An artificial neural network-based snow cover predictive modeling in the higher Himalayas

With trends indicating increase in temperature and decrease in winter precipitation, a significant negative trend in snow-covered areas has been identified in the last decade in the Himalayas. This requires a quantitative analysis of the snow cover in the higher Himalayas. In this study, a nonlinear autoregressive exogenous model, an artificial neural network （ANN）, was deployed to predict the snow cover in the Kaligandaki river basin for the next 30 years. Observed climatic data, and snow covered area was used to train and test the model that captures the gross features of snow under the current climate scenario. The range of the likely effects of climate change on seasonal snow was assessed in the Himalayas using downscaled temperature and precipitation change projection from - HadCM3, a global circulation model to project future climate scenario, under the AIB emission scenario, which describes a future world of very rapid economic growth with balance use between fossil and non-fossil energy sources. The results show that there is a reduction of 9% to 46% of snow cover in different elevation zones during the considered time period, i.e., 2Oll to 2040. The 4700 m to 52oo m elevation zone is the most affected area and the area higher than 5200 m is the least affected. Overall, however, it is clear from the analysis that seasonal snow in the Kaligandaki basin is likely to be subject to substantialchanges due to the impact of climate change.     

A new MODIS daffy cloud free snow cover mapping algorithm on the Tibetan Plateau

Because of similar reflective characteristics of snow and cloud, the weather status seriously affects snow monitoring using optical remote sensing data. Cloud amount analysis during 2010 to 2011 snow seasons shows that cloud cover is the major limitation for snow cover monitoring using MOD10A1 and MYD10A1. By use of MODIS daily snow cover products and AMSR-E snow wa- ter equivalent products （SWE）, several cloud elimination methods were integrated to produce a new daily cloud flee snow cover product, and information of snow depth from 85 climate stations in Tibetan Plateau area （TP） were used to validate the accuracy of the new composite snow cover product. The results indicate that snow classification accuracy of the new daily snow cover product reaches 91.7% when snow depth is over 3 cm. This suggests that the new daily snow cover mapping algorithm is suitable for monitoring snow cover dynamic changes in TP.     

Thermodynamic properties of snow cover on sea ice during the austral summer in Prydz Bay,East Antarctica

The thermodynamic properties of snow cover on sea ice play a key role in the ice-ocean-atmosphere system and have been a focus of recent scientific research. In this study, we investigated the thermodynamic properties of snow cover on sea ice in the Nella Fjord, Prydz Bay, East Antarctica(69°20′S, 76°07′E), near the Chinese Antarctic Zhongshan Station. Our observations were carried out during the 29th Chinese National Antarctic Research Expedition. We found that the vertical temperature profile of snow cover changed considerably in response to changes in air temperature and solar radiation during the summer. Associated with the changes in the temperature profile were fluctuations in the temperature gradient within the upper 10 cm of the snow cover. Results of previous research have shown that the thermal conductivity of snow is strongly correlated with snow density. To calculate the thermal conductivity in this study, we measured densities in three snow pits. The calculated thermal conductivity ranged from 0.258–0.569 W?m-1?K-1. We present these datasets to show how involved parameters changed, and to contribute to a better understanding of melting processes in the snow cover on sea ice.     

A Dipole Pattern of Summer Precipitation over Mid-high Latitude Asia and Related Snow Cover Anomalies in the Preceding Spring

A dipole pattern of summer precipitation over the mid-high latitudes of Asia, which is characterized by opposing summer precipitation variations between the Mongolian and Northeast China （MNC） region and the West Siberian Plain （WSP）, is found to be clear and stable on both interdecadal and interannual scales during 1981- 2011. Spring snow cover anomalies over a small region within the WSP and the Heilongjiang River （HR） region are closely related to the variation of this dipole mode during the subsequent summer, and they can therefore be considered as forecasting factors. Our statistical results imply a potential process explaining the relationship between the spring snow anomalies and the summer rainfall dipole. Corresponding to the snow anomalies, Rossby waves propagate along a path from the WSP region, via the Mongolian Plateau, to the Stanovoy Range during summer. At the same time, Rossby-wave energy divergences and convergences along this path maintain and reinforce an anomalous cyclone and anticyclone pairing over the Asian continent, which is significantly linked to opposite summer precipitation anomalies between the MNC and WSP regions. Numerical experiments are need- ed to further confirm the above conjecture and demonstrate the detailed physical mechanisms linking the spring snow cover anomalies and summer precipitation dipole.     

近50年果洛地区积雪的气候特征分析

利用果洛6县自建站至2011年近50年的地面积雪日数、积雪深度等资料,对果洛积雪的气候特征进行了较为全面的分析。通过气候倾向率的分析发现:近50年来,果洛地区玛沁、达日、班玛、久治的积雪日数呈增加趋势,玛多变化不大,甘德每十年减少1.2天。从最长积雪日数、积雪深度的资料分析看:玛多、甘德、达日、久治是最易发生雪灾的地区,其中玛多、甘德、达日是特大雪灾的易发地;玛沁、班玛是出现雪灾最少的地方。从积雪增量的变化看近50年来果洛积雪增量经历了一次由多到少的转变过程,积雪增量的这种变化与积雪日数的年变化相一致。     

海南铜鼓岭国家级自然保护区海域珊瑚的分布及其健康状况评价

沿铜鼓岭国家级自然保护区海岸南北两侧沿岸布设8个站位,采用断面监测法调查了珊瑚的种类多样性、覆盖率、死亡率和补充量等指标,并利用健康指数（CI）评估了铜鼓岭珊瑚礁生态系统的健康状况和遭受环境压力的程度.本次调查共发现铜鼓岭造礁石珊瑚11科23属40种,软珊瑚8种,造礁石珊瑚和软珊瑚覆盖率分别为13.8%和19.4%,该海域珊瑚礁生态系统保存较为完好和健康.铜鼓岭珊瑚的覆盖率呈现明显的空间分布特征,北侧珊瑚覆盖率为0.1%～9.8%之间,远低于南侧的水平（8.1%～66.1%）.从珊瑚补充量来看,铜鼓岭北侧珊瑚的恢复能力基本为零,而铜鼓岭以南的区域可以有0.4个/m^2珊瑚新个体.通过比较2006年以来珊瑚种类、覆盖率、死亡率、补充量、健康指数等方面的调查数据,认为铜鼓岭保护区的珊瑚礁生态系统得到有效保护,珊瑚礁生态系统处于健康状态.     

被动微波遥感雪深反演混合像元问题研究EI北大核心CSCD

积雪深度是反映地表积雪量变化的重要因子,是水文模型和气候模式中的重要参数之一。被动微波遥感以其穿云透雾、对雪层信息敏感等特点,被广泛应用于雪深的反演研究中。被动微波传感器的低空间分辨率(数千米至数十千米)及地表覆盖的复杂性,使星载被动微波遥感影像中的混合像元现象十分突出,严重制约了被动微波雪深遥感监测的应用和发展。目前,被动微波遥感雪深反演中的混合像元问题研究仍存在着诸多挑战:①理论支撑不足,对被动微波混合像元亮温响应特征及影响机制的研究尚不充分;②针对混合像元问题所发展的被动微波雪深反演算法,对地表异质性特征考虑不足。     

HJ-1B的积雪参数反演研究

积雪参数如雪盖、雪深是标示气候变化的敏感因子,具有较高时空分辨率的HJ-1B卫星是专门用于灾害监测与评估业务的国产卫星之一,开展以HJ-1B为主的积雪参数反演对于我国国产卫星的理论研究与深入应用具有重要意义。本文针对积雪参数反演,根据HJ卫星CCD和IRS传感器的数据特征,深入分析积雪等典型地物的光谱特性,而后针对同时具有HJ-1B/CCD、IRS数据和只有CCD或者IRS传感器数据3种情况展开积雪信息提取方法研究;在进行浅雪区雪深反演时,利用两种不同的统计回归模型进行交叉验证、研究对比。研究结果表明,3种情况下提取出的积雪精度都达到了80%以上,以第1种情况提取精度最高,两种统计模型反演出的浅雪区雪深的一致度达到83%左右,说明HJ星数据能较好地反演雪盖及浅雪区的雪深,能满足实际应用的需要。     

在冰川邂逅最美的冬季

<正>除了海洋,地球上最大的天然水库是什么?答案不是湖泊,亦不是河流,而是冰川。多年的积雪一直冰封在高山上,经过漫长的光阴,受重力作用挤压成     

我国国有土地使用权登记覆盖率达85％

“十五”期间，中国国有土地使用权登记覆盖率已从2001年初的58％上升到了2005年的85％；集体土地所有权登记覆盖率由16％上升到了51％；集体土地使用权登记覆盖率由61％上升到了73％，依法有效地保护了土地产权人的合法权益。