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

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 .

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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, 18-21 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

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

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

  7. CAM Forecast run specification Initialize realistically ERA40 reanalysis • 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 ? 5-day forecast Starting daily at 00 UT Observations ERA40

  8. 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 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

  9. CAM-UW CAM CAM-dilute Forecast temperature errors at day 5 CAM-UWSome improvement in the cumulus region CAM-diluteReduces T bias near ITCZError increases above 300 mb and in the lower troposphere. Changes in regions where the deep convection is not active

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

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

  12. --- CAM--- CAM-dilute ITCZ regime: Temperature equation Total tendency Advective tendency Physics tendency

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

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

  15. Stratocumulus: timeseries of T and q error TCAM-TERA40 qCAM-qERA40

  16. Stratocumulus: q equation (single forecast) Advective tendency Physics tendency q 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

  19. Observations along the cross-section LWP SWCF LWCF CERES SSM/I CERES Low cloud Precipitation Mid/high cloud ISCCP, D1 ISCCP, D1 GPCP

  20. --- Obs--- CAM--- CAM-UW--- CAM-dilute Model versus observations LWP SWCF LWCF CERES SSM/I CERES Low cloud Precipitation Mid/high cloud ISCCP, D1 ISCCP, D1 GPCP

  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 DatasetDaily precipitation • CAMLoses water very quickly during day 1. • CAM-dilutePrecipitation increases during day 1.

  24. ITCZ regime: Temperature equation

  25. Stratocumulus regime (Q, CLOUD, CLDLIQ)

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