[论文解读] How different are deterministic physics suites when coupled to fixed model dynamics and why?

Edward Groot, Hannah Christensen+6 more|arXiv (Cornell University)|Jan 6, 2026

Meteorological Phenomena and Simulations被引用 0

一句话总结

这项研究评估在强制同一固定大尺度动力学下，四个确定性物理套件的表现，发现各套件在降水方面高度一致，但相对于对流允许基准存在显著的欠分散，并且存在轻微的非线性动力学反馈。

ABSTRACT

It is often difficult to attribute uncertainty and errors in atmospheric models to designated model components. This is because sub-grid parameterised processes interact strongly with the large-scale transport represented by the explicit model dynamics. We carry out experiments with prescribed large-scale dynamics and different sub-grid physics suites. This dataset has been constructed for the Model Uncertainty Model Intercomparison Project (MUMIP), in which each suite forecasts sub-grid tendencies at a 22km grid. The common dynamics is derived from a convection-permitting benchmark: an ICON DYAMOND experiment (2.5km grid). We compare four different physics suites for atmospheric models in an Indian Ocean experiment. We analyse their joint PDFs of precipitation and associated physics tendencies for a full month. Precipitation is selected because it is a dominant uncertainty in the models that redistributes large amounts of heat. We find that all physics suites produce very similar precipitation amounts, with very high correlations between models, which exceed 0.95 at the native grid. However, the convection-permitting benchmark is more dissimilar from each of the physics suites, with correlations of $\approx$0.80. Similarly, we show that the vertically averaged physics tendencies in the free-troposphere are highly similar between the four physics suites, yet different if reconstructed for the benchmark. The water vapour sink is very closely linked with precipitation in the four physics suites. This suggests that the coarse-grid models are overconfident. We hypothese is that variation in unresolved convective structures can lead to variation in the dynamics, following a given amount of latent heating at fine grids, but not in our physics suites. The abstract length limit of ArXiv requires you to proceed in the PDF.

研究动机与目标

• 在固定大尺度动力学下评估确定性物理套件的相似性。
• 量化确定性物理倾向与对流组织与聚合之间的关系。
• 探索确定性物理与在对流允许模型中观察到的非线性动力学反馈之间的潜在联系。

提出的方法

• 使用模型不确定性模型互比项目（MUMIP） SCM 强迫场文件，源自 2.5 公里 DYAMOND ICON 模拟。
• 用来自共享动力学的粗粒度平流趋势强迫 SCM，以计算物理响应。
• 在 31 天内，对 44,000 个网格盒（间距 22 公里）进行 3–6 小时提前时的降水与垂直趋势的联合概率密度函数（PDF）计算。
• 从 SCM 动力中重构伪 ICON 物理倾向，便于与对流允许基准进行比较。
• 在 ICON 降水与 SCM 降水之间拟合 y = a + b x^p 的指数关系，以检验非线性（p ≠ 1）。
• 评估各套件与基准之间自由对流层及混合层中的湿度和温度趋势的相关性。

Figure 1: Under conditions of fixed column precipitation rate (as proxy for latent heating rate), the mass divergence rate depends on convective organisation and aggregation in large-eddy and convection-permitting ICON simulations, but not in coarser ICON simulations of the same case study ( Groot e

实验结果

研究问题

• RQ1 在固定动力学下，不同确定性物理套件是否产生相似的降水和物理倾向响应？
• RQ2 相对于对流允许基准，SCMs 是否存在欠分散，这与亚网格变率有何关系？
• RQ3 在使用粗网格物理量时，是否存在对流组织/动力学与降水之间的非线性反馈证据？
• RQ4 自由对流层和混合层中的湿度与温度趋势在各套件之间以及与基准之间的相关性如何？
• RQ5 重力波相互作用和对流组织在观测到的物理与动力学关系中扮演何种角色？

主要发现

SCM/Physics suite	Best estimate of p	Uncertainty p (1σ)	Best estimate of a	Uncertainty a (1σ)
IFS/IFS	1.06	0.004	-0.036	0.002
ARPEGE/ARPEGE	1.05	0.004	0.019	0.002
CCPP/GFS	1.02	0.004	-0.104	0.003
CCPP/RAP	1.05	0.005	-0.069	0.002

• 各物理套件之间的降水成对相关性非常高（0.96–0.98），但与对流允许基准的相关性较低（约 0.80）。
• 在粗粒化到 1.0 度时，重构的基准降水与 SCM 的相关性约为 0.93–0.94，但 SCM–基准的相关性仍显著低于 SCM–SCM 的相关性。
• 自由对流层的湿度趋势在套件之间相关性很高（约 0.97），但与基准趋势相比下降至约 0.80–0.82。
• 与基准相比，SCMs 在湿度趋势上存在显著的欠分散，表明未被表示的亚网格变率。
• 对于大多数套件，来自 SCM 的 ICON 降水最适合的非线性关系为 p 约为 1.05–1.06，表明存在微弱但稳健的非线性动力学反馈；GFS 显示信号较弱且不太稳健。
• 自由对流层的温度趋势在套件之间高度相关（约 0.93–0.97），且欠分散程度低于湿度，意味着在 SCM 趋势中湿度是未被充分表示的亚网格不确定性主导因素。

Figure 2: Joint PDFs of precipitation accumulation over all available columns, left top: for ARPEGE and IFS at lead times of 3hr to 6hr; right top: IFS (same lead time) and ICON over all available columns; bottom: same as right top, after regridding to 1.0 degrees. Blue lines represent the 1:1-relat