THE INTEGRATION OF CLOUD SATELLITE IMAGES WITH PREDICTION OF ICY CONDITIONS ON DEVON'S ROADS

The need for improved cloud parameterisations in a road surface temperature model is demonstrated. Case studies from early 1994 are used to investigate methods of tracking cloud cover using satellite imagery and upper level geostrophic flow. Two of these studies are included in this thesis. Errors encountered in cloud tracking methods were investigated as well as relationships between cloud height and pixel brightness in satellite imagery. For the first time, a one dimensional energy balance model is developed to investigate the effects of erroneous cloud forecasts on surface temperature. The model is used to determine detailed dependency of surface freezing onset time and minimum temperature on cloud cover. Case studies from the 1995/96 winter in Devon are undertaken to determine effects of differing scenarios of cloud cover change. From each study, an algorithm for predicting road surface temperature is constructed which could be used in future occurrences of the corresponding scenario of the case study. Emphasis is strongly placed on accuracy of predictions of surface freezing onset time and minimum surface temperature. The role o f surface and upper level geostrophic flow, humidity and surface wetness in temperature prediction is also investigated. In selected case studies, mesoscale data are also analysed and compared with observations to determine feasibility of using mesoscale models to predict air temperature. Finally, the algorithms constructed from the 1995/96 studies are tested using case studies from the 1996/97 winter. This winter was significantly different from its preceding one which consequently meant that the algorithm from only one scenario of the 1995/96 winter could be tested. An algorithm is also constructed from a 1996/97 winter case study involving a completely different scenario Recommendations for future research suggest testing of existing algorithms with guidance on additional scenarios.Devon County Counci

Social Entrepreneurship as a Path to Alleviate Global Socio-Economic and Environmental Issues

This project focused on the work of eight students who are part of the Global Scholars program for the 2018-2019 school year. As a team, we traveled to Australia for 10 days in January 2019 to partner with two different nonprofit social enterprises, and five students from Central Queensland University. The primary research question we reviewed was, ‘How can social entrepreneurship save the Great Barrier Reef?’. To answer this, we conducted ethnographic research and the collection of 75 surveys from various individuals and interviewees. Once back at Boise State, we conducted archive research, analyzed our data, and made recommendations to the partner organizations on how they can increase their business operations, resulting in greater impact and positive results on saving the Great Barrier Reef. Conclusions emphasize that no single social enterprise model is sufficient to tackle environmental issues, but that as part of a greater initiative, each model can play a significant role

Keyhole fluctuation and pore formation mechanisms during laser powder bed fusion additive manufacturing

Keyhole porosity is a key concern in laser powder-bed fusion (LPBF), potentially impacting component fatigue life. However, some keyhole porosity formation mechanisms, e.g., keyhole fluctuation, collapse and bubble growth and shrinkage, remain unclear. Using synchrotron X-ray imaging we reveal keyhole and bubble behaviour, quantifying their formation dynamics. The findings support the hypotheses that: (i) keyhole porosity can initiate not only in unstable, but also in the transition keyhole regimes created by high laser power-velocity conditions, causing fast radial keyhole fluctuations (2.5–10 kHz); (ii) transition regime collapse tends to occur part way up the rear-wall; and (iii) immediately after keyhole collapse, bubbles undergo rapid growth due to pressure equilibration, then shrink due to metal-vapour condensation. Concurrent with condensation, hydrogen diffusion into the bubble slows the shrinkage and stabilises the bubble size. The keyhole fluctuation and bubble evolution mechanisms revealed here may guide the development of control systems for minimising porosity

Using spectral indices to estimate water content and GPP in Sphagnum moss and other peatland vegetation

Peatlands provide important ecosystem services including carbon stroage and biodiversity conservation. Remote sensing shows potential for monitoring peatlands, but most off-the-shelf data produces are developed for unsaturated environments and it is unclear how well they can perform in peatland ecosystems. Sphagnum moss is an important peatland genus with specific characteristics which can affect spectral reflectance, and we hypothesized that the prevalence of Sphagnum in a peatland could affect the spectral signature of the area. This study combines results from both laboratory and field experiments to assess the relationship between spectral indices and the moisture content and GPP of peatland (blanket bog) vegetation species. The aim was to consider how well the selected indices perform under a range of conditions, and whether Sphagnum has a significant impact on the relationships tested. We found that both water indices tested (NDWI and fWBI) were sensitive to the water content changes in Sphagnum moss in the laboratory, and there was little difference between them. Most of the vegetation indices tested (the NDVI, EVI, SIPI and CIm) were found to have a strong relationship with GPP both in the laboratory and in the field. The NDVI and EVI are useful for large-scale estimation of GPP, but are sensitive to the proportion of Sphagnum present. The CIm is less affected by different species proportions and might therefore be the best to use in areas where species cover is unknown. The PRI is shown to be best suited to small-scale studies of single species

Viral load is strongly associated with length of stay in adults hospitalised with viral acute respiratory illness

Background: respiratory viruses are detectable in a large proportion of adults hospitalised with acute respiratory illness. For influenza and other viruses there is evidence that viral load and persistence are associated with certain clinical outcomes but it is not known if there is an association between viral load and hospital length of stay. Methods: 306 adults hospitalised with viral acute respiratory illness were studied. Associations between viral load and length of stay were examined. Multiple linear regression analysis was performed to control for age, comorbidity, influenza vaccine status, duration of illness prior to hospitalisation, bacterial co-infection, clinical group and virus subtype.Results: high viral load was associated with a longer duration of hospitalisation for all patients (p &lt;0.0001). This remained significant across all virus types and clinical groups and when adjusted for age, comorbidity, duration of illness prior to hospitalisation, bacterial co-infection and other factors. Conclusions: high viral loads are associated with prolonged hospital length of stay in adults with viral acute respiratory illness. This further supports existing evidence demonstrating that viral acute respiratory illness is a viral load driven process and suggests that viral load could be used in clinical practise to predict prolonged hospitalisation and prioritise antivirals. International Standard Randomised Controlled Trial Number (ISRCTN): 21521552<br/

Assessing the reliability of peatland GPP measurements by remote sensing: from plot to landscape scale

Estimates of peatland carbon fluxes based on remote sensing data are a useful addition to monitoring methods in these remote and precious ecosystems, but there are questions as to whether large-scale estimates are reliable given the small-scale heterogeneity of many peatlands. Our objective was to consider the reliability of models based on Earth Observations for estimating ecosystem photosynthesis at different scales using the Forsinard Flows RSPB reserve in Northern Scotland as our study site. Three sites across the reserve were monitored during the growing season of 2017. One site is near-natural blanket bog, and the other two are at different stages of the restoration process after removal of commercial conifer forestry. At each site we measured small (flux chamber) and landscape scale (eddy covariance) CO2 fluxes, small scale spectral data using a handheld spectrometer, and obtained corresponding satellite data from MODIS. The variables influencing GPP at small scale, including microforms and dominant vegetation species, were assessed using exploratory factor analysis. A GPP model using land surface temperature and a measure of greenness from remote sensing data was tested and compared to chamber and eddy covariance CO2 fluxes; this model returned good results at all scales (Pearson’s correlations of 0.57 to 0.71 at small scale, 0.76 to 0.86 at large scale). We found that the effect of microtopography on GPP fluxes at the study sites was spatially and temporally inconsistent, although connected to water content and vegetation species. The GPP fluxes measured using EC were larger than those using chambers at all sites, and the reliability of the TG model at different scales was dependent on the measurement methods used for calibration and validation. This suggests that GPP measurements from remote sensing are robust at all scales, but that the methods used for calibration and validation will impact accuracy

The observed state of the water cycle in the early twenty-first century

Author Posting. © American Meteorological Society, 2015. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 28 (2015): 8289–8318, doi:10.1175/JCLI-D-14-00555.1.This study quantifies mean annual and monthly fluxes of Earth’s water cycle over continents and ocean basins during the first decade of the millennium. To the extent possible, the flux estimates are based on satellite measurements first and data-integrating models second. A careful accounting of uncertainty in the estimates is included. It is applied within a routine that enforces multiple water and energy budget constraints simultaneously in a variational framework in order to produce objectively determined optimized flux estimates. In the majority of cases, the observed annual surface and atmospheric water budgets over the continents and oceans close with much less than 10% residual. Observed residuals and optimized uncertainty estimates are considerably larger for monthly surface and atmospheric water budget closure, often nearing or exceeding 20% in North America, Eurasia, Australia and neighboring islands, and the Arctic and South Atlantic Oceans. The residuals in South America and Africa tend to be smaller, possibly because cold land processes are negligible. Fluxes were poorly observed over the Arctic Ocean, certain seas, Antarctica, and the Australasian and Indonesian islands, leading to reliance on atmospheric analysis estimates. Many of the satellite systems that contributed data have been or will soon be lost or replaced. Models that integrate ground-based and remote observations will be critical for ameliorating gaps and discontinuities in the data records caused by these transitions. Continued development of such models is essential for maximizing the value of the observations. Next-generation observing systems are the best hope for significantly improving global water budget accounting.This research was funded by multiple grants from NASA’s Energy and Water Cycle Study (NEWS) program.2016-05-0