Coupled High-Resolution Modeling of the Earth System
The Coupled High-Resolution Modeling of the Earth System (CHiMES) project is the basis for a new collaboration between the Department of Energy (DoE) and the National Oceanic and Atmospheric Administration (NOAA). NOAA/GFDL, whose Earth System models are recognized as being at the pinnacle of research into global climate change, has been granted access to DoE's Leadership Computing Facilities at Oakridge and Berkeley National Labs. The goal is to develop and perform scientific simulations of the global climate at unprecedented resolution.
CHiMES Scientific Mission
To simulate the Earth's climate using Earth System models (ESMs) to understand and predict natural and forced variability of the coupled climate system at "high" (i.e beyond the IPCC AR4 norm) resolution.
The predictive understanding of climate change, and the detection and attribution of climate change to anthropogenic and natural components are among the leading human issues of our time. Comprehensive Earth System models have proven to be among the best methods of meeting this challenge.
While the global-mean response of climate to anthropogenic forcing seems now to be confirmed with a great deal of confidence, the cutting edge of research and policy questions is now moving to the issue of understanding and predicting climate variability and change on regional scales. Such regional scales are the ones of most direct relevance to society and decision-makers. Current resolutions of IPCC-class models are mostly in the 100-km range for both ocean and atmosphere. A central concern for the next generation of models is to understand natural and forced variability as we make the next leap in resolution. This leap is particularly interesting as fundamental new physics appears in models of both atmosphere and ocean at the next step: at 25 km resolution or so, we begin to see the influence of both ocean eddies and organized atmospheric storm systems (tropical cyclones and mid-latitude fronts). Two key scientific themes that emerge at high resolution are currently being emphasized in the CHIMES Project.
Decadal predictability of the Earth system
Weather — that is, the day-to-day fluctuations of the local atmospheric state — is largely unpredictable beyond a week or two: i.e, a small perturbation of the initial conditions will over that period lead to two solutions that are essentially uncorrelated. However, the presence of persistent long-term circulation anomalies in the oceanic state suggests that the climate — the year-to-year fluctuations of the global climate state superimposed on the secular trend - is predictable at timescales of decades or longer.
The longevity of these circulation anomalies is dependent on dissipation by small-scale eddies. A key result that may be obtained at the resolutions proposed for this project is an answer to the "decadal predictability" conundrum, which is principally driven by the ocean state: are there modes of variability of the coupled ocean-atmosphere system that are predictable on timescales of a decade or more; and to what extent is this dependent on ocean resolution? We propose long-term simulations of the climate under constant external forcing, with a very high-resolution ocean capable of permitting direct simulation of the time and space scales associated with ocean eddies.
Correlating tropical cyclone statistics with the climate state
The decadal predictability study examines the climate response to fine-scale events in the ocean. Conversely, we also seek to answer the question of whether the statistics of fine-scale phenomena (e.g interannual variability in hurricane frequency and intensity) is predictable on the basis of free-running ESMs under time-varying forcing. The link between tropical cyclone frequencies and intensities and climate change is one of the hottest topics of current research: and besides the peer-reviewed literature, it is also the topic of a recent popular science bestseller: Storm World by Chris Mooney, in which GFDL and its scientists play starring roles. At GFDL, we have begun using high-resolution regional models to study the response of tropical storms to variations in the background climate state: these studies are limited by the technical problems of driving regional models from global data. We now propose to apply the extraordinary computational resources made available in the CHiMES project to study tropical storm statistics in a global high resolution model.
These studies: one of which examines the response of the equilibrium climate to fine-scale dynamics, and the second which looks at the response of fine-scale features to climate change, represent a pair of linked themes where fundamental advances in the predictive understanding of climate change follow from steep increases in model resolution.
GFDL's Earth system models
NOAA/GFDL, in conjunction with Princeton University, have in recent years constructed models that are considered premier models worldwide, as shown by the leading role played by its scientists and model results within the recently-concluded IPCC AR4 process. References to the NOAA/GFDL models, including the peer-reviewed literature, may be obtained starting from GFDL Data Portal. The GFDL models are built on a software engineering approach that is fast becoming standard across the community, as witnessed by the emergence of community standard frameworks such as the Earth System Modeling Framework (ESMF) and the Program for Integrated Earth System Modeling (PRISM). The GFDL Flexible Modeling System (FMS), which served as a design prototype for these projects, is a framework that enables different components of the climate system (e.g ocean, atmosphere) to be constructed by independent groups of scientists and algorithm developers and assembled in a variety of ways. These include hydrostatic and non-hydrostatic atmosphere models on conventional and "cubed-sphere" grids; and ocean models with a variety of vertical coordinate options on a tripolar grid. Underpinning this framework is a highly-scalable parallel communication fabric that exploits both shared and distributed memory approaches in a manner that is transparent to "user code": the science modules within the model.
We now have models that are highly scalable and are limited only by available hardware. DoE's proposal to make available the Leadership Computing Facilities for this project provides an unprecedented match between capability computing resources and a state-of-the-art model.
Significance of Research
Current approaches to generating consensus and uncertainty estimates of climate change rely on statistical methods comparing results from many models. The IPCC is a key example of such a process. In particular, the Climate Change Science Plan (CCSP) calls out the GFDL and NCAR models as the flagship models of the US, and central to such assessments. The design of model comparison studies is based in part on the understanding of the behaviour of a known suite of models at some target resolution. The proposed research addresses key scientific issues that centers will each have to tackle independently before making the leap to higher resolutions. In short, the significance of this research is that it gives us an early look at scientific issues associated with becoming able to resolve mesoscale features in the atmospheric and ocean circulations, and its implications for understanding of forced and natural variability of the climate system. Results from such simulations will provide us with insight as to what to expect in the near future in terms of understanding regional climate change, and may in fact inform the design of international modeling campaigns aimed at addressing those questions.
A proposal summarizing the research to be undertaken was presented to a DoE science team in July 2007. Pending the approval of the full project, discretionary resources were made available for preliminary work.
Some key current results based on current resources may be seen following the project links on right.
Please address all inquires to v. balaji (firstname.lastname@example.org).
created by v. balaji (balajiprinceton.edu) in emacs using the emacs-muse mode.
last modified: 18 January 2010