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Climate change scenarios of surface solar radiation in data sparse regions: a case study in Malaprabha River Basin, India

机译:数据稀疏地区地表太阳辐射的气候变化情景:以印度马拉帕布哈河流域为例

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摘要

A variety of methods are available to estimate future solar radiation (SR) scenarios at spatial scales that are appropriate for local climate change impact assessment. However, there are no clear guidelines available in the literature to decide which methodologies are most suitable for different applications. Three methodologies to guide the estimation of SR are discussed in this study, namely: Case 1: SR is measured, Case 2: SR is measured but sparse and Case 3: SR is not measured. In Case 1, future SR scenarios are derived using several downscaling methodologies that transfer the simulated large-scale information of global climate models to a local scale (measurements). In Case 2, the SR was first estimated at the local scale for a longer time period using sparse measured records, and then future scenarios were derived using several downscaling methodologies. In Case 3: the SR was first estimated at a regional scale for a longer time period using complete or sparse measured records of SR from which SR at the local scale was estimated. Finally, the future scenarios were derived using several downscaling methodologies. The lack of observed SR data, especially in developing countries, has hindered various climate change impact studies. Hence, this was further elaborated by applying the Case 3 methodology to a semi-arid Malaprabha reservoir catchment in southern India. A support vector machine was used in downscaling SR. Future monthly scenarios of SR were estimated from simulations of third-generation Canadian General Circulation Model (CGCM3) for various SRES emission scenarios (A1B, A2, B1, and COMMIT). Results indicated a projected decrease of 0.4 to 12.2 W m-2 yr-1 in SR during the period 2001-2100 across the 4 scenarios. SR was calculated using the modified Hargreaves method. The decreasing trends for the future were in agreement with the simulations of SR from the CGCM3 model directly obtained for the 4 scenarios.
机译:有多种方法可以在适合本地气候变化影响评估的空间尺度上估算未来的太阳辐射(SR)情景。但是,文献中没有明确的指南来确定哪种方法最适合不同的应用。本研究讨论了三种指导SR估算的方法,即:情况1:测量了SR,情况2:测量了SR但稀疏,而情况3:未测量到SR。在案例1中,未来的SR情景是使用几种缩减规模的方法得出的,这些方法将全球气候模型的模拟大规模信息转移到了局部规模(测量值)。在案例2中,首先使用稀疏的测量记录在较长的时间范围内在本地范围内估计SR,然后使用几种缩减规模的方法来得出将来的方案。在情况3中:首先使用完整或稀疏的SR记录在较长的时间范围内在区域范围内估算SR,并据此估算本地规模的SR。最后,使用几种缩减规模的方法来得出未来的情况。缺乏观测到的SR数据,特别是在发展中国家,阻碍了各种气候变化影响研究。因此,通过将案例3的方法应用于印度南部的半干旱Malaprabha水库集水区来进一步阐述这一点。支持向量机用于缩小SR。 SR的未来月度情景是根据第三代加拿大一般环流模型(CGCM3)针对各种SRES排放情景(A1B,A2,B1和COMMIT)的估计而估算的。结果表明,在这4种情景中,在2001-2100年期间,SR预计将下降0.4至12.2 W m-2 yr-1。 SR是使用改良的Hargreaves方法计算的。未来的下降趋势与从这4种情况直接获得的CGCM3模型进行的SR模拟相一致。

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