Tropical to extratropical : marine environmental changes associated with Superstorm Sandy prior to its landfall

Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 41 (2014): 8935–8943, doi:10.1002/2014GL061357.Superstorm Sandy was a massive storm that impacted the U.S. East Coast on 22–31 October 2012, generating large waves, record storm surges, and major damage. The Coupled Ocean-Atmosphere-Wave-Sediment Transport modeling system was applied to hindcast this storm. Sensitivity experiments with increasing complexity of air-sea-wave coupling were used to depict characteristics of this immense storm as it underwent tropical to extratropical transition. Regardless of coupling complexity, model-simulated tracks were all similar to the observations, suggesting the storm track was largely determined by large-scale synoptic atmospheric circulation, rather than by local processes resolved through model coupling. Analyses of the sea surface temperature, ocean heat content, and upper atmospheric shear parameters showed that as a result of the extratropical transition and despite the storm encountering much cooler shelf water, its intensity and strength were not significantly impacted. Ocean coupling was not as important as originally thought for Sandy.Research support provided by USGS Coastal Process Project, NOAA grant NA11NOS0120033, and NASA grant NNX13AD80G is much appreciated.2015-06-1

Impact of SST and surface waves on Hurricane Florence (2018): a coupled modeling investigation

Author Posting. © American Meteorological Society , 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Zambon, J. B., He, R., Warner, J. C., & Hegermiller, C. A. Impact of SST and surface waves on Hurricane Florence (2018): a coupled modeling investigation. Weather and Forecasting, 36(5), (2021): 1713–1734, https://doi.org/10.1175/WAF-D-20-0171.1.Hurricane Florence (2018) devastated the coastal communities of the Carolinas through heavy rainfall that resulted in massive flooding. Florence was characterized by an abrupt reduction in intensity (Saffir–Simpson category 4 to category 1) just prior to landfall and synoptic-scale interactions that stalled the storm over the Carolinas for several days. We conducted a series of numerical modeling experiments in coupled and uncoupled configurations to examine the impact of sea surface temperature (SST) and ocean waves on storm characteristics. In addition to experiments using a fully coupled atmosphere–ocean–wave model, we introduced the capability of the atmospheric model to modulate wind stress and surface fluxes by ocean waves through data from an uncoupled wave model. We examined these experiments by comparing track, intensity, strength, SST, storm structure, wave height, surface roughness, heat fluxes, and precipitation in order to determine the impacts of resolving ocean conditions with varying degrees of coupling. We found differences in the storm’s intensity and strength, with the best correlation coefficient of intensity (r = 0.89) and strength (r = 0.95) coming from the fully coupled simulations. Further analysis into surface roughness parameterizations added to the atmospheric model revealed differences in the spatial distribution and magnitude of the largest roughness lengths. Adding ocean and wave features to the model further modified the fluxes due to more realistic cooling beneath the storm, which in turn modified the precipitation field. Our experiments highlight significant differences in how air–sea processes impact hurricane modeling. The storm characteristics of track, intensity, strength, and precipitation at landfall are crucial to predictability and forecasting of future landfalling hurricanes.This work has been supported by the U.S. Geological Survey Coastal/Marine Hazards and Resources Program, and by Congressional appropriations through the Additional Supplemental Appropriations for Disaster Relief Act of 2019 (H.R. 2157). The authors also wish to acknowledge research support through NSF Grant OCE-1559178 and NOAA Grant NA16NOS0120028. We also wish to thank Chris Sherwood from the U.S. Geological Survey for his help in deriving wave length from WAVEWATCH III data

Ocean–atmosphere dynamics during Hurricane Ida and Nor’Ida : an application of the coupled ocean–atmosphere–wave–sediment transport (COAWST) modeling system

This paper is not subject to U.S. copyright. The definitive version was published in Ocean Modelling 43-44 (2012): 112–137, doi:10.1016/j.ocemod.2011.12.008.The coupled ocean–atmosphere–wave–sediment transport (COAWST) modeling system was used to investigate atmosphere–ocean–wave interactions in November 2009 during Hurricane Ida and its subsequent evolution to Nor’Ida, which was one of the most costly storm systems of the past two decades. One interesting aspect of this event is that it included two unique atmospheric extreme conditions, a hurricane and a nor’easter storm, which developed in regions with different oceanographic characteristics. Our modeled results were compared with several data sources, including GOES satellite infrared data, JASON-1 and JASON-2 altimeter data, CODAR measurements, and wave and tidal information from the National Data Buoy Center (NDBC) and the National Tidal Database. By performing a series of numerical runs, we were able to isolate the effect of the interaction terms between the atmosphere (modeled with Weather Research and Forecasting, the WRF model), the ocean (modeled with Regional Ocean Modeling System (ROMS)), and the wave propagation and generation model (modeled with Simulating Waves Nearshore (SWAN)). Special attention was given to the role of the ocean surface roughness. Three different ocean roughness closure models were analyzed: DGHQ (which is based on wave age), TY2001 (which is based on wave steepness), and OOST (which considers both the effects of wave age and steepness). Including the ocean roughness in the atmospheric module improved the wind intensity estimation and therefore also the wind waves, surface currents, and storm surge amplitude. For example, during the passage of Hurricane Ida through the Gulf of Mexico, the wind speeds were reduced due to wave-induced ocean roughness, resulting in better agreement with the measured winds. During Nor’Ida, including the wave-induced surface roughness changed the form and dimension of the main low pressure cell, affecting the intensity and direction of the winds. The combined wave age- and wave steepness-based parameterization (OOST) provided the best results for wind and wave growth prediction. However, the best agreement between the measured (CODAR) and computed surface currents and storm surge values was obtained with the wave steepness-based roughness parameterization (TY2001), although the differences obtained with respect to DGHQ were not significant. The influence of sea surface temperature (SST) fields on the atmospheric boundary layer dynamics was examined; in particular, we evaluated how the SST affects wind wave generation, surface currents and storm surges. The integrated hydrograph and integrated wave height, parameters that are highly correlated with the storm damage potential, were found to be highly sensitive to the ocean surface roughness parameterization.Primary funding for this study was furnished by the US Geological Survey, Coastal and Marine Geology Program, under the Carolinas Coastal Processes Project

Overview of the Processes driving Exchange At Cape Hatteras Program

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Seim, H., Savidge, D., Andres, M., Bane, J., Edwards, C., Gawarkiewicz, G., He, R., Todd, R., Muglia, M., Zambon, J., Han, L., & Mao, S. Overview of the Processes driving Exchange at Cape Hatteras Program. Oceanography, (2022), https://doi.org/10.5670/oceanog.2022.205.The Processes driving Exchange At Cape Hatteras (PEACH) program seeks to better understand seawater exchanges between the continental shelf and the open ocean near Cape Hatteras, North Carolina. This location is where the Gulf Stream transitions from a boundary-trapped current to a free jet, and where robust along-shelf convergence brings cool, relatively fresh Middle Atlantic Bight and warm, salty South Atlantic Bight shelf waters together, forming an important and dynamic biogeographic boundary. The magnitude of this convergence implies large export of shelf water to the open ocean here. Background on the oceanography of the region provides motivation for the study and gives context for the measurements that were made. Science questions focus on the roles that wind forcing, Gulf Stream forcing, and lateral density gradients play in driving exchange. PEACH observational efforts include a variety of fixed and mobile observing platforms, and PEACH modeling included two different resolutions and data assimilation schemes. Findings to date on mean circulation, the nature of export from the southern Middle Atlantic Bight shelf, Gulf Stream variability, and position variability of the Hatteras Front are summarized, together with a look ahead to forthcoming analyses.We gratefully acknowledge NSF funding (OCE-1558920 to UNC-CH, OCE-1559476 to SkIO, OCE-1558521 to WHOI, OCE-1559178 to NCSU); technical support from Sara Haines, Craig Marquette, Trip Patterson, Nick DeSimone, Erran Sousa, Gabe Matthias, Patrick Deane, Brian Hogue, Frank Bahr, and Ben Hefner; cruise participants Jacob Forsyth, Joleen Heiderich, Chuxuan Li, Marco Valero, Lauren Ball, John McCord, and Kyle Maddux-Lawrence; and the crew of R/V Armstrong for their able support during three PEACH cruises

Development of a Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) Modeling System

This paper is not subject to U.S. copyright. The definitive version was published in Ocean Modelling 35 (2010): 230-244, doi:10.1016/j.ocemod.2010.07.010.Understanding the processes responsible for coastal change is important for managing our coastal resources, both natural and economic. The current scientific understanding of coastal sediment transport and geology suggests that examining coastal processes at regional scales can lead to significant insight into how the coastal zone evolves. To better identify the significant processes affecting our coastlines and how those processes create coastal change we developed a Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) Modeling System, which is comprised of the Model Coupling Toolkit to exchange data fields between the ocean model ROMS, the atmosphere model WRF, the wave model SWAN, and the sediment capabilities of the Community Sediment Transport Model. This formulation builds upon previous developments by coupling the atmospheric model to the ocean and wave models, providing one-way grid refinement in the ocean model, one-way grid refinement in the wave model, and coupling on refined levels. Herein we describe the modeling components and the data fields exchanged. The modeling system is used to identify model sensitivity by exchanging prognostic variable fields between different model components during an application to simulate Hurricane Isabel during September 2003. Results identify that hurricane intensity is extremely sensitive to sea surface temperature. Intensity is reduced when coupled to the ocean model although the coupling provides a more realistic simulation of the sea surface temperature. Coupling of the ocean to the atmosphere also results in decreased boundary layer stress and coupling of the waves to the atmosphere results in increased bottom stress. Wave results are sensitive to both ocean and atmospheric coupling due to wave–current interactions with the ocean and wave growth from the atmosphere wind stress. Sediment resuspension at regional scale during the hurricane is controlled by shelf width and wave propagation during hurricane approach

Efficient Passive ICS Device Discovery and Identification by MAC Address Correlation

Owing to a growing number of attacks, the assessment of Industrial Control Systems (ICSs) has gained in importance. An integral part of an assessment is the creation of a detailed inventory of all connected devices, enabling vulnerability evaluations. For this purpose, scans of networks are crucial. Active scanning, which generates irregular traffic, is a method to get an overview of connected and active devices. Since such additional traffic may lead to an unexpected behavior of devices, active scanning methods should be avoided in critical infrastructure networks. In such cases, passive network monitoring offers an alternative, which is often used in conjunction with complex deep-packet inspection techniques. There are very few publications on lightweight passive scanning methodologies for industrial networks. In this paper, we propose a lightweight passive network monitoring technique using an efficient Media Access Control (MAC) address-based identification of industrial devices. Based on an incomplete set of known MAC address to device associations, the presented method can guess correct device and vendor information. Proving the feasibility of the method, an implementation is also introduced and evaluated regarding its efficiency. The feasibility of predicting a specific device/vendor combination is demonstrated by having similar devices in the database. In our ICS testbed, we reached a host discovery rate of 100% at an identification rate of more than 66%, outperforming the results of existing tools.Comment: http://dx.doi.org/10.14236/ewic/ICS2018.

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

Intraperitoneal drain placement and outcomes after elective colorectal surgery: international matched, prospective, cohort study

Despite current guidelines, intraperitoneal drain placement after elective colorectal surgery remains widespread. Drains were not associated with earlier detection of intraperitoneal collections, but were associated with prolonged hospital stay and increased risk of surgical-site infections.Background Many surgeons routinely place intraperitoneal drains after elective colorectal surgery. However, enhanced recovery after surgery guidelines recommend against their routine use owing to a lack of clear clinical benefit. This study aimed to describe international variation in intraperitoneal drain placement and the safety of this practice. Methods COMPASS (COMPlicAted intra-abdominal collectionS after colorectal Surgery) was a prospective, international, cohort study which enrolled consecutive adults undergoing elective colorectal surgery (February to March 2020). The primary outcome was the rate of intraperitoneal drain placement. Secondary outcomes included: rate and time to diagnosis of postoperative intraperitoneal collections; rate of surgical site infections (SSIs); time to discharge; and 30-day major postoperative complications (Clavien-Dindo grade at least III). After propensity score matching, multivariable logistic regression and Cox proportional hazards regression were used to estimate the independent association of the secondary outcomes with drain placement. Results Overall, 1805 patients from 22 countries were included (798 women, 44.2 per cent; median age 67.0 years). The drain insertion rate was 51.9 per cent (937 patients). After matching, drains were not associated with reduced rates (odds ratio (OR) 1.33, 95 per cent c.i. 0.79 to 2.23; P = 0.287) or earlier detection (hazard ratio (HR) 0.87, 0.33 to 2.31; P = 0.780) of collections. Although not associated with worse major postoperative complications (OR 1.09, 0.68 to 1.75; P = 0.709), drains were associated with delayed hospital discharge (HR 0.58, 0.52 to 0.66; P < 0.001) and an increased risk of SSIs (OR 2.47, 1.50 to 4.05; P < 0.001). Conclusion Intraperitoneal drain placement after elective colorectal surgery is not associated with earlier detection of postoperative collections, but prolongs hospital stay and increases SSI risk