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Abstract Storm surge has the potential to significantly increase suspended sediment flux to microtidal marshes. However, the overall effects of storm surge on microtidal marsh deposition have not been well quantified, with most modeling studies focusing on regular (astronomical) tidal flooding. Here we applied the Delft3D model to a microtidal bay‐marsh complex in Hog Bay, Virginia to quantify the contributions of storm surge to marsh deposition. We validated the model using spatially distributed hydrodynamic and suspended sediment data collected from the site and ran model simulations under different storm surge conditions with/without storm‐driven water level changes. Our results show that episodic storm surge events occurred 5% of the time at our study site, but contributed 40% of marsh deposition during 2009–2020. Our simulations illustrate that while wind‐driven waves control sediment resuspension on tidal flats, marsh deposition during storms was largely determined by tidal inundation associated with storm‐driven water levels. A moderate storm surge event can double sediment flux to most marshes around the bay and deliver more sediment to the marsh interior compared to simulations that include wind waves but not storm surge variations in water levels. Simulations of bay and marsh response to different storm surge events with varying magnitude of storm surge intensity reveal that total marsh deposition around the bay increased linearly with storm surge intensity, suggesting that future changes to storm magnitude and/or frequency would have significant implications for sediment supply to marshes at our study site.
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NEER Preliminary Data Report : Winter Storm January 2022
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Abstract We perform the first global analysis of the spatial footprints of storm surges, using observed and simulated storm surge data. Three different techniques are applied to quantify the spatial footprints: clustering analysis, percentage of co‐occurrence, and joint probability analysis. The capability of the simulated data to represent the observed storm surge footprints is demonstrated. Results lead to the identification of coastline stretches prone to be impacted simultaneously by the same storm surge events. The spatial footprint sizes differ around the globe, partially conditioned by the geography of the coastline, that is, more irregular coastlines consist of a larger number of different storm surge clusters with varying footprint sizes. For the northwestern Atlantic, spatial footprints of storm surges vary when specifically accounting for tropical cyclones, using storm track information in the storm surge simulations. Our results provide important new insights into the spatial footprints of storm surges at the global scale and will help to facilitate improvements in how coastal flood risk is identified, assessed, and managed, by taking these spatial features into account.more » « less
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Abstract. Assessments of water balance changes, watershed response, and landscapeevolution to climate change require representation of spatially andtemporally varying rainfall fields over a drainage basin, as well as theflexibility to simply modify key driving climate variables (evaporativedemand, overall wetness, storminess). An empirical–stochastic approach to theproblem of rainstorm simulation enables statistical realism and the creationof multiple ensembles that allow for statistical characterization and/or timeseries of the driving rainfall over a fine grid for any climate scenario.Here, we provide details on the STOchastic Rainfall Model (STORM), which usesthis approach to simulate drainage basin rainfall. STORM simulates individualstorms based on Monte Carlo selection from probability density functions(PDFs) of storm area, storm duration, storm intensity at the core, and stormcenter location. The model accounts for seasonality, orography, and theprobability of storm intensity for a given storm duration. STORM alsogenerates time series of potential evapotranspiration (PET), which arerequired for most physically based applications. We explain how the modelworks and demonstrate its ability to simulate observed historical rainfallcharacteristics for a small watershed in southeast Arizona. We explain the datarequirements for STORM and its flexibility for simulating rainfall forvarious classes of climate change. Finally, we discuss several potentialapplications of STORM.more » « less
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Hurricanes can alter the rates and trajectories of biogeochemical cycling in coastal wetlands. Defoliation and vegetation death can lead to increased soil temperatures, and storm surge can variously cause erosion or deposition of sediment leading to changes in soil bulk density, nutrient composition, and redox characteristics. The objective of this study was to compare the biogeochemistry of pre-storm soils and a carbonate-rich sediment layer deposited by Hurricane Irma that made landfall in southwest Florida as a category 3 storm in September 2017. We predicted that indicators of biogeochemical activity (e.g., potential soil respiration rates, microbial biomass (MBC), and extracellular enzyme activities) would be lower in the storm sediment layer because of its lower organic matter content relative to pre-storm soils. There were few differences between the storm sediment and pre-storm soils at two of the sites closest to the Gulf of Mexico (GOM). This suggests that marine deposition regularly influences soil formation at these sites and is not something that occurs only during hurricanes. At a third site, 8 km from the GOM, the pre-storm soils had much greater concentrations of organic matter, total N, total P, MBC, and higher potential respiration rates than the storm layer. At this same site, CO2 fluxes from intact soil cores containing a layer of storm sediment were 30% lower than those without it. This suggests that sediment deposition from storm surge has the potential to preserve historically sequestered carbon in coastal soils through reduced respiratory losses.more » « less
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Abstract We review observations of solar activity, geomagnetic variation, and auroral visibility for the extreme geomagnetic storm on 1872 February 4. The extreme storm (referred to here as the Chapman–Silverman storm) apparently originated from a complex active region of moderate area (≈ 500μsh) that was favorably situated near disk center (S19° E05°). There is circumstantial evidence for an eruption from this region at 9–10 UT on 1872 February 3, based on the location, complexity, and evolution of the region, and on reports of prominence activations, which yields a plausible transit time of ≈29 hr to Earth. Magnetograms show that the storm began with a sudden commencement at ≈14:27 UT and allow a minimum Dst estimate of ≤ −834 nT. Overhead aurorae were credibly reported at Jacobabad (British India) and Shanghai (China), both at 19.°9 in magnetic latitude (MLAT) and 24.°2 in invariant latitude (ILAT). Auroral visibility was reported from 13 locations with MLAT below ∣20∣° for the 1872 storm (ranging from ∣10.°0∣–∣19.°9∣ MLAT) versus one each for the 1859 storm (∣17.°3∣ MLAT) and the 1921 storm (∣16.°2∣ MLAT). The auroral extension and conservative storm intensity indicate a magnetic storm of comparable strength to the extreme storms of 1859 September (25.°1 ± 0.°5 ILAT and −949 ± 31 nT) and 1921 May (27.°1 ILAT and −907 ± 132 nT), which places the 1872 storm among the three largest magnetic storms yet observed.more » « less
