洋山海域海雾客观预报方法研究

An objective forecast method for sea fog over the Yangshan Sea

利用上海小洋山多年自动气象站数据和海温再分析资料及洋山浮标海温等资料,以风向、风速、气温、气海温差和相对湿度等要素作为预报海雾的因子。首先将各预报因子按其阈值不同进行分区组合,每一个分区组合均对应一类海雾发生时的条件,再根据每一时刻的各预报因子值将全部历史样本分别归入各分区中,然后根据预报对象的各因子判断其所属分区,利用该分区的历史样本建立该次过程的能见度预报方程,最后对这一方法分别进行了后报检验和个例预报。该方法克服了传统的单一线性回归方程不能描述预报因子与能见度的非线性关系和预报方程需设定临界值的问题。不同类型的雾用不同的方程进行预报,使得方程更具有物理意义。检验结果表明,该方法对于具有充足相似历史样本的海雾事件有较好的预报效果;随着不同类型海雾历史样本的增加,预报效果能得到进一步提高。

Statistical equations for sea-fog forecast were established using the Yangshan automatic weather station data, sea surface temperature of reanalysis data, and buoy temperature data over Yangshan Sea area in recent years. Many elements, including wind direction, wind speed, air temperature, temperature difference between air and sea surface, and relative humidity were selected as factors for sea-fog forecast. For establishing the forecast equations, firstly each of the forecast factors was divided into several ranges, which were then crossly combined to form a number of groups. Each group corresponds to a kind of conditions for generating and sustaining sea fog. Secondly, based on their historical sample groups, visibility forecast equations were established. This method can overcome the weakness that traditional linear regression equations can’t describe the nonlinear relationship between forecast factors and visibility, and the weakness that critical thresholds must be set in traditional regression equations. In this study, the sea fog in different conditions can be forecasted by more applicable equations, which have physical meanings. The results show that using this method good forecast can be acquired for sea-fog events with sufficient historical samples. With accumulation of sea-fog samples in different conditions, sea-fog forecast can be further improved.