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.     

Fresh snow chemistry from high mountain regions in central himalayas

Investigations of atmospheric composition in the Himalayas has been limited in both temporal and spatial scales, mainly due to difficult logistics. Ideal sites for monitoring atmospheric composition and its evolution should be free from local pollution and representative of the remote troposphere (HUEBERT et al., 1980). As the Himalayas are far removed from highly industrialized regions they provide suitable locations to monitor the chemistry of the remote troposphere and to study the evolu…     

我国南方西南和中东部区域两次持续性低温雨雪过程与关键环流系统的关系研究

利用NCEP再分析资料和国家气象信息中心提供的753站逐日气温和降水资料,对比分析了我国南方西南和中东部区域两次持续10 d以上的低温雨雪过程,结果表明:(1)两次过程中欧亚大陆中高纬东亚大槽均加深,但环流形势有差异。西南过程呈现"北高南低"形势,关键脊区在贝加尔湖,而中东部区域过程"北高南低"和"西高东低"形势共存,关键脊区从乌拉尔山延伸至贝加尔湖。两次过程异常的环流与北大西洋向东传播的波列有关。(2)西南过程关键脊区提前过程3 d发展并东移至贝加尔湖,形成稳定形势;而中东部区域过程关键脊区提前过程一周发展,在开始日达最强。两次过程均伴随蒙古高压东移南压使地面降温,500 hPa关键脊区超前蒙古高压2 d变化。西南过程降温主要受到冷平流和绝热冷却影响,而中东部区域过程主要受到冷平流的影响。(3)西南过程水汽来自孟加拉湾,只受南支槽支配。中东部区域过程水汽来自孟加拉湾、南海和西太平洋,由南支槽和西太平副热带高压的共同影响。两次过程水汽正收支主要来自南边界。     

SNOW WETNESS ESTIMATES OF VEGETATED TERRAIN FROM SATELLITE PASSIVE MICROWAVE DATA

The Special Sensor Microwave/Imager (SSM/I) radiometer is a useful tool for monitoring snow wetness on a large scale because water content has a significant effect on the microwave emissions at the snowpack surface. To date, SSM/I snow wetness algorithms, based on statistical regression analysis, have been developed only for specific regions. Inadequate ground-based snow wetness measurements and the non-linearity between SSM/I brightness temperatures (T_Bs) and snow wetness over varied vegetation covered terrain has impeded the development of a general model. In this study, we used a previously developed linear relationship between snowpack surface wetness (% by volume) and concurrent air temperature (°C) to estimate the snow wetness at ground weather stations. The snow condition (snow free, dry, wet or refrozen snow) of each SSM/I pixel (a 37 × 29 km area at 37.0 GHz) was determined from ground-measured weather data and the T_B signature. SSM/I T_Bs of wet snow were then linked with the snow wetness estimates as an input/output relationship. A single-hidden-layer back-propagation (backprop) artificial neural network (ANN) was designed to learn the relationships. After training, the snow wetness values estimated by the ANN were compared with those derived by regression models. Results show that the ANN performed better than the existing regression models in estimating snow wetness from SSM/I data over terrain with different amounts of vegetation cover.     

Thickness distribution and extent of sea ice and snow in Prydz Bay and surrounding waters observed in 2012/2013 austral summer

Three ship-based observational campaigns were conducted to survey sea ice and snow in Prydz Bay and the surrounding waters(64.40°S–69.40°S, 76.11°E–81.29°E) from 28 November 2012 to 3 February 2013. In this paper, we present the sea ice extent and its variation, and the ice and snow thickness distributions and their variations with time in the observed zone. In the pack ice zone, the southern edge of the pack ice changed little, whereas the northern edge retreated significantly during the two earlier observation periods. Compared with the pack ice, the fast ice exhibited a significantly slower variation in extent with its northernmost edge retreating southwards by 6.7 km at a rate of 0.37 km?d-1. Generally, ice showed an increment in thickness with increasing latitude from the end of November to the middle of December. Ice and snow thickness followed an approximate normal distribution during the two earlier observations(79.7±28.9 cm, 79.1±19.1 cm for ice thickness, and 11.6±6.1 cm, 9.6±3.4 cm for snow thickness, respectively), and the distribution tended to be more concentrated in mid-December than in late November. The expected value of ice thickness decreased by 0.6 cm, whereas that of snow thickness decreased by 2 cm from 28 November to 18 December 2012. Ice thickness distribution showed no obvious regularity between 31 January and 3 February, 2013.     

欧亚大陆冬季雪深的时空演变特征及其影响因子分析

利用美国冰雪资料中心(National Snow and Ice Data Center)提供的前苏联1948~1994年逐日积雪深度资料,定义了冬季雪深增量的概念,探讨了欧亚大陆秋末雪深、冬季雪深、冬季雪深增量的时空演变规律,通过比较分析三者的异常变化特征,揭示了三者之间可能存在的联系。经验正交函数分解(EOF)结果表明:欧亚大陆冬季雪深、冬季雪深增量的第一模态的空间分布特征均为大致以50°N为界的南北反相变化,欧亚大陆北部的积雪深度和冬季雪深增量都呈现出一致性的变化趋势;两者对应的时间序列均反映了显著的年代际变化特征,且年代际转变均发生在20世纪70年代中期前后。第二模态则呈现出欧亚大陆东、西部反相的偶极型空间分布特征。进一步分析表明,欧亚大陆秋末雪深无论从空间分布还是时间演变来看与冬季雪深几乎不存在相关性。欧亚大陆冬季雪深变化主要是冬季雪深增量影响所致,与秋末雪深无关。     

中国风吹雪区划

分析了我国风吹雪及其变化趋势,指出风吹雪和雪崩不能放在一起区划的原因,提出了风吹雪区划的理论,原则,要求和区划单位系统,指标及方法,据此,把中国风吹雪区划分为２个区域,３个大区,１３个地带,３９个地区和１３１个区,使其更加显示出专门区划的特色。     

近50年云南区域气候变化特征分析

利用云南气温和降水资料, 分析了云南气候变化特征及强降水极端天气和高温干旱事件对全球气候变暖的响应。以云南香格里拉、西双版纳、昆明地区为代表, 分析了区域气象要素变化趋势。结果表明: 云南近50 年气温变化与全球、北半球、中国变化趋势基本一致, 气温变化幅度略大于全球, 弱于北半球和全国变化。云南20 世纪80 年代中后期以后出现增暖现象, 以90 年代后期增温最明显, 1986 年以来出现13 年暖冬, 大部分地区冬春季降霜日数减少。随气候变暖, 香格里拉地区降雪日数呈下降趋势, 西双版纳地区雾日明显减少, 全省降雨日数逐渐减少, 大雨频率变化不大, 暴雨、大暴雨频率上升, 高温干旱事件频率增加。进入21 世纪以后, 云南降水减少, 高温干旱事件有增强增多趋势, 由2～3 年一遇变为1～2 年一遇。2005 年春夏连旱和2006 年春旱是云南近50 年和20 年来最严重的旱灾。     

中国天山西部山区森林积雪消融过程观测分析——以巩乃斯河谷为例

通过对2013年春季中国科学院天山积雪与雪崩研究站区内阳坡无林地和阴坡不同开阔度森林内积雪深度、融雪速率以及常规气象的观测,分析了融雪期不同开阔度森林积雪的消融过程以及积雪表面能量平衡特征。结果表明:不同开阔度林冠下积雪深度具有相同的变化趋势,森林的林冠开阔度越大,林下积雪深度越大,林下积雪开始消融和完全消融的时间越晚,消融期也越长。森林积雪融雪开始和结束时间比阳坡无林地区晚20~30 d左右。融雪前期林冠开阔度越大,其林下融雪速率越小。融雪后期则森林开阔度越大,森林积雪的融雪速率越大。不同时期由于不同开阔度林冠下雪面能量收支以及雪层深度等物理特性的差异,从而使不同开阔度林冠下森林积雪融雪速率的相对大小,融雪速率最大值出现时间和日变化特征均不相同。晴天森林积雪的消融速率和日变化特征取决于净短波辐射和长波辐射变化特征。降水期间,其融雪速率的变化则主要受降水形式、降水量以及积雪深度等雪层特性的影响。     

A rain on snow climatology and temporal analysis for the eastern United States

ABSTRACT

Rain-on-snow (ROS) has the potential to produce devastating floods by enhancing runoff from snowmelt. Although a common phenomenon across the eastern United States, little research has focused on ROS in this region. This study used a gridded observational snow dataset from 1960–2009 to establish a comprehensive seasonal climatology of ROS for this region. Additionally, different rain and snow thresholds were compared while considering temporal trends in ROS occurrence at four grid cells representing individual locations. Results show most ROS events occur in MAM (March-April-May). ROS events identified with rainfall >1 cm are more frequent near the east coast and events identified with >1 cm snow loss are more common in higher latitudes and/or elevations. Decreasing trends in DJF (December-January-February) ROS events were identified near the coastal areas, with increasing trends in the northern portion of the domain. Significant decreasing trends in MAM ROS are likewise present on a regional scale. Factors playing a role in snowpack depth and rainfall, such as movement of storm tracks in this region, should be considered with future work to discern mechanisms causing the changes in ROS frequency.