For the first time, ocean data and the GOOS Essential Ocean Variables are called out in a WMO Unified Policy. This is a call for action to share ocean data that reaches beyond the global meteorological community.

Photo: Sam Greenfield/Volvo Ocean Race 2018

The 2021 Extraordinary World Meteorological Congress (11-22 October) approved the new WMO Unified Data Policy, which supersedes its older policies relating to the international exchange of meteorological, hydrological and climate data between the 193 Member states and territories of WMO. The approved WMO Unified Data Policy Resolution (Res.1) can be found here. 

“WMO has started favouring the Earth system approach rather than talking about weather, climate and water as separate items”, says Petteri Taalas, Secretary-General at WMO. The new WMO Unified Data Policy encompasses all relevant Earth system data – weather, climate, hydrology, atmospheric composition, cryosphere, oceans and space weather. 

The policy retains a two-tier approach to the international provision and exchange of Earth system data and mandates that core data ‘shall’ be exchanged, alongside recommended data that ‘should’ be exchanged. For the first time, ocean data are explicitly included in the policy, covering in situ and remotely sensed observational data both in and above the ocean and at the sea-surface, from the open ocean to the coast. 

The ocean data aspects of the policy were developed in collaboration with the GOOS community, and specify that all physical GOOS Essential Ocean Variable (EOVs) and GCOS Essential Climate Variables (ECV’s) data collected as part of GOOS are classed as core data that shall be exchanged on a free and unrestricted basis, while the exchange of all other observed biogeochemical and biological/ecosystems GOOS EOVs and GCOS ECVs is recommended (Table 1). 

Table 1

The new policy commits WMO Member Nations to supporting the free and open exchange of ocean data, as detailed in the Ocean section of Annex 1. This implies a commitment at national government level, which has an impact beyond the meteorological world. The GOOS community will need to monitor the exchange of these ocean data through the work of the global  ocean observing networks and the OceanOPS operational monitoring centre, in order to assess and report how GOOS is delivering towards the new Data Policy.

“We rely on global Numerical Weather Prediction models to generate medium-range forecasts and provide boundary data for higher resolution regional models used to generate most forecast products. All of our weather and climate predictions demand ocean information; and the further ahead we need to forecast, the deeper we need to go into the oceans for these data”, says Jon Turton, UK Met Office.

The exchange of all types of environmental data will enable WMO Members to provide more accurate weather and climate forecasts and other services, which will support better decision-making and ultimately allow to protect lives and livelihoods, as well as build resilient and sustainable blue economies.

GOOS Essential Ocean Variables

To be able to deliver ocean forecasts and early warnings, climate projections and assessments, and protect ocean health and its benefits, it is vital to measure Essential Ocean Variables (EOVs). They help us interpret the connection between the ocean and elements such as the atmosphere, biosphere, hydrosphere, cryosphere, and anthroposphere. Because EOVs are perennial, they allow the observing system to change and develop around them as technology and capability evolve. Essential Ocean Variables are identified by the GOOS Expert Panels, based on the following criteria:

Relevance: The variable is effective in addressing the overall GOOS Themes – Climate, Operational Ocean Services, and Ocean Health.

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.

See the list of current GOOS EOVs here.