AGS-PRF: Assessing Causes of the Divergence between Past and Projected Responses of Global Aridity to Greenhouse Warming

这一奖项为国际和平研究所提供了为期两年的博士后研究奖学金，他们将在哥伦比亚大学理查德·西格教授的指导下工作。该项目的目标是调和全球变暖导致的水文气候预期变化与过去气候的古气候替代数据之间的明显差异。全球变暖模拟通常表明，随着气温上升，大陆上的水将变得更加稀缺，这是因为蒸发需求的增加超过了降雨量的增加。但如果干燥伴随着变暖，那么同样的逻辑将表明，更冷的气候，包括冰河时代的气候，应该更潮湿。这一论点显然与地质证据相矛盾，地质证据表明，冰河时代实际上比今天的气候更干燥。此外，有证据表明，尽管气温较高，但早新生代(约5500万年前)的温暖气候比今天的世界更潮湿。为了解决这种差异，人们寻求了三种研究方法，第一种方法是仔细检查参与耦合模式相互比较项目5(CMIP5)的气候模型的现代气候模拟。前提是，这些模型在气候变化模拟中产生的干燥可能与当前模拟中的偏差有关，因此，如果模型在控制模拟中始终偏向干燥，则可能高估未来的干燥。第二项活动是对最后一次冰川盛期(LGM，大约在2万至25000年前)进行模式模拟，对大陆水气候进行诊断性检查，该模式取自古气候模式国际比较项目第三版(PMIP3)。虽然已经在未来的气候模拟中详细研究了降水和潜在蒸散量的变化，但还没有对LGM模拟进行可比的诊断。第三是重新检查古替代记录，以确保LGM干燥的证据没有被误解。这些证据大部分是基于植被，植被可能是对二氧化碳(CO2)值降低和二氧化碳施肥量减少做出反应，而不是对可用水的减少做出反应。PI建议通过查看与植被无关的替代数据来解决这种可能性，例如湖泊水位和蒸发岩沉积。如果非植被指标没有显示出与基于植被的指标(花粉、化石、碳同位素比率)相同的干旱信号，二氧化碳施肥的作用似乎是可能的。由于缺水对人类福祉和自然生态系统的深远影响，这项工作具有内在的更广泛的影响。这项工作具体解决了气候变化可能导致水资源短缺的问题，以及基于气候模型模拟我们能在多大程度上预测这种短缺的问题。此外，在一位知名科学家的指导下，博士后研究奖学金将有助于推动国际和平研究所的事业，从而为这一科学学科未来的工作人员提供支持。

This award provides funds for a 2-year Postdoctoral Research Fellowship for the PI, who will work under the mentorship of Professor Richard Seager at Columbia University. The goal of the project is to reconcile an apparent discrepancy between expected changes in hydroclimate due to global warming with paleoclimate proxy data from past climates. Global warming simulations typically suggest that water will become more scarce over the continents as temperatures rise, due to increases in evaporative demand that outpace increases in precipitation. But if drying accompanies warming then the same logic would suggest that colder climates, including ice age climates, should be wetter. This argument is apparently in conflict with the geological evidence, which suggests that the ice ages were in fact dryer than today's climate. Moreover, there is evidence that the warm climate of the early Cenozoic (about 55 million years ago) was wetter than today's world despite the higher temperatures.Three avenues of research are pursued to address this discrepancy, the first of which is a careful examination of modern-day climate simulations from climate models participating in the Coupled Model Intercomparison Project version 5 (CMIP5). The premise is that the drying produced in climate change simulations from these models could be associated with biases in the present-day simulations, thus models may overestimate future drying if they are consistently biased dry in their control simulations. The second activity is a diagnostic examination of continental hydroclimate in model simulations of the last glacial maximum (LGM, roughly 20 to 25 thousand years ago), taken from the Paleoclimate Model Intercomparison Project version 3 (PMIP3). While changes in precipitation and potential evapotranspiration have been examined in detail for future climate simulations, comparable diagnoses have not been performed for LGM simulations.The third is a reexamination of the paleo-proxy record to make sure that the evidence for LGM drying has not been misinterpreted. Much of this evidence is based on vegetation, and it is possible that the vegetation is responding to lower values of carbon dioxide (CO2) and a reduction in CO2 fertilization, rather than a reduction in available water. The PI proposes to address this possibility by looking at proxy data which is not related to vegetation, for example lake levels and evaporite deposits. If the non-vegetation proxies do not show the same aridity signal found in vegetation-based proxies (pollen, fossils, carbon isotope ratios), a role for CO2 fertilization would seem likely.The work has inherent broader impacts due to the profound consequences of water shortages for human well-being and natural ecosystems. The work specifically addresses the potential for climate change to produce water shortages and the question of how well we can anticipate such shortages based on climate model simulations. In addition, the postdoctoral research fellowship, under the mentorship of an established scientist, will help to build the career of the PI, thereby providing support for the future workforce in this scientific discipline.