The Response of Convective Precipitating Storms to Anthropogenically Enhanced Global Radiative Forcing

对流降水风暴(CPSS)及其相关的冰雹、破坏性地面风、龙卷风和山洪灾害对生命和财产构成严重威胁。这些有害现象是由大气湿度、温度和风的三维分布决定的。简单的物理论证表明，温室气体(GHG)浓度的人为增加导致这些状态变量的变化，反过来将影响CPSS的频率和强度。在早期的工作中，首席调查人员(PI)已经表明，利用对流过程在次网格尺度上被参数化的气候模式，可以获得关于这种局部响应的动力学的有价值的见解。然而，这种“间接”方法的局限性突显了应用数值模式明确解决大片大陆地区对流风暴的重要性。在初步工作中，PIS还确定了伸缩模拟战略的基本可行性，该战略由嵌套在全球模式(G-C战略)内的允许对流云模式[天气研究和预报(WRF)模式]和嵌套在全球模式(G-R-C战略)内的区域模式(G-R-C战略)组成。在这项试点工作取得成功的基础上，私人投资促进机构将利用这些战略，在现代和未来一段时间内生成CPSS的气候和相关的危害。将进行一些以重新分析为全球驱动因素的初步实验，主要是为了揭示CPS统计数据中的模型偏差。大部分实验将涉及WRF模型的高分辨率集成，这是由政府间气候变化专门委员会关于排放情景的特别报告强制执行的一整套气候模型推动的。这一集合将有助于量化CPS动力学对大尺度边界条件变化的敏感性。伴随这些实验的将是分析信息丰富的WRF模型输出的新技术。首先，将使用先前开发的自动化的、面向对象的分析程序来识别、表征和分类沉淀系统。这将允许进一步考虑属性，如对流与层状降水的面积范围。其次，将采用一种替代方法，为CPSS提供当地规模的危险天气服务人员的量化。例如，龙卷风的发生将使用经验参数中的风暴尺度风场来估计。类似的破坏风和冰雹的参数也将被开发出来。最后，将使用一种被称为次抽样的强大的重抽样技术来从观察和建模的时间序列中计算统计特征及其可信区间，包括均值、方差、偏度、相关性和极值分布的参数。这一项目的学术价值在于，它将估计对流降水风暴和相关现象对温室气体浓度增加导致的全球辐射强迫增强的潜在反应。这将通过一种新的跨尺度建模方法实现，然后通过同样新颖的分析技术实现。该项目的一个更广泛的影响是，它将提供可用于评估人为气候变化的潜在影响的额外信息。该项目还将影响普渡大学的研究生和本科教育。例如，很大一部分研究将由研究生在教师的指导下进行，从而培训下一代气候和气象科学家的尖端技能。为了增强这一技能，将为普渡大学的学生和教职员工提供一个关于气候建模工具的年度研讨会。此外，从非主修本科生到研究生的课程中已经纳入了PIS试点项目的部分内容，包括开发一门气候统计研究生课程。PIS将继续(并扩大)这一纳入研究生和本科生课程的内容。

Convective precipitating storms (CPSs) and the associated hazards of hail, destructive surface winds, tornadoes, and flash floods pose serious risks to life and property. These hazardous phenomena are governed by the three-dimensional distributions of atmospheric moisture, temperature, and wind. Simple physical arguments suggest that changes in these state variables resulting from anthropogenic increases in greenhouse gas (GHG) concentrations will in turn affect the frequency and intensity of CPSs. In earlier work, the Principal Investigators (PIs) have shown that valuable insight about the dynamics of this local response can be gained using climate models in which convective processes are parameterized at subgrid scales. However, the limitations of this "indirect" approach highlight the importance of applying numerical models that explicitly resolve convective storms over large continental areas. In preliminary work, the PIs also established the basic viability of telescoping modeling strategies that consist of integrations of a convective-cloud-permitting model [the Weather Research and Forecasting (WRF) model] nested within a global model (the G-C strategy) and within a regional model that is itself nested within a global model (the G-R-C strategy). Building on the success of this pilot work, the PIs will utilize these strategies for the purpose of generating climatologies of CPSs and associated hazards over modern and future time periods. Some initial experiments using reanalyses as the global driver will be conducted, primarily to reveal model biases in the CPS statistics. The bulk of the experimentation will involve high-resolution integrations of the WRF model, driven by an ensemble of climate models forced by Intergovenmental Panel on Climate Change Special Report on Emissions Scenarios. This ensemble will help to quantify the sensitivity of the CPS dynamics to variations in the large-scale boundary conditions. Accompanying these experiments will be novel techniques to analyze the information-rich WRF model output. First, previously developed automated, object-oriented analysis procedures will be used to identify, characterize, and classify the precipitating systems. This will allow further consideration of attributes such as the areal extent of convective versus stratiform precipitation. Second, a proxy method will be adapted to provide a quantification of local-scale hazardous weather attendant with the CPSs. For example, tornado occurrence will be estimated using the storm-scale wind field in an empirical parameter. Similar parameters for damaging wind and hail will also be developed. Finally, a powerful resampling technique known as subsampling will be employed to compute statistical characteristics and their confidence intervals from observed and modeled time series, including means, variances, skewnesses, correlations, and parameters of extreme value distributions. The intellectual merit of this project is that it will provide an estimate of the potential response of convective precipitating storms and associated phenomena to the enhanced global radiative forcing associated with increases in GHG concentrations. This will be achieved through a novel scale-spanning modeling approach, and then through equally novel analysis techniques. One of the broader impacts of this project is that it will offer additional information that can be used to assess the potential impacts of anthropogenic climate change. The project will also affect graduate and undergraduate education at Purdue University. For example, a significant portion of the research will be performed by graduate students under the mentorship of faculty, thereby training the next generation of climate and weather scientists in cutting edge skills. To enhance this skill set, an annual workshop on climate modeling tools will be offered to Purdue students and faculty. In addition, components of the PIs' pilot project have already been incorporated into courses from the non-major, undergraduate level to the graduate level, including development of a graduate course on climate statistics. The PIs will continue (and expand) this incorporation into the graduate and undergraduate curriculum.