Sensitivity to the PBL and convective schemes in forecasts with CAM along the Pacific Cross-section

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1 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, September 2006

2 Motivation Using forecast runs to test new parameterizations during the model development? Is the GCSS-Pacific Cross-Section a good candidate to do this?

3 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

4 Models: PBL and convective schemes CAM - Boundary layer: Holtslag-Boville (1993) - Shallow convection: Hack (1993) - Deep convection: Zhang-McFarlane (1995) CAM-UW (Chris Bretherton) CAM-dilute (Richard Neale) - 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 - Deep convection: parcels are diluted by environment air

5 Observations along the cross-section (JJA 1998) SWCF LWCF LWP CERES SSM/I CERES Low cloud Mid/high cloud Precipitation ISCCP, D2 ISCCP, D2 GPCP

6 Model versus observations SWCF LWCF LWP CERES --- Obs --- CAM --- CAM-UW --- CAM-dilute SSM/I CERES Low cloud Mid/high cloud Precipitation ISCCP, D2 ISCCP, D2 GPCP

7 Forecast run specification Initialize realistically ERA40 reanalysis CAM 5-day forecast Starting daily at 00 UT Observations ERA40 Strategy If the model is initialized realistically, we assume the error comes from the parameterizations deficiencies. Advantages Full feedback apple SCM Deterministic apple statistical Look at process level Limitations Accuracy of the atmospheric state?

8 Forecast errors and climate errors (CAM-ERA40) Forecast T error (K), day 1 Forecast T error (K), day 5 Climate T error (K), JJA1998 Forecast q error (g/kg), day 1 Forecast q error (g/kg), day 5 Climate q error (g/kg), JJA1998 Cloud regimes => range of error structures Climate bias appears very quickly in CAM Climate error ~ Forecast error at day 5

9 Forecast temperature errors at day 5 CAM CAM-UW CAM-dilute 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

10 Select a range of cloud regimes and forecast errors 3 locations Forecast T error at day 5, CAM Stratocumulus Trade cumulus ITCZ

11 ITCZ regime: forecast T error (JJA 1998) CAM CAM-dilute ITCZ region: very sensitive to the deep convective scheme

12 ITCZ regime: Temperature equation T t = V T ω( T p RT pc p ) + Q physics Total tendency Advective tendency Physics tendency

13 Select a range of cloud regimes and forecast errors 3 locations Forecast T error at day 5, CAM Stratocumulus Trade cumulus ITCZ

14 Stratocumulus: moisture and PBL (JJA 1998) Specific humidity PBL height CAM day 0 day 1 day 2 day 5 CAM-UW PBL collapses Stronger daily cycle

15 Stratocumulus: timeseries of T and q error T CAM -T ERA40 q CAM -q ERA40

16 Stratocumulus: q equation (single forecast) q Advective tendency Physics tendency CAM CAM-UW

17 Stratocumulus regime (Physics terms) PBL tendency Shallow tendency Prognostics cloud water tendency CAM CAM-UW

18 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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21 Cumulus regime: Forecast q errors CAM CAM-UW

22 Cumulus regime: moisture budget terms 2 PBL/ShCu schemes operate in very different way.

23 ITCZ regime: Precipitation (JJA 1998) - GPCP Dataset Daily precipitation - CAM Loses water very quickly during day 1. - CAM-dilute Precipitation increases during day 1.