摘要
ENSO(ElNiño-SouthernOscillation)循环被认为是年际气候变化的最强信号,是由东亚季风异常造成的赤道西太平洋异常纬向风驱动的热带太平洋次表海温距平的循环。利用NOAA提供的ONI(OceanicNiñoIndex)指数资料与福建省近地层质量臭氧浓度(ρ(O_(3)))资料,经数理统计、标准化处理,以滞后相关为切入点,开展福建省不同城市O_(3)Z指数与NiñoZ海温距平指数相关性分析,并探讨了ENSO不同相位对福建省ρ(O_(3))产生强迫的程度及其滞后效应。(1)福建省ρ(O_(3))的年际变化与ENSO的年际变化存在着一定的关系,城市O_(3)Z指数与NiñoZ海温距平指数呈现明显的负相关关系,且滞后在3个月时二者相关(绝对值)达到最大,加权平均后,相关系数为-0.5102,通过ɑ=0.001显著性检验。(2)不同城市O_(3)Z指数与NiñoZ海温距平指数的相关性有一定的差异,内陆城市比沿海城市明显偏小,且滞后性也不同,前者均在滞后1个月后相关系数(绝对值)达到最大值,平均相关系数-0.4048(ɑ=0.01),后者在滞后3个月时相关系数(绝对值)达到最大值,平均相关系数-0.5487(ɑ=0.001)。(3)ENSO循环对福建省ρ(O_(3))变化的影响主要表现为在ElNiño影响时ρ(O_(3))较常年平均值偏低,在LaNiña影响时ρ(O_(3))较常年平均值偏高,且O_(3)年超标天数偏多。研究的主要目的是基于ENSO预测,为开展福建省ρ(O_(3))长期趋势预测奠定基础。
The El Niño and La Niña(ENSO)cycle is the strongest signal of inter-annual climate change.It is a cycle of subsurface sea temperature anomalies in the tropical Pacific driven by abnormal zonal winds in the equatorial western Pacific caused by the anomalous East Asian monsoon.Based on the Oceanic Niño Index(ONI)data provided by NOAA and the near-surface mass ozone concentration(ρ(O_(3)))data of Fujian Province,the present study uses mathematical statistics and standardized processing methods with lag correlation as the starting point to study the correlation between the O_(3)Z index and the Niño Z sea temperature anomaly index in different cities.The forcing and lag effect of ENSO phases onρ(O_(3))in Fujian are also discussed.The results show that:(1)There is a relationship between the inter-annual variability ofρ(O_(3))and that of ENSO in Fujian where the O_(3)Z index and Niño Z sea temperature anomaly index show a significant negative correlation.The correlation(absolute value)between the two reaches the maximum after a lag of 3 months,and the weighted average correlation coefficient is-0.5102,passing theɑ=0.001 confidence level test.(2)The correlation between the O_(3)Z index and the Niño Z sea temperature anomaly index of different cities has certain differences.Those of the inland cities are significantly smaller than those of the coastal cities,and the lag is also different.The former has a maximum correlation coefficient(absolute value)after a lag of 1 month and the average correlation coefficient is-0.4048(ɑ=0.01),whereas the latter has a maximum correlation coefficient(absolute value)after a lag of 3 months and the average correlation coefficient is-0.5487(ɑ=0.001).(3)The impact of the ENSO cycle on the change ofρ(O_(3))in Fujian Province is mainly manifested in several aspects.ρ(O_(3))becomes lower than the normal annual average under the influence of El Niño,and it becomes higher than the normal annual average under the influence of La Niña.The number of days when O_(3)exceeds the normal level in a year is higher than the normal annual average.The main purpose of this study is to lay the basis for the medium-and long-term trend prediction ofρ(O_(3))in Fujian Province based on ENSO prediction.
作者
王宏
郑秋萍
温珍治
黄艳艳
WANG Hong;ZHENG Qiu-ping;WEN Zhen-zhi;HUANG Yan-yan(Fujian Key Laboratory of Severe Weather,Fuzhou 350001,China;Fujian Institute of Meteorological Science,Fuzhou 350001,China;Laboratory of Straits Meteorology,Xiamen,Fujian 361012,China;Fujian Climate Center,Fuzhou 350001,China;Fujian Environmental Monitoring Central Station,Fuzhou 350003,China)
出处
《热带气象学报》
CSCD
北大核心
2021年第2期145-153,共9页
Journal of Tropical Meteorology
基金
国家自然科学基金(U1405235)
华东区域气象科技协同创新基金(QYHZ201813)
福建省气象局开放式研究基金(2019KX04)
福建省生态环境厅环保科技项目(2021R023)共同资助。