北京地区干旱预测不确定性来源贡献度量化  

Quantification of multi-source uncertainty contribution in drought prediction across Beijing area

作　　者：李占玲 霍鹏颖 叶瀛韬 谢成 LI Zhanling;HUO Pengying;YE Yingtao;XIE Cheng(Key Laboratory of Groundwater Conservation of Ministry of Water Resources(in preparation),China University of Geosciences(Beijing),Beijing 100083,China)

机构地区：[1]中国地质大学(北京)水利部地下水保护重点实验室(筹),北京100083

出　　处：《水科学进展》2024年第5期794-804,共11页Advances in Water Science

基　　金：国家自然科学基金资助项目(41101038);水灾害防御全国重点实验室“一带一路”水与可持续发展科技基金资助项目(2021nkms03)。

摘　　要：受多种因素影响,干旱预测往往存在很大的不确定性。对不同来源不确定性贡献度进行量化有助于识别关键不确定性来源,为提高干旱预测和风险评估精度提供依据。本文以北京地区气象干旱为研究对象,采用多因素方差分析法对全球气候模式(Global Climate Model,GCM)、排放情景、干旱指数对北京地区干旱特征变量(历时、峰值和烈度)预测的不确定性贡献度进行量化,通过系统抽样和导函数分析法探讨GCM不确定性被合理估计时的最少模式数量。结果表明:GCM及排放情景与GCM交互作用对该地区平均及最大干旱特征变量预测的不确定性贡献度最大;最大不确定性来源并未具有明显的时空差异性;当GCM少于7个时,其引发的研究区干旱特征变量不确定性被低估。Drought prediction is often fraught with significant uncertainties due to various factors.It is crucial to identify the key contribution source of uncertainty,and therefore enhancing the reliability of drought prediction and risk assessment.This study focuses on Beijing as a case study,employing multivariate analysis of variance(MVANOVA)to assess the contributions of uncertainties from three primary sources:Global Climate Models(GCMs),Shared Socioeconomic Pathway(SSP)scenarios,and drought indices.These factors were analyzed to predict meteorological drought characteristics such as duration,peak,and intensity,while also examining their spatiotemporal variations.Additionally,the minimum number of GCMs was explored by using the systematic sampling and derivative function methods to ensure the uncertainty triggered by GCMs reasonably estimated.The results indicated that,GCMs,and the interactions between SSPs and GCMs,are the two most significant sources of uncertainty affecting drought characteristic prediction in Beijing area.The main sources of uncertainty remain consistent across spatial and temporal scales.Furthermore,when the number of GCMs is less than seven,the uncertainty caused by the GCMs may be underestimated in Beijing area.These findings underscore the importance of reducing GCM-related uncertainties for reliable drought predictions and highlight the need to account for the interactions among factors in uncertainty research.

关 键 词：干旱预测 不确定性 多因素方差分析 全球气候模式 贡献度 北京 

分 类 号：P429[天文地球—大气科学及气象学]