Response of Glacier and Lake Covariations to Climate Change in Mapam Yumco Basin on Tibetan Plateau during 1974–2003

The study of spatial and temporal covariances of glaciers and lakes would help us to understand the impact of climate change within a basin in Tibet. This study focuses on glacier and lake variations in the Mapam Yumco(玛旁雍错)Basin (covering 7 786.44 km2)by Integrationg series of spatial data from topographic maps and digital satellite images at four different times 1974, 1990, 1999,and 2003. The results indicate that (1) decreased lakes, retreated glaciers, enlarged lakes and advanced glaciers co-exist in the basin during the last 30 years; (2) glacier recession was accelerated in recent years due to the warmer climate; (3) lake areas in the basin are both reduced and enlarged by an accelerated speed with more water supplies from speeding melt glaciers or frozen ground in the last three decades.     

Tracking performance of a HSGPS receiver under avalanche deposited snow

The tracking performance of High Sensitivity Global Positioning System (HSGPS) receivers under avalanche deposited snow was investigated. Two field trials were held during April 2006 in the Canadian Rocky Mountains to study the factors affecting GPS signals and positioning performance for avalanche rescue. The PLAN Group at the University of Calgary has developed the miniature Global Navigation Asset Tracker (GNAT™) which integrates the SiRFstar III HSGPS receivers with a microcontroller, onboard flash storage and a 2.4 GHz Zigbee radio modem. The test systems were placed down a 6 cm hole bored in avalanche deposited snow for 2.5 h with data collected at 1 Hz. Post-mission analysis showed average GPS signal attenuation of approximately 11 to 13 dB within the first 1.5 m of avalanche debris. Sufficient GPS signals for positioning were received by GPS receivers buried in 2.7 m of avalanche deposited snow. Methods of improving the GPS position beneath the avalanche debris were investigated, resulting in horizontal position RMS values of 7.4 and 2.8 m at depths of 2.0 and 2.68 m respectively.     

2017年汛期气候预测先兆信号的综合分析

2017年夏季（2017年6—8月）,全国平均降水量348.6 mm,较常年同期（322.6 mm）偏多8.1%,呈现南、北两条多雨带。东亚夏季风偏弱,西太平洋副热带高压显著偏强,脊线位置偏南;欧亚中高纬呈现“两槽一脊”环流型,贝加尔湖地区为正距平控制。赤道中东太平洋海温从前冬冷水向春、夏季暖水发展,20世纪80年代以来容易出现南方多雨的Ⅳ类雨型,夏季贝加尔湖阻塞高压发展。2017年赤道中东太平洋海温从前冬冷水向春、夏季暖水发展,春季北大西洋三极子正位相和2016年欧亚积雪从秋到冬的减少,均有利于夏季贝加尔湖阻塞高压发展,这是夏季主要多雨带位于长江以南的重要前兆信号。     

2018年4月大气环流和天气分析

2018年4月大气环流的主要特征是极涡偏强且呈偶极型分布,中高纬环流呈4波型,西太平洋副热带高压强度较常年偏弱,南支槽强度较常年偏强。4月全国平均气温12.4℃,较常年同期偏高1.4℃;全国平均降水量43.6 mm,比常年同期（44.7 mm）偏少2.5%。月内我国有3次冷空气过程,其中2—7日为一次全国性强冷空气过程,造成大范围剧烈降温和雨雪天气;北方地区出现5次沙尘过程;南方地区出现3次暴雨过程,其中22—24日的暴雨过程给长江中下游地区造成严重的暴雨洪涝灾害。     

乌鲁木齐冬季清雪预报服务研究

以乌鲁木齐冬季清雪工作需求为牵引,利用乌鲁木齐2006—2016年冬季(当年11月—翌年3月)逐日降雪量、积雪深度、气温和173 d降雪日的逐时降雪量资料,分析了近11年冬季各量级降雪的分布特征、降雪持续时间和降雪的日变化特征;对积雪深度和对应降雪量做线性拟合,得出二者比值大体为0.968 cm/mm。得出清雪预报服务的重点是:小雪的有无、降雪起止时间和累积降雪量、积雪深度的预报,难点是中雪、大雪特别是暴雪和对应的积雪深度的精细化预报。     

内蒙古东南部大到暴雪过程影响系统及物理量场特征分析

利用1951—2013年63a的地面观测、MICAPS、NCEP、历史天气图等资料,将发生在内蒙古东南部的150次大到暴雪过程的700hPa影响系统分为7种类型,对其中2007—2013年的26次大到暴雪过程,分型统计了25个测站中的降大到暴雪的测站的物理量场。结果表明:散度场总体表现为低空辐合、高空辐散的特征,对应了高、低空急流的耦合作用,使得垂直速度场维持整层、长时间的强上升气流,因类型不同达到的高度有所不同;最大相对湿度分布在925~500hPa之间,水汽通量散度辐合主要表现在925~700hPa,比湿场随高度增高迅速减小,各类型925hPa最小比湿在2~2.9g·kg~(-1)、850hPa最小比湿在1.7~3.2g·kg~(-1)之间,反映了低空西南暖湿急流的作用,尤其是925hPa超低空急流对大到暴雪的贡献;75百分位的1000hPa即近地面层基本为冷平流,925hPa以上均为暖平流,具有冷垫作用,为大到暴雪的发生提供了动力触发条件。     

雨雪冰冻监测系统的设计与应用

雨雪冰冻气象灾害会严重影响交通、电力等各行各业,通过建设雨雪冰冻监测系统,增加积雪深度、称重降水、实景观测等观测要素,加强积雪、固态降水自动化监测。利用OpenCV技术对雪深监测数据进行质量控制,采用等值线wContour类库画图方法绘制等值线图,结合实景拍摄及时准确反映雨雪冰冻情况。通过分析显示系统,综合各类气象观测资料,为气象工作者或决策部门提供直观、准确的气象信息,为气象防灾减灾提供有效的技术手段,提高气象服务水平。     

冰川冰储量计算方法及发展趋势

冰川冰储量不仅是冰川的重要属性,而且是核算冰川水资源及预测冰川变化的基础数据,因此准确计算冰川冰储量及其变化具有重要的理论与现实意义。目前冰川储量估算的主要方法有经验公式法、冰厚模型估算法、探地雷达法;冰川储量相对变化计算方法有实地测量法和遥感监测法。通过系统分析和讨论各计算方法的原理、现状及存在的问题,以期为冰川储量估算提供方法参考。研究表明：对于冰川冰储量计算而言,经验公式法适用于区域性或全球性的冰川储量估算;模型估算法适用于个体或小范围冰川储量估算;探地雷达法适用于人类易到达区域冰川储量的估算。对于冰川冰储量相对变化计算,实地测量法适用于对精度要求高且满足实地测量条件的单条或中小型冰川,遥感监测法适用于全球性冰储量变化估算,但需改进算法和提高数据空间分辨率。目前,随着无人机技术的逐步应用,以及冰川流速等理论模型的提出,为冰川冰储量估算方法的发展提供了新契机。     

Spatial variations of Pb,As, and Cu in surface snow along the transect from the Zhongshan Station to Dome A,East Antarctica

The spatial distributions of lead, arsenic, and copper(Pb, As, and Cu, respectively) in surface snow along the transect from the Zhongshan Station to Dome A, East Antarctica, are presented. The mean concentrations of Pb, As, and Cu are1.04±1.56 pg/g, 0.39±0.08 pg/g, and 11.2±14.4 pg/g, respectively. It is estimated that anthropogenic contributions are dominant for Pb, As, and Cu. Spatially, Pb concentrations show an exponentially decreasing trend from the coast inland, while a moderate decreasing trend is observed for Cu concentrations in the coastal area(below 2,000 m above sea level(a.s.l.)).In the intermediate area(2,000–3,000 m a.s.l.), the concentrations and enrichment factors of all these elements show high variability due to the complicated characteristics of climate and environment. On the inland plateau(above 3,000 m a.s.l.),the high concentrations of As and Pb are induced by high deposition efficiency, the existence of polar stratospheric precipitation, and the different fraction deposition to East Antarctica. The extremely high concentrations with maximum values of9.59 pg/g and 69.9 pg/g for Pb and Cu, respectively, are suggested to result mainly from local human activities at the station. Our results suggest that source, transport pathway, and deposition pattern, rather than distance from the coast or altitude, lead to the spatial distributions of Pb, As, and Cu; and it is further confirmed by spatial variations of the three metals deposited over the whole continent of Antarctica.     

A GIS-based modeling of snow accumulation and melt processes in the Votkinsk reservoir basin

Coupled hydrological and atmospheric modeling is an efficient method for snowmelt runoff forecast in large basins. We use short-range precipitation forecasts of mesoscale atmospheric Weather Research and Forecasting (WRF) model combining them with ground-based and satellite observations for modeling snow accumulation and snowmelt processes in the Votkinsk reservoir basin (184,319 km²). The method is tested during three winter seasons (2012–2015). The MODIS-based vegetation map and leaf area index data are used to calculate the snowmelt intensity and snow evaporation in the studied basin. The GIS-based snow accumulation and snowmelt modeling provides a reliable and highly detailed spatial distribution for snow water equivalent (SWE) and snow-covered areas (SCA). The modelling results are validated by comparing actual and estimated SWE and SCA data. The actual SCA results are derived from MODIS satellite data. The algorithm for assessing the SCA by MODIS data (ATBD-MOD 10) has been adapted to a forest zone. In general, the proposed method provides satisfactory results for maximum SWE calculations. The calculation accuracy is slightly degraded during snowmelt periods. The SCA data is simulated with a higher reliability than the SWE data. The differences between the simulated and actual SWE may be explained by the overestimation of the WRF-simulated total precipitation and the unrepresentativeness of the SWE measurements (snow survey).