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A new model to downscale urban and rural surface and air temperatures evaluated in Shanghai, China

Liu, D., Grimmond, C. S. B., Tan, J., Ao, X., Peng, J., Cui, L., Ma, B., Hu, Y. and Du, M. (2018) A new model to downscale urban and rural surface and air temperatures evaluated in Shanghai, China. Journal of Applied Meteorology and Climatology. ISSN 1558-8424 (In Press)

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To link to this item DOI: 10.1175/JAMC-D-17-0255.1

Abstract/Summary

A simple model, TsT2m (Surface Temperature and near surface air Temperature (at 2 m) model), is developed to downscale numerical model output (such as from ECMWF) to obtain higher temporal and spatial resolution surface and near surface air temperature. It is evaluated in Shanghai, China. Surface temperature (TS) and near surface air temperature (Ta) sub-models account for variations in land covers and their different thermal properties, resulting in spatial variations of surface and air temperature. The Net All Wave Radiation Parameterization (NARP) scheme is used to compute net wave radiation for the surface temperature sub-model, the Objective Hysteresis Model (OHM) is used to calculate the net storage heat fluxes, and the surface temperature is obtained by the force-restore method. The near surface air temperature sub-model considers the horizontal and vertical energy changes for a column of well mixed air above the surface. Modeled surface temperatures reproduce the general pattern of MODIS images well, while providing more detailed patterns of the surface urban heat island. However, the simulated surface temperatures capture the warmer urban land cover and are 10.3°C warmer on average than those derived from the coarser MODIS data. For other land cover types values are more similar. Downscaled, higher temporal and spatial resolution air temperatures are compared to observations at 110 Automatic Weather Stations across Shanghai. After downscaling with the TsT2m model, the average forecast accuracy of near surface air temperature is improved by about 20%. The scheme developed has considerable potential for prediction and mitigation of urban climate conditions, particularly for weather and climate services related to heat stress

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:78893
Publisher:American Meteorological Society

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