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Meteorological trends over Satluj River Basin in Indian Himalaya under climate change scenarios

机译:气候变化情景下印度喜马拉雅省Satluj River盆地的气象趋势

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Temperature and precipitation distributions depend on variable topography and heterogeneous landuse/landcover in the Indian Himalayan Region (IHR). It imparts a major concern for hydrological, glaciological modelling, dam structure assessment, etc. Thus, there is an inherent requirement of robust information for climate impact studies over the topographical variable and landuse heterogenous region in the Indian Himalayan Region (IHR). In particular, the importance of bias corrections become critically important over Himalayan river basins, in which model outputs with the corresponding in-situ observations are used for improving the model distribution. These improved details in present and future, as well, are important to carry out the climate change impact studies at basin scale for hydrological, glaciological, climatological studies, etc. Thus, in the present study firstly, model fields are bias corrected with the corresponding in-situ observations. And then trends in these bias corrected data is compared with the corresponding in-situ observations. These assessment of present and future changes in temperature and precipitation over Satluj River Basin (SRB) located in the western Himalayas is illustrated. Model fields are considered from a Regional climate model (REMO) from Coordinated Regional Downscaling Experiment-South Asia (CORDEX-SA) in three Representative Concentration Pathways (RCPs), i.e., 2.6, 4.5 and 8.5 W/m$^{2}$. These projections are bias corrected using distributed quantile mapping. The precipitation (temperature) bias correction is performed using the distributed quantile mapping on the gamma (normal) distribution. The standard trend statistics is applied for quantitative assessment. A good capture of bias correction in temperature and precipitation is illustrated. Efficient bias removal is depicted in cumulative distribution curve (CDF) at individual station. Trend analysis shows that highest rate of precipitation decrement at low altitude station (Kasol) with the rate of $a??$6.362 mm/year in RCP 8.5. Over the SRB highest rate of temperature increment is seen at highest altitude station (Kaza) with the rate of 0.084$^{circ}$C/year in RCP 8.5. On an average, fall in precipitation and increase in temperature with 99% confidence level in RCP 8.5 is seen. In addition, intensity lowers in other lower RCPs. The study sums up with the efficacy of CORDEX-SA REMO model in capturing present and future change in temperature and precipitation over the SRB in western Himalayas using the bias correction.
机译:温度和降水分布依赖于印度喜马拉雅地区(IHR)的可变地形和异质土地用地/土地层。它赋予水文,冰川造型建模,大坝结构评估等重大担忧。因此,对印度喜马拉雅地区(IHR)的地形变量和土地使用异构区的气候影响研究有一个固有的鲁棒信息。特别是,偏差校正的重要性在喜马拉雅河流域方面变得严重重要,其中使用相应的原位观察的模型输出用于改善模型分布。这些改进的细节以及未来的细节,也很重要,以便在盆地进行水文,冰川疾病,气候学研究等中进行气候变化影响研究。因此,在本研究中,模型字段与相应的偏差校正原位观察。然后将这些偏置数据的趋势与对应的原位观察进行比较。阐述了位于喜马拉雅西部的Satluj River盆地(SRB)的现状和未来温度和降水变化的评估。来自三个代表性浓度途径(RCP),即2.6,4.5和8.5 W / M $ ^ {2} $的区域气候模型(Cordex-SA)的区域气候模型(REMO)考虑了来自区域气候模型(REMO)。 。这些投影是使用分布式分位数映射校正的偏差。使用伽马(普通)分布上的分布式定位映射来执行沉淀(温度)偏压校正。标准趋势统计应用于定量评估。说明了温度和沉淀在温度和沉淀中的良好捕获。在单个站的累积分布曲线(CDF)中描绘了有效的偏差去除。趋势分析表明,低空站(卡苏尔)的最高降水递减率,速度为$ a -? $ 6.362 mm /年/年。在最高的高度站(卡扎),在最高高度站(卡扎)中看到了SRB的最高速率,其RCP 8.5中的0.084美元^ { circ} $ c /年。在平均,沉淀下降并增加了RCP 8.5中的置位水平> 99%的置信水平。此外,强度在其他下RCP中降低。该研究总结了Cordex-SA Remo模型在使用偏置校正中捕获Himalayas的SRB温度和降水的温度和降水变化的功效。

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