Essential Climate Variables (ECVs) were originally defined by the Global Climate Observing System (GCOS) as a set of Earth system variables whose global measurement over time was believed able to aid climate and climate change assessment. Each ECV was considered potentially technically feasible and cost-effective for large-scale, systematic observation - many relying heavily on satellite Earth Observation methods to perform this task.

There are ECVs related to Earth’s ocean, cryosphere, biosphere, hydrosphere and atmosphere, and a rigorous definition is: “An ECV is a physical, chemical or biological variable or a group of linked variables that critically contributes to the characterisation of Earth’s climate.''

ECVs are identified based on the following criteria from GCOS:

Relevance: The variable is critical for characterising the climate system and its changes - providing a picture of climate change at a global scale.

Feasibility: Observing or deriving the variable on a global scale is technically feasible using proven, scientifically understood methods.

Cost-effectiveness: Generating and archiving data on the variable is affordable, mainly relying on coordinated observing systems using proven technology, taking advantage where possible of historical datasets.

Collectively, ECV's provide empirical evidence to support further development of climate science, to underpin current assessments of climate variability and change drivers and impacts, and to deliver improved forecasts of potential futures. EVCs can be used to help guide climate change mitigation and adaptation measures, to assess climate risks, to attribute climatic events to underlying mechanisms, and to support climate services.

To assess the accuracy of ECVs, scientists compare them to independent field measurements and model simulation results. These comparisons have two purposes: (i) to adjust the data values to remove systematic biases, if any, and (ii) to estimate the quality of the derived ECVs (this is called validation), which is required by both climate science and modelling communities. Validation addresses the question: how good is this dataset? It involves comparing pixel-level values with reliable in-situ field measurements from around the world.

In this video, Michael Buchwitz summaries ECV's, and provides a detailed example of one Atmospheric Composition ECV - Carbon Dioxide (CO₂).

Featured Educator

• Dr Michael Buchwitz, Senior Scientist, University of Bremen

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