A data assimilation approach for reconstructing sea ice volume in the Southern Hemisphere
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1 Harmony on Ice 2 meeting Paris, Nov A data assimilation approach for reconstructing sea ice volume in the Southern Hemisphere F. Massonnet, P. Mathiot, T. Fichefet, H. Goosse, C. König Beatty, M. Vancoppenolle, T. Lavergne, L. Bertino
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3 Do you know Google Fight?
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6 NSIDC, Oct 20th 2011
7 10 6 km² Simulated sea ice extent (NEMO-LIM + atmospheric reanalyses) Average +/- 2 standard deviations
8 Arctic sea ice thickness (Louvain-la-Neuve sea Ice Model) Mean September September 2011 Volume 26,000 km³ Volume 10,000 km³ Lowest minimum of the model
9 Arctic sea ice: clear changes Arctic sea ice is shrinking [Comiso et al., 2008] is thinning [Kwok and Rothrock, 2009] is younger [Nghiem et al., 2007] has similar trends when simulated by climate models [Arzel et al., 2006] + these changes are significant
![Antarctic sea ice: complicated changes Trends of observed [OSISAF, 2010] sea ice concentrations, 1983-2007 Antarctic sea ice is slightly expanding [Turner et al.](/docs-images/79/79268438/images/10-0.jpg ", 2009] shows marked regional trends in concentration [Comiso and Nishio, 2008] thickness is not sufficiently sampled [Worby et al., 2008] simulated by models shows contradictory trends [Arzel et al.")
10 Antarctic sea ice: complicated changes Trends of observed [OSISAF, 2010] sea ice concentrations, Antarctic sea ice is slightly expanding [Turner et al., 2009] shows marked regional trends in concentration [Comiso and Nishio, 2008] thickness is not sufficiently sampled [Worby et al., 2008] simulated by models shows contradictory trends [Arzel et al., 2006] + significance is data set- and time period- dependent [%/decade]
11 «So, your claim is that Antarctic sea ice is more challenging?»
12 «So, your claim is that Antarctic sea ice is more challenging?» «Yes, that s why we d like to reconstruct its volume»
13 «But you just said observations of ice thickness were not well sampled»
14 «But you just said observations of ice thickness were not well sampled» «Let s use a model!»
15 «This model has probably biases»
16 «This model has probably biases» «It does. Let s go for some data assimilation!»
17 Ensemble Kalman Filtering x a = x f + K (d H x f ) [Evensen, 2003] [Sakov and Bertino, 2011] Analysis Forecast (daily, NEMO- LIM2, ORCA2) Kalman gain Includes obs. error and model forecast error covariance matrices Observations Global, daily sea-ice concentrations (OSISAF, 2010) Projection Interpolation modelobservation grids Observational errors: Model forecast errors: provided with the sea-ice concentration products 25 members, gaussian wind perturbations + + EnKF is statistically consistent Multivariate data assimilation No correction of freshwater budget
18 Multivariate DA the quest for the Holy Grail K = P f H T (H P f H T + R) -1 Variable X is impacted by assimilation of variable Y as long as they are correlated Mean absolute difference of sea ice thickness with respect to the ASPeCT data set [Worby et al., 2008], in different ocean sectors of Antarctica. «FREE RUN», resp. «ASSIM RUN» denotes the run without and with assimilation of sea ice concentration. mean Δh (m) FREE RUN ASSIM RUN Weddell Ind. Ocean West Pacific Ross Amund. Bel Whole Antarctica
19 Antarctic sea ice volume changes Anomalies of sea ice volume (NEMO-LIM2 + assim sea ice concentration), linear fits +/- 2 std and their trends km³/10y +1.9 km³/10y km³/10y km³/10y 50.3 km³/10y km³/10y
20 Antarctic sea ice thickness changes Trends of Antarctic sea ice thickness (NEMO-LIM2+assim sea ice concentration) [cm/decade]
21 How to explain these changes? On the large scale changes in volume follow those in extent increase attributed to increased winds due to ozone depletion? [Turner et al., 2009] enhanced ocean stratification due to warmer air temperatures? [Zhang, 2007] On the regional scale thickness trends follow concentration thinning in Amundsen/Bellingshausen Sea: remote effects of Soutern Oscillation? [Kwok and Comiso, 2002]
22 On the importance of errors K = P f H T (H P f H T + R) -1 Obs. covariance error matrix
23 On the importance of errors (ctd) February Antarctic sea ice extent OBS ASSIM-NEW ERRORS ASSIM-OLD ERRORS FREE Sea ice extent is not much sensitive to the update in observational errors
24 On the importance of errors (ctd) February Antarctic sea ice volume ASSIM-NEW ERRORS ASSIM-OLD ERRORS FREE Sea ice volume is sensitive to the update in observational errors
25 Arctic sea ice changes Anomalies of sea ice volume (NEMO-LIM2 + assim sea ice concentration), linear fits +/- 2 std and their trends km³/10y Change is more than 1 order of magnitude larger than in Antarctica (with opposite sign)!
26 Fram Strait - area FREE OBS ASSIM
27 Fram Strait - volume FREE OBS ASSIM
28 Recommandations Don t look at Antarctic sea ice as a whole («not all sea ice cells can t talk to each other») Take advantage of multivariate DA Never underestimate the potential of errors Keep in mind the limitations of the method
29 Thank you! Useful links This presentation is available:
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