The ADV/ASV AATSR aerosol retrieval algorithm:current status and presentation of a full-mission AOD dataset

An advanced along-track scanning radiometer(AATSR)global multi-year aerosol retrieval algorithm is described.Over land,the AATSR dual-view(ADV)algorithm utilizes the measured top of the atmosphere(TOA)reflectance in both the nadir and forward views to decouple the contributions of the atmosphere and the surface to retrieve aerosol properties.Over ocean,the AATSR single-view(ASV)algorithm minimizes the discrepancy between the measured and modelled TOA reflectances in one of the views to retrieve the aerosol information using an ocean reflectance model.Necessary steps to process global,multiyear aerosol information are presented.These include cloud screening,the averaging of measured reflectance,and post-processing.Limitations of the algorithms are also discussed.The main product of the aerosol retrieval is the aerosol optical depth(AOD)at visible/near-infrared wavelengths.The retrieved AOD is validated using data from the surface-based AERONET and maritime aerosol network(MAN)sun photometer networks as references.The validation shows good agreement with the reference(r=0.85,RMSE=0.09 over land;r=0.83,RMSE=0.09 at coasts and r=0.96,RMSE=0.06 over open ocean).The results of the aerosol retrievals are presented for the full AATSR mission years 2002–2012 with seasonally averaged time series for selected regions.

Global operational land imager Landsat-8 reflectance-based active fire detection algorithm

A global operational land imager(GOLI)Landsat-8 daytime active fire detection algorithm is presented.It utilizes established contextual active fire detection approaches but takes advantage of the significant increase in fire reflectance in Landsat-8 band 7(2.20μm)relative to band 4(0.66μm).The detection thresholds are fixed and based on a statistical examination of 39 million non-burning Landsat-8 pixels.Multi-temporal tests based on band 7 reflectance and relative changes in normalized difference vegetation index in the previous six months are used to reduce commissions errors.The probabilities of active fire detection for the GOLI and two recent Landsat-8 active fire detection algorithms are simulated to provide insights into their performance with respect to the fire size and temperature.The algorithms are applied to 11 Landsat-8 images that encompass a range of burning conditions and environments.Commission and omission errors are assessed by visual interpretation of detected active fire locations and by examination of the Landsat-8 images and higher spatial resolution Google Earth imagery.The GOLI algorithm has lower omission and comparable commission errors than the recent Landsat-8 active fire detection algorithms.The GOLI algorithm has demonstrable potential for global application and is suitable for implementation with other Landsat-like reflective wavelength sensors.

Demonstration of uncertainty resulting from MODerate resolution Imaging Spectroradiometer-like geometries:an albedo case study

This research examines uncertainty in MODerate resolution Imaging Spectroradiometer(MODIS)observations,and demonstrates the direct influence of geometric distortions resulting from the standard practice of geolocating swath observations.MODIS observations vary dependent on the ground sample distance,which varies dependent on the view zenith angle that changes with every orbit.MODIS Level 2G(L2G)land products are generated by applying a geolocation algorithm that resamples the variable observation geometries to a consistent grid of fixed pixel size and location,a process which itself introduces variability associated with the changing observational footprint.For this study,broadband albedo was simulated for five validation sites,representing five distinct land cover types,exhibiting quantifiable variability,with additional seasonal variability exhibited in some sites.All site simulations exhibit compounded uncertainty attributable to the geometric distortion sufficient to influence climate models(i.e.ranges from 0.01 to 0.045 albedo).These results indicate there is a minimum level of uncertainty associated with the variable geometry that should be factored into L2Gbased products,particularly for nominal 250 m band data.Aggregating the data to coarser resolutions and smoothing the data through average resampling can mitigate the uncertainty.