High Resolution Model Intercomparison Project Research Articles

Impact of model resolution on Arctic sea ice and North Atlantic Ocean heat transport

Arctic sea-ice area and volume have substantially decreased since the beginning of the satellite era. Concurrently, the poleward heat transport from the North Atlantic Ocean into the Arctic has increased, partly contributing to the loss of sea ice. Increasing the horizontal resolution of general circulation models (GCMs) improves their ability to represent the complex interplay of processes at high latitudes. Here, we investigate the impact of model resolution on Arctic sea ice and Atlantic Ocean heat transport (OHT) by using five different state-of-the-art coupled GCMs (12 model configurations in total) that include dynamic representations of the ocean, atmosphere and sea ice. The models participate in the High Resolution Model Intercomparison Project (HighResMIP) of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Model results over the period 1950–2014 are compared to different observational datasets. In the models studied, a finer ocean resolution drives lower Arctic sea-ice area and volume and generally enhances Atlantic OHT. The representation of ocean surface characteristics, such as sea-surface temperature (SST) and velocity, is greatly improved by using a finer ocean resolution. This study highlights a clear anticorrelation at interannual time scales between Arctic sea ice (area and volume) and Atlantic OHT north of 60,^circ hbox {N} in the models studied. However, the strength of this relationship is not systematically impacted by model resolution. The higher the latitude to compute OHT, the stronger the relationship between sea-ice area/volume and OHT. Sea ice in the Barents/Kara and Greenland–Iceland–Norwegian (GIN) Seas is more strongly connected to Atlantic OHT than other Arctic seas.

A statistical and process-oriented evaluation of cloud radiative effects in high-resolution global models

Abstract. This study evaluates the impact of atmospheric horizontal resolution on the representation of cloud radiative effects (CREs) in an ensemble of global climate model simulations following the protocols of the High Resolution Model Intercomparison Project (HighResMIP). We compare results from four European modelling centres, each of which provides data from “standard”- and “high”-resolution model configurations. Simulated radiative fluxes are compared with observation-based estimates derived from the Clouds and Earth's Radiant Energy System (CERES) dataset. Model CRE biases are evaluated using both conventional statistics (e.g. time and spatial averages) and after conditioning on the phase of two modes of internal climate variability, namely the El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). Simulated top-of-atmosphere (TOA) and surface CREs show large biases over the polar regions, particularly over regions where seasonal sea-ice variability is strongest. Increasing atmospheric resolution does not significantly improve these biases. The spatial structure of the cloud radiative response to ENSO and NAO variability is simulated reasonably well by all model configurations considered in this study. However, it is difficult to identify a systematic impact of atmospheric resolution on the associated CRE errors. Mean absolute CRE errors conditioned on the ENSO phase are relatively large (5–10 W m−2) and show differences between models. We suggest this is a consequence of differences in the parameterization of SW radiative transfer and the treatment of cloud optical properties rather than a result of differences in resolution. In contrast, mean absolute CRE errors conditioned on the NAO phase are generally smaller (0–2 W m−2) and more similar across models. Although the regional details of CRE biases show some sensitivity to atmospheric resolution within a particular model, it is difficult to identify patterns that hold across all models. This apparent insensitivity to increased atmospheric horizontal resolution indicates that physical parameterizations play a dominant role in determining the behaviour of cloud–radiation feedbacks. However, we note that these results are obtained from atmosphere-only simulations and the impact of changes in atmospheric resolution may be different in the presence of coupled climate feedbacks.

Climate model configurations of the ECMWF Integrated Forecasting System (ECMWF-IFS cycle 43r1) for HighResMIP

Abstract. This paper presents atmosphere-only and coupled climate model configurations of the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) for different combinations of ocean and atmosphere resolution. These configurations are used to perform multi-decadal ensemble experiments following the protocols of the High Resolution Model Intercomparison Project (HighResMIP) and phase 6 of the Coupled Model Intercomparison Project (CMIP6). These experiments are used to evaluate the sensitivity of major biases in the atmosphere, ocean, and cryosphere to changes in atmosphere and ocean resolution. All configurations successfully reproduce the observed long-term trends in global mean surface temperature. Furthermore, following an adjustment to account for drift in the subsurface ocean, coupled configurations of ECMWF-IFS realistically reproduce observation-based estimates of ocean heat content change since 1950. Climatological surface biases in ECMWF-IFS are relatively insensitive to an increase in atmospheric resolution from ∼ 50 to ∼ 25 km. However, increasing the horizontal resolution of the atmosphere while maintaining the same vertical resolution enhances the magnitude of a cold bias in the lower stratosphere. In coupled configurations, there is a strong sensitivity to an increase in ocean model resolution from 1 to 0.25°. However, this sensitivity to ocean resolution takes many years to fully manifest and is less apparent in the first year of integration. This result has implications for the ECMWF coupled model development strategy that typically relies on the analysis of biases in short ( < 1 year) ensemble (re)forecast data sets. The impacts of increased ocean resolution are particularly evident in the North Atlantic and Arctic, where they are associated with an improved Atlantic meridional overturning circulation, increased meridional ocean heat transport, and more realistic sea-ice cover. In the tropical Pacific, increased ocean resolution is associated with improvements to the magnitude and asymmetry of El Niño–Southern Oscillation (ENSO) variability and better representation of non-linear sea surface temperature (SST)–radiation feedbacks during warm events. However, increased ocean model resolution also increases the magnitude of a warm bias in the Southern Ocean. Finally, there is tentative evidence that both ocean coupling and increased atmospheric resolution can improve teleconnections between tropical Pacific rainfall and geopotential height anomalies in the North Atlantic.

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.