Infrared radiation emitted to space simulated by an atmospheric model under development at GFDL. (1 frame/3 hours for one full year, starting in January).
My goal in this blog is to provide a forum for discussion of climate dynamics, with an emphasis, but not an exclusive focus, on climate change. The level of discussion is meant to be appropriate for graduate students in atmospheric and oceanic sciences, but I hope that this type of discussion is also useful to students in other fields with good applied math, physics and/or engineering backgrounds, to practicing scientists in other fields, and to some of my own colleagues. Different threads will probably focus on different parts of this intended readership.
Comments will be heavily moderated to maintain a tone and a level of discussion appropriate for the intended audience. Moderation will likely be slow. Comments must be closely related to the topic under discussion. I hope to post something every other week, on average.
I am employed by NOAA (and also lecture and advise graduate students at Princeton University). The opinions that I express are mine and not official positions of NOAA. However, I consider working on this blog to be fully consistent with NOAA’s outreach and communications policies.
I call myself an atmospheric or climate dynamicist/theorist/modeler. I am sure that there are philosophers of science who distinguish between the terms “theory” and “model”, but I don’t. I work with a range of theories of different kinds; when these reach a certain level of complexity they are typically referred to as computer models. The most relevant distinction relates to the purpose of the model. Some models are meant to improve our understanding of the climate system, not to simulate it with any precision. I like to talk about building a hierarchy of these models designed to improve and encapsulate our understanding. The most comprehensive models can be thought of as our best attempts at simulation, limited by available computer resources and our understanding of the effective governing dynamics on space and time scales resolvable with those resources.
Here is an example of a very simple model consisting of two coupled linear ordinary differential equations:
and represent the perturbations to the global mean surface temperature and deep ocean temperature resulting from the radiative forcing . This model is used in a recent paper by myself and several colleagues to help frame the discussion of what we refer to as the recalcitrant component of global warming.
The animation at the top is a small part of the output from another model that a group of us have been analyzing lately, a global atmospheric/land model living on a grid with approximately 50km spacing in the horizontal. (One can think of the atmospheric component of this model as 37,519,200 coupled ordinary differential equations — not that this is a good measure of the complexity of the model.) Shown in the animation is a full year of the infrared energy emitted to space (black is high emission, white is low emission.) What one sees mostly are the simulated high clouds that provide cold weakly emitting surfaces, but if one looks carefully one can see the diurnal cycle in the emission from the surface, which provides a feeling for the rate at which time is passing. Notice the sharp distinction between the mid-latitude atmosphere (dominated by non-linear waves) and the tropical atmosphere (dominated by smaller scale moist convection).
The model is introduced in this paper. It is initialized at some point in the past (about 20 years before this animation loop) and is constrained only by imposed boundary conditions over the ocean and sea ice. In a full climate model, the state of the oceans and sea ice would evolve freely as well. Comparing this particular simulated space-time field with observations in ways that are most informative about model deficiencies and the reliability of the model for various applications is a formidable challenge.
The two-box model and this high resolution atmospheric model illustrate two very distinct elements in the hierarchy of climate models. I’ll discuss both models in the next few posts. My own work seems to gravitate towards creating models intermediate in complexity between these two limits, in an attempt to both increase our understand of the climate and provide ideas on how to improve our high-end models. See this essay for a discussion of the importance of model hierarchies.
[The views expressed on this blog are in no sense official positions of the Geophysical Fluid Dynamics Laboratory, the National Oceanic and Atmospheric Administration, or the Department of Commerce.]