Observing trends and extreme events impacts on lakes using ESA CCI Climate Research Data Package

Lakes are integrators of environmental and climatic changes occurring within their contributing basins. Factors driving lake condition vary widely across space and time, and lakes, in turn, play an important role in local and global climate regulation, with positive and negative feedback depending on the catchment. Understanding the complex behaviour of lakes in a changing environment is essential to effective water resource management and mitigation of climate change effects. Lakes integrate responses over time and studies of globally distributed lakes can capture different aspects of climate change. A globally harmonized observation approach is needed to identify climate signals in lake physical, hydrological and biogeochemical change and to feed lake state into numerical models. The objective of Lakes_cci is to exploit satellite Earth Observation data to create the largest and longest possible consistent, global record of the five lake climate variables: Lake Water Level (LWL), Lake Water Extent (LWE), Lake Surface Water Temperature (LSWT), Lake Water-Leaving Reflectance (LWLR), and Lake Ice Cover (LIC). Lakes_cci represents a unique framework to provide consistent and homogenous data to the multiple communities of lake scientists. The project actively engages with this community to assess the utility and future improvement of Lakes_cci products. The first phase of the project has recently been completed with the release of the last version (v2.0.2) of the dataset, which is comprised of processed satellite observations at the global scale, over the period 1992-2020, for over 2000 inland water bodies, where and when data quality appropriate for climate studies can be achieved. Phase 2 of the project started in July 2022, with the inclusion of the Lake Ice Thickness variable. One scope of the project is the integration of different satellite-derived products across ESA CCI projects (e.g., Fire, Land). In this study potential of the CCI dataset is explored in three different case studies in the Eurasian region.