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Modeling Seasonal Variation in Urban Weather in Sub-Tropical Region of Delhi
Journal of the Indian Society of Remote Sensing ( IF 2.2 ) Pub Date : 2020-10-16 , DOI: 10.1007/s12524-020-01198-1
Kshama Gupta , Pushplata , Allaka Lalitha , Payel Ghosh Dastidar , Jillela Malleswara Rao , Praveen Thakur , Jai Shankar Gummapu , A. Senthil Kumar

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.

中文翻译:

德里亚热带地区城市天气季节变化建模

城市地区的复杂性和异质性导致城市天气模拟和气候建模的困难。城市地区的多样性和规模需要将全球气候模型缩小到城市规模(~数百米),并加强模型中的城市参数化,以真实地模拟城市天气条件。因此,在本研究中,通过采用 Resourcesat-2 LISS IV 数据开发了一种方法来生成多级城市土地利用土地覆盖 (LULC)。天气研究和预测 (WRF) 模型也是一种中尺度数值天气预报和区域气候模型,用于将气象参数缩小到 0.5 公里的网格分辨率。在德里模型中摄取了用改进的城市参数和更新的地表参数 (LSP) 准备的多类城市 LULC,以评估模型在三个主要季节(即夏季、季风和冬季)的性能。使用地面观测数据对模型性能进行评估表明,与仅摄取多类城市 LULC 相比,多类城市 LULC 和更新的 LSP 提供了改进的 RMSE 值 2.31° C、1.79 m/s 和 0.94 mbar(RMSE 值为3.42° C、3.72 m/s 和 1.58 mbar),分别对应 2 m 处的温度、风速和表面压力。发现温度在夏季最高 (38.58° C),在冬季最低,而相对湿度在季风季节最高 (~ 88%),夏季最低 (~ 30%)。
更新日期:2020-10-16
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