Articles | Volume 24, issue 7
https://doi.org/10.5194/nhess-24-2461-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-2461-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Jul 2024
Research article |
| 19 Jul 2024
| 19 Jul 2024
Estuarine hurricane wind can intensify surge-dominated extreme water level in shallow and converging coastal systems
Marine and Coastal Research Laboratory, Energy and Environment Directorate, Pacific Northwest National Laboratory, Sequim, WA 98382, USA
James J. Benedict
Los Alamos National Laboratory, Los Alamos, NM 87544, USA
Ning Sun
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA 99354, USA
Zhaoqing Yang
Marine and Coastal Research Laboratory, Energy and Environment Directorate, Pacific Northwest National Laboratory, Sequim, WA 98382, USA
Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
Robert D. Hetland
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA 99354, USA
David Judi
Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA 99354, USA
Taiping Wang
Marine and Coastal Research Laboratory, Energy and Environment Directorate, Pacific Northwest National Laboratory, Sequim, WA 98382, USA
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Cited articles
Balaguru, K., Xu, W., Chang, C.-C., Leung, L. R., Judi, D. R., Hagos, S. M., Wehner, M. F., Kossin, J. P., and Ting, M.: Increased U. S. coastal hurricane risk under climate change, Science Advances, 9, eadf0259, https://doi.org/10.1126/sciadv.adf0259, 2023. a
Bates, P. D., Quinn, N., Sampson, C., Smith, A., Wing, O., Sosa, J., Savage, J., Olcese, G., Neal, J., Schumann, G., Giustarini, L., Coxon, G., Porter, J. R., Amodeo, M. F., Chu, Z., Lewis-Gruss, S., Freeman, N. B., Houser, T., Delgado, M., Hamidi, A., Bolliger, I., E. McCusker, K., Emanuel, K., Ferreira, C. M., Khalid, A., Haigh, I. D., Couasnon, A., E. Kopp, R., Hsiang, S., and Krajewski, W. F.: Combined Modeling of US Fluvial, Pluvial, and Coastal Flood Hazard Under Current and Future Climates, Water Resour. Res., 57, e2020WR028673, https://doi.org/10.1029/2020WR028673, 2021. a
Bilskie, M. V., Hagen, S. C., Medeiros, S. C., Cox, A. T., Salisbury, M., and Coggin, D.: Data and numerical analysis of astronomic tides, wind-waves, and hurricane storm surge along the northern Gulf of Mexico, J. Geophys. Res.-Oceans, 121, 3625–3658, https://doi.org/10.1002/2015JC011400, 2016. a
Brown, B., Jensen, T., Gotway, J. H., Bullock, R., Gilleland, E., Fowler, T., Newman, K., Adriaansen, D., Blank, L., Burek, T., Harrold, M., Hertneky, T., Kalb, C., Kucera, P., Nance, L., Opatz, J., Vigh, J., and Wolff, J.: The Model Evaluation Tools (MET): More than a Decade of Community-Supported Forecast Verification, B. Am. Meteorol. Soc., 102, E782–E807, https://doi.org/10.1175/bams-d-19-0093.1, 2021. a
Callahan, J. A. and Leathers, D. J.: Estimation of Return Levels for Extreme Skew Surge Coastal Flooding Events in the Delaware and Chesapeake Bays for 1980–2019, Frontiers in Climate, 3, https://doi.org/10.3389/fclim.2021.684834, 2021. a
Cangialosi, J. P., Blake, E., DeMaria, M., Penny, A., Latto, A., Rappaport, E., and Tallapragada, V.: Recent Progress in Tropical Cyclone Intensity Forecasting at the National Hurricane Center, Weather Forecast., 35, 1913–1922, https://doi.org/10.1175/WAF-D-20-0059.1, 2020. a
Chen, C., Liu, H., and Beardsley, R. C.: An Unstructured Grid, Finite-Volume, Three-Dimensional, Primitive Equations Ocean Model: Application to Coastal Ocean and Estuaries, J. Atmos. Ocean. Tech., 20, 159–186, https://doi.org/10.1175/1520-0426(2003)020<0159:AUGFVT>2.0.CO;2, 2003. a, b
Chen, M., Shi, W., Xie, P., Silva, V. B. S., Kousky, V. E., Higgins, R. W., and Janowiak, J. E.: Assessing objective techniques for gauge-based analyses of global daily precipitation, J. Geophys. Res., 113, D04110, https://doi.org/10.1029/2007jd009132, 2008. a
Cyriac, R., Dietrich, J., Fleming, J., Blanton, B., Kaiser, C., Dawson, C., and Luettich, R.: Variability in Coastal Flooding predictions due to forecast errors during Hurricane Arthur, Coast. Eng., 137, 59–78, https://doi.org/10.1016/j.coastaleng.2018.02.008, 2018. a
Deb, M.: Estuarine hurricane wind and Delaware Bay and River extreme water level, Zenodo [data set], https://doi.org/10.5281/zenodo.7988098 2024. a
Deb, M., Sun, N., Yang, Z., Wang, T., Judi, D., Xiao, Z., and Wigmosta, M. S.: Interacting Effects of Watershed and Coastal Processes on the Evolution of Compound Flooding During Hurricane Irene, Earths Future, 11, e2022EF002947, https://doi.org/10.1029/2022EF002947, 2023. a
Defne, Z., Ganju, N. K., and Moriarty, J. M.: Hydrodynamic and Morphologic Response of a Back-Barrier Estuary to an Extratropical Storm, J. Geophys. Res.-Oceans, 124, 7700–7717, https://doi.org/10.1029/2019JC015238, 2019. a
Developmental Testbed Center: Model Evaluation Tools Tropical Cyclone (MET-TC), Computer Software, GitHub [code], https://github.com/dtcenter/MET (last access: 16 July 2024), 2024. a
Dietrich, J. C., Bunya, S., Westerink, J. J., Ebersole, B. A., Smith, J. M., Atkinson, J. H., Jensen, R., Resio, D. T., Luettich, R. A., Dawson, C., Cardone, V. J., Cox, A. T., Powell, M. D., Westerink, H. J., and Roberts, H. J.: A High-Resolution Coupled Riverine Flow, Tide, Wind, Wind Wave, and Storm Surge Model for Southern Louisiana and Mississippi. Part II: Synoptic Description and Analysis of Hurricanes Katrina and Rita, Mon. Weather Rev., 138, 378–404, https://doi.org/10.1175/2009MWR2907.1, 2010. a
Dietrich, J., Zijlema, M., Westerink, J., Holthuijsen, L., Dawson, C., Luettich, R., Jensen, R., Smith, J., Stelling, G., and Stone, G.: Modeling hurricane waves and storm surge using integrally-coupled, scalable computations, Coast. Eng., 58, 45–65, https://doi.org/10.1016/j.coastaleng.2010.08.001, 2011. a
Egbert, G. D. and Erofeeva, S. Y.: Efficient Inverse Modeling of Barotropic Ocean Tides, J. Atmos. Ocean. Tech., 19, 183–204, https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2, 2002. a
Emanuel, K.: Increasing destructiveness of tropical cyclones over the past 30 years, Nature, 436, 686–688, 2005. a
Emanuel, K.: Response of Global Tropical Cyclone Activity to Increasing CO2: Results from Downscaling CMIP6 Models, J. Climate, 34, 57–70, https://doi.org/10.1175/JCLI-D-20-0367.1, 2021. a, b
E3SM Project, DOE: Energy Exascale Earth System Model v3.0.0, Computer Software, E3SM Project, DOE [code], https://doi.org/10.11578/E3SM/dc.20240301.3, 2024. a
Familkhalili, R. and Talke, S. A.: The effect of channel deepening on tides and storm surge: A case study of Wilmington, NC, Geophys. Res. Lett., 43, 9138–9147, https://doi.org/10.1002/2016GL069494, 2016. a
Garner, A. J., Kopp, R. E., and Horton, B. P.: Evolving Tropical Cyclone Tracks in the North Atlantic in a Warming Climate, Earths Future, 9, e2021EF002326, https://doi.org/10.1029/2021EF002326, 2021. a
Glahn, B., Taylor, A., Kurkowski, N., and Shaffer, W.: The role of the SLOSH model in National Weather Service storm surge forecasting, National Weather Digest, 33, 3–14, 2009. a
Golaz, J.-C., Roekel, L. P. V., Zheng, X., Roberts, A. F., Wolfe, J. D., Lin, W., Bradley, A. M., Tang, Q., Maltrud, M. E., Forsyth, R. M., Zhang, C., Zhou, T., Zhang, K., Zender, C. S., Wu, M., Wang, H., Turner, A. K., Singh, B., Richter, J. H., Qin, Y., Petersen, M. R., Mametjanov, A., Ma, P.-L., Larson, V. E., Krishna, J., Keen, N. D., Jeffery, N., Hunke, E. C., Hannah, W. M., Guba, O., Griffin, B. M., Feng, Y., Engwirda, D., Vittorio, A. V. D., Dang, C., Conlon, L. M., Chen, C.-C.-J., Brunke, M. A., Bisht, G., Benedict, J. J., Asay-Davis, X. S., Zhang, Y., Zhang, M., Zeng, X., Xie, S., Wolfram, P. J., Vo, T., Veneziani, M., Tesfa, T. K., Sreepathi, S., Salinger, A. G., Eyre, J. E. J. R., Prather, M. J., Mahajan, S., Li, Q., Jones, P. W., Jacob, R. L., Huebler, G. W., Huang, X., Hillman, B. R., Harrop, B. E., Foucar, J. G., Fang, Y., Comeau, D. S., Caldwell, P. M., Bartoletti, T., Balaguru, K., Taylor, M. A., McCoy, R. B., Leung, L. R., and Bader, D. C.: The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation, J. Adv. Model. Earth Sy., 14, e2022MS003156, https://doi.org/10.1029/2022ms003156, 2022. a, b, c, d
Gori, A., Lin, N., Xi, D., and Emanuel, K.: Tropical cyclone climatology change greatly exacerbates US extreme rainfall–surge hazard, Nat. Clim. Change, 12, 171–178, 2022. a
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91, https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009. a
He, F. and Posselt, D. J.: Impact of Parameterized Physical Processes on Simulated Tropical Cyclone Characteristics in the Community Atmosphere Model, J. Climate, 28, 9857–9872, https://doi.org/10.1175/JCLI-D-15-0255.1, 2015. a, b, c, d
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2023. a
Hsu, C.-E., Serafin, K. A., Yu, X., Hegermiller, C. A., Warner, J. C., and Olabarrieta, M.: Total water levels along the South Atlantic Bight during three along-shelf propagating tropical cyclones: relative contributions of storm surge and wave runup, Nat. Hazards Earth Syst. Sci., 23, 3895–3912, https://doi.org/10.5194/nhess-23-3895-2023, 2023. a
Hu, K., Ding, P., Wang, Z., and Yang, S.: A 2D/3D hydrodynamic and sediment transport model for the Yangtze Estuary, China, J. Marine Syst., 77, 114–136, https://doi.org/10.1016/j.jmarsys.2008.11.014, 2009. a
Huang, B., Liu, C., Banzon, V., Freeman, E., Graham, G., Hankins, B., Smith, T., and Zhang, H.-M.: Improvements of the Daily Optimum Interpolation Sea Surface Temperature (DOISST) Version 2.1, J. Climate, 34, 2923–2939, https://doi.org/10.1175/JCLI-D-20-0166.1, 2021. a
Jelesnianski, C. P.: SLOSH: Sea, lake, and overland surges from hurricanes, vol. 48, US Department of Commerce, National Oceanic and Atmospheric Administration, https://repository.library.noaa.gov/view/noaa/7235 (last access: 16 July 2024), 1992. a
Knapp, K. R., Kruk, M. C., Levinson, D. H., Diamond, H. J., and Neumann, C. J.: The International Best Track Archive for Climate Stewardship (IBTrACS), B. Am. Meteorol. Soc., 91, 363–376, https://doi.org/10.1175/2009bams2755.1, 2010. a
Knapp, K. R., Diamond, H. J., Kossin, J. P., Kruk, M. C., and Schreck, C. J.: International Best Track Archive for Climate Stewardship (IBTrACS) Project, Version 4, B. Am. Meteorol. Soc., 91, 363–376, https://doi.org/10.1175/2009bams2755.1, 2018. a
Knutson, T. R., Sirutis, J. J., Bender, M. A., Tuleya, R. E., and Schenkel, B. A.: Dynamical downscaling projections of late twenty-first-century U. S. landfalling hurricane activity, Climatic Change, 171, 28, https://doi.org/10.1007/s10584-022-03346-7, 2022. a
Lin, N., Emanuel, K. A., Smith, J. A., and Vanmarcke, E.: Risk assessment of hurricane storm surge for New York City, J. Geophys. Res.-Atmos., 115, D18121, https://doi.org/10.1029/2009JD013630, 2010. a
Lin, N., Marsooli, R., and Colle, B. A.: Storm surge return levels induced by mid-to-late-twenty-first-century extratropical cyclones in the Northeastern United States, Climatic Change, 154, 143–158, 2019. a
Lyddon, C., Brown, J. M., Leonardi, N., and Plater, A. J.: Uncertainty in estuarine extreme water level predictions due to surge-tide interaction, PLOS ONE, 13, e0206200, https://doi.org/10.1371/journal.pone.0206200, 2018. a
Marsooli, R. and Lin, N.: Numerical Modeling of Historical Storm Tides and Waves and Their Interactions Along the U. S. East and Gulf Coasts, J. Geophys. Res.-Oceans, 123, 3844–3874, https://doi.org/10.1029/2017JC013434, 2018. a, b
Marsooli, R., Lin, N., Emanuel, K., and Feng, K.: Climate change exacerbates hurricane flood hazards along US Atlantic and Gulf Coasts in spatially varying patterns, Nat. Commun., 10, 3785, https://doi.org/10.1038/s41467-019-11755-z, 2019. a
MEDM Lab: UMass Dartmouth, The Finite Volume Coastal Ocean Model, Computer Software, GitHub [code], https://github.com/FVCOM-GitHub/FVCOM (last access: 16 July 2024), 2024. a
Mori, N., Kato, M., Kim, S., Mase, H., Shibutani, Y., Takemi, T., Tsuboki, K., and Yasuda, T.: Local amplification of storm surge by Super Typhoon Haiyan in Leyte Gulf, Geophys. Res. Lett., 41, 5106–5113, https://doi.org/10.1002/2014GL060689, 2014. a
National Ocean Service and National Oceanic and Atmospheric Administration: Water Levels, https://tidesandcurrents.noaa.gov/ (last access: 16 July 2024), 2024. a
NOAA: NOAA OI SST V2 High Resolution Dataset, NOAA [data set], https://www.psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html (last access: 16 July 2024), 2024. a
OSU TPXO: OSU TPXO Tide Models, https://www.tpxo.net/home (last access: 16 July 2024), 2024. a
Parker, K., Erikson, L., Thomas, J., Nederhoff, K., Barnard, P., and Muis, S.: Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water-level hindcast, Nat. Hazards, 117, 2219–2248, https://doi.org/10.1007/s11069-023-05939-6, 2023. a
Perkins, W. A., Duan, Z., Sun, N., Wigmosta, M. S., Richmond, M. C., Chen, X., and Leung, L. R.: Parallel Distributed Hydrology Soil Vegetation Model (DHSVM) using global arrays, Environ. Modell. Softw., 122, 104533, https://doi.org/10.1016/j.envsoft.2019.104533, 2019. a
PNNL: Distributed Hydrology Soil Vegetation Model, https://www.pnnl.gov/projects/distributed-hydrology-soil-vegetation-model (last access: 16 July 2024), 2024. a
Reed, K., Wehner, M. F., Stansfield, A. M., and Zarzycki, C. M.: Anthropogenic Influence on Hurricane Dorian's Extreme Rainfall, B. Am. Meteorol. Soc., 102, S9–S15, https://doi.org/10.1175/bams-d-20-0160.1, 2021. a
Reed, K. A., Stansfield, A. M., Wehner, M. F., and Zarzycki, C. M.: Forecasted attribution of the human influence on Hurricane Florence, Science Advances, 6, eaaw9253, https://doi.org/10.1126/sciadv.aaw9253, 2020. a, b, c, d
Rego, J. L. and Li, C.: On the importance of the forward speed of hurricanes in storm surge forecasting: A numerical study: Forward Speed Of A Hurricane, Geophys. Res. Lett., 36, L07609, https://doi.org/10.1029/2008GL036953, 2009. a
Resio, D. T. and Westerink, J. J.: Modeling the physics of storm surges, Phys. Today, 61, 33–38, https://doi.org/10.1063/1.2982120, 2008. a
Roberts, M. J., Camp, J., Seddon, J., Vidale, P. L., Hodges, K., Vannière, B., Mecking, J., Haarsma, R., Bellucci, A., Scoccimarro, E., Caron, L.-P., Chauvin, F., Terray, L., Valcke, S., Moine, M.-P., Putrasahan, D., Roberts, C. D., Senan, R., Zarzycki, C., Ullrich, P., Yamada, Y., Mizuta, R., Kodama, C., Fu, D., Zhang, Q., Danabasoglu, G., Rosenbloom, N., Wang, H., and Wu, L.: Projected Future Changes in Tropical Cyclones Using the CMIP6 HighResMIP Multimodel Ensemble, Geophys. Res. Lett., 47, e2020GL088662, https://doi.org/10.1029/2020GL088662, 2020. a
Shen, J., Gong, W., and Wang, H. V.: Water level response to 1999 Hurricane Floyd in the Chesapeake Bay, Cont. Shelf Res., 26, 2484–2502, https://doi.org/10.1016/j.csr.2006.07.021, 2006a. a, b, c
Shen, J., Wang, H., Sisson, M., and Gong, W.: Storm tide simulation in the Chesapeake Bay using an unstructured grid model, Estuar. Coast. Shelf S., 68, 1–16, https://doi.org/10.1016/j.ecss.2005.12.018, 2006b. a, b, c
Suh, S.-W. and Lee, H.-Y.: Forerunner storm surge under macro-tidal environmental conditions in shallow coastal zones of the Yellow Sea, Cont. Shelf Res., 169, 1–16, https://doi.org/10.1016/j.csr.2018.09.007, 2018. a, b
Sun, N., Yearsley, J., Voisin, N., and Lettenmaier, D. P.: A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds, Hydrol. Process., 29, 2331–2345, https://doi.org/10.1002/hyp.10363, 2015. a
Sun, N., Wigmosta, M. S., Yan, H., Eldardiry, H., Yang, Z., Deb, M., Wang, T., and Judi, D.: Amplified Extreme Floods and Shifting Flood Mechanisms in the Delaware River Basin in Future Climates, Earths Future, 12, e2023EF003868, https://doi.org/10.1029/2023EF003868, 2024. a
Taylor, A. A. and Glahn, B.: Probabilistic guidance for hurricane storm surge, in: 19th Conf. on Probability and Statistics, January 2008, New Orleans, LA, Amer. Meteor. Soc., https://ams.confex.com/ams/88Annual/techprogram/paper_132793.htm (last access: 16 July 2024), 2008. a
Ullrich, P.: ClimateGlobalChange/tempestextremes, GitHub [code], https://github.com/ClimateGlobalChange/tempestextremes (last access: 16 July 2024), 2024. a
Ullrich, P. A., Zarzycki, C. M., McClenny, E. E., Pinheiro, M. C., Stansfield, A. M., and Reed, K. A.: TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets, Geosci. Model Dev., 14, 5023–5048, https://doi.org/10.5194/gmd-14-5023-2021, 2021. a
Valle-Levinson, A., Olabarrieta, M., and Heilman, L.: Compound flooding in Houston-Galveston Bay during Hurricane Harvey, Sci. Total Environ., 747, 141272, https://doi.org/10.1016/j.scitotenv.2020.141272, 2020. a
Villarini, G., Goska, R., Smith, J. A., and Vecchi, G. A.: North Atlantic Tropical Cyclones and U. S. Flooding, B. Am. Meteorol. Soc., 95, 1381–1388, https://doi.org/10.1175/BAMS-D-13-00060.1, 2014. a
Wahl, T., Jain, S., Bender, J., Meyers, S. D., and Luther, M. E.: Increasing risk of compound flooding from storm surge and rainfall for major US cities, Nat. Clim. Change, 5, 1093–1097, 2015. a
Wang, S., McGrath, R., Hanafin, J., Lynch, P., Semmler, T., and Nolan, P.: The impact of climate change on storm surges over Irish waters, Ocean Model., 25, 83–94, https://doi.org/10.1016/j.ocemod.2008.06.009, 2008. a
Weaver, M. M. and Garner, A. J.: Varying genesis and landfall locations for North Atlantic tropical cyclones in a warmer climate, Scientific Reports, 13, 5482, https://doi.org/10.1038/s41598-023-31545-4, 2023. a
Weisberg, R. H. and Zheng, L.: Hurricane storm surge simulations comparing three-dimensional with two-dimensional formulations based on an Ivan-like storm over the Tampa Bay, Florida region, J. Geophys. Res.-Oceans, 113, C12001, https://doi.org/10.1029/2008JC005115, 2008. a, b, c, d
Wong, K.-C. and Moses-Hall, J. E.: On the relative importance of the remote and local wind effects to the subtidal variability in a coastal plain estuary, J. Geophys. Res.-Oceans, 103, 18393–18404, https://doi.org/10.1029/98JC01476, 1998. a
Wong, K.-C. and Trowbridge, J. H.: Some observational evidence on the effect of atmospheric forcing on tidal variability in the upper Delaware Bay, J. Geophys. Res., 95, 16229, https://doi.org/10.1029/JC095iC09p16229, 1990. a, b
Xiao, Z., Yang, Z., Wang, T., Sun, N., Wigmosta, M., and Judi, D.: Characterizing the Non-linear Interactions Between Tide, Storm Surge, and River Flow in the Delaware Bay Estuary, United States, Frontiers in Marine Science, 8, 1811332, https://doi.org/10.3389/fmars.2021.715557, 2021. a
Zarzycki, C. M.: Betacast, Computer Software, Zenodo [code], https://doi.org/10.5281/zenodo.6047091, 2023. a
Zarzycki, C. M. and Jablonowski, C.: Experimental Tropical Cyclone Forecasts Using a Variable-Resolution Global Model, Mon. Weather Rev., 143, 4012–4037, https://doi.org/10.1175/mwr-d-15-0159.1, 2015. a
Zarzycki, C. M., Thatcher, D. R., and Jablonowski, C.: Objective tropical cyclone extratropical transition detection in high-resolution reanalysis and climate model data, J. Adv. Model. Earth Sy., 9, 130–148, https://doi.org/10.1002/2016ms000775, 2017. a
Short summary
We coupled earth system, hydrology, and hydrodynamic models to generate plausible and physically consistent ensembles of hurricane events and their associated water levels from the open coast to tidal rivers of Delaware Bay and River. Our results show that the hurricane landfall locations and the estuarine wind can significantly amplify the extreme surge in a shallow and converging system, especially when the wind direction aligns with the surge propagation direction.
We coupled earth system, hydrology, and hydrodynamic models to generate plausible and physically...
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