Improving the simulation of landfast ice by combining tensile strength and a parameterization for grounded ridges

ABSTRACT: In some coastal regions of the Arctic Ocean, grounded ice ridges contribute to stabilizing andmaintaining a landfast ice cover. Recently, a grounding scheme representing this effect on sea ice dynamicswas introduced and tested in a viscous-plastic sea ice model. This grounding scheme, based on a basalstress parameterization, improves the simulation of landfast ice in many regions such as in the East SiberianSea, the Laptev Sea, and along the coast of Alaska. Nevertheless, in some regions like the Kara Sea, the areaof landfast ice is systematically underestimated. This indicates that another mechanism such as ice archingis at play for maintaining the ice cover fast. To address this problem, the combination of the basal stressparameterization and tensile strength is investigated using a 0.258Pan-Arctic CICE-NEMO configuration.Both uniaxial and isotropic tensile strengths notably improve the simulation of landfast ice in the Kara Seabut also in the Laptev Sea. However, the simulated landfast ice season for the Kara Sea is too short com-pared to observations. This is especially obvious for the onset of the landfast ice season which systematical-ly occurs later in the model and with a slower build up. This suggests that improvements to the sea icethermodynamics could reduce these discrepancies with the data. Key Points - A grounding scheme is not enough to simulate landfast ice in Pan-Arctic simulations; - Both uniaxial and isotropic tensile strengths notably improve the simulation of landfast ice in deep coastal regions; - Simulated landfast ice season in the Kara Sea is still too short suggesting that thermodynamics should be improved

The importance of sea ice area biases in 21st century multimodel projections of Antarctic temperature and precipitation

Climate models exhibit large biases in sea ice area (SIA) in their historical simulations. This study explores the impacts of these biases on multimodel uncertainty in Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble projections of 21st century change in Antarctic surface temperature, net precipitation, and SIA. The analysis is based on time slice climatologies in the Representative Concentration Pathway 8.5 future scenario (2070–2099) and historical (1970–1999) simulations across 37 different CMIP5 models. Projected changes in net precipitation, temperature, and SIA are found to be strongly associated with simulated historical mean SIA (e.g., cross-model correlations of r = 0.77, 0.71, and −0.85, respectively). Furthermore, historical SIA bias is found to have a large impact on the simulated ratio between net precipitation response and temperature response. This ratio is smaller in models with smaller-than-observed SIA. These strong emergent relationships on SIA bias could, if found to be physically robust, be exploited to give more precise climate projections for Antarctica

High Energy QCD: Stringy Picture from Hidden Integrability

We discuss the stringy properties of high-energy QCD using its hidden integrability in the Regge limit and on the light-cone. It is shown that multi-colour QCD in the Regge limit belongs to the same universality class as superconformal $\cal{N}$=2 SUSY YM with $N_f=2N_c$ at the strong coupling orbifold point. The analogy with integrable structure governing the low energy sector of $\cal{N}$=2 SUSY gauge theories is used to develop the brane picture for the Regge limit. In this picture the scattering process is described by a single M2 brane wrapped around the spectral curve of the integrable spin chain and unifying hadrons and reggeized gluons involved in the process. New quasiclassical quantization conditions for the complex higher integrals of motion are suggested which are consistent with the $S-$duality of the multi-reggeon spectrum. The derivation of the anomalous dimensions of the lowest twist operators is formulated in terms of the Riemann surfacesComment: 37 pages, 3 figure

A SIMULATED REDUCTION IN ANTARCTIC SEA-ICE AREA SINCE 1750: IMPLICATIONS OF THE LONG MEMORY OF THE OCEAN

Using the three-dimensional coarse-resolution climate model ECBILT-CLIO, 1000-year long ensemble simulations with natural and anthropogenic forcings have been performed to study the long-term variation of the ice cover in the Southern Ocean. Over the last 250 years, the ice area has decreased by about 1 x 10(6) km(2) in its annual mean. A comparison with experiments driven by only natural forcings suggests that this reduction is due to both natural and anthropogenic forcing, the latter playing a larger role than natural forcing over the last 150 years. Despite this contribution from anthropogenic forcing, the simulated ice area at the end of the 20th century is similar to that simulated during the 14th century because of the slow response of the Southern Ocean to radiative forcing. Sensitivity experiments performed with the model show that the model's initial conditions have a large influence on the simulated ice cover and that it is necessary to start simulations at least two centuries before the period of interest in order to remove this influence. Copyright (c) 2005 Royal Meteorological Society

Variation in climate sensitivity and feedback parameters during the historical period

We investigate the climate feedback parameter α (W m−2 K−1) during the historical period (since 1871) in experiments using the HadGEM2 and HadCM3 atmosphere general circulation models (AGCMs) with constant preindustrial atmospheric composition and time-dependent observational sea surface temperature (SST) and sea ice boundary conditions. In both AGCMs, for the historical period as a whole, the effective climate sensitivity is ∼2 K (α≃1.7 W m−2 K−1), and α shows substantial decadal variation caused by the patterns of SST change. Both models agree with the AGCMs of the latest Coupled Model Intercomparison Project in showing a considerably smaller effective climate sensitivity of ∼1.5 K (α = 2.3 ± 0.7 W m−2 K−1), given the time-dependent changes in sea surface conditions observed during 1979–2008, than the corresponding coupled atmosphere-ocean general circulation models (AOGCMs) give under constant quadrupled CO2 concentration. These findings help to relieve the apparent contradiction between the larger values of effective climate sensitivity diagnosed from AOGCMs and the smaller values inferred from historical climate change

Ocean‐Only FAFMIP: Understanding Regional Patterns of Ocean Heat Content and Dynamic Sea Level Change

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Causes of differences in model and satellite tropospheric warming rates

In the early twenty-first century, satellite-derived tropospheric warming trends were generally smaller than trends estimated from a large multi-model ensemble. Because observations and coupled model simulations do not have the same phasing of natural internal variability, such decadal differences in simulated and observed warming rates invariably occur. Here we analyse global-mean tropospheric temperatures from satellites and climate model simulations to examine whether warming rate differences over the satellite era can be explained by internal climate variability alone. We find that in the last two decades of the twentieth century, differences between modelled and observed tropospheric temperature trends are broadly consistent with internal variability. Over most of the early twenty-first century, however, model tropospheric warming is substantially larger than observed; warming rate differences are generally outside the range of trends arising from internal variability. The probability that multi-decadal internal variability fully explains the asymmetry between the late twentieth and early twenty-first century results is low (between zero and about 9%). It is also unlikely that this asymmetry is due to the combined effects of internal variability and a model error in climate sensitivity. We conclude that model overestimation of tropospheric warming in the early twenty-first century is partly due to systematic deficiencies in some of the post-2000 external forcings used in the model simulations

Sea-breeze dynamics and convection initiation: the influence of convective parameterization in weather and climate model biases

There are some long-established biases in atmospheric models that originate from the representation of tropical convection. Previously, it has been difficult to separate cause and effect because errors are often the result of a number of interacting biases. Recently, researchers have gained the ability to run multiyear global climate model simulations with grid spacings small enough to switch the convective parameterization off, which permits the convection to develop explicitly. There are clear improvements to the initiation of convective storms and the diurnal cycle of rainfall in the convection-permitting simulations, which enables a new process-study approach to model bias identification. In this study, multiyear global atmosphere-only climate simulations with and without convective parameterization are undertaken with the Met Office Unified Model and are analyzed over the Maritime Continent region, where convergence from sea-breeze circulations is key for convection initiation. The analysis shows that, although the simulation with parameterized convection is able to reproduce the key rain-forming sea-breeze circulation, the parameterization is not able to respond realistically to the circulation. A feedback of errors also occurs: the convective parameterization causes rain to fall in the early morning, which cools and wets the boundary layer, reducing the land–sea temperature contrast and weakening the sea breeze. This is, however, an effect of the convective bias, rather than a cause of it. Improvements to how and when convection schemes trigger convection will improve both the timing and location of tropical rainfall and representation of sea-breeze circulations

Investigating the impact of CO2 on low-frequency variability of the AMOC in HadCM3

This study investigates the impact of CO2 on the amplitude, frequency, and mechanisms of Atlantic meridional overturning circulation (AMOC) variability in millennial simulations of the HadCM3 coupled climate model. Multichannel singular spectrum analysis (MSSA) and empirical orthogonal functions (EOFs) are applied to the AMOC at four quasi-equilibrium CO2 forcings. The amount of variance explained by the first and second eigenmodes appears to be small (i.e., 11.19%); however, the results indicate that both AMOC strength and variability weaken at higher CO2 concentrations. This accompanies an apparent shift from a predominant 100–125-yr cycle at 350 ppm to 160 yr at 1400 ppm. Changes in amplitude are shown to feed back onto the atmosphere. Variability may be linked to salinity-driven density changes in the Greenland–Iceland– Norwegian Seas, fueled by advection of anomalies predominantly from the Arctic and Caribbean regions. A positive density anomaly accompanies a decrease in stratification and an increase in convection and Ekman pumping, generating a strong phase of the AMOC (and vice versa). Arctic anomalies may be generated via an internal ocean mode that may be key in driving variability and are shown to weaken at higher CO2, possibly driving the overall reduction in amplitude. Tropical anomalies may play a secondary role in modulating variability and are thought to be more influential at higher CO2, possibly due to an increased residence time in the subtropical gyre and/or increased surface runoff driven by simulated dieback of the Amazon rain forest. These results indicate that CO2 may not only weaken AMOC strength but also alter the mechanisms that drive variability, both of which have implications for climate change on multicentury time scales