Evaluation of simulated sea-ice concentrations from sea-ice/ocean models using satellite data and polynya classification methods

Sea-ice concentrations in the Laptev Sea simulated by the coupled North Atlantic-Arctic Ocean-Sea-Ice Model and Finite Element Sea-Ice Ocean Model are evaluated using sea-ice concentrations from Advanced Microwave Scanning Radiometer-Earth Observing System satellite data and a polynya classification method for winter 2007/08. While developed to simulate largescale sea-ice conditions, both models are analysed here in terms of polynya simulation. The main modification of both models in this study is the implementation of a landfast-ice mask. Simulated sea-ice fields from different model runs are compared with emphasis placed on the impact of this prescribed landfast-ice mask. We demonstrate that sea-ice models are not able to simulate flaw polynyas realistically when used without fast-ice description. Our investigations indicate that without landfast ice and with coarse horizontal resolution the models overestimate the fraction of open water in the polynya. This is not because a realistic polynya appears but due to a larger-scale reduction of ice concentrations and smoothed ice-concentration fields. After implementation of a landfast-ice mask, the polynya location is realistically simulated but the total open-water area is still overestimated in most cases. The study shows that the fast-ice parameterization is essential for model improvements. However, further improvements are necessary in order to progress from the simulation of large-scale features in the Arctic towards a more detailed simulation of smaller-scaled features (here polynyas) in an Arctic shelf sea.

A systematic method of parameterisation estimation using data assimilation

In numerical weather prediction, parameterisations are used to simulate missing physics in the model. These can be due to a lack of scientific understanding or a lack of computing power available to address all the known physical processes. Parameterisations are sources of large uncertainty in a model as parameter values used in these parameterisations cannot be measured directly and hence are often not well known; and the parameterisations themselves are also approximations of the processes present in the true atmosphere. Whilst there are many efficient and effective methods for combined state/parameter estimation in data assimilation (DA), such as state augmentation, these are not effective at estimating the structure of parameterisations. A new method of parameterisation estimation is proposed that uses sequential DA methods to estimate errors in the numerical models at each space-time point for each model equation. These errors are then fitted to pre-determined functional forms of missing physics or parameterisations that are based upon prior information. We applied the method to a one-dimensional advection model with additive model error, and it is shown that the method can accurately estimate parameterisations, with consistent error estimates. Furthermore, it is shown how the method depends on the quality of the DA results. The results indicate that this new method is a powerful tool in systematic model improvement.

Sampling uncertainty in gridded sea surface temperature products and Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) data

Sea surface temperature (SST) data are often provided as gridded products, typically at resolutions of order 0.05 degrees from satellite observations to reduce data volume at the request of data users and facilitate comparison against other products or models. Sampling uncertainty is introduced in gridded products where the full surface area of the ocean within a grid cell cannot be fully observed because of cloud cover. In this paper we parameterise uncertainties in SST as a function of the percentage of clear-sky pixels available and the SST variability in that subsample. This parameterisation is developed from Advanced Along Track Scanning Radiometer (AATSR) data, but is applicable to all gridded L3U SST products at resolutions of 0.05-0.1 degrees, irrespective of instrument and retrieval algorithm, provided that instrument noise propagated into the SST is accounted for. We also calculate the sampling uncertainty of ~0.04 K in Global Area Coverage (GAC) Advanced Very High Resolution Radiometer (AVHRR) products, using related methods.

Still searching for graves: an analytical strategy for interpreting geophysical data used in the search for “unmarked” graves

Searching for and mapping the physical extent of unmarked graves using geophysical techniques has proven difficult in many cases. The success of individual geophysical techniques for detecting graves depends on a site-by-site basis. Significantly, detection of graves often results from measured contrasts that are linked to the background soils rather than the type of archaeological feature associated with the grave. It is evident that investigation of buried remains should be considered within a 3D space as the variation in burial environment can be extremely varied through the grave. Within this paper, we demonstrate the need for a multi-method survey strategy to investigate unmarked graves, as applied at a “planned” but unmarked pauper’s cemetery. The outcome from this case study provides new insights into the strategy that is required at such sites. Perhaps the most significant conclusion is that unmarked graves are best understood in terms of characterization rather than identification. In this paper, we argue for a methodological approach that, while following the current trends to use multiple techniques, is fundamentally dependent on a structured approach to the analysis of the data. The ramifications of this case study illustrate the necessity of an integrated strategy to provide a more holistic understanding of unmarked graves that may help aid in management of these unseen but important aspects of our heritage. It is concluded that the search for graves is still a current debate and one that will be solved by methodological rather than technique-based arguments.

Are Reanalysis Data Useful for Calculating Climate Indices over South America?

Precipitation and temperature climate indices are calculated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and validated against observational data from some stations over Brazil and other data sources. The spatial patterns of the climate indices trends are analyzed for the period 1961-1990 over South America. In addition, the correlation and linear regression coefficients for some specific stations were also obtained in order to compare with the reanalysis data. In general, the results suggest that NCEP/NCAR reanalysis can provide useful information about minimum temperature and consecutive dry days indices at individual grid cells in Brazil. However, some regional differences in the climate indices trends are observed when different data sets are compared. For instance, the NCEP/NCAR reanalysis shows a reversal signal for all rainfall annual indices and the cold night index over Argentina. Despite these differences, maps of the trends for most of the annual climate indices obtained from the NCEP/NCAR reanalysis and BRANT analysis are generally in good agreement with other available data sources and previous findings in the literature for large areas of southern South America. The pattern of trends for the precipitation annual indices over the 30 years analyzed indicates a change to wetter conditions over southern and southeastern parts of Brazil, Paraguay, Uruguay, central and northern Argentina, and parts of Chile and a decrease over southwestern South America. All over South America, the climate indices related to the minimum temperature (warm or cold nights) have clearly shown a warming tendency; however, no consistent changes in maximum temperature extremes (warm and cold days) have been observed. Therefore, one must be careful before suggesting an), trends for warm or cold days.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

The Schenberg data acquisition and analysis: results from its first commissioning run

The Mario Schenberg gravitational wave detector has started its commissioning phase at the Physics Institute of the University of Sao Paulo. We have collected almost 200 h of data from the instrument in order to check out its behavior and performance. We have also been developing a data acquisition system for it under a VXI System. Such a system is composed of an analog-to-digital converter and a GPS receiver for time synchronization. We have been building the software that controls and sets up the data acquisition. Here we present an overview of the Mario Schenberg detector and its data acquisition system, some results from the first commissioning run and solutions for some problems we have identified.

Harmonization Of Vocabularies For Water Data

Observational data encodes values of properties associated with a feature of interest, estimated by a specified procedure. For water the properties are physical parameters like level, volume, flow and pressure, and concentrations and counts of chemicals, substances and organisms. Water property vocabularies have been assembled at project, agency and jurisdictional level. Organizations such as EPA, USGS, CEH, GA and BoM maintain vocabularies for internal use, and may make them available externally as text files. BODC and MMI have harvested many water vocabularies alongside others of interest in their domain, formalized the content using SKOS, and published them through web interfaces. Scope is highly variable both within and between vocabularies. Individual items may conflate multiple concerns (e.g. property, instrument, statistical procedure, units). There is significant duplication between vocabularies. Semantic web technologies provide the opportunity both to publish vocabularies more effectively, and achieve harmonization to support greater interoperability between datasets. - Models for vocabulary items (property, substance/taxon, process, unit-of-measure, etc) may be formalized OWL ontologies, supporting semantic relations between items in related vocabularies; - By specializing the ontology elements from SKOS concepts and properties, diverse vocabularies may be published through a common interface; - Properties from standard vocabularies (e.g. OWL, SKOS, PROV-O and VAEM) support mappings between vocabularies having a similar scope - Existing items from various sources may be assembled into new virtual vocabularies However, there are a number of challenges: - use of standard properties such as sameAs/exactMatch/equivalentClass require reasoning support; - items have been conceptualised as both classes and individuals, complicating the mapping mechanics; - re-use of items across vocabularies may conflict with expectations concerning URI patterns; - versioning complicates cross-references and re-use. This presentation will discuss ways to harness semantic web technologies to publish harmonized vocabularies, and will summarise how many of the challenges may be addressed.

Quality of TEC Estimated with Mod Ion Using GPS and GLONASS Data

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Simulations under Ideal and Nonideal Conditions for Characterization of a Passive Doppler Geographical Location System Using Extension of Data Reception Network

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Choosing between Cox proportional hazards and logistic models for interval-censored data via bootstrap

This work develops a new methodology in order to discriminate models for interval-censored data based on bootstrap residual simulation by observing the deviance difference from one model in relation to another, according to Hinde (1992). Generally, this sort of data can generate a large number of tied observations and, in this case, survival time can be regarded as discrete. Therefore, the Cox proportional hazards model for grouped data (Prentice & Gloeckler, 1978) and the logistic model (Lawless, 1982) can befitted by means of generalized linear models. Whitehead (1989) considered censoring to be an indicative variable with a binomial distribution and fitted the Cox proportional hazards model using complementary log-log as a link function. In addition, a logistic model can be fitted using logit as a link function. The proposed methodology arises as an alternative to the score tests developed by Colosimo et al. (2000), where such models can be obtained for discrete binary data as particular cases from the Aranda-Ordaz distribution asymmetric family. These tests are thus developed with a basis on link functions to generate such a fit. The example that motivates this study was the dataset from an experiment carried out on a flax cultivar planted on four substrata susceptible to the pathogen Fusarium oxysoprum. The response variable, which is the time until blighting, was observed in intervals during 52 days. The results were compared with the model fit and the AIC values.

Existence and asymptotic behaviour for the parabolic-parabolic Keller-Segel system with singular data

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Strangeness data with light projectiles from a hydrodynamical point of view

The usual particle emission scenario used in hydrodynamics presupposes that particles instantaneously stop interacting (freeze-out) once they reach some three-dimensional surface. Another formalism has recently been developed where particle emission occurs continuously during the whole expansion of thermalized matter. Here we compare both mechanisms in a simplified hydrodynamical framework and show that they lead to a drastically different interpretation of data.

Strangeness data with heavy projectiles from a hydrodynamical point of view

We compare the results obtained by using the continuous emission model with data from Ph-Ph collisions. We determine the initial conditions necessary to reproduce the strange particle ratios (experiment WA97) and with the obtained results, we study the dependence on particle mass of the inverse slope parameter T. Some particle spectra are also shown.