Method to force surface salinity

Arctic fresh water content

Force surface salinity

Problem:

Could be unstable and/or produce unphysical oscillations

Solution:

Use partially coupled climate models (simple but costly)

Other suggestions?Gerdes, Hurlin & Griffies, 2006

Coupled models much more stable

1. Heat advection feedback counters salt advection feedback

2. Almost closed water balance at each time Example

- increase in run-off into the Arctic Ocean- Reduction in meridional transport of salt- Accumulation of salt in the subtropics (enhanced by the

atmospheric transport of water from the subtropics into the Arctic)

- Transport of more saline water northward

20th century forcing for global ocean-sea ice models

Rüdiger Gerdes

Availabe data and methods

Reconstruction for the Arctic Ocean (Kauker et al., JGR, 2009)

CALYPSO climate reanalysis project (failed to get funded)

Reanalysis projects for the 20th century (Compo et al., BAMS, 2006)

CALYPSO - ClimAte variabiLitY assessment through re-analyses of PaSt Oceanic data

In summary, the specific goals of CALYPSO are the production of: • ORE-50 (1958-2008): Ocean RE-analyses at highest horizontal and vertical resolutions with different models/assimilation schemes for the ocean essential variables at global and regional (Pan- European Seas) scales forced with atmospheric forcing from 1958-2008 produced specifically for CALYPSO inside the project and derived from the ECMWF ERA-40 and other forcing data set. • ORE-120 (1888-2008): Ocean RE-analyses for the ocean essential variables with different models/assimilation schemes at global and regional (Pan-European Seas) scales forced with AMIP forcing from 1888-2008 produced specifically for CALYPSO for the period 1888-2008. • REP-120 and REP-50: REProcessed multi-satellite and in-situ observational data for the period 1888-2008. • REC-120 and/or REC-50: REConstructed data sets using statistical algorithms for the longest possible period.

CALYPSO produces both purely observational analyses or ‘REConstructions’ (REC) and the so-called ‘Ocean RE-analyses’ (ORE) that meld numerical general circulation model information with observations. It uses the longest time series of relevant ocean climate variables available in historical archives already available at European level. The present-day project organizing the archives of the ocean data is SeaDataNet, in which many of the CALYPSO partners also participate. CALYPSO makes use of the metadata infrastructures build by SeaDataNet and MyOcean and uses both satellite and in-situ observations from both services.

Reconstruction of atmospheric forcing(as in Kauker et al., 2009)

Can be done in many different ways. Needs to be validated – if possible.

Needs expertise and time.

Can not yield patterns that are not present in the tuning period. (In our case: Tuning period 1948 – 1978 instead of 1958 – 1988 did not reproduce the recent warming anomaly.)

Have ot be aware of possible overfitting.

Can give results that are in better agreement with station data than reanalsis.

Reconstruction for the 20th century

Reconstruct sea ice thickness for the whole 20th century- have to use ocean-sea ice model- needs atmospheric forcing- reconstructed forcing has to be validated

Reconstruction of forcing:-redundancy analysis linking NCEP with observational data (station data and gridded data)-validation for periods where comprehensive datasets are available-validation using sea ice simulation and „observed“ sea ice extent for the 20th century-The method yields pairs of patterns of the predictor (station data) and the predictand (model grid) in which the predictand pattern is optimized to represented the highest possible variance in the fitting period.

AWI-wichtigste DatenStation data from 1900 to 1997:

Number of missing monthly values (1900 - 1997) for surface air temperature

Kauker, Köberle, Gerdes & Karcher, JGR, 2009

AWI-wichtigste Daten2nd redundancy mode for two SAT predictor datasets:

AARI data

AICSEX/IARC data

AWI-wichtigste Daten

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

-0.4

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^6 k

m^2

Zakharov

GSFC

REC NCEP

Simulated and observed ice extent :

1930s warm anomaly:

zonally averaged SAT anomalies (Johannesen et al., 2004)

00 10 20 30 40 50 60 70 80 90 00

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75-80 N

REC NCEP

fit3 val1 val2 val

merge iarc_tryck hadslp1.0-240 mslpg120

iarc_tryck

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ar

hadslp1.0-240 mslpg

merge iarc_tryck hadslp1.0-240 mslpg120

penalty sumII sumIII

mslpg-meanropts

Sea ice thickness reconstruction

30000

20000

10000

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km3

Trend: 110 km3/a±10 km3/a

CMIP3 vs. NAOSIM sea ice volume trends

30000

20000

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km3

AWI-wichtigste DatenClimate models underestimate the sea ice volume trend

hindcast

Km

^3/y

ear

Model #

The 20th Century

Reanalysis Project

Jeff Whitaker, Gil Compo, Nobuki Matsui and Prashant Sardesmukh

NOAA/ESRL and Univ. of Colorado/CIRES

The 20th Century Reanalysis

• What:– A 6-hourly reanalysis from 1892-present (1918-1949 done so far),

using only surface pressure observations.• Why:

– No daily gridded tropospheric-wide circulation dataset before 1948 exists.

– Evaluate models, understand causes for 20th century climate variations (e.g. 30’s U.S. drought, 20-40’s polar warming).

• How:– 56 member Ensemble Kalman Filter, T26L28 CFS03 model.– Includes analysis error estimate.

EnKFError=34 m

EC 4DVarError=31 m

EC 3DVarError=104 m

NCEPOperational

FIG. 2. Comparison of analyses of 0000 UTC 20 Dec 2001 500-hPa geopotential height from (top left) full NCEP–NCAR reanalysis using all available observations at all levels (> 150,000) and parallel assimilation experiments with a simulated 1895 network of only 308 surface pressure observations from (top right) EnsClim (rms difference with full NCEP–NCAR reanalysis is 95.7 m), (bottom left) EnsFilt (rms difference with full reanalysis is 49.2 m), and (bottom right) CDAS-SFC (rms differencewith full reanalysis is 96.0 m).

Blue dots indicate the location of the surface pressure observations used to make the experimental analyses.

The 5500-m line is thickened, and the contour interval is 50 m.

Summary• Accuracy: Mid-tropospheric circulation fields

about as accurate as a 3-day forecast today.• Timeline: 1918-1949 done, full 1892-present

done by end of 2008.• Data Access: Will be freely available from

NCAR, NOAA/ESRL and NOAA/NCDC. 1918-1949 in early 2008, rest late 2008/early 2009.

• For status updates, email jeffrey.s.whitaker@noaa.gov or gilbert.p.compo@noaa.gov

Twentieth Century Reanalysis (V1)

• Objectively-analyzed weather maps with uncertainty• 6-hourly, daily average, monthly values for 1908 – 1958• 2o by 2o, global grid

The analysis is performed with Ensemble Filter (Compo et al., 2006). Observations of surface pressure and sea level pressure from the International Surface Pressure Databank version1.1 and ICOADS version 2.4 were assimilated every six hours.

http://www.cdc.noaa.gov/data/gridded/data.20thC_Rean.html

Surface temperature April 1910

Arctic methods for evaluating simulations

Fram Strait 10+ years timeseries

Changes in Arctic hydrography

Difference fwc 2007 -

2006

Net freezing 2007 - 2006

Changes ... in fwc... in Atlantic Water properties... in river water distribution... in sea ice formation... in Pacific Water pathways

AWI-wichtigste DatenDecreasing ice thickness in the transpolar drift:

2004

2007

Haas et al., 2008

AWI-wichtigste DatenGroßräumige Verteilungen aus Computermodellen:

North Atlantic-Arctic Ocean-Sea Ice Model (NAOSIM)

Im Gegensatz zu den Klimamodellen werden hier Beobachtungen der Atmosphäre berücksichtigt (hindcast-Simulationen).

Tracers: 18O (meteoric water, run-off)Radioactive tracers (Atlantic Water)Silicate (Pacific Water)

Use of cost function of adjoint NAOSIM

Difference in 100m salinity (2080-2100) – (1980-2000) CCSM (20C3M, A1B, run1)

Difference in surface salinity (2080-2100) – (1980-2000) (20C3M, A1B, run1)

4

0

-4CCSM MPI

Fresh water content (rel. 35) (2080 – 2100) – (1980 – 2000)

CCSM MPI

AOMIP status

AOMIP: coordinated activities to improve models and model predictionsA. Proshutinsky1, R. Gerdes2, D. Holland3, G. Holloway4 and M. Steele5

Synthesis – to identify consistent errors across models, propose solutions, and find the most suitable and reliable coupled ice-ocean models for use in fully coupled regional and global climate models;

Process studies– to improve models, investigate processes using model results and observations. In particular, AOMIP focuses on: How to better model the arctic halocline which creates the stratification necessary to insulate perennial sea ice from the Atlantic Water layer? How to avoid restoring and flux correction? What is the role of different mechanisms influencing heat fluxes in the ocean - sea-ice - atmosphere system?

AOMIP also focuses on fresh water and heat problems to answer the fundamental questions: how does the fresh water/heat enter the Arctic Ocean system? How does it move about which includes phase changes, and how does it finally exit the system?

Under the process studies theme, AOMIP furthermore investigates the role of tides in Arctic climate, parameterization of stress-driven and convection-driven mixing and the role of small- meso- and large-scale turbulence (eddies and gyres).

The major contributors of the global change in Arctic climate are changes associated with atmospheric conditions and in the changes brought to the Arctic with the Atlantic water. The latter was the major topic of recent AOMIP studies and AOMIP will continue working with the Atlantic water role in the Arctic and global climate interaction.

AOMIP coordinated experiments

Bering Strait volume, heat and salt fluxes

Canada Basin: shelf-basin exchange and mechanisms Pacific water circulation (origin, forcing, pathways) Canada basin: major mechanisms of halocline formation and variability

Circulation and fate of fresh water from river runoff (pathways and seasonal transformation due to mixing and freezing)

AOMIP coordinated experiments (cont.)

Beaufort Gyre: mechanisms of fresh water accumulation and release (origin of the BG freshwater reservoir, sources and sinks, role of sea ice dynamics and seasonal transformations, Ekman pumping)

Fresh water balance of the Arctic Ocean: seasonal and interannual variability (sources, sinks, pathways)

Fresh water regional studies: diversion of liquid FW north of Fram Strait and impact of this on sea ice

Atlantic water circulation (circulation patterns, variability and heat exchange, model validation based on observations) Ecosystem experiments

Data assimilation and numerical methods

AOMIP activities

1. AOMIP collaborators were invited to organize a session in MOCA-09 (IAMAS, IAPSO and IACS Joint Assembly, to be held in July 19-29, 2009 in Montréal, Québec, Canada). Prior to that assembly, AOMIP collaborators are also participating in the modeling workshop “Arctic System Modeling Workshop III” (International Collaboration in Arctic System Modeling) to be held on July 16-17, at the University of Quebec at Montreal (UQAM)

http://www.iarc.uaf.edu/workshops/2009/arctic_system_model_09/

2. The AOMIP participants agreed to meet again in fall 2009 (October 21-23, 2009), at Woods Hole Oceanographic Institution to report about numerical experiments and other project results

AOMIP – WGOMD collaboration

Take advantage of a)Regional expertise in key regionb)Global exchanges, esp. Bering Strait – CAA/Fram Straitc)Identical forcing fields (CORE II)d)Data repository/postprocessing

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