Oral Session 1

Developing colored dissolved organic matter (CDOM) estimation algorithm based on optical water type classification for global lakes

Lakes play an important role in global carbon cycle. Colored dissolved organic matter (CDOM) is a potential proxy to quantitatively estimate carbons in lakes from satellite images. Accurately estimating CDOM from satellite remote sensing data is challenge because of its weak signal compared to chlorophyll-a and non-algal particles. There is currently no existing CDOM products for global lakes due mainly to the lack of global applicable algorithm. With the support from European Space Agency Lakes Climate Change Initiative (ESA Lakes_cci) project, we compiled more than 4,000 in situ remote sensing reflectance and CDOM data pairs from global inland water bodies. By using the in situ data, we evaluated 19 existing algorithms, and recalibrated 21 algorithms for retrieving CDOM from remote sensing reflectance. We then proposed an optical water type (OWT) classification-based approach by blending the most accurate CDOM algorithm for each OWT. We also compiled 282, 335 and 879 satellite matchups from Medium Resolution Imaging Spectrometer (MERIS), Sentinel-3 Ocean and Land Color Instrument (OLCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) respectively. Following the same method, we proposed an OWT classification-based approach for estimating CDOM directly from atmospheric-corrected satellite images. The proposed method can produce more accurate CDOM estimates in a wide range compared to existing algorithms. The proposed OWT-based CDOM estimation algorithm is integrated into the Calimnos processing chain, and will be used to produce CDOM product for global lakes within the ESA Lakes_cci project.

Dalin Jiang, University of Stirling, UK, United Kingdom, https://orcid.org/0000-0001-5676-5860

Evangelos Spyrakos, University of Stirling, United Kingdom

Xiaohan Liu, Plymouth Marine Laboratory, United Kingdom

Stefan Simis, Plymouth Marine Laboratory, United Kingdom

Clement Albergel, European Space Agency Climate Office, United Kingdom

Mortimer Werther, Swiss Federal Institute of Aquatic Science and Technology, Switzerland

Andrew Tyler, University of Stirling, United Kingdom

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