北京地区不同类型降水对气溶胶粒子的影响

利用2013~2015年大气成分与气象观测资料,分析了北京地区不同类型降水对气溶胶粒子的影响,结果表明：随着降水强度增大,PM₁₀、PM_2.5、PM₁浓度下降的时次比例、浓度下降比例均增大,PM₁₀下降幅度大于PM_2.5和PM₁;不同类型降水对气溶胶浓度影响不同,对流性降水中大气运动剧烈,对3种颗粒物都有快速而显著的清除效果;稳定性降水细分为3类,显著冷空气型的冷空气垂直下沉运动和降水湿清除可使粒子浓度缓慢下降,无显著冷空气但有颗粒物传输型的降水过程对气溶胶粒子的湿沉降效果有限,无显著冷空气无传输型气溶胶粒子吸湿增长可能导致粒子浓度不会下降;降雪或雨夹雪过程中随着降雪强度增大,气溶胶粒子浓度下降比例增大,但下降时次比例呈指数或者对数变化.雨雪相态转换的降水过程更为复杂,除了上述因素之外,还需考虑雨雪相态转变带来的水滴（雪）粒径、降水粒子对周边气流的动力拖曳作用的变化、冷空气下沉运动对流型的改变.     

Observed Changes in Climate and Streamflow in the Upper Rio Grande Basin

Observed streamflow and climate data are used to test the hypothesis that climate change is already affecting Rio Grande streamflow volume derived from snowmelt runoff in ways consistent with model‐based projections of 21st‐Century streamflow. Annual and monthly changes in streamflow volume and surface climate variables on the Upper Rio Grande, near its headwaters in southern Colorado, are assessed for water years 1958–2015. Results indicate winter and spring season temperatures in the basin have increased significantly, April 1 snow water equivalent (SWE) has decreased by approximately 25%, and streamflow has declined slightly in the April–July snowmelt runoff season. Small increases in precipitation have reduced the impact of declining snowpack on trends in streamflow. Changes in the snowpack–runoff relationship are noticeable in hydrographs of mean monthly streamflow, but are most apparent in the changing ratios of precipitation (rain + snow, and SWE) to streamflow and in the declining fraction of runoff attributable to snowpack or winter precipitation. The observed changes provide observational confirmation for model projections of decreasing runoff attributable to snowpack, and demonstrate the decreasing utility of snowpack for predicting subsequent streamflow on a seasonal basis in the Upper Rio Grande Basin.     

Management Implications of Snowpack Sensitivity to Temperature and Atmospheric Moisture Changes in Yosemite National Park,CA

In order to investigate snowpack sensitivity to temperature increases and end‐member atmospheric moisture conditions, we applied a well‐constrained energy‐ and mass‐balance snow model across the full elevation range of seasonal snowpack using forcing data from recent wet and dry years. Humidity scenarios examined were constant relative humidity (high) and constant vapor pressure between storms (low). With minimum calibration, model results captured the observed magnitude and timing of snowmelt. April 1 snow water equivalent (SWE) losses of 38%, 73%, and 90% with temperature increases of 2, 4, and 6°C in a dry year centered on areas of greatest SWE accumulation. Each 2°C increment of warming also resulted in seasonal snowline moving upslope by 300 m. The zone of maximum melt was compressed upward 100–500 m with 6°C warming, with the range reflecting differences in basin hypsometry. Melt contribution by elevations below 2,000 m disappeared with 4°C warming. The constant‐relative‐humidity scenario resulted in 0–100 mm less snowpack in late spring vs. the constant‐vapor‐pressure scenario in a wet year, a difference driven by increased thermal radiation (+1.2 W/m²) and turbulent energy fluxes (+1.2 W/m²) to the snowpack for the constant‐relative‐humidity case. Loss of snowpack storage and potential increases in forest evapotranspiration due to warming will result in a substantial shift in forest water balance and present major challenges to land management in this mountainous region.     

中国雪灾及相关研究述评

雪灾作为自然灾害的一种,相对于其他灾种,发生的范围和频率较小。历史上发生的雪灾有记载的200多次,其中重大的上百次。学界有关雪灾问题的研究存在着很大的不足：一是有关研究大都包涵在自然灾害之中作为灾种的一部分进行简单论述,而没有单独作为一个专题进行更为详实的研究;二是近30年来,学界多从气象学角度出发,对雪灾的形成机制及原因等方面进行分析,而从社会学与史学的角度进行研究的成果极其少见。     

Metal contamination of short-term snow cover near urban crossroads: correlation analysis of metal content and fine particles distribution

Snow samples were collected near crossroads in Novi Sad, Serbia, during December 2009 to assess metal concentrations (Ca, K, Zn, Fe, Cu, Mn, Al, Pb and Na), fine particle distribution and pH value. The filtered samples of melted snow were analysed, with a focus on particles smaller than a few μm. The most common values of the frequency number distribution curve were either in the range of 0.05-0.07 μm or one order of magnitude higher (0.2-0.5 μm). At examined locations metal concentrations varied from 0.0004 mg L⁻¹ for Pb to 18.9 mg L⁻¹ for Na. Besides Na, which mostly originated from de-icing salt, Ca is found to be the most abundant element in snow indicating the dominant influence of natural factors on snow chemistry. No significant difference was found in concentration of the elements at locations near crossroads with either low or high traffic volume, except for Na and Zn.To investigate how metals were related a correlation analysis was done for the concentrations of metals and with respect to the particle size distribution parameters and pH values. The major influence on the fine particle volume (mass) was concluded to be due to the elements from anthropogenic sources. This conclusion was based on the significant positive correlation between Fe, Zn and Al and the fine particle volume based distribution parameters.     

基于HJ 1A/1B卫星遥感数据的积雪识别方法研究

积雪分布与变化是标示气候变化的敏感因子,采用具有长时间序列的大范围同步获取信息优势的卫星遥感数据进行积雪识别提取,具有重要的理论意义和实际应用价值。针对HJ 1A/1B卫星数据,结合积雪遥感监测的理论方法,在分析HJ 1A/1B卫星CCD和IRS传感器光谱响应特征的基础上,将应用较广的归一化差分积雪指数(NDSI)引入到HJ 1A/1B卫星中,得到了基于CCD和IRS两个传感器数据的HJ NDSI积雪识别方法。为避免由幅宽、扫描区域等因素的差异引起的两种不同传感器同时相数据难获取的问题,对HJ NDSI方法进行了改进,提出了一种仅利用IRS传感器数据的HJ MNDSI积雪识别方法。通过对HJ卫星数据的统计分析,给出了两种方法中的推荐阈值。以西藏普兰为实验区,对上述两种方法得到的结果进行精度评价,结果表明,HJ NDSI和HJ MNDSI方法提取积雪的精度分别为97.66%和94.92%,均能满足实际应用的需要,但HJ MNDSI方法能保证更大的积雪监测范围。     

基于GIS的锡林郭勒盟雪灾救助区划

锡林郭勒盟位于内蒙古自治区东部、冷高压前端,冬季寒冷而漫长,极易发生雪灾,几乎每10年就会发生一次雪灾,给人们的生命、财产安全造成了极大的威胁.根据自然灾害理论,构建了锡盟雪灾救助区划评价指标模型.以雪灾历史灾情、人口分布、牲畜分布和第一、二、三产业为危险性指标,以人口分布、GDP分布、道路通达性为救灾能力评价指标,并利用先进的3S技术和计算机存储技术,将各个指标进行空间模拟计算.最后利用层次分析法确定各指标权重,得到了锡林郭勒盟5级救助区划图.根据当地的自然条件和社会经济条件,结合救灾点分布情况,依次制定了各级地区的救助方案,为政府的减灾救灾工作提供决策支持.     

风雪共同作用下膜结构雪压分布规律的数值模拟研究

对膜结构在风雪共同作用下的雪压分布规律进行了数值模拟研究。首先采用两相流原理对雪漂运动中的空气相和雪相分别进行了数值建模,然后采用CFD数值模拟技术,研究了在风雪共同作用下双坡型膜结构表面的雪荷载分布规律,分析了双坡型膜结构的重要几何参数变化时,雪漂及屋面雪荷载分布的变化规律,总结了双坡型膜屋面在风雪共同作用下的雪压分布规律。结果表明,屋面倾角和屋面宽度是影响风雪共同作用下膜结构表面雪压分布的重要因素,檐口高度和屋面长度是影响膜结构表面雪压分布的次要因素。本文研究为更安全、经济地进行膜结构的抗风雪设计、施工提供了可靠的科学依据。     

SNOTEL,the Soil Climate Analysis Network,and water supply forecasting at the Natural Resources Conservation Service: Past,present, and future

The Snow Survey and Water Supply Forecasting (SSWSF) Program and the Soil Climate Analysis Network (SCAN) of the United States Department of Agriculture's Natural Resources Conservation Service (NRCS) generate key observational and predictive information for water managers. Examples include mountain climate and snow monitoring through manual snow surveys and the SNOw TELemetry (SNOTEL) and SNOtel LITE networks, in situ soil moisture data acquisition through the SCAN and SNOTEL networks, and water supply forecasting using river runoff prediction models. The SSWSF Program has advanced continuously over the decades and is a major source of valuable water management information across the western United States, and the SCAN network supports agricultural and other water users nationwide. Product users and their management goals are diverse, and use-cases range from guiding crop selection to seasonal flood risk assessment, drought monitoring and prediction, avalanche and fire prediction, hydropower optimization, tracking climate variability and change, environmental management, satisfying international treaty and domestic legal requirements, and more. Priorities going forward are to continue innovating to enhance the accuracy and completeness of the observational and model-generated data products these programs deliver, including expanded synergies with the remote sensing community and uptake of artificial intelligence while maintaining long-term operational reliability and consistency at scale.     

河西走廊东部冬春季积雪对沙尘天气的影响

利用河西走廊东部5个气象站1961─2007年逐月积雪深度、积雪日数和沙尘天气的常规观测资料,分析了河西走廊东部冬春季积雪深度、积雪日数和春夏季沙尘日数的时空变化特征,进而探讨河西走廊东部冬春季积雪与春夏季沙尘天气的关系. 结果表明:受海拔高度、地理位置以及天气系统等影响,河西走廊东部积雪从东南向西北递减,高海拔地区的积雪多于低海拔地区;沙尘日数从西北向东南递减,低海拔地区的沙尘日数明显多于高海拔地区. 河西走廊东部冬春季积雪与春夏季沙尘日数呈显著负相关. 积雪深度与沙尘日数的负相关性高于积雪日数与沙尘日数的负相关性;冬春季积雪对春季沙尘的影响大于对夏季沙尘的影响;山区积雪与沙尘日数的相关性高于平原区积雪与沙尘日数的相关性.