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。     

青海南部冬季积雪和雪灾变化的特征及其预评估

利用1961-2003年青海南部牧区气象台站观测的气温、降水、积雪资料,用气候诊断方法分析了该地区积雪等气候要素的年代际演变特征以及雪灾变化的成因。结果表明:20世纪60-90年代冬季,青南牧区中雪和大雪出现的站次以及雪灾出现的站次有逐步增多的趋势,降雪量和地表平均积雪量每10 a分别增加1.454 mm、9.861cm,单站积雪量在4 100 m左右的高度上增加比较明显,冬季降雪和积雪增加的趋势和新疆完全一致。典型多(少)雪年500 hPa高度距平场高原西部与中国东部地区为“- ”(“ -”)型。未来10 a冬季积雪增多的趋势仍将维持,雪灾发生的几率仍然偏大。     

Estimating Climate-Change Impacts on Colorado Plateau Snowpack Using Downscaling Methods

This study develops observed climate-based downscaling transfer functions that are used with general circulation model (GCM) output to assess potential global-change impacts on Upper Colorado Plateau, USA, water resources. Daily automated snow water equivalent stations are used with 700 mb atmospheric circulation to determine empirical transfer functions. Downscaling methodologies using multiple regression and neural networks are evaluated, with the neural network results explaining approximately 70%of the daily snowfall variance. The neural network-based transfer functions are used with the GENESIS GCM to simulate snowfall characteristics in both a 1xCO₂ and a 2xCO₂ climate. While the total precipitation simulated by the 2xCO₂ analysis remains nearly the same as today, less will fall as snow; specifically, snow water equivalence shows significant reduction (except in the Green River Basin) as the snow season is reduced by 58 days on average.     

MAJOR SNOWFALL EVENTS IN THE GREAT PLAINS: TEMPORAL ASPECTS AND RELATIVE IMPORTANCE

The purpose of this research is to develop a better understanding of the spatial and temporal aspects of central Great Plains snowstorms by: (1) identifying trends in the frequency of snow events, (2) determining the relative importance of significant snowfalls (those producing snowfall amounts of 10 cm or more), and (3) identifying temporal and/or latitudinal variations in the frequency of significant snowstorms. Using NCDC data from cooperative program weather stations along a north-south transect, summary statistics, correlation coefficients, and frequency histograms were generated. The results provided evidence of a highly variable spatial and temporal record. Significant snowstorms are more critical to total snowfall amounts in Nebraska, Kansas, and Texas. Although strong, regionally coherent temporal trends were not detected, a predominance of January through March snow events was observed. The greater frequency of January snowstorms coincides with the mean position of the polar front, while February and March snowfall frequency reflects the increased incidence of Colorado cyclones. Decadally, snowfall variability corresponds with a change in mean temperatures and predominant upper atmospheric flow that occurred around 1950. This change brought less snow to the Southern and Central Plains states, but more snow to the north. [Key words: snowfall, Great Plains, temporal/spatial variability.]     

Estimating Climate-Change Impacts on Colorado Plateau Snowpack Using Downscaling Methods

This study develops observed climate-based downscaling transfer functions that are used with general circulation model (GCM) output to assess potential global-change impacts on Upper Colorado Plateau, USA, water resources. Daily automated snow water equivalent stations are used with 700 mb atmospheric circulation to determine empirical transfer functions. Downscaling methodologies using multiple regression and neural networks are evaluated, with the neural network results explaining approximately 70%of the daily snowfall variance. The neural network-based transfer functions are used with the GENESIS GCM to simulate snowfall characteristics in both a 1xCO₂ and a 2xCO₂ climate. While the total precipitation simulated by the 2xCO₂ analysis remains nearly the same as today, less will fall as snow; specifically, snow water equivalence shows significant reduction (except in the Green River Basin) as the snow season is reduced by 58 days on average.     

A georeferenced agent-based model to analyze the climate change impacts on ski tourism at a regional scale

One main argument for modeling socio-ecological systems is to advance the understanding of dynamic correlations between various human and environmental factors, including impacts and responses to environmental change. We explore the shift in skier distribution among ski resorts taking into account the behavioral adaptation of individuals due to the impact of climate change on snow conditions. This analysis is performed at a regional scale by means of a coupled gravity and georeferenced agent-based model. Four different scenarios are considered. Two scenarios assume an increase of winter mean temperature of +2°C and +4°C, respectively, taking into account only natural snow conditions. Two additional scenarios add the effect of snowmaking to enhance the natural snow depth and extend the skiing season in the +2°C and +4°C base scenarios. Results show differing vulnerability levels, allowing the classification of ski resorts into three distinct groups: (1) highly vulnerable ski resorts with a strong reduction in visitors attendance for all climate change scenarios, characterized by unfavorable geographical and attractiveness conditions, making it difficult to ensure snow availability in the future; (2) low vulnerability ski resorts, with moderate reduction in season length during a high climate change scenario but no reduction (or even an increase) in a low one, characterized by ski resorts with a medium capacity and attractiveness to ensure enough snow conditions and capture skiers from other ski resorts; and (3) resilient ski resorts, with good conditions to ensure future snow-reliable seasons and outstanding attractiveness, allowing them to offer longer ski seasons than their competitors and potentially attracting skiers from other closed or marginal resorts. Ski resorts included in this last group increase their skier attendance in all climate change scenarios. Although similar studies in the literature foretell a significant reduction of the ski market in the near future, another probable effect outlined in this study is a redefinition of this market due to a redistribution of skiers, from vulnerable ski resorts to more resilient ones.     

祁连山区季节性积雪资源的气候分析*

本文采用1986年10月至1988年9月NOAA—9、10两颗卫星的AVHRR资料标准化后反演的积雪参量,对照祈连山区26个气象站1951—1988年逐日雪深、雪密度和积雪日数的资科,修正卫星反演的平均值。得到高分辨率多年平均雪深和雪盖频率的空间分布。从而估算出各流域平均雪储量,并与降雪量和春季融雪径流作对此分析。     

IS THE EXTREME SNOW DEPTH RECORD FOR NORDLAND,NORWAY RELIABLE?

A snow depth of 370 cm at Dunderlandsdalen in winter 1919–20 is the largest recorded at stations in Nordland, Norway. During the period 1895–1924, the average maximum annual value there was 150.4 cm; at other stations it ranged from 38.5 to 190.1 cm. The ratio of maxima at other stations to that at Dunderlandsdalen was particularly low in 1919–20. In Nordland generally, that winter's recorded precipitation was slightly above the 30‐year average, but at Dunderlandsdalen it exceeded the average by 34%. At all stations except Dunderlandsdalen, 26 Jan.–1 Feb. was a dry period; at Dunderlandsdalen, 51.7 mm was recorded. Only one day without snowfall was recorded at Dunderlandsdalen between early January and early February, but elsewhere there were few days with snowfall. The difference in snowfall frequency and snow depth at Dunderlandsdalen in 1919–20 from values recorded elsewhere in Nordland contrasts with the relationships in other winters between 1895 and 1924. No observations were made at Dunderlandsdalen in winter 1917–18. Two of the householders there died in 1916. A change of personnel making the observations may have been responsible for the data gap and for the anomalous 1919 data. Changes made to buildings or the recording site in 1917 or 1918 may have resulted in increased snow depths as a result of drifting. Maintaining a record of climatic extremes and their environmental consequences is important. Data must be accurate. In view of this, it would be sensible to regard the validity of the 370 cm Dunderlandsdalen maximum as doubtful.     

1956～2004年长江源区河川径流量的变化特征

利用1956~2004年长江源区水文和气象台站观测的流量、气温、降水资料,用气候诊断方法分析了该地区径流量的季节和年代际变化特征以及突变特点。结果表明:近50 a来长江源区月平均最大、最小和雨季、年及年较差流量均呈减小的趋势,月平均最小和最大流量分别出现在2月和7~8月,20世纪60和80年代的单峰峰值出现在7月,1970年代、1990年代的单峰峰值出现在8月,近14 a直门达水文站年径流共减少了96×108m3。雨季平均流量的距平基本经历了一个"正-负-正-负"的历史变化过程,雨季和过渡季节降水量、季节积雪融水量和高山冰雪融水量所形成的总流量呈下降趋势。枯季和雨季平均流量均经历了3次明显的转折,并具有10~12 a、6~8 a和3 a的共同变化周期。     

近50年青藏高原东部冬季积雪的时空变化特征

选取青藏高原东部地区1961-2010 年64 个测站的积雪数据,分析了冬季积雪日数的空间分布和年代际变化特征,结果表明：高原东部冬季积雪空间分布差异较大,巴颜喀拉山、唐古拉山和念青唐古拉山多雪且变率大,藏南谷地、川西干暖河谷地带及柴达木盆地少雪且变率小,这样的空间分布是由周边大气环流系统及复杂局地地形共同造成的;高原东部冬季积雪表现出“少—多—少”的年代际变化特征,分别在80 年代末和20 世纪末发生由少到多和由多到少的两次突变,尤其是20 世纪末的突变更为显著;降雪和气温的变化是影响积雪日数的重要因素,其中降雪的影响更为显著;80 年代末高原冬季降雪由少到多的突变是造成积雪日数发生相应变化的主要原因;20 世纪末高原冬季气温和降雪分别发生由低到高和由多到少突变,其影响叠加导致积雪日数发生了更为显著的突变。     

秦岭南北降雪异常空间模态识别及其影响因素分析

识别降雪异常空间模态,明晰降雪异常的影响因素,对理解中国南北过渡带气候变化规律具有重要的实践意义。论文基于1970—2020年逐日气象数据,辅以湿球温度动态阈值法、经验正交分解法等气候诊断方法,对秦岭南北冷季(11月—次年5月)降雪异常空间模态进行识别,探讨了不同主导模态与海气异常的相关关系。结果表明：(1)秦岭南北冷季降雪异常存在2个主导模态。第1模态为“全区一致型”,降雪异常偏强区分布于关中平原、秦岭山地、汉江谷地和大巴山区东段;第2模态为“山地主导下降型”,反映山地降雪异常对气候变化的敏感性;(2)在时间变化上,第1模态以年际波动为主,20世纪90年代中期后,空间模态多处于负相位,即全区一致降雪偏少;第2模态以年代转折为主,近期空间模态多处于正相位,即山地降雪异常偏少;(3)在影响因素上,第1模态降雪异常与1月中高纬度500 hPa欧亚遥相关波列相关,第2模态降雪异常与冬季赤道中东太平洋海温异常密切相关。研究将降雪异常格局与环流异常机制组合研究,可为理解中国南北过渡带降雪异常预警信号提供理论基础。     

Daily Air Temperature Variability Associated With Climatic Variability at Columbus,Ohio

Snow is an important component of the earth's environment, and can significantly impact the everyday life of those living in a large portion of the United States. However, accurate and complete information on snowfall and snow cover is presently being collected at only 57% of the official climate observing stations in states where regional snows occur on an annual basis. The quality of the data varies significantly from one state to another, although it tends to be weakest where snow is least common. As a result of this evaluation, the list of stations with daily snow data published in National Oceanic and Atmospheric Administration Climatohgical Data publications has been revised and expanded. [Key words: snow, snow observations, climate data, United States.]     

近35 年青藏高原雨量和雨日的变化特征

利用青藏高原1971-2005 年49 个气象台站逐日雨量和雨日资料, 分析了青藏高原年、 季雨量和雨日变化趋势。结果表明, 近35 年西藏大部分地区年雨量、雨日呈现显著增加趋 势, 而青海省大部分地区雨量、雨日却呈减少趋势。夏半年, 高原上雨日减少, 雨量增加, 说明降水越来越集中, 降水强度在增加。冬半年, 高原上雨日、雨量均在增加。高原夏半年小雨(0.1~4.9 mm) 雨日减少, 雨量增加; 小雨(5.0~9.9 mm) 和中雨的雨日和雨量均呈增加趋 势, 大雨以上的雨日和雨量均减少。冬半年, 青藏高原小雪、中雪、大雪不同量级日数和雪 日的平均雪量均呈增加趋势; 暴雪日和雪量变化均不明显。     

锡林郭勒积雪日数时空分布规律研究

利用1971-2015年锡林郭勒地区15个气象观测站近45 a的逐日积雪日数资料,采用滑动T检验、Mann-Kendall检验、小波分析和EOF方法对研究区的积雪日数时空变化特征进行分析。结果表明：研究期内积雪日数在1996年发生了一次由多到少的突变,且日数变化存在7 a的主周期和11 a、22 a的副周期。积雪月际变化呈单峰型的分布特征,多雪期主要集中在12~2月,少雪期分布在10月份和4月份;研究区空间分布差异性显著,总体呈东多西少、南多北少的分布格局,区内大部地区属于稳定积雪区。对积雪日数及其影响因子进行聚类分析,将研究区划分为4种类型,分别为降雪量偏少-积雪日数偏高区、降雪量-积雪日数一致偏高区、降雪量-积雪日数中值区、降雪量-积雪日数一致偏少区。该区有3种异常分布型：第一模态为全区一致偏多（少）型;第二模态为北多（少）南少（多）型;第三模态为中西部多（少）,东南部少（多）型。     

青海高原近40 a降水变化特征及其对生态环境的影响

 利用青海省1961-2002年26个代表站逐日雨量资料和高原东部地区10个站的降水自记资料,分析了近40 a来降水量、雨日、雨强的气候变化特征。结果表明:青海高原近40 a来年降水量无明显的变化,但夏半年降水量呈减少趋势,冬半年降水量呈明显的增多趋势；夏半年降水量和雨日虽在减少,但降水强度在增大；夏半年降水量的减少主要是降水日数的减少造成的,而冬半年降水量的增加是由于雨日增多和每个降水日平均雨量的增大所造成；随着气候变暖,夏、秋季降水明显偏少,出现暖干化的气候趋势。     

近60 a新疆塔城地区不同相态降水时空变化特征

基于1961—2020年9个国家气象观测站逐日资料,采用气候统计学方法分析了塔城地区不同相态降水的时空分布及变化规律,探讨了降水相态的变化成因及其可能影响。结果表明：(1)近60 a塔城地区年平均降水日数88.1 d,其中降雨日数最多,降雪日数次之,雨夹雪日数最少;3种相态降水在空间上呈现地区西北部多、中东部少的分布格局。(2)从不同相态降水日数的月际分布来看,降雨主要出现在4—9月,降雪在11月—翌年3月较多,3—4月和10—11月期间3种相态降水共存。(3)近60 a塔城地区各站不同相态降水的变化趋势存在一定的差异,总体呈现降雨日数增加而降雪日数减少的变化趋势,且降雨量的增速高于降雪量增速,其结果导致雪雨比率以-0.33%·(10a)^-1的速率减小。(4)气温增暖是塔城地区降水相态向多雨化转变的主要原因,同时北极涛动指数(Arctic oscillation index,AO)、北大西洋涛动指数(North Atlantic oscillation index,NAO)以及北半球极涡指数对降水相态的变化也有一定的影响。     

新疆北部小时降雪特征及大暴雪天气影响系统研究

新疆北部是我国降雪高频区之一,随着全球变暖降雪量呈显著增加趋势,对新疆气候产生重要影响,由于观测资料限制对该区域小时降雪研究还未开展,影响降雪精细化预报和服务能力提升。因此,利用新疆天山山区及其以北（以下称“新疆北部”）2012年11月—2021年2月50个国家气象站小时降雪观测资料,分析了冷季（11月—翌年2月）小时降雪特征,并按日降雪量从高到低挑选30个大暴雪过程分析其小时降雪特征、影响系统及典型环流配置。结果表明：（1） 阿勒泰北部、塔城盆地、伊犁河谷为降雪小时数（SHN）高频区,可达200 h·a^-1以上;天山山区SHN高频区为海拔1800~2000 m的中山带,达127.3 h·a^-1,2000 m以上降雪很少。（2） 北疆和天山山区小时降雪量（R）≤1.0 mm·h^-1量级SHN占比分别为91.7%和91.9%,对降雪量贡献分别为70.7%和68.9%,R>1.0 mm·h^-1为小时极端降雪事件,对北疆和天山山区降雪量贡献分别为29.3%和31.1%。（3） 极端暴雪过程平均SHN为25.5 h,平均降雪量为30.7 mm,雪强约为1.2 mm·h^-1,大暴雪过程由长时间降雪导致,降雪持续时间是开展大暴雪研究和进行预报服务的关键点,造成大暴雪过程的影响系统主要有中亚长波槽、中亚低涡、乌拉尔山长波槽和西西伯利亚低涡（槽）,占比分别为30.0%、6.7%、13.3%和50.0%,中纬度长波槽（涡）和北方西西伯利亚低涡（槽）系统各为50.0%。     

1970—2018年秦岭南北冷季降雪量时空变化及其影响因素

基于72个气象站点逐日观测数据,对1970/1971—2018/2019年秦岭南北冷季（11月~次年5月）降水类型（降雪、降雨和雨夹雪）进行识别;重点关注降雪时空变化特征,探讨降雪与气温、湿球温度的响应关系;依据“夏季-秋季-冬季”Niño 3.4区海温异常状态,细化4种不同发展过程的厄尔尼诺-南方涛动（ENSO）事件,分析降雪异常与不同ENSO事件的对应关系。结果表明：① 相比气候平均态（1970—2000年）,1990—2018年,秦岭南坡（山地暖温带）降雪量下降了3.1 mm,基本与关中平原降雪量（17.1 mm）持平;② 空间趋势上,低海拔河谷地带降雪量以年代波动为主,山地高海拔地区为降雪下降区;③ 秦岭高山地区气温或湿球温度每升高1.0℃,降雪量分别下降23.1 mm和24.3 mm;从地带性角度分析,由北向南气温或湿球温度每升高1.0℃,秦岭南北降雪量分别下降3.0 mm和2.8 mm;④ 当厄尔尼诺/拉尼娜持续型发生时,关中平原降雪异常偏多;当拉尼娜发展型发生时,秦岭山地和大巴山区降雪异常偏少。当厄尔尼诺发展型发生时,秦岭南北降雪异常呈现“东西分异”,秦岭山地东部和关中平原为降雪异常偏少区。     

近50年青藏高原东部降雪的时空演变

选用1967-2012年青藏高原东部60个站点的观测资料,分析了该地区降雪的时空演变特征,并结合降水和气温的变化,探讨了降雪与积雪的关系,结果表明：青藏高原东部年降雪量在1.3~152.5 mm范围内变化,空间分布差异显著;秋季降雪表现出中间多、周边少的特征,冬季降雪表现出由东南向西北递减的特征,春季降雪最多且空间分布与年降雪基本一致;降雪可划分为青南高原区、藏北高原区、柴达木盆地区、青藏高原东南缘区、川西高原西北部区、青藏高原南缘区、青海东北部区及藏南谷地区;就青藏高原整体而言,除秋季外,整年、冬季和春季降雪均表现出“少—多—少”的年代际变化特征,其中冬季降雪在1986年发生了由少到多的突变,整年、冬季和春季降雪均在1997年发生了由多到少的突变;不同区域降雪的时间变化规律各具特点;降雪与积雪的关系十分密切,春季降雪受气温的影响最为显著,秋季次之,冬季最弱;20世纪末,春季降雪受气温升高的影响表现出与降水变化相反的由多到少的气候突变特征。     

Distribution and trend on consecutive days of severe weathers in China during 1959–2014

Based on daily surface climate data and weather phenomenon data, the spatial and temporal distribution and trend on the number of consecutive days of severe weathers were analyzed in China during 1959–2014. The results indicate that the number of consecutive days for hot weathers increased at a rate of 0.1 day per decade in China as a whole, while that for cold weathers, snowfall weathers, thunderstorm weathers and foggy weathers showed significant decreasing trends at rates of 1.4, 0.3, 0.4 and 0.4 day per decade, respectively. Spatially, there were more consecutive hot days and rainstorm days in southeastern China, and more consecutive cold days and snowfall days in northeastern China and western China. Consecutive thunderstorm days were more in southern China and southwestern China, and consecutive foggy days were more in some mountain stations. Over the past 56 years, annual number of consecutive cold days decreased mainly in most parts of western China and eastern China. Consecutive thunderstorm days decreased in most parts of China. The trend of consecutive hot days, snowfall days and foggy days was not significant in most parts of China, and that of consecutive rainstorm days was not significant in almost the entire China.