全球平均气温未来情景的降尺度分析
Downscaling of Global Mean Annual Temperature under Different Scenairos
查看参考文献26篇
文摘
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如何提高全球气候模拟数据的分辨率,以满足全球、区域乃至局地陆地生态系统全球变化响应的定量分析,是当今全球气候变化研究的核心内容之一。在全球尺度上,本文利用全球气象观测站点的气候数据和DEM数据,对全球年平均气温与纬度和海拔高程之间相关性进行回归分析,建立全球气候降尺度空间模拟的统计转移函数,并与高精度曲面建模(HASM)方法进行集成,从而实现IPCC GCM HadCM3的模拟数据从3.75°×2.5°到0.125°×0.125°的降尺度处理。研究结果表明,在3种气候情景的T1-T4时段内,格陵兰岛平均气温在0℃以下的区域和南极洲平均气温在-35℃以下的区域均呈逐渐缩减趋势,赤道至南北回归线之间的平均气温大于40℃以上的区域呈逐渐增加趋势。其中,A1Fi情景的平均气温上升速度最快,A2情景次之,B2情景的平均气温上升速度最慢。构建降尺度方法有效地将IPCC GCMs的粗分辨率的气候情景数据降尺度转换成高分辨率的气候数据,并克服和弥补了目前IPCC GCMs的模拟数据因分辨率低而不能对区域乃至局地气候变化的细节及趋势进行刻画的缺陷。 |
其他语种文摘
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One of the key issues of global change research is how to improve the simulated data resolution of Global Climate Models(GCMs) for the quantitative analysis of terrestrial ecosystems in response to the climate change at global,regional and local levels.In this paper,the statistcial transfer funcitons are developed by establishing the regression analysis of relation between mean annual temperature and latitude and elevation with the digital elevation models and climate data from global meteorological stations aton global level.The High Accuracy Surface Modelling(HASM) method integrated the statistical transfer functions,is used to downscale the simulated data of HadCM3 from a spatial resolution of 3.75° × 2.5° to 0.125° × 0.125°.The simualted results of A1Fi,A2 and B2 scenarios show that the mean annual temperature would be increasing in the 21st century,the areas in Greenland where the mean annual temperature is below 0℃ and in Antarctica below-35℃ would shrink,and the areas between north and south tropics where the mean annual temperature is higher than 40℃ would expand.The increase rate under scenario A1Fi is the highest and that under scenario B2 is slowest among three scenarios during the period from T1 to T4.The results also show that the coarse resolution data of IPCC GCMs can be availably downscaled to high resolution data by integrating the statistcial transfer funcitons and HASM methods,which could overcome the limitation that the current simulated data resolution of IPCC GCMs can not be used to explain and describe the details of climate change at regional level,especially at local level. |
来源
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地理科学进展
,2012,31(3):267-274 【核心库】
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关键词
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全球平均气温
;
未来情景
;
降尺度
;
HASM方法
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地址
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1.
中国科学院地理科学与资源研究所, 资源与环境信息系统国家重点实验室, 北京, 100101
2.
山东科技大学测绘科学与工程学院, 青岛, 266510
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语种
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中文 |
文献类型
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研究性论文 |
ISSN
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1007-6301 |
学科
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大气科学(气象学) |
基金
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国家自然科学基金青年科学基金
;
国家自然科学基金国家杰出青年科学基金
;
国家973计划
;
资源与环境信息系统国家重点实验室青年人才培养基金
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文献收藏号
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CSCD:4491884
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参考文献 共
26
共2页
|
1.
Rosenrweig C. Potential impact of climate change on world food supply.
Nature,1994,367:133-138
|
CSCD被引
62
次
|
|
|
|
2.
Zhou G S. Global change and climate-vegetation classification.
Chinese Science Bulletin,2000,45(7):577-585
|
CSCD被引
14
次
|
|
|
|
3.
Wood Jr F B. The need for system research on global climate change.
System Research,1988,5(3):225-240
|
CSCD被引
1
次
|
|
|
|
4.
周广胜. 全球变化与气候-植被分类研究和展望.
科学通报,1999,44(24):2587-2593
|
CSCD被引
41
次
|
|
|
|
5.
Forster P M. Climate forcing and climate sensitivities diagnosed from coupled climate model integrations.
Journal of Climate,2006,19(23):6181-6194
|
CSCD被引
9
次
|
|
|
|
6.
Walsh J E. Global climate model performance over Alaska and Greenland.
Journal of Climate,2008,21(23):6156-6174
|
CSCD被引
8
次
|
|
|
|
7.
Koutsoyiannis D. On the credibility of climate predictions.
Hydrological Sciences,2008,53(4):671-684
|
CSCD被引
3
次
|
|
|
|
8.
许崇海. IPCC-AR4模式对东亚地区气候模拟能力的分析.
气候变化研究进展,2007,3(5):287-292
|
CSCD被引
71
次
|
|
|
|
9.
孙颖. IPCC-AR4气候模式对东亚夏季风年代际变化的模拟性能评估.
气象学报,2008,66(5):755-780
|
CSCD被引
2
次
|
|
|
|
10.
江志红. 7个IPCC AR4模式对中国地区极端降水指数模拟能力的评估及其未来情景预估.
大气科学,2009,33(1):109-120
|
CSCD被引
87
次
|
|
|
|
11.
顾问. IPCC-AR4全球气候模式在华东区域气候变化的预估能力评价与不确定性分析.
地理科学进展,2010,29(7):818-826
|
CSCD被引
8
次
|
|
|
|
12.
Xue Y K. Assessment of dynamic downscaling of the continental U.S. regional climate using the Eta/SSiB regional climate model.
Journal of Climate,2007,20(16):4172-4193
|
CSCD被引
9
次
|
|
|
|
13.
Akinyemi F O. A GIS-based procedure for downscaling climate data for west Africa.
Transactions in GIS,2008,12(5):613-631
|
CSCD被引
1
次
|
|
|
|
14.
Charles S P. Validation of downscaling models 384 for changed climate conditions: case study of southwestern Australia.
Climate Research,1999,385(12):1-14
|
CSCD被引
1
次
|
|
|
|
15.
Ashiq M W. GIS-based high-resolution spatial interpolation of precipitation in mountainplain areas of Upper Pakistan for regional climate change impact studies.
Theoretical and Applied Climatology,2010,99(3/4):239-253
|
CSCD被引
10
次
|
|
|
|
16.
Dickinson R E. A regional climate model for the western U.
S. Climatic Change,1989,15(3):383-422
|
CSCD被引
78
次
|
|
|
|
17.
Jones P D. Simulation of climate change over Europe using a nested regional-climate model, I: Assessment of control climate, including sensitivity to location of lateral boundaries.
Quarterly Journal of the Royal Meteorological Society,1995,121(526):1413-1449
|
CSCD被引
17
次
|
|
|
|
18.
Grotch S L. The use of general circulation models to predict regional climate change.
Journal of Climate,1991,4(3):286-303
|
CSCD被引
14
次
|
|
|
|
19.
Zorita E. The analog method as a simple statistical downscaling technique: comparison with more complicated methods.
Journal of Climate,1999,12:2474-2489
|
CSCD被引
31
次
|
|
|
|
20.
Brown B G. Regional analysis of temperature extremes: Spatial analog for climate change.
Journal of Climate,1995,8(1):108-119
|
CSCD被引
3
次
|
|
|
|
|