D4.2 EUMETSAT, UCL, BC, NPL, JRC, RF QA4ECV Mid-Term Review - PowerPoint PPT Presentation

QA4ECV WP4 T4.2 - Recommendations for land ECV retrieval D4.2 EUMETSAT, UCL, BC, NPL, JRC, RF QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

T4.2 Recommendations on Land ECV(1) Sensors/datasets considered for the BRDF/Albedo retrieval  GlobAlbedo heritage:  MERIS L1b  SPOT-VGT L1P  New LEO sensors:  AVHRR LTDR  MODIS Aqua/Terra SDR (MOD09GA/MYD09GA)  Proba-V L1b  (A)ATSR(2)  New GEO sensors:  Meteosat MVIRI/SEVIRI QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

T4.2 Recommendations on Land ECV(1) AATSR data as candidate for ingestion  as there were well known geolocation issues in previous AATSR datasets, an assessment study is required to check if ingestion of AATSR data in BRDF/albedo retrieval improves, does not change, or even degrades the quality of the inversion applied in the algorithm  In order to measure the impact of the inclusion of AATSR data on the BRDF model inversion, three different processing modes were applied:  caseA : only MERIS and VGT were used  caseB : only AATSR nadir-view, MERIS and VGT  caseC : all samples from AATSR, forward and nadir view, MERIS and VGT  this study was performed by Gerardo Lopez for the previous AATSR reprocessing version. He found that the use of AATSR even degrades the quality of the inversion . We repeated Gerardo’s study (MODIS tile h25v06, 16-day period of BBDR input data in 2005), but with the modifications:  use AATSR input from the latest reprocessing version,  pre- process with a coregistration scheme proposed by Dan Fisher (King’s College London) QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

T4.2 Recommendations on Land ECV(1) AATSR data as candidate for ingestion  as an estimate of the model parameters derived from the three different cases were used to calculate the ‘goodness of fit’, which is basically a chi-square test. This measure describes how well it fits a set of observations, with values closer to zero indicating that the model fits better to the observation set:  Results: see histograms below showing:  Goodness_of_Fit for caseA  difference of Goodness_of_Fit for caseB – caseA  difference of Goodness_of_Fit for caseC - caseA QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

T4.2 Recommendations on Land ECV(1) AATSR data as candidate for ingestion  Goodness_of_Fit for caseA QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

T4.2 Recommendations on Land ECV(1) AATSR data as candidate for ingestion  difference of Goodness_of_Fit for caseB - caseA QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

T4.2 Recommendations on Land ECV(1) AATSR data as candidate for ingestion  difference of Goodness_of_Fit for caseC - caseA QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016

T4.2 Recommendations on Land ECV(1) AATSR data as candidate for ingestion  Conclusions:  The best goodness of fit is found for ‘caseA’ when using only MERIS and VGT data for the BRDF model inversion  the decrease in inversion quality seems to be less serious as for non-coregistered input, but is still visible  gof_diff_caseB_caseA shows now a more or less symmetric histogram (mean value just slightly positive, ~ 2.0), indicating that ingestion of coregistered AATSR nadir has not much influence on inversion quality  gof_diff_caseC_caseA still shows an asymmetric histogram towards positive values (i.e. between +25 and +50, mean value ~ 7.0). Although not as obvious as for the non-coregistered data, ingestion of AATSR nadir and forward still seems to decrease inversion quality   Suggestion: Add AATSR to the retrieval, but only Nadir view and only period 1998-2002 when no MERIS data are available QA4ECV Mid-Term Review Meeting, MSSL, 14-16 June 2016