Applied Science & Research Standing Committee Action from IICWG-VII

Co-Chairs Lars-Anders Breivik & Pablo Clemente Colón

Applied Science and Research IICWG-7 Action Items

SC6.2:

Re-identify ice service/national Science representatives for all member nations. For those services which do not have Science sections, Heads of Ice Service will be contacted to propose appropriate national representatives as a contact

Responsible

: Science Committee Co-Chairs

Target Date(s)

:

December 2006 Status:

Open

2

National representatives, draft list

• • • • • • • • • • • • • • Canada: Roger DeAbreu Denmark: (Søren Andersen) Finland: Jari Haapala Germany: Iceland: Ingibjörg Jónsdóttir Japan: Norway: Lars-Anders Breivik Russia: Sweden: USA: Pablo Clemente-Colón Lithuania: UK: John Stark Australia: Tony Worby WCRP / CliC: (Tony Worby will make contact) 3

Applied Science and Research IICWG-7 Action Items SC6.7:

Each national member requested to give a brief summary of Top Research priorities and plans to facilitate identification of complementary &/or common activities and areas for collaboration.

An updated list will be put on the IICWG web page

Responsible

: Science Committee Co-Chairs (Breivik)

Target Date(s) Status:

Open

: December 2006 4

Applied Science and Research IICWG-7 Action Items

SC6.8:

Develop a process for rotation of Committee Co-Chairs.

Flett stepping down as Co-Chair for IICWG-7.

Clements-Colon step in.

Suggested procedure: Rotation with a change every 2. meeting (3 years ?) Co-Chairs from Canada/USA and Europe(+) Overlap in rotation

Responsible

: All

Target Date(s)

: IICWG-8

Status: OPEN

5

Applied Science and Research IICWG-7 Action Items

SC7.1:

IICWG, IPY data assimilation and modelling project: Send out to each project partner template for project outline (Carrieres). This shall be completed and sent back within December 2006.

Responsible

: Tom Carrieres

Target Date

: December 2006

Status:

Closed (see 7.2)

Applied Science and Research IICWG-7 Action Items

SC7.2:

IICWG, IPY data assimilation and modelling project:

Prepare and arrange a dedicated workshop.

ice modelling and data assimilation

Place: met.no, Oslo Time: May 2006:

Responsible Target Date

May 2006

Status:

Closed

: : Breivik with support from Carrieres

Status on sea ice data assimilation

Report from IICWG work shop Oslo 14-16 May, 2007

IICWG - data assimilation history

• • • • • • Tromsø 2002, ice modeling and DA defined as a main priority St Petersburg 2003,

White paper

Hamburg 2004, dedicated science workshop Ottawa 2005,

IPY –proposal

Helsinki 2006, … Oslo 2007,

Dedicated workshop

Sea Ice – Ocean modeling, status

Sea ice – modeling, status

• Relying on a two-dimensional continuum hypothesis for description of the ice, and uses Viscous-Plastic rheology. None of the groups are using discrete element models, or other Lagrangian types of models, despite that some of the forecast systems are operating with a few km horizontal resolution. –

climate applications has been the main constraint.

• How complex a model system is needed for the ice forecasts (uncoupled ice, coupled ice-ocean, fully coupled atmosphere ice-ocean, or a hybrid in between those) depends on the type and length of the forecast, and on what kind of physical processes that are the most important for that specific case.

Data assimilation challenge From a limited set of surface observations - obtain a well balanced 4-dimensional ice-ocean model field

First approach:

Simple nudging of Ice concentration and SST towards observations (externally analyzed fields) satellite Model + 0 h Model + 120 h satellite

Main challenge

Specifying the background (model) error covariances for a coupled ice-ocean analysis

Especially important for: – Unobserved variables (e.g. under-ice ocean variables) – when the horizontal coverage of ice observations is not complete over the analysis domain (e.g. SAR or AVHRR data) Ignoring important spatial and multivariate covariances can lead to imbalances or artificial spatial discontinuities in the analyzed model state.

Facing the main challenge:

The groups are working on more advanced methods for estimating model error covariances:

EnKF SEIK

Example of estimating background error covariances using EnKF for one ice-season

Averaged (spatially and temporally) covariance between OWF  Ocean Temperature Local covariance between SST and OWF

Alain Caya, Meteorological Research Division, Environment Canada

Observations

1) 2) 3) Ice concentration analysis Ice drift vectors High resolution data

OSI SAF, AMSR-E, ice conc October 14 2007 IFREMER, AMSR-E, 3day ice drift, May 1 2007 FIMR, SAR & Insitu Ice Thickness charts

Observation errors

Example: use of Ice drift data:

3-day coarse resolution IFREMER -> 1-day fine resolution DNSC ->-> Recommendations: •

Specify accurate start and end times of displacement vectors

•

Specify elaborate error statistics

Very brief summary

• Not as far as hoped for in 2002 (Tromsø) • •

However

Promising results in advanced methods (3DVAR, EnKF, SEIK), Long term R&D focus is needed Simple pragmatic approaches for short term forecast systems are implemented and works To be followed up by new workshop in fall 2008 (at DMI)