Understanding the Role of the Low-Level Jet in Land-Atmosphere Interactions and Drought over the Southern Great Plains

当地土地条件在干旱演变中的作用，作为当地气候自我调节的潜在因素，以及所涉及的多尺度陆地-大气相互作用，人们知之甚少。该项目将通过协同努力分析低层急流对大平原上空当地陆地-大气耦合的影响以及海洋对大平原低层急流的调节作用，增进对大平原南部干旱演变及其可预测性的了解。具体地说，该项目将研究当地干旱条件如何在不同的天气序列和大范围气候变化条件下触发降雨并最终从干旱中恢复过来。该项目的主要工具包括观测数据分析(表格和综合分析，概率事件特征，干旱和低层急流变率的天气和中尺度分析)和数值模拟。该项目将产生对干旱可预测性机制的新知识和见解，这些新知识和见解反过来可用于指导天气、季节预报和气候模式的过程级改进。对于作为国家粮食和能源安全支柱的半干旱的大平原南部地区，更好地了解干旱及其机制至关重要，特别是在气候多变和变化的背景下。除了公共安全和健康，经济的每一个部门都受益于预测技能的提高。其他重要项目成果包括验证目前的云解析模型，培训天气尺度和中尺度气象学领域的一名研究生和一名博士后研究员，以及耦合建模。

The role of local land conditions in drought evolution, as a potential agent of local climate self-regulation is poorly understood, as are the multi-scale land-atmosphere interactions involved. This project will improve understanding of drought evolution and its predictability in the southern Great Plains through synergistic efforts in analyzing impacts of low-level jets on local land-atmosphere couplings over the Great Plains and the regulatory role of the ocean on the Great Plains low-level jet. Specifically, this project will examine how local drought conditions may, under different conditions of weather sequencing and large-scale climate variability, serve to trigger rainfall and initiate an eventual recovery from drought. The primary tools for this project include observational data analyses (tabular and composite analyses, probabilistic event characterization, and synoptic and mesoscale analyses of droughts and low-level jet variability) and numerical modeling.The project will yield new knowledge and insights into mechanisms of drought predictability, which can in-turn be used to guide process-level refinement of weather-, seasonal forecast-, and climate models. For the semi-arid southern Great Plains, a pillar of the nation's food and energy security, it is critical that drought and its mechanisms be better understood, particularly in the context of climate variability and change. Every sector of the economy, in addition to public safety and health, benefits from improved forecast skill. Other important project outcomes include the validation of current cloud-resolving models and the training of one graduate student and one postdoctoral researcher in the areas of synoptic-scale and mesoscale meteorology, and coupled modeling.