Saw this on S.D.A.:
The Sound Of Settled Science
May 26, 2018 Kate Climate Cult Unsettled Science
@JudithCurry —“A new angle on climate model uncertainty: changing the order in which different climate processes are computed can vary climate feedback parameter by half the full CMIP5 spread in climate feedback. “
That points at this paper:
Impact of Physics Parameterization Ordering in a Global Atmosphere Model
Aaron S. Donahue
Peter M. Caldwell
First published: 02 February 2018
This article has been contributed to by US Government employees and their work is in the public domain in the USA.
Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid‐scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k‐means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.
I’m slogging through it now. So it looks to me like the “Climate Scientists” are learning that Math Is Hard, especially when it involves numbers, and computers do not make it easier, they just hide the problems better.
I could have told them that. Oh, wait, I have…