Climate Change Impacts for the Conterminous USA: An Integrated Assessment

Here we simulate dryland agriculture in the United States in order to assess potential future agricultural production under a set of general circulation model (GCM)-based climate change scenarios. The total national production of three major grain crops—corn, soybeans, and winter wheat—and two forage crops—alfalfa and clover hay—is calculated for the actual present day core production area (CPA) of each of these crops. In general, higher global mean temperature (GMT) reduces production and higher atmospheric carbon dioxide concentration ([CO₂]) increases production. Depending on the climatic change scenarios employed overall national production of the crops studied changes by up to plus or minus 25% from present-day levels. Impacts are more significant regionally, with crop production varying by greater than ±50% from baseline levels. Analysis of currently possible production areas (CPPAs) for each crop indicates that the regions most likely to be affected by climate change are those on the margins of the areas in which they are currently grown. Crop yield variability was found to be primarily influenced by local weather and geographic features rather than by large-scale changes in climate patterns and atmospheric composition. Future US agronomic potential will be significantly affected by the changes in climate projected here. The nature of the crop response will depend primarily on to what extent precipitation patterns change and also on the degree of warming experienced.     

The role of surface heterogeneity in modelling the stable boundary layer

High-resolution numerical simulations are performed for three nights for each of two areas of the United Kingdom. Area-averaging techniques are then used to calculate effective stability functions for turbulence parametrizations in models using typical mesoscale and global spatial resolutions. Comparisons are made with parametrizations commonly used in numerical weather prediction models. The present results do not suggest that significant enhancement of the stability functions above 50 m is justified. Closer to the surface, more significant enhancement is observed in some regions. It is shown that the amount of enhancement is related to the variability of the orography.     

Regionalisation of population growth projections in coastal exposure analysis

Large-area coastal exposure and impact analysis has focussed on using sea-level rise (SLR) scenarios and has placed little emphasis on socioeconomic scenarios, while neglecting spatial variations of population dynamics. We use the Dynamic Interactive Vulnerability Assessment (DIVA) Framework to assess the population exposed to 1 in 100-year coastal flood events under different population scenarios, that are consistent with the shared socioeconomic pathways (SSPs); and different SLR scenarios, derived from the representative concentration pathways (RCPs); and analyse the effect of accounting for regionalised population dynamics on population exposure until 2100. In a reference approach, we use homogeneous population growth on national level. In the regionalisation approaches, we test existing spatially explicit projections that also account for urbanisation, coastal migration and urban sprawl. Our results show that projected global exposure in 2100 ranges from 100 million to 260 million, depending on the combination of SLR and population scenarios and method used for regionalising the population projections. The assessed exposure based on the regionalised approaches is higher than that derived from the reference approach by up to 60 million people (39%). Accounting for urbanisation and coastal migration leads to an increase in exposure, whereas considering urban sprawl leads to lower exposure. Differences between the reference and the regionalised approaches increase with higher SLR. The regionalised approaches show highest exposure under SSP5 over most of the twenty-first century, although total population in SSP5 is the second lowest overall. All methods project the largest absolute growth in exposure for Asia and relative growth for Africa.     

Governing resilience building in Thailand's tourism-dependent coastal communities: Conceptualising stakeholder agency in social-ecological systems

In current scientific efforts to harness complementarity between resilience and vulnerability theory, one response is an ‘epistemological shift’ towards an evolutionary, learning based conception of the ‘systems-actor’ relation in social-ecological systems. In this paper, we contribute to this movement regarding the conception of stakeholder agency within social-ecological systems. We examine primary evidence from the governance of post-disaster recovery and disaster risk reduction efforts in Thailand's coastal tourism-dependent communities following the 2004 Indian Ocean Tsunami. Through an emerging storyline from stakeholders, we construct a new framework for conceptualising stakeholder agency in social-ecological systems, which positions the notion of resilience within a conception of governance as a negotiated normative process. We conclude that if resilience theory is proposed as the preferred approach by which disaster risk reduction is framed and implemented, it needs to acknowledge much more explicitly the role of stakeholder agency and the processes through which legitimate visions of resilience are generated.     

Assessing spatial associations between perceptions of landscape value and climate change risk for use in climate change planning

This study examines spatially referenced perceived landscape values and climate change risks collected through public participation geographic information systems for potential use in climate change planning. Using survey data from the Southern Fleurieu Peninsula, South Australia, we present a method for identifying perceived landscape values and climate change risks to describe and quantify their spatial associations. Two spatial data models??vector and raster??and two analytical methods??Jaccard coefficients and spatial cross-correlations were used to describe the spatial associations. Results indicate that perceptions of climate change risk are driven, in part, by the values people assign or hold for places on the landscape. Biodiversity and intrinsic landscape values have strong spatial association with biodiversity loss risk while recreation values have strong spatial association with riparian flooding, sea-level rise and wave action risks. Other landscape values show weak to no spatial association with perceived climate change risks. The methodology described in this research provides a mechanism for government agencies to develop place-based adaptation strategies based on these associations.     

Spatial correlation of marine wind‐speed observations

Abstract

The spatial characteristics of the wind speeds from ships, drilling platforms, and satellites (SASS and SMMR) were investigated through autocorrelation analysis. Values of the spatial correlation coefficient in minimum separation classes revealed that SASS winds contained the least noise, followed by drilling‐platform and SMMR winds, measured ship winds and estimated ship winds. The variances explained by wind‐speed observations within a 100‐km radius of each other were found to be 86, 72, 62, 48 and 41%, respectively. Ship wind‐speed estimates made during hours of darkness showed significantly higher noise than daytime reports.     

Bottom-up climate risk assessment of infrastructure investment in the Niger River Basin

The Niger River is the third largest river in the African continent. Nine riparian countries share its basin, which rank all among the world’s thirty poorest. Existing challenges in West Africa, including endemic poverty, inadequate infrastructure and weak adaptive capacity to climate variability, make the region vulnerable to climate change. In this study, a risk-based methodology is introduced and demonstrated for the analysis of climate change impacts on planned infrastructure investments in water resources systems in the Upper and Middle Niger River Basin. The methodology focuses on identifying the vulnerability of the Basin’s socio-economic system to climate change, and subsequently assessing the likelihood of climate risks by using climate information from a multi-run, multi-GCM ensemble of climate projections. System vulnerabilities are analyzed in terms of performance metrics of hydroelectricity production, navigation, dry and rainy season irrigated agriculture, flooding in the Inner Delta of the Niger and the sustenance of environmental flows. The study reveals low to moderate risks in terms of stakeholder-defined threshold levels for most metrics in the 21st Century. The highest risk levels were observed for environmental flow targets. The findings indicate that the range of projected changes in an ensemble of CMIP3 GCM projections imply only relatively low risks of unacceptable climate change impacts on the present large-scale infrastructure investment plan for the Basin.     

Updating the Phase 1 habitat map of Wales, UK, using satellite sensor data

The Phase 1 Survey is the most comprehensive and widely used national level map of semi-natural habitats in Wales. However, the survey was based largely on field survey and was conducted over several decades, before being completed in 1997. Given that resources for a repeat survey were limited, this study has used an object-orientated rule-based classification implemented within eCognition of multi-temporal satellite sensor data acquired between 2003 and 2006 to map semi-natural habitats and agricultural land across Wales, thereby allowing a progressive update of the Phase 1 Survey. The classification of objects to Phase 1 habitat classes was undertaken in two steps; firstly the landscape of Wales was divided into objects using orthorectified SPOT-5 High Resolution Geometric (HRG) reflectance data (10 m spatial resolution) and Land Parcel Information System (LPIS) boundaries. A rule-base was then developed to progressively discriminate and map the distribution of 105 sub-habitats across Wales based on time-series of SPOT HRG, Terra-1 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Indian Remote Sensing Satellite (IRS) LISS-3 data, derived datasets (e.g., vegetation indices, fractional images) and ancillary information (e.g., topography). The rules coupled knowledge of ecology and the information content of these remote sensing data using a combination of thresholds, Boolean operations and fuzzy membership functions. A second rule-base was then developed to translate the more detailed sub-habitat classification to Phase 1 habitat classes. Indicative accuracies of the revised Phase 1 mapping, based on comparisons with the later Phase 2 survey (for selected habitats), were >80% overall and typically between 70% and 90% for many classes. Through this exercise, Wales has become the first country in Europe to produce a national map of habitats (as opposed to land cover) through object-orientated classification of satellite sensor data. Furthermore, the approach can be adapted to allow continual monitoring of the extent and condition of habitats and agricultural land.     

INDUSTRIAL PHOTOGRAMMETRY: NEW DEVELOPMENTS AND RECENT APPLICATIONS

Over the past decade, photogrammetry has been increasingly applied as a precise three dimensional measuring tool in industrial and engineering works. Analytical photogrammetry is now routinely employed in tasks of measurement as diverse as machine tool inspection and fixture checking, structural deformation monitoring, the provision of control databases to guide industrial robots and the measurement of structures in earth orbit. Traditional photogrammetric techniques and instrumentation are usually inappropriate for industrial work and the development of complete, fully integrated close range photogrammetric systems has recently gained considerable impetus. This paper details some of the significant new developments in industrial photogrammetry, with particular reference to technological advances in the Simultaneous Triangulation and Resection System (STARS) designed by Geodetic Services, Inc. for industrial photograininetry. Practical aspects of industrial measurement are also presented in a review of some of the varying tasks that GSI has carried out in recent years. Emphasis is placed on demonstrating the flexibility, accuracy, reliability and economy of photogrammetry, as well as the progress made in automating this measurement technique.