Plastic After an Extreme Storm: The Typhoon-Induced Response of Micro- and Mesoplastics in Coastal Waters

Extreme storms, such as tropical cyclones, are responsible for a significant portion of the plastic debris transported from land to sea yet little is known about the storm response of microplastics and other debris in offshore and open waters. To investigate this, we conducted floating plastic surveys in the center of Sagami Bay, Japan approximately 30 km from the coastline, before and after the passage of a typhoon. The concentrations (number of particles/km2) of micro- and mesoplastics were two orders of magnitude higher 1-day after the typhoon than the values recorded pre-typhoon and the mass (g/km2) of plastic particles (sum of micro- and mesoplastics) increased 1,300 times immediately after the storm. However, the remarkably high abundance of micro- and mesoplastics found at 1-day after the typhoon returned to the pre-typhoon levels in just 2 days. Model simulations also suggested that during an extreme storm a significant amount of micro- and mesoplastics can be rapidly swept away from coastal to open waters over a short period of time. To better estimate the annual load of plastics from land to sea it is important to consider the increase in leakages of plastic debris into the ocean associated with extreme storm events.

The Influence of Reef Topography on Storm-Driven Sand Flux

Natural formations of rock and coral can support geologically controlled beaches, where the beach dynamics are significantly influenced by these structures. However, little is known about how alongshore variations in geological controls influence beach morphodynamics. Therefore, in this study we focus on the storm response of a beach (Yanchep in south Western Australia) that has strong alongshore variation in the level of geological control because of the heterogeneous calcarenite limestone reef. We used a modified version of XBeach to simulate the beach morphodynamics during a significant winter storm event. We find that the longshore variation in topography of the reef resulted in: (1) strong spatial difference in current distribution, including areas with strong currents jets; and (2) significant alongshore differences in sand flux, with larger fluxes in areas strongly geologically controlled by reefs. In particular, this resulted in enhanced beach erosion at the boundary of the reef where strong currents jet-exited the nearshore.

Sensitivity of Storm Response to Antecedent Topography in the XBeach Model

Antecedent topography is an important aspect of coastal morphology when studying and forecasting coastal change hazards. The uncertainty in morphologic response of storm-impact models and their use in short-term hazard forecasting and decadal forecasting is important to account for when considering a coupled model framework. This study provided a methodology to investigate uncertainty of profile response within the storm impact model XBeach related to varying antecedent topographies. A parameterized island Gaussian fit (PIGF) model generated an idealized baseline profile and a suite of idealized profiles that vary specific characteristics based on collated observed LiDAR data from Dauphin Island, AL, USA. Six synthetic storm scenarios were simulated on each of the idealized profiles with XBeach in both 1- and 2-dimensional setups and analyzed to determine the morphological response and uncertainty related to the varied antecedent topographies. Profile morphologic response tends to scale with storm magnitude but among the varied profiles there is greater uncertainty in profile response to the medium range storm scenarios than to the low and high magnitude storm scenarios. XBeach can be highly sensitive to morphologic thresholds, both antecedent and time-varying, especially with regards to beach slope.

Panic makes you more susceptible to covid-19 (Preprint)

UNSTRUCTURED COVID-19 is the official name describing the coronavirus disease causing by the virus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). Its higher infection rate has led to worldwide spread making it a more dangerous threat than other coronavirus related diseases. As this virus spreads and responses from governments become more constraining of normal activities, we are seeing levels of anxiety among people increase over a relatively short period of time. When we are stressed the immune system’s ability to defend us from infections is reduced. Stress can suppress the innate immune system that provides the initial defence against viral infection making us more susceptible to Covid-19. In contrast, stress can cause overactivity of the adaptive immune system making a cytokine storm response leading to severe disease and death more likely. Management of stress levels has become an important strategy to reduce the risks of COVID-19.

Differences in the Effects of Storms on Dissolved Organic Carbon (DOC) in Boreal Lakes during an Early Summer Storm and an Autumn Storm

In boreal lakes, increased precipitation events have been linked to increased concentrations of dissolved organic carbon (DOC), however the effects of seasonal differences on DOC and how this may impact storm response remain unclear. We evaluated DOC concentration and a set of DOC quality metrics during an early summer storm and an autumn storm on a suite of six lakes in Acadia National Park in Maine, USA. to better understand differences in seasonal storm responses. Our results revealed differences in the response of DOC quality metrics to an early summer versus an autumn storm, with changes in DOC quality metrics varying by storm and lake features. During the early summer storm, we observed greater changes in various DOC quality metrics in deep lakes with longer residence times, whereas during the autumn storm, lakes with large watershed area to lake area ratios experienced the greatest changes. Land cover was highly correlated with changing DOC quality metrics in the early summer storm but did not play a significant role in the autumn storm response. Our research provides evidence of seasonal differences in the effects of storms on boreal lakes, which are ultimately mediated by a combination of lake and watershed characteristics as well as seasonal differences in climate such as solar radiation and antecedent weather conditions.

SURROGATE MODELING OF STORM RESPONSE

Surrogate models are yielding simple, fast and accurate storm response predictions. Surrogate modelling is being applied to compute regional response or compute thousands of realizations in seconds. These tools are useful for forecasting, scenario analysis and risk assessments. Approaches used for coastal application include artificial neural networks (ANN), Gaussian process regression (Kriging), and response surface techniques (e.g. Kim et al. 2015, Jia et al. 2013,). These previous approaches were limited to hurricane suites that were already optimally preconfigured using joint probability methods. The results were surprisingly effective in large part because the simulation suites were already optimized and the high dimensional parameter space was well correlated in time and space. The kriging method was applied for the study reported here to: 1) Optimize the parameter space and resulting selection of storms for high fidelity modelling, and 2) Construct surrogate models for both extratropical and tropical storm suites and for wave transformation as well as hurricane surge and other hurricane responses. The results were used for forecasting, scenario analysis, and risk assessments.