The nodal dependence of long-period ocean tides in the Drake Passage

Almost three decades of bottom pressure recorder (BPR) measurements at the Drake Passage, and 31 years of hourly tide gauge data from the Vernadsky Research Base on the Antarctic Peninsula, have been used to investigate the temporal and spatial variations in this region of the three main long-period tides Mf, Mm and Mt (in order of decreasing amplitude, with periods of a fortnight, a month and one-third of a month, respectively). The amplitudes of Mf and Mt, and the phase lags for all three constituents, vary over the nodal cycle (18.61 years) in essentially the same way as in the equilibrium tide, so confirming the validity of Doodson's nodal factors for these constituents. The amplitude of Mm is found to be essentially constant, and so inconsistent at the 3σ level from the ±13% (or  ∼ ±0.15mbar) anticipated variation over the nodal cycle, which can probably be explained by energetic non-tidal variability in the records at monthly timescales and longer. The north–south differences in amplitude for all three constituents are consistent with those in a modern ocean tide model (FES2014), as are those in phase lag for Mf and Mt, while the phase difference for Mm is smaller than in the model. BPR measurements are shown to be considerably superior to coastal tide gauge data in such studies, due to the larger proportion of non-tidal variability in the latter. However, correction of the tide gauge records for non-tidal variability results in the uncertainties in nodal parameters being reduced by a factor of 2 (for Mf at least) to a magnitude comparable (approximately twice) to those obtained from the BPR data

Tide Gauges: From single hazard to multi-hazard warning systems

As the name suggests, tide gauges were originally devised for the singular purpose of monitoring tidal fluctuations in sea level in order to aid safe navigation and port operations. Early tide gauges, such as that used by the famous dockmaster William Hutchinson at Liverpool in the late eighteenth century, consisted of little more than graduated markers on sea walls or posts, against which the sea surface could be measured by eye (Figure 1). These were used to record and then forecast the times and heights of high and low water each day; printed in local tide tables, they provided rudimentary information on variations in the tide

An evaluation of edge effects in nutritional accessibility and availability measures: a simulation study

<p>Abstract</p> <p>Background</p> <p>This paper addresses the statistical use of accessibility and availability indices and the effect of study boundaries on these measures. The measures are evaluated via an extensive simulation based on cluster models for local outlet density. We define outlet to mean either food retail store (convenience store, supermarket, gas station) or restaurant (limited service or full service restaurants). We designed a simulation whereby a cluster outlet model is assumed in a large study window and an internal subset of that window is constructed. We performed simulations on various criteria including one scenario representing an urban area with 2000 outlets as well as a non-urban area simulated with only 300 outlets. A comparison is made between estimates obtained with the full study area and estimates using only the subset area. This allows the study of the effect of edge censoring on accessibility measures.</p> <p>Results</p> <p>The results suggest that considerable bias is found at the edges of study regions in particular for accessibility measures. Edge effects are smaller for availability measures (when not smoothed) and also for short range accessibility</p> <p>Conclusions</p> <p>It is recommended that any study utilizing these measures should correct for edge effects. The use of edge correction via guard areas is recommended and the avoidance of large range distance-based accessibility measures is also proposed.</p

Evaluating geographic imputation approaches for zip code level data: an application to a study of pediatric diabetes

<p>Abstract</p> <p>Background</p> <p>There is increasing interest in the study of place effects on health, facilitated in part by geographic information systems. Incomplete or missing address information reduces geocoding success. Several geographic imputation methods have been suggested to overcome this limitation. Accuracy evaluation of these methods can be focused at the level of individuals and at higher group-levels (e.g., spatial distribution).</p> <p>Methods</p> <p>We evaluated the accuracy of eight geo-imputation methods for address allocation from ZIP codes to census tracts at the individual and group level. The spatial apportioning approaches underlying the imputation methods included four fixed (deterministic) and four random (stochastic) allocation methods using land area, total population, population under age 20, and race/ethnicity as weighting factors. Data included more than 2,000 geocoded cases of diabetes mellitus among youth aged 0-19 in four U.S. regions. The imputed distribution of cases across tracts was compared to the true distribution using a chi-squared statistic.</p> <p>Results</p> <p>At the individual level, population-weighted (total or under age 20) fixed allocation showed the greatest level of accuracy, with correct census tract assignments averaging 30.01% across all regions, followed by the race/ethnicity-weighted random method (23.83%). The true distribution of cases across census tracts was that 58.2% of tracts exhibited no cases, 26.2% had one case, 9.5% had two cases, and less than 3% had three or more. This distribution was best captured by random allocation methods, with no significant differences (p-value > 0.90). However, significant differences in distributions based on fixed allocation methods were found (p-value < 0.0003).</p> <p>Conclusion</p> <p>Fixed imputation methods seemed to yield greatest accuracy at the individual level, suggesting use for studies on area-level environmental exposures. Fixed methods result in artificial clusters in single census tracts. For studies focusing on spatial distribution of disease, random methods seemed superior, as they most closely replicated the true spatial distribution. When selecting an imputation approach, researchers should consider carefully the study aims.</p

An empirical approach to improving tidal predictions using recent real-time tide gauge data

Harmonic tidal prediction methods are often problematic in estuaries owing to the distortion of tidal fluctuations in shallow water, causing disparity between predicted and observed sea levels. The UK National Tidal and Sea Level Facility attempted to reduce prediction errors for the short-term forecasting of High Water (HW) extremes using three alternative techniques to the Harmonic Method in the Bristol Channel, where prediction errors are relatively large. A simple procedure for correcting Harmonic Method HW predictions using recent observations (referred to as the Empirical Correction Method) proved most effective and was also successfully applied to sea-level records from 42 of the 44 UK Tide Gauge Network locations. It is to be incorporated into the operational systems of the UK Coastal Monitoring and Forecasting Partnership to improve UK short-term sea level predictions

Tides at a coast

People often experience tidal influence at the coast, where the sea meets the land, with a daily or twice-daily rise and fall of the water level. Understanding and predicting tides is critical for: shoreline/hazard management; port, harbor, and shipping activities; renewable energy; and infrastructure management (e.g., telecommunication cables). Accurate prediction is also critical to ensure water sports and beach activities are carried out safely. In shallow waters, tides interact with bathymetry and other physical processes, such as: surges, waves, and density currents. Understanding the net (tidally averaged or residual) flow is key to explaining the transport of particulate and dissolved biogeochemical tracers and physical properties, such as heat and carbon. To observe the tide, (global) gage networks are installed, often providing near real-time data. Harmonic analysis of these data allows accurate prediction of the tide to support the numerous recreational and commercial activities that take place in shelf seas and at the coast

Probabilistic approaches to coastal risk decision-making under future sea level projections

Coastal communities are increasingly threatened by flooding from climate change-induced sea level rise and potential increases in storminess. Informed decisions on risk and resilience related to flood risk need to be made, but the assessment process is complex. It is difficult to bring all of the climate science and sea level rise projections to decision-making, and as a result, decisions are made without a real understanding of the uncertainties involved, a problem magnified the further projections go into the future (Figure 1)

Validating sea-level altimetry data against tide gauge for coastal risk analysis in Mozambique

Satellite altimetry data provide a solution to the lack of in situ tide gauge data, which are essential for comprehending various marine processes worldwide. In the present study, we seek to validate ALES−retrieved sea−level data against tide gauge observations from four ground stations on the coast of Mozambique. The approach consisted of extracting data from selected tracks of the Jason−1, Jason−2 and Jason−3 missions, and processing it to (i) remove outliers, (ii) collocate alongside tide gauge data, (iii) remove the tidal component and detrend, and (iv) perform a set of statistical analyses. Good agreement was found between the altimetry and tide gauge data in three of the four stations (Maputo, r = 0.59; Inhambane, r = 0.87; and Pemba, r = 0.75), with the exception of Beira. The annual and semi-annual cycles in the two datasets revealed that the altimetry signal is smaller in amplitude and ahead (with a few exceptions) of tide gauge by a varying number of days in each location. Both the annual and semi-annual cycles are far more comparable in Pemba, where the amplitude in particular has the same order of magnitude, followed by the Maputo station. The study concluded that the selected altimetry data for Pemba and Maputo stations are valid and can be used for coastal risk analysis and other applications. No altimetry data could be validated for Inhambane and Beira stations due to lack of consistent and sufficiently long tide gauge records. This difficulty urges the need for improved maintenance practices of ground stations located near human settlements that rely on sound information of the sea level and its variability to protect lives, infrastructure and livelihoods