The information on the future scenarios of sea level anomaly, with respect to (1995-2014), as a function of GWLs (1 °C, 1.5 °C, 2 °C, and 4 °C) in Kotor (Montenegro), southern Adriatic Sea. Left panel, the multi-model median anomaly is presented with uncertainties of 50% reported as shaded bars, together with extremes as sticks. The right panel reports the statistics of the 95% multi-model monthly extremes, as a function of GWLs (1 °C, 1.5 °C, 2 °C, and 4 °C) in the same location. The shaded bars and the sticks have the same meaning described for the left panel.

News

Sea level rise uncertainties and Global Warming Levels

11/11/2024

🌊 One of the specific objectives of the MedSeaRise project is to generate datasets 📊 supporting the application of methodologies and best practices on the use of sea level rise 🌍 information for risk assessment and adaptation actions.

🔹 Thanks to a specific project action, these datasets are created based on ensembles of numerical simulations 📈 from future climate scenarios, sourced from international scientific projects 🌐.

🔗 For case studies aiming to assess the risk sensitivity of sea level rise trends, it’s necessary to link local sea level evolution with global warming scenarios 🔥.

🌡️ Global Warming Level (GWL) represents the average air temperature rise 🌞 close to Earth’s surface, compared to the pre-industrial period (1850-1900). GWLs adopted in the latest IPCC report 📑 include 1°C, 1.5°C, 2°C, and 4°C, and MedSeaRise analyzed sea level scenarios for each GWL across Mediterranean areas 🌐.

🔎 Results show that the uncertainty around sea level rise data impacts sensitivity to GWLs, especially at extreme levels 🚨 (see figure 1). This finding sheds light on how sea level scenarios must be integrated into risk assessments 🛠️.

📈 Ongoing work is investigating the large uncertainties within multi-model ensembles, aided by a recent workshop with sea level rise experts 🧑‍🔬 held in Kotor, Montenegro this past October.

🌡️ For comparison, local air temperature responds more sensitively to GWLs, though with seasonal and geographic differences 🗺️ (see figure 2&3).