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Sensitivity to the PBL and convective schemes in forecasts with CAM along the Pacific Cross-section Cécile Hannay, Jeff Kiehl, Dave Williamson, Jerry Olson, Jim Hack, Richard Neale and Chris Bretherton* National Center for Atmospheric Research, Boulder *University of Washington, Seattle Joint GCSS-GPCI/BLCL-RICO Workshop, NASA/GISS, 18-21 September 2006
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Motivation Using forecast runs to test new parameterizations during the model development ? Is the GCSS-Pacific Cross-Section a good candidate to do this ?
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Outline Models: PBL and convective schemes Cross-section: climate runs versus observations. Forecast runs settings Forecast errors along the cross-section Examples: 3 cloud regimes – ITCZ region – Trade-Cumulus – Stratocumulus Conclusion
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Models: PBL and convective schemes CAM - Boundary layer: Holtslag-Boville (1993) - Shallow convection: Hack (1993) - Deep convection: Zhang-McFarlane (1995) CAM-UW (Chris Bretherton) - Turbulence scheme: Grenier-Bretherton (2001) includes explicit entrainment at the top of the PBL - Shallow convection: cloud-base mass flux based on surface TKE and convection inhibition near cloud base CAM-dilute (Richard Neale) - Deep convection: parcels are diluted by environment air
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Observations along the cross-section (JJA 1998) SWCFLWCF LWP Low cloud Mid/high cloud Precipitation CERES SSM/I ISCCP, D2GPCPISCCP, D2
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Model versus observations SWCFLWCF LWP Low cloud Mid/high cloud Precipitation CERES SSM/I ISCCP, D2 GPCP ISCCP, D2 --- Obs --- CAM --- CAM-UW --- CAM-dilute
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Forecast run specification Strategy If the model is initialized realistically, we assume the error comes from the parameterizations deficiencies. Advantages Full feedback SCM Deterministic statistical Look at process level Limitations Accuracy of the atmospheric state ? Initialize realistically ERA40 reanalysis CAM 5-day forecast Starting daily at 00 UT Observations ERA40
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Forecast errors and climate errors (CAM-ERA40) Cloud regimes => range of error structures Climate bias appears very quickly in CAM Climate error ~ Forecast error at day 5 Forecast T error (K), day 1Forecast T error (K), day 5Climate T error (K), JJA1998 Forecast q error (g/kg), day 1Forecast q error (g/kg), day 5Climate q error (g/kg), JJA1998
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Forecast temperature errors at day 5 CAM-UW Some improvement in the cumulus region CAM-dilute Reduces T bias near ITCZ Error increases above 300 mb and in the lower troposphere. Changes in regions where the deep convection is not active CAM CAM-UW CAM-dilute
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Select a range of cloud regimes and forecast errors 3 locations ITCZStratocumulusTrade cumulus Forecast T error at day 5, CAM
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ITCZ regime: forecast T error (JJA 1998) CAM CAM-dilute ITCZ region: very sensitive to the deep convective scheme
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Total tendencyAdvective tendencyPhysics tendency ITCZ regime: Temperature equation --- CAM --- CAM-dilute
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Select a range of cloud regimes and forecast errors 3 locations ITCZStratocumulusTrade cumulus Forecast T error at day 5, CAM
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Stratocumulus: moisture and PBL (JJA 1998) PBL heightSpecific humidity CAM CAM-UW Stronger daily cyclePBL collapses day 0 day 1 day 2 day 5
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Stratocumulus: timeseries of T and q error T CAM -T ERA40 q CAM -q ERA40
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Stratocumulus: q equation (single forecast) CAM CAM-UW q Advective tendency Physics tendency
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Stratocumulus regime (Physics terms) CAM CAM-UW PBL tendency Shallow tendency Prognostics cloud water tendency
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Conclusion CAM forecasts allows for diagnosing model errors in the different cloud regimes. Climate bias appears very quickly in CAM – Where deep convection is active, error is set within 1 day – 5-day errors are comparable to the mean climate errors. New schemes: CAM-UW and CAM-dilute -CAM-dilute: improves the warm bias in upper troposphere, but cold bias increases in lower troposphere and near top of the model. -CAM-UW: does not change the error structure but CAM-UW operates very differently than CAM at the process level. Difficult to decide what is causing the errors in such a coupled system => need observations. => Comparison along the A-train
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Observations along the cross-section SWCFLWCF LWP Low cloud Mid/high cloud Precipitation CERES SSM/I ISCCP, D1GPCPISCCP, D1
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Model versus observations SWCFLWCF LWP Low cloud Mid/high cloud Precipitation CERES SSM/I ISCCP, D1 GPCP ISCCP, D1 --- Obs --- CAM --- CAM-UW --- CAM-dilute
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Cumulus regime: Forecast q errors CAM CAM-UW
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Cumulus regime: moisture budget terms 2 PBL/ShCu schemes operate in very different way.
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ITCZ regime: Precipitation (JJA 1998) - GPCP Dataset Daily precipitation - CAM Loses water very quickly during day 1. - CAM-dilute Precipitation increases during day 1.
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ITCZ regime: Temperature equation
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Stratocumulus regime (Q, CLOUD, CLDLIQ)
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