Abstract
Weather models coupled with urban parameterizations require robust and realistic urban parameter inputs such as actual building distribution. Acquiring real building parameters often require huge amount of time and money. In this study, we introduce a simplified but precise approximation of urban parameters through a readily-available, high-resolution global dataset. Regression equations were derived from the spatial relationship of global 1-km population dataset adjusted by nightlight distribution to real urban parameters in Japan and Istanbul, Turkey. These equations can readily estimate urban parameters globally. Derived global urban parameters were incorporated into a weather model to investigate urban heat island in neighboring megacities in South and Southeast Asia. UHI phenomena of 5 mega cities depended a great deal on location and climate zone of each city.
