The Effect of Data Inaccuracy on Tests of Space‐Time Interaction

Space‐time event data are often subject to deficiencies in: (1) locational accuracy; (2), temporal accuracy; and (3) completeness. This work explores how these failings in the quality of input data may affect the results of global space‐time interaction tests. While previous work has partially investigated the impact of locational inaccuracy on the results of these tests, more work remains. The impacts of temporal inaccuracy and incomplete data reporting on the results of these tests remain completely unexplored. This study examines the influence of these problems individually and collectively, using a series of simulations. Findings demonstrate that even in cases of slight inaccuracy or underreporting, the consequences on results are potentially severe. Although the study is couched in terms of data inaccuracy, its relevance to situations where inaccuracy is replaced with uncertainty is self‐evident.     

Interferometric visibility and closure phase of microlensing events with finite source size

Interferometers from the ground and space will be able to resolve the two images in a microlensing event. This will at least partially lift the inherent degeneracy between physical parameters in microlensing events. To increase the signal-to-noise ratio, intrinsically bright events with large magnifications will be preferentially selected as targets. These events may be influenced by finite source size effects both photometrically and astrometrically. Using observed finite source size events as examples, we show that the fringe visibility can be affected by ∼5–10 per cent, and the closure phase by a few degrees – readily detectable by ground and space interferometers. Such detections will offer unique information about the lens–source trajectory relative to the baseline of the interferometers. Combined with photometric finite source size effects, interferometry offers a way to measure the angular sizes of the source and the Einstein radius accurately. Limb-darkening changes the visibility by a small amount compared with a source with uniform surface brightness, marginally detectable with ground-based instruments. We discuss the implications of our results for the plans to make interferometric observations of future microlensing events.     

Numerical simulation of overbank processes in topographically complex floodplain environments

This article presents results from an investigation of the hydraulic characteristics of overbank flows on topographically‐complex natural river floodplains. A two‐dimensional hydraulic model that solves the depth‐averaged shallow water form of the Navier–Stokes equations is used to simulate an overbank flow event within a multiple channel reach of the River Culm, Devon, UK. Parameterization of channel and floodplain roughness by the model is evaluated using monitored records of main channel water level and point measurements of floodplain flow depth and unit discharge. Modelled inundation extents and sequences are assessed using maps of actual inundation patterns obtained using a Global Positioning System, observational evidence and ground photographs. Simulation results suggest a two‐phase model of flooding at the site, which seems likely to be representative of natural floodplains in general. Comparison of these results with previous research demonstrates the complexity of overbank flows on natural river floodplains and highlights the limitations of laboratory flumes as an analogue for these environments. Despite this complexity, frequency distributions of simulated depth, velocity and unit discharge data closely follow a simple gamma distribution model, and are described by a shape parameter (α) that exhibits clear systematic trends with changing discharge and floodplain roughness. Such statistical approaches have the potential to provide the basis for computationally efficient flood routing and overbank sedimentation models. Copyright © 2002 John Wiley & Sons, Ltd.     

Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring

Free and open access to the Landsat archive has enabled the implementation of national and global terrestrial monitoring projects. Herein, we summarize a project characterizing the change history of Canada’s forested ecosystems with a time series of data representing 1984–2012. Using the Composite2Change approach, we applied spectral trend analysis to annual best-available-pixel (BAP) surface reflectance image composites produced from Landsat TM and ETM+ imagery. A total of 73,544 images were used to produce 29 annual image composites, generating ～400 TB of interim data products and resulting in ～25 TB of annual gap-free reflectance composites and change products. On average, 10% of pixels in the annual BAP composites were missing data, with 86% of pixels having data gaps in two consecutive years or fewer. Change detection overall accuracy was 89%. Change attribution overall accuracy was 92%, with higher accuracy for stand-replacing wildfire and harvest. Changes were assigned to the correct year with an accuracy of 89%. Outcomes of this project provide baseline information and nationally consistent data source to quantify and characterize changes in forested ecosystems. The methods applied and lessons learned build confidence in the products generated and empower others to develop or refine similar satellite-based monitoring projects.     

Application of Aqua MODIS sensor data for estimating chlorophyll a in the turbid Case 2 waters of Lake Erie using bio-optical models

There is considerable interest in accurately estimating water quality parameters in turbid (Case 2) and eutrophic waters such as the Western Basin of Lake Erie (WBLE). Lake Erie is a large, open freshwater body that supports diverse ecosystem, and over 12 million people in the mid-western part of the United States depend on it for drinking water, fisheries, navigational, and recreational purposes. The increasing utilization of the freshwater has deteriorated the water severely and currently the lake is experiencing recurring harmful algal blooms (HABs). Improving the water quality of Lake Erie requires the use of robust monitoring tools that help water quality managers understand sources and pathways of influxes that trigger HABs. Satellite-based remote sensing sensor such as the moderate resolution imaging spectroradiometer (MODIS) may provide frequent and synoptic view of the water quality indices. In this study, data set from field measurements was used to evaluate the performance of 14 existing ocean color algorithms. Results indicated that MODIS data consistently underestimated the chlorophyll a concentrations in the WBLE, with the largest source of errors from dissolved organic matter and xanthophyll accessory pigments in this data set. Most of the global algorithms, including OC4v4 and the Baltic model, generated near-identical statistical parameters with an average R² of ~0.57 and RMSE ~2.9 μg/l. MODIS performed poorly (R² ~0.18) when its NIR/red bands were used. A slightly improved model was developed using similar band ratio approach generating R² of ~0.62 and RMSE ~1.8 μg/l.     

Dissolution rates of talc as a function of solution composition, pH and temperature

Steady-state talc dissolution rates, at far-from-equilibrium conditions, were measured as a function of aqueous silica and magnesium activity, pH from 1 to 10.6, and temperature from 25 to 150 °C. All rates were measured in mixed flow reactors and exhibited stoichiometric or close to stoichiometric dissolution. All measured rates at pH > 2 obtained at a fixed ionic strength of 0.02 M can be described to within experimental uncertainty using