Geomatic Ventures (United Kingdom)

<strong class="journal-contentHeaderColor">Abstract.</strong> Tidal storm surges can result in significant damage and inundation if sea defences are insufficiently robust. Coastal planners need to know the risk of flooding so that sea defences and coastal developments can be specified and sited appropriately. Since Gumbel's original work on extreme value statistics, several modifications and new methods have been proposed for evaluating the risk of tidal inundation, with the Skew Surge Joint Probability Method (SSJPM) recently gaining popularity. However, SSJPM is complex, often requiring manual intervention, and is difficult to automate. Guided by the search for a method specifically applicable to tides that is amenable to automation, this paper proposes several modifications to Gumbel's original approach. The novel technique is termed TMAX since its initial time unit is one tidal day, rather than the usual annual maxima (AMAX). Compared to AMAX, the TMAX method offers more efficient use of extreme data events, provides reduced variance in design height, and more efficiently handles missing data. The results of TMAX are compared with those of a recent study using the SSJPM method at 35 United Kingdom identical coastal locations, showing broad agreement. This new approach provides a robust mechanism for extreme tide analysis and better informs strategies for coastal management and resilience.

Based upon a radically new approach, this paper describes a 2-box absolute flow model that calculates the CO2 transfer between the atmosphere and a terrestrial / ocean mixing reservoir. Given the inputs of anthropogenic fossil fuel emissions (CO2ff), atmospheric CO2 mixing-ratio and nuclear weapons bomb yields, the model calculates atmospheric d13C and &amp;Delta;14C time-series, with the level of agreement for d13C being to within &amp;plusmn; 0.05 &amp;permil;, for &amp;Delta;14C to within &amp;plusmn; 3&amp;permil;, spanning 200 years. The model contains only seven internal parameters which are varied to optimize the fit. Yet according to conventional wisdom, this model should not work. It is commonly held that the 13C and 14C isotopic forms of carbon bypass seawater carbonate chemistry, resulting in very different absorption properties (Revelle factor) as compared to 12C. This study rejects this assumption, and uses the same residence time and reservoir mixing properties for all isotopes. The paper includes an analysis justifying why the isotopic bypass of the Revelle factor is not significant. The study describes the use of the model to track CO2ff takeup using two separate measures, a) the amount of molecular CO2ff remaining in the atmosphere and b) the amount of atmospheric growth attributable to CO2ff, thereby resolving discrepancies in published values.

Abstract Peatland surface motion is a key property of peatland that relates to condition. However, field‐based techniques to measure surface motion are not cost‐effective over large areas and long time periods. An alternative method that can quantify peatland surface motion over large areas is interferometric synthetic aperture radar. Although field validation of the accuracy of this method is difficult, the value of interferometric synthetic aperture radar (InSAR) as a means of quantifying peat condition can be tested. To achieve this, the characteristics of InSAR time series measured over an18‐month period at 22 peatland sites in the Flow Country northern Scotland were compared to site condition assessment based on plant functional type and site management history. Sites in good condition dominated by Sphagnum display long‐term stability or growth and a seasonal cycle with maximum uplift and subsidence in August–November and April–June, respectively. Drier and partially drained sites dominated by shrubs display long‐term subsidence with maximum uplift and subsidence in July–October and February–June, respectively. Heavily degraded sites with large bare peat extent display subsidence with no distinct seasonal oscillations. Seasonal oscillation in surface motion at sites with a dominant nonvascular plant community is interpreted as resulting from changes in seasonal evaporative demand. On sites with extensive vascular plants cover and falling water table, surface oscillations are interpreted as representing sustained drawdown during the growing season and subsequent recharge in late winter. This study highlights the potential to use InSAR to characterize peatland condition and provide a new view of the surface dynamics of peatland landscapes.

Detailed knowledge of the shape of the seafloor is crucial to humankind. Bathymetry data is critical for safety of navigation and is used for many other applications. In an era of ongoing environmental degradation worldwide, bathymetry data (and the knowledge derived from it) play a pivotal role in using and managing the world’s oceans in a way that is in accordance with the United Nations Sustainable Development Goal 14 - conserve and sustainably use the oceans, seas and marine resources for sustainable development. However, the vast majority of our oceans is still virtually unmapped, unobserved, and unexplored. Only a small fraction of the seafloor has been systematically mapped by direct measurement. The remaining bathymetry is predicted from satellite altimeter data, providing only an approximate estimation of the shape of the seafloor. Several global and regional initiatives are underway to change this situation. This paper presents a selection of these initiatives as best practice examples for bathymetry data collection, compilation and open data sharing as well as the Nippon Foundation-GEBCO (The General Bathymetric Chart of the Oceans) Seabed 2030 Project that complements and leverages these initiatives and promotes international collaboration and partnership. Several non-traditional data collection opportunities are looked at that are currently gaining momentum as well as new and innovative technologies that can increase the efficiency of collecting bathymetric data. Finally, recommendations are given towards a possible way forward into the future of seafloor mapping and towards achieving the goal of a truly global ocean bathymetry.

Satellite Earth Observation (EO) is often used as a cost-effective method to report on the condition of remote and inaccessible peatland areas. Current EO techniques are primarily limited to reporting on the vegetation classes and properties of the immediate peat surface using optical data, which can be used to infer peatland condition. Another useful indicator of peatland condition is that of surface motion, which has the potential to report on mass accumulation and loss of peat. Interferometic SAR (InSAR) techniques can provide this using data from space. However, the most common InSAR techniques for information extraction, such as Persistent Scatterers’ Interferometry (PSI), have seen limited application over peat as they are primarily tuned to work in areas of high coherence (i.e., on hard, non-vegetated surfaces only). A new InSAR technique, called the Intermittent Small BAseline Subset (ISBAS) method, has been recently developed to provide measurements over vegetated areas from SAR data acquired by satellite sensors. This paper examines the feasibility of the ISBAS technique for monitoring long-term surface motion over peatland areas of the Flow Country, in the northeast of Scotland. In particular, the surface motions estimated are compared with ground data over a small forested area (namely the Bad a Cheo forest Reserve). Two sets of satellite SAR data are used: ERS C-band images, covering the period 1992–2000, and Sentinel-1 C-band images, covering the period 2015–2016. We show that the ISBAS measurements are able to identify surface motion over peatland areas, where subsidence is a consequence of known land cover/land use. In particular, the ISBAS products agree with the trend of surface motion, but there are uncertainties with their magnitude and direction (vertical). It is concluded that there is a potential for the ISBAS method to be able to report on trends in subsidence and uplift over peatland areas, and this paper suggests avenues for further investigation, but this requires a well-resourced validation campaign.

This article describes an “absolute” calibration of Jason-1 (J-1) altimeter sea surface height bias using a method developed for TOPEX/Poseidon (T/P) bias determination reported previously. The method makes use of U.K. tide gauges equipped with Global Positioning System (GPS) receivers to measure sea surface heights at the same time, and in the same geocentric reference frame, as Jason-1 altimetric heights recorded in the nearby ocean. The main time-dependent components of the observed altimeter-minus-gauge height-difference time series are due to the slightly different ocean tides at the gauge and in the ocean. The main harmonic coefficients of the tide differences are calculated from analysis of the copious TOPEX data set and then applied to the determination of T, P, and J-1 bias in turn. Datum connections between the tide gauge and altimetric sea surface heights are made by means of precise, local geoid differences from the EGG97 model. By these means, we have estimated Jason-1 altimeter bias determined from Geophysical Data Record (GDR) data for cycles 1–61 to be 12.9 cm, with an accuracy estimated to be approximately 3 cm on the basis of our earlier work. This J-1 bias value is in close agreement with those determined by other groups, which provides a further confirmation of the validity of our method and of its potential for application in other parts of the world where suitable tide gauge, GPS, and geoid information exist.