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Met Office GPCI simulations

Adrian Lock. Met Office GPCI simulations. UK Met Office simulations in GPCI. HadGAM1 climate – for IPCC AR4 38 levels (~300m at 1km), N96 (~150km) HadGAM1a climate – development version for AR5 Operational forecast ~ HadGAM1a but different! 38 levels, N216 (~70km)

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Met Office GPCI simulations

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  1. Adrian Lock Met Office GPCI simulations

  2. UK Met Office simulations in GPCI • HadGAM1 climate – forIPCCAR4 • 38 levels (~300m at 1km), N96 (~150km) • HadGAM1a climate – development version for AR5 • Operational forecast ~ HadGAM1a but different! • 38 levels, N216 (~70km) • 5 day forecasts from ECMWF analyses (2003) • Dynamics and Physics ~same in both: • Grid-point model: semi-implicit semi-lagrangian scheme • PBL: K-profile+explicit entrainment; Ri scheme for SBL • Massflux: Gregory-Rowntree + aspects of Grant & Brown for shallow • Cloud: diagnostic RH scheme, Smith • Radiation: Edwards-Slingo

  3. Recent Model Changes Forecast upgrade 15th March 2006 • In both forecast and HadGAM1a but NOT HadGAM1: • Convection • Adaptive detrainment (A. Maidens, S. Derbyshire) • Boundary Layer • Revised marine scalar surface exchange (J. Edwards) • Non-gradient stress(A. Brown) • Sharp tailed stability functions over Sea (R. Beare) • Additional changes in HadGAM1a • Major overhaul of aerosols • Differences between forecast and HadGAM1 • cumulus cloud cover parametrization (esp. significant for shallow) • Interactive aerosols

  4. GPCI cross-section: problem • Problem with SSTs in the forecast model: • Unable to use ECMWF SSTs • Can’t use climate SSTs because those are for a 360 day calendar • Both these should become possible soon - rerun • Can’t easily include Met Office operational SSTs • My GPCI forecasts used a multi-year climatology [I discovered afterwards!]

  5. GPCI cross-section: JJA cloud cover • Colder SSTs in forecast model imply reduced surface fluxes compared to the climate simulations • Spin-up in surface fluxes during forecast (as atmosphere cools down to new SST?) Sensible heat flux (W/m2) Latent heat flux (W/m2)

  6. GPCI cross-section: JJA cloud cover Deep cumulus cloud-top falls during forecast, to ~ climate model level “Anvil” cloud cover increases during forecast to ~ HG1a amount < HG1 = Ad Detr Mean field 0 100 Differences

  7. GPCI cross-section: JJA cloud cover Stratocu cloud-top rises during forecast to reach ~ level in climate model Cloud cover increases Cloud cover excessive in 5 day forecast “transition region” – lack of GB CFCu

  8. GPCI cross-section: JJA cloud cover • Higher stratocu top associated with deepening BL during the forecast • BL also becomes more well mixed: • reduced near-surface RH • recall increase in surface fluxes

  9. Omega • Rise in cloud top not due to reduced subsidence • Ascent in ITCZ increases during forecast > climate

  10. GPCI cross-section: JJA cloud amounts • Reduced stratocumulus in HadGAM1a – reduced aerosol concentrations? • Cu cloud in forecast “transition region” gives large LWP by day 5

  11. Climate model TCA • Cross-section representivity? • Some quantitative difference between 5 and 1 year JJA • HadGAM1a still loses some Sc • Correctly reduced marine aerosol gives excessive precipitation at low LWP • Precip needs retuning? JJA 2003 JJA 5 years

  12. Zonal winds • Forecast spins up easterlies in tropics • HadGAM1a has weaker easterlies than HadGAM1

  13. Summary • Deep convection doesn’t penetrate high enough (as high as ECMWF analysis) • Stratocumulus thickens up and rises from EC analysis • Aerosol change between climate model versions highlights importance of drizzle • Persistent problems with Met Office models in Sc-Cu transition regions • GB shallow cu cloud fraction parametrization helps • Still tends to be too cloudy • Further work on interaction between cumulus and inversion

  14. Questions? Thanks!

  15. Tropical Temperature Errors vs SondesSummer 2005

  16. Tropical R. Humidity Errors vs SondesSummer 2005

  17. Tropical Wind Errors vs SondesSummer 2005

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