DUE GlobAEROSOL: Summary of current results and prospects for the future

1. DUE GlobAEROSOL: Summary of current results and prospects for the future R. Siddans

2. Status at End of Phase I • 1-month test data set generated, validated by comparison to Aeronet and intercompared with other satellite data-sets • System in place to produce full data set for 1995-2007 • Quality comparable to that of contemporary satellite sensors • Over sea, better agreement with MODIS than MISR • Over land, better agreement with MISR than MODIS • Two advances over other long-term aerosol data-sets: • Accuracy of multi-view from ATSR (cf MISR from 2000) • Denser sampling over Europe from SEVIRI • ORAC’s optimal estimation framework, with simultaneous fitting of vis/nir radiances with consistent aerosol model gives valuable error information & quality control • Data-set to be generated in Phase II will meet the needs of identified user applications

3. Phase 2 activities Planned: • Process 1995 – 2007 • Some improvements to scheme at QR ready & desirable to implement • Extensive validation of full data-set against Aeronet & intercomparison with other satellites • Improve QC and bias correction for GAPs • Initial evaluation of data through CTM model comparisons • Comparisons with independent MERIS/ATSR/SEVIRI schemes would also be welcome • Workshop in 2008 • Identify potential advances (beyond Phase II resource) for future re-processing.

4. Scope for future improvements • All satellite aerosol data-sets strongly affected by: • Cloud contamination. • Small amount of cloud in field-of-view introduces strong bias in aerosol • Mitigation by cloud screening but... • False screening of cloud • High aerosol load can be flagged as cloud, leading to under-detection of events and negative bias in averages • Modelling of surface reflectance (BRDF) • Especially over bright surfaces, and especially in absence of multi-view • Aerosol speciation • Wrongly assumed aerosol composition leads to errors in derived AOT • Intrinsically difficult to speciate from space measurements alone. • Progress on each in GlobAerosol Phase I • Current configuration suitable for phase II though further improvements in each area possible

5. Recommendations for Phase II:(a) Prior to large-scale production • Two advances to ORAC scheme developed in parallel at Oxford & RAL: • Radiative transfer model which properly represents BRDF • Dual-view scheme for (A)ATSR. • Results included in PVAR are demonstrably better than baseline • Recommend both be adopted in GlobAEROSOL Phase II. • ORAC cloud detection sometimes too severe. • For SEVIRI, preferable to process all scenes irrespective of the cloud mask and screen post-processing for clouds. • Nothing to lose as all scenes with any cloud rejected currently • (I.e. no benefit in identifying sub-10km cloud-free areas) • Less clear that this would be beneficial for (A)ATSR • Implement pre-processor to handle recently-identified anomalies in AATSR operational L1 scheme. • Process as many SEVIRI scenes per day as possible within CPU limits. • Fix MERIS angstrom coefficient over land (used to derive 0.55 micron

6. Longer-term developments The planned development of the ORAC algorithm can be split into three categories: • For SEVIRI, exploitation of the high temporal sampling to determine BRDF from SEVIRI itself, removing the reliance on MODIS product. • Use SEVIRI observations over multiple times + days to fit BRDF & aerosol • The inclusion of thermal infrared channels into the aerosol retrieval • Allows retrieval of dust over desert surfaces & potentially also information on height • Integration with ORAC cloud retrieval scheme • Cloud properties obtained from ATSR-2 with ORAC in GRAPE project now. Not yet applied AATSR & SEVIRI. Algorithm improvements feasible. These are all under development at Oxford & RAL, but not in scope for GlobAerosol phase II

7. Summary • Changes recommended to formally current scheme for Phase II: • Dual-view – ready & demonstrated for AATSR • Process all SEVIRI 10km scenes & post-screen cloud – ready • Pre-processor for AATSR L1 data (end of Jan) • Process additional SEVIRI time-slots – subject to CPU limits • Change in use of Angstrom coef for MERIS over land • Generate GlobAerosol full data set for extensive validation & exploitation by users. • Model comparison within scope of Phase 2 – to be defined • Intercomparison with independent MERIS/ATSR/SEVIRI schemes • Workshop to be convened in 2008 • Future advances (beyond scope of Phase 2 resource), potentially including: • SEVIRI IR dust retrieval • SEVIRI derived BRDF + aerosol

9. Recommendations for Phase II:Further enhancements • The following minor changes will be investigated should not to delay processing: • Implement correction to the a priori surface reflectance from the MODIS BRDF product, to account for differences in spectral response between MODIS and (A)ATSR and SEVIRI • Test potential for reduce over-severe cloud flagging for (A)ATSR. Requires more care than SEVIRI as current status with AATSR is that sub-pixel cloud detection increases number of useful scenes. • Tests to flag cases of aerosol as opposed to cloud would be most pragmatic short-term solution • (Longer term solution might be to include cloud in retrieval) • MERIS not CPU-limiting, so input data of demonstrably improved quality from other projects could potentially be ingested in Phase-II

10. Processing Issues • For 1st analysis – all L1B data were processed as generated – i.e. pre-2004 data have no corrections • i.e. no nonlinearity or drift correction • For archive – some data have been reprocessed (pre-2004?) • 1.6um nonlinearity correction included for all data • Drift correction not applied to all data • For 2nd reprocessing • 1.6um nonlinearity will be correct for all data • No bias corrections applied • Some or no drift corrections applied – depending on acquisition time NOT processing time. • Situation is confusing as the product does not give any direct reference to the calibration corrections being applied • Some users are not aware of the issues. • i.e. no version number for calibration

11. Aerosol + BRDF retrieval from SEVIRI • By observing every 15 minutes, SEVIRI observes surface + aerosol + cloud through comprehensive range of scattering geometry • Surface contribution can be separated by making assumptions wrt spatial & temporal correlations • RAL currently working on joint aerosol + BRDF scheme, first through retrieval simulation in ESA CAMELOT study From C.Popp, JGR • Others (Popp, Govaerts) also developing schemes based on this approach – however combination with ORACs multi-spectral, optimal fitting to consistent aerosol optical model required to fully exploit information content • Full joint scheme would be much more computationally demanding than current scheme + considerable development work required. • However 2-step BRDF, then aerosol scheme might yield benefits in shorter term & this could be investigated

12. ORAC: Thermal IR aerosol retrieval Large aerosol particles, such as wind blown dust, can have a strong impact on the TOA radiance in thermal window channels Incorporating this information into the retrieval greatly improves the detection of dust over desert surfaces Needs work to develop into scheme for global processing and extend to (A)ATSR – cannot replace vis/nir scheme at present but could complement it for dust GT will be able supply an animation of this:

13. ORAC cloud retrieval ORAC started life as a cloud retrieval algorithm and has been used process the ATSR-2 dataset for the GRAPE project. Users interested in cloud/aerosol interactions encouraged to use GRAPE cloud data + GlobAerosol. Cloud scheme will benefit from new developments of ORAC in GlobAerosol & re-processing of ATSR-2 + AATSR for cloud is envisaged outside context of GlobAerosol.

14. Proposed Way Forward • It is possible to identify in the L1B products which calibration files were used – and hence which corrections were applied • If GC1 file name is ATS_GC1_AXVIEC20020123_073430_20020101_000000_20200101_000000 then no nonlinearity correction is NOT applied to 1.6um channel. • VC1 file generation date indicates which drift correction has been applied. • Date before 29-Nov-2005 13:20:26 then no correction applied • Date between 29-Nov-2005 13:20:26 and 18-Dec-2007 20:14:15 then exponential drift correction is applied • Date after 18-Dec-2007 20:14:15 then thin film correction is applied • One proposal is to provide a look up table with the relevant drift corrections.