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Atmospheric Forcing Fields for Ice-Ocean Models Axel Schweiger University of Washington Applied Physics Lab Polar Science Center Missing Atmosphere • Need to specify energy exchange at the ice/ocean atmosphere boundary • All “forced” climate variability needs to be transferred from the atmosphere to the ocean Overview • Components of atmospheric forcing fields • Sensitivity of simulations to forcing • Data sources. Choices to make • Highlights of some differences • Problems • Bibliography P S E F QE QH Sea Ice R F S NetR=F -F+S-S QH QE From Lindsay, 1998 How do you do it? • Flux fields often not available • Specify near surface state of “atmosphere” from better • • known quantities (pressure, wind, near surface temperature, humidity, …clouds) Parameterize heat exchange as functions of near surface atmospheric state and model SST/IST using bulk formulae In the open ocean: Model can be forced/restored to SST directly Wind Stress C U U a D z z Surface Stress a : Density of air C D : Neutral Stability Coefficien t for Drag U z : Vector difference in between wi nd at height z and surface Sensible Heat Flux QH c C a p H z TSST / IST U QH Sensible Heat Flux a : Density of air c p : Specific heat of air C H : Neutral Stability Coefficien t for Heat z : Potential temperatu re at reference height z TSST / IST : Air/Surfac e interface temperatu re Sea/Ice/Sn ow Surface Temperatur e U z : Difference in wind speed between wi nd at height z and surface z Latent Heat Flux QE C qz q0 U a E z QE Sensible Heat Flux a : Density of air CE : Neutral Stability Coefficien t for Evaporatio n q z , q0 : Specific humidity at reference height z and surface U z : Difference in wind speed between wi nd at height z and surface Turbulent exchange C U U a D z z QH c C a p H z TSST / IST U QE C qz q0 U a E z z Depend on: •Stability •Roughness •Reference Height z Parameterized LW Radiation: F Longwave down Fluxes at Sheba RMS: 12 Wm-2 R^2 : 0.96 Parameterization for LW: (Efimova, 1961, Jacobs) F clr =*Tair4*(0.746+0.0066*q) FcldFclr*(1+0.26)*Ct Inputs: • Ct: Cloud fraction (Metobs) • Tair : ETL Tower • q : specific humidity (saturated/ice) Parameterized SW Fluxes (SHEBA) May - August Shine Parm. Inputs: • C: Cloud Fraction, Sheba Metobs a: albedo, ETL/Tower : optical depth, Inverted monthly average Solar zenith angle • e: water vapor pressure R2 : 0.88 RMS : 28 Wm2 S cldy 53.5 1274.5 cos( ) (1 0.139(1.0 0.935a ) S o cos( ) 2 1.2 cos( ) (1 cos( ) * 0.001e _ 0.0445) S clr (1 C ) S cldyC S clr Stot See Key et al. 1996 for a systematic evaluation of radiation parameterizations in the Arctic Sensitivity Studies: • Wide range of studies examine sensitivities. • (Perturbation/Substitution) 1-D ice models – – – – Maykut and Untersteiner, 1971: Snow Shine and Crane, 1984: Clouds Curry et al 2002: Various Makshtas, 2007: Various – – – – Harder et al., 2000: Wind Rothrock and Zhang, 1996: Radiative Fluxes Holland, 1993: about everything Hunke and Holland, 2007: Different forcing data sets • 3-D Radiation: Forcing Variable H Ice Downwelling shortwave radiation S 10 Wm-2 20 cm Downwelling longwave radiation F 10 Wm-2 50 cm Ice Export: 2%/Wm-2 (LW), Lemke et al, 2000 After Rothrock and Zhang, 1996 Wind: Fram Strait Ice Export From Harder et al. 2000 Tair, p, u, q, c Control NP forcing NCEP clouds Makshtas et al. 2007 Thermodynamic only Model All NCEP forcing Temporal Resolution monthly Daily Curry at al. 2002 Hourly and 6-hourly Not just ice: Changed Ocean Circulation Hunke and Holland, 2007 Ocean Currents at 466 m depth a) modified AOMIP b) original AOMIP Sensitivity Summary • Small changes in forcings have large impact • Smaller components of the heat budget are still important! • Thermodynamics-only models more sensitive. Negative Thermodynamics/Dynamics feedback Sources for Forcing Data • Global/Arctic domain • In-situ Observations/Climatologies • Weather Models (Reanalysis, Operational) (data assimilation to improve initial conditions for forecast) • Satellite Data • Hybrid Data Sets • Reconstructions Reanalysis Data Sets Name Period Available Temporal Resolution Spatial Resolution Assimilation Scheme Comment NCEP/NCAR Renalysis (1) 1948-present 6-hourly T62 (2x2 Deg) 3D Var? Most widely used NCEP/NCAR DOE 2 1979-2008 6-hourly T62 ( 2x2 Deg) 3D Var Some bug fixes ERA-15 1979-1993 6-hourly T106 (1.1 Deg) OI ERA-40 1958-2002 6-hourlyu T159 (1.1 Deg) 3D Var ERA-Interim 1989-present 6-hourly T255 (0.75 Deg) 4D Var JRA-25 1979-2007 6-hourly T106 (1.1 Deg) 3D Var MERRA (NASA) 1979-present Hourly 0.5 Lat, 0.77 Lon 3D Var NCAR/CIRES 20th Century Renalysis 1908-1958 6-hourly T62 (2x2 Deg) EKF Only surface pressure assimilated On the Horizon • NCEP: CFSSR: Climate System Reanalysis and Reforecast, 1979-2009, T382 (35 km), Interactive Ocean/Sea Ice model. Starting in 2010? • JRA-55: 1958-2012. T319, 4D Var. Production starting in 2009 • ERA-70 ? Walsh and Chapman, 2009 Cloud Anomaly June-August 2007 ( w.r.t 2000-2006) NCEP Schweiger et al. 2008 MODIS Adjusted Renalysis: NCEP-ADJ NCEP DSW corrected to ERA-40: 29 Wm-2 RMS daily means (NCEP-ERA-40) Precip NCEP R1 MERRA 1-day sample of daily-averaged precip Buoy locations by type from 1980-2006 TAD Buoy Not all buoys are the same! …and they don’t seem to measure the same thing Annual cycle of difference between in situ observation and NCEP R1 by Observation Type OBS – NCEP(R1) OBS – NCEP (R1) OBS – ERA40 Contours: ERA40 – NCEP(R1) Circles: Obs – NCEP(R1) Hats: NP – NCEP(R1) Difference between ERA40 and NCEP R1 is largely due to incorporation of buoys! Satellite-derived Products Tskin, S , F • Global: – ISCCP 1983-2008, global, D: clouds, FD: radiative fluxes – SRB: Based on ISCCP, radiative fluxes, Tskin • Arctic: – TOVS (1980-2006, N60) • Path-P: Cloud fraction, Tskin • Path-P derived: Downwelling Longwave • Path-P PFLX: Parameterized (SW, LW) – APP-X: 1983-2004 AVHRR-derived, radiative fluxes, Tskin (all-sky) Option: Hybrid Data Sets • Pick/choose parameters • Correct/adjust others – AOMIP Forcings – Large and Yeager, 2004, 2008 – Modified AOMIP – Roeske, 2006 (OMIP) based on ERA-15, NYF • Adjusted NCEP radiation AOMIP forcing set Wind From SLP NCEP/NCAR-R1 Air Temperature NCEP/NCAR- R1 Humidity Fixed to 90% Clouds OMIP v.2 (ERA-15 climatology) Shortwave Radiation Downwelling: Parkinson and Washington, 1979 (Zillman. 1972) using OMIP clouds. fixed humidity Longwave Radiation Net: Rosati and Miyakoda, 1988, OMIP clouds, NCEP/NCAR Tair Model SST/IST, fixed humidity Precipitation Serreze and Hurst, 2000 Climatology Large and Yeager, 2004, 2008 Variable Source Adjustment Wind NCEP/NCAR-R1 Spatially varying ncreased globally to match Scatterometer measurements (most in tropics/high lats Air Temperature NCEP/NCAR-R1 Corrected to IABP/POLES in the Arctic, Antarctic Minimum Specified Humidity NCEP/NCAR-R1 Reduced spatially varying, 3% minimum Clouds Not Needed Shortwave Radiation ISCCP-FD Reduced by 5% between 50S and 30N Longwave Radiation ISCCP-FD Reduced by 5 Wm-2 in the Arctic to increase sea ice thickness Precipitation Multi-Source (Xie and Arkin) Defaults to NCEP/NCAR in the Arctic LY 2008=> CORE-1 (NYF) , CORE-2 Forcing (Inter-annual) RÖSKE, 2006 (P-OMIP) • Based on ERA-15 (1,2) /ERA-40 (version 36) • NYF (representative annual cycle) • Budget closure, adjustments to match measured oceanic transport http://www.omip.zmaw.de/omip/overview.php Hunke and Holland, 2007 Variable Source Adjustment Wind LY-04, NCEP/NCAR-R1 Spatially varying increased globally to match Scatterometer measurements (most in tropics/high lats Air Temperature LY-04, NCEP/NCAR-R1 AS LY04, Corrected to IABP/POLES in the Arctic, Antarctic Minimum Specified Humidity LY-04, NCEP/NCAR-R1 (additional reduction) Limit to 100% over ice Clouds P-OMIP (Roeske, Version 2, ERA-15) Shortwave Radiation As original AOMIP, Parkinson and Washington, P-OMIP clouds Same as AOMIP Longwave Radiation As original AOMIP, Rosati and Miyakoda, 1988 Slightly different from AOMIP because of different Temperature Precipitation LY04 Normal Year Defaults to NCEP/NCAR in the Arctic Issues with Hybrids • Choices are difficult to make • Inconsistent Forcing Fields • Adjustments may alter sensitivities Sensible Heat Flux: Affected by Radiation ISCCP-FD Radiation Observed (Lindsay,1998) Modified AOMIP From Hunke and Holland, 2007 AOMIP Model Validation Ice Extent NET Cloud Forcing (Radiative Effect) at SHEBA (1998) Data from Intrieri 2002, Key and Wang, 2005 Albedo is low enough Problems lack of Atmosphere • Lack of feedback Initial State Cold Air Ice Coupled “Real” World Cold Air Ice Warm Air Ocean Ice-Ocean Model World Warm Air Ocean Model Ice Edge Movement Cold Air Ice Warm Air Ocean Model Ice Edge Movement From Griffies et al. 2008 Conclusions • Models are highly sensitive to forcing parameters • Accuracy of forcing fields is still lacking • Tuning of models remains a necessity – But: Are sensitivities to climate variations maintained? • Keep in mind: Lack of atmosphere ocean feedback