THE IMPACT OF EXTREME STORM WAVES AT THE COAST; THE ROLE OF INFRAGRAVITY WAVES

Infragravity (IG) waves are long period waves with frequencies lower than wind-waves and swell, usually in the frequency band 0.003 to 0.05 Hz. IG waves are known to dominate hydrodynamic and sediment transport processes close to the shoreline on low sloping sandy beaches, especially when the incoming swell and wind-driven waves (incident waves) are large. However, in extreme wave conditions, how their importance varies on coarser grain sized and steeper beaches, and with different mixes of incoming swell and wind-waves, is largely unknown. Here, a new dataset comprising in-situ and remote observations from five contrasting sites (one low-sloping sandy beach, two steep gravel beaches and two compound/mixed sand and gravel beaches), under extreme wave conditions is used to assess infragravity response across a wider range of wave heights & periods, beach slopes and grain sizes than has been previously explored. The beaches studied ranged in slope from tanβ = 0.02 – 0.35 with median grain sizes (D50) of between 0.25 – 60 mm. During the experiments significant wave heights (Hs) of up to 7 m and peak periods (Tp) up to 20 s were observed. During the five storms recorded, waves in excess of the 95th percentile of the long-term record of Hs were observed at all sites, with waves representative of a 1-in-1, 1-in-5, 1-in-10, 1-in-20 and 1-in-40 year event at the five sites respectively. Video observations of a 1-in-40 year storm, ‘Emma’, impacting a steep gravel beach revealed that significant infragravity swash height (Sig) dominated over significant gravity swash height (Sg) at the shoreline when offshore wave height (H0) exceeded 1.5 m, where ‘dominance’ was defined by the ratio of Sig/Sg exceeding 1. Sig increased linearly with offshore wave height (H0), as has been reported in previously published field work on sandy beaches. However, for a given wave height, Sig was between one third and three times larger on the steep gravel beach than values quoted in the literature for sandy beaches. Observations collected on the steep gravel beach during storm ‘Emma’ were compared to data collected at an additional four sites (a low-sloping sandy beach, a second steeper gravel beach and two compound/mixed sand and gravel beaches). Sig at the shoreline in excess of 0.5 m was consistently observed at all five contrasting beaches. The largest infragravity swash heights were observed at the steeper gravel beach (Sig up to 11.4 m), followed by the low-sloping sandy beach (Sig up to 3.2 m), and the less steep gravel beach (Sig up to 2.6 m) and were lowest at the compound/mixed sites. Due to contrasting incident wave breaking and dissipation processes, infragravity frequencies were observed to be most dominant over gravity frequencies on the low-sloping sandy beach (Sig/Sg up to 4.4), occasionally dominant on the gravel beaches (Sig/Sg up to 2.5), and rarely dominant on the compound/mixed beaches (Sig/Sg up to 1.1). An existing equation commonly used to parameterize Sig on sandy beaches was tested on the new dataset, performing well on data from the sandy beach but less well on data from the gravel beach. An existing equation commonly used to parametrize runup on gravel beaches was modified to produce a new gravel specific parametrization of Sig, which performed well on the gravel sites and less well on the sandy site. Both equations performed poorly when applied to the dataset combining sand and gravel beaches. H02T, proportional to deep water wave power, was found to accurately predict Sig on both the sand and gravel beaches, demonstrating that, under extreme storm wave conditions, combined wave height and period are the main drivers of infragravity oscillations at the shoreline, with the beach morphology playing a secondary role. In-situ observations were collected seaward of the incident wave breakpoint by bed-mounted acoustic Doppler current profilers and through the surf zone by intertidal arrays of pressure transducers at two of the five sites (the low-sloping sandy beach and the less steep of the two gravel beaches). Analysis revealed that energy transferred to the IG band seaward of the surf zone at the sandy beach and landward of breakpoint at the gravel beach. The surf beat similarity parameter (ξSurfbeat) indicated that bound long wave release was the dominant IG wave generating mechanism on the low sloping sandy beach (ξSurfbeat 0.1). The findings presented in this thesis highlight the importance of collecting field data over a wide range of conditions. When deep water significant wave height (H0) exceeds 2 m, IG energy dominates the inner surf zone and swash on both sand and gravel beaches. Therefore, in addition to their well-known importance on sandy sites, infragravity waves are also implicated in the inundation and erosion of gravel beaches during storms

Evaluating operational AVHRR sea surface temperature data at the coastline using surfers

Sea surface temperature (SST) is an essential climate variable that can be measured routinely from Earth Observation (EO) with high temporal and spatial coverage. To evaluate its suitability for an application, it is critical to know the accuracy and precision (performance) of the EO SST data. This requires comparisons with co-located and concomitant in situ data. Owing to a relatively large network of in situ platforms there is a good understanding of the performance of EO SST data in the open ocean. However, at the coastline this performance is not well known, impeded by a lack of in situ data. Here, we used in situ SST measurements collected by a group of surfers over a three year period in the coastal waters of the UK and Ireland, to improve our understanding of the performance of EO SST data at the coastline. At two beaches near the city of Plymouth, UK, the in situ SST measurements collected by the surfers were compared with in situ SST collected from two autonomous buoys located ∼7 km and ∼33 km from the coastline, and showed good agreement, with discrepancies consistent with the spatial separation of the sites. The in situ SST measurements collected by the surfers around the coastline, and those collected offshore by the two autonomous buoys, were used to evaluate the performance of operational Advanced Very High Resolution Radiometer (AVHRR) EO SST data. Results indicate: (i) a significant reduction in the performance of AVHRR at retrieving SST at the coastline, with root mean square errors in the range of 1.0 to 2.0 °C depending on the temporal difference between match-ups, significantly higher than those at the two offshore stations (0.4 to 0.6 °C); (ii) a systematic negative bias in the AVHRR retrievals of approximately 1 °C at the coastline, not observed at the two offshore stations; and (iii) an increase in the root mean square error at the coastline when the temporal difference between match-ups exceeded three hours. Harnessing new solutions to improve in situ sampling coverage at the coastline, such as tagging surfers with sensors, can improve our understanding of the performance of EO SST data in coastal regions, helping inform users interested in EO SST products for coastal applications. Yet, validating EO SST products using in situ SST data at the coastline is challenged by difficulties reconciling the two measurements, which are provided at different spatial scales in a dynamic and complex environment

Expanding Aquatic Observations through Recreation

Accurate observations of the Earth system are required to understand how our planet is changing and to help manage its resources. The aquatic environment—including lakes, rivers, wetlands, estuaries, coastal and open oceans—is a fundamental component of the Earth system controlling key physical, biological, and chemical processes that allow life to flourish. Yet, this environment is critically undersampled in both time and space. New and cost-effective sampling solutions are urgently needed. Here, we highlight the potential to improve aquatic sampling by tapping into recreation. We draw attention to the vast number of participants that engage in aquatic recreational activities and argue, based on current technological developments and recent research, that the time is right to employ recreational citizens to improve large-scale aquatic sampling efforts. We discuss the challenges that need to be addressed for this strategy to be successful (e.g., sensor integration, data quality, and citizen motivation), the steps needed to realize its potential, and additional societal benefits that arise when engaging citizens in scientific sampling

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

Background Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. Methods We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). Findings In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683–0·717]). Interpretation In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. Funding British Journal of Surgery Society