Interdisciplinary climate: The case of the first 50 years of British observations in Australia

This paper presents the case for improved interdisciplinarity in climate research in the context of assessing and discussing the caution required when utilizing some types of historical climate data. This is done by a case study examining the reliability of the instruments used for collecting weather data in Australia between 1788 and 1840, as well as the observers themselves, during the British settlement of New South Wales. This period is challenging because the instruments were not uniformly calibrated and were created, repaired, and used by a wide variety of people with skills that frequently remain undocumented. Continuing significant efforts to rescue such early instrumental records of climate are likely to be enhanced by more open, interdisciplinary research that encourages discussion of an apparent dichotomy of view about the quantitative value of early single-instrument data between historians of physics (including museum curators) and climate researchers. © 2012 American Meteorological Society

Crystallization of agility: Back to basics

There are a number of agile and traditional methodologies for software development. Agilists provide agile principles and agile values to characterize the agile methods but there is no clear and inclusive definition of agile methods; subsequently it is not feasible to draw a clear distinction between traditional and agile software development methods in practice. The purpose of this paper is to explain the concept of agility in detail; and then to suggest a definition of agile methods that would help in the ranking or differentiation of agile methods from other available methods

Improving agile software development by the application of method engineering practices

Despite the vast attention and wide acceptance of the newly engineered agile methods for software development, those methods are seldom linked to the goals of software process improvement (SPI), an approach that aims to provide support for significant improvement of both the quality of those methods as well as the resultant software products. In this paper, we propose an extension to agile methods by adding extra characteristics in order for agile methods to better support SPI. We explain how agile methods can gain those extra attributes through the application of a method engineering approach along with our new tool (4-DAT) that assists method engineers and managers in selecting the most appropriate method fragments for their needed agile methods. Finally, we summarize a number of industrial case studies carried out over several years in order to test and improve the efficiency of our theory of adding SPI to an agile methodological approach

Assessing simulations of daily temperature and precipitation variability with global climate models for present and enhanced greenhouse climates

The enhanced greenhouse climates of five different global climate models are examined with reference to the ability of the models to characterize the frequency of extreme events on both a regional and global scale. Ten years of model output for both control and enhanced greenhouse conditions are utilized to derive return periods for extreme temperature and precipitation events and to characterize the variability of the model climate at both regional and global scales. Under enhanced greenhouse conditions, return periods for extreme precipitation events are shorter and there is a general increase in the intensity of precipitation and number of wet spells in most areas. There is a decrease in frequency of cold temperature extremes and an increase in hot extremes in many areas. The results show a reasonable level of agreement between the models in terms of global scale variability, but the difference between model simulations of precipitation on a regional scale suggests that model derived estimates of variability changes must be carefully justified

Abstracting modelling languages: A reutilization approach

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-31095-9_9Proceedings of 24th International Conference, CAiSE 2012, Gdansk, Poland, June 25-29, 2012Model-Driven Engineering automates the development of information systems. This approach is based on the use of Domain-Specific Modelling Languages (DSMLs) for the description of the relevant aspects of the systems to be built. The increasing complexity of the target systems has raised the need for abstraction techniques able to produce simpler versions of the models, but retaining certain properties of interest. However, developing such abstractions for each DSML from scratch is a time and resource consuming activity. Our solution to this situation is a number of techniques to build reusable abstractions that are defined once and can be reused over families of modelling languages sharing certain requirements. As a proof of concept, we present a catalogue of reusable abstractions, together with an implementation in the MetaDepth multi-level meta-modelling tool.Work funded by the Spanish Ministry of Economy and Competitivity (TIN2011-24139), and the R&D programme of Madrid Region (S2009/TIC-1650)

Empirically Driven Use Case Metamodel Evolution

Metamodel evolution is rarely driven by empirical evidences of metamodel drawbacks. In this paper, the evolution of the use case metamodel used by the publicly available requirements management tool REM is presented. This evolution has been driven by the analysis of empirical data obtained during the assessment of several metrics–based verification heuristics for use cases developed by some of the authors and previously presented in other international fora. The empirical analysis has made evident that some common defects found in use cases developed by software engineering students were caused not only by their lack of experience but also by the expressive limitations imposed by the underlying use case metamodel used in REM. Once these limitations were clearly identified, a number of evolutionary changes were proposed to the REM use case metamodel in order to increase use case quality, i.e. to avoid those situations in which the metamodel were the cause of defects in use case specifications.Ministerio de Ciencia y Tecnología TIC 2003-02737-C02-0

Large-scale Validation of AMIP II Land-surface Simulations: Preliminary Results for Ten Models

This report summarizes initial findings of a large-scale validation of the land-surface simulations of ten atmospheric general circulation models that are entries in phase II of the Atmospheric Model Intercomparison Project (AMIP II). This validation is conducted by AMIP Diagnostic Subproject 12 on Land-surface Processes and Parameterizations, which is focusing on putative relationships between the continental climate simulations and the associated models' land-surface schemes. The selected models typify the diversity of representations of land-surface climate that are currently implemented by the global modeling community. The current dearth of global-scale terrestrial observations makes exacting validation of AMIP II continental simulations impractical. Thus, selected land-surface processes of the models are compared with several alternative validation data sets, which include merged in-situ/satellite products, climate reanalyses, and off-line simulations of land-surface schemes that are driven by observed forcings. The aggregated spatio-temporal differences between each simulated process and a chosen reference data set then are quantified by means of root-mean-square error statistics; the differences among alternative validation data sets are similarly quantified as an estimate of the current observational uncertainty in the selected land-surface process. Examples of these metrics are displayed for land-surface air temperature, precipitation, and the latent and sensible heat fluxes. It is found that the simulations of surface air temperature, when aggregated over all land and seasons, agree most closely with the chosen reference data, while the simulations of precipitation agree least. In the latter case, there also is considerable inter-model scatter in the error statistics, with the reanalyses estimates of precipitation resembling the AMIP II simulations more than to the chosen reference data. In aggregate, the simulations of land-surface latent and sensible heat fluxes appear to occupy intermediate positions between these extremes, but the existing large observational uncertainties in these processes make this a provisional assessment. In all selected processes as well, the error statistics are found to be sensitive to season and latitude sector, confirming the need for finer-scale analyses which also are in progress