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.

Twin experiments with the equivalent weights particle filter and HadCM3

This paper investigates the use of a particle filter for data assimilation with a full scale coupled ocean–atmosphere general circulation model. Synthetic twin experiments are performed to assess the performance of the equivalent weights filter in such a high-dimensional system. Artificial 2-dimensional sea surface temperature fields are used as observational data every day. Results are presented for different values of the free parameters in the method. Measures of the performance of the filter are root mean square errors, trajectories of individual variables in the model and rank histograms. Filter degeneracy is not observed and the performance of the filter is shown to depend on the ability to keep maximum spread in the ensemble.

Shifting sand, shifting livelihoods? Reflections on a coastal gold rush in Ghana

Artisanal and small-scale mining (ASM) is often characterised as rush-type activity undertaken by people looking to ‘get-rich quick’. An alternative view posits ASM as poverty-driven activity which provides a valuable source of employment to a rural population where agriculture has failed to provide an adequate income. Against this dichotomy, this article critically reviews the short-lived, but high profile, gold rush which occurred on the beaches of Elmina, a fishing town in Ghana’s Central Region. At its peak, more than 1000 people, including local fishermen and career miners from the Western Region and Eastern Region of the country, were mining on the beaches. Drawing on interviews with miners and local business owners, the analysis explores the dynamics of the rush and its implications for understanding the ASM sector in Ghana. The discussion highlights the challenges associated with managing resources in dynamic and heterogeneous contexts, reconciling separate and conflicting sectoral priorities and the need to go beyond simplified and dualistic representations of the sector.

A Variance-Minimizing Filter for Large-Scale Applications

A truly variance-minimizing filter is introduced and its per for mance is demonstrated with the Korteweg– DeV ries (KdV) equation and with a multilayer quasigeostrophic model of the ocean area around South Africa. It is recalled that Kalman-like filters are not variance minimizing for nonlinear model dynamics and that four - dimensional variational data assimilation (4DV AR)-like methods relying on per fect model dynamics have dif- ficulty with providing error estimates. The new method does not have these drawbacks. In fact, it combines advantages from both methods in that it does provide error estimates while automatically having balanced states after analysis, without extra computations. It is based on ensemble or Monte Carlo integrations to simulate the probability density of the model evolution. When obser vations are available, the so-called importance resampling algorithm is applied. From Bayes’ s theorem it follows that each ensemble member receives a new weight dependent on its ‘ ‘distance’ ’ t o the obser vations. Because the weights are strongly var ying, a resampling of the ensemble is necessar y. This resampling is done such that members with high weights are duplicated according to their weights, while low-weight members are largely ignored. In passing, it is noted that data assimilation is not an inverse problem by nature, although it can be for mulated that way . Also, it is shown that the posterior variance can be larger than the prior if the usual Gaussian framework is set aside. However , i n the examples presented here, the entropy of the probability densities is decreasing. The application to the ocean area around South Africa, gover ned by strongly nonlinear dynamics, shows that the method is working satisfactorily . The strong and weak points of the method are discussed and possible improvements are proposed.

Analysis Scheme in the Ensemble Kalman Filter

This paper discusses an important issue related to the implementation and interpretation of the analysis scheme in the ensemble Kalman filter . I t i s shown that the obser vations must be treated as random variables at the analysis steps. That is, one should add random perturbations with the correct statistics to the obser vations and generate an ensemble of obser vations that then is used in updating the ensemble of model states. T raditionally , this has not been done in previous applications of the ensemble Kalman filter and, as will be shown, this has resulted in an updated ensemble with a variance that is too low . This simple modification of the analysis scheme results in a completely consistent approach if the covariance of the ensemble of model states is interpreted as the prediction error covariance, and there are no further requirements on the ensemble Kalman filter method, except for the use of an ensemble of sufficient size. Thus, there is a unique correspondence between the error statistics from the ensemble Kalman filter and the standard Kalman filter approach

Assimilation of Geosat Altimeter Data for the Agulhas Current Using the Ensemble Kalman Filter with a Quasigeostrophic Model

The ring-shedding process in the Agulhas Current is studied using the ensemble Kalman filter to assimilate geosat altimeter data into a two-layer quasigeostrophic ocean model. The properties of the ensemble Kalman filter are further explored with focus on the analysis scheme and the use of gridded data. The Geosat data consist of 10 fields of gridded sea-surface height anomalies separated 10 days apart that are added to a climatic mean field. This corresponds to a huge number of data values, and a data reduction scheme must be applied to increase the efficiency of the analysis procedure. Further, it is illustrated how one can resolve the rank problem occurring when a too large dataset or a small ensemble is used.

A prospectus for future geomorphological investigation of the Namib sand sea

The Namib Sand Sea in southern Africa offers an ideal location in which to consider general questions about the evolution of sand seas, about the fluxes of sand through contemporary dune fields and about the patterns of dune form that are created. This paper aims to provide a concise account of the approaches and techniques that are currently being used and will be used in the future to address these questions. The paper considers the techniques employed to investigate wind climate, the morphometry of the dunes, the internal structure of dune sediments, the age of the dunes and the potential to model dune development

Ecuador Paraiso Escondido virus, a new flavivirus isolated from New World sand flies in Ecuador, is the first representative of a novel clade in the genus flavivirus

A new flavivirus, Ecuador Paraiso Escondido virus (EPEV), named after the village where it was discovered, was isolated from sand flies (Psathyromyia abonnenci, formerly Lutzomyia abonnenci) that are unique to the New World. This represents the first sand fly-borne flavivirus identified in the New World. EPEV exhibited a typical flavivirus genome organization. Nevertheless, the maximum pairwise amino acid sequence identity with currently recognized flaviviruses was 52.8%. Phylogenetic analysis of the complete coding sequence showed that EPEV represents a distinct clade which diverged from a lineage that was ancestral to the nonvectored flaviviruses Entebbe bat virus, Yokose virus, and Sokoluk virus and also the Aedes-associated mosquito-borne flaviviruses, which include yellow fever virus, Sepik virus, Saboya virus, and others. EPEV replicated in C6/36 mosquito cells, yielding high infectious titers, but failed to reproduce either in vertebrate cell lines (Vero, BHK, SW13, and XTC cells) or in suckling mouse brains. This surprising result, which appears to eliminate an association with vertebrate hosts in the life cycle of EPEV, is discussed in the context of the evolutionary origins of EPEV in the New World.The flaviviruses are rarely (if ever) vectored by sand fly species, at least in the Old World. We have identified the first representative of a sand fly-associated flavivirus, Ecuador Paraiso Escondido virus (EPEV), in the New World. EPEV constitutes a novel clade according to current knowledge of the flaviviruses. Phylogenetic analysis of the virus genome showed that EPEV roots the Aedes-associated mosquito-borne flaviviruses, including yellow fever virus. In light of this new discovery, the New World origin of EPEV is discussed together with that of the other flaviviruses.

Implicit equal-weights particle filter

Filter degeneracy is the main obstacle for the implementation of particle filter in non-linear high-dimensional models. A new scheme, the implicit equal-weights particle filter (IEWPF), is introduced. In this scheme samples are drawn implicitly from proposal densities with a different covariance for each particle, such that all particle weights are equal by construction. We test and explore the properties of the new scheme using a 1,000-dimensional simple linear model, and the 1,000-dimensional non-linear Lorenz96 model, and compare the performance of the scheme to a Local Ensemble Kalman Filter. The experiments show that the new scheme can easily be implemented in high-dimensional systems and is never degenerate, with good convergence properties in both systems.

Species-specific identification of Leishmania in naturally infected sand flies captured in Mato Grosso do Sul State, Brazil

An increase in cutaneous and visceral leishmaniasis cases has been reported in recent years in the state of Mato Grosso do Sul, Brazil, and little is known to date about their etiological agents. An investigation into natural Leishmania infection of sand flies captured in this state between December 2003 and August 2004 was carried out. Mini-exon sequences were used as targets to identify Leishmania, and an RFLP technique was employed for those identified as belonging to the Viannia subgenus. Calculation of the minimal infection rate (MR) revealed that 1.6% of sand flies captured in the forest, peridomicile and intradomicile were positive. Six species were found to be infected by Leishmania (V.) braziliensis. Interestingly, two of the six species. Lutzomyia longipalpis and Nyssomyia whitmani, were captured in anthropic environments. The findings of this study constitute a useful tool for planning control measures against this disease in the State of Mato Grosso do Sul. (C) 2010 Elsevier B.V. All rights reserved.

The Diffusion Kernel Filter

A particle filter method is presented for the discrete-time filtering problem with nonlinear ItA ` stochastic ordinary differential equations (SODE) with additive noise supposed to be analytically integrable as a function of the underlying vector-Wiener process and time. The Diffusion Kernel Filter is arrived at by a parametrization of small noise-driven state fluctuations within branches of prediction and a local use of this parametrization in the Bootstrap Filter. The method applies for small noise and short prediction steps. With explicit numerical integrators, the operations count in the Diffusion Kernel Filter is shown to be smaller than in the Bootstrap Filter whenever the initial state for the prediction step has sufficiently few moments. The established parametrization is a dual-formula for the analysis of sensitivity to gaussian-initial perturbations and the analysis of sensitivity to noise-perturbations, in deterministic models, showing in particular how the stability of a deterministic dynamics is modeled by noise on short times and how the diffusion matrix of an SODE should be modeled (i.e. defined) for a gaussian-initial deterministic problem to be cast into an SODE problem. From it, a novel definition of prediction may be proposed that coincides with the deterministic path within the branch of prediction whose information entropy at the end of the prediction step is closest to the average information entropy over all branches. Tests are made with the Lorenz-63 equations, showing good results both for the filter and the definition of prediction.

A Phylogenetic Lineage of Closely Related Trypanosomes (Trypanosomatidae, Kinetoplastida) of Anurans and Sand Flies (Psychodidae, Diptera) Sharing the Same Ecotopes in Brazilian Amazonia

Analysis of the phylogenetic relationships among trypanosomes from vertebrates and invertebrates disclosed a new lineage of trypanosomes circulating among anurans and sand flies that share the same ecotopes in Brazilian Amazonia. This assemblage of closely related trypanosomes was determined by comparing whole SSU rDNA sequences of anuran trypanosomes from the Brazilian biomes of Amazonia, the Pantanal, and the Atlantic Forest and from Europe, North America, and Africa, and from trypanosomes of sand flies from Amazonia. Phylogenetic trees based on maximum likelihood and parsimony corroborated the positioning of all new anuran trypanosomes in the aquatic clade but did not support the monophyly of anuran trypanosomes. However, all analyses always supported four major clades (An01-04) of anuran trypanosomes. Clade An04 is composed of trypanosomes from exotic anurans. Isolates in clades An01 and An02 were from Brazilian frogs and toads captured in the three biomes studied, Amazonia, the Pantanal and the Atlantic Forest. Clade An01 contains mostly isolates from Hylidae whereas clade An02 comprises mostly isolates from Bufonidae; and clade An03 contains trypanosomes from sand flies and anurans of Bufonidae, Leptodactylidae, and Leiuperidae exclusively from Amazonia. To our knowledge, this is the first study describing morphological and growth features, and molecular phylogenetic affiliation of trypanosomes from anurans and phlebotomines, incriminating these flies as invertebrate hosts and probably also as important vectors of Amazonian terrestrial anuran trypanosomes.

Spatial and temporal patterns of occurrence of Lutzomyia sand fly species in an endemic area for cutaneous leishmaniasis in the Atlantic Forest region of northeast Brazil

Sand fly populations of different ecological niches in the Amaraji endemic American Cutaneous Leishmaniasis (ACL) focus of the Pernambuco Atlantic Forest region of northeastern Brazil were monitored spatiotemporally. Lutzomyia whitmani was dominant in all niches but occurred in smaller numbers in forested locations. L. whitmani was significantly less seasonal than the other species, being present throughout the year while other species were more abundant between February and April. These results suggest that L. whitmani may potentially be the principal vector of ACL in the region, even though the sand fly fauna was diverse: 88% were L.whitmani and 12% belonged to 11 other species. Two other species, L. complexa (1.3%) and L. migonei (0.8%), considered to be ACL vectors in other regions, were also present. This detailed picture of the sand fly population`s abundance and spatiotemporal distribution provides a basis for future modeling studies of forecasting sand fly activity patterns and ACL occurence.