福建省冬季暴雨过程及其环流特征

利用福建省66个气象观测站1960年12月至2008年2月的暴雨资料,分析了福建冬季暴雨的时空特征及主要影响天气系统。结果表明,冬季暴雨主要发生在闽西;福建冬季暴雨主要是南支槽东移、切变线维持和冷空气南下影响所致;冬季暴雨的产生与充沛的水汽、对流不稳定和辐合上升运动密切相关,但大气层结比汛期暴雨要稳定得多;冬季暴雨异常与500 hPa大气环流和赤道中东太平洋海温异常关系密切,它们可能主要通过大气环流的改变引起福建冬季暴雨异常。     

厄尔尼诺事件和拉尼娜事件的成因与预测

通过对南极气温资料、环南极海冰资料、臭氧变化资料、太平洋海温资料、地球自转速度变化资料、厄尔尼诺和拉尼娜资料的综合验证,发现了构造运动与厄尔尼诺因果关系。大气、海洋与岩石圈的角动量交换在南半球和北半球有不同的形式,这是由陆海分布的差异决定的。南极上空臭氧变化和环南极海冰变化是赤道海温和全球气候准两年振荡的原因。其中,德雷克海峡的海冰变化起主要作用。这个结论给出了作者提出的“海洋锅炉效应”、“臭氧洞漏能效应”、“德雷克海冰气候开关效应”和“大洋地壳跷跷板运动”的相互关系,证明构造运动对厄尔尼诺的重要影响。强潮汐准4a周期的发现,表明南极海冰变化、东太平洋海温变化、地球自转变化和厄尔尼诺都具有4a准周期变化的原因。海温和海冰开关的准2a周期和日食-厄尔尼诺系数理论有较好的预测效果。     

高低层纬向风切变的年际变率及气候学意义

用1959～1998共40年全球格点风场资料计算了200 hPa与850 hPa的纬向风速差, 即对流层纬向风切变(简称TZWS),并在此基础上得到其距平值。为了全面考察对流层中环流异常的年际变率特征, 根据TZWS的标准差分布, 文中选出了7个TZWS标准差数值大于5 m/s的代表性区域。这7个区域分别位于赤道中太平洋、赤道东太平洋、北太平洋亚热带地区、南太平洋亚热带地区、赤道大西洋、亚洲西南部以及东北部。前5个分别位于赤道、亚热带太平洋和大西洋的区域TZWS指数, 其年际变率与ENSO循环有密切联系, 反映了热带海洋温度异常对低纬度地区对流层环流的影响; 后2个区域的TZWS指数反映的是亚洲西南部和东北部的气候统变率, 在年际时间尺度上与ENSO循环有着明显的区别。通过对全球陆地降水和温度场的分析, 比较了热带、副热带的TZWS指数以及北极涛动指数的异同, 发现后2个区域TZWS指数能很好且能独立反映出北半球中高纬度地区陆地降水及陆地温度的异常模态。     

初论雪峰山地区基性-超基性岩镍钴铜金矿找矿方向

近年来,雪峰山地区的基性-超基性岩矿床找矿工作取得了一定的进展。为了及时总结成矿规律,指导进一步的找矿工作,本文在大量野外调研的基础上,系统总结了该地区基性-超基性岩岩体的地质特征、已有找矿进展的长界镍矿和字溪金矿地质特征及已发现的镍钴铜金等矿化特征,并与国内外同类型矿床的成矿特征进行了比较,最后提出了如下认识:雪峰山地区具备找寻基性-超基性岩矿床潜力,目标矿种主要为镍、钴、铜及金矿,主要矿床类型为岩浆硫化物型镍钴铜矿及蚀变热液型金矿。前者目标地质体以通道-洪江-中方-古丈一带新元古代基性-超基性岩群/带最为有利,后者则以隘口岩群及艾头坪-大洪山岩群的大洪山段最为有利。     

对ENSO循环机理的一些新认识

近几年国内学者通过资料诊断、理论分析和数值试验,对ENSO循环的机理提出了一些新的看法,其中包括El Nino和La Nina的起源,与ENSO循环相联系的暖、冷水的传播过程,热带西太平洋纬向风应力异常,以及热带东太平洋经向风应力异常在ENSO循环中的动力作用等.作者介绍了我国在这些方面的一些研究成果.     

2000—2019年秦岭南北实际蒸散发时空变化特征

基于遥感数据全面认识复杂地形单元实际蒸散发时空规律,对区域可持续水资源管理具有重要的意义。论文基于MODIS实际蒸散发(ET)数据,对2000—2019年秦岭南北ET时空变化特征进行分析,探究不同分区ET对植被变化的响应关系,进而识别ET趋势和年代变化的高相关海气环流因素。结果表明：① 在变化趋势上,以1000 m等高线为界,即秦岭地区北亚热带和山地暖温带的分界线,低海拔河谷地带为ET显著增加区,山地高海拔地区为ET下降区;② 除城市、乡镇周边地区,研究期间秦岭南北下垫面相对稳定,转为生态用地的活跃区主要分布在山地1000 m过渡带,其是ET与NDVI变化显著相关区,而1000 m以上高海拔地区两者相关性较低;③ ENSO、青藏高原北部气压异常,与秦岭山地、汉江谷地ET的趋势变化和年代波动显著相关,而西太平洋副热带高压与ET的趋势显著相关,与年代波动特征相关较弱。即发生中部型厄尔尼诺事件时,西太平洋副热带高压偏强,对流层低层形成异常反气旋,导致中国东部雨带北移,秦岭山地和汉江谷地降水偏少,气温偏高,ET往往偏大。研究结果启示：秦岭南北科学适应气候变化时,应关注秦岭山地、汉江谷地ET变化显著相关的环流信号;应深刻理解秦岭高海拔地区蒸散发下降趋势对区域水资源管理的影响。     

Contrasting Regional Responses of Indian Summer Monsoon Rainfall to Exhausted Spring and Concurrently Emerging Summer El Ni?o Events

The inverse relationship between the warm phase of the El Ni?o Southern Oscillation(ENSO) and the Indian Summer Monsoon Rainfall(ISMR) is well established. Yet, some El Ni?o events that occur in the early months of the year(boreal spring) transform into a neutral phase before the start of summer, whereas others begin in the boreal summer and persist in a positive phase throughout the summer monsoon season. This study investigates the distinct influences of an exhausted spring El Ni?o(springtime)...     

中国东北地区冬季气温趋势及反相模态分析

利用1951—2010年我国东北地区共97个台站的逐月气温资料,应用trend-EOF和EOF分析方法研究了我国东北地区冬季气温的趋势模态和反相模态及其影响因子。trend-EOF的结果表明,东北地区均为一致型的趋势变化,trend-PC1有明显的年代际周期变化和更长期的上升趋势变化特征。去除全球变暖信号后的EOF分析结果表明:第一模态仍为全区一致型的空间分布,而第二模态的空间分布呈现南北反相型的分布特征,是东北冬季气温变化模态中极为重要的一部分,对应的时间序列有明显的年际周期变化,前两个模态可以解释总方差80%以上的变化。东北地区全区一致的上升趋势是在全球变暖大背景下发生的,既是对全球变暖的局地响应,同时全球变暖也使大气环流发生了变化,西伯利亚高压减弱,纬向环流增强,导致了东北地区冬季气温全区的上升趋势。赤道东太平洋的异常海温对第二模态的出现具有一定的预示意义,当太平洋出现典型的厄尔尼诺年海温距平场分布特征时,东北南部较常年偏暖,北部地区却较常年偏冷。     

CMIP5模式中El Ni?o-EAWM关系的模拟对东亚冬季风模拟的影响

本文利用统计学的方法,评估了17个参加第五次国际耦合模式比较计划(CMIP5)的海气耦合模式对东亚冬季风(EAWM)年际变化的模拟。结果表明:多数模式对东亚冬季风的年际变化有一定的模拟能力,其中对东亚大槽年际变化的模拟最好;模式对东亚冬季主要系统的年际变化在空间上的模拟好于强度,对强度的模拟以偏弱为主;通过综合评估得到模拟能力好的模式有:bcc-csm1-1,CCSM4,HadCM3,NorESM1-M。针对模式间对冬季风年际变化模拟能力差别较大的现象,选取了4个模拟能力最好的模式和5个最差的进行讨论;通过评估El Ni?o对东亚冬季环流的影响,发现模式对El Ni?o与EAWM之间相互关系(El Ni?o-EAWM)的模拟能力是模式间对冬季风年际变化模拟偏差较大的原因之一,即对El Ni?o-EAWM模拟好的模式对东亚冬季风年际变化的模拟也好。     

Fire activity in Borneo driven by industrial land conversion and drought during El Niño periods, 1982–2010

Tropical rainforests, naturally resistant to fire when intact, are increasingly vulnerable to burning due to ongoing forest perturbation and, possibly, climatic changes. Industrial-scale forest degradation and conversion are increasing fire occurrence, and interactions with climate anomalies such as El Niño induced droughts can magnify the extent and severity of fire activity. The influences of these factors on fire frequency in tropical forests has not been widely studied at large spatio-temporal scales at which feedbacks between fire reoccurrence and forest degradation may develop. Linkages between fire activity, industrial land use, and El Niño rainfall deficits are acute in Borneo, where the greatest tropical fire events in recorded history have apparently occurred in recent decades. Here we investigate how fire frequency in Borneo has been influenced by industrial-scale agricultural development and logging during El Niño periods by integrating long-term satellite observations between 1982 and 2010 – a period encompassing the onset, development, and consolidation of its Borneo’s industrial forestry and agricultural operations as well as the full diversity of El Niño events. We record changes in fire frequency over this period by deriving the longest and most comprehensive spatio-temporal record of fire activity across Borneo using AVHRR Global Area Coverage (GAC) satellite data. Monthly fire frequency was derived from these data and modelled at 0.04° resolution via a random-forest model, which explained 56% of the monthly variation as a function of oil palm and timber plantation extent and proximity, logging intensity and proximity, human settlement, climate, forest and peatland condition, and time, observed using Landsat and similar satellite data. Oil-palm extent increased fire frequency until covering 20% of a grid cell, signalling the significant influence of early stages of plantation establishment. Heighted fire frequency was particularly acute within 10 km of oil palm, where both expanding plantation and smallholder agriculture are believed to be contributing factors. Fire frequency increased abruptly and dramatically when rainfall fell below 200 mm month⁻¹, especially as landscape perturbation increased (indicated by vegetation index data). Logging intensity had a negligible influence on fire frequency, including on peatlands, suggesting a more complex response of logged forest to burning than appreciated. Over time, the epicentres of high-frequency fires expanded from East Kalimantan (1980’s) to Central and West Kalimantan (1990’s), coincidentally but apparently slightly preceding oil-palm expansion, and high-frequency fires then waned in East Kalimantan and occurred only in Central and West Kalimantan (2000’s). After accounting for land-cover changes and climate, our model under-estimates observed fire frequency during ca. 1990–2002 and over-estimates it thereafter, suggesting that a multi-decadal shift to industrial forest conversion and forest landscapes may have diminished the propensity for high-frequency fires in much of this globally significant tropical region since ca. 2000.