Plasticity and dynamical heterogeneity in driven glassy materials

Many amorphous glassy materials exhibit complex spatio-temporal mechanical response and rheology, characterized by an intermittent stress-strain response and a fluctuating velocity profile. Under quasistatic and athermal deformation protocols this heterogeneous plastic flow was shown to be composed of plastic events of various sizes. In this paper, through numerical study of a 2D LJ amorphous solid, we generalize the study of the heterogeneous dynamics of glassy materials to the finite shear-rate and temperature case. The global mechanical response obtained through the use of Molecular Dynamics is shown to converge to the quasistatic limit obtained with an energy minimization protocol. The detailed analysis of the plastic deformation at different shear rates shows that the glass follows different flow regimes. At sufficiently low shear rates the mechanical response reaches a shear-rate independent regime that exhibits all the characteristics of the quasistatic response (finite size effects, yield stress...). At intermediate shear rates the rheological properties are determined by the externally applied shear-rate. Finally at higher shear the system reaches a shear-rate independent homogeneous regime. The existence of these three regimes is also confirmed by the detailed analysis of the atomic motion. The computation of the four-point correlation function shows that the transition from the shear-rate dominated to the quasistatic regime is accompanied by the growth of a dynamical cooperativity length scale $\xi$ that is shown to diverge with shear rate. This divergence is compared with the prediction of a simple model that assumes the diffusive propagation of plastic events.Comment: 22 pages, 15 figures, submitted to EPJ

Network connectivity between the winter Arctic Oscillation and summer sea ice in CMIP6 models and observations

The indirect effect of winter Arctic Oscillation (AO) events on the following summer Arctic sea ice extent suggests an inherent winter-to-summer mechanism for sea ice predictability. On the other hand, operational regional summer sea ice forecasts in a large number of coupled climate models show a considerable drop in predictive skill for forecasts initialised prior to the date of melt onset in spring, suggesting that some drivers of sea ice variability on longer timescales may not be well represented in these models. To this end, we introduce an unsupervised learning approach based on cluster analysis and complex networks to establish how well the latest generation of coupled climate models participating in phase 6 of the World Climate Research Programme Coupled Model Intercomparison Project (CMIP6) are able to reflect the spatio-temporal patterns of variability in Northern Hemisphere winter sea-level pressure and Arctic summer sea ice concentration over the period 1979–2020, relative to ERA5 atmospheric reanalysis and satellite-derived sea ice observations, respectively. Two specific global metrics are introduced as ways to compare patterns of variability between models and observations/reanalysis: the adjusted Rand index – a method for comparing spatial patterns of variability – and a network distance metric – a method for comparing the degree of connectivity between two geographic regions. We find that CMIP6 models generally reflect the spatial pattern of variability in the AO relatively well, although they overestimate the magnitude of sea-level pressure variability over the north-western Pacific Ocean and underestimate the variability over northern Africa and southern Europe. They also underestimate the importance of regions such as the Beaufort, East Siberian, and Laptev seas in explaining pan-Arctic summer sea ice area variability, which we hypothesise is due to regional biases in sea ice thickness. Finally, observations show that historically, winter AO events (negatively) covary strongly with summer sea ice concentration in the eastern Pacific sector of the Arctic, although now under a thinning ice regime, both the eastern and western Pacific sectors exhibit similar behaviour. CMIP6 models however do not show this transition on average, which may hinder their ability to make skilful seasonal to inter-annual predictions of summer sea ice

The influence of the Covid-19 pandemic and climate change on water use and supply: experience of Istanbul, Türkiye

The coronavirus (Covid-19) pandemic has affected not only populations around the world but also the environment and natural resources. Lockdowns and restricted lifestyles have had wide-ranging impacts on the environment (e.g., air quality in cities). Although hygiene and disinfection procedures and precautions are effective ways to protect people from Covid-19, they have significant consequences for water usage and resources especially given the increasing impacts of climate change on rainfall patterns, water use and resources. Climate change and public health issues may compound one another, and so we used a drivers, pressures, state, impact, response framework (not previously used to examine the actual and potential impacts of Covid-19 and climate change on water consumption and resources) to scope the main factors that may interact to affect water use and resources (in the form of reservoirs) using evidence from Istanbul, Türkiye, with some discussion of the comparative situation elsewhere. We modified initial views on the framework to account for the regional, city and community level experiences. We note that water consumption in Istanbul has been increasing over the last two decades (except in times of very low rainfall/drought); that there were increases in water consumption in the early stages of the Covid-19 pandemic; and, despite some increase in rainfall, water levels in reservoirs appeared to decrease during lockdowns (for a range of reasons). Through a new simple way of visualising the data, we also noted that a low resource capacity might be recurring every 6 or 7 years in Istanbul (a similar finding to Thames Reservoir in London). We made no attempt in this paper to quantify the relative contribution that climate change, population growth, etc., are making to water consumption and reservoir levels as we focused on looking at those social, environmental and economic factors that appear to play a role in potential water stress and on developing a drivers, pressures, state, impact, response framework for policy and adaptive management options for Istanbul and other large complex conurbations. If there are periodic water resource issues and temperatures rise as expected in climate projections with an accompanying increase in the duration of hot spells, the subsequent additional stress on water systems might make managing future public health emergencies, such as a pandemic, even more difficult

Digitizing Ottoman daily weather observations of Halkali Agricultural School in Istanbul, Turkiye (1896–1917)

Daily weather observations measured by students and staff at Halkali Agricultural School (a school opened in 1892 on agriculture and animal husbandry during the Ottoman period) from 1896 to 1917 in Istanbul, Turkiye have been transcribed from the original publications into digital form and translated from Ottoman Turkish (the Perso-Arabic script) to English (Latin alphabet). Over 55,000 observations of daily maximum, minimum and average temperature; rainfall, soil and under soil (0.25 m) temperature; humidity, pressure and wind speed were recovered. In addition, weather observations taken in Kandilli Observatory and Earthquake Research Institute from 1911 to 1936 and taken in Florya Meteorological Station from 1937 to 2022 could inform long-term temperature changes in Istanbul. The publication of a new historical data set that includes, for the first time, digitized and quality-controlled daily meteorological observations in Istanbul will enhance the understanding of weather changes in Turkiye back to the late 19th century. These observations will be used to fill gaps in existing temperature and pressure records and to the improvement of the accuracy of reanalysis products prior to the 1950s. It will be the first data set publication of other parameters such as soil temperature, wind speed and humidity for that period in that region. Data are available on the CEDA Archive in csv file format

Solar Geoengineering in the Polar Regions: A Review

Solar geoengineering refers to proposals, including stratospheric aerosol injection (SAI), to slow or reverse climate change by reflecting away incoming sunlight. The rapid changes ongoing in the Arctic and Antarctic, and the risk of exceeding tipping points in the cryosphere within decades, make limiting such changes a plausible objective of solar geoengineering. Here, we review the impacts of SAI on polar climate and cryosphere, including the dependence of these impacts on the latitude(s) of injection, and make recommendations for future research directions. SAI would cool the polar regions and reduce many changes in polar climate under future warming scenarios. Some under-cooling of the polar regions relative to the global mean is expected under SAI without high latitude injection, due to latitudinal variation in insolation and CO2 forcing, the forcing dependence of the polar lapse rate feedback, and altered atmospheric dynamics. There are also potential limitations in the effectiveness of SAI to arrest changes in winter-time polar climate and to prevent sea-level rise from the Antarctic ice sheet. Finally, we also review the prospects for three other solar geoengineering proposals targeting the poles: marine cloud brightening, cirrus cloud thinning, and sea-ice albedo modification. Sea-ice albedo modification appears unlikely to be viable on pan-Arctic or Antarctic scales. Whether marine cloud brightening or cirrus cloud thinning would be effective in the polar regions remains uncertain. Solar geoengineering is an increasingly prominent proposal and a robust understanding of its consequences in the polar regions is needed to inform climate policy in the coming decades

The impact of variable sea ice roughness on changes in Arctic Ocean surface stress: a model study

The Arctic sea ice cover is thinning and retreating, causing changes in surface roughness that in turn modify the momentum flux from the atmosphere through the ice into the ocean. New model simulations comprising variable sea ice drag coefficients for both the air and water interface demonstrate that the heterogeneity in sea ice surface roughness significantly impacts the spatial distribution and trends of ocean surface stress during the last decades. Simulations with constant sea ice drag coefficients as used in most climate models show an increase in annual mean ocean surface stress (0.003 N/m2 per decade, 4.6%) due to the reduction of ice thickness leading to a weakening of the ice and accelerated ice drift. In contrast, with variable drag coefficients our simulations show annual mean ocean surface stress is declining at a rate of -0.002 N/m2 per decade (3.1%) over the period 1980-2013 because of a significant reduction in surface roughness associated with an increasingly thinner and younger sea ice cover. The effectiveness of sea ice in transferring momentum does not only depend on its resistive strength against the wind forcing but is also set by its top and bottom surface roughness varying with ice types and ice conditions. This reveals the need to account for sea ice surface roughness variations in climate simulations in order to correctly represent the implications of sea ice loss under global warming

On the study of local stress rearrangements during quasistatic plastic shear of a model glass: do local stress components contain enough information?

We present a numerical study of the mechanical response of a 2D Lennard-Jones amorphous solid under steady quasistatic and athermal shear. We focus here on the evolution of local stress components. While the local stress is usually taken as an order parameter in the description of the rheological behaviour of complex fluids, and for plasticity in glasses, we show here that the knowledge of local stresses is not sufficient for a complete description of the plastic behaviour of our system. The distribution of local stresses can be approximately described as resulting from the sum of localized quadrupolar events with an exponential distribution of amplitudes. However, we show that the position of the center of the quadrupoles is not related to any special evolution of the local stress, but must be described by another variable

Local elasticity map and plasticity in a model Lennard-Jones glass

In this work we calculate the local elastic moduli in a weakly polydisperse 2DLennard-Jones glass undergoing a quasistatic shear deformation at zero temperature. The numerical method uses coarse grained microscopic expressions for the strain, displacement and stress fields. This method allows us to calculate the local elasticity tensor and to quantify the deviation from linear elasticity (local Hooke's law) at different coarse-graining scales. From the results a clear picture emerges of an amorphous material with strongly spatially heterogeneous elastic moduli that simultaneously satisfies Hooke's law at scales larger than a characteristic length scale of the order of five interatomic distances. At this scale the glass appears as a composite material composed of a rigid scaffoldingand of soft zones. Only recently calculated in non homogeneous materials, the local elastic structure plays a crucial role in the elasto-plastic response of the amorphous material. For a small macroscopic shear strain the structures associated with the non-affine displacement field appear directly related to the spatial structure of the elastic moduli. Moreover for a larger macroscopic shear strain we show that zones of low shear modulus concentrate most of the strain in form of plastic rearrangements. The spatio-temporal evolution of this local elasticity map and its connection with long term dynamical heterogeneity as well as with the plasticity in the material is quantified. The possibility to use this local parameter as a predictor of subsequent local plastic activity is also discussed.Comment: 17 pages, 18 figure

Processes controlling surface, bottom and lateral melt of Arctic sea ice in a state of the art sea ice model

We present a modelling study of processes controlling the summer melt of the Arctic sea ice cover. We perform a sensitivity study and focus our interest on the thermodynamics at the ice–atmosphere and ice–ocean interfaces. We use the Los Alamos community sea ice model CICE, and additionally implement and test three new parametrization schemes: (i) a prognostic mixed layer; (ii) a three equation boundary condition for the salt and heat flux at the ice–ocean interface; and (iii) a new lateral melt parametrization. Recent additions to the CICE model are also tested, including explicit melt ponds, a form drag parametrization and a halodynamic brine drainage scheme. The various sea ice parametrizations tested in this sensitivity study introduce a wide spread in the simulated sea ice characteristics. For each simulation, the total melt is decomposed into its surface, bottom and lateral melt components to assess the processes driving melt and how this varies regionally and temporally. Because this study quantifies the relative importance of several processes in driving the summer melt of sea ice, this work can serve as a guide for future research priorities

Mapping Arctic Sea-Ice Surface Roughness with Multi-Angle Imaging SpectroRadiometer

Sea-ice surface roughness (SIR) is a crucial parameter in climate and oceanographic studies, constraining momentum transfer between the atmosphere and ocean, providing preconditioning for summer-melt pond extent, and being related to ice age and thickness. High-resolution roughness estimates from airborne laser measurements are limited in spatial and temporal coverage while pan-Arctic satellite roughness does not extend over multi-decadal timescales. Launched on the Terra satellite in 1999, the NASA Multi-angle Imaging SpectroRadiometer (MISR) instrument acquires optical imagery from nine near-simultaneous camera view zenith angles. Extending on previous work to model surface roughness from specular anisotropy, a training dataset of cloud-free angular reflectance signatures and surface roughness, defined as the standard deviation of the within-pixel lidar elevations, from near-coincident operation IceBridge (OIB) airborne laser data is generated and is modelled using support vector regression (SVR) with a radial basis function (RBF) kernel selected. Blocked k-fold cross-validation is implemented to tune hyperparameters using grid optimisation and to assess model performance, with an R2 (coefficient of determination) of 0.43 and MAE (mean absolute error) of 0.041 m. Product performance is assessed through independent validation by comparison with unseen similarly generated surface-roughness characterisations from pre-IceBridge missions (Pearson’s r averaged over six scenes, r = 0.58, p < 0.005), and with AWI CS2-SMOS sea-ice thickness (Spearman’s rank, rs = 0.66, p < 0.001), a known roughness proxy. We present a derived sea-ice roughness product at 1.1 km resolution (2000–2020) over the seasonal period of OIB operation and a corresponding time-series analysis. Both our instantaneous swaths and pan-Arctic monthly mosaics show considerable potential in detecting surface-ice characteristics such as deformed rough ice, thin refrozen leads, and polynyas