CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011
CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011
CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011
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CLIMATE VARIABILITY AND PREDICTABILITY<br />
Additional experiments have also been carried out and published. Additional members have been added<br />
leading to a total of 10 for each forecast date. 2 additional dates per decade have been also integrated,<br />
namely 1959, 1964, 1969, ..., 2004, as a supplement to the mandatory 1960, 1965, 1970, ..., 2005 suite.<br />
Finally, a fake <strong>2010</strong>-pinatubo eruption has been introduced in an additional set of forecasts for the 2005-<br />
2035 timeslot. The decadal forecast activity at Cerfacs is also part of the ongoing EC-FP7 COMBINE<br />
project coordinated by MPI, the GICC EPIDOM project started at the beginning of <strong>2011</strong> and coordinated<br />
by Cerfacs and the ANR CECILE coordinated by BRGM. The two main preliminary results are listed<br />
below.<br />
2.2.1 Ocean initialization<br />
In order to minimize the initial shocks and drifts during the forecasts, initial conditions are obtained from<br />
a coupled simulation of CNRM-CM5 integrated from 1958 to present where the sole ocean is nudged in<br />
temperature and salinity towards the NEMOVAR-COMBINE (Balmaseda et al. <strong>2010</strong>) ocean reanalysis.<br />
Within this simulation, the other components (atmosphere, sea-ice, continents etc) are thus freely coupled<br />
and do not contain any observational data. The NEMOVAR-COMBINE reanalysis has been produced using<br />
a multivariate 3D-var data assimilation method (Weaver et al. 2005, Daget et al. 2009) applied to the NEMO<br />
model running on the same ORCA1 configuration as CNRM-CM5, and with the physical parameterizations<br />
as close as possible. The surface temperature and salinity are restored towards NEMOVAR using a flux<br />
derivative term while the subsurface ocean nudging is based on a 3D Newtonian damping in temperature<br />
and salinity (see Madec et al. 2008 for details) which is function of depth and space. No 3D damping is<br />
applied between the surface and the thermocline thus leaving the mixed layer free to evolve ; the damping<br />
is equal to 10 days below the thermocline and to 360 days for the deep ocean (below 800m depth). There is<br />
no nudging near the coasts to avoid spurious effects on boundary currents, neither within the tropical band.<br />
The latter choice tends to account for the fact that tropical subsurface ocean and tropical surface wind should<br />
be consistent to minimize the excitation of tropical Kelvin and Rossby waves when one lets the model go<br />
at the beginning of the forecast. We performed two sets of experiments where nudging is excluded either<br />
within 1 o N-1 o S (hereafter GLOB) or within 15 o N-15 o S (hereafter EXTROP). We show that GLOB has<br />
a much stronger initial shock than EXTROP ; it is characterized by a systematic excitation of an El Niño<br />
events in the Pacific leading, by teleconnection, to enhanced drift in the entire Northern Hemisphere. We<br />
found that such a disruption affects the mean drift of the model up to about 4 year leadtime stressing out<br />
the importance of the initialization step (Sanchez et al <strong>2011</strong>).<br />
2.2.2 Skill score<br />
<strong>Dec</strong>adal predictability arises from two sources : anomalous states assimilated in the initial conditions of<br />
the climate system (here the NEMOVAR ocean, -first kind predictability) and so-called external forcings<br />
linked to natural (volcanoes and solar activities) events or anthropogenic influences (e.g. GHGs increase,<br />
aerosols emission, land use etc. -second kind of predictability). Skill scores have been computed for global<br />
temperature as a function of leadtime. Data have been debiased following the CMIP5 linear protocol. Very<br />
high positive scores (from 0.93 to 0.98) are found whatever the leadtime. At global scale, the predictive skill<br />
is mostly explained by the warming trend and the interannual cooling events associated with the external<br />
forcings, respectively the increase of GHG concentrations and the volcanic aerosols that are prescribed in<br />
the model (Figure 2.1).<br />
118 <strong>Jan</strong>. <strong>2010</strong> – <strong>Dec</strong>. <strong>2011</strong>