The ionospheric impact of the October 2003 storm event on Wide Area Augmentation System

The United States Federal Aviation Administrations (FAA) Wide-Area Augmentation System (WAAS) for civil aircraft navigation is focused primarily on the Conterminous United States (CONUS). Other Satellite-Based Augmentation Systems (SBAS) include the European Geostationary Navigation Overlay Service (EGNOS) and the Japanese Multi-transport Satellite-based Augmentation System (MSAS). Navigation using WAAS requires accurate calibration of ionospheric delays. To provide delay corrections for single frequency global positioning system (GPS) users, the wide-area differential GPS systems depend upon accurate determination of ionospheric total electron content (TEC) along radio links. Dual-frequency transmissions from GPS satellites have been used for many years to measure and map ionospheric TEC on regional and global scales. The October 2003 solar-terrestrial events are significant not only for their dramatic scale, but also for their unique phasing of solar irradiance and geomagnetic events. During 28 October, the solar X-ray and EUV irradiances were exceptionally high while the geomagnetic activity was relatively normal. Conversely, 29–31 October was geomagnetically active while solar irradiances were relatively low. These events had the most severe impact in recent history on the CONUS region and therefore had a significant effect on the WAAS performance. To help better understand the event and its impact on WAAS, we examine in detail the WAAS reference site (WRS) data consisting of triple redundant dual-frequency GPS receivers at 25 different locations within the US. To provide ground-truth, we take advantage of the three co-located GPS receivers at each WAAS reference site. To generate ground-truth and calibrate GPS receiver and transmitter inter-frequency biases, we process the GPS data using the Global Ionospheric Mapping (GIM) software developed at the Jet Propulsion Laboratory. This software allows us to compute calibrated high resolution observations of TEC. We found ionospheric range delays up to 35 m for the day-time CONUS during quiet conditions and up to 100 m during storm time conditions. For a quiet day, we obtained WAAS planar fit slant residuals less than 2 m (0.4 m root mean square (RMS)) and less than 25 m (3.4 m RMS) for the storm day. We also investigated ionospheric gradients, averaged over distances of a few hundred kilometers. The gradients were no larger than 0.5 m over 100 km for a quiet day. For the storm day, we found gradients at the 4 m level over 100 km. Similar level gradients are typically observed in the low-latitude region for quiet or storm conditions.     

Unemployment in Non-Metropolitan Australia: integrating geography,social and individual contexts

Despite a significant period of strong economic and jobs growth nationally, there is well-established evidence in Australia that the proceeds of this growth have not been shared equally, either between places or between individuals. Empirically, it is well known that particular socioeconomic groups have a higher risk of unemployment and it has become equally well established that there are particular geographic patterns of labour market disadvantage that suggest that local geographic context is also important. What is not well understood are the ways in which phenomena at the geographic level are associated with individual-level characteristics and other social contexts in ways that negatively impact on a range of social outcomes, including unemployment. The present paper specifically addresses this issue by using a multi-scalar approach and using survey data from the Housing, Income and Labour Force Dynamics Australia (HILDA) survey and aggregate level census data to model unemployment risk. The paper argues that to better understand unemployment and to add to sound policy development, approaches that incorporate a variety of contexts, including the impact of local geographies, are important.     

Goniatites

Most people are familiar with ammonites (see Fossils Explained 62, this issue), with their beautiful, logarithmically spiralled shells, but not everyone has heard of goniatites. They too were fascinating dwellers of past oceans. Goniatites are extinct cephalopods ranging from the middle of the Devonian to the end of the Permian. Although, in the strictest definition, goniatites are those ammonoids that belong to the order Goniatitida, the term goniatite is commonly used as a synonym for all Palaeozoic ammonoids. In the course of this article, the looser definition will apply.     

Current remote sensing approaches to monitoring forest degradation in support of countries measurement,reporting and verification (MRV) systems for REDD+

Forest degradation is a global phenomenon and while being an important indicator and precursor to further forest loss, carbon emissions due to degradation should also be accounted for in national reporting within the frame of UN REDD+. At regional to country scales, methods have been progressively developed to detect and map forest degradation, with these based on multi-resolution optical, synthetic aperture radar (SAR) and/or LiDAR data. However, there is no one single method that can be applied to monitor forest degradation, largely due to the specific nature of the degradation type or process and the timeframe over which it is observed. The review assesses two main approaches to monitoring forest degradation: first, where detection is indicated by a change in canopy cover or proxies, and second, the quantification of loss (or gain) in above ground biomass (AGB). The discussion only considers degradation that has a visible impact on the forest canopy and is thus detectable by remote sensing. The first approach encompasses methods that characterise the type of degradation and track disturbance, detect gaps in, and fragmentation of, the forest canopy, and proxies that provide evidence of forestry activity. Progress in these topics has seen the extension of methods to higher resolution (both spatial and temporal) data to better capture the disturbance signal, distinguish degraded and intact forest, and monitor regrowth. Improvements in the reliability of mapping methods are anticipated by SAR-optical data fusion and use of very high resolution data. The second approach exploits EO sensors with known sensitivity to forest structure and biomass and discusses monitoring efforts using repeat LiDAR and SAR data. There has been progress in the capacity to discriminate forest age and growth stage using data fusion methods and LiDAR height metrics. Interferometric SAR and LiDAR have found new application in linking forest structure change to degradation in tropical forests. Estimates of AGB change have been demonstrated at national level using SAR and LiDAR-assisted approaches. Future improvements are anticipated with the availability of next generation LiDAR sensors. Improved access to relevant satellite data and best available methods are key to operational forest degradation monitoring. Countries will need to prioritise their monitoring efforts depending on the significance of the degradation, balanced against available resources. A better understanding of the drivers and impacts of degradation will help guide monitoring and restoration efforts. Ultimately we want to restore ecosystem service and function in degraded forests before the change is irreversible.     

Numerical modeling of Maranhão Gulf tidal circulation and power density distribution

Ocean Dynamics - Marine resources are outstanding among renewable energy for their wide occurrence and diverse possibilities of exploitation. The tidal resource can be harnessed by the use of both...     

Automated GPS processing for global total electron content data

A software package known as MIT Automated Processing of GPS (MAPGPS) has been developed to automate the processing of GPS data into global total electron density (TEC) maps. The goal of the MAPGPS software is to produce reliable TEC data automatically, although not yet in real time. Observations are used from all available GPS receivers during all geomagnetic conditions where data has been successfully collected. In this paper, the architecture of the MAPGPS software is described. Particular attention is given to the algorithms used to estimate the individual receiver biases. One of the largest sources of error in estimating TEC from GPS data is the determination of these unknown receiver biases. The MAPGPS approach to solving the receiver bias problem uses three different methods: minimum scalloping, least squares, and zero-TEC. These methods are described in detail, along with their relative performance characteristics. A brief comparison of the JPL and MAPGPS receiver biases is presented, and a possible remaining error source in the receiver bias estimation is discussed. Finally, the Madrigal database, which allows Web access to the MAPGPS TEC data and maps, is described.