Essential Variables

Data Model
Essential Variables
Expert-Based Approach
Goal-Based Approach
Gap Analysis
Virtual Stakeholder Table
Related Projects

The Concept

The concept of “Essential Variables” was introduced by the climate change community under the UNFCCC and was subsequently assimilated by several SBAs in GEO. The ConnectinGEO project conducted a review of all GEO SBAs and thematic groups with respect to how they are determining and validating EVs relevant to their domain (ConnectinGEO, 2015). It was found that there was a wide range of definitions, approaches to identify EVs, and processes to validating them. Moreover, specifying observational requirements for EVs is in all communities at a very inital state.

Definition of Essential Variables

To get a useful definition of EVs it is necessary to clarify the meaning of the terms “essential” and “variable”. The adjective “essential” has a number of different meanings, ranging from absolutely necessary and indispensable to containing an essence of something. A variable that significantly improves the reliability and accuracy of desired results can be considered essential. A variable that provides important information related to a specific goal is essential for this goal, independent of the capability to actually observe the variable. The essentiality of a variable may also depend on the information needs of different communities and target users (science, policy, etc.). In principle any variable can be “essential” for somebody or for achieving something. Therefore, the definition of what an EV is needs to be formalized and endorsed according to the collective interest and preferably in an internationally recognized process.

In the context of the ConnectinGEO project, EVs are “a minimal set of variables that determine the system’s state and developments, are crucial for predicting system developments, and allow us to define metrics that measure the trajectory of the system” (ConnectinGEO, 2015). The spatial and temporal resolution of observations of any given EV depend on the use of the observations, and in some cases, available observations of an EV may not be ready for use for specific applications. Limited knowledge of EVs implies limited predictive capabilities and limited means to measure where the system is heading. The generic nature of this EV definition allows us to identify sets of EVs for whatever system is being considered and for whatever goals are established in relation to this system. It allows for a broad application across different communities, and can be complemented with the specific requirements that each community may have related to the system the community is focusing on. Moreover, in a system of systems approach, sets of EVs can be aggregated into larger sets supporting prioritization of efforts across community and system boundaries.

The concept of “variable” embedded in the definition given above has a certain level of abstraction. Identifying a variable does not imply that observation requirements in terms of spatial and temporal resolution, accuracy, latency, observation interval, etc. are also specified. Nor does it imply that measurement instruments are available to observe the variable. In some cases, variable may not be observable directly and have to be derived from a combination of observations. In such cases, the essential variable may have to be composed of a set of sub-variables that together provide the required information.

One of the most important Workshop’s objectives was to review the different definition of EVs used in the different communities engaged or linked to GEO and to evaluate the level of consistency of these definitions. Although the “landscape” is quite diverse and complex, there seems to be some level of consistency with the system relevance of EVs but also considerable diversity with respect to the process how EVs are identified, validated and accepted.

The definition of the Essential Climate Variables (ECVs) developed by the Global Climate Observing System (GCOS) and endorsed by the United Nation Framework Convention on Climate Change (UNFCCC) is consistent with the definition chosen by ConnectinGEO: “An ECV is a physical, chemical, or biological variable or a group of linked variables that critically contributes to the characterization of Earth’s climate.” Datasets of ECV provide the empirical evidence needed to document, understand and predict the evolution of climate, to guide mitigation and adaptation measures, to assess risks and enable attribution of climatic events to underlying causes, and to underpin climate services (Bojinski et al., 2014). ECVs are widely accepted and used at international level.

Despite the significant progress made in ensuring that Earth Observations (EOs)_are collected and available to meet the information needs of a wide range of users, there are still many user needs that are not being met. There is still insufficiently consistency in monitoring and sharing of such information. Along with sometimes inadequate financial resources, a key obstacle is the lack of general consensus about what variables are essential to monitor. Different organizations and projects promote diverse measurements and many initiatives collecting EOs could benefit from the existence of a set of commonly agreed EVs as a basis to commit resources and to support progress towards an evidence-based knowledge base for decision making. Important gaps still remain and many key variables central to scientific and societal information needs are not, or not sufficiently observed. In particular, only a few GEO SBAs and themes have agreed, or have made significant progress towards agreement, on a specific set of EVs. The concept of EVs assumes that there is a (small) number of variables that are essential to characterize the state and trends in a system without losing significant information. It is that set of variables that needs to be observed if past changes in the system have to be documented and if predictability of future changes is to be developed. Identifying this set of EVs allows for a commitment of inherently scarce resources to the essential observation needs. It also supports and eases the management of data and observations all along the chain from the measurement of raw data, through the processing and to the delivery of products, information and services needed by end users. EVs are needed to: Describe natural and human systems and their processes, at physical, biogeochemical and biological level. Monitor status and trends of these systems in the different domains Predict, detect and attribute (i.e., identify drivers) changes Assess the impacts of these changes Identify tolerable limits of these changes (sustainable development and planetary boundaries) They are helpful to: Agree on a list of variables that are of common interest in a collective. Agree on variables that are feasible to measure in terms of cost, effort, and impact. Set up a list of key variables to be considered for the long-term measurement. Better communicate to funding agencies the need for long-term acquisition. Develop a consistent way to communicate messages to decision maker through homogeneous descriptions. Facilitate high acceptance by the stakeholders. In the frame of GEO, EVs are ideally needed to optimize the efforts and concentrate on a smaller set of variables characterizing one or (possibly) more GEO Societal benefits in a global scale and the topics of the Communities of Practice (CoPs). This would optimize the activities of the community working within GEO and possibly also promote collaboration among different tasks that may need the same EVs. The EVs identified by the collaborative work of the ConnectinGEO project will be also proposed for the new GEO Work Plan for the 2016-2025 period.