变化背景下的当代中国自然地理学——2017全国自然地理学大会述评

面对变化中的全球环境以及变化中的学科热点,以“变化背景下自然地理学新发展与新挑战”为主题的第一届全国自然地理学大会于2017年11月20-22日在南京召开。聚焦地理学与可持续发展、自然地理要素与过程集成、空间数据挖掘与系统决策等当代自然地理学研究的前沿内容,通过学科前沿理论的凝练,引导自然地理过程研究的继续深化;依托理论与方法创新;在典型流域、区域实现了自然地理过程的初步集成,切实服务于人地耦合视角下的可持续社会决策。深化自然地理学分支学科的过程研究、推进综合自然地理学的发展、提升陆地表层系统观测和模拟水平,将有助于进一步巩固自然地理学在地理科学学科体系中的基础学科地位,为满足国家重大战略需求和全球可持续发展作出重要的学科贡献。     

The trade network of the Belt and Road Initiative and its topological relationship to the global trade network

Unimpeded trade is one of the cooperation priorities in the Belt and Road Initiative proposed by China. On 15 May 2017, the Joint Communique of the Leaders Roundtable of the Belt and Road Forum for International Cooperation reaffirmed the participants’ shared commitment to build an open economy and ensure free and inclusive trade. The Belt and Road Initiative (BRI) is not only China's new action to drive its open and global development, but also a platform for an increasing number of countries to explore free and inclusive trade and promote a universal, rule-based, open, non-discriminatory, and equitable multilateral trade system. It is therefore important to examine the topological relationship between the BRI and global trade networks. More specifically, this article first analyzes the community structure of trade networks using a community detection algorithm, and then estimates the topological relationship between different trade communities. The findings of this article are as follows. First, this research identified three trade communities and two sub-communities in the BRI trade network, in which China is the core, Russia is the sub-core of the biggest trade community, and India, United Arab Emirates, and Saudi Arabia are cores of the second trade community (South Asia-West Asia). Second, it identified five trade communities in the global trade network, centred on China, USA, Russia, India-United Arab Emirates, and Germany- Netherlands-France-Britain and other European developed countries. Third, the topological analysis indicated that in the global trade network, most BRI countries are attracted by the core nodes of the BRI regions, such as the China, Russia and India-United Arab Emirates core nodes, and have strong trade contacts with BRI countries. Most Central-East European countries are mainly attracted by Germany-Netherlands-France-Britain and other developed European countries with a low penetration of BRI trade. Although some Southeast Asian countries are incorporated into the Asia-Australia-South Africa community with China as the core, they still need to strengthen trade linkages with BRI countries.     

Maritime network dynamics before and after international events

Investigating the influence of international events on global maritime networks is a challenging task that must comprehensively incorporate geographical, political, and maritime sciences. Understanding global maritime network dynamics is an initial and critical step in this investigation. This study proposes an automatic identification system (AIS)-based approach to understanding maritime network dynamics before and after international events. In this approach, a spatiotemporal modeling method is introduced to measure the similarity in shipping trends before and after international events. Then, a spatiotemporal analytic framework is proposed to understand the maritime network dynamics by grouping similar situation, and assessing possible indirect effects within a network. Finally, three case studies of international events, military conflict, lifted economic sanctions, and government elections, were used to investigate the observed network dynamics possibly affected by international events. The results indicate that container, tanker, and bulk shipping between India and its connected countries all declined more than 69% after military conflicts between India and Pakistan in August 2015. Tanker shipping between Iran and the United Arab Emirates increased 51% after economic sanctions on Iran were lifted. Container shipping between Sri Lanka and Singapore, Malaysia, and India increased more than 74% after the general election in Sri Lanka. These investigations demonstrate the feasibility of the proposed approach in assessing the possible effects of international events on maritime network dynamics.     

A discrete global grid system for earth system modeling

To support Earth system modeling, we propose a discrete global grid system that expresses multi-resolution spatial data. Specifically, a unified coding model that expresses a grid of nodes, edges, and cells is constructed for a triangular discrete global grid system. To fulfill the requirements of practical applications, we design a code-based topological query method for this grid system and an algorithm to transform between grid codes and geographic coordinates. We evaluate the Global Finite Volume Community Ocean Model (Global-FVCOM) on the triangular discrete global grid system in the proposed uniform coding model. The ocean tidal waves simulated by the Global-FVCOM running on the coded grid are then compared with results obtained using a traditional irregular spherical grid system, and the results display comparable accuracy. The uniform coding model proposed in this paper provides a triangular discrete global grid system that can represent multi-resolution spatial data and can be used in Earth system models. This unified coding model can also be applied to the geographic coordinate system made up of latitudes and longitudes, as well as diamond and hexagonal grids.     

Climate Change of 4°C Global Warming above Pre-industrial Levels

Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4°C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4°C global warming will occur is 2084. Based on the median results of models that project a 4°C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-to-noise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5°C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the inter-model consistency is better for temperature than for precipitation.     

Modeling the Warming Impact of Urban Land Expansion on Hot Weather Using the Weather Research and Forecasting Model: A Case Study of Beijing,China

The impacts of three periods of urban land expansion during 1990–2010 on near-surface air temperature in summer in Beijing were simulated in this study, and then the interrelation between heat waves and urban warming was assessed. We ran the sensitivity tests using the mesoscale Weather Research and Forecasting model coupled with a single urban canopy model,as well as high-resolution land cover data. The warming area expanded approximately at the same scale as the urban land expansion. The average regional warming induced by urban expansion increased but the warming speed declined slightly during 2000–2010. The smallest warming occurred at noon and then increased gradually in the afternoon before peaking at around 2000 LST—the time of sunset. In the daytime, urban warming was primarily caused by the decrease in latent heat flux at the urban surface. Urbanization led to more ground heat flux during the day and then more release at night, which resulted in nocturnal warming. Urban warming at night was higher than that in the day, although the nighttime increment in sensible heat flux was smaller. This was because the shallower planetary boundary layer at night reduced the release efficiency of near-surface heat. The simulated results also suggested that heat waves or high temperature weather enhanced urban warming intensity at night. Heat waves caused more heat to be stored in the surface during the day, greater heat released at night, and thus higher nighttime warming. Our results demonstrate a positive feedback effect between urban warming and heat waves in urban areas.     

基于定量化植物防御效应的臭氧通量模型的优化

继SUM06、AOT40之后,基于气孔臭氧累计吸收通量（AFstY）的研究方法被广泛应用于臭氧风险评估中.然而通量模型中的阈值Y并不能很好地代表植物对臭氧的抗氧化能力以及自我修复能力,如何动态模拟植物自身的防御机制对于提高臭氧风险评估的准确性尤为重要.本文基于前人的研究成果探讨如何定量化植物对臭氧的防御效应,运用光合定量方法动态模拟伤害阈值并计算臭氧有效吸收通量,运用SODA模型从气孔吸收和质外体解毒两个方面探讨细胞内抗坏血酸对臭氧原生质膜通量的影响,旨在为臭氧通量模型研究开辟一个新的视角,并为后续的臭氧胁迫效应研究打下基础.     

THE DOUBLE-LAYER STRUCTURE OF THE HADLEY CIRCULATION AND ITS INTERDECADAL EVOLUTION CHARACTERISTICS

Based on the three-pattern decomposition of global atmospheric circulation(TPDGAC), this study investigates the double-layer structure of the Hadley circulation(HC) and its interdecadal evolution characteristics by using monthly horizontal wind field from NCEP/NCAR reanalysis data from 1948—2011. The following major conclusions are drawn: First, the double-layer structure of the HC is an objective fact, and it constantly exists in April,May, June, October and November in the Southern Hemisphere. Second, the double-layer structure is more obvious in the Southern than in the Northern Hemisphere. Since the double-layer structure is sloped in the vertical direction, it should be taken into consideration when analyzing the variations of the strength and location of the center of the HC.Third, the strength of the double-layer structure of the HC in the Southern Hemisphere consistently exhibits decadal variations with a strong, weak and strong pattern in all five months(April, May, June, October, and November), with cycles of 20-30 a and 40-60 a. Fourth, the center of the HC(mean position of the double-layer structure) in the Southern Hemisphere consistently and remarkably shifts southward in all the five months. The net poleward shifts over the 64 years are 5.18°, 2.11°, 2.50°, 1.79° and 5.76° for the five respective months, with a mean shift of 3.47°.     

Empirical calibration of climate policy using corporate solvency: a case study of the UK’s carbon price support

Emission reductions improve the chances that dangerous anthropogenic climate change will be averted, but could also cause some firms financial distress. Corporate failures, especially if they are unnecessary, add to the social cost of abatement. Social value can be permanently destroyed by the dissolution of organizational capital, deadweight losses paid to liquidators, and unemployment. This article proposes using measures of corporate solvency as an objective tool for policy makers to calibrate the optimal stringency of climate change policies, so that they can deliver the least loss of corporate solvency for a given level of emission reductions. They could also be used to determine the generosity of any compensation to address losses to corporate solvency. We demonstrate this approach using a case study of the UK’s Carbon Price Support (a carbon tax).

Key policy insights

• Solvency metrics could be used to empirically calibrate the optimal stringency of climate policies.

• An idealized solvency trajectory for firms affected by climate change policy would cause corporate solvency to initially decline – approaching but not exceeding ‘distressed’ levels – and then gradually improve to a new ‘steady state’ once the low-carbon transition had been achieved.

• In terms of the UK’s Carbon Price Support, corporate solvency of energy-intensive industries was found to be stable subsequent to its introduction. Therefore, the available evidence does not support its later weakening.

     

全球1.5℃和2.0℃升温对中国小麦产量的影响研究

采用部门间影响模式比较计划（ISI-MIP）的气候模式,确定全球升温1.5℃和2.0℃出现的时间,并结合农业技术转移决策支持系统（DSSAT）模型模拟小麦的产量,最终选取4套数据对比研究中国小麦区温度和降水变化特征以及各区域小麦产量变化趋势,综合评价了不同升温情景对中国小麦产量的影响。结果表明：(1)在全球升温1.5℃和2.0℃背景下,我国小麦生育期内温度相对于工业革命前分别升高1.17℃和1.81℃。两种升温情景下我国春麦区升温幅度大于冬麦区升温幅度。春麦区中新疆春麦区升温幅度最大,西北春麦区升温幅度最小;冬麦区中温度变化最大和最小的麦区分别为西南冬麦区和黄淮冬麦区。(2)在全球升温1.5℃和2.0℃情景下,我国小麦生育期内降水相对于历史时段(1986—2005年)分别增加9.1%和11.3%。从各麦区来看,两种升温情景下春麦区降水增加幅度略大于冬麦区的增加幅度。所有麦区中只有新疆春麦区降水低于历史时段降水。春麦区降水增加幅度最大的麦区为北部春麦区。冬麦区中降水增加较大的麦区为北部冬麦区和黄淮冬麦区,降水增加较小的麦区为华南冬麦区和西南冬麦区。(3)两种升温情景下,我国小麦单产相对于历史时段(1986—2005年)平均减产分别为5.2%和4.6%,两种升温情景对中国小麦产量并没有显著的差异。在全球升温大背景下我国春小麦主要呈现增产趋势,冬小麦主要呈现减产趋势。减产幅度较大的麦区为华南冬麦区和青藏春麦区,增产幅度最大的麦区为西北春麦区。从各麦区产量减产面积比例上看,我国各麦区减产面积所占比例趋势为从北向南由多变少再变多,其中华南冬麦区减产面积所占比例最大,北部冬麦区最小。