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The assessment of the human-induced climate change on a global level can be carried out only after the study of local and regional climate change patterns. This study was an attempt to establish a link between regional climate and the surface parameters. The study was carried out for Ranchi, India to assess the changes in climatic pattern over the years (1901-2016) and applied Mann-Kendall Trend analysis test. The pre-monsoon period was chosen due to high intensity and number of thunderstorms taking place in the study area. Maximum temperature (Tmax), minimum temperature (Tmin), rainfall (P) &diurnal temperature range (DTR) for the months (March, April & May) were studied, and a significant negative trend in Tmax and DTR was observed. Autoregressive Integrated Moving Average (ARIMA) model was applied to fit the datasets and predict 5 values for the meteorological parameters, and the model depicted positive temperature trends and negative rainfall and DTR trends in the future. Land surface process parameters such as sensible heat flux, momentum flux, frictional velocity, shortwave radiation, longwave radiation, and net radiation for Ranchi were also fit into the ARIMA model, and the fitness of the model and predictions were determined.

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Poulomi Chakravarty, & Manoj Kumar. (2020). Trend Analysis and ARIMA Modeling to Assess Meteorological and Surface Parameters In Ranchi, India During Pre-Monsoon Months. GIS Business, 15(2), 69-87.