1967—2016年黄河上游河曲地区降水变化特征研究

利用1967~2016年黄河上游河曲地区的5个气象站观测气象站的逐日地面降水和气温资料,利用气候变化趋势分析、距平、Mann-kendall 时间序列突变及趋势检验方法分析了该地区气温变化特征、不同类型各等级降水量及降水日数的气候特征。结果表明：(1)近50年黄河上游河曲地区年均气温以0.459℃/10a趋势显著上升,上升速度低于全国其它地区,且在2002年气温发生突变后升温加剧；(2)年降水量和降水日数呈减少趋势,主要是由夏季小雨量和小雨日数的减少引起；(3)在2002年气温突增后,强降水对总降水量贡献率增加,且年降水量和降水日数波动幅度也明显增大,这可能预示该地区洪涝灾害的风险在增加。降水日数的贡献率增加,增加明显的是中雨日数和小雨日数,分别增加了1.1%和1.7%。     

商丘暴雨日及分布特征研究

对商丘国家观象台1954--2005年月报表中挑取的符合暴雨日条件的142个样本分析，结果表明：商丘暴雨日具有明显的季节性，频发于7、8月份；暴雨日年平均2．73个；日暴雨量最大（193．3mm）不超过200mm；最长连续暴雨日数不超过2日；连续暴雨日降水量累计（223．9mm）不超过250mm；1h最大降水量不超过70mm。暴雨目的年代际变化特征明显，20世纪80年代后暴雨日出现较晚，60--90年代的暴雨日数递减，90年代后有增加趋势；大暴雨日数自60年代起有逐步增加趋势。暴雨日对月、年降水量有显著贡献，4—9月暴雨日对月降水量的贡献很大，且从4月到7月暴雨目的贡献呈递增趋势。一年内暴雨日出现5次时，当年的年雨量为偏多年份。     

热气候指数评价中国南方城市夏季舒适度

利用南方14个城市1981-2013年6-9月的逐日气象资料,根据生物环境特点,制定了基于通用热气候指数的新评价方法,对中国南方城市夏季舒适度进行评价研究。结果表明:中国南方城市的高温不舒适天数近33 a来以3.4 d/10a的速度增加,并有5 a震荡周期。舒适度排名显示,体感温度最高的4个城市分别为重庆、福州、南昌和长沙,杭州与重庆的体感舒适度下降速率较快。对比高温不舒适天数和高温日数发现,两者具有很好的一致性,证明了高温不舒适度与气温关系的密切性。同时,由于热气候指标计算要素的多重考虑,结果与高温日数存在一些差异,但其更具有一定参考和应用价值。     

Study on the extremely cold winter of 1670 over the middle and lower reaches of the Yangtze River

The snow-cover days over the middle and lower reaches of the Yangtze River （MLRYR） in the winter of 1670 were extracted from Chinese historical documents. By these records, the winter temperature anomalies （compared to the mean of 1961-1990） recorded at seven meteorological stations and the regional mean winter temperature were estimated. The results show that： （1） There was an average of about 30 snow-cover days over the MLRYR region in 1670, ranging from 11-20 days in Shanghai and eastern Zhejiang to 5140 days in eastern Hunan Province. The snow-cover days averaged about 40 days in Anqing and Nan- cheng, and ranged from 30 to 40 days in Quzhou, Jingdezhen, and Nanchang; and （2） the regional mean winter temperature in 1670 was estimated to be approximately 4.0 ℃ lower than that of 1961-1990. The maximum negative anomaly of 5.6℃ occurred in Nanchang and the minimum anomaly of-2.8 ℃ was detected in Quzhou. Both of these were lower than that of the coldest winter during the instrumental observation period of 1951-2010. This research could not only provide a method to es- timate historical climate extremes, but also provide a background to understand the recent instrumentally climate extremes.     

绵阳市度日数特征及其变化趋势分析

从20世纪50年代以来,度日数一直作为气候变化与供暖关系的一个综合评价指标。基于全球变暖可能对我国供暖天数和温度产生深刻的影响,本文采用绵阳市1946~2005年共49年的日最低、最高气温资料,分析了绵阳市度日数年变化特征,并对其进行了趋势分析。结果表明:绵阳市历年供暖度日数最小值处于1998年,比1976年最大值低93.5%,10a年均供暖度日数变化趋势为二次曲线;制冷度日数波动性很大,1960~1979年在1500℃·d左右波动,1979~1990年在1400℃·d左右波动,1990年以后基本处于1500℃·d以上,10a年均制冷度日数拟合趋势曲线为三次曲线。基于Mann-Kendall(M-K)检验法,在α=0.05水平下,对绵阳市供暖和制冷度日数进行检验,研究发现:供暖度日数明显减少,1992年为突变起始年份;制冷度日数波动增长,且自1997年起突变。     

雷电定位系统与人工观测雷暴日数统计比较

为了利用雷电定位系统 (lightning location system,LLS) 资料统计人工观测雷暴日数,采用湖北省2007—2012年LLS监测资料,选取25个气象站为圆心,统计其不同监测半径 (r) 圆区域内LLS监测的雷电日数,并与人工观测雷暴日数进行比较。结果表明:r≤7 km时,LLS监测平均年雷电日数小于人工观测平均年雷暴日数;r≥8 km时, LLS监测平均年雷电日数大于人工观测平均年雷暴日数;r=22 km圆区域内年平均雷电日数可替代最大年雷暴日数。根据r=7 km,r=8 km圆区域内LLS监测的年雷电日数、年平均地闪密度资料,分别采用直接替代法、地闪密度法和该文提出的二元法计算年雷暴日数,结果显示:二元法效果最好。二元法计算的2007—2012年25个站平均年雷暴日数与人工观测相等,平均差异为7.4%;二元法计算的2013年年雷暴日数与人工观测相差0.8 d,平均差异为12.3%。     

哈尔滨雾霾天气候特征

利用哈尔滨地面气象观测数据,对1961-2010年哈尔滨雾霾天气候特征进行分析,得出:1961-2010年,哈尔滨的雾霾天经历了一个减少-增多-减少的过程;哈尔滨市雾霾天气出现较频繁,有四到五成的日子会有雾霾天气出现,雾霾天以烟幕和轻雾天为主;雾霾天冬季出现最多,其次秋季,春、夏季较少;雾生多在凌晨3-6时,消多在清晨5-9时;持续时间多4 h(占有记录的雾持续时间81%)。     

中国降雪气候学特征

利用逐日地面降雪观测资料,分析中国25oN以北范围内降雪量、降雪日数、雪带分布和各强度降雪的气候学特征,得到以下结论:①雪季长度与年降雪日数在东部呈纬向分布,大兴安岭北部最长(>210 d),长江以南最短(常年无雪或偶尔降雪);在西部青海省南部和西藏自治区北部最长(>300 d),滇、川、藏交界处及新疆自治区北部较长,南疆较短(<60 d)。年降雪量东南部最少,东北和西北北部较多(>30 mm),青海和西藏降雪量最多(>60 mm)。平均降雪强度江淮一带最大。②根据雪季降雪频次划分中国的雪带,东北大部、内蒙自治区东部、新疆北部、青藏高原大部、秦岭等地区为常年多雪带;长江以南的滇南、四川盆地、江浙沿海等地区为永久无雪带;其余地区为常年降雪带和偶尔降雪带。③不同区域各级降雪日数占总降雪日数的比例都是暴雪日数最少,大雪日数其次,小雪日数最多;但中雪降雪量占总降雪量的比例在东北北部、华北、西北、新疆、东南、青藏高原东部等区域仅高于小雪降雪量,而在黄-淮地区仅次于暴雪降雪量。④降雪年内分配在东北北部、西北、新疆、青藏高原东部等地区都呈双峰型,最多雪时节在早冬和晚冬、早春,隆冬时节并不是降雪最多时间,黄-淮和东南地区呈单峰型,东南地区峰值更陡。⑤总降雪日数和除暴雪外的各等级降雪日数与地理位置关系较明显,在中国东部主要随着纬度升高增加,在中国西部随海拔高度增加而增加;随着纬度升高,东部和西部的总降雪强度都减小,西部的小雪强度也减小。     

Changing Trends of Daily Temperature Extremes with Different Intensities in China

By comparing two sets of quality-controlled daily temperature observation data with and without the inhomogeneity test and adjustment from 654 stations in China during 1956-2004 and 1956-2010, impacts of inhomogeneity on changing trends of four percentile temperature extreme indices, including occurrences of cold days, cold nights, warm days, and warm nights with varying intensities, were discussed. It is found that the inhomogeneity affected the long-term trends averaged over extensive regions limitedly. In order to minimize the inhomogeneity impact, the 83 stations identified with obvious inhomogeneity impacts were removed, and an updated analysis of changing trends of the four temperature extreme indices with varying intensities during 1956-2010 was conducted. The results show that annual occurrences of both cold nights and cold days decreased greatly while those of warm nights and warm days increased significantly during the recent 20 years. The more extreme the event is, the greater the magnitude of changing trends for the temperature extreme index is. An obvious increasing trend was observed in annual occurrences of cold days and cold nights in the recent four years. The magnitude of changing trends of warm extreme indices was greater than that of cold extreme indices, and it was greater in northern China than in southern China. Trends for summer occurrence of cold days were not significant. Decreasing trends of occurrences of both cold nights and cold days were the greatest in December, January, and February (DJF) but the least in June, July, and August (JJA), while increasing trends of warm nights were the greatest in JJA. Cold nights significantly decreased from 1956 to 1990, and then the decreasing trend considerably weakened. The decreasing trend also showed an obvious slowdown in recent years for occurrence of cold days. However, increasing trends of warm nights and warm days both have been accelerated continuously since the recent decades. Further analysis presents that the evolution of the trends for occurrences of the four temperature extreme indices was dominated by the changes in northern China.