Sensitivity to the CAM candidate schemes in climate and forecast runs along the Pacific Cross-section

Transcription

1 Sensitivity to the CAM candidate schemes in climate and forecast runs along the Pacific Cross-section Cécile Hannay, Dave Williamson, Jerry Olson, Jim Hack, Jeff Kiehl, Richard Neale and Chris Bretherton* National Center for Atmospheric Research, Boulder *University of Washington, Seattle AMWG, NCAR, January 2007

2 Outline The Pacific Cross Section Models: PBL and convective schemes Climate runs - Model versus observations along the cross-section Forecast runs Conclusion - Forecast runs settings - Forecast errors along the cross-section - Sensitivity to the 3 candidate deep convection schemes - Sensitivity to the UW shallow convection/pbl schemes

3 The Pacific Cross-section - Pacific Cross-section: several cloud regimes stratocumulus, shallow cumulus, deep convection - EUROCS project JJA GCSS intercomparison JJA 1998/ Observations ISCCP data SSM/I product TOVS atmosphere GPCP precipitation AIRS data - Reanalyses NCEP/ERA40

4 Models: PBL and convective schemes Control Both resolution and dycore Neale+Richter Wu Finite volume 1.9x vertical levels Zhang CAM-UW Eulerian T42 30 vertical levels

5 Observations along the cross-section, JJA 1998 SWCF LWCF LWP CERES SSM/I CERES Low cloud Mid/high cloud Precipitation ISCCP, D1 ISCCP, D1 GPCP

6 Climate runs versus observations, JJA 1998 SWCF LWCF LWP CERES --- Obs --- Control --- Neale +Richter --- Zhang --- Wu SSM/I CERES Low cloud Mid/high cloud Precipitation ISCCP, D1 ISCCP, D1 GPCP

7 Climate runs versus observations --- Obs --- Control --- CAM-UW SWCF LWCF LWP CERES SSM/I CERES Low cloud Mid/high cloud Precipitation ISCCP, D1 ISCCP, D1 GPCP

8 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?

9 Forecast errors and climate errors: Control-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

10 Sensitivity to the deep convection schemes Location on the cross-section ITCZ

11 Forecast temperature errors at day 5, July 1998 Control Neale+ Richter Zhang Wu All deep convection candidates Reduces warm T bias near ITCZ Error increases in the lower troposphere and above 300 mb. Changes in regions where the deep convection is not active

12 ITCZ regime, forecast T error, July 1998 Control Warm bias Cold bias Neale+ Richter Zhang Wu ITCZ region: forecast error is set within 1 day

13 ITCZ regime, temperature equation terms T t = V T ω( T p RT pc p ) + Q physics --- Control --- Neale +Richter --- Zhang --- Wu Total tendency Advective tendency Physics tendency

14 ITCZ regime, physics tendency terms --- Control --- Neale+Richter --- Zhang --- Wu Total physics Deep convection Shallow convection PBL Radiation Prognostic cloud

15 Deep convection tendency along cross-section Control Neale+ Richter Zhang Wu

16 ITCZ regime, Precipitation, July GPCP --- Control --- Neale+Richter --- Zhang --- Wu Total precipitation - GPCP Dataset Daily precipitation - Control Loses water very quickly during day 1. - Wu and Zhang Strong diurnal cycle. Omega

17 ITCZ regime, omega at day 1, July Obs --- Control --- Neale +Richter --- Zhang --- Wu

18 Skill scores, July Control --- Neale+Richter --- Zhang --- Wu V 250, RMS error V 850, RMS error Tropics Tropics

19 Skill scores, July 1998 Z 500, RMS error SLP, RMS error --- Control --- Neale+Richter --- Zhang --- Wu North hemisphere South hemisphere

20 Sensitivity to the UW scheme Location on the cross-section Stratocumulus

21 Forecast temperature errors at day 5, JJA 1998 Control CAM-UW CAM-UW does not change much the error structure.

22 Stratocumulus, moisture and PBL, JJA 1998 Specific humidity PBL height Control day 0 day 1 day 2 day 5 CAM-UW PBL collapses Stronger daily cycle

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

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

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

26 Conclusion CAM forecasts allows for diagnosing model errors in the different cloud regimes. Climate bias appears very quickly Where deep convection is active, error is set within 1 day 5-day errors are comparable to the mean climate errors. Sensitivity to candidate parameterizations - All deep convection schemes improve the warm bias in upper troposphere, but cold bias increases in lower troposphere and near top of the model. Change the error where the deep convection is not active. - CAM-UW: does not change the error structure but CAM-UW operates very differently than Control at the process level.

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28 Extra slides

29 Climate runs versus observations, JJA 1998 SWCF LWCF LWP CERES --- Obs --- Control --- Neale --- Zhang --- Wu SSM/I CERES Low cloud Middle cloud High cloud ISCCP, D1 ISCCP, D1 ISCCP, D1

30 Climate errors: eulerian versus finite volume FV T42

31 ITCZ regime: Cloud fraction

32 ITCZ regime, omega, July 1998 Control Neale+ Richter Zhang Wu