Global Marine Flyways Identified for Long‐Distance Migrating Seabirds From Tracking Data

Aim: To identify the broad‐scale oceanic migration routes (‘marine flyways’) used by multiple pelagic, long‐distance migratory seabirds based on a global compilation of tracking data. Location: Global. Time Period: 1989–2023. Major Taxa Studied: Seabirds (Families: Phaethontidae, Hydrobatidae, Diomedeidae, Procellariidae, Laridae and Stercorariidae). Methods: We collated a comprehensive global tracking dataset that included the migratory routes of 48 pelagic and long‐distance migrating seabird species across the Atlantic, Indian, Pacific and Southern Oceans. We grouped individuals that followed similar routes, independent of species or timings of migration, using a dynamic time warping clustering approach. We visualised the routes of each cluster using a line density analysis and used knowledge of seabird spatial ecology to combine the clusters to identify the broad‐scale flyways followed by most pelagic migratory seabirds tracked to‐date at an ocean‐basin scale. Results: Six marine flyways were identified across the world's oceans: the Atlantic Ocean Flyway, North Indian Ocean Flyway, East Indian Ocean Flyway, West Pacific Ocean Flyway, Pacific Ocean Flyway and Southern Ocean Flyway. Generally, the flyways were used bidirectionally, and individuals either followed sections of a flyway, a complete flyway, or their movements linked two or more flyways. Transhemispheric figure‐of‐eight routes in the Atlantic and Pacific oceans, and a circumnavigation flyway in the Southern Ocean correspond with major wind ‐ driven ocean currents. Main Conclusions: The marine flyways identified demonstrate that pelagic seabirds have similar and repeatable migration routes across ocean‐basin scales. Our study highlights the need to account for connectivity in seabird conservation and provides a framework for international cooperation

Clear-sky ultraviolet radiation modelling using output from the Chemistry Climate Model Initiative

Abstract. We have derived values of the ultraviolet index (UVI) at solar noon using the Tropospheric Ultraviolet Model (TUV) driven by ozone, temperature and aerosol fields from climate simulations of the first phase of the Chemistry-Climate Model Initiative (CCMI-1). Since clouds remain one of the largest uncertainties in climate projections, we simulated only the clear-sky UVI. We compared the modelled UVI climatologies against present-day climatological values of UVI derived from both satellite data (the OMI-Aura OMUVBd product) and ground-based measurements (from the NDACC network). Depending on the region, relative differences between the UVI obtained from CCMI/TUV calculations and the ground-based measurements ranged between −5.9 % and 10.6 %. We then calculated the UVI evolution throughout the 21st century for the four Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0 and 8.5). Compared to 1960s values, we found an average increase in the UVI in 2100 (of 2 %–4 %) in the tropical belt (30∘ N–30∘ S). For the mid-latitudes, we observed a 1.8 % to 3.4 % increase in the Southern Hemisphere for RCPs 2.6, 4.5 and 6.0 and found a 2.3 % decrease in RCP 8.5. Higher increases in UVI are projected in the Northern Hemisphere except for RCP 8.5. At high latitudes, ozone recovery is well identified and induces a complete return of mean UVI levels to 1960 values for RCP 8.5 in the Southern Hemisphere. In the Northern Hemisphere, UVI levels in 2100 are higher by 0.5 % to 5.5 % for RCPs 2.6, 4.5 and 6.0 and they are lower by 7.9 % for RCP 8.5. We analysed the impacts of greenhouse gases (GHGs) and ozone-depleting substances (ODSs) on UVI from 1960 by comparing CCMI sensitivity simulations (1960–2100) with fixed GHGs or ODSs at their respective 1960 levels. As expected with ODS fixed at their 1960 levels, there is no large decrease in ozone levels and consequently no sudden increase in UVI levels. With fixed GHG, we observed a delayed return of ozone to 1960 values, with a corresponding pattern of change observed on UVI, and looking at the UVI difference between 2090s values and 1960s values, we found an 8 % increase in the tropical belt during the summer of each hemisphere. Finally we show that, while in the Southern Hemisphere the UVI is mainly driven by total ozone column, in the Northern Hemisphere both total ozone column and aerosol optical depth drive UVI levels, with aerosol optical depth having twice as much influence on the UVI as total ozone column does. </jats:p

Clear-sky ultraviolet radiation modelling using output from the Chemistry Climate Model Initiative

International audienceWe have derived values of the ultraviolet index (UVI) at solar noon using the Tropospheric Ultraviolet Model (TUV) driven by ozone, temperature and aerosol fields from climate simulations of the first phase of the Chemistry-Climate Model Initiative (CCMI-1). Since clouds remain one of the largest uncertainties in climate projections, we simulated only the clear-sky UVI. We compared the modelled UVI climatologies against present-day climatological values of UVI derived from both satellite data (the OMI-Aura OMUVBd product) and ground-based measurements (from the NDACC network). Depending on the region, relative differences between the UVI obtained from CCMI/TUV calculations and the ground-based measurements ranged between − 5.9 % and 10.6 %. We then calculated the UVI evolution throughout the 21st century for the four Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0 and 8.5). Compared to 1960s values, we found an average increase in the UVI in 2100 (of 2 %-4 %) in the tropical belt (30 • N-30 • S). For the mid-latitudes, we observed a 1.8 % to 3.4 % increase in the Southern Hemisphere for RCPs 2.6, 4.5 and 6.0 and found a 2.3 % decrease in RCP 8.5. Higher increases in UVI are projected in the Northern Hemisphere except for RCP 8.5. At high latitudes, ozone recovery is well identified and induces a complete return of mean UVI levels to 1960 values for RCP 8.5 in the Southern Hemisphere. In the Northern Hemisphere, UVI levels in 2100 are higher by 0.5 % to 5.5 % for RCPs 2.6, 4.5 and 6.0 and they are lower by 7.9 % for RCP 8.5. We analysed the impacts of greenhouse gases (GHGs) and ozone-depleting substances (ODSs) on UVI from 1960 by comparing CCMI sensitivity simulations (1960-2100) with fixed GHGs or ODSs at their respective 1960 levels. As expected with ODS fixed at their 1960 levels, there is no large decrease in ozone levels and consequently no sudden increase in UVI levels. With fixed GHG, we observed a delayed return of ozone to 1960 values, with a corresponding pattern of change observed on UVI, and looking at the UVI difference between 2090s values and 1960s values, we found an 8 % increase in the tropical belt during the summer of each hemisphere. Finally we show that, while in the Southern Hemisphere the UVI is mainly driven by total ozone column, in the Northern Hemisphere both total ozone column and aerosol optical depth drive UVI levels, with aerosol optical depth having twice as much influence on the UVI as total ozone column does

Ultraviolet Radiation evolution during the 21st century

International audienceIn the context of a changing climate, the acceleration of the Brewer-Dobson circulation [Butchart 2014] leadsto a decrease of the ozone total column in the tropics. This decrease affects directly surface ultraviolet radiation,which are already very high in this area. Following the work of (Bais et al., 2011), (Butchart, 2014)and (Hegglin & Shepherd, 2009) on the future evolution of surface irradiance derived from Chemistry ClimateModels (CCM) projections, we projected here surface irradiance from 2010 to 2100 with focus on the tropics.We used the latest chemistry climate projection exercise ; Chemistry Climate Model Initiative (CCMI) coupledwith a radiative transfer model (TUV (Madronich, 1993)) to calculate the evolution of surface Ultravioletradiation throughout the 21st century. Ultraviolet Index (UVi) has been specifically considered (McKenzie,Matthews, & Johnston, 1991).At first, simulation from RefC2 Chemistry Climate Model Initiative have been coupled with a radiativetransfer model, in order to obtained modeled UV index (UVi-M). UVi-M is then compared against availablesatellite ultraviolet radiation observations (OMI OMUVbd product) between 2005 and 2016. Statistical differenceand variance have been analysed versus different parameters: geographical location, model or ensembleof model outputs used in the radiative transfer calculation