Project: AKA | Centre of Excellence of I... (336791), AKA | Seismic full-waveform inv... (321761), AKA | Centre of Excellence of I... (336791), AKA | Seismic full-waveform inv... (321761)
POPCORN Sentinel-3 Synergy aerosol parameter post-process correction. This version carries out both accuracy and spatial anomaly corrections. Release version 1.0.0. This release consists of a Python script and trained deep learning models to post-process correct the Sentinel-3 Synergy (SY_2_SYN) aerosol data products. Developed by: Finnish Meteorological Institute and University of Eastern Finland Development of the algorithm was funded by the European Space Agency EO science for society programme via POPCORN project. Contact info: Antti Lipponen (firstname.lastname@example.org) Github repository: https://github.com/TUT-ISI/S3POPCORN/
Project: AKA | Centre of Excellence in I... (250215), AKA | Centre of Excellence in I... (250215)
Source code, data, and documentation to test the Bayesian Aerosol Retrieval algorithm for aerosol retrieval over land. The code is related to the article: Lipponen, A., Mielonen, T., Pitkänen, M. R. A., Levy, R. C., Sawyer, V. R., Romakkaniemi, S., Kolehmainen, V., and Arola, A.: Bayesian Aerosol Retrieval Algorithm for MODIS AOD retrieval over land, Atmos. Meas. Tech., https://doi.org/10.5194/amt-2017-359, accepted, 2018. The most recent version of the codes can be found at https://github.com/TUT-ISI/BARalgorithm
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