Data supporting the North Atlantic Climate System: Integrated Studies (ACSIS) programme, including atmospheric composition, oceanographic and sea ice observations (2016–2022) and output from ocean, atmosphere, land and sea-ice models (1950–2050)

Abstract

Abstract. The North Atlantic Climate System: Integrated Study (ACSIS) was a large multidisciplinary research programme funded by the United Kingdom’s Natural Environment Research Council (NERC). ACSIS ran from 2016–22 and brought together around 80 scientists from seven leading UK-based environmental research institutes to deliver major advances in understanding North Atlantic climate variability and extremes. Here we present an overview of the data generated by the ACSIS programme. The datasets cover the full North Atlantic System comprising: the North Atlantic Ocean, the atmosphere above it including its composition, Arctic Sea Ice and the Greenland Ice Sheet. Atmospheric composition datasets include measurements from 7 aircraft campaigns (between 3 and 10 flights each, 0–10 km altitude range) in the north eastern Atlantic (~40° W–5° E,~15° N–55° N) made at intervals of from 6 months to 2 years between February 2017 and may 2022. The flights measured chemical species (including greenhouse gases, ozone precursors and VOCs) and aerosols (organic, SO4, NH4, NO3, and nss-Cl) (https://dx.doi.org/10.5285/6285564c34a246fc9ba5ce053d85e5e7 (FAAM et al. (2024)). Ground based stations at the Cape Verde Atmospheric Observatory (CVAO), Penlee Point Atmospheric Observatory (PPAO) and Plymouth Marine Laboratory (PML) recorded ozone, ozone precursors, halocarbons, as well as greenhouse gases (CO2, methane), SO2 and photolysis rates. (CVAO, http://catalogue.ceda.ac.uk/uuid/81693aad69409100b1b9a247b9ae75d5, National Centre for Atmospheric Science et al. (2014)), O3 and CH4 (PPAO, https://catalogue.ceda.ac.uk/uuid/8f1ff8ea77534e08b03983685990a9b0 (Plymouth Marine Laboratory and Yang (2024)) and aerosols (PML, https://dx.doi.org/10.5285/e74491c96ef24df29a9342a3d57b5939, Smyth (2024)). Complementary model simulations of atmospheric composition were performed with the UK Earth System Model, UKESM1, for the period 1982 to 2020 using CMIP6 historical forcing up to 2014 and SSP3-7.0 scenario from 2015–2020. Model temperature and winds were relaxed towards ERA reanalysis. Monthly mean model data for ozone, NO, NO2, CO, methane, stratospheric ozone tracers and 30 regionally emitted tracers are available to download (https://data.ceda.ac.uk/badc/acsis/UKESM1-hindcasts, Abraham (2024)). ACSIS also generated new ocean heat content diagnostics https://doi.org/10/g6wm, https://doi.org/10/g8g2, Moat et al. (2021a–b) and gridded temperature and salinity based on objectively mapped Argo measurements https://doi.org/10.5285/fe8e524d-7f04-41f3-e053-6c86abc04d51 (King (2023). An ensemble of atmosphere-forced global ocean-sea ice simulations using the NEMO-CICE model was performed with horizontal resolutions of ¼° and 1/12° covering the period 1958–2020 using several different atmosphere reanalysis based surface forcing datasets, supplemented by additional global simulations and standalone sea ice model simulations with advanced sea ice physics using the CICE model (http://catalogue.ceda.ac.uk/uuid/770a885a8bc34d51ad71e87ef346d6a8, Megann et al. (2021e). Output is stored as monthly averages and includes 3D potential temperature, salinity, zonal, meridional and vertical velocity; 2D sea surface height, mixed layer depth, surface heat and freshwater fluxes, ice concentration and thickness and a wide variety of other variables. In addition to the data presented here we provide a brief overview of several other datasets that were generated during ACSIS which have been described previously in the literature.

Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator

“…Model simulations of UKESM were performed with a horizontal grid of meteorology (Telford et al, 2008) to allow for better comparison with observations. For more information on the model configuration and details of the simulations, the reader is referred to the model description in Russo et al, (2023) and Archibald et al, (2024).…”