Stochastic particle approximation of the Keller-Segel equation and two-dimensional generalization of Bessel processes

International audienceThe Keller-Segel partial differential equation is a two-dimensional model for chemotaxis. When the total mass of the initial density is one, it is known to exhibit blow-up in finite time as soon as the sensitivity $\chi$ of bacteria to the chemo-attractant is larger than $8\pi$. We investigate its approximation by a system of $N$ two-dimensional Brownian particles interacting through a singular attractive kernel in the drift term.In the very subcritical case $\chi0$, pairs of particles do collide with positiveprobability: the singularity of the drift is indeed visited. Nevertheless, when $\chi<2\pi N$, it is possible to control the drift and obtain existence of the particle system until the first time when at least three particles collide. We check that this time is a.s. infinite,so that global existence holds for the particle system,if and only if $\chi\leq 8\pi(N-2)/(N-1)$.Finally, we remark that in the system with $N=2$ particles, the difference between the two positions provides a natural two-dimensional generalization of Bessel processes, which we study in details

Sea ice inertial oscillations in the Arctic Basin

International audienceAn original method to quantify the amplitude of inertial motion of oceanic and ice drifters, through the introduction of a non-dimensional parameter M defined from a spectral analysis, is presented. A strong seasonal dependence of the magnitude of sea ice inertial oscillations is revealed, in agreement with the corresponding annual cycles of sea ice extent, concentration, thickness, advection velocity, and deformation rates. The spatial pattern of the magnitude of the sea ice inertial oscillations over the Arctic Basin is also in agreement with the sea ice thickness and concentration patterns. This argues for a strong interaction between the magnitude of inertial motion on one hand, the dissipation of energy through mechanical processes, and the cohesiveness of the cover on the other hand. Finally, a significant multi-annual evolution towards greater magnitudes of inertial oscillations in recent years, in both summer and winter, is reported, thus concomitant with reduced sea ice thickness, concentration and spatial extent

Parameterising ocean-induced melt of an idealised Antarctic ice shelf using deep learning

The largest uncertainty when projecting the Antarctic contribution to sea-level rise comes from the ocean-induced melt at the base of Antarctic ice shelves. Current parameterisations used to link the hydrographic properties in front of ice shelves to the melt at their base struggle to accurately simulate basal melt patterns. We suggest that deep learning can be used to tackle this issue. We train a deep feed-forward neural network to emulate basal melt rates simulated by highly-resolved ocean simulations in an idealised geometry. We explore the advantages and limitations of this new approach through sensitivity studies varying hyperparameters, input variables and training choices. We show that large neural networks perform better, that the input format of the temperature and salinity matters most, and that the neural network can be applied to conditions outside of its training range if trained appropriately. The results are promising and we make recommendations for further work with this approach

Rapid subsurface warming and circulation changes of Antarctic coastal waters by poleward shifting winds

The southern hemisphere westerly winds have been strengthening and shifting poleward since the 1950s. This wind trend is projected to persist under continued anthropogenic forcing, but the impact of the changing winds on Antarctic coastal heat distribution remains poorly understood. Here we show that a poleward wind shift at the latitudes of the Antarctic Peninsula can produce an intense warming of subsurface coastal waters that exceeds 2°C at 200-700 m depth. The model simulated warming results from a rapid advective heat flux induced by weakened near-shore Ekman pumping and is associated with weakened coastal currents. This analysis shows that anthropogenically induced wind changes can dramatically increase the temperature of ocean water at ice sheet grounding lines and at the base of floating ice shelves around Antarctica, with potentially significant ramifications for global sea level rise. Key Points Twenty-first century winds drive Antarctic coastal warming and circulation changes The winds cause coastal isotherms to shoal and weaken coastal currents Fine model grid resolution is required to represent the coastal Ekman dynamic

Numerical simulations of flow around vegetation with Telemac2D: application on laboratory experiments and on the Isère river (France)

Water Qualit

Evaluation of monsoon seasonality and the tropospheric biennial oscillation transitions in the CMIP models

Author Posting. © American Geophysical Union, 2012. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 39 (2012): L20713, doi:10.1029/2012GL053322.Characteristics of the Indian and Australian summer monsoon systems, their seasonality and interactions are examined in a variety of observational datasets and in the Coupled Model Intercomparison Project Phase 3 and 5 (CMIP3 and CMIP5) climate models. In particular, it is examined whether preferred monsoon transitions between the two regions and from one year to another, that form parts of the Tropospheric Biennial Oscillation, can lead to improved predictive skill. An overall improvement in simulation of seasonality for both monsoons is seen in CMIP5 over CMIP3, with most CMIP5 models correctly simulating very low rainfall rates outside of the monsoon season. The predictability resulting from each transition is quantified using a Monte Carlo technique. The transition from strong/weak Indian monsoon to strong/weak Australian monsoon shows ∼15% enhanced predictability in the observations, in estimating whether the following monsoon will be stronger/weaker than the climatology. Most models also successfully simulate this transition. However, enhanced predictability for other transitions is less clear.This project was supported by funding from the Australian Research Council (DP110100601) and the Centre of Excellence for Climate System Science. This work was also supported by an award under the Merit Allocation Scheme on the NCI National Facility at the ANU2013-04-2

Cold tongue and warm pool ENSO events in CMIP5 : mean state and future projections

Author Posting. © American Meteorological Society, 2014. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 27 (2014): 2861–2885, doi:10.1175/JCLI-D-13-00437.1.The representation of the El Niño–Southern Oscillation (ENSO) under historical forcing and future projections is analyzed in 34 models from the Coupled Model Intercomparison Project phase 5 (CMIP5). Most models realistically simulate the observed intensity and location of maximum sea surface temperature (SST) anomalies during ENSO events. However, there exist systematic biases in the westward extent of ENSO-related SST anomalies, driven by unrealistic westward displacement and enhancement of the equatorial wind stress in the western Pacific. Almost all CMIP5 models capture the observed asymmetry in magnitude between the warm and cold events (i.e., El Niños are stronger than La Niñas) and between the two types of El Niños: that is, cold tongue (CT) El Niños are stronger than warm pool (WP) El Niños. However, most models fail to reproduce the asymmetry between the two types of La Niñas, with CT stronger than WP events, which is opposite to observations. Most models capture the observed peak in ENSO amplitude around December; however, the seasonal evolution of ENSO has a large range of behavior across the models. The CMIP5 models generally reproduce the duration of CT El Niños but have biases in the evolution of the other types of events. The evolution of WP El Niños suggests that the decay of this event occurs through heat content discharge in the models rather than the advection of SST via anomalous zonal currents, as seems to occur in observations. No consistent changes are seen across the models in the location and magnitude of maximum SST anomalies, frequency, or temporal evolution of these events in a warmer world.2014-10-1

Extreme rainfall variability in Australia: Patterns, drivers and predictability

Leading patterns of observed monthly extreme rainfall variability in Australia are examined using an Empirical Orthogonal Teleconnection (EOT) method. Extreme rainfall variability is more closely related to mean rainfall variability during austral summer than in winter. The leading EOT patterns of extreme rainfall explain less variance in Australia-wide extreme rainfall than is the case for mean rainfall EOTs. We illustrate that, as with mean rainfall, the El Niño-Southern Oscillation (ENSO) has the strongest association with warm-season extreme rainfall variability, while in the cool-season the primary drivers are atmospheric blocking and the subtropical ridge. The Indian Ocean Dipole and Southern Annular Mode also have significant relationships with patterns of variability during austral winter and spring. Leading patterns of summer extreme rainfall variability have predictability several months ahead from Pacific sea surface temperatures (SSTs) and as much as a year in advance from Indian Ocean SSTs. Predictability from the Pacific is greater for wetter than average summer months than for months that are drier than average, whereas for the Indian Ocean the relationship has greater linearity. Several cool-season EOTs are associated with mid-latitude synoptic-scale patterns along the south and east coasts. These patterns have common atmospheric signatures denoting moist onshore flow and strong cyclonic anomalies often to the north of a blocking anti-cyclone. Tropical cyclone activity is observed to have significant relationships with some warm season EOTs. This analysis shows that extreme rainfall variability in Australia can be related to remote drivers and local synoptic-scale patterns throughout the year