Ten-year climatology of surface winds over the coastal China seas using QuikSCAT data and comparison with NCEP reanalysis
Abstract
Using high-resolution QuikSCAT data, a 10-year climatology of surface winds over the coastal China seas is compiled. The statistical characteristics of both high- and low-frequency winds, as well as their temporal and spatial variations, are exhaustively documented. The surface wind in winter is found to be the strongest (wind speed 7.46 m/s) and steadiest (wind steadiness 82.83), corresponding to the East Asian winter monsoon. Wind gustiness is largest in spring (1.94). The mean wind speed increases from north to south, with the South China Sea (SCS) being the windiest region (wind speed 5.39 m/s). Two wind maxima with mean wind speeds exceeding 12 m/s are identified in the Taiwan Strait and the western part of the Bashi Channel in winter and autumn. These winds then weaken and become part of a lower wind area across Taiwan Island in summer. The Bohai Sea and the Yellow Sea (BSYS) are found to have the highest gustiness in spring, corresponding to their low wind speed and steadiness. The East China Sea (ECS) has modest mean wind speed, steadiness, and gustiness. Relevant results based on NCEP/NCAR reanalysis (NRA) data are derived for an intercomparison. The NRA also shows the major climatological features of winds over the China seas, especially for relatively long-term (monthly and seasonal) mean winds. However, these data can not adequately represent some important wind maxima or their seasonal evolution. Finally it is found that both the QuikSCAT and NRA data can reveal the extreme winds of typical weather systems over the China seas. But limitations are found for both datasets.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2010
- Bibcode:
- 2010AGUFMGC13A0676S
- Keywords:
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- 3309 ATMOSPHERIC PROCESSES / Climatology;
- 3339 ATMOSPHERIC PROCESSES / Ocean/atmosphere interactions;
- 3360 ATMOSPHERIC PROCESSES / Remote sensing;
- 3364 ATMOSPHERIC PROCESSES / Synoptic-scale meteorology