Spatial and Temporal Validation of In-Situ and Satellite Weather Data for the South West Agricultural Region of Australia

Seasonal variations in weather have significant impacts on crop yields. The accuracy of weather data is an import-ant consideration for crop yield models. This ...     

Community collaboration and climate change research in the Canadian Arctic

Research on climate change impacts, vulnerability and adaptation, particularly projects aiming to contribute to practical adaptation initiatives, requires active involvement and collaboration with community members and local, regional and national organizations that use this research for policy-making. Arctic communities are already experiencing and adapting to environmental and socio-cultural changes, and researchers have a practical and ethical responsibility to engage with communities that are the focus of the research. This paper draws on the experiences of researchers working with communities across the Canadian Arctic, together with the expertise of Inuit organizations, Northern research institutes and community partners, to outline key considerations for effectively engaging Arctic communities in collaborative research. These considerations include: initiating early and ongoing communication with communities, and regional and national contacts; involving communities in research design and development; facilitating opportunities for local employment; and disseminating research findings. Examples of each consideration are drawn from climate change research conducted with communities in the Canadian Arctic.     

Observing Convective Aggregation

Convective self-aggregation, the spontaneous organization of initially scattered convection into isolated convective clusters despite spatially homogeneous boundary conditions and forcing, was first recognized and studied in idealized numerical simulations. While there is a rich history of observational work on convective clustering and organization, there have been only a few studies that have analyzed observations to look specifically for processes related to self-aggregation in models. Here we review observational work in both of these categories and motivate the need for more of this work. We acknowledge that self-aggregation may appear to be far-removed from observed convective organization in terms of time scales, initial conditions, initiation processes, and mean state extremes, but we argue that these differences vary greatly across the diverse range of model simulations in the literature and that these comparisons are already offering important insights into real tropical phenomena. Some preliminary new findings are presented, including results showing that a self-aggregation simulation with square geometry has too broad distribution of humidity and is too dry in the driest regions when compared with radiosonde records from Nauru, while an elongated channel simulation has realistic representations of atmospheric humidity and its variability. We discuss recent work increasing our understanding of how organized convection and climate change may interact, and how model discrepancies related to this question are prompting interest in observational comparisons. We also propose possible future directions for observational work related to convective aggregation, including novel satellite approaches and a ground-based observational network.     

Quantifying uncertainty in remotely sensed land cover maps

Remotely sensed land cover maps are increasingly used as inputs into environmental simulation models whose outputs inform decisions and policy-making. Risks associated with these decisions are dependent on model output uncertainty, which is in turn affected by the uncertainty of land cover inputs. This article presents a method of quantifying the uncertainty that results from potential mis-classification in remotely sensed land cover maps. In addition to quantifying uncertainty in the classification of individual pixels in the map, we also address the important case where land cover maps have been upscaled to a coarser grid to suit the users’ needs and are reported as proportions of land cover type. The approach is Bayesian and incorporates several layers of modelling but is straightforward to implement. First, we incorporate data in the confusion matrix derived from an independent field survey, and discuss the appropriate way to model such data. Second, we account for spatial correlation in the true land cover map, using the remotely sensed map as a prior. Third, spatial correlation in the mis-classification characteristics is induced by modelling their variance. The result is that we are able to simulate posterior means and variances for individual sites and the entire map using a simple Monte Carlo algorithm. The method is applied to the Land Cover Map 2000 for the region of England and Wales, a map used as an input into a current dynamic carbon flux model.     

The Final Stage of Silicic Island Arc Magmatism in the Northern Urals

Doklady Earth Sciences - The date of cessation of calc-alkaline volcanic complex accumulation within the Devonian (Frasnian) island arc in the Northern Urals was determined for the first time. It...     

Combined hillslope diffusion and sediment transport simulation applied to landscape dynamics modelling

We present a new numerical approach for simulating geomorphic and stratigraphic processes that combines open‐channel flow with non‐uniform sediment transport law and semi‐empirical diffusive mass wasting. It is designed to facilitate modelling of surface processes across multiple space‐ and time‐scales, and under a variety of environmental and tectonic conditions. The physics of open‐channel flow is primarily based on an adapted Lagrangian formulation of shallow‐water equations. The interaction between flow and surface geology is performed by a non‐uniform total‐load sediment transport law. Additional hillslope processes are simulated using a semi‐empirical method based on a diffusion approach. In the implementation, the resolution of flow dynamics is made on a triangulated grid automatically mapped and adaptively remeshed over a regular orthogonal stratigraphic mesh. These new methods reduce computational time while preserving stability and accuracy of the physical solutions. In order to illustrate the potential of this method for landscape and sedimentary system modelling, we present a set of three generic experiments focusing on assessing the influence of contrasting erodibilities on the evolution of an active bedrock landscape. The modelled ridges morphometrics satisfy established relationships for drainage network geometry and slope distribution, and provide quantitative information on the relative impact of hillslope and channel processes, sediment discharge and alluviation. Our results suggest that contrasting erodibility can stimulate autogenic changes in erosion rate and influence the landscape morphology and preservation. This approach offers new opportunities to investigate joint landscape and sedimentary systems response to external perturbations. The possibility to define and track a large number of materials makes the implementation highly suited to model source‐to‐sink problems where material dispersion is the key question that needs to be addressed, such as natural resources exploration and basin analysis. Copyright © 2014 John Wiley & Sons, Ltd.