High‐resolution wind hindcast over the Bohai Sea and the Yellow Sea in East Asia: Evaluation and wind climatology analysis

Abstract

A 34 year (1979–2012) high-resolution (7 km grid) atmospheric hindcast over the Bohai Sea and the Yellow Sea (BYS) has been performed using COSMO-CLM (CCLM) forced by ERA-Interim reanalysis data (ERA-I). The accuracy of CCLM in surface wind reproduction and the added value of dynamical downscaling to ERA-I have been investigated through comparisons with the QuikSCAT Level2B 12.5 km version 3 (L2B12v3) swath data and in situ observations. The results revealed that CCLM has a reliable ability to reproduce the regional wind characteristics over the BYS. Added value to ERA-I has been detected in the coastal areas with complex orography. CCLM wind quality had strong seasonal variability, with better performance in the summer relative to ERA-I, even in the offshore areas. CCLM was better able to represent light and moderate winds but had even more added value for strong winds relative to ERA-I. The spatial digital filter method was used to investigate the scale of the added value, and the results show that CCLM adds value to ERA-I mainly in medium scales of wind variability. Furthermore, wind climatology was investigated, and significant increasing trends in the south Yellow Sea especially in winter and spring were found for seasonal mean wind speeds

Low‐Level Jets Over the Bohai Sea and Yellow Sea: Climatology, Variability, and the Relationship With Regional Atmospheric Circulations

“…In the present study, the climatology and variability features of LLJs over the BYS were investigated based on a long‐term (1979–2013) high‐resolution (7 km) atmospheric hindcast, which was produced by a regional climate model (CCLM) constrained by ERA‐Interim reanalysis. The high‐resolution data set was of good quality in terms of its ability to reproduce surface wind speeds and coastal mesoscale phenomena in comparison with observations (Li, ; Li, von Storch, & Geyer, ). In this study, we further verified the data set against several radiosonde observations and wind profiler radar observations.…”

State and Perspectives of the Concept of Large‐Scale Conditioning of Regional Climate Modelling

“…The most common application is the construction of regional climatologies for different parts of the world, namely Europe (Geyer, 2013) including the Mediterranean region (Cavicchia et al 2014a), East Asia and the Northwestern Pacific (Feser and von Storch, 2008a, b;Barcikowska et al, 2017;Li et al, 2016;Plantonov et al, 2017), the South Atlantic (Tim et al, 2015), Central Siberia (Klehmet et al, 2013); other applications are for studying meteorological processes (Kolstad et al, 2016) and regional detail in forecasting (Zhao et al, 2016). These climatologies have been used to study changing weather-related phenomena, such as storms, ocean waves, storm surges, atmospheric deposition and transport of chemical elements, marine biota modelling, carbon cycle studies, plant productivity analyses, but also for economic applications such as oil spill simulations or ship routing and design.…”

Is there added value of convection-permitting regional climate model simulations for storms over the German Bight and Northern Germany?

“…An added value for RCM simulations was found mainly due to a more detailed spatial variability of surface variables as, for instance, the 2 m temperature in coastal areas or regions with structured topography. Li et al (2016) investigated the added value of an RCM using satellite and in situ observations as references for the region of the Bohai Sea and Yellow Sea and found an added value especially in coastal regions. Winterfeldt and Weisse (2009) discussed the added value of an RCM with a resolution of 50 km for a time period of 10 years (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003) and showed an added value for RCM wind speed compared with reanalyses (they also used satellite data as a reference).…”