Royal Dutch Meteorological Institute; Ministery Of Infrastructure And The Environment

Publications, presentations and other activities
Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud cci project
by Stengel (DWD, Germany), Stapelberg (DWD, Germany), Sus (DWD, Germany), Schlundt (DWD, Germany), Poulsen (RAL, UK) Thomas (RAL, UK) Christensen (RAL, UK) Carbajal Henken (FUB, Germany) Preusker (FUB, Germany) Fischer (FUB, Germany) Devasthale (SMHI, Sweden) Willen (SMHI, Sweden) Karlsson (SMHI, Sweden) McGarragh (Oxford Univ, UK) Proud (Oxford Univ, UK) Povey (Oxford Univ, UK) Grainger (Oxford Univ, UK) Meirink (KNMI) Feofilov (LMD, France) Bennartz (Vanderbilt Univ, USA) Bojanowski (MS, Switzerland) Hollmann (DWD, Germany)

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 etrievals are applied to simultaneously retrieve loud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at isible, near-infrared and thermal infrared avelengths, 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 MERISCAATSR, each comprising a specific subset of all available sensors. The individual haracteristics 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 onsistency and the rigorousuncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency mong 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:
Cloud_cci AVHRR-PM:
Cloud_cci MODIS-Terra:
Cloud_cci MODIS-Aqua:
Cloud_cci ATSR2-AATSR:

Bibliographic data
Stengel, Stapelberg, Sus, Schlundt, Poulsen, Thomas, Christensen, Carbajal Henken, Preusker, Fischer, Devasthale, Willen, Karlsson, McGarragh, Proud, Povey, Grainger, Meirink, Feofilov, Bennartz, Bojanowski and Hollmann, Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud cci project
Earth System Science Data, 2017, 9, 881-904, doi:10.5194/essd-9-881-2017.
Abstract (html)