Projected temperature and precipitation changes using the LARS-WG statistical downscaling model in the Shire River Basin, Malawi,International Journal of Climatology

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Projected temperature and precipitation changes using the LARS-WG statistical downscaling model in the Shire River Basin, Malawi
International Journal of Climatology ( IF 3.5 ) Pub Date : 2021-06-10 , DOI: 10.1002/joc.7250
Sheila Kavwenje ₁ , Lin Zhao _{1,

2} , Liang Chen _{2,

3} , Evance Chaima _{2,

3}

Affiliation

This study analyzes local-scale temperature and precipitation projections in the Shire River Basin (SRB) in Malawi using 10 global circulation models (GCMs) available in the coupled model intercomparison project phase 5 (CMIP5), under two representative concentration pathways (RCP 4.5 and RCP 8.5). For nine stations in the study area, large-scale maximum temperature (Tmax), minimum temperature (Tmin) and precipitation data from the selected GCMs were downscaled by the sixth version of the Long Ashton Research Station Weather Generator (LARS-WG6). The mean seasonal and annual change projections for Tmax, Tmin and precipitation during two future periods, that is, the middle future (2041–2070) and late future (2071–2100) periods were analyzed. Modelling results demonstrated that the LARS-WG model is capable of simulating temperature more accurately than precipitation in the SRB. All 10 GCMs revealed that continually rising temperatures are anticipated in the study area; however, the projected magnitude of change varied across GCMs and between RCPs. Generally, the increase in average Tmax and Tmin was observed to be higher under RCP 8.5 compared with RCP 4.5 due to unmitigated greenhouse gas emissions (GHGs). Future precipitation change results showed more complexity and uncertainty than for temperature; not all GCMs agree on whether there will be positive or negative changes in precipitation and no systematic variations under RCP4.5 and RCP8.5 were observed during the two future time period, illustrating that both GCMs and RCPs are important sources of the relatively large uncertainties in future precipitation projections in the SRB. Thus, this study indicated that uncertainties constrained by both GCMs and RCPs are crucial and need to always be considered when executing climate impact studies and adaptation, particularly at river basin level.

中文翻译：

使用 LARS-WG 统计降尺度模型预测马拉维 Shire 河流域的温度和降水变化

本研究使用耦合模型比对项目第 5 阶段 (CMIP5) 中可用的 10 个全球环流模型 (GCM) 分析马拉维 Shire 河流域 (SRB) 的局部尺度温度和降水预测，在两个代表性浓度路径下 (RCP 4.5 和RCP 8.5)。对于研究区的 9 个站，来自选定 GCM 的大尺度最高温度 (Tmax)、最低温度 (Tmin) 和降水数据通过朗阿斯顿研究站天气发生器 (LARS-WG6) 的第六版进行了缩减。分析了两个未来时期，即未来中期（2041-2070）和未来后期（2071-2100）期间Tmax、Tmin和降水的平均季节和年度变化预测。建模结果表明，LARS-WG 模型能够比 SRB 中的降水更准确地模拟温度。所有 10 个 GCM 都显示，预计研究区域的温度将持续上升；然而，预计的变化幅度在 GCM 和 RCP 之间是不同的。一般来说，在 RCP 8.5 下观察到平均 Tmax 和 Tmin 的增加高于 RCP 4.5，这是由于温室气体排放 (GHG) 未减缓。未来降水变化结果显示出比温度更复杂和不确定的结果；并非所有 GCM 都同意降水是否会发生正面或负面变化，并且在未来两个时间段内未观察到 RCP4.5 和 RCP8.5 下的系统变化，说明 GCM 和 RCP 都是 SRB 未来降水预测中相对较大不确定性的重要来源。因此，本研究表明，受 GCM 和 RCP 约束的不确定性至关重要，在执行气候影响研究和适应时需要始终考虑，特别是在流域层面。

更新日期：2021-06-10

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