Abstract

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.

Highlights

  • (1) United States Geological Survey (USGS), (2) MODIS‐based land use data (MODIS), (3) user-modified USGS and (4) user-modified land use data coupled with urban canopy model (UCM) for incorporation of canopy features

  • Difference in land use/land cover As stated earlier in “Description of land use datasets” section, there has been a significant change in land use/ land cover (LULC) over many areas in Delhi owing to progressive urbanization

  • It can be seen that modified and UCM LULC is closest to that observed by Mohan et al (2011) based on LISS3 image of study area

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Summary

Introduction

Land surface processes impact meteorology on local as well as climate time scales. Land cover and land use are essential parameters in land surface processes. 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.

Results
Conclusion
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