steffen m olsen, polar oceanography, dmi, copenhagen dk ct3 hamburg 22-23/4 2013 geomar (6) mojib...

Steffen M Olsen, Polar Oceanography, DMI, Copenhagen DK

CT3 Hamburg 22-23/4 2013

NACLIM Core Theme 3:People

GEOMAR (6)• Mojib Latif (CT/WP lead)• Wonsun Park• Thomas Martin

MPG (2)• Johann Jungclaus• Katja Lohmann

UHAM (1)• Detlef Stammer• Armin Köhl

DMI (7)• Steffen M. Olsen (CT/WP lead)• Jacob L. Høyer• Rasmus T. Tonboe• Torben Schmith (tbc)


Suitability of the ocean observing system components for

initialization

Impact of Arctic initialization on forecast

skill

Initialization of prediction systems with ocean observations

WP 3.1Mojib Latif

WP 3.2Steffen M. Olsen

NACLIM Core Theme 3:Structure


Suitability of the ocean observing system components for

initialization

WP 3.1

NACLIM Core Theme 3:WP 3.1

Objectives• Investigate and quantify the benefit of

different components of the ocean observing system for prediction systems (decadal)

• Identify necessary enhancements and potential reductions in the present system

Methodology• Ideal model World hindcast experiments (using the adjoint assimilation

system of UHAM - an environment for climate model initialization ?)

• Re-start simulations with truncated ocean initial conditions corresponding to different ocean regions and observing systems



Deliverables

D9 (GEOMAR, month 12): Report on the setup of coupled model and hindcasts conducted with initial conditions corresponding to ARGO-like sampling

D 26 (GEOMAR, month 24): Report on hindcasts conducted with initial conditions extended to include ”RAPID”, and on the feasibility of decadal forecasts with the current ocean observing system

D 39 (GEOMAR, month 36): Report on hindcasts conducted with satellite information

D 58 (GEOMAR, month 44): Report on the identifications of potential needs that are not captured by the present ocean observing system for enhancing decadal predictions.


Impact of Arctic initialization on forecast

skill

WP 3.2


Objectives• Establish the impact of Arctic data and ini-

tialization of the Arctic region on forecast skill

• Construct a 15 year combined SST/IST dataset for the Arctic Ocean

• Explore the potential to constrain the state of the Arctic Ocean by remote observations – flux monitoring system at the GSR.Methodology

• This WP address in detail the Arctic region of sparse data coverage. • Work is organized along three parallel tracks including

- ideal model experiments (data withholding, potential predictability)- improving data availability and - explore the use of remote transport measurements.



Deliverables

D10 (DMI, month 12): Assessment of model build-up, storage and release of Arctic Ocean freshwater pools.

D27 (UHAM, month 24): Report on the documentation and description of improved model parameters.

D28 (DMI, month 24): Report on the documentation and description of the new Arctic Ocean dataset combining SST and IST.

D40 (DMI, month 36): Report on the establishment of impact of the Arctic region initialization, and on the sources of predictive skill from data withholding experiments.

D51 (DMI, month 44): Assessment of the value of the GSR flux monitoring time series for confining the initial state of the upper Arctic Ocean.


NACLIM Core Theme 3:Open questions at kick-off

Verify the list of CT3 people and their involvement – done!

Explore overlapping synergies with CT1 ongoing – ongoing!

Decide on the level of internal coordination and WP specific meetings in addition to the annual meetings – done!

- joint activities with CT1 on overarching themes

New questions

CT2 work includes a complete work package on joint model-observational data comparison (WP 2.3, UHAM+FMI). Possibilities for involvement.



Combined satellite SST and IST for the Arctic Ocean

• DMI is experienced with SST and Ice Surface Temperature data processing through Eumetsat (OSI-SAF), ESA (CCI) and EU (MyOcean) projects.

• Arctic SST reanalysis product (1985-present) will be available from end of the year (within other project)

• 15 years combined SST and Ice Surface Temperature data record will be developed within NACLIM, based upon AVHRR observations.

• Both Level 3 (with gaps) and level 4 (gap-free) fields will be produced.

• Special attention will be on error characterization and uncertainties

• Objective: to demonstrate the impact of improved data on the forecast skills.



Combined satellite SST and IST for the Arctic Ocean

Level 3 example of Ice, Sea and Marginal Ice Zone – Surface Temperatures from METOP AVHRR

References:Tonboe, R. T., Dybkjær, G. and Høyer, J. L.Simulations of the snow covered sea ice surface temperature and microwave effective temperature, Tellus , 63A, 1028–1037, 2011

Høyer, J. L., Ioanna Karagali, Gorm Dybkjær, Rasmus Tonboe, Multi sensor validation and error characteristics of Arctic satellite sea surface temperature observations, Remote Sensing of Environment, Volume 121, June 2012, Pages 335-346, ISSN 0034-4257, 10.1016/j.rse.2012.01.013.

Dybkjær, G., Høyer, J., Tonboe, R., 2012. Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data. In press, Ocean Sci., 9, doi:10.5194/osd-9-1009-2012, 2012.



Combined satellite SST and IST for the Arctic OceanLong term satellite datasets with uncertainties for model validation and assimilation: ice surface temperature and ice concentration


de Steur et al. 2012 (in prep)

Preindustrial



Freshwater content relative to S=34.8

Arctic Ocean+Baffin Subpolar North Atlantic GIN Seas

8000 km3

Historical RCP8.5



The Arctic FW reservoir appears weakly constrainedDistributions may suggest two modes? - no significant atmospheric mode identified

FWC (103 km3)



Difference in SLP between high and low anomalies in FWC changes

• Changes in FWC are driven by multi annual variations in AO• Results are consistent with the concept of a cumulative process of

uncorrelated variability with AO constituting the signal. • If so, the autocorrelation of the FWC is practically unlimited and

predictable• but this was not what we expected to establish…

No relation – no concern !



The research leading to these results has received funding from the European Union 7th Framework Programme (FP7 2007-2013), under grant agreement n.308299

NACLIM www.naclim.eu

steffen m olsen, polar oceanography, dmi, copenhagen dk ct3 hamburg 22-23/4 2013 geomar (6) mojib...

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