The sea ice model component of HadGEM3-GC3.1

A new sea ice configuration, GSI8.1, is implemented in the Met Office global coupled configuration HadGEM3-GC3.1 which will be used for all CMIP6 (Coupled Model Intercomparison Project Phase 6) simulations. The inclusion of multi-layer thermodynamics has required a semi-implicit coupling scheme between atmosphere and sea ice to ensure the stability of the solver. Here we describe the sea ice model component and show that the Arctic thickness and extent compare well with observationally based data

Improving Arctic weather and seasonal climate prediction: recommendations for future forecast systems evolution from the European project APPLICATE

The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development.The results discussed in this article were supported by the project APPLICATE (727862), funded by the European Union's Horizon 2020 research and innovation programme. PO was additionally supported by the Spanish fellowship RYC-2017-22772.Peer ReviewedArticle signat per 29 autors/es: Pablo Ortega (1), Edward W. Blockley (2), Morten Køltzow (3), François Massonnet (4), Irina Sandu (5), Gunilla Svensson (6), Juan C. Acosta Navarro (1), Gabriele Arduini (5), Lauriane Batté (7), Eric Bazile (7), Matthieu Chevallier (8), Rubén Cruz-García (1), Jonathan J. Day (5), Thierry Fichefet (4), Daniela Flocco (9), Mukesh Gupta (4), Kerstin Hartung (6,10), Ed Hawkins (9), Claudia Hinrichs (11), Linus Magnusson (5), Eduardo Moreno-Chamarro (1), Sergio Pérez-Montero (1), Leandro Ponsoni (4), Tido Semmler (11), Doug Smith (2), Jean Sterlin (4), Michael Tjernström (6), Ilona Välisuo (7,12), and Thomas Jung (11,13) // (1) Barcelona Supercomputing Center, Barcelona, Spain | (2) Met Office, Exeter, UK | (3) Norwegian Meteorological Institute, Oslo, Norway | (4) Université catholique de Louvain, Earth and Life Institute, Georges Lemaître Centre for Earth and Climate Research, Louvain-la-Neuve, Belgium | (5) European Centre for Medium-Range Weather Forecasts, Reading, UK | (6) Department of Meteorology, Stockholm University, Stockholm, Sweden | (7) CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France | (8) Météo-France, Toulouse, France | (9) National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, UK. | (10) Now at: Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany | (11) Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany | (12) Now at: Meteorology Unit, Finnish Meteorological Institute, Helsinki, Finland | (13) Department of Physics and Electrical Engineering, University of Bremen, Bremen, GermanyPostprint (published version

Antarctic Sea Ice Area in CMIP6

Fully coupled climate models have long shown a wide range of Antarctic sea ice states and evolution over the satellite era. Here, we present a high‐level evaluation of Antarctic sea ice in 40 models from the most recent phase of the Coupled Model Intercomparison Project (CMIP6). Many models capture key characteristics of the mean seasonal cycle of sea ice area (SIA), but some simulate implausible historical mean states compared to satellite observations, leading to large intermodel spread. Summer SIA is consistently biased low across the ensemble. Compared to the previous model generation (CMIP5), the intermodel spread in winter and summer SIA has reduced, and the regional distribution of sea ice concentration has improved. Over 1979–2018, many models simulate strong negative trends in SIA concurrently with stronger‐than‐observed trends in global mean surface temperature (GMST). By the end of the 21st century, models project clear differences in sea ice between forcing scenarios

UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions

Versions 6 and 7 of the UK Global Ocean configuration (known as GO6 and GO7) will form the ocean components of the Met Office GC3.1 coupled model and UKESM1 earth system model to be used in CMIP61 simulations. The label “GO6” refers to a traceable hierarchy of three model configurations at nominal 1, 1∕4 and 1∕12° resolutions. The GO6 configurations are described in detail with particular focus on aspects which have been updated since the previous version (GO5). Results of 30-year forced ocean-ice integrations with the 1∕4° model are presented, in which GO6 is coupled to the GSI8.1 sea ice configuration and forced with CORE22 fluxes. GO6-GSI8.1 shows an overall improved simulation compared to GO5-GSI5.0, especially in the Southern Ocean where there are more realistic summertime mixed layer depths, a reduced near-surface warm and saline biases, and an improved simulation of sea ice. The main drivers of the improvements in the Southern Ocean simulation are tuning of the vertical and isopycnal mixing parameters. Selected results from the full hierarchy of three resolutions are shown. Although the same forcing is applied, the three models show large-scale differences in the near-surface circulation and in the short-term adjustment of the overturning circulation. The GO7 configuration is identical to the GO6 1∕4° configuration except that the cavities under the ice shelves are opened. Opening the ice shelf cavities has a local impact on temperature and salinity biases on the Antarctic shelf with some improvement in the biases in the Weddell Sea

Evaluating the physical and biogeochemical state of the global ocean component of UKESM1 in CMIP6 historical simulations

The ocean plays a key role in modulating the climate of the Earth system (ES). At the present time it is also a major sink both for the carbon dioxide (CO2) released by human activities and for the excess heat driven by the resulting atmospheric greenhouse effect. Understanding the ocean's role in these processes is critical for model projections of future change and its potential impacts on human societies. A necessary first step in assessing the credibility of such future projections is an evaluation of their performance against the present state of the ocean. Here we use a range of observational fields to validate the physical and biogeochemical performance of the ocean component of UKESM1, a new Earth system model (ESM) for CMIP6 built upon the HadGEM3-GC3.1 physical climate model. Analysis focuses on the realism of the ocean's physical state and circulation, its key elemental cycles, and its marine productivity. UKESM1 generally performs well across a broad spectrum of properties, but it exhibits a number of notable biases. Physically, these include a global warm bias inherited from model spin-up, excess northern sea ice but insufficient southern sea ice and sluggish interior circulation. Biogeochemical biases found include shallow remineralization of sinking organic matter, excessive iron stress in regions such as the equatorial Pacific, and generally lower surface alkalinity that results in decreased surface and interior dissolved inorganic carbon (DIC) concentrations. The mechanisms driving these biases are explored to identify consequences for the behaviour of UKESM1 under future climate change scenarios and avenues for model improvement. Finally, across key biogeochemical properties, UKESM1 improves in performance relative to its CMIP5 precursor and performs well alongside its fellow members of the CMIP6 ensemble

Historical simulations with HadGEM3-GC3.1 for CMIP6

We describe and evaluate historical simulations which use the third Hadley Centre Global Environment Model in the Global Coupled configuration 3.1 (HadGEM3-GC3.1) model and which form part of the UK's contribution to the sixth Coupled Model Intercomparison Project, CMIP6. These simulations, run at two resolutions, respond to historically evolving forcings such as greenhouse gases, aerosols, solar irradiance, volcanic aerosols, land use, and ozone concentrations. We assess the response of the simulations to these historical forcings and compare against the observational record. This includes the evolution of global mean surface temperature, ocean heat content, sea ice extent, ice sheet mass balance, permafrost extent, snow cover, North Atlantic sea surface temperature and circulation, and decadal precipitation. We find that the simulated time evolution of global mean surface temperature broadly follows the observed record but with important quantitative differences which we find are most likely attributable to strong effective radiative forcing from anthropogenic aerosols and a weak pattern of sea surface temperature response in the low to middle latitudes to volcanic eruptions. We also find evidence that anthropogenic aerosol forcings play a role in driving the Atlantic Multidecadal Variability and the Atlantic Meridional Overturning Circulation, which are key features of the North Atlantic ocean. Overall, the model historical simulations show many features in common with the observed record over the period 1850–2014 and so provide a basis for future in-depth study of recent climate change

The coupled atmosphere-ocean response to Antarctic sea-ice loss

Antarctic sea ice is projected to decrease in response to increasing greenhouse gas concentrations. Limited studies so far have examined the coupled atmosphere-ocean response to Antarctic sea-ice loss. Here, we isolate the response to Antarctic sea-ice loss in the atmosphere and ocean using bespoke sea-ice albedo perturbation experiments with HadGEM3-GC31-LL, provide the first detailed examination of the global ocean response, and quantify the importance of atmosphere-ocean coupling, through comparison to uncoupled experiments with prescribed Antarctic sea-ice loss. Lower tropospheric warming and moistening over regions of sea-ice loss and the nearby Southern Ocean are simulated in both coupled and uncoupled configurations but are of greater magnitude in the coupled model. A weakening and equatorward shift of the tropospheric westerly jet are simulated in both configurations, but are also larger in the coupled model. Ocean coupling allows the warming response to spread northward, and by poleward atmospheric energy transport, back to the Antarctic interior. Warmer tropical sea surface temperatures enhance atmospheric convection, driving upper-tropospheric warming and triggering atmospheric teleconnections to the extratropics, including a weakened Aleutian Low. A 20% reduction in Antarctic Circumpolar Current transport and a weakening of the shallow tropical convergence cell are simulated. Surface waters warm and freshen globally, becoming more stratified and stable in the Southern Ocean, with similar changes, but of lesser magnitude, in the Arctic Ocean, where sea ice declines. Our results suggest that the climate effects of Antarctic sea-ice loss stretch from pole-to-pole and from the heights of the tropical troposphere to the depths of the Southern Ocean

A multiple length scale correlation operator for ocean data assimilation

Ocean data assimilation systems can take into account time and space scale variations by representing background error covariance functions with more complex shapes than the classical Gaussian function. In particular, the construction of the correlation functions can be improved to give more flexibility. We describe a correlation operator that features high correlations within a short scale and weak correlations within a larger scale. This multiple length scale correlation operator is defined as a linear combination of Whittle–Matérn functions with different length scales. The main characteristics of the resulting correlation function are described. In particular, a focus is given on features that might be of interest to determine the parameters of the model: the Daley length scale, the normalised spectrum inflexion point and the kurtosis coefficient.The multiple length scale operator has been implemented in NEMOVAR, a variational ocean data assimilation system. A dual length scale formulation was tested in a one-year reanalysis and compared with a single length scale formulation. The results emphasise the importance of estimating with great care the factors used within the combination. They also demonstrate the potential of the dual length scale formulation, in particular through a decrease of the innovation statistics for salinity profiles. The dual length scale formulation is now operational at the Met Office