ENSEMBLES STREAM2 INGV C-ESM SRA1B run1, monthly mean values

Manzini, Elisa

These data represent monthly averaged values of selected variables for ENSEMBLES (http://www.ensembles-eu.org). The list of output variables can be found in: http://ensembles.wdc-climate.de/output-variables. The model output corresponds to the IPCC AR4 "720 ppm stabilization experiment (SRES A1B)".

The 21st century simulation (2001-2100) is forced with changes of greenhouse gas concentations (CO2, CH4, N2O, CFC-11* and CFC-12), ozone and sulfate aerosols.

The datasets are available in netCDF format.
The dataset names are composed of
- centre/model acronym (INGVCE: Istituto Nazionale di Geofisica e Vulcanologia / Carbon - Earth system model)
- scenario acronym (SRA1B)
- run number (1: run 1)
- time interval (MM:monthly mean)
- variable acronym [with level value] (e.g. hur850: relative humidity, 850 hPa)
example: INGVCE_SRA1B_1_MM_hur850

Technical data to this experiment:
The model, named INGV Carbon Earth System Model (INGV C-ESM), is an evolution of the SINTEX-F model (Fogli et al. 2009 in preparation, Gualdi et al., 2003a, 2003b; Guilyardi et al., 2003, Luo et al. 2003).
The ocean component is the OPA 8.2 model (Madec et al., 1998), with the ORCA2 configuration: 2x2 degrees cos(latitude) with increased meridional resolutions to 0.5 degree near the equator, 31 vertical levels. The evolution of the sea-ice is described by the LIM model (Louvain-La-Neuve sea-ice model; Fichefet and Morales Maqueda, 1997, 1999; Timmermann et al., 2005), which is a thermodynamic-dynamic snow sea-ice model.
The atmospheric component is the ECHAM5 model (Roeckner et al., 2003, 2006), with T31 horizontal resolution and 19 hybrid sigma-pressure levels. The coupling information, without flux corrections, is exchanged every 1 day by means of the OASIS 3 coupler (Valcke et al., 2007). The dynamical vegetation and land surface component is the SILVA model (Alessandri, 2006; Alessandri et al., 2007) and the marine biogeochemistry uses the PELAGOS model (Vichi et al., 2007a,b).
ENSEMBLES (Production of seasonal to decadal hindcasts and climate change scenarios)
World (global)
Spatial Coverage
Longitude 0 to 360 Latitude -90 to 90 Altitude: 0 m to 10 hPa
Temporal Coverage
2001-01-01 to 2099-12-31 (calendrical)
Use constraints
According to Ensembles Data Policy (http://ensembles-eu.metoffice.com/docs/Ensembles_Data_Policy_261108.pdf)
Data Catalog
World Data Center for Climate
2.33 GiB (2499580408 Byte)
completely archived
Creation Date
Cite as
Manzini, Elisa (2009). ENSEMBLES STREAM2 INGV C-ESM SRA1B run1, monthly mean values. World Data Center for Climate (WDCC) at DKRZ. https://hdl.handle.net/21.14106/17caf68f68bfef027b3e10eae9b86809cd786640

consistent as the model is
Contact typePersonORCIDOrganization

Is described by

[1] Roeckner, E.; Baeuml, G.; Bonaventura, L.; Brokopf, R.; Esch, M.; Giorgetta, M.; Hagemann, S.; Kirchner, I.; Kornblueh, L.; Manzini, E.; Rhodin, A.; Schlese, U.; Schulzweida, U.; Tompkins, A. (2003). The atmospheric general circulation model ECHAM 5. PART I: Model description. http://hdl.handle.net/11858/00-001M-0000-0012-0144-5
[2] Madec, G.; Delecluse, P.; Imbard, M.; Levy, C. (1999). OPA 8.1 Ocean General Circulation Model reference manual. http://forge.ipsl.jussieu.fr/nemo/raw-attachment/wiki/Documentation/Doc_OPA8.1.pdf
[3] Fogli, P.G.; Manzini, E.; Vichi, M.; Alessandri, A.; Patara, L.; Navarra, A. (2000). The CMCC Earth System Model (ESM).
[5] Alessandri, A. (2009). Effects of land surface and vegetation processes on the climate simulated by an atmospheric general circulation model.
[6] DOI Alessandri, Andrea; Gualdi, Silvio; Polcher, Jan; Navarra, Antonio. (2007). Effects of Land Surface-Vegetation on the Boreal Summer Surface Climate of a GCM. doi:10.1175/JCLI3983.1
[7] DOI Vichi, M.; Pinardi, N.; Masina, S. (2007). A generalized model of pelagic biogeochemistry for the global ocean ecosystem. Part I: Theory. doi:10.1016/j.jmarsys.2006.03.006
[8] DOI Vichi, M.; Masina, S.; Navarra, A. (2007). A generalized model of pelagic biogeochemistry for the global ocean ecosystem. Part II: Numerical simulations. doi:10.1016/j.jmarsys.2006.03.014


[1] DOI Roeckner, E.; Brokopf, R.; Esch, M.; Giorgetta, M.; Hagemann, S.; Kornblueh, L.; Manzini, E.; Schlese, U.; Schulzweida, U. (2006). Sensitivity of Simulated Climate to Horizontal and Vertical Resolution in the ECHAM5 Atmosphere Model. doi:10.1175/JCLI3824.1
[2] DOI Gualdi, S.; Guilyardi, E.; Navarra, A.; Masina, S.; Delecluse, P. (2003). The interannual variability in the tropical Indian Ocean as simulated by a CGCM. doi:10.1007/s00382-002-0295-z
[3] DOI Gualdi, S.; Navarra, A.; Guilyardi, E.; Delecluse, P. (2003). Assessment of the tropical Indo-Pacific climate in SINTEX CGCM. doi:10.4401/ag-3385
[4] DOI Guilyardi, Eric; Delecluse, Pascale; Gualdi, Silvio; Navarra, Antonio. (2003). Mechanisms for ENSO Phase Change in a Coupled GCM. doi:10.1175/1520-0442(2003)16<1141:MFEPCI>2.0.CO;2
[5] DOI Luo, Jing-Jia; Masson, Sebastien; Behera, Swadhin; Delecluse, Pascale; Gualdi, Silvio; Navarra, Antonio; Yamagata, Toshio. (2003). South Pacific origin of the decadal ENSO-like variation as simulated by a coupled GCM. doi:10.1029/2003GL018649
[6] DOI Fichefet, T.; Maqueda, M. A. Morales. (1997). Sensitivity of a global sea ice model to the treatment of ice thermodynamics and dynamics. doi:10.1029/97JC00480
[7] DOI Fichefet, T.; Maqueda, M. A. Morales. (1999). Modelling the influence of snow accumulation and snow-ice formation on the seasonal cycle of the Antarctic sea-ice cover. doi:10.1007/s003820050280
[8] DOI Timmermann, Ralph; Goosse, Hugues; Madec, Gurvan; Fichefet, Thierry; Ethe, Christian; Dulière, Valérie. (2005). On the representation of high latitude processes in the ORCA-LIM global coupled sea ice-ocean model. doi:10.1016/j.ocemod.2003.12.009

Attached Datasets ( 116 )

Details for selected entry
[Entry acronym: ENSEMBLES2_INGVCE_SRA1B_1_MM] [Entry id: 2208479]