Lakes and enclosed inland seas 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 have been observed as sentinels of climate change, both directly and indirectly through watershed changes. Lakes integrate responses over time and studies of globally distributed lakes can capture different aspects of climate change. Therefore, a global and consistent climate data record of lakes is essential to mitigate and adapt to climate change.

The Lakes_cci project develops satellite-derived products for the Lakes Essential Climate Variable, as defined by GCOS-200:


The overarching objective of the Lakes project is to produce and validate a consistent data set of the variables grouped under the Lakes ECV. This includes aiming for the longest period of combined satellite observations by designing and operating processing chains, designed to ultimately feature in a sustainable production system.

The main ambition associated with this objective is to establish wide uptake by a varied and fragmented landscape of potential users. This requires significant alignment of current practices for producing the individual Lake variables, cross-variable validation, and demonstration in the form of use cases. Successfully tackling the challenge of producing a single data set for the Lakes ECV creates an opportunity to move the science community towards wider uptake of Earth Observation data in limnological studies.

To achieve this global objective, the specific objectives for the Lakes project are to:

Deriving the Lakes Essential Climate Variable (ECV) from satellite records requires the use of various remote sensing techniques including radar altimetry, thermal and optical sensing. The state-of-the-art used to produce the ECV products applies distinct sensor combinations and methodologies for calibration and validation for each product. The Lakes_cci team therefore consists of experts representing each remote sensing domain.

The purpose of this project is to revisit the algorithms required for the generation of each parameter, aiming to fulfil the GCOS requirements to the extent possible with modern and legacy sensors.

The Lakes_cci project has entered its second project phase under the ESA CCI+ programme. The first phase started in 2018 and was completed in 2022 and delivered two data releases and associated product documentation. The second phase started in June 2022 and will last three years.

The project is divided into two data processing phases composed of five steps each:

The distinct components of work are briefly summarized as follows:

WP1: User requirements: In coordination with the WP5 team, this work package is dedicated to analysis of end-user requirements, identifying multiple users and use cases and translating their needs into development tasks.

WP2: Algorithm development: The origin of algorithms used in the project to calculate the five parameters is two-fold:

In both cases, the algorithms are assessed, developed or adopted, and their associated uncertainty is estimated while end-products are validated through round-robin exercises.

WP3: System Development: The aim of this work package is to maintain and further develop prototype data processing systems to generate the ECV products. The Lakes_cci project is a distributed data processing infrastructure due to the wide suite of satellite input products and expertise required to generate the full ECV set.

WP4: Production Generation and Validation: Products are generated based on the algorithms analysed in WP2, taking the user requirements into account (WP1) and using the systems developed in WP3.

WP5: Assessment of the ECVs products: In this package of work we:

During Phase 1 (2018-2022), five use cases were studied

During Phase 2, two options are also explored: