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Thomas Holzer-Popp (DLR), Stefan Kinne (MPI-M) & the Aerosol_cci team. aerosol_cci. URD - sources. GCOS as baseline CMUG as model-oriented update Applications: model development, assimiation, decadal forecasting, trend monitoring AEROCOM as aerosol_cci CRG
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Thomas Holzer-Popp (DLR), Stefan Kinne (MPI-M)& the Aerosol_cci team aerosol_cci
URD - sources • GCOS as baseline • CMUG as model-oriented update • Applications: model development, assimiation, decadal forecasting, trend monitoring • AEROCOM as aerosol_cci CRG • Applications: process studies, trend monitoring • MACC (currently added) • Application: assimilation (re-analysis)
GCOS requirements • Aerosol optical depth • goalthreshold • accuracy 0.01 0.02 • stability 0.005 / decade N/A • resolution 1 km / daily 10 km / weekly • Other aerosol properties • to supplement AOD • e.g. single scattering albedo • accuracy 0.02 • stability 0.015 / decade • Comprehensive ground-based independent validation • -> can not be met (per pixel) by any satellite product
URD - requirements • Overall user needs: • Easy availability (netCDF) • proven and documented quality • aerosol properties should identify aerosol species linked to source categories • observation of long-term trends (many years) for regions and globally • analysis of specific issues (absorption, aerosol above clouds, vertical profile, …) • prepare for easy and complete re-processing with new versions
URD - requirements • Level2 products for data assimilation: • AOD at 4 wavelengths (440, 550, 670, 870 nm) and several layers • 500 (1000) observations per hour • 1 - 3 years covered • 20 km ( 5 km) horizontal • 3 km vertical • accuracy and precision 0.05 (0.02) • with pixel level uncertainty (random + systematic) • consistent with clouds and fire
URD - requirements • Level3 products for process studies and trend monitoring: • AOD at 4 wavelengths • Angstrom coefficient (440-870), fine mode fraction (D<1μm), dust fraction • Absorption aerosol optical depth (or single scattering albedo) • aerosol vertical extinction / AOD profile (any information is valuable) • accuracy: combined absolute (low AOD) and relative (high AOD) • error characteristics
URD - requirements derived stability need regional AOD range (0.1 – 0.5) * 5% trend detection -> 0.005
URD - consistency • With CMUG requirements • Same basic parameters • CMUG gives higher priority and detail to vertical information • CMUG adds depolarisation ratio • Aerosol_cci adds aerosol type properties • horizontal / temporal resolution: • CMUG one dimension more demanding • aerosol_cci adds regional level • accuracy • aerosol_cci links to horizontal resolution and adds relative criterium • aerosol_cci has lower goal for aerosol type variables • agreement on regional level for AOD, difference for AAOD • stability • aerosol_cci defines target per temporal analysis grid • agreement on decadal level for AOD, difference for AAOD
URD - evolution Aerosol_cci URD_v1.3 accepted Continuing iterations adding MACC data assimilation requirements (v1.4) Further iteration with other ECVs to complete their requirements Feeding aerosol_cci URD into WMO-GAW SAG aerosol input to GCOS aim to harmonize between different requirements –> iteration with contributors SAG chair: “The aerosol_cci document is far superior to anything else that I have seen concerning requirements.” – including CMUG table Apreaciates tying to applications (CMUG) and accuracy resolution-dependance (aerosol_cci)
URD - harmonization • SAG chair questions and recommendations • overall process • use the WMO RRR excelsheet to avoid missinterpretations and gaps • add 1 line for each application / resolution • questions • can we harmonize application domains? • can we harmonize / justify vertical layers (3km – 5km)? • CMUG: Why 2 values for accuracy and precision? • CCI: 1° x 1° : not equal area / shall we restrict requirements to level2 products? • recommendations • add duration, coverage (for process studies) • add requirements for sub-orbital data (model/sat validation, assimilation)
Planned product use Model development and inter-comparison -> AEROCOM Data assimilation -> MACC (as far as possible) Trend monitoring: only later (longer dataset needed) options proposed for larger dataset processing
ECV consistency Other ECV participants in Aerosol_cci algorithm workshops cloud masking (cloud, fire, landcover, ozone) surface treatment (oceancolour, landcover, fire) aerosol model -> interest of other ECVs to get our recommendation / tech note) Consistent 3-level cloud masks with cloud_cci Need recommendations from oceancolour_cci and landcover_cci for chlorophyll / sediments and BRDF auxiliary datasets + reference data exchange of URDs between ECV aerosol_cci URD distributed to CMUG and ECVs -> collect further requirements aerosol_cci contributed to cloud_cci URD
Product uncertainties Known uncertainty contributors cloud screening surface treatment (assumed) aerosol optical properties radiometric calibration pixel size /atmospheric noise radiative transfer / look-up tables Characterization of uncertainty contributions production of test datasets (1 month) with different algorithm versions harmonization of critical modules for round robin – where possible
Product uncertainties An example: synergetic retrieval algorithm (first estimation based on validation results)
ECMWF data needs These have already iterated with D. Tann -> aerosol_cci DARD • Parameters from ERA Interim, Atmospheric model, Analysis • Requested analysis times: 0000, 0600, 1200, 1800 UTC • Dates: 01/01/1997 to 31/12/1997; 01/10/2008 to 31/12/2008 • Requested representation: Lat/long grid • Requested representation: 0.7 degree • Requested area: Global