The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

Article, Other literature type English OPEN
Valdes, Paul J. ; Armstrong, Edward ; Badger, Marcus P. S. ; Bradshaw, Catherine D. ; Bragg, Fran ; Davies-Barnard, Taraka ; Day, Jonathan J. ; Farnsworth, Alex ; Hopcroft, Peter O. ; Kennedy, Alan T. ; Lord, Natalie S. ; Lunt, Dan J. ; Marzocchi, Alice ; Parry, Louise M. ; Roberts, William H. G. ; Stone, Emma J. ; Tourte, Gregory J. L. ; Williams, Jonny H. T. (2017)

Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea ice, and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the HadCM3 coupled general circulation model. This model was developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies, but has now been largely superseded for many scientific studies by more recently developed models. However, it continues to be extensively used by various institutions, including the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol, who have made modest adaptations to the base HadCM3 model over time. These adaptations mean that the original documentation is not entirely representative, and several other relatively undocumented configurations are in use. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, which together make up HadCM3@Bristol version 1.0. In order to differentiate variants that have undergone development at BRIDGE, we have introduced the letter B into the model nomenclature. We include descriptions of the atmosphere-only model (HadAM3B), the coupled model with a low-resolution ocean (HadCM3BL), the high-resolution atmosphere-only model (HadAM3BH), and the regional model (HadRM3B). These also include three versions of the land surface scheme. By comparing with observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation, and vegetation. This evaluation, combined with the relatively fast computational speed (up to 1000 times faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3B family of coupled climate models, predominantly for quantifying uncertainty and for long multi-millennial-scale simulations.
  • References (135)
    135 references, page 1 of 14

    Adam, J. C., Clark, E. A., Lettenmaier, D. P., and Wood, E. F.: Correction of Global Precipitation Products for Orographic Effects, J. Climate, 19, 15-38, https://doi.org/10.1175/JCLI3604.1, 2006.

    Antonov, J. I., Seidov, D., Boyer, T. P., Locarnini, R. A., Mishonov, A. V., Garcia, H. E., Baranova, O. K., Zweng, M. M., and Johnson, D. R.: Volume 2: Salinity, World Ocean Atlas 2009, NOAA Atlas NESDIS, U.S. Government Printing Office, Washington, D.C., 2010.

    Arakawa, A. and Lamb, V. R.: Computational Design of the Basic Dynamical Processes of the UCLA General Circulation Model, in: General Circulation Models of the Atmosphere, edited by: Chang, J., Vol. 17, Methods in Computational Physics: Advances in Research and Applications, 173-265, Elsevier, https://doi.org/10.1016/B978-0-12-460817-7.50009-4, 1977.

    Armstrong, E., Valdes, P., House, J., and Singarayer, J.: The Role of CO2 and Dynamic Vegetation on the Impact of Temperate LandUse Change in the HadCM3 Coupled Climate Model, Earth Interact., 20, 1-20, https://doi.org/10.1175/EI-D-15-0036.1, 2016.

    Arnell, N. W., Hudson, D. A., and Jones, R. G.: Climate change scenarios from a regional climate model: Estimating change in runoff in southern Africa, J. Geophys. Res.-Atmos., 108, 4519, https://doi.org/10.1029/2002JD002782, 2003.

    Beerling, D. J., Fox, A., Stevenson, D. S., and Valdes, P. J.: Enhanced chemistry-climate feedbacks in past greenhouse worlds, P. Natl. Acad. Sci. USA, 108, 9770-9774, https://doi.org/10.1073/pnas.1102409108, 2011.

    Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description - Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677-699, https://doi.org/10.5194/gmd-4-677-2011, 2011.

    Betts, R. A., Cox, P. M., Collins, M., Harris, P. P., Huntingford, C., and Jones, C. D.: The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming, Theor. Appl. Climatol., 78, 157-175, 2004.

    Bhaskaran, B., Jones, R. G., Murphy, J. M., and Noguer, M.: Simulations of the Indian summer monsoon using a nested regional climate model: domain size experiments, Clim. Dynam., 12, 573-587, https://doi.org/10.1007/BF00216267, 1996.

    Booth, B. B. B., Jones, C. D., Collins, M., Totterdell, I. J., Cox, P. M., Sitch, S., Huntingford, C., Betts, R. A., Harris, G. R., and Lloyd, J.: High sensitivity of future global warming to land carbon cycle processes, Environ. Res. Lett., 7, 024002, https://doi.org/10.1088/1748-9326/7/2/024002, 2012.

  • Metrics
    No metrics available