非典型周期和气候突变的识别与判定

通过两种新方法分析了无锡站降水年际变化的突变性、周期性等特征,揭示了旱涝演化的自然规律。研究表明,1934、1978、2013年是我国近现代气候突变的临界点,这是旱涝演化的自然选择;无锡站年际降水的观测历史可分成四个特征不同的时段,每个时段节点对应的都是一次气候突变;气候突变会改变年际降水序列的一致性,分段法研究可以大幅度降低模拟难度、提高预测效率。发现并确认了3个气候突变点,实现了超长缺测中断期(13a)旱涝趋势的精确插补,完成了无锡站近百年降雨序列的周期性分析与旱涝趋势预测模拟,研究成果改变了近现代气候历史无法细分的现状。     

Hydrological trends and the evolution of catchment research in the Alptal valley,central Switzerland

When the observation of small headwater catchments in the pre-Alpine Alptal valley (central Switzerland) started in the late 1960s, the researchers were mainly interested in questions related to floods and forest management. Investigations of geomorphological processes in the steep torrent channels followed in the 1980s, along with detailed observations of biogeochemical and ecohydrological processes in individual forest stands. More recently, research in the Alptal has addressed the impacts of climate change on water supply and runoff generation. In this article, we describe, for the first time, the evolution of catchment research at Alptal, and present new analyses of long-term trends and short-term hydrologic behaviour. Hydrometeorological time series from the past 50 years show substantial interannual variability, but only minimal long-term trends, except for the ~2°C increase in mean annual air temperature over the 50-year period, and a corresponding shift towards earlier snowmelt. Similar to previous studies in larger Alpine catchments, the decadal variations in mean annual runoff in Alptal's small research catchments reflect the long-term variability in annual precipitation. In the Alptal valley, the most evident hydrological trends were observed in late spring and are related to the substantial change in the duration of the snow cover. Streamflow and water quality are highly variable within and between hydrological events, suggesting rapid shifts in flow pathways and mixing, as well as changing connectivity of runoff-generating areas. This overview illustrates how catchment research in the Alptal has evolved in response to changing societal concerns and emerging scientific questions.     

Terrestrial discharge influences microbioerosion and microbioeroder community structure in coral reefs

Microbioerosion rates and microbioeroder community structure were studied in four Kenyan protected coral-reef lagoons using shell fragments of Tridacna giant clams to determine their response to the influence of terrestrial run-off. Fourteen different microbioeroder traces from seven cyanobacteria, three green algae and four fungi species were identified. The river discharge-impacted reef and ‘pristine’ reef showed similar composition but higher microbioeroder abundance and total cyanobacteria- and chlorophyte-bioeroded areas when compared with the other study reefs. Cyanobacteria dominated during the north-east monsoon (NEM) relative to the south-east monsoon (SEM) season, with algae and cyanobacteria being major microbioeroders in the river-impacted and pristine reefs. The rate of microbioerosion varied between 4.3 g CaCO3 m^?2 y^?1 (SEM) and 134.7 g CaCO₃ m^?2 y^?1 (NEM), and was highest in the river-impacted reef (127.6 g CaCO₃ m^?2 y^?1), which was almost double that in the pristine reef (69.5 g CaCO₃ m^?2 y^?1) and the mangrove-fringed reef (56.2 g CaCO₃ m^?2 y^?1). The microbioerosion rates measured in this study may not be high enough to cause concern with regard to the health and net carbonate production of Kenya’s coral reefs. Nevertheless, predicted increases in the frequency and severity of stresses related to global climate change (e.g. increased sea surface temperature, acidification), as well as interactions with local disturbances and their influence on bioerosion, may be increasingly important in the future.     

从第三极到北极： 积雪变化研究进展

在全球气候变化背景下， 第三极和北极地区积雪是地表最活跃的自然要素之一， 其动态变化对气候环境和人类生活产生重要影响。通过回顾第三极和北极积雪研究进展， 阐述了降雪、 积雪范围、 积雪日数、 积雪深度和雪水当量在第三极和北极地区的时空分布特征和变化趋势。结果表明： 近50年， 特别是进入21世纪以来， 第三极和北极地区降雪比率均呈下降趋势； 积雪范围、 积雪日数、 积雪深度、 雪水当量总体均呈减小趋势， 融雪首日有所提前。同时就积雪变化对生态系统与气候系统的影响进行了论述， 评估了积雪的反馈作用。通过总结第三极和北极积雪变化研究进展， 凝练研究中存在的不足和未来发展趋势， 为提升积雪对气候变化及经济社会发展影响的认识提供重要科学支撑。     

Climatological Characteristics of the East Asian Winter Monsoon Simulated by CWRF Regional Climate Model

Based on the ERA-Interim atmospheric reanalysis data from the European Medium-Term Weather Forecast Center from 1979 to 2016 and the ERSSTv4 sea surface temperature data from the US National Oceanic and Atmospheric Administration, the regional climate model CWRF was used to simulate the climate characteristics in East Asia. The results show that the CWRF model can well reproduce the average characteristics of the East Asian winter monsoon circulation, including the location and intensity of the low-level continental cold high pressure and variation characteristics of wind field in high and low levels. The occurrence area and frequency of the north wind in the simulation and the reanalysis data were further calculated and compared. It is shown that they are basically consistent. The distribution of air temperature and precipitation over China are well represented by the model. The water vapor transport is also in good agreement with the reanalysis data. The water vapor from the Bay of Bengal plays a vital role in the precipitation over South China. The simulation results of apparent heat source and apparent moisture sink show that the model can well simulate the thermal difference between the East Asian continent and the adjacent sea area. The analysis results indicate that CWRF model has the ability to simulate the main characteristics of the East Asian winter monsoon.     

基于多变量LSTM神经网络的地下水水位预测

为解决以往模型未考虑地下水位相关影响因素的问题，探讨长短期记忆（LSTM）神经网络在地下水位预测中的应用，利用长短期记忆神经网络，采用多变量输入的方式，构建了基于多变量LSTM神经网络的地下水水位预测模型。以泰安市岱岳区J1号监测井为例，采用2001-2014年地下水水位动态监测资料与相关影响因素数据，利用多变量LSTM神经网络对2015-2016年地下水位进行预测，并与单变量LSTM神经网络和反向传播（BP）神经网络进行对比。研究结果表明：以相关影响变量为输入的BP神经网络无法考虑时序变化规律，预测均方根误差最大，为2.399 3；以地下水位为变量输入的单变量LSTM神经网络仅能根据时序变化作出相应预测，无法考虑相关变量影响，预测均方根误差为2.102 2；基于多变量输入的LSTM神经网络的预测精度显著高于单变量LSTM神经网络和BP神经网络，预测均方根误差最小，仅为1.919 1。总体上，多变量LSTM神经网络地下水位预测模型仅在某些峰值处误差较大，但总体预测效果较为理想。     

基于PSR-WSVM模型的边坡位移预测

为建立高精度的边坡位移预测模型，采用相空间重构（PSR）将边坡位移时间序列数据转换为多维数据，同时构造小波核函数改进的支持向量机模型，建立PSR-WSVM模型并应用于边坡位移预测。将PSR-WSVM模型预测结果与传统支持向量机（SVM）模型、小波支持向量机（WSVM）模型和基于相空间重构的支持向量机（PSR-SVM）模型预测结果进行对比，通过平均绝对误差（MAE）、平均绝对误差百分比（MAPE）和均方根误差（RMSE）3个精度评价指标验证PSR-WSVM模型的可行性。工程实例结果表明，PSR-WSVM模型预测结果的3个精度评价指标都优于另外3种模型，边坡位移预测的精度明显提升。     

Variations in glacier volume and snow cover and their impact on lake storage in the Paiku Co Basin,in the Central Himalayas

Glaciers and snow cover are important constituents of the surface of the Tibetan Plateau. The responses of these phenomena to global environmental changes are sensitive, rapid and intensive due to the high altitudes and arid cold climate of the Tibetan Plateau. Based on multisource remote sensing data, including Landsat images, MOD10A2 snow product, ICESat, Cryosat-2 altimetry data and long-term ground climate observations, we analysed the dynamic changes of glaciers, snow melting and lake in the Paiku Co basin using extraction methods for glaciers and lake, the degree-day model and the ice and lake volume method. The interaction among the climate, ice-snow and the hydrological elements in Paiku Co is revealed. From 2000 to 2018, the basin tended to be drier, and rainfall decreased at a rate of −3.07 mm/a. The seasonal temperature difference in the basin increased, the maximum temperature increased at a rate of 0.02°C/a and the minimum temperature decreased at a rate of −0.06°C/a, which accelerated the melting from glaciers and snow at rates of 0.55 × 10⁷ m³/a and 0.29 × 10⁷ m³/a, respectively. The rate of contribution to the lake from rainfall, snow and glacier melted water was 55.6, 27.7 and 16.7%, respectively. In the past 18 years, the warmer and drier climate has caused the lake to shrink. The water level of the lake continued to decline at a rate of −0.02 m/a, and the lake water volume decreased by 4.85 × 10⁸ m³ at a rate of −0.27 × 10⁸ m³/a from 2000 to 2018. This evaluation is important for understanding how the snow and ice melting in the central Himalayas affect the regional water cycle.     

Swedish Forests in the Bioeconomy: Stories from the National Forest Program

Abstract

The concept of a bioeconomy has been placed central in formation of a Swedish National Forest Program (NFP). Drawing on Hajer’s conceptual framework of storylines, we present a discourse analysis of the working group reports underlying the establishment of the NFP strategy. We ask what stories about Swedish forests come to dominate the NFP process, how well they reflect the commitment of balancing economic, social and environmental interests, and what role the concept of a bioeconomy, has on the formation of these stories. Storylines of Swedish forests in the bioeconomy unite wider European discourses on the bioeconomy and climate change with historical Swedish forest policy discourses, revitalizing a discourse coalition comprising the state and the industry. Particular to the Swedish discourse is the strong emphasis on creating consensus around a single story of the forest-based bioeconomy.     

天山南坡高冰川覆盖率的木扎提河流域水文过程对气候变化的响应

木扎提河是天山南坡冰川面积覆盖率最大（48.2%）的河流， 流域径流过程对气候变化极为敏感， 为了合理管理和规划水资源， 确保水资源的可持续利用， 亟需定量评估气候变化对该流域水文过程的影响。以VIC-CAS分布式水文模型为计算平台， 利用实测的径流和两次冰川编目间的冰川面积变化数据开展了模型的多目标参数化校正和验证， 有效提高了模拟结果的“真实性”， 然后通过数值模拟结果结合观测数据定量解析了流域径流的组成、 变化特征及对气候变化的响应机理。结果表明： 木扎提河总径流集中在暖季（5 - 9月）， 占全年总径流量的77.9%， 冰川径流、 融雪径流和降雨径流分别占总径流量的66.6%、 26.4%和7.0%。1971 - 2010年木扎提河流域气温和降水呈显著增加趋势， 由于降水的增加， 降雨和融雪径流均呈增加趋势， 但冰川径流呈现明显减少趋势， 导致总径流呈现下降趋势。在RCP4.5情景下， 未来该流域气温呈现明显升高趋势， 降水表现为微弱下降趋势； 气候变暖后， 更多降水以降雨形式发生， 未来降雨径流将明显增加， 降雪和融雪径流已于20世纪90年代达到峰值， 随后明显减少； 冰川面积将持续萎缩， 冰川径流于21世纪10年代达到拐点， 随后明显减少， 导致河道总径流量也将明显减少。