Granular slumping in a fluid : focus on runout distances

We investigate the effect of an ambient fluid on the dynamics of collapse and spread of a granular column simulated by means of a recently developed model which takes into account both fluid forces that act on each grain and contacts between grains. The model couples the contact dynamics method for discrete element modeling of the grains and their interactions with the finite element method for the integration of Navier-Stokes equations in 2D. The coupling is based on the fictitious domain approach in which the fluid domain is extended to that of grains, and the rigid-body motion of the grains is imposed by means of distributed Lagrange multipliers. As in similar numerical and experimental works with dry grains, we focus here on the run-out distances and avalanche durations for different column aspect ratios (height vs width). We consider three options for the surrounding fluid: 1) no fluid, 2) water and 3) a viscous fluid that allows us to perform our simulations in the grain-inertial, fluid-inertial and viscous regimes, respectively. The run-out distance is found to increase as a power law with the aspect ratio of the column, and surprisingly, for a given aspect ratio and packing fraction, it may be similar in the grain-inertial regime and fluid inertial regimes but with considerably longer duration in the latter case. We show that the effect of the fluid in viscous and fluid-inertial regimes is both to reduce the kinetic energy during the collapse and enhance the flow by lubrication during the spread. Hence, the run-out distance in a fluid may be below or equal to that in the absence of fluid due to compensation between those effects

Failure in porous granular aggregates

We use a 3D Lattice Element Method, based on the discretization of the particles and binding matrix on a regular lattice, to investigate the particle-scale origins of the strength and failure of porous granular aggregates under tensile loading. Damage growth is analyzed by considering the evolution of stress probability density and the number of broken bonds in the particle phase. We show that the stress probability density functions are increasingly broader for a decreasing matrix volume fraction, the stresses being more and more concentrated in the interparticle contact zones with an exponential distribution as in cohesionless granular media [4]. We carried out a detailed parametric study in order to evaluate the combined influence of the matrix volume fraction and particlematrix adherence. Our findings are in agreement with 2D results previously reported in the literature [6]. Three regimes of crack propagation are evidenced, corresponding to no particle damage, particle abrasion and particle fragmentation, respectively. The crack morphology (tortuosity...) is another important feature that we investigate for different distributions of the particles and pores within porous granular aggregates

Model uncertainties in climate change impacts on Sahel precipitation in ensembles of CMIP5 and CMIP6 simulations

The impact of climate change on Sahel precipitation suffers from large uncertainties and is strongly model-dependent. In this study, we analyse sources of inter-model spread in Sahel precipitation change by decomposing precipitation into its dynamic and thermodynamic terms, using a large set of climate model simulations. Results highlight that model uncertainty is mostly related to the response of the atmospheric circulation to climate change (dynamic changes), while thermodynamic changes are less uncertain among climate models. Uncertainties arise mainly because the models simulate different shifts in atmospheric circulation over West Africa in a warmer climate. We linked the changes in atmospheric circulation to the changes in Sea Surface Temperature, emphasising that the Northern hemispheric temperature gradient is primary to explain uncertainties in Sahel precipitation change. Sources of Sahel precipitation uncertainties are shown to be the same in the new generation of climate models (CMIP6) as in the previous generation of models (CMIP5)

Respective impacts of Arctic sea ice decline and increasing greenhouse gases concentration on Sahel precipitation

The impact of climate change on Sahel precipitation is uncertain and has to be widely documented. Recently, it has been shown that Arctic sea ice loss leverages the global warming effects worldwide, suggesting a potential impact of Arctic sea ice decline on tropical regions. However, defining the specific roles of increasing greenhouse gases (GHG) concentration and declining Arctic sea ice extent on Sahel climate is not straightforward since the former impacts the latter. We avoid this dependency by analysing idealized experiments performed with the CNRM-CM5 coupled model. Results show that the increase in GHG concentration explains most of the Sahel precipitation change. We found that the impact due to Arctic sea ice loss depends on the level of atmospheric GHG concentration. When the GHG concentration is relatively low (values representative of 1980s), then the impact is moderate over the Sahel. However, when the concentration in GHG is levelled up, then Arctic sea ice loss leads to increased Sahel precipitation. In this particular case the ocean-land meridional gradient of temperature strengthens, allowing a more intense monsoon circulation. We linked the non-linearity of Arctic sea ice decline impact with differences in temperature and sea level pressure changes over the North Atlantic Ocean. We argue that the impact of the Arctic sea ice loss will become more relevant with time, in the context of climate change

Future evolution of the Sahel precipitation zonal contrast in CESM1

The main focus of this study is the zonal contrast of the Sahel precipitation shown in the CMIP5 climate projections: precipitation decreases over the western Sahel (i.e., Senegal and western Mali) and increases over the central Sahel (i.e., eastern Mali, Burkina Faso and Niger). This zonal contrast in future precipitation change is a robust model response to climate change but suffers from a lack of an explanation. To this aim, we study the impact of current and future climate change on Sahel precipitation by using the Large Ensemble of the Community Earth System Model version 1 (CESM1). In CESM1, global warming leads to a strengthening of the zonal contrast, as shown by the difference between the 2060–2099 period (under a high emission scenario) and the 1960–1999 period (under the historical forcing). The zonal contrast is associated with dynamic shifts in the atmospheric circulation. We show that, in absence of a forced response, that is, when only accounting for internal climate variability, the zonal contrast is associated with the Pacific and the tropical Atlantic oceans variability. However, future patterns in sea surface temperature (SST) anomalies are not necessary to explaining the projected strengthening of the zonal contrast. The mechanisms underlying the simulated changes are elucidated by analysing a set of CMIP5 idealised simulations. We show the increase in precipitation over the central Sahel to be mostly associated with the surface warming over northern Africa, which favour the displacement of the monsoon cell northwards. Over the western Sahel, the decrease in Sahel precipitation is associated with a southward shift of the monsoon circulation, and is mostly due to the warming of the SST. These two mechanisms allow explaining the zonal contrast in precipitation change

Coupled climate response to Atlantic Multidecadal Variability in a multi-model multi-resolution ensemble

North Atlantic sea surface temperatures (SSTs) underwent pronounced multidecadal variability during the twentieth and early twenty-first century. We examine the impacts of this Atlantic Multidecadal Variability (AMV), also referred to as the Atlantic Multidecadal Oscillation (AMO), on climate in an ensemble of five coupled climate models at both low and high spatial resolution. We use a SST nudging scheme specified by the Coupled Model Intercomparision Project’s Decadal Climate Prediction Project Component C (CMIP6 DCPP-C) to impose a persistent positive/negative phase of the AMV in the North Atlantic in coupled model simulations; SSTs are free to evolve outside this region. The large-scale seasonal mean response to the positive AMV involves widespread warming over Eurasia and the Americas, with a pattern of cooling over the Pacific Ocean similar to the Pacific Decadal Oscillation (PDO), together with a northward displacement of the inter-tropical convergence zone (ITCZ). The accompanying changes in global atmospheric circulation lead to widespread changes in precipitation. We use Analysis of Variance (ANOVA) to demonstrate that this large-scale climate response is accompanied by significant differences between models in how they respond to the common AMV forcing, particularly in the tropics. These differences may arise from variations in North Atlantic air-sea heat fluxes between models despite a common North Atlantic SST forcing pattern. We cannot detect a widespread effect of increased model horizontal resolution in this climate response, with the exception of the ITCZ, which shifts further northwards in the positive phase of the AMV in the higher resolution configuratio

A role of the Atlantic Ocean in predicting summer surface air temperature over North East Asia?

We assess the ability of the DePreSys3 prediction system to predict the summer (JJAS) surface-air temperature over North East Asia. DePreSys3 is based on a high resolution ocean–atmosphere coupled climate prediction system (~ 60 km in the atmosphere and ~ 25 km in the ocean), which is full-field initialized from 1960 to 2014 (26 start-dates). We find skill in predicting surface-air temperature, relative to a long-term trend, for 1 and 2–5 year leadtimes over North East Asia, the North Atlantic Ocean and Eastern Europe. DePreSys3 also reproduces the interdecadal evolution of surface-air temperature over the North Atlantic subpolar gyre and North East Asia for both lead times, along with the strong warming that occurred in the mid-1990s over both areas. Composite analysis reveals that the skill at capturing interdecadal changes in North East Asia is associated with the propagation of an atmospheric Rossby wave, which follows the subtropical jet and modulates surface-air temperature from Europe to Eastern Asia. We hypothesise that this ‘circumglobal teleconnection’ pattern is excited over the Atlantic Ocean and is related to Atlantic multi-decadal variability and the associated changes in precipitation over the Sahel and the subtropical Atlantic Ocean. This mechanism is robust for the 2–5 year lead-time. For the 1 year lead-time the Pacific Ocean also plays an important role in leading to skill in predicting SAT over Northeast Asia. Increased temperatures and precipitation over the western Pacific Ocean was found to be associated with a Pacific-Japan like-pattern, which can affect East Asia’s climate

Predicting the seasonal evolution of southern African summer precipitation in the DePreSys3 prediction system

We assess the ability of the DePreSys3 prediction system to predict austral summer precipitation (DJF) over southern Africa, defined as the African continent south of 15°S. DePresys3 is a high resolution prediction system (at a horizontal resolution of ~ 60 km in the atmosphere in mid-latitudes and of the quarter degree in the Ocean) and spans the long period 1959–2016. We find skill in predicting interannual precipitation variability, relative to a long-term trend; the anomaly correlation skill score over southern Africa is greater than 0.45 for the first summer (i.e. lead month 2–4), and 0.37 over Mozambique, Zimbabwe and Zambia for the second summer (i.e. lead month 14–16). The skill is related to the successful prediction of the El-Nino Southern Oscillation (ENSO), and the successful simulation of ENSO teleconnections to southern Africa. However, overall skill is sensitive to the inclusion of strong La-Nina events and also appears to change with forecast epoch. For example, the skill in predicting precipitation over Mozambique is significantly larger for the first summer in the 1990–2016 period, compared to the 1959–1985 period. The difference in skill in predicting interannual precipitation variability over southern Africa in different epochs is consistent with a change in the strength of the observed teleconnections of ENSO. After 1990, and consistent with the increased skill, the observed impact of ENSO appears to strengthen over west Mozambique, in association with changes in ENSO related atmospheric convergence anomalies. However, these apparent changes in teleconnections are not captured by the ensemble-mean predictions using DePreSys3. The changes in the ENSO teleconnection are consistent with a warming over the Indian Ocean and modulation of ENSO properties between the different epochs, but may also be associated with unpredictable atmospheric variability

Current and emerging developments in subseasonal to decadal prediction

Weather and climate variations of subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus remains broadly similar (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correct, calibration and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Prograame (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis