45 research outputs found
Changes to estimates of extreme sea levels for Wales when data from the 2013/2014 winter are included. Report for Natural Resources Wales
No full textThe effect of the novel antifungal drug F901318 (Olorofim) on the growth and viability of Aspergillus fumigatus
No full textWe thank our colleagues at F2G Ltd. for their support in this work, as well as the Manchester Fungal Infection Group at the University of Manchester. We also thank Gillian Milne and the Microscopy and Histology Core Facility at the Medical Research Council Centre for Medical Mycology at the University of Aberdeen for their assistance with TEM. We also thank John Rex for critical reading of the manuscript. The Microscopy and Histology Core Facility at the Medical Research Council Centre for Medical Mycology at the University of Aberdeen is supported by grant number MR/N006364/1. S.D.P. and M.C.A. are supported by the European Marie Curie ITN FungiBrain grant PITN-GA-2013-607963. S.D.P. was the primary author and performed the live-cell imaging microscopy, TEM, viability staining, and the analysis of the data. N.B. performed the postexposure effect assays. M.C.A. assisted with TEM. G.E.M.S. designed F901318. N.B., A.C.B., D.L., M.B., N.D.R., and J.D.O. provided guidance and assistance during this project and in the preparation of the manuscript.Peer reviewe
Fast error analysis of continuous GPS observations
No full textIt has been generally accepted that the noise in continuous GPS observations can be well described by a power-law plus white noise model. Using maximum likelihood estimation (MLE) the numerical values of the noise model can be estimated. Current methods require calculating the data covariance matrix and inverting it, which is a significant computational burden. Analysing 10 years of daily GPS solutions of a single station can take around 2 h on a regular computer such as a PC with an AMD AthlonTM 64 X2 dual core processor. When one analyses large networks with hundreds of stations or when one analyses hourly instead of daily solutions, the long computation times becomes a problem. In case the signal only contains power-law noise, the MLE computations can be simplified to a process where N is the number of observations. For the general case of power-law plus white noise, we present a modification of the MLE equations that allows us to reduce the number of computations within the algorithm from a cubic to a quadratic function of the number of observations when there are no data gaps. For time-series of three and eight years, this means in practise a reduction factor of around 35 and 84 in computation time without loss of accuracy. In addition, this modification removes the implicit assumption that there is no environment noise before the first observation. Finally, we present an analytical expression for the uncertainty of the estimated trend if the data only contains power-law nois
Commentary on ‘Coastal Planning Should Be Based on Proven Sea Level Data' by A. Parker and C.D. Ollier (Ocean & Coastal Management, 124, 1–9, 2016)
No full textA recent paper by A. Parker and C.D. Ollier (Ocean & Coastal Management, 124, 1–9, 2016), concerned with the use of 'proven’ sea-level data for coastal planning, contained a number of incorrect or misleading statements about sea-level data sets and measurement methods. In this commentary, we address aspects of sea-level records that could have been misunderstood by readers of that paper. While we agree with the main point made by the authors, that the best possible sea-level data are required by coastal planners, we suggest that planners should base their work on wider and better informed sources of sea-level information
The impact of future sea-level rise on the tides
No full textTides (along with mean sea-level and surges) are a key component in coastal extreme water levels. This investigation begins by assessing the effect of future sea-level rise (SLR) on the tides of the northwest European Continental Shelf. Tides here are dominated by semidiurnal constituents; therefore the focus is on changes in the M2 constituent and the spring and neap tides. The validated operational Dutch Continental Shelf Model is run for the present day sea-level as well as uniform 2 and 10m SLR scenarios. M2 tidal amplitude responds to SLR in a spatially non-uniform manner, with substantial amplitude increases and decreases in both scenarios. The North Sea M2 tidal response is not proportional to SLR between 2 and 10m. In the 2m SLR scenario the M2 constituent is particularly responsive in the resonant areas. Changes in the spring tide are generally larger (-49cm St. Malo to +35cm Cuxhaven) than those in the M2, neap or shallow water tides. With SLR the depth, wave speed and wave length are increased causing changes in near resonant areas. In expansive shallow areas SLR also causes reduced energy dissipation by bottom friction. These mechanisms result in the migration of tidal amphidromes and complex patterns of non-proportional change in the tide with SLR. These substantial alterations to the tides are contrary to some previous studies.These results motivate a subsequent investigation into the effect of future SLR on the global tides. We use a fully global forward tidal model, OTISmpi, to simulate the response of the four primary tidal constituents (M2, S2, K1, O1) as well as mean high water (MHW) and maximum range to various SLR scenarios. Attention is paid to changes at the 136 largest coastal cities (populations >1 million), where changes would have the greatest significance. A refined model setup is shown to have good skill at representing the present day tides. Uniform SLR scenarios 0.5-10m with fixed coastlines show the tidal amplitudes in shelf seas globally to respond strongly (increases and decreases) and non-proportionally to SLR. The changes in K1 and O1 tides are confined to Asian shelves. With 0.5m, 1m and 2m SLR MHW changes exceed ±10% of the SLR at 13, 13 and 10 of the 136 cities, respectively. Uniform SLR scenarios including coastal recession show a stronger and increasingly negative MHW response. The regularly opposing signs of change between the fixed and recession cases are explained through the opposing effect of the perturbations on the natural period of oscillation of the basin. These results suggest it may be possible to influence the sign of the tidal amplitude change through coastal management strategies. Non-uniform SLR, due to ice melt, causes the largest difference from the uniform SLR tidal response at high latitudes, in the near field (diminished response) and far field (amplified response) of the mass loss.Changes in the tide will influence: coastal flooding, renewable and nuclear power generation, water reliant industry, sediment transport, dredging, shipping, tidal mixing fronts and intertidal habitats
Fast error analysis of continuous GNSS observations with missing data
No full textOne of the most widely used method for the time-series analysis of continuous Global Navigation Satellite System (GNSS) observations is Maximum Likelihood Estimation (MLE) which in most implementations requires O(n3)operations for nn observations. Previous research by the authors has shown that this amount of operations can be reduced to O(n2) for observations without missing data. In the current research we present a reformulation of the equations that preserves this low amount of operations, even in the common situation of having some missing data. Our reformulation assumes that the noise is stationary to ensure a Toeplitz covariance matrix. However, most GNSS time-series exhibit power-law noise which is weakly non-stationary. To overcome this problem, we present a Toeplitz covariance matrix that provides an approximation for power-law noise that is
accurate for most GNSS time-series. Numerical results are given for a set of synthetic data and a set of International GNSS Service (IGS) stations, demonstrating a reduction in computation time of a factor of 10–100 compared to the standard MLE method, depending on the length of the time-series and the amount of missing data
The effect of temporal correlated noise on the sea level rate and acceleration uncertainty
No full textIt is well known that sea level variations exhibit temporal correlation. This is sometimes ignored in the estimation process of the sea level rise or taken into account using a first-order autoregressive model. We have verified that this stochastic model is accurate for yearly tide gauge and sea level reconstruction time-series but it underestimates the real rate uncertainty in satellite altimetry and monthly tide gauge data by a factor of 1.3–1.5 and sometimes even 2. Similar results were found for sea level acceleration. An original finding is that in 13–17 per cent of the tide gauge data, we found random walk which increases the rate uncertainty on average by an additional factor of 3. The estimation errors presented in this research should be added to the other sources of uncertainty, such as the vertical land movement, spatial correlation and altimeter drift, to obtain the total sea level rate and acceleration error
Estimation of offsets in GPS time-series and application to the detection of earthquake deformation in the far-field.
No full textExtracting geophysical signals from Global Positioning System (GPS) coordinate time-series is a well-established practice that has led to great insights into how the Earth deforms. Often small discontinuities are found in such time-series and are traceable to either broad-scale deformation (i.e. earthquakes) or discontinuities due to equipment changes and/or failures. Estimating these offsets accurately enables the identification of coseismic deformation estimates in the former case, and the removal of unwanted signals in the latter case which then allows tectonic rates to be estimated more accurately. We develop a method to estimate accurately discontinuities in time series of GPS positions at specified epochs, based on a so-called ‘offset series’. The offset series are obtained by varying the amount of GPS data before and after an event while estimating the offset. Two methods, a mean and a weighted mean method, are then investigated to produce the estimated discontinuity from the offset series. The mean method estimates coseismic offsets without making assumptions about geophysical processes that may be present in the data (i.e. tectonic rate, seasonal variations), whereas the weighted mean method includes estimating coseismic offsets with a model of these processes. We investigate which approach is the most appropriate given certain lengths of available data and noise within the time-series themselves. For the Sumatra–Andaman event, with 4.5 yr of pre-event data, we show that between 2 and 3 yr of post-event data are required to produce accurate offset estimates with the weighted mean method. With less data, the mean method should be used, but the uncertainties of the estimated discontinuity are larger
Analysis of the uncertainties in tidal constants obtained from short tide gauge records and their value for tidal studies
No full textWe conduct a study to estimate uncertainties in tidal constants from M2, S2, N2, K1, O1, Q1 and related K2, P1, 2N2 constituents from 35-day tide gauge records in the northern Australia and Papua New Guinea regions. The motivation for this study stems from the availability of ∼300 short tide gauge records (most ∼ 30 days long) in these regions, but their accuracy for tidal studies is not clear. We simulate the 35-day uncertainties by dividing a selected set of 14 long tide gauge records (19-years where available) from the GESLA3 data set into consecutive 35-day sections. Amplitudes and phase lags computed from each long record are treated as the ‘true’ values, from which we compute and analyse inference information for the short records. Comparison of empirical amplitude ratios and phase lag differences with the relationships from the Equilibrium tide show significant differences in both amplitude and phase lag in some constituents and locations. We also compare inference information derived from the FES2022b ocean tide model, which suggests that such models could be used in this way in some instances. Empirical uncertainties in the 35-day records were no more than 0.045 m with maximum errors reaching 0.093 m. The largest 35-day errors appeared in the K1 constituent, mostly in the Torres Strait and northwest Australia. Empirical inference information showed improvement on the Equilibrium assumption for S2 and K1 reference constituents and related constituents K2, 2N2 and P1, demonstrating that the latter can be accurately derived from short records with accurate inference information
Improved and extended tide gauge records for the British Isles leading to more consistent estimates of sea level rise and acceleration since 1958
No full textThis paper describes methods of obtaining improved estimates of long-term sea level trends for the British Isles. This is achieved by lengthening the sea level records where possible, then removing known sources of variability, and then further adjusting for datum errors that are revealed by the previous processes after verification using metadata from archived sources. Local sea level variability is accounted for using a tide and surge model. Far field variability is accounted for using a “common mode”. This combination reduces the residual variability seen at tide gauges around the coast of the British Isles to the point that a number of previously unrecognised steps in individual records become apparent, permitting a higher level of quality control to be applied. A comprehensive data archaeology exercise was carried out which showed that these step-like errors are mostly coincident with recorded site-specific changes in instrumentation, and that in many cases the periodic tide gauge calibration records can be used to quantify these steps. A smaller number of steps are confirmed by “buddy-checking” against neighbouring tide gauges. After accounting for the observed steps, using levelling information where possible and an empirical fit otherwise, the records become significantly more consistent. The steps are not found to make a large difference to the trend and acceleration observed in UK sea level overall, but their correction results in much more consistent estimates of first order (Sea Level Rise) and second order (Sea Level Acceleration) trends over this 60-year period. We find a mean rate of sea level rise of 2.39 ± 0.27 mm yr−1, and an acceleration of 0.058 ± 0.030 mm yr−2 between Jan. 1958 and Dec. 2018. The cleaner dataset also permits us to show more clearly that the variability other than that derived from local meteorology is indeed consistent around the UK, and relates to sea level changes along the eastern boundary of the North Atlantic
