广东雾霾天气能见度时空特征分析--年际年代际变化

Spatial and Temporal Distribution of Visibility under Fog and Haze Conditions in Guangdong Province:Annual and Inter-Annual Change

利用1980―2003年广东省22个地面气象观测站24 a的气象观测资料,采用经验正交函数分解(EOF)和连续功率谱分析方法,分析广东省雾霾天气下能见度的时空分布特征。结果发现,广东地区雾霾天气能见度的年际年代际变化主要表现在EOF的前2个主模态,方差贡献分别占17.4﹪和11.8﹪。其中第1主模态的空间场与广东省自然地理区划基本对应,其时间序列反映的主要是雾霾天气下能见度的年代际变化。在1992年前后由正向负的逐渐减小可能与上世纪90年代以后广东地区经济活动的明显增强有关;第2主模态的空间场反映出广东地区能见度时空变化一致性的特点,其时间序列具有显著的准2 a、4 a和8 a振荡周期,所反映的主要是雾霾天气能见度的年际变化,可能与大尺度季风区对ENSO年际变化信号的响应有关。

Analysis on the temporal and spatial distribution of visibility under fog and haze conditions is of great significance to understanding and forecasting the occurrence of the fog and haze. In this paper, meteorological visibility collected from 26 ground stations in Guangdong Province from 1980 to 2003 was used for the fog and haze analysis. Empirical orthogonal function （EOF） method and continuous power spectral analysis method were applied to the 24 years observation data. The spatial and temporal distribution of the visibility under fog and haze weather condition was then analyzed. The EOF results show that the inter-annual changes of the visibility under fog and haze condition of Guangdong Province can be divided into two main modes. The spatial distribution of the first mode （which rated at 17.4%） is exactly corresponding to the geographical divisions of Guangdong Province. The time series distribution of the first mode reflects the inter-annual changes of the visibility in fog and haze conditions. The decrease of the time sequence from positive to negative in 1992 is mainly due to the economic development of Guangdong Province since 1990s. The second mode （rated at 11.8%） reflects consistent spatial and temporal changes of the visibility. Its time sequence indicates 3 inter-annual periodical oscillations, which are the 2-year periodical oscillations, 4-year periodical oscillations and 8-year periodical oscillations. This annual periodicity of the visibility under fog and haze conditions may be primarily related to the large-scale tele-connection of monsoon and ENSO（E1 Nino/South Oscillation）.