Overview of the Coupled Model Intercomparison Project (CMIP)

The Coupled Model Intercomparison Project (CMIP) involves study and intercomparison of multimodel simulations of present and future climate. The simulations of the future use idealized forcing in which CO, increase is compounded 1% yr(-1) until it doubles (near year 70) with global coupled models that contain, typically, components representing atmosphere, ocean, sea ice, and land surface. Results from CMIP diagnostic sub-projects were presented at the Second CMIP Workshop held at the Max Planck Institute for Meteorology in Hamburg, Germany, in September 2003. Significant progress in diagnosing and understanding results from global coupled models has been made since the time of the First CMIP Workshop in Melbourne, Australia, in 1998. For example, the issue of flux adjustment is slowly fading as more and more models obtain stable multicentury surface climates without them. El Nino variability, usually about half the observed amplitude in the previous generation of coupled models, is now more accurately simulated in the present generation of global coupled models, though there are still biases in simulating the patterns of maximum variability. Typical resolutions of atmospheric component models contained in coupled models are now usually around 2.5degrees latitude-longitude, with the ocean components often having about twice the atmospheric model resolution, with even higher resolution in the equatorial Tropics. Some new-generation coupled models have atmospheric resolutions of around 1.5degrees latitude - longitude. Modeling groups now routinely run the CMIP control and 1% CO2 simulations in addition to twentieth- and twenty-first-century climate simulations with a variety of forcings e.g., volcanoes, solar variability, anthropogenic sulfate aerosols, ozone, and greenhouse gases, with the anthropogenic forcings for future climate as well. However, persistent systematic errors noted in previous generations of global coupled models are still present in the current generation (e.g., overextensive equatorial Pacific cold tongue, double ITCZ). This points to the next challenge for the global coupled climate modeling community. Planning and commencement of the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4) has prompted rapid coupled model development, which is leading to an expanded CMIP-like activity to collect and analyze results for the control, 1% CO2, and twentieth-, twenty-first, and twenty-second-century simulations performed for the AR4. The international climate community is encouraged to become involved in this analysis effort

The WCRP CMIP3 multi-model dataset: a new era in climate change research

A coordinated set of global coupled climate model [atmosphere–ocean general circulation model (AOGCM)] experiments for twentieth- and twenty-first-century climate, as well as several climate change commitment and other experiments, was run by 16 modeling groups from 11 countries with 23 models for assessment in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Since the assessment was completed, output from another model has been added to the dataset, so the participation is now 17 groups from 12 countries with 24 models. This effort, as well as the subsequent analysis phase, was organized by the World Climate Research Programme (WCRP) Climate Variability and Predictability (CLIVAR) Working Group on Coupled Models (WGCM) Climate Simulation Panel, and constitutes the third phase of the Coupled Model Intercomparison Project (CMIP3). The dataset is called the WCRP CMIP3 multimodel dataset, and represents the largest and most comprehensive international global coupled climate model experiment and multimodel analysis effort ever attempted. As of March 2007, the Program for Climate Model Diagnostics and Intercomparison (PCMDI) has collected, archived, and served roughly 32 TB of model data. With oversight from the panel, the multimodel data were made openly available from PCMDI for analysis and academic applications. Over 171 TB of data had been downloaded among the more than 1000 registered users to date. Over 200 journal articles, based in part on the dataset, have been published so far. Though initially aimed at the IPCC AR4, this unique and valuable resource will continue to be maintained for at least the next several years. Never before has such an extensive set of climate model simulations been made available to the international climate science community for study. The ready access to the multimodel dataset opens up these types of model analyses to researchers, including students, who previously could not obtain state-of-the-art climate model output, and thus represents a new era in climate change research. As a direct consequence, these ongoing studies are increasing the body of knowledge regarding our understanding of how the climate system currently works, and how it may change in the future

GLACE: the global land–atmosphere coupling experiment. Part I: overview

Permission to place copies of these works on this server has been provided by the American Meteorological Society (AMS). The AMS does not guarantee that the copies provided here are accurate copies of the published work. © Copyright 2006 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/AMS) or from the AMS at 617-227-2425 or [email protected] Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here

Abalone Industry Development: local assessment and management by industry

Because abalone larvae do not move far from their parents and abalone on different reefs start to reproduce at very different sizes, it is important to manage the stocks in each area with different size limits and catch limits. Otherwise, although the overall quota limit for a fishery zone at a given size limit may be correct, those places where abalone grow fastest are likely to become depleted, while areas with slow-growing abalone would be under-utilised. Such fine scale assessment and management of reef-stocks cannot be achieved by state regulations alone, so that collaborative management by industry stakeholders, assisted by state management agencies and researchers, is essential. This project was developed as a collaboration between researchers, industry stakeholders and managers, to empower industry to assess reef-stocks using diver observations of the shape and fouling of abalone shells

Global mean cloud feedbacks in idealized climate change experiments

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94978/1/grl21109.pd

Cloud feedback in atmospheric general circulation models: An update

Six years ago, we compared the climate sensitivity of 19 atmospheric general circulation models and found a roughly threefold variation among the models; most of this variation was attributed to differences in the models' depictions of cloud feedback. In an update of this comparison, current models showed considerably smaller differences in net cloud feedback, with most producing modest values. There are, however, substantial differences in the feedback components, indicating that the models still have physical disagreements

Response of ocean ecosystems to climate warming

Author Posting. © American Geophysical Union, 2004. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 18 (2004): GB3003, doi:10.1029/2003GB002134.We examine six different coupled climate model simulations to determine the ocean biological response to climate warming between the beginning of the industrial revolution and 2050. We use vertical velocity, maximum winter mixed layer depth, and sea ice cover to define six biomes. Climate warming leads to a contraction of the highly productive marginal sea ice biome by 42% in the Northern Hemisphere and 17% in the Southern Hemisphere, and leads to an expansion of the low productivity permanently stratified subtropical gyre biome by 4.0% in the Northern Hemisphere and 9.4% in the Southern Hemisphere. In between these, the subpolar gyre biome expands by 16% in the Northern Hemisphere and 7% in the Southern Hemisphere, and the seasonally stratified subtropical gyre contracts by 11% in both hemispheres. The low-latitude (mostly coastal) upwelling biome area changes only modestly. Vertical stratification increases, which would be expected to decrease nutrient supply everywhere, but increase the growing season length in high latitudes. We use satellite ocean color and climatological observations to develop an empirical model for predicting chlorophyll from the physical properties of the global warming simulations. Four features stand out in the response to global warming: (1) a drop in chlorophyll in the North Pacific due primarily to retreat of the marginal sea ice biome, (2) a tendency toward an increase in chlorophyll in the North Atlantic due to a complex combination of factors, (3) an increase in chlorophyll in the Southern Ocean due primarily to the retreat of and changes at the northern boundary of the marginal sea ice zone, and (4) a tendency toward a decrease in chlorophyll adjacent to the Antarctic continent due primarily to freshening within the marginal sea ice zone. We use three different primary production algorithms to estimate the response of primary production to climate warming based on our estimated chlorophyll concentrations. The three algorithms give a global increase in primary production of 0.7% at the low end to 8.1% at the high end, with very large regional differences. The main cause of both the response to warming and the variation between algorithms is the temperature sensitivity of the primary production algorithms. We also show results for the period between the industrial revolution and 2050 and 2090.J. L. Sarmiento and R. Slater were supported by the NOAA Office of Global Programs grant NA56GP0439 to the Carbon Modeling Consortium for model development and by NSF grant OCE00973166 for model and observational interpretations as part of the JGOFS Synthesis and Modeling Project. R. Barber was supported by NSF grant OCE 0136270 as part of the JGOFS Synthesis and Modeling Project. S. Doney and J. Kleypas wish to thank the Community Climate System Model science team and the Climate Simulation Laboratory at NCAR and acknowledge support from NOAA-OGP grant NOAA-NA96GP0360S. Spall is funded through the UK Department for Environment, Food and Rural Affairs contract PECD 7/12/37