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MyOcean2 First Annual Meeting – 17-18 April 2013

Development of coupled atmosphere-wave-ocean predictions Adrian Hines, Ann Shelley, Tim Johns, Isabelle Mirouze, Dan Lea – Met Office Peter Janssen, Øyvind Breivik – ECMWF Including work supported by MyOcean2 WP19.4.1. MyOcean2 First Annual Meeting – 17-18 April 2013. Context.

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MyOcean2 First Annual Meeting – 17-18 April 2013

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  1. Development of coupled atmosphere-wave-ocean predictionsAdrian Hines, Ann Shelley, Tim Johns, Isabelle Mirouze, Dan Lea – Met Office Peter Janssen, Øyvind Breivik – ECMWF Including work supported by MyOcean2 WP19.4.1 MyOcean2 First Annual Meeting – 17-18 April 2013

  2. Context • Coupled ocean-atmosphere modelling is long-established • Manabe and Bryan, 1969 • Driven by climate modelling requirements • Latest generation coupled climate models at high resolution • Also applied for seasonal forecasts • Short-range forecasts generally use forced models • Coupled atmosphere-wave forecasts are an exception • Development of coupled ocean-atmosphere-wave short-range forecasts is an emerging activity • This talk will aim to illustrate some of the progress that is being made • Contributions from work within WP19.4.1, from MyWave, and from Met Office and ECMWF initiatives Then Now MyOcean2 First Annual Meeting – 17-18 April 2013

  3. Content • A starting point: application of existing coupled models to short-range forecasts • Developing a more sophisticated approach: • Coupled data assimilation • - Including waves • - Coupled atmosphere-waves • - Coupled ocean-waves • - Ensemble coupled prediction • - Summary and future prospects for coupled short-range ocean-atmosphere-wave forecasts MyOcean2 First Annual Meeting – 17-18 April 2013

  4. Application of existing coupled models to short-range forecasts • CoupledNWP case studies undertaken at the Met Office using the HadGEM3 coupled model • Similar to system used in Met Office seasonal forecasts and from which MyOcean2 global coupled forecasts will be delivered MyOcean2 First Annual Meeting – 17-18 April 2013

  5. Application of existing coupled models: Verification in the Tropics 500hPa Height DJF 925hPa T JJA BIAS BIAS • Two examples of good coupled skill relative to atmosphere-only control forecasts • Tropics is the main area of atmospheric performance difference • Performance mostly comparable in the extra-tropics Atmosphere only Coupled RMS RMS RMSE T+ 1 5 10 15 T+ 1 5 10 15 MyOcean2 First Annual Meeting – 17-18 April 2013

  6. Application of existing coupled models: A synoptic case study Bay Of Bengal Tropical Monsoon depression August 2008 – Day 3 Forecasts Central pressure (<990hPa) captured by day 3 in coupled model forecast but atmosphere control has shallower depression. Additional skill comes from interactive ocean – see cooling in BoB in evolution of the SST (day 3-day 1: colour shading) 990 Analysis 990 992 Atmos Control Coupled Model MyOcean2 First Annual Meeting – 17-18 April 2013

  7. Application of existing coupled models: SST verification Coupled outperforms ocean-only control forecasts at all lead times (for RMSE and bias, winter and summer) MyOcean2 First Annual Meeting – 17-18 April 2013

  8. Application of existing coupled models: Conclusions • Straightforward approach to apply coupled model to initialised short-range forecasts • Shows promise for improving short range forecasting skill • Coupled NWP forecasts generally • Are competitive with atmosphere / ocean-only control forecast skill in the extra-tropics • Show improvements in skill in the tropics in both the atmosphere and ocean components • Provides a good starting point for development • Potential to improve various aspects of the system MyOcean2 First Annual Meeting – 17-18 April 2013

  9. Coupled Data Assimilation Three options for initialising a coupled forecast: Uncoupled DA Weakly coupled DA Strongly coupled DA DA Forecast Atmosphere Ocean Coupled MyOcean2 First Annual Meeting – 17-18 April 2013

  10. Development of weakly coupled DA Met Office developing a weakly-coupled DA system Background field: 6-hour forecast from HadGEM3 Atmosphere DA: Met Office 4DVar (Rawlins et al., 2007) Ocean and sea ice DA: NEMOVAR (Mogensen et al., 2009)

  11. Coupled DA: Impact on SST Ocean DA only Coupled DA Daily average SST difference from OSTIAfor 23/11/2010. Note that the ocean DA is not identical FOAM Coupled DA RMS (solid) and mean (dotted) error for SST background state minus in situ observations

  12. Coupled DA: Impact on relative humidity Atmosphere DA only Coupled DA Mean RMS Relative humidity analysis error vs. observations on the Northern Hemisphere sea and ice points

  13. Coupled DA: Conclusions • A weakly-coupled data assimilation system has been developed • Initial tests show some potential benefits • Further development and investigation underway • Some key challenges: • Initialisation shock • Treating coupled biases • Coupled error covariances • Longer term aim to develop fully coupled data assimilation MyOcean2 First Annual Meeting – 17-18 April 2013

  14. Atmosphere – Wave coupling CD10N x 1000 U10N (m/s) • Atmosphere slowed by growing ocean waves through wave-induced stress • Energy loss to the ocean dependent on the state of the ocean waves • Steep wind waves remove more energy than gentle ’swells’ • Sea state dependent drag has impact on medium-range and longer time scale • Various approaches to specifying sea-state dependent drag • Parameterise based on wave age or wave steepness • Calculate by integrating wave model input source term [Janssen et al, 2004] • ECMWF have used coupled A-W system for medium range forecasts for many years Use of wave-induced stress improves drag coefficient (Figure: J. Edson)

  15. Atmosphere – Wave Coupling Synoptic example: ECMWF 4-day forecast of surface pressure over the North Atlantic Valid for 19 February 1997 Atmosphere only Low 952 Analysis Low 961 Coupled Atmosphere Wave Low 959

  16. Ocean – Wave coupling • Wave effects on ocean circulation result from a number of processes: • Wave-breaking induced production of TKE • Langmuir turbulence • Stokes Drift • Stokes-Coriolis forcing • Sea-state dependent momentum fluxes and drag • ECMWF developing ocean-wave coupling in NEMO • Testing impacts in 20-year runs • ORCA1 with 42 levels and 10m top layer • ERA-interim forcing with bulk formulae • Sea-state information from WAM • Processes included

  17. Ocean – Wave Coupling Combined impact on SST averaged over a 20 year period

  18. Wave coupling - conclusions • Atmosphere-wave coupling long-established • Positive impact on NWP forecasts has been demonstrated • Ocean-wave coupling in development • Evidence of significant impact on SSTs • Atmosphere-ocean-wave coupled system is the longer term aim • Mainly a technical challenge once processes are included in model components

  19. Ensemble Coupled Prediction • Ensemble coupled prediction systems are in operation at the Met Office (GloSea5), and in development at ECMWF • Typically have access to large supercomputer resources • Can be used to provide an ensemble of coupled short-range forecasts • ECMWF investigated impact of using a coupled model ensemble • Results for 16 cases with 50 members in the ensemble running a T639 (c. 30km) - 1⁰ model • Analysis of the probability distribution of temperature at 200 hPa in the Tropics • Continuous Ranked Probability Score (CRPS) is used • Measures RMS error in modelled cumulative PDF against observed occurence • Smaller CRPS means better skill

  20. Ensemble Coupled Prediction Coupled Persisted SST t200hPa in Tropics: CRPS Coupled CRPS – Persisted SST CRPS • Coupling with ocean gives large improvement • Systematic improvements also seen in the extra-tropics Bars indicate significance

  21. Ensemble Coupled Prediction - Conclusions • Ensemble coupled prediction systems are in operation and under development • Generally aimed at medium range to seasonal timescales • Can also provide ensemble of short-range coupled forecasts • Evidence of benefit of using a coupled model

  22. Summary • Recent years have seen a new focus on coupled systems for short-range forecasting • Experience being drawn from coupled climate modelling and seasonal forecasting communities • Straightforward approach of applying existing model shows potential • Good progress being made in other areas • Coupled DA • Ocean-atmosphere-wave coupling • Ensemble coupled prediction  Rapid R&D progress towards viable coupled short-range forecast systems

  23. Future prospects for coupled ocean-atmosphere-wave forecasts • Trials of coupled NWP, coupled DA and ensemble coupled predictions all show clear benefits of a coupled approach • Work underway will deliver high resolution global coupled ocean-atmosphere-wave systems • Ocean and waves are relatively cheap compared to atmosphere • Natural step from current systems to fully coupled approaches  Real prospect of fully coupled NWP systems in the medium term

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