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Air-sea interaction in a seamless system. ORAS4 exploitation Documentation: Techmemo and invited paper to QJ Engaging with CLIVAR/GODAE reanalysis intercomparison Dissemination: Reanalysis conference, data in public servers, web Scientific papers: Ocean Heat Content Hiatus (submitted) .
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Air-sea interaction in a seamless system ORAS4 exploitation Documentation: Techmemo and invited paper to QJ Engaging with CLIVAR/GODAE reanalysis intercomparison Dissemination: Reanalysis conference, data in public servers, web Scientific papers: Ocean Heat Content Hiatus (submitted) Two different streams of work • From ORAS4 to the next system Upgrading software (NEMO/NEMOVAR) Coupled Data Assimilation SeaIce modelling and prediction SeaIce initialization High resolution ocean Modelling air-sea interaction
ECMWF Ocean reanalyses used by the external community Seasonal Forecasting (COLA) Decadal Forecasting (MPI) Above) Initializing NCEP SF model with NEMOVAR results in improved forecast skill (better than simple multimodel). From Zhu et al GRL 2012. Right) Initializing the MPI decadal forecasting system improves their decadal predictions (year 2). Courtesy of H. Polhmann.
Trends, Volcanic Eruptions, ElNino cooling and Hiatus periods in ORAS4 Submitted to GRL
ECMWF NEMOVAR references • COMBINE-NV • Balmaseda M.A., K. Mogensen, F. Molteni, A. Weaver, 2010: The NEMOVAR-COMBINE ocean re-analysis. COMBINE Technical Report No 1. • Zhu J., B. Huang, L. Marx,J. L. Kinter III, M.A. Balmaseda, R.-H. Zhang,and Z-Z Hu, 2012: Ensemble ENSO hindcasts initialized from multiple ocean analyses. Geophys. Res. Lett., 39, L09602, 7 PP.,doi:10.1029/2012GL051503 • Zhu J., Bohua Huang, and Magdalena A. Balmaseda, 2012: An ensemble estimation of the variability of upper-ocean heat content over the tropical Atlantic Ocean with multi-ocean reanalysis products. Clim. Dyn. 39, 1001-1020. doi: 10.1007/s00382-011-1189-8 • ORAS4 • Mogensen K., M. A. Balmaseda, A. Weaver, 2012: The NEMOVAR ocean data assimilation system as implemented in the ECMWF ocean analysis for System 4. ECMWF Technical Memorandum 668. 59 pages. • BalmasedaM.A,. K. Mogensen, A. Weaver, 2013: Evaluation of the ECMWF Ocean Reanalysis ORAS4. Q. J. Roy. Met. Soc. Accepted.
ORAS4 in the public domain ECMWF web pages. Graphics and documentation http://www.ecmwf.int/products/forecasts/d/charts/oras4/reanalysis/ EasyInit, Hamburg: Data (ORCA1, 1x1 grids), LAS and DODS servers http://icdc.zmaw.de/easy_init_ocean.html?&L=1 APDRC, Hawaii: Data (ORCA1, 1x1 grids), LAS and DODS servers http://apdrc.soest.hawaii.edu/datadoc/ecmwf_oras4.php Re-analysis.org web: earth system reanalysis site http://reanalyses.org/ocean/overview-current-reanalyses NCAR Climate Data Guide: https://climatedataguide.ucar.edu/guidance/oras4-ecmwf-ocean-reanalysis
Spin up of activities on several fronts 2011 2012 ORAS4 & S4 Ocean Model Version: NEMO v3.0 Data Assimilation: NEMOVAR l30e12 Resolution: ORCA1_Z42 Forcing: Flux SeaIce: Prescribed Coupler: OASIS ORAS4 & S4 Ocean Model Version: NEMO v3.4 Data Assimilation: NEMOVAR l34e? Resolution: ORCA1_Z42, ORCA1_Z75, ORCA025_Z75 Forcing: Flux and Bulk SeaIce: LIM2 Initialization and coupling Coupler: Single exe SI Initialization SI Model & Predict HighRes DA KM HighRes coupled Project buroc Air-Sea Interaction Documenting transition Coupled Data Assim Steady progress in many directions
AMOC volume flux (Sv) at 26 N HIGH RES CTL-1 ASM-1 CTL-025 ASM-025 ORA4 CTL Runs ASM Runs
Temperature RMS errors Salinity RMS errors CTL-1 ASM-1 CTL-025 ASM-025 ORA4 1 degree 1/4 degree
Temperature bias and increment at 100m (198909) ASM-025 ASM-1 FG – OBS FG - OBS Incrememt Increment
SEA-ICE assimilation using Nudging In PIOMAS, X is a function of the innovation as follows: • Experiments: K=cte and K_PIOMAS • Result: Ice Thickness (unconstrained) very sensitive to the nudging scheme • Comments: • The PIOMAS expression is somehow ad-hoc, not easy to apply to a variational formulation. • Importance of the flow dependence. Can we find an alternative effective flow dependent formulation for background error? • One possibility is the log transformation (so ice concentration errors are Gaussian), but this is not enough or not trivial (a,b,c). Non linear K (Rα=0.01) Typical values ( α=6 and Rα=0.01) α = 3, 6 , 9 X-Sea-ice. Bounded Non Gaussian Y-transformed. Gaussian.
Summary • Exploitation and divulgation of NEMOVAR ORAS4 • Transition to NEMO V3.4 and NEMOVAR V3.4 • NEMOVAR working in ORCA025 • Sea Ice sensitivity to nudging schemes. Alternative variational formulation. • Still need improvement • Weak AMOC at 26N. • Tuning NEMOVAR/NEMO namelists for ORC025. MetOffice background errors wanted. • Sensitivity tests of DA window, spin up • Apply direct bias correction • Include new OSTIA SST dataset • MDT. MetOffice algorithm wanted. • Apply sea surface height assimilation • ……