Modeling Anthropogenic Desiccation of the Aral Sea: A Unique Test of the Predictive Capabilities of a Regional Earth System Model

模拟咸海的人为干燥：对区域地球系统模型预测能力的独特测试

• 批准号: 9632304
• 负责人: Lisa Sloan
• 金额: $ 17.49万
• 依托单位: University of California-Santa Cruz
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-09-01 至 2000-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9632304&HistoricalAwards=false
• 关键词: Modeling; Anthropogenic; Desiccation; Aral; Sea

Abstract ATM-9632304 Sloan, Lisa C. University of California, Santa Cruz Title: Modeling Anthropogenic Desiccation of the Aral Sea: A Unique Test of the Predictive Capabilities of a Regional Earth System Model The utility of global and regional earth system models (ESMs) for investigating causes of past climate change, and predicting impacts of future human activities, depends on how accurately changes driven by specific perturbations are predicted. This accuracy is controlled primarily by how well feedbacks are simulated. The accuracy of ESM-predicted changes is unknown, because previous model validation has been limited to assessing how well present conditions are reproduced or comparing paleoclimate model results with sparse and potentially ambiguous proxy data. In order to conduct a more thorough evaluation of ESM performance, model- predicted and observed changes resulting from known perturbations over historical timescales will be compared. In this study, anthropogenic desiccation of the Aral Sea will be used as a test of the predictive accuracy of a regional ESM (the RegCM2 and lake model associated with the National Center for Atmospheric Research) that includes an interactively coupled atmosphere and lake. Desiccation of the Aral Sea since 1960, resulting from diversion of water for intensive irrigation in the surrounding basin, has been extensive enough to produce a regional climatic response. Desiccation of this magnitude should also produce a model response. Importantly. meteorological and hydrologic observations that span the interval of desiccation are available so the actual changes can be quantified. The predictive capabilities of the model will be tested by comparing model-simulated changes with observed changes that have occurred between 1960 and 1995. The work consists of three components. First, observations will be used to quantify regional climate and lake hydrologic changes that are likely due to Aral Sea desiccation. These obser ved changes will be used to (i) test model predictions, (ii) directly measure how the presence of the Aral Sea alters regional climate, (iii) directly measure how lake-level variations have impacted the Aral Sea's hydrology, and (iv) quantify regional-scale human impacts. Second, the interactively coupled Reg CM2-lake model's strengths and weaknesses in predicting changes will be assessed, by comparing simulated and observed desiccation-induced regional climate and lake hydrologic changes. In order to gain a more thorough understanding of the causes for the coupled model's successes and failures, the predictive accuracy of independent (non-interactive) versions of RegCM2 and the lake model, driven by meteorological or hydrologic observations, will also be evaluated. Third, the regional climate effects generated by the Aral for seas of different surface area, depth and salinity will be calculated. This will allow: (i) quantification of lake-atmosphere interactions and feedbacks associated with lake-level variations; (ii) prediction of future climate changes driven by further anthropogenic Arals Sea desiccation; and (iii) assessment of how much of the model predicted change between pre- desiccation and -present and present intervals was due to large-scale meteorological variability. Predictions of future climate changes resulting from additional desiccation will be prepared and evaluated in terms of the model's strengths and weaknesses as determined. This research is important because it seeks to test how well coupled regional climate lake models predict the impact of human activities on a large shallow terminal lake and how that feedbacks on the regional and global climate.

摘要 ATM-9632304斯隆，丽莎C。 加州大学，圣克鲁斯题目：模拟咸海人为干燥：区域地球系统模型预测能力的独特测试 全球和区域地球系统模式（ESM）在调查过去气候变化的原因和预测未来人类活动的影响方面的效用取决于对特定扰动驱动的变化的预测准确程度。 这种准确性主要取决于反馈的模拟程度。 ESM预测的变化的准确性是未知的，因为以前的模型验证已被限制在评估如何以及目前的条件是复制或比较古气候模型结果与稀疏和潜在的模糊代理数据。 为了对无害环境管理的绩效进行更全面的评估，将对历史时间尺度上已知扰动导致的模型预测和观察到的变化进行比较。 在这项研究中，咸海的人为干化将被用来测试区域ESM（RegCM 2和湖泊模型与国家大气研究中心），其中包括一个相互耦合的大气和湖泊的预测精度。自1960年以来，由于将水转移到周围盆地进行密集灌溉，咸海干涸的范围之广足以产生区域气候反应。 这种程度的干燥也应该产生模型响应。 重要的是。可利用跨越干旱期间的气象和水文观测数据，从而可以量化实际变化。 将通过将模型模拟的变化与1960年至1995年期间观察到的变化进行比较，检验模型的预测能力。 这项工作包括三个部分。 首先，观测将用于量化区域气候和湖泊水文变化，可能是由于咸海干燥。 这些观测到的变化将用于（i）测试模型预测，（ii）直接测量咸海的存在如何改变区域气候，（iii）直接测量湖泊水位变化如何影响咸海的水文，以及（iv）量化区域规模的人类影响。 其次，交互耦合Reg CM 2湖模型的优势和劣势，预测变化将进行评估，通过比较模拟和观测到的干燥引起的区域气候和湖泊水文变化。 为了更深入地了解耦合模型成功和失败的原因，还将评估由气象或水文观测驱动的RegCM 2和湖泊模型的独立（非交互）版本的预测准确性。 第三，将计算咸海对不同表面积、深度和盐度的海洋产生的区域气候影响。 这将允许：（i）量化湖泊-大气相互作用和与湖泊水位变化相关的反馈;（ii）预测未来由咸海进一步人为干化驱动的气候变化;（iii）评估模型预测的干化前和干化后以及干化前和干化后之间的变化有多少是由于大尺度气象变率造成的。 将根据所确定的模式的优点和缺点，编制和评价关于进一步干燥所造成的未来气候变化的预测。 这项研究很重要，因为它试图测试耦合良好的区域气候湖泊模型如何预测人类活动对大型浅水终端湖泊的影响，以及如何反馈区域和全球气候。