 |
| Titel |
Sea-ice data assimilation in coupled climate models - are ice concentration observations sufficient? |
| VerfasserIn |
Steffen Tietsche, Dirk Notz, Johann Jungclaus, Jochem Marotzke |
| Konferenz |
EGU General Assembly 2011
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 13 (2011) |
| Datensatznummer |
250055134
|
|
|
|
|
|
| Zusammenfassung |
| Sea-ice initial conditions contribute to decadal predictability of polar climate. For skilful
predictions, coupled climate models hence need to be initialised with sea-ice conditions that
are both close to observations, and compatible with model dynamics.
Here, we investigate the feasibility of sea-ice data assimilation in the coupled climate
model ECHAM/MPI-OM. In particular, we examine how observations of Northern
Hemisphere sea-ice concentration can be used to improve the simulated ice volume and ocean
surface properties. We employ a simple nudging approach for ice concentration, and the
analysis increments for ice volume, sea surface salinity and temperature are prescribed as a
function of the concentration analysis increments.
Although the simulation of ice concentration is almost always improved, we
find that the quality of the simulated ice volume depends critically on the choice
for the functional dependence between the analysis increments of concentration
and volume. Schemes that conserve ice volume or ice thickness, as they have been
suggested in other studies, do not give satisfying results in our data assimilation
framework.
We show that the problems in those schemes arise when the dynamics of the coupled
model provide a too strong negative feedback on the analysis increments. For the
thickness-conserving scheme, the internal sea-ice stress can cause unrealistic ice advection in
summer, and for the volume-conserving scheme the strong dependence of surface heat flux on
ice concentration can cause unrealistic ice growth in winter.
We suggest a new scheme for sea-ice data assimilation with volume analysis increments
that are proportional to concentration analyis increments. This scheme provides a volume
correction that mitigates the adverse effects introduced by negative model feedbacks, and is
able to significantly improve the analysed sea-ice state using only observations of ice
concentration. Therefore, this scheme is a promising candidate to be combined with
atmospheric and oceanic data assimilation in order to initialise the model for seasonal to
decadal predictions. |
|
|
|
|
|
|