MPI Metorology comparing ISCCP and GEWEX products Madison, July 2006 Stefan Kinne Max Planck Institute for Meteorology Hamburg, Germany Ehrhard Raschke University of Hamburg Hamburg, Germany

MPI-M 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

MPI-M Earth’s radiation budget how accurate defined is the radiation 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

MPI-M 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: , res: 250km (spatial), 3hr (temp) processedC at NASA-GISS (Rossow, Zhang)  GEWEX-SRB GOAL: determine radiation budgets at the surface years: , res: 100km (spatial), daily (temp) processed at NASA-Langley (Stackhouse) clouds properties are ‘based‘ on the ISCCP climatology !

MPI-M 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

MPI-M 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

MPI-M solar fluxes  solar  ToA the ‘solar’ driver  solar  surface solar atm. transmittance  solar  /  surface surface albedo  solar  /  ToA planetary albedo typical plot: timeseries of monthly averages diff.colors for diff.latitude zones  ISCCP - GEWEX deviation Time (starting in 1983) 

MPI-M ISCCP – GEWEX  sol  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

MPI-M conclusion # 1  un-necessary deviation for ‘solar driver’  low sun, avg (  lat,  t)  also an issue in global modeling IPCC-4AR   use consistent routines for ToA insolation !  agree on orbit and S o  implement properly!  spat/temp integration solar insolation of IPCC models

MPI-M ISCCP – GEWEX sol  sur  text

MPI-M ISCCP – GEWEX sol  sur  text at surface: differences among data-sets are larger ! high lat. peaks are out phase to ToA peaks TOA a cloud issue !

MPI-M conclusion # 2  ‘sol  ToA’ differences are lost at ‘sol  surface’ and ‘sol  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)

MPI-M ISCCP – GEWEX  sol  /  sur largest differences during NH mid-lat winters - at high latitudes (not shown) even worse ! a snow issue !

MPI-M 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 !

MPI-M ISCCP - GEWEX sol  /  toa  text a combination of all previous biases

MPI-M 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

MPI-M infrared  IR  surface[emission]surf. temp effect  IR  surface(low) cloud effect  IR  at ToA[OLR](high) cloud effect  ISCCP - GEWEX deviation typical plot: timeseries of monthly averages diff.colors for diff.latitude zones Time (starting in 1983) 

MPI-M ISCCP – GEWEX  ir  sur  text

MPI-M ISCCP – GEWEX  ir  sur  text can this trend be detected at - ir  sur ? - ir  toa ? ‘false’ trend due to the use of incorrect surface temperature data for ISCCP in the tropics

MPI-M ISCCP – GEWEX  ir  sur  there NO: atm. effects (clouds) dominate

MPI-M ISCCP-GEWEX  ir  toa  text NO: atm. effects (clouds) dominate

MPI-M ISCCP-GEWEX  ir  toa/sur  text toa sur lower GEWEX opt.depth/cover higher GEWEX opt.depth/cover

MPI-M 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

MPI-M 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

MPI-M 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.

MPI-M

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

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ISCCP – GEWEX  sol  sur  text MAY 2006 high latitudes only

MPI-M ISCCP sol  sur  text MAY 2006 lower latitudes

MPI-M GEWEX sol  sur  text lower latitudes MAY 2006

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ISCCP/GEWEX sol (  sur/  toa)  text

MPI-M ISCCP/GEWEX sol (  sur/  toa)  text

MPI-M GEWEX sol (  sur /  toa)  text

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ISCCP – GEWEX  sol  /  toa  text lower latitudes

MPI-M ISCCP – GEWEX  sol  /  toa  text high latitudes

MPI-M ISCCP sol  /  toa  text

MPI-M GEWEX sol  /  toa  text

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ISCCP – GEWEX  ir  sur  text

MPI-M ISCCP ir  sur  text

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ISCCP-GEWEX  ir  toa  text lower latitudes

MPI-M ISCCP – GEWEX  ir  toa  text high latitudes

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ISCCP-GEWEX cld effect sol  sur  text

MPI-M ISCCP cloud effect sol  /  toa  text

MPI-M ISCCP cloud effect ir  toa  text

MPI-M ISCCP sol+ir  toa  text Raschke et al., Int.J. Clim. 2005

MPI-M ISCCP sol+ir atm  text Raschke et al., Int.J. Clim. 2005