Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud-cci project

Martin Stengel, Stefan Stapelberg, Oliver Sus, Cornelia Schlundt, Caroline Poulsen, Gareth Thomas, Matthew Christensen, Cintia Carbajal Henken, Rene Preusker, Jürgen Fischer, Abhay Devasthale, Ulrika Willén, Karl Göran Karlsson, Gregory R. McGarragh, Simon Proud, Adam C. Povey, Roy G. Grainger, Jan Fokke Meirink, Artem Feofilov, Ralf BennartzJedrzej S. Bojanowski, Rainer Hollmann

Research output: Contribution to journalArticleResearchpeer-review

41 Citations (Scopus)

Abstract

New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud-cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude-longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the Cloud-cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the impact of temporal sampling and spatial resolution on cloud climatologies. For each dataset a digital object identifier has been issued: Cloud-cci AVHRR-AM: https://doi.org/10.5676/DWD/ESA-Cloud-cci/AVHRR-AM/V002 Cloud-cci AVHRR-PM: https://doi.org/10.5676/DWD/ESA-Cloud-cci/AVHRR-PM/V002 Cloud-cci MODIS-Terra: https://doi.org/10.5676/DWD/ESA-Cloud-cci/MODIS-Terra/V002 Cloud-cci MODIS-Aqua: https://doi.org/10.5676/DWD/ESA-Cloud-cci/MODIS-Aqua/V002 Cloud-cci ATSR2-AATSR: https://doi.org/10.5676/DWD/ESA-Cloud-cci/ATSR2-AATSR/V002 Cloud-cci MERISCAATSR: https://doi.org/10.5676/DWD/ESA-Cloud-cci/MERIS+AATSR/V002.

Original languageEnglish
Pages (from-to)881-904
Number of pages24
JournalEarth System Science Data
Volume9
Issue number2
DOIs
Publication statusPublished - 23 Nov 2017
Externally publishedYes

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