哈巴雪山第四纪冰川发育特点的初步研究

哈巴雪山(5 396 m)位于横断山脉中北段,与玉龙雪山(5 596 m)以金沙江相隔,受西南季风影响强烈。在哈巴雪山3 100 m以上保存第四纪冰川侵蚀与堆积地貌,主要沿哈巴雪山西北脊两侧分布。应用相对地貌法,对比邻近山地尤其是玉龙雪山,将哈巴雪山冰期系列初步划分为:倒数第二次冰期、末次冰期早期和末次冰盛期(LGM)。以哈巴雪山哈巴河谷的冰碛物为研究对象,其末端海拔高度在倒数第二次冰期、末次冰期早期、末次冰盛期分别约为3 100 m、3 500 m、3 900 m。应用TSAM法、MEIM法、CF法计算得出哈巴雪山古雪线高度在倒数第二次冰期、末次冰期早期、末次冰盛期分别为3 675 m、4 000 m、4 200 m。     

四川盆地汛期旱涝预测研究

对近１０年来四川盆地汛期降水预测水平进行了定量评估,并与国家气候中心预测水平作了对比。在分析影响四川盆地汛期降水主要物理因素的基础上,提出了四川盆地汛期旱涝预测的基本思路和技术方法,并在实际业务预报中取得了较好的效果。     

新疆积雪对气候变暖的响应

积雪对全球变暖的响应是当前正在争论的问题.文中通过地面气象台站和SMMR微波卫星遥感两种积雪资料所建立的两个独立的积雪序列的一致性,证明前者在表现新疆积雪长期变化能力方面具有可靠性.阐明了积雪年际变化特征及其与冬季气温和降水量年际波动的关系,检验了积雪长期变化趋势.研究表明,虽然近50a来新疆冬季变暖十分显著,尤其20世纪90年代为最温暖的时期,但是积雪并未出现持续减少的现象;积雪长期变化表现为显著的年际波动过程叠加在长期缓慢的增加趋势之上.积雪年际波动是冬季降水量和气温两者年际波动共同作用的结果;冬季气温和降雪量变化受不同的欧亚环流振荡所控制;积雪增加趋势与降雪量趋势相一致,这可能是由于全球变暖导致海洋蒸发量增加,以及在寒冷干燥气候下积雪对降雪量变化更为敏感的缘故.     

西岭雪山滑雪场秋冬旅游降雪预报研究

利用大邑、西岭雪山滑雪场及周边区域自动站2005～2017年每年10月～次年2月逐日最低温度资料,通过统计分析区域自动站与大邑站候平均最低温度差值,建立以大邑本站最低温度预报值为基础,加上逐候最低温度差值后得到区域各站的日最低温度预报的候最低温度差值订正方法;用距滑雪场最近的格点温度预报数据代替滑雪场站点温度预报,选出最低温度,以气温预报变化量,建立最低气温预报的模式温度订正方法;建立以候最低温度差值订正和模式温度订正进行加权平均的最低温度集成订正方法。通过对以上三种最低温度预报方法进行检验,发现最低温度集成订正方法预报准确率最高。基于最低温度集成订正方法预报西岭雪山滑雪场的最低温度,结合智能网格降水预报结果和降雪最低温度阈值判别,建立西岭雪山降雪的订正预报方法。     

中国西部积雪对我国汛期降水的影响

本文利用台站及卫星资料建立了中国西部积雪３０年逐月时间序列。该序列是目前资料时间最长、最好的序列，为研究该区积雪月际和年际变化及其影响提供了较可靠的依据。中国西部冬春积雪对我国汛期降水的影响平均为负相关趋势，与６月降水的相关分布较有规律，冬春多（少），其它地区６月降水偏多（少）。我国西部多（少）雪对６月从份５００ｈＰａ高度的变化是：高原北边高纬高度降低（升高）及副热地区升高（降低），有（不）利于高     

青藏高原东部牧区雪灾的环流型及水汽场分析

冬、春季雪灾是青藏高原东部牧区重要的灾害性天气。本文利用历史天气图和国家气象中心T106L19全球模式的分析值格点资料，分析了青藏高原东部牧区近20年来冬，冬季降雨的天气形势和水汽场。结果表明，北脊南槽型、乌山脊型、阶梯槽型和国境槽型是造成高原东部牧区降雪的四类主要环流型；在高原东部牧区强降雪天气过程时气柱可降水量有明显增加，记要降雪区与水汽通量辐合区吻合，主要水汽来自孟加拉湾地区。     

Environmental significance of snowpit chemistry in the typical monsoonal temperate glacier region,Baishui glacier no. 1, Mt Yulong,China

Samples were collected from two snowpits in Baishui glacier no. 1, Mt Yulong, China, in May 2006. Snowpit chemistry was studied, using ion tracer techniques, HYSPLIT model, factor analysis, correlation and trend analysis. It indicated that total cation concentration is higher in 4,900-m snowpit than in 4,750-m snowpit, whereas total anion concentration is higher in 4,750-m snowpit. Cations, especially Ca²⁺, dominate ionic concentrations in Baishui glacier no. 1. According to correlation analysis and factor analysis, ions can be categorized as follows: Cl⁻ and NO₃ ⁻ as Group 1, SO₄ ²⁻ as Group 2, Mg²⁺ and Ca²⁺ as Group 3, Na⁺ as Group 4, K⁺ as Group 5. Contribution made by terrestrial dust to ionic concentration accounts for 52.27, 100, 99.36, 98.91, 96.16 and 99.97% of Cl⁻, NO₃ ⁻, SO₄ ²⁻, K⁺, Mg²⁺ and Ca²⁺, respectively, in 4,900-m snowpit, and for 64.00, 100, 99.57, 98.63, 96.25 and 99.97% in 4,750-m snowpit. Local dust is the principal source of snowpit chemical components. Pollutants brought from industrial areas of South Asia, Southeast Asia and South China by monsoonal circulation also makes some contribution to anion concentrations, but pollution associated with human activities makes a very slight contribution in study area. The chemical characteristics of two snowpits are different owing to the difference of deposition mechanism and local environment in different altitudes.     

Impacts of a bottom trawling exclusion zone on Snow Crab abundance and fish harvester behavior in the Labrador Sea, Canada

The Hawke Box trawling exclusion zone off southern Labrador is a 8610 km² closed area implemented in 2003 to protect soft-shelled pre-recruit Snow Crab and juvenile cod from mortality imposed by shrimp trawling and other bottom-impact fisheries. This study utilizes survey, logbook, and observer data from the Snow Crab and Northern Shrimp fisheries to assess the effectiveness of the Hawke Box in protecting and possibly enhancing the Snow Crab resource off southern Labrador. The results indicate that the exclusion zone has failed to protect pre-recruit crabs largely due to a redistribution and intensification of directed Snow Crab effort inside the Box in the years following closure. This unexpected outcome resulted in a high level of fishery-induced mortality to pre-recruit crabs and masked any potential positive outcomes from the cessation of trawling. The shortcomings that contributed to the failure of this exclusion area are discussed in relation to the current state of knowledge on the effectiveness of marine protected areas in general as management tools for conserving aquatic resources.     

Estimation of snow density using full-polarimetric Synthetic Aperture Radar (SAR) data

In this paper, a new snow density estimation methodology is proposed for full-polarimetric Synthetic Aperture Radar (SAR) data. The generalized four component polarimetric decomposition with unitary transformation (G4U) based generalized volume parameter is utilized to invert snowpack dielectric constant using the Fresnel transmission coefficients. The snow density is then estimated using an empirical relationship. Six Radarsat-2 fine resolution full-polarimetric C-band datasets were acquired over Himachal Pradesh, India. The near-real time in-situ measurements were collected with the satellite pass to validate the proposed method. The mean absolute error (MAE) of the proposed method is 0.027 g cm⁻³ and the root mean square error (RMSE) is 0.032 g cm⁻³. The snow density variation within a season were also analyzed using multi-temporal Radarsat-2 data.     

Time–space continuity of daily maps of fractional snow cover and albedo from MODIS

Using reflectance values from the seven MODIS “land” bands with 250 or 500 m resolution, along with a corresponding cloud product, we estimate the fraction of each 500 m pixel that snow covers, along with the albedo of that snow. The daily products have data gaps and errors because of cloud cover and sensor viewing geometry. Rather than make users interpolate and filter these patchy daily maps without completely understanding the retrieval algorithm and instrument properties, we use the daily time series to improve the estimate of the measured snow properties for a particular day. We use a combination of noise filtering, snow/cloud discrimination, and interpolation and smoothing to produce our best estimate of the daily snow cover and albedo. We consider two modes: one is the “predictive” mode, whereby we estimate the snow-covered area and albedo on that day using only the data up to that day; the other is the “retrospective” mode, whereby we reconstruct the history of the snow properties for a previous period.