comparing ISCCP and GEWEX products

1. comparingISCCP and GEWEX products Stefan Kinne Max Planck Institute for Meteorology Hamburg, Germany Ehrhard RaschkeUniversity of Hamburg Hamburg, Germany Madison, July 2006

2. overview • available long-term global data-sets for radiative fluxes • at the Top of Atmosphere (ToA) • at the surface (sur) • concept on investigating consistency • assessments of solar flux comparisons • assessments of infrared flux comparisons • recommendations

3. Earth’s radiation budget • how accurate defined is theradiation budget of our climate system? • know your clouds … • size-distribution (z) • cover (z) • know ancillary data … • surface + s-processes • anthop. influences • …on regional and seasonal scales

4. 2 long-term data-sets describe radiation budgets at ToA and surface • ISCCP • GOAL: extract data on cloud field characteristics from operational meteorological satellite sensors • years: 1983-2004, res: 250km (spatial) , 3hr (temp) • processedC at NASA-GISS (Rossow, Zhang) • GEWEX-SRB • GOAL: determine radiation budgets at the surface • years: 1983-2004, res: 100km (spatial) , daily (temp) • processed at NASA-Langley (Stackhouse) • clouds properties are ‘based‘ on the ISCCP climatology !

5. task at hand • two bb-flux data sets • for same time-period • based on the same cloud data • we should expect similar (if not the same) data • let’s test that • stratify data into zonal bands of monthly means • display differences (always ISCCP minus GEWEX) • interpret differences and highlight issues

6. regional temporal choices • 75-90N (1.7%) • 60-75N (5.0%) • 30-60N (18.3%) • 0-30N (25.0%) • 0-30S (25.0%) • 30-60N (18.3%) • 60-75N (5.0%) • 75-90N (1.7%) use monthly averages

7. solar fluxes • solar i ToA the ‘solar’ driver • solar i surface solar atm. transmittance • solar h/i surface surface albedo • solar h/i ToA planetary albedo typical plot: timeseries of monthly averages diff.colors for diff.latitude zones h ISCCP - GEWEX deviation Time (starting in 1983) g

8. ISCCP – GEWEX D sol i toa DECEMBER 2005 WHY DEVIATIONS ? simplified treatment of GEWEX solar insolation at low sun-elevations for the record: larger deviations are gone In new GEWEX data

9. conclusion # 1 solar insolation of IPCC models • un-necessary deviation for ‘solar driver’ • low sun, avg (Dlat, Dt) • also an issue in global modeling IPCC-4AR a • use consistent routines for ToA insolation ! • agree on orbit and So • implement properly! • spat/temp integration

10. ISCCP – GEWEX sol isur • text

11. ISCCP – GEWEX sol isur TOA • text at surface: differences among data-sets are larger ! high lat. peaks are out phase to ToA peaks a cloud issue !

12. conclusion # 2 • ‘sol i ToA’ differences are lost at ‘sol i surface’ and ‘sol i surface’ differences are larger (!) • differences in atmospheric properties dominate • larger differences (season dep.) at higher latitudes • most probable explanation • diff. in cloud-cover / cloud opt.depth (for data-sets) • assessment: cloud cover / optical depth differ ! • ‘cloud’ differences have a seasonal dependence • GEWEX cloud (opt. depth/cover) impact is stronger especially during polar summers (particularly in SH) (… yet weaker during mid-latitude summer in SH)

13. ISCCP – GEWEX D sol h/i sur largest differences during NH mid-lat winters - at high latitudes (not shown) even worse ! a snow issue !

14. conclusion # 3 • solar surface albedo in models differs • differences have a seasonal dependence • sign of diff. varies between high and low latitudes • largest differences are linked to snow (alb. / cover) • GEWEX has smaller solar surface albedos at higher latitudes especially in seasons, when snow can be expected … yet larger solar surface albedos in the tropics • assessment on solar surface albedo: accuracy and consistency of ancillary (non-cloud data) data matters !

15. ISCCP - GEWEX sol h/i toa • text a combination of all previous biases

16. conclusion # 4 • diff. in plantetary albedo display combined effect • solar insolation biases • solar surface albedo • atmospheric properties (especially those of clouds) • potential for offsetting errors • planetary albedo at ToA differences • surface albedo diff. at mid/ high lat. are modulated as expected by cloud impact based on solar transm. - except for tropics: GEWEX clouds less reflective! • assessment: cloud microphysics differ

17. infrared • IR h surface [emission] surf. temp effect • IR i surface (low) cloud effect • IR h at ToA [OLR] (high) cloud effect typical plot: timeseries of monthly averages diff.colors for diff.latitude zones h ISCCP - GEWEX deviation Time (starting in 1983) g

18. ISCCP – GEWEXD ir h sur • text

19. ISCCP – GEWEXD ir h sur • can this trend • be detected at • ir i sur ? • ir h toa ? • text ‘false’ trend due to the use of incorrect surface temperature data for ISCCP in the tropics

20. ISCCP – GEWEXD ir i sur • there NO: atm. effects (clouds) dominate

21. ISCCP-GEWEXD ir h toa NO: atm. effects (clouds) dominate • text

22. ISCCP-GEWEXD ir h toa/sur toa • text lower GEWEX opt.depth/cover higher GEWEX opt.depth/cover sur

23. conclusion # 5 • atmospheric properties are main IR modulators • surface emission differences vs OLR differences • usually consistent with cloud (opt.depth/cover) bias • … though not always ! • cloud boundary temperatures matter • atm. temp. profile or altitude placement of cloud? • assessment: cloud altitude placement differs • other important ancillary data: • surface temperature / atm. temperature profile

24. conclusions • ISCCP and GEWEX radiations products often disagree on cloud and ancillary data • significant difference for cloud properties surprise, given the same cloud data-source • larger disagreements at high-latitudes • potential offsets can dilute severity of problem • careful validation to quality data are needed • ground-based network (BSRN) ? • use synergy of advanced space sensors (A-train) • collaboration of data/analyzing groups needed

25. recommendations • develop a reference algorithm for ToA solar insolation • Earth’s orbital data, solar constant, low sun elevation issue • re-evaluate cloud properties and ancillary data (T, snow) • compare to in-situ and ground-based quality data • identify systematic diff. on regional / seasonal scales • treat cloud and ancillary data in a consistent manner • implementation ( … to suit model / data-set resolution) • document your steps ! • supply complete and detailed explanations on assumptions and methods – including a brief summary to allow a hasty user to understand major characteristics and error sources.

27. extras • solar downward surface flux ‘trend’ • solar transmission ratio and ‘trend’ • solar planetary ‘trend’ / ‘trend’ differences • infrared surf emission ‘trend’ / ‘trend’ differences • infrared outgoing ir flux ‘trend’ differences • all-sky vs. clear-sky: the cloud effect

29. ISCCP – GEWEXD sol i sur MAY 2006 • text high latitudes only

30. ISCCP sol i sur MAY 2006 • text lower latitudes

31. GEWEX sol i sur MAY 2006 • text lower latitudes

33. ISCCP/GEWEX sol (isur/itoa) • text

34. ISCCP/GEWEX sol (isur/itoa) • text

35. GEWEX sol (isur /itoa) • text

37. ISCCP – GEWEX D sol h/i toa • text lower latitudes

38. ISCCP – GEWEX D sol h/i toa • text high latitudes

39. ISCCP sol h/i toa • text

40. GEWEX sol h/i toa • text

42. ISCCP – GEWEXD ir h sur • text

43. ISCCP ir h sur • text

45. ISCCP-GEWEXD ir h toa • text lower latitudes

46. ISCCP – GEWEX D ir h toa • text high latitudes

48. ISCCP-GEWEX cld effect solisur • text

49. ISCCP cloud effect sol h/i toa • text

50. ISCCP cloud effect ir h toa • text