373 research outputs found
NEMO circum-Antarctic configuration for SAM sensitivity tests
No full textDescription paper: Verfaillie, D., Pelletier, C., Goosse, H. et al. The circum-Antarctic ice-shelves respond to a more positive Southern Annular Mode with regionally varied melting. Commun Earth Environ 3, 139 (2022). https://doi.org/10.1038/s43247-022-00458-x
NEMO, LIM and XIOS (a NEMO-compatible I/O library) are developed by the NEMO consortium, and distributed under the CeCILL license (included herein). The NEMO-LIM version used is a local fork springing from NEMO 3.6 (revision 6859) which includes the following modifications:
an undocumented lateral sea-ice melt scheme (J. Raulier, UCLouvain);
the ice-shelf coupling module from the revision 11248 of the dev_isf_remapping_UKESM_GO6package_r9314 NEMO development branch. Complete NEMO documentation is available from the NEMO consortium website.Developed within the framework of the PARAMOUR project, Decadal predictability and variability of polar climate: the role of atmosphere-ocean-cryosphere multiscale interactions. Fonds de la Recherche Scientifique–FNRS Grant number O0100718F (EOS ID 30454083)
Modeling the climate response to a massive methane release from gas hydrates
No full text[1] The climate response to a massive release of methane from gas hydrates is simulated in two 2500-year-long numerical experiments performed with a three-dimensional, global coupled atmosphere-sea ice-ocean model of intermediate complexity. Two different equilibrium states were used as reference climates; the first state with preindustrial forcing conditions and the second state with a four times higher atmospheric CO2 concentration. These climates were perturbed by prescribing a methane emission scenario equivalent to that computed for the Paleocene/Eocene thermal maximum (PETM; similar to55.5 Ma), involving a sudden release of 1500 Gt of carbon into the atmosphere in 1000 years. In both cases, this produced rapid atmospheric warming (up to 10degreesC at high latitudes) and a reorganization of the global overturning ocean circulation. In the ocean, maximum warming (2-4degreesC) occurred at intermediate depths where methane hydrates are stored in the upper slope sediments, suggesting that further hydrate instability could result from the prescribed scenario
Holocene climate variability at high-southern latitudes: an integrated perspective (HOLOCLIP)
No full textPARASO source code (no COSMO)
No full textSource code for the PARASO Antarctic configuration, except the COSMO model (atmosphere), which is only accessible to CLM-Community members (free membership charge for all research applications). A full version of these sources, including the COSMO part, has been uploaded to the CLM-Community RedC under "Downloads" -> "COSMO-CLM".
Hence, these sources are provided for dicdactical purposes, not for running the full model (which requires COSMO).
Model described in:
Pelletier, C., Fichefet, T., Goosse, H., Haubner, K., Helsen, S., Huot, P.-V., Kittel, C., Klein, F., Le clec'h, S., van Lipzig, N. P. M., Marchi, S., Massonnet, F., Mathiot, P., Moravveji, E., Moreno-Chamarro, E., Ortega, P., Pattyn, F., Souverijns, N., Van Achter, G., Vanden Broucke, S., Vanhulle, A., Verfaillie, D., and Zipf, L.: PARASO, a circum-Antarctic fully-coupled ice-sheet - ocean - sea-ice - atmosphere - land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2021-315, in review, 2021.Developed within the framework of the PARAMOUR project, Decadal predictability and variability of polar climate: the role of atmosphere-ocean-cryosphere multiscale interactions.
Fonds de la Recherche Scientifique–FNRS Grant number O0100718F (EOS ID 30454083)
PARASO ERA5 forcings
No full textExternal forcings from ERA5, used for forcing the PARASO configuration. Due to their size, only three months are provided here (from 01-JAN-2000 to 31-MAR-2000), for testing purposes. The data should be uncompressed with the uncpr_paraso.sh script.
Model described in: PARASO, a circum-Antarctic fully-coupled ice-sheet - ocean - sea-ice - atmosphere - land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5. C. Pelletier, T. Fichefet, H. Goosse, K. Haubner, S. Helsen, P.-V. Huot, C. Kittel, F. Klein, S. Le clec'h, N. P. M. van Lipzig, S. Marchi, F. Massonnet, P. Mathiot, E. Moravveji, E. Moreno-Chamarro, P. Ortega, F. Pattyn, N. Souverijns, G. Van Achter, S. Vanden Broucke, D. Verfaillie, L. Zipf. Submitted to Geoscientific Model Development, 2021.
Model source code: 10.5281/zenodo.5337510
The ERA5 data (Hersbach, 2018) was downloaded on 01-SEP-2019 from the Copernicus Climate Change Service (C3S) Climate Data Store. The results contain modified Copernicus Climate Change Service information 2020. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1979 to present, https://doi.org/10.24381/cds.adbb2d47, downloaded from the Copernicus Climate Change Service (C3S); Climate Data Store (CDS) on 01-SEP-2019, 2018.Developed within the framework of the PARAMOUR project, Decadal predictability and variability of polar climate: the role of atmosphere-ocean-cryosphere multiscale interactions.
Fonds de la Recherche Scientifique–FNRS Grant number O0100718F (EOS ID 30454083)
Modelling Uncertainties in the Climate of the Last Millennium: the ASTER Project
No full textThe LOVECLIM model (Driesschaert et al., 2007; Goosse et al., 2007) is used to simulate the climate of the last millennium with several 'climate' parameter sets yielding different sensitivities of the climate and the carbon cycle model. The purpose of these simulations is twofold. We intend to assess first the role of the carbon cycle on the climate, and second, the ability of the different selected parameter sets to drive the model within the range of the observed climate, and further to assess the uncertainty related to these parameters. The high frequency variability of the forcings is taken into account. For each set of parameters, LOVECLIM is driven by the natural evolution of insolation, solar irradiance and stratospheric aerosol concentrations due to volcanic activity as well as by changes caused by human activities such as deforestation, CO2 emission or concentration changes, changes in concentrations of greenhouse gases other than CO2 (including ozone) and in sulphate aerosol load. Several transient experiments are conducted for each parameter set. A first transient simulation (CONC) is forced with reconstructed atmospheric CO2 concentration. In the next two simulations, the emissions of carbon are taken into account, the model computing the corresponding atmospheric CO2 concentration. First (EMIS), the emissions due both to the land use changes and the fossil fuel burning are provided. Second (EFOR), only the emissions from fossil fuel burning are provided in addition to the vegetation change related to deforestation. The Northern Hemisphere annual mean temperatures simulated by the model according to the different parameter sets and carbon cycle sensitivities do not show striking differences. The general pattern shows slightly warmer conditions in the early part of the simulation and cooler ones during the Little Ice Age. At last, the global warming of the last century is also clearly simulated. The response of the carbon cycle to the evolution of forcings over the last millennium does not differ much among experiments although there is a much larger spread when considering different emission scenarios (e.g. EFOR and EMIS). Sensitivity tests to the amplitude of the variation of the total solar irradiance (TSI) are performed; a very first quick look at the simulations does not show significant differences in the pattern of the simulated climate in response to modification in the TSI amplitude. Further analysis must be conducted. Climate response to different schemes of deforestation will also be presented. Driesschaert E., Fichefet T., Goosse H., Huybrechts P., Janssens I., Mouchet A., Munhoven G., Brovkin V., and Weber S. L., 2007. Modelling the influence of Greenland ice sheet melting on the Atlantic meridional overturning circulation during the next millennia. Geophys. Res. Lett., 34:L1070, 2007. Goosse H., Driesschaert E., Fichefet T., and Loutre M.F., 2007. Information on the early Holocene climate constrains the summer sea ice projections for the 21st century Clim. Past 3, 683-692
Antarctic interglacial climate variability and implications for changes in ice sheet topography
No full textNew studies focusing on Antarctic climate variability during the current and earlier interglacial periods highlight the interplay between long-term climatic changes and climate variability in Antarctica, and enable the fingerprint of past changes in ice sheet topography to be investigated
Increased variability of the Arctic summer ice extent in a warmer climate
No full textSimulations performed with general circulation models and a model of intermediate complexity show that the variability of the September sea ice extent in the Arctic of the 21st century increases first when the mean extent decreases from present-day values. A maximum of the variance is found when the mean September ice extent is around 3 million km(2). For lower extents, the variance declines with the mean extent. The behavior is clearly different in Antarctica where the variance always decreases as the mean ice extent decreases, following roughly a square-root law compatible with very simple geometric arguments. Several mechanisms are responsible for the non-linear behavior of the Arctic. However, the strong interhemispheric contrast suggests that the difference in geometrical setting, with an open ocean in the south and a semi-closed basin in the north, plays a significant role. Citation: Goosse, H., O. Arzel, C. M. Bitz, A. de Montety, and M. Vancoppenolle (2009), Increased variability of the Arctic summer ice extent in a warmer climate, Geophys. Res. Lett., 36, L23702, doi: 10.1029/2009GL040546
Description of the Earth system model of intermediate complexity LOVECLIM version 1.2
No full textThe main characteristics of the new version 1.2 of the three-dimensional Earth system model of intermediate complexity LOVECLIM are briefly described. LOVECLIM 1.2 includes representations of the atmosphere, the ocean and sea ice, the land surface (including vegetation), the ice sheets, the icebergs and the carbon cycle. The atmospheric component is ECBilt2, a T21, 3-level quasi-geostrophic model. The ocean component is CLIO3, which consists of an ocean general circulation model coupled to a comprehensive thermodynamic-dynamic sea-ice model. Its horizontal resolution is of 3° by 3°, and there are 20 levels in the ocean. ECBilt-CLIO is coupled to VECODE, a vegetation model that simulates the dynamics of two main terrestrial plant functional types, trees and grasses, as well as desert. VECODE also simulates the evolution of the carbon cycle over land while the ocean carbon cycle is represented by LOCH, a comprehensive model that takes into account both the solubility and biological pumps. The ice sheet component AGISM is made up of a three-dimensional thermomechanical model of the ice sheet flow, a visco-elastic bedrock model and a model of the mass balance at the ice-atmosphere and ice-ocean interfaces. For both the Greenland and Antarctic ice sheets, calculations are made on a 10 km by 10 km resolution grid with 31 sigma levels. LOVECLIM1.2 reproduces well the major characteristics of the observed climate both for present-day conditions and for key past periods such as the last millennium, the mid-Holocene and the Last Glacial Maximum. However, despite some improvements compared to earlier versions, some biases are still present in the model. The most serious ones are mainly located at low latitudes with an overestimation of the temperature there, a too symmetric distribution of precipitation between the two hemispheres, and an overestimation of precipitation and vegetation cover in the subtropics. In addition, the atmospheric circulation is too weak. The model also tends to underestimate the surface temperature changes (mainly at low latitudes) and to overestimate the ocean heat uptake observed over the last decade
Comparison of data and model simulations over 4, 6, 8 and 10 ka snapshots at high-southern latitudes
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