青藏高原江河源区近40年来气候变化特征及其对区域环境的影响

以江河源区12个气象台站1971-2008年间的逐月气温、风速和降水资料为基础,对该区气候变化特征进行了分析,结果表明:近40年来,江河源区气候持续变暖,年均气温的增温率为0.37℃/(10 a),1987年和1998年气温由低向高突变;年均风速显著降低,每10 a降幅为0.24 m/s,1981年和1992年风速由高向低突变,年均风速与年均气温间呈负相关关系;1980年代降水偏多,1970和1990年代偏少,21世纪以来降水量有所回升,增幅因区域而异;年陆面蒸发量整体显著增加.结合前人研究,探讨了气候变化对环境的影响:持续升温导致江河源区内冰川退缩、多年冻土退化;1980年代气候相对暖湿,水资源量较丰;气候暖干化、水资源量减少、生态环境恶化是该区在1990年代和21世纪最初几年的显著特征;2004年左右以来,江河源区气候转湿,水资源量增加,生态环境有所好转.     

试论未来极端气候事件发展趋势的不确定性

极端气候事件是在一定时间尺度上发生的不同于气候系统平均状态的气候突变.早第三纪的最热事件（PETM）,第四纪中国黄土高原古土壤S4、S5记录的暖湿事件,砂黄土L9、L15记录的干冷事件等都是在轨道时间尺度上发生的极端气候事件.末次冰消期的YD冷事件、全新世9次冷事件是在千—百年尺度上发生的极端气候事件.这些极端气候事件出现于地球气候系统不同的冷暖背景下,它们的成因机制和表现形式有很多不确定性.20世纪以来发生的干旱、洪水、飓风、雪灾、沙尘暴等极端气候事件,无法用持续增加的温室气体的变化来解释.关于极端气候事件发生频率和强度随＂全球变暖＂而增加的结论也存在一定程度的不确定性.因此,简单地将现代极端气候事件统统归因于＂气候变暖＂既不科学也不合理.深入研究各个时间尺度上发生的极端气候事件的波动性、周期性和不确定性特征,有助于科学预测未来气候变化背景下极端气候事件的发展趋势.     

中国中世纪暖期气候变化的基本特征

对中世纪暖期（MWP）的时空分异和区域影响进行综合分析,关系到对近百年来全球气候变暖驱动力的正确认识,也有助于客观地解析20世纪气候变化增暖的历史地位.本研究对中国疆域内各个地区MWP的一些成果进行梳理和再思考,表明MWP在中国疆域内的存在是毋庸置疑的,但不同地区MWP表现出明显的时空差异.中国中东部地区在800—1300 AD存在明显温暖期,各种地质记录和文献记载都有较明显反映;虽然西北部MWP表现不很明显,但是众多石笋、湖泊沉积和风沙沉积也记录了500—1500 AD间呈现温暖湿润的气候特征;青藏高原各地MWP的表现差异明显,其中800—1100 AD暖期是高原东北部最暖的时期,而南部和西部最暖期分别出现于1150—1400 AD和1250—1500 AD.太阳辐射变化和火山活动可能是形成MWP的基本原因,而中国三大自然区下垫面条件的复杂多样性造成MWP发生过程和表现形式的时空分异.     

从沙尘暴变化趋势看全球气候变化

近年来人们对全球气候变化的问题尤为关注,因为,如今气候变化不仅仅是科学问题、环境问题,还是一个国际政治问题、经济问题,事关社会的长远发展.本研究以沙尘暴为切入点,在前人研究的基础上,总结了近年来沙尘暴及沙尘天气发生频率的变化趋势及其地域性差异,并进一步讨论了沙尘暴发生频率变化趋势与温度变化的响应机制,认为沙尘暴发生频率变化与气温变化呈负相关关系.近年来中国沙尘暴发生频率呈整体下降趋势,表明近年来中国气温有整体升高的趋势,这可能是全球变冷大趋势中的次级波动.     

中国不同区域能源消费碳足迹的时空变化(英文)

Study on regional carbon emission is one of the hot topics under the background of global climate change and low-carbon economic development, and also help to establish different low-carbon strategies for different regions. On the basis of energy consumption and land use data of different regions in China from 1999 to 2008, this paper established carbon emission and carbon footprint models based on total energy consumption, and calculated the amount of carbon emissions and carbon footprint in different regions of China from 1999 to 2008. The author also analyzed carbon emission density and per unit area carbon footprint for each region. Finally, advices for decreasing carbon footprint were put forward. The main conclusions are as follows: (1) Carbon emissions from total energy consumption increased 129% from 1999 to 2008 in China, but its spatial distribution pattern among different regions just slightly changed, the sorting of carbon emission amount was: Eastern China > Northern China > Central and Southern China > Southwest China > Northwest China. (2) The sorting of carbon emission density was: Eastern China > Northeast China > Central and Southern China > Northern China > Southwest China > Northwest China from 1999 to 2003, but from 2004 Central and Southern China began to have higher carbon emission density than Northeast China, the order of other regions did not change. (3) Carbon footprint increased significantly since the rapid increasing of carbon emissions and less increasing area of pro-ductive land in different regions of China from 1999 to 2008. Northern China had the largest carbon footprint, and Northwest China, Eastern China, Northern China, Central and Southern China followed in turn, while Southwest China presented the lowest area of carbon footprint and the highest percentage of carbon absorption. (4) Mainly influenced by regional land area, Northern China presented the highest per unit area carbon footprint and followed by Eastern China, and Northeast China; Central and Southern China, and Northwest China had a similar medium per unit area carbon footprint; Southwest China always had the lowest per unit area carbon footprint. (5) China faced great ecological pressure brought by carbon emission. Some measures should be taken both from reducing carbon emission and increasing carbon absorption.     

1961-2008年中国西南地区极端气候变化幅度的海拔效应(英文)

A total of 12 indices of temperature extremes and 11 indices of precipitation ex-tremes at 111 stations in southwestern China at altitudes of 285-4700 m were examined for the period 1961-2008. Significant correlations of temperature extremes and elevation in-cluded the trends of diurnal temperature range, frost days, ice days, cold night frequency and cold day frequency. Regional trends of growing season length, warm night frequency, coldest night and warmest night displayed a statistically significant positive correlation with altitude. These characteristics indicated the obvious warming with altitude. For precipitation extreme indices, only the trends of consecutive dry days, consecutive wet days, wet day precipitation and the number of heavy precipitation days had significant correlations with increasing alti-tude owing to the complex influence of atmospheric circulation. It also indicated the increased precipitation mainly at higher altitude areas, whereas the increase of extreme precipitation events mainly at lowers altitude. In addition, the clearly local influences are also crucial on climate extremes. The analysis revealed an enhanced sensitivity of climate extremes to ele-vation in southwestern China in the context of recent warming.     

Adaptation models of mountain glacier tourism to climate change: a case study of Mt. Yulong Snow scenic area

Mountain glaciers have an obvious location advantage and tourist market condition over polar and high latitude glaciers. Due to the enormous economic benefit and heritage value, some mountain glaciers will always receive higher attention from commercial media, government departments and mountain tourists in China and abroad. At present, more than 100 glaciers have been developed successfully as famous tourist destinations all over the world. However, global climate change seriously affects mountain glaciers and its surrounding environment. According to the current accelerated retreat trend, natural and cultural landscapes of some glaciers will be weakened, even disappear in the future. Climate change will also inevitably affect mountain ecosystems, and tourism routes under ice and glacier experience activities in these ecosystems. Simultaneously, the disappearance of mountain glaciers will also lead to a clear reduction of tourism and local economic benefits. Based on these reasons, this paper took Mt. Yulong Snow scenic area as an example and analyzed the retreat trend of a typical glacier. We then put forward some scientific and rational response mechanisms and adaptation models based on climate change in order to help future sustainable development of mountain glacier tourism.     

Validation of the effects of temperature simulated by multi-model ensemble and prediction of mean temperature changes for the next three decades in China

Using series of daily average temperature observations over the period of 1961–1999 of 701 meteorological stations in China, and simulated results of 20 global climate models (such as BCCR_BCM2.0, CGCM3T47) during the same period as the observation, we validate and analyze the simulated results of the models by using three factor statistical method, achieve the results of multi- model ensemble, test and verify the results of multi-model ensemble by using the observation data during the period of 1991–1999. Finally, we analyze changes of the annual mean temperature result of multi-mode ensemble prediction for the period of 2011–2040 under the emission scenarios A2, A1B and B1. Analyzed results show that: (1) Global climate models can reproduce Chinese regional spatial distribution of annual mean temperature, especially in low latitudes and eastern China. (2) With the factor of the trend of annual mean temperature changes in reference period, there is an obvious bias between the model and the observation. (3) Testing the result of multi-model ensemble during the period of 1991–1999, we can simulate the trend of temperature increase. Compared to observation, the result of different weighing multi-model ensemble prediction is better than the same weighing ensemble. (4) For the period of 2011–2040, the growth of the annual mean temperature in China, which results from multi-mode ensemble prediction, is above 1 °C. In the spatial distribution of annual mean temperature, under the emission scenarios of A2, A1B and B1, the trend of growth in South China region is the smallest, the increment is less than or equals to 0.8 °C; the trends in the northwestern region and south of the Qinghai-Tibet Plateau are the largest, the increment is more than 1 °C.     

Snow water equivalent over Eurasia in the next 50 years projected by aggregated CMIP3 models

Based on remote sensing snow water equivalent (SWE) data, the simulated SWE in 20C3M experiments from 14 models attending the third phase of the Coupled Models for Inter-comparison Project (CMIP3) was first evaluated by computing the different percentage, spatial correlation coefficient, and standard deviation of biases during 1979–2000. Then, the diagnosed ten models that performed better simulation in Eurasian SWE were aggregated by arithmetic mean to project the changes of Eurasian SWE in 2002–2060. Results show that SWE will decrease significantly for Eurasia as a whole in the next 50 years. Spatially, significant decreasing trends dominate Eurasia except for significant increase in the northeastern part. Seasonally, decreasing proportion will be greatest in summer indicating that snow cover in warmer seasons is more sensitive to climate warming. However, absolute decreasing trends are not the greatest in winter, but in spring. This is caused by the greater magnitude of negative trends, but smaller positive trends in spring than in winter. The changing characteristics of increasing in eastern Eurasia and decreasing in western Eurasia and over the Qinghai-Tibetan Plateau favor the viewpoint that there will be more rainfall in North China and less in the middle and lower reaches of the Yangtze River in summer. Additionally, the decreasing rate and extent with significant decreasing trends under SRES A2 are greater than those under SRES B1, indicating that the emission of greenhouse gases (GHG) will speed up the decreasing rate of snow cover both temporally and spatially. It is crucial to control the discharge of GHG emissions for mitigating the disappearance of snow cover over Eurasia.