Seasonal climate predictions for marine risk assessment in the Barents Sea
Iuliia Polkova, Laura Schaffer, Øivin Aarnes and 1 more
Climate Services · 2022
doi:10.1016/j.cliser.2022.100291 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
We investigate the potential for using seasonal climate predictions for marine risk assessment in the Barents Sea. Marine risk is based on the diagnostic of the probability of extreme climate conditions and their consequences to identify time and regions vulnerable to climate hazards. The information on marine risk is operationally provided by Det Norske Veritas (DNV) to support sustainable and safe marine activities. So far, the probability of climate conditions was based on historical observations. Here, we implement predicted probabilities from an ensemble of seasonal predictions provided by the German Meteorological Service. We analyze predicted probabilities for summer for three indicators from the DNV’s marine service: two of them represent meteorological properties such as wind speed and 2-meter temperature. The third indicator, the wind chill index (WCI), is a combination of the previous two. The prediction skill, the “trust level” for predictions, is assessed over 1990–2017 and suggests that 2-meter temperature has the highest skill followed by WCI and wind speed. In addition, we use a real-time prediction to represent an actual application example. The maps of the real-time predicted probabilities show that large areas of the Barents Sea represent favorable conditions for marine operations considering low likelihood for WCI above 1000 W/m2 and T2m below 0 °C in July and August. Wind speed is poorly predicted beyond the first forecast month. We describe the workflow for an application of seasonal predictions for the DNV’s marine service as well as lessons learned for similar applications involving risk assessment.
Abstract licence: CC BY-NC
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.