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Modeling Seasonal Variation in Urban Weather in Sub-Tropical Region of Delhi

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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 multi-class 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.

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Acknowledgements

Authors are grateful to Indian Institute of Remote Sensing, Dehradun (a unit of Indian Space Research Organization), and Centre for Space Science and Technology Education in Asia–Pacific (CSSTE-AP), Dehradun, for financial and logistics support. They are also grateful to Regional Meteorological Centre, Indian Meteorological Department, New Delhi, and Indian Agricultural Research Institute, New Delhi, for providing surface observation data for validation. Authors wish to thank reviewers for their valuable time and critical suggestions for improvement in manuscript.

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Authors and Affiliations

  1. Indian Institute of Remote Sensing, 4, Kalidas Road, Dehradun, Uttrakhand, India

    Kshama Gupta, Payel Ghosh Dastidar & Praveen Thakur

  2. Indian Institute of Technology, Roorkee, Uttrakhand, India

    Pushplata

  3. Centre for Space Science and Technology Education in Asia and the Pacific, Dehradun, Uttrakhand, India

    Allaka Lalitha & A. Senthil Kumar

  4. Advanced Data Processing Research Institute, Hyderabad, Telengana, India

    Jillela Malleswara Rao

  5. College of Engineering, Andhra University, Visakhapatnam, India

    Jai Shankar Gummapu

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  1. Kshama Gupta
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Gupta, K., Pushplata, Lalitha, A. et al. Modeling Seasonal Variation in Urban Weather in Sub-Tropical Region of Delhi. J Indian Soc Remote Sens 49, 193–213 (2021). https://doi.org/10.1007/s12524-020-01198-1

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