SGER: Seasonal Cycle of Drought in Coupled Climate Models and its Implication for the Hydro-ecosystem

这是气候变化和可预测性（CLIVAR）计划试点项目DRICOMP下的一笔赠款，用于耦合模型项目中的干旱，本研究的重点是对全球气候模式输出的干旱机制进行初步探讨，并试图评估这些模式在模拟干旱方面的可靠性。如果能揭示其季节性周期，就能更好地理解它。 例如，发生在旱季的干旱比发生在雨季的影响更大。 研究人员将在新推出的耦合模型相互比较项目3（CMIP 3）模型中探索降水变化的季节性周期，超越对总降水变化的典型分析。 将对20世纪世纪控制气候模拟进行分析，并与观测结果进行比较，以初步评估其季节周期和年度平均值的真实性。 在此过程中，将制定一个可能有助于评估预测气候变化的区域标准。 然后，从所有存档的模式将分析从20世纪世纪到未来的降水变化。 将强调其季节性周期，特别是旱季行为，并将按季节对具有更强信号的区域进行分类，从而初步了解未来干旱的可能性和机制。 重点将放在三个区域：密西西比盆地、萨赫勒和亚马逊，这三个区域代表三种不同的气候状况，具有重大的经济和环境意义。预测未来的降水量，温度，土壤湿度和其他相关变量的变化，从代表CMIP 3模式将被用来驱动耦合陆面和动态植被模型，VEGAS。 因此，将评估生态系统和水循环对季节循环中不同特征变化的敏感性。 模拟的土壤湿度和植被状况将与传统的干旱指数，如降水异常，帕尔默干旱指数（PDSI）和标准化降水指数（SPI）进行比较。 这些分析可能有助于回答一个重要问题，即传统的干旱指数在多大程度上足以描述和预测水文生态系统的未来变化。这些研究的更广泛影响在于它有助于评估气候变暖时的干旱风险。 该项目将涉及一名研究生，并将为她/他提供一个月的支持。

This is a grant under a Climate Variability and Predictability (CLIVAR) Program pilot project called DRICOMP, for the Drought in Coupled Models Project, which focuses on making initial explorations into the mechanisms of drought as they are represented in the output of global climate models and on attempting to assess the reliability of these models in simulating drought.This research explores implications of the hypothesis that the severity of drought is better understood if its seasonal cycle is revealed. For example, the impact of a drought is greater when it occurs during the dry season than during the wet season. The investigators will explore the seasonal cycles of precipitation changes in the newly available Coupled Model Intercomparison Project 3 (CMIP3) models, going beyond the typical analysis of total precipitation change. The 20th century control climate simulations will be analyzed and compared with observations, in an initial effort to assess the realism of their seasonal cycles as well as their annual means. In doing so, a region-dependent criterion will be developed that may be useful for evaluating predicted climate change. Then, precipitation changes from the 20th century to the future from all the archived models will be analyzed. Their seasonal cycles, especially the dry season behaviors, will be emphasized, and regions with more robust signals will be classified by seasons, providing initial insights into the likelihood and the mechanisms of future droughts. The focus will be on three regions: the Mississippi basin, the Sahel, and the Amazon, which represent three distinct climatic regimes and which have great economic and environmental significance. The projected future changes in precipitation, temperature, soil moisture and other relevant variables from representative CMIP3 models will be used to drive a coupled land-surface and dynamic vegetation model, VEGAS. The ecosystem and water cycle sensitivity to different characteristic changes in seasonal cycles will thus be assessed. The simulated soil moisture and vegetation state will be compared to traditional drought indices such as the precipitation anomaly, the Palmer Drought Severity Index (PDSI), and the Standardized Precipitation Index (SPI). These analyses may help answer the important question of how adequate are the traditional drought indices for the purposes of characterizing and predicting future changes in the hydro-ecosystem. Broader impacts of the studies are in its contribution to assessing the risk of drought in a warmer climate. The project will involve a graduate student and will provide her/him with one month of support.