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Long-Term Rainfall Trends and Future Projections over Xijiang River Basin, China

机译:中国西江盆地的长期降雨趋势和未来预测

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Precipitation trend detection is vital for water resources development and decision support systems. This study predicts the climate change impacts on long-term precipitation trends. It deals with the analysis of observed historical (1960–2010) and arithmetic mean method in assembling precipitation from CMIP5 Global Climate Models (GCMs) datasets for a future period (2020–2099) under four emission scenarios. Daily precipitation data of 32 weather stations in the Xijiang River Basin were provided by National Meteorological Information Centre (NMIC) of the China Meteorological Administration (CMA) and Global Climate Models (GCMs) with all four emission scenarios statistically downscaled using Bias Correction Special Disaggregation (BCSD) and applied for bias correction via Climate Change Toolkit (CCT). Nonparametric Mann–Kendall test was applied for statistical significance trend analysis while the magnitude of the trends was determined by nonparametric Sen’s estimator method on a monthly scale to detect monotonic trends in annual and seasonal precipitation time series. The results showed a declined trend was observed for the past 50 years over the basin with negative values of MK test (Z) and Sen’s slope Q. Historical GCMs precipitation detected decreasing trends except for NoerESM1-M which observed slightly increasing trends. The results are further validated by historical precipitation recorded by the Climate Research Unit (CRU-TS-3.1). The future scenarios will likely be positive trends for annual rainfall. Significant positive trends were observed in monsoon and winter seasons while premonsoon and postmonsoon seasons will likely be slightly downward trends. The 2040s will likely observe the lowest increase of 6.6% while the 2050s will observe the highest increase of 11.5% over the 21st century under future scenarios. However, due to the uncertainties in CMIP5, the future precipitation projections should be interpreted with caution. Thus, it could be concluded that the trend of change in precipitation around the Xijiang River Basin is on the increase under future scenarios. The results can be valuable to water resources and agriculture management policies, as well as the approach for managing floods and droughts under the perspective of global climate change.
机译:降水趋势检测对于水资源开发和决策支持系统至关重要。本研究预测了气候变化对长期降水趋势的影响。它涉及观察到的历史(1960-2010)和算术平均法在四个发射方案下组装CMIP5全球气候模型(GCMS)数据集的算术平均法。 xijiang河流域32个气象站的日降水数据由中国气象管理(CMA)和全球气候模型(GCMS)提供的全球气候信息中心(GCMS)提供,所有四种发射情景都使用偏压校正特殊分类( BCSD)并通过气候变化工具包(CCT)应用于偏置校正。非参数Mann-Kendall测试用于统计显着性趋势分析,同时趋势的幅度由非参议鉴定的估计方法确定每月规模,以检测年度和季节降水时间序列的单调趋势。结果表明,在盆地过去50岁上观察到趋势下降,具有MK试验(Z)和森坡Q.历史GCMS降水量检测到趋势降低,除了Noeresm1-M,观察到略微增加趋势。通过气候研究单位(CRU-TS-3.1)记录的历史降水进一步验证了结果。未来的情景可能是年降雨量的积极趋势。在季风和冬季观察到显着的积极趋势,而前瞻性和德隆森季节可能会略微下行趋势。 2040年代可能会观察到最低增加6.6%,而2050年代将在未来的情况下观察21世纪的最高增加11.5%。但是,由于CMIP5中的不确定性,应谨慎地解释未来的降水预测。因此,可以得出结论,西江盆地沉淀变化的趋势正在减少未来的情景。结果对水资源和农业管理政策有价值,以及在全球气候变化的角度下管理洪水和干旱的方法。

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