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.
Abstract The Arctic hydrological cycle is amplified due to sea ice decline, which can influence warming and precipitation over land. However, the response of the terrestrial hydrological cycle, in climate models, to Arctic warming may be dependent on model spatial resolution. Two spatial resolutions of the same CMIP6 physical climate model, HadGEM3-GC3.1, show that the hydrological storage terms and precipitation behave identically with warming. The exception is snow volume which declines faster at low spatial resolution. Surface elevations are smoothed for low resolution, with the result that orographically induced precipitation is lower than at higher resolution. As a consequence, low resolution models will likely overestimate the rate of snow decline with warming compared with higher resolution models. Thus, caution is advised when using low resolution climate models for regional snow impact studies, and with mixed resolution models for climate model inter-comparisons,
Abstract We describe the scientific and technical implementation of two models for a core set of experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The models used are the physical atmosphere‐land‐ocean‐sea ice model HadGEM3‐GC3.1 and the Earth system model UKESM1 which adds a carbon‐nitrogen cycle and atmospheric chemistry to HadGEM3‐GC3.1. The model results are constrained by the external boundary conditions (forcing data) and initial conditions. We outline the scientific rationale and assumptions made in specifying these. Notable details of the implementation include an ozone redistribution scheme for prescribed ozone simulations (HadGEM3‐GC3.1) to avoid inconsistencies with the model's thermal tropopause, and land use change in dynamic vegetation simulations (UKESM1) whose influence will be subject to potential biases in the simulation of background natural vegetation. We discuss the implications of these decisions for interpretation of the simulation results. These simulations are expensive in terms of human and CPU resources and will underpin many further experiments; we describe some of the technical steps taken to ensure their scientific robustness and reproducibility.
Abstract. There is an increasing need to understand how water is cycled and transported within the atmosphere to aid water management. Here, atmospheric water tracers are added to the Met Office Unified Model (UM) to allow tracking of water within the model. This requires the implementation of water tracers in the following parts of the model code: large-scale advection, surface evaporation, boundary layer mixing, large-scale precipitation (microphysics), large-scale clouds, stochastic physics and convection. A single water tracer is found to track all water in the model to a high degree of accuracy during a 35-year simulation; the differences are typically less than 10-16 kg kg-1 at the end of every timestep, prior to a very small adjustment to prevent the build up of numerical error. The increase in computing time for each water tracer is between 3.1 and 3.8 % depending on the model resolution. The model development is tested by using the water tracers to find the sources of precipitation in a historical UM simulation. As expected, the majority of precipitation is found to be sourced directly from the ocean, with the recycling of water over land becoming increasingly important downwind across continents. The UM results for the mean evaporative source properties of precipitation are comparable to those of the ECHAM6 atmospheric model, with some interesting local differences over Antarctica, Greenland and the Indian monsoon region. Finally, the components of the model’s global hydrological cycle that can be derived from the water tracers are presented to illustrate the additional information that can be provided from the new development.
Abstract. The Antarctic Ice Sheet will play a crucial role in the evolution of global mean sea level as the climate warms. An interactively coupled climate and ice sheet model is needed to understand the impacts of iceâclimate feedbacks during this evolution. Here we use a two-way coupling between the UK Earth System Model and the BISICLES (Berkeley Ice Sheet Initiative for Climate at Extreme Scales) dynamic ice sheet model to investigate Antarctic iceâclimate interactions under two climate change scenarios. We perform ensembles of SSP1â1.9 and SSP5â8.5 (Shared Socioeconomic Pathway) scenario simulations to 2100, which we believe are the first such simulations with a climate model that include two-way coupling of atmosphere and ocean models to dynamic models of the Greenland and Antarctic ice sheets. We focus our analysis on the latter. In SSP1â1.9 simulations, ice shelf basal melting and grounded ice mass loss from the Antarctic Ice Sheet are generally lower than present rates during the entire simulation period. In contrast, the responses to SSP5â8.5 forcing are strong. By the end of the 21st century, these simulations feature order-of-magnitude increases in basal melting of the Ross and FilchnerâRonne ice shelves, caused by intrusions of masses of warm ocean water. Due to the slow response of ice sheet drawdown, this strong melting does not cause a substantial increase in ice discharge during the simulations. The surface mass balance in SSP5â8.5 simulations shows a pattern of strong decrease on ice shelves, caused by increased melting, and strong increase on grounded ice, caused by increased snowfall. Despite strong surface and basal melting of the ice shelves, increased snowfall dominates the mass budget of the grounded ice, leading to an ensemble mean Antarctic contribution to global mean sea level of a fall of 22âmm by 2100 in the SSP5â8.5 scenario. We hypothesise that this signal would revert to sea-level rise on longer timescales, caused by the ice sheet dynamic response to ice shelf thinning. These results demonstrate the need for fully coupled iceâclimate models in reducing the substantial uncertainty in sea-level rise from the Antarctic Ice Sheet.
Abstract The impact of melt ponds on sea ice albedo has been observed and documented. In general circulation models, ponds are now accounted for through indirect diagnostic treatments (“implicit” schemes) or prognostic melt-pond parameterizations (“explicit” schemes). However, there has been a lack of studies showing the impacts of these schemes on simulated Arctic climate. We focus here on rectifying this using the general circulation model HadGEM3, one of the few models with a detailed explicit pond scheme. We identify the impact of melt ponds on the sea ice and climate, and associated ice–ocean–atmosphere interactions. We run a set of constant forcing simulations for three different periods and show, for the first time, that using mechanistically different pond schemes can lead to very significantly different sea ice and climate states. Under near-future conditions, an implicit scheme never yields an ice-free summer Arctic, while an explicit scheme yields an ice-free Arctic in 35% of years and raises autumn Arctic air temperatures by 5° to 8°C. We find that impacts on climate and sea ice depend on the ice state: under near-future and last-interglacial conditions, the thin sea ice is very sensitive to pond formation and parameterization, whereas during the preindustrial period the thicker sea ice is less sensitive to the pond scheme choice. Both of these two commonly used parameterizations of sea ice albedo yield similar results under preindustrial conditions but in warmer climates lead to very different Arctic sea ice and ocean and atmospheric temperatures. Thus, changes to physical parameterizations in the sea ice model can have large impacts on simulated sea ice, ocean, and atmosphere. Significance Statement This study investigates the impacts of melt ponds on Arctic sea ice under different climate conditions, using the HadGEM3-GC3.1-LL general circulation model (GCM). Additionally, we study the impact of changing the type of pond scheme used. We find that changing the pond scheme causes large differences to how a GCM simulates Arctic sea ice, the ocean, and the atmosphere, for both near-future and warmer paleoclimate conditions. These large differences have not been found previously, because this is one of the first GCM studies of this type. Our results demonstrate the importance of melt ponds, and their wider impacts on ocean and atmosphere. Furthermore, they suggest that better evaluation of the representation of sea ice processes is vital for the robust projection of future climate change.
We assess the response of Antarctic sea ice, the Southern Ocean, and global climate to mass loss from the Antarctic continent in a new multi-model ensemble. Antarctic ice-mass loss from ice sheets and ice shelves is increasing and is projected to increase further as the climate warms. The fresh water entering the Southern Ocean due to this ice-mass loss has been proposed as a mechanism responsible for the lack of decline in Antarctic sea ice area between 1979 and 2015, in contrast to the sea-ice loss seen in the Arctic. The fresh water impacts sea ice by increasing the density gradient between the near-surface waters and deeper waters around the Antarctic continent, which inhibits vertical transport of warmer, deeper water to the surface. This results in surface cooling and increased sea ice growth, as has been shown in previous studies. Though this increased Antarctic ice-mass loss is expected to impact climate it is absent from almost all models in the current Coupled Model Intercomparison Project (CMIP6), which typically enforce that the continent remain in perpetual mass balance, with no gain or loss of mass over time. Further, previous non-CMIP6 model experiments that include changing Antarctic ice-mass loss suggest that the climate response depends on the model used, and that the reasons for this model dependence are not clear. We present results from the Southern Ocean Freshwater Input from Antarctica (SOFIA) Initiative, an international model intercomparison, in which freshwater is added to the ocean surrounding Antarctica to simulate the otherwise missing ice-sheet mass loss. This unique suite of models allows us compare the response to Antarctic mass loss across climate models, identify reasons for model discrepancies, and quantify the potential impact of the absence of increasing Antarctic ice-mass loss on Antarctic sea ice and climate. We will give an overview of the SOFIA initiative including the experiment design and participating models. We will present results from the “antwater” experiment outlined in the SOFIA protocol in which a constant freshwater input of 0.1 Sv is distributed evenly around the Antarctic continent at the ocean surface in an experiment with pre-industrial control forcing. We show that there is a spread of up to a factor of 3 across models in the Antarctic sea ice area response to identical freshwater forcing. There are also substantial differences in the spatial pattern of the sea ice response depending on the model used. We explore the dependence of the response on the mean state of Antarctic sea ice and the Southern Ocean in the pre-industrial control runs, as well as the response of the ocean stratification and oceanic deep convection in the models. We also explore the seasonality of the sea ice and oceanic response.
Low-level winds over Antarctica are overwhelmingly controlled by the local orography. They, in turn, exert a large control on sea ice formation and transport. In Global Circulation Models, the influence of orography on the climate system is modelled via orographic gravity wave drag (OGWD) parameterizations. Models usually partition the drag exerted on the atmosphere by the sub-grid scale orography into two components due to flow blocking and gravity waves. In this work, we investigate the relationship between Antarctic sea ice and the parameterized OGWD in the UK Earth System Model (UKESM). We present results from sensitivity tests performed using the UKESM-CMIP6 historical runs.In these simulations, the partition between the “flow-blocking” component and the “gravity wave” component of the OGWD parameterization was altered to simulate “flow-over” and “flow-blocking” regimes. These experiments show that sea ice strongly responds to changes in the orographic gravity wave drag. The strong sea ice decline simulated by the control run from 1980 to 2015, not matched by the observational record, is halted and is delayed by 15-20 years (across the ensemble members) in our flow-blocking regime simulation. Conversely, in the flow-over regime simulation, sea ice begins declining about 10 years earlier than in the control run. The systematic response of the coupled system suggests the existence of a dynamical relationship between sea ice and OGWD. The pan-Antarctic signal for sea ice decline derives from the Weddell Sea sector. The pathway through which OGWD influences sea ice is via modifications of the flow regime across the Antarctic Peninsula, and thus the surface wind stress across the Weddell Sea sector, which in turn alters the occurrence of oceanic deep convection. This happens because the flow regime across the Antarctic Peninsula is critical in determining the strength and pattern of the surface winds on both the windward side (Bellingshausen and Amundsen Seas sector) and the lee side (Weddell Sea sector) of the mountain ridge.
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