Climate projections for southern Africa using complementary methods

被引:7
|
作者
Lutz, Julia [1 ]
Volkholz, Jan [1 ]
Gerstengarbe, Friedrich-Wilhelm [1 ]
机构
[1] Potsdam Inst Climate Impact Res PIK, Climate Impacts & Vulnerabil Res Domain 2, Potsdam, Germany
关键词
Southern Africa; Climate projection; Statistical downscaling; Dynamical downscaling; STARS; CCLM; Africa; Climate change; Climatology; PERFORMANCE; VARIABILITY; SIMULATIONS; ADAPTATION;
D O I
10.1108/17568691311327550
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Purpose - The Orange River is one of the largest river basins in southern Africa. Since it plays a crucial role in the region's ecology and economy, it is important to estimate future developments in its hydrology. A necessary means to this end are climate projections. This paper seeks to address this issue. Design/methodology/approach - In this work the authors present projections obtained by two complementary methods; they use a Statistical Analogue Re-sampling Scheme (STARS) and a dynamical regional climate model (CCLM - COSMO in Climate Mode). In order to determine the viability of these methods, the authors perform cross-validations for the years 1976-2000. Findings - CCLM shows good performance regarding the 2m temperature but the reproduction of precipitation is rather poor. STARS, on the other hand, produces very good results for both variables. The climate projections of both models show a considerable temperature increase for the future (2036-2060, SRES A1B scenario), especially in the inland of the simulation area. However, while CCLM projects a general decrease in precipitation, STARS indicates a strong precipitation decrease in the already dry western part of the region and a moderate decrease resp. no change in the east during the rain season. Originality/value - For the first time the statistical approach used gridded data as its input. Therefore, it was possible to apply complementary methods in order to generate the climate projections and to compare them.
引用
收藏
页码:130 / 151
页数:22
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