Day 4

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Paper title A new global XCO2 data set created with the FOCAL v10 retrieval algorithm for the OCO-2 satellite
Authors
  1. Maximilian Reuter Institute of Environmental Physics (IUP), University of Bremen, Germany
  2. Michael Hilker University of Bremen, Institute of Environmental Physics (IUP)
  3. Michael Buchwitz University of Bremen
  4. Stefan Noël Institute of Environmental Physics, University Bremen
  5. Heinrich Bovensmann Institut für Umweltphysik, Universität Bremen
  6. John P. Burrows Institute of Environmental Physics (IUP), University of Bremen, Germany
  7. Blanca Fuentes Andrade Institute of Environmental Physics, University Bremen Speaker
Form of presentation Poster
Topics
  • A1. Atmosphere
    • A1.04 Greenhouse Gases
Abstract text CO2 (carbon dioxide) is the most important anthropogenic greenhouse gas and driving global climate change. Despite this, there are still large uncertainties in our understanding of anthropogenic and natural carbon fluxes to the atmosphere. Satellite observations of the Essential Climate Variable CO2 have the potential to significantly improve this situation. Therefore, a key objective of ESA’s GHG-CCI+ project is to further develop satellite retrieval algorithms needed to generate new high quality satellite-derived XCO2 (column-averaged dry-air mole fraction of atmospheric CO2) data products. One of these algorithms is the fast atmospheric trace gas retrieval FOCAL for OCO-2. FOCAL has been applied also to other satellite instruments (e.g., GOSAT and GOSAT-2) and its development is co-funded by EUMETSAT as it is a candidate algorithm to become one of the CO2M retrieval algorithms operated in EUMETSAT’s ground segment. Within our presentation, we will discuss the most recent retrieval developments incorporated in FOCAL-OCO2 v10 and present the corresponding improved XCO2 data product which is part of ESA’s GHG-CCI+ climate research data package 7 (CRDP7). The retrieval developments comprise a new cloud filtering technique by means of a random forest classifier, usage of a new CO2 a priori climatology, a new bias correction scheme using a random forest regressor, modifications of the radiative transfer, and others. The improved global data product exhibits an about three times higher data density and spans a time period of eight years (2014-2021). The results of a validation study using TCCON data will also be presented.

M.Reuter, M.Buchwitz, O.Schneising, S.Noel, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017a

M.Reuter, M.Buchwitz, O.Schneising, S.Noel, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2 Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017b

Noël, S., Reuter, M., Buchwitz, M., Borchardt, J., Hilker, M., Bovensmann, H., Burrows, J. P., Di Noia, A., Suto, H., Yoshida, Y., Buschmann, M., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Kivi, R., Morino, I., Notholt, J., Ohyama, H., Petri, C., Podolske, J. R., Pollard, D. F., Sha, M. K., Shiomi, K., Sussmann, R., Té, Y., Velazco, V. A., and Warneke, T.: XCO2 retrieval for GOSAT and GOSAT-2 based on the FOCAL algorithm Atmospheric Measurement Techniques, 14, 3837–3869, doi:10.5194/amt-14-3837-2021, 2021