Collaborative Research: Understanding and Modeling Key Arctic Cloud-ABL-Surface Processes and Interactions

北极对流层下层代表了地表、大气边界层和云过程之间的敏感平衡，形成了一个云- abl -地面（CAS）系统。对该系统中某个组件的改变将在其他组件中产生物理反应，最终形成对该变化的净系统反应。为了准确地模拟CAS的净贡献和对组分变化的响应，例如对从主要是多年海冰到第一年海冰的预测变化的响应，必须很好地理解CAS组分之间的过程相互作用，并在耦合气候模式中定量表示。不幸的是，对各种关键过程及其相互作用的理解非常初级，导致当前全球或区域气候模式的表述不佳。因此，在云分数、冰水路径和液态水路径等模拟参数中存在显著的不确定性，导致不同模式之间的地表云辐射强迫变化为40 W m-2，而模拟的地表湍流热通量与观测值相关性较差。即使是基本的表面参数，如反照率，通常也不能物理地表示，并为CAS系统提供了一个重大误差的来源。本建议的重点是利用现有的观测和过程模型来理解北极CAS系统的复杂过程和相互作用，并改进这些过程模型中的关键参数化。在分析中将使用广泛的现有原位和遥感观测数据。过程建模将使用天气和研究预报模型（WRF）的多分辨率配置来完成。观测分析和模型评估将使用面向过程的诊断进行，诊断揭示了与过程和/或参数化直接相关的物理关系。通过与国家大气研究中心（NCAR）的非正式合作，还将对最先进的全球气候模式（GCM），即社区气候系统模式（CCSM）忠实地反映这些过程相互作用的能力进行初步评估，从而初步了解在观测和过程模式中发现的关键过程和关系是否也反映在CCSM中。

The Arctic lower troposphere represents a sensitive balance between surface, atmospheric boundary layer, and cloud processes, forming a cloud-ABL-surface (CAS) system. Changes to a component in this system will produce physical responses in the other components, culminating in the net system response to the change. In order to accurately simulate the net CAS contributions and responses to a component change, such as to the predicted change from primarily multi-year sea-ice to first-year sea-ice, the process interactions between the CAS components must be well understood and quantitatively represented in coupled climate models. Unfortunately, the understanding of various key processes and their interactions is very nascent, leading to poor representations in current global or regional climate models. Hence, significant uncertainties exist in modeled parameters such as cloud fraction, ice water path, and liquid water path, resulting in surface cloud radiative forcing that varies by 40 W m-2 among models and modeled surface turbulent heat fluxes that have poor correlations with observations. Even basic surface parameters, such as albedo, are often not physically represented and provide a source of significant errors to the CAS system. This proposal focuses on understanding the complex processes and interactions in the Arctic CAS system using existing observations and process models and on improving key parameterizations in these process models. A broad range of existing in-situ and remotely sensed observational data will be used in the analyses. The process modeling will be done with multiple-resolution configurations of the Weather and Research Forecasting Model (WRF). Observational analyses and model evaluations will be conducted using process-oriented diagnostics -- diagnostics that reveal physical relationships directly relevant to a process and/or parameterization. Through informal collaboration with the National Center for Atmospheric Research (NCAR), preliminary evaluations of the ability of a state-of-the-art global climate model (GCM), the Community Climate System Model (CCSM), to faithfully represent these process interactions will also be performed, providing initial insight as to whether key processes and relationships found in observations and process models are also represented in CCSM.