观测间隔对极值风速的影响研究

由于早期观测设备都需要人工干预，气象部门提供的风气候历史观测数据一般都不是连续观测的，常常是每隔1 h或若干小时观测一次，这导致的数据遗漏可能会使极值风速的估算存在偏差。该文将美国11座城市气象站记录的风速连续观测数据，分别制作成“每隔1 h”、“每隔6 h”以及“无间隔连续”3种观测间隔的2 min平均风速值序列。结合改进的独立风暴法和与极值I型分布模型计算得到给定重现期的风速极值，并分析了3种观测间隔之间关系。研究结果表明:观测间隔为“1 h”和“6 h”的观测数据序列对应的日风速极值，与“连续观测”序列对应的日风速极值的差值均满足瑞利分布；利用风速差值的概率分布特性给出了修正方法。修正后的数据可给出准确性更高的极值风速估算结果。

STUDY ON THE INFLUENCE OF OBSERVING INTERVAL ON EXTREME WIND SPEED

Because the early observation equipment needs manual intervention, the historical observation data of wind and climate provided by the meteorological department are generally not continuous data. They are often observed every one or several hours, so data omission is inevitable, which may lead to deviation in the estimate of extreme wind speed. The continuous observation data of wind speed recorded by 11 urban meteorological stations in the United States are extracted into two minutes average wind speed series with three kinds of observation intervals of every 1 hour, every 6 hours and no interval. Combined with the improved independent storm method and the extreme value I-type distribution model, the extreme values of wind speed in given returned periods are obtained, and the relationship between them is analyzed. The results show that, the difference between the extreme wind speed corresponding to the continuous observation series and the extreme wind speed corresponding to the observation data series with the interval of one hour or six hours meets Rayleigh distribution. And the correction method is given by using the probability distribution characteristics of the wind speed difference. The modified data can give more accurate estimation results of extreme wind speed.