WRF Resourcesat-2 LISS IV Multi-class urban LULC Delhi
Introduction Urban weather is complex to model and predict because of its highly heterogeneous nature and convoluted development. They are generally warmer than their surroundings, which manifests into Urban Heat Island (UHI) & Kshama Gupta [email protected] 1
Indian Institute of Remote Sensing, 4, Kalidas Road, Dehradun, Uttrakhand, India
2
Indian Institute of Technology, Roorkee, Uttrakhand, India
3
Centre for Space Science and Technology Education in Asia and the Pacific, Dehradun, Uttrakhand, India
4
Advanced Data Processing Research Institute, Hyderabad, Telengana, India
5
College of Engineering, Andhra University, Visakhapatnam, India
phenomenon (Howard 1820; Arnfield 2003). The magnitude of UHI is a function of urban morphology, size, composition of land surface covers, thermal properties of building materials, 3D configuration of urban canyons, anthropogenic heat emission and synoptic weather conditions (Stewart and Oke 2012; Bechtel et al. 2015). Most of the global cli
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