Urban heat island effect has been assessed using weather research and forecasting model (WRF v3.5) focusing on air temperature and surface skin temperature in the sub-tropical urban Indian megacity of Delhi. Impact of urbanization-related changes in land use/land cover (LULC) on model outputs has been analyzed. Four simulations have been carried out with different types of LULC data viz. (1) USGS, (2) MODIS, (3) user-modified USGS and (4) user-modified land use data coupled with urban canopy model (UCM) for incorporation of canopy features. Heat island intensities have been estimated based on these simulations and subsequently compared with those derived from in situ and satellite observations. There is a significant improvement in model performance with modification of LULC and inclusion of UCM. Overall, RMSEs for near surface temperature improved from 6.3 to 3.9 °C and index of agreement for mean urban heat island intensities (UHI) improved from 0.4 to 0.7 with modified land use coupled with UCM. In general, model is able to capture the magnitude of UHI as well as high UHI zones well. A simple method of bias correction in model has been applied to improve model results for further application. The study highlights the importance of appropriate and updated the representation of land use–land cover and urban canopies for improving predictive capabilities of the mesoscale models. Urban heat island has been known to have effect on human thermal comfort. In the present study, Heat Index, a commonly used indicator of thermal comfort, is assessed spatially using WRF-UCM derived results. Urban areas were found to have higher Heat Index than non-urban areas by a difference of about 1.5–2 °C. Further, it was found that urban canopy effect leads to rise in thermal discomfort by increasing Heat Index. There is an increase in Heat Index of about 2.0–2.5 °C at dense built-up stations. Decrease in thermal comfort causes a significant impact on energy demand. Hence, analysis of urban heat island effect vis-a-vis thermal comfort provides useful information with regard to impact on human comfort and welfare.

中文翻译：

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WRF-城市雨棚模型评估，用于评估不同土地利用/土地覆盖条件下印度城市流域的热岛和热舒适度

已使用天气研究和预报模型（WRF v3.5）对城市热岛效应进行了评估，该模型着重于亚热带城市印度大城市德里的空气温度和表皮温度。分析了与城市化有关的土地利用/土地覆被变化（LULC）对模型产出的影响。使用不同类型的LULC数据进行了四次模拟。（1）USGS，（2）MODIS，（3）用户修改的USGS和（4）用户修改的土地利用数据，结合城市冠层模型（UCM）以合并冠层特征。根据这些模拟估算了热岛强度，然后将其与从实地和卫星观测中得出的强度进行了比较。通过修改LULC和包含UCM，模型性能有了显着改善。总体，在土地改良和UCM结合的情况下，近地表温度的RMSE从6.3升高到3.9°C，城市平均热岛强度（UHI）的一致性指数从0.4升高到0.7。通常，模型能够很好地捕获UHI以及高UHI区的大小。在模型中使用了一种简单的偏差校正方法来改善模型结果，以便进一步应用。该研究强调了适当和更新土地利用的表述的重要性-土地覆盖和城市冠层对于提高中尺度模型的预测能力。已知城市热岛对人类的热舒适性有影响。在本研究中，使用WRF-UCM得出的结果在空间上评估了热指数（一种常用的热舒适指标）。人们发现城市地区的热指数比非城市地区高1.5至2°C。此外，已经发现，城市树冠效应通过增加热指数而导致热不适感增加。在密集的建筑站中，热指数增加了约2.0–2.5°C。热舒适性的降低会严重影响能源需求。因此，相对于热舒适性而言，城市热岛效应的分析提供了有关对人类舒适性和福利影响的有用信息。