AR6气候变化情景下的未来降雨特征——以泰国pasak河流域为例

Ketvara Sittichok
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摘要

泰国位于东南亚,被认为极易受到气候变化的影响。这个国家很可能会成为遭受气候变化负面影响的国家之一。为了减少气候变化对干旱和洪水的影响,需要制定气候变化下的水资源管理计划。在气候变化排放情景下,未来降雨量的变化具有重要作用,需要进一步研究。本研究旨在描述AR6气候变化情景下的预估降雨特征。在Pasak河流域,使用分位数映射方法将10个gcm产生的降雨量降至流域尺度。与采用Nash-Sutcliff系数和体积误差方法的观测数据相比,降尺度过程后模拟的降水在量级和体积上都有显著提高。使用确定系数,发现缩小尺度和观测降水之间的细微差异具有可接受的结果。分析了SSP1-2.6、SSP24.5、SSP3-7.0和SSP5-8.5 4种模式下未来降水的变率。各模式预测的年平均降雨量略有不同,但与其他模式相比,在INM-CM5中可以发现较大的变化。然后计算了历史和未来两个时期(近期(2015-2050)和长期(2051-2100)的标准化异常指数,并给出了干湿事件的频率。在SSP2-4.5和SSP1-2.6条件下,2051-2100年分别出现极湿年和极干年。最后,SSP2-4.5、SSP3-7.0和SSP5-8.5短期和所有长期情景的年降雨量均明显增加。在SSP1-2.6下,仅近期有轻微下降趋势。
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Future rainfall characteristics under AR6 climate change scenarios, case study of pasak river basin, Thailand
Thailand is located in Southeast Asia where it is indicated as highly vulnerable to climate change. This country will likely be one of the countries that have experienced negative impacts of climate change. To reduce the impact of climate change on drought and flood, a water management plan under climate change needs to be prepared. The changes of future rainfalls under climate change emission scenarios play an important role and need to be investigated. This study aims to describe projected rainfall characteristics under AR6 climate change scenarios. Rainfalls generated from 10 GCMs were downscaled to a basin scale at the Pasak River Basin using the quantile mapping method. After the downscaling process simulated precipitation significantly improved in both magnitude and volume compared to the observed data using the Nash-Sutcliff coefficient and volume error methods. Slight differences between downscaled and observed precipitation were found with acceptable results using the coefficient of determination. Variabilities of future precipitation under four scenarios (SSP1-2.6, SSP24.5, SSP3-7.0 and SSP5-8.5) of each model were revealed. Annual average of projected rainfalls was slightly different between the models, but large variation compared to others could be found in INM-CM5. The standardized anomaly index was then calculated for historical and two future periods: the near-term (2015-2050) and the long-term (2051-2100), and the frequencies of wet and dry incidents were presented. Very-extremely wet and dry years often occurred in 2051-2100 under SSP2-4.5 and SSP1-2.6 respectively. Finally, the increments in annual rainfalls were obviously seen in SSP2-4.5, SSP3-7.0 and SSP5-8.5 for the near-term and in all scenarios of the long-term. Slight decreasing trend was only found in the near-term under SSP1-2.6.
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