P29 Micro-climate downscaling over Shenzhen, China, with different high-resolution global climate reanalysis data

Zhang, Yongxin, Yubao Liu, National Center for Atmoshperic Research, Lei Li, Yin Jiang, Shenzhen National Climate Observatory, China, Wanli Wu, Linlin Pan, and Yuewei Liu, National Center for Atmospheric Research

Climate downscaling using a dynamic model relies on (a) adequate simulation of the local terrain and land surface forcing and fine-scale weather systems, (b) accurate global reanalysis data that provide proper large scale weather forcing through lateral boundary conditions, and in some cases, initial conditions, and (c) extensively validated model output. Over Southeast China where Shenzhen, one of the most dynamic and fastest developing megacities in the world, is situated, hilly terrain and intricate land-sea contrasts result in a host of local circulations that are essential to consider in micro-climate simulations and climate change assessment at regional and local scales. The uniqueness of the Shenzhen domain is that a very dense observational network has been established for providing continuous observations that can be used for micro-climate downscaling as well as model output verification.

In this study, WRF is used to downscale newly emerged high-resolution global climate reanalysis data over the Shenzhen domain at multiple grid sizes (27 km -> 9 km -> 3 km -> 1 km). The global reanalyses tested include the NCEP CFSR (Climate Forecast System Reanalysis), ECMWF ERA-Interim, NASA MERRA (Modern Era Retrospective-Analysis for Research and Applications), and NCEP FNL (Final Analysis) data. The objective of this current study is two-fold: (a) identifying which climate reanalysis works best for the Shenzhen domain, and (b) examining the impacts of the model grid size increases on the model simulations. In this presentation, the analysis results and implications