U.K. Community Earth System Modeling for CMIP6.

We describe the approach taken to develop the United Kingdom's first community Earth system model, UKESM1. This is a joint effort involving the Met Office and the Natural Environment Research Council (NERC), representing the U.K. academic community. We document our model development procedure and the subsequent U.K. submission to CMIP6, based on a traceable hierarchy of coupled physical and Earth system models. UKESM1 builds on the well-established, world-leading HadGEM models of the physical climate system and incorporates cutting-edge new representations of aerosols, atmospheric chemistry, terrestrial carbon, and nitrogen cycles and an advanced model of ocean biogeochemistry. A high-level metric of overall performance shows that both models, HadGEM3-GC3.1 and UKESM1, perform better than most other CMIP6 models so far submitted for a broad range of variables. We point to much more extensive evaluation performed in other papers in this special issue. The merits of not using any forced climate change simulations within our model development process are discussed. First results from HadGEM3-GC3.1 and UKESM1 include the emergent climate sensitivity (5.5 and 5.4 K, respectively) which is high relative to the current range of CMIP5 models. The role of cloud microphysics and cloud-aerosol interactions in driving the climate sensitivity, and the systematic approach taken to understand this role, is highlighted in other papers in this special issue. We place our findings within the broader modeling landscape indicating how our understanding of key processes driving higher sensitivity in the two U.K. models seems to align with results from a number of other CMIP6 models.

A field comparison of marine mammal detections via visual, acoustic, and infrared (IR) imaging methods offshore Atlantic Canada.

Impulsive sounds generated during seismic surveys have elicited behavioral responses in marine mammals and could cause hearing impairment or injury. Mitigating exposure to seismic sound often relies on real-time marine mammal detection. Detection performance is influenced by detection method, environmental conditions, and observer experience. We conducted a field comparison of real-time detections made by marine mammal observers (MMOs), a rotating infrared (IR) camera, and via passive acoustic monitoring (PAM). Data were collected from a 38 m research vessel offshore Atlantic Canada. Our results indicate that overall detection rates increase when complementary methods are used. MMOs and PAM are likely the most effective combination during high seas and precipitation. PAM and IR can be used in darkness. In good visibility, MMOs with IR or PAM should increase detections. Our results illustrate the importance of addressing false positive IR detections, matching system capabilities to sea conditions/species of interest, and employing experienced observers.

The Low-Resolution Version of HadGEM3 GC3.1: Development and Evaluation for Global Climate.

A new climate model, HadGEM3 N96ORCA1, is presented that is part of the GC3.1 configuration of HadGEM3. N96ORCA1 has a horizontal resolution of ~135 km in the atmosphere and 1° in the ocean and requires an order of magnitude less computing power than its medium-resolution counterpart, N216ORCA025, while retaining a high degree of performance traceability. Scientific performance is compared to both observations and the N216ORCA025 model. N96ORCA1 reproduces observed climate mean and variability almost as well as N216ORCA025. Patterns of biases are similar across the two models. In the northwest Atlantic, N96ORCA1 shows a cold surface bias of up to 6 K, typical of ocean models of this resolution. The strength of the Atlantic meridional overturning circulation (16 to 17 Sv) matches observations. In the Southern Ocean, a warm surface bias (up to 2 K) is smaller than in N216ORCA025 and linked to improved ocean circulation. Model El Niño/Southern Oscillation and Atlantic Multidecadal Variability are close to observations. Both the cold bias in the Northern Hemisphere (N96ORCA1) and the warm bias in the Southern Hemisphere (N216ORCA025) develop in the first few decades of the simulations. As in many comparable climate models, simulated interhemispheric gradients of top-of-atmosphere radiation are larger than observations suggest, with contributions from both hemispheres. HadGEM3 GC3.1 N96ORCA1 constitutes the physical core of the UK Earth System Model (UKESM1) and will be used extensively in the Coupled Model Intercomparison Project 6 (CMIP6), both as part of the UK Earth System Model and as a stand-alone coupled climate model.

The Rossby Centre Regional Atmospheric Climate Model part I: model climatology and performance for the present climate over Europe.

The Rossby Centre Atmospheric Regional Climate Model (RCA2) is described and simulation results, for the present climate over Europe, are evaluated against available observations. Systematic biases in the models mean climate and climate variability are documented and key parameterization weaknesses identified. The quality of near-surface parameters is investigated in some detail, particularly temperature, precipitation, the surface energy budget and cloud cover. The model simulates the recent, observed climate and variability with a high degree of realism. Compensating errors in the components of the surface radiation budget are highlighted and the fundamental causes of these biases are traced to the relevant aspects of the cloud, precipitation and radiation parameterizations. The model has a tendency to precipitate too frequently at small rates, this has a direct impact on the simulation of cloud-radiation interaction and surface temperatures. Great care must be taken in the use of observations to evaluate high resolution RCMs, when they are forced by analyzed boundary conditions. This is particularly true with respect to precipitation and cloudiness, where observational uncertainty is often larger than the RCM bias.

The Rossby Centre Regional Atmospheric Climate Model part II: application to the Arctic climate.

The Rossby Centre regional climate model (RCA2) has been integrated over the Arctic Ocean as part of the international ARCMIP project. Results have been compared to observations derived from the SHEBA data set. The standard RCA2 model overpredicts cloud cover and downwelling longwave radiation, during the Arctic winter. This error was improved by introducing a new cloud parameterization, which significantly improves the annual cycle of cloud cover. Compensating biases between clear sky downwelling longwave radiation and longwave radiation emitted from cloud base were identified. Modifications have been introduced to the model radiation scheme that more accurately treat solar radiation interaction with ice crystals. This leads to a more realistic representation of cloud-solar radiation interaction. The clear sky portion of the model radiation code transmits too much solar radiation through the atmosphere, producing a positive bias at the top of the frequent boundary layer clouds. A realistic treatment of the temporally evolving albedo, of both sea-ice and snow, appears crucial for an accurate simulation of the net surface energy budget. Likewise, inclusion of a prognostic snow-surface temperature seems necessary, to accurately simulate near-surface thermodynamic processes in the Arctic.