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作 者:吴晓京[1] 李云[1] 黄彬 王曦[1] 宋晚郊[1] WU Xiaojing LI Yun HUANG Bin WANG Xi SONG Wanjiao(National Satellite Meteorological Center ,Beijing 100081 ,China National Meteorological Center ,Beijing 100081 ,China)
机构地区:[1]国家卫星气象中心,北京100081 [2]国家气象中心,北京100081
出 处:《海洋气象学报》2017年第2期31-41,共11页Journal of Marine Meteorology
基 金:环渤海区域科技协同创新基金项目(QYXM201601);国家自然科学基金项目(41675110)
摘 要:有效的观测是提高对海雾认知和预报水平的关键因素,卫星数据是当前最可行的观测数据源,但需要高质量的观测数据和精细的检测技术。本文为提高风云二号海雾检测水平,在现有卫星观测数据条件下借鉴了动态获取云雾阈值的思想,定制设计了一套从获取动态检测阈值到温度、纹理、噪声检测等步骤的黄渤海海雾检测方法流程。对黄渤海白天海雾检测结果的检验表明,虽然对于秋、冬非海雾季月份的效果还有待提高,但在春季海雾季已接近国际同类产品水平。同时该技术方法也需要继续搜集实例,进一步优化阈值获取方案。Effective observation is a key factor in improving cognition and prediction of sea fog. Satellite data is the most feasible observational data source, but requires high quality and fine detection technology. In order to improve the sea fog detection accuracy under current conditions of FY-2 data resources, a new method of sea fog detection for Yellow Sea and Bohai Sea is put forward in this paper. The new method is based on dynamic threshold technics, and includes temperature, texture, noise detection steps. The test results of day-time sea fog detection experiments show that though it still can be improved during autumn and winter, the detection accuracy has been close to the international advanced level in spring, which is a high-occurrence season of sea fog. To further improve the new method, more sea fog events need to be collected to optimize the threshold acquisition scheme.
分 类 号:P405[天文地球—大气科学及气象学]
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