Continuous structural parameterization (CSP) is a proposed method for approximating different numerical model parameterizations of the same process as functions of the same grid‐scale variables. This allows systematic comparison of parameterizations with each other and observations or resolved simulations of the same process. Using the example of two convection schemes running in the Met Office Unified Model (UM), we show that a CSP is able to capture concisely the broad behavior of the two schemes, and differences between the parameterizations and resolved convection simulated by a high resolution simulation. When the original convection schemes are replaced with their CSP emulators within the UM, basic features of the original model climate and some features of climate change are reproduced, demonstrating that CSP can capture much of the important behavior of the schemes. Our results open the possibility that future work will estimate uncertainty in model projections of climate change from estimates of uncertainty in simulation of the relevant physical processes.

中文翻译：

---

连续结构参数化：一种表示大气对流的结构内表示不同模型参数化的建议方法

连续结构参数化（CSP）是一种用于将相同过程的不同数值模型参数化近似为相同网格规模变量的函数的拟议方法。这样可以对参数设置进行系统的比较，并对同一过程进行观察或解析模拟。使用在Met Office统一模型（UM）中运行的两个对流方案的示例，我们表明CSP能够简明扼要地捕获这两种方案的广泛行为，以及高分辨率解析模拟的参数化和解析对流之间的差异。在UM中将原始对流方案替换为CSP仿真器后，原始模型气候的基本特征和气候变化的某些特征得以再现，证明CSP可以捕获该方案的许多重要行为。我们的结果为未来的工作将根据相关物理过程模拟中的不确定性估计来估计气候变化模型预测中的不确定性提供了可能性。