© Crown copyright Met Office Accuracy of Ocean Forecasts and Future Priorities Mike Bell 11 May 2011

© Crown copyright Met Office Outline Some verification statistics Temperature profiles Daily mean surface currents near equator (Pat Hyder) Examples of improvements/sensitivity studies Sediments (Peter Sykes) Vertical coordinates Vertical mixing Atmosphere ocean coupling (Catherine Guiavarc’h) Future priorities Focus is on modelling

© Crown copyright Met Office RMS Accuracy of MyOcean / Mercator Profiles (Figure 26) What is useful ? Analysis Initialised 3 day 6 day Climate TemperatureSalinity Surface 500m Global statistics from Dec 11 – Feb 12 Significant level of skill in analyses/forecasts Interesting regional variations in statistics

© Crown copyright Met Office MyOcean / Met Office SST forecasts VariableForecast day 1 Forecast day 3 Forecast day 5 SST ( o C) (surface drifters) Skill compared to persistence should be a major focus Assessments should consider diurnal variations Results depend on quality of observation datasets

© Crown copyright Met Office Equatorial current structure An. Mn versus Obs. at 140 o W Wang (2005), Johnson et al (2001) Flow structure generally similar, except for vertical extent Sub surface counter currents not fully resolved Note – one would expect difference in flow depth due to La Nina -10 Latitude Zonal Velocity m depth 0m ASM 2008OBS 91-99

© Crown copyright Met Office Equatorial structure and flows An (10S to 10N – 140W) ASM ASM FREE FREE Equatorial undercurrent slightly too strong in free run SEC too strong on equator and too weak in southern branch T U

© Crown copyright Met Office Global Tropical Moored Buoy Array ~45 surface current sites Not many sites with 100m currents

© Crown copyright Met Office Taylor Diagrams at all locations Zonal surface velocity Global ASM Global FREE General improvement in skill for ASM c.f. FREE run Less low correlations for ASM c.f. FREE run

© Crown copyright Met Office Taylor Diagrams for Indian Ocean Zonal surface velocity Global V1 High res V1

© Crown copyright Met Office Some Improvements and sensitivity studies - Sediments - Hybrid vertical coordinates - Vertical mixing - Atmosphere ocean coupling

© Crown copyright Met Office Sediment Model Modifications (Peter Sykes) Base-line sediment model Souza, Holt & Proctor (2007) New settling velocities (so new sizes) – ms -1 for the fine and ms -1 for the coarse to provide a background population and a more dynamic resuspendable population. Decrease in critical erosion term – to make it easier to erode sediment (was 0.4ms -1 flow now 0.2ms -1 ) Terrestrial sediment sources are now all fine – were all large, quickly sank and remained on bed Increased bed initialisation to 300gm -2 for entire domain and 0gm -3 sediment in water – the bed was a “reflection” of the surface satellite images, now uniform to provide a “purer” result

© Crown copyright Met Office Sediments (gm -3 ) Satellite-model data intercomparisons for 2009 (Peter Sykes) Original model Satellite data Improved model winter spring summer autumn

© Crown copyright Met Office Vertical coordinates Use of Song and Haidvogel S-σ stretching. Uses geopotential (Z) levels at high coordinate slope Minimises coordinate slope errors whilst maintaining vertical resolution. In practice a small number of cells <<1% intersect with sea bed small loss of active cells vs significant improvements in numerical accuracy Schematic on the Z*-S-σ coordinate system over-emphasises the “disappearing” coordinates for illustrative purposes Potential to use z-tilde (LeClair & Madec 2010?)

© Crown copyright Met Office The S-coordinate Pressure Gradient Error problem Pressure Gradient Errors in hybrid Z*-S coordinates green=0cm/s, red=+20cm/s, blue=-20cm/s POLCOMS Z-interpolation NEMO PressureJacobian (Hedong Liu, NOC) NEMO +hybrid Z/S coords Surface velocities

© Crown copyright Met Office Jun-Aug 2008 top minus bottom temperature difference Stratification and frontal locations closer to ICES climatology in NEMO than POLCOMS Improvements mainly due to better TKE scheme NEMOPOLCOMSCLIM

© Crown copyright Met Office Model drift diagnostics (Dave Storkey) Diagnose model biases by looking at short-term drift from initial state: time-mean increments time-mean forecast errors time-mean trends Benchmarking and sensitivity studies. Use of trends to try to identify cause of errors.

© Crown copyright Met Office Annual mean temperature increments (K/day) 10m V1 V0 50N section in Pacific 100m 0m 400m

© Crown copyright Met Office Impact of Burchard (2002) change to TKE scheme (August 2007) new TKE old TKE 1 day forecast – anal error daily-mean trend from ZDF 0m 400m 0m -0.2K0.2K -0.2K0.2K

© Crown copyright Met Office SST diurnal cycle in ORCA025L50 (Pacific warm pool 170W 2N) 3-hourly fluxes operational at V1 28.5ºC 30.5ºC rms = 0.15ºC rms = 0.18ºC (Catherine Guiavarc’h) 0 20Day in September Temperature

© Crown copyright Met Office Impact of including currents in wind stress calculation one-month run (Sep 09) wind stress calculated from Smith (1980) with or without effect of currents other fluxes as normal Change in zonal currents at surface Change in zonal currents on equatorial Pacific Depth (m) Velocity (cm/s)

© Crown copyright Met Office Future Priorities - Coupled ensemble forecasts with ORCA025 and N216 or N320 Charnock parameter Langmuir circulations & other diurnal surface layers (temperatures and currents) SST response to storms (weather f/c skill for 3-5 days) correct phasing of MJO - Diagnosis of Biases Mixing parametrisations Parametrisation of form drag (Gent / McWilliams) ?

© Crown copyright Met Office Equatorial drift in ORCA025 ASM-FREE 2008 Temperature La Nina strength too weak in FREE c.f. ASM Consistent with too weak equatorial wind forcing which is ~5% too weak in NWP (Ingelby, 2010) Momentum mixing & form drag parametrisations ? 0m 400m