The effect of the equivalent-weights particle filter on dynamical balance in a primitive equation model

The disadvantage of the majority of data assimilation schemes is the assumption that the conditional probability density function of the state of the system given the observations [posterior probability density function (PDF)] is distributed either locally or globally as a Gaussian. The advantage, however, is that through various different mechanisms they ensure initial conditions that are predominantly in linear balance and therefore spurious gravity wave generation is suppressed. The equivalent-weights particle filter is a data assimilation scheme that allows for a representation of a potentially multimodal posterior PDF. It does this via proposal densities that lead to extra terms being added to the model equations and means the advantage of the traditional data assimilation schemes, in generating predominantly balanced initial conditions, is no longer guaranteed. This paper looks in detail at the impact the equivalent-weights particle filter has on dynamical balance and gravity wave generation in a primitive equation model. The primary conclusions are that (i) provided the model error covariance matrix imposes geostrophic balance, then each additional term required by the equivalent-weights particle filter is also geostrophically balanced; (ii) the relaxation term required to ensure the particles are in the locality of the observations has little effect on gravity waves and actually induces a reduction in gravity wave energy if sufficiently large; and (iii) the equivalent-weights term, which leads to the particles having equivalent significance in the posterior PDF, produces a change in gravity wave energy comparable to the stochastic model error. Thus, the scheme does not produce significant spurious gravity wave energy and so has potential for application in real high-dimensional geophysical applications.

Stability of probiotic Lactobacillus plantarum in dry microcapsules under accelerated storage conditions

This study investigated the stability of freeze dried and fluid bed dried alginate microcapsules coated with chitosan containing model probiotic bacteria, Lactobacillus plantarum, during storage for up to 45 days at different water activities (0.11, 0.23, 0.40 and 0.70) and temperatures (4, 30 and 37 °C). The loss in cell viability was around 0.8 log in the case of fluid bed drying and around 1.3 in the case of freeze drying, with the former method resulting in dried capsules of smaller size (~ 1 mm vs 1.3 mm), more irregular shape, and with a rougher surface. In both cases, the water activity and water content were less than 0.25 and 10% w/w, respectively, which favours high storage stability. The storage stability studies demonstrated that as the water activity and temperature decreased the survival of the dried encapsulated cells increased. Considerably better survival was observed for fluid bed dried encapsulated cells compared to freeze dried encapsulated cells and freeze dried free cells with 10% sucrose (control), and in some cases, e.g. at 4 and 30 °C at water activities of 0.11, 0.23 and 0.40, there was more than 1 log difference after 45 days, with concentrations higher than 108 CFU/g after 45 days of storage. The results indicate that fluid bed drying is an effective and efficient manufacturing method to produce probiotic containing capsules with enhanced storage stability.

Explicit time-stepping for moving meshes

In order to move the nodes in a moving mesh method a time-stepping scheme is required which is ideally explicit and non-tangling (non-overtaking in one dimension (1-D)). Such a scheme is discussed in this paper, together with its drawbacks, and illustrated in 1-D in the context of a velocity-based Lagrangian conservation method applied to first order and second order examples which exhibit a regime change after node compression. An implementation in multidimensions is also described in some detail.

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.