The use of ground sampled water quality information for global studies is limited due to practical and financial constraints. Remote sensing is a valuable means to overcome such limitations and to provide synoptic views of ambient water quality at appropriate spatio-temporal scales. In past years several large data processing efforts were initiated to provide corresponding data sources. The Diversity II water quality dataset consists of several monthly, yearly and 9-year averaged water quality parameters for 340 lakes worldwide and is based on data from the full ENVISAT MERIS operation period (2002–2012). Existing retrieval methods and datasets were selected after an extensive algorithm intercomparison exercise using in situ reference measurements for more than 40 lakes representing a wide range of bio-optical conditions. Chlorophyll-<i>a</i>, total suspended matter, turbidity, coloured dissolved organic matter, lake surface water temperature, cyanobacteria and floating vegetation maps, as well as several auxiliary data layers, provide a generically specified data basis that can be used for assessing a variety of locally relevant ecosystem properties and environmental problems. We demonstrate the use of the products by illustrating and discussing remotely sensed evidence of lake-specific processes and prominent regime shifts documented in literature. The Diversity II data are available from <a href="https://doi.pangaea.de/10.1594/PANGAEA.871462" target ="_blank">https://doi.pangaea.de/10.1594/PANGAEA.871462</a>, and Python scripts for their analysis and visualization are provided at <a href="https://github.com/odermatt/diversity/" target ="_blank">https://github.com/odermatt/diversity/</a>.