Disruptive Role of Vertical Land Motion in Future Assessments of Climate Change-Driven Sea Level Rise and Coastal Flooding Hazards in the Chesapeake Bay.

Inundation projections from Sea Level Rise (SLR), Vertical Land Motion (VLM) and storm surges for hurricane Isabel at climate scenarios namely Shared Socioeconomic Pathways (SSPs) 1-1.9, 1-2.6, 2-4.5, 3-7.0 and 5-8.5 at three-time scales (2030-2050-2100) at medium confidence, median values, likely ranges upper and lower (for three selected SSPs: see below) are provided. Additionally, inundated area from SLR, Subsidence at SSP 1-2.6 and 5-8.5 for likely ranges (upper and lower) at low confidence scenarios are provided. <br> Sentinel-1 and ALOS data from 2007-2020 are processed used WabInSAR algorithm. We use future SLR scenarios from the Sixth Assessment Report (AR6) following SSPs adopted by the IPCC for projection periods of 2030, 2050 till 2100, relative to a baseline of 1995-2014 with medium confidence and low confidence. <br> Anyone wishing to use this dataset should cite Sherpa et al. 2022 and contact Sonam Futi Sherpa at [e-mail] for any questions with details of their work, so that we may offer guidance in regards to the best usage of our produced inundation scenarios dataset. <br> Files/Folders in Dataset and Description of Files <br> There are 23 compressed files as listed below. SUB_INUN represents inundation from subsidence only, SLR_inundation represents inundation from only sea-level rise, SLR_SUB indicates inundation from both sea-level rise and subsidence, SLR_SUB_StormSurge represents inundation from sea level rise, subsidence and storm surge including either hurricane Isabel. “medium” represents medium confidence,“low” represents low confidence, “median” is 50th percentile, “upperbound” is 83th percentile, “lowerbound” is 17th percentile and “ssp” is shared socioeconomic pathways. <br> SUB_INUN SLR _inundation_medium_median_ssp119 SLR _inundation_medium_median_ssp370 SLR _inundation_medium_median_ssp585 SLR_StormSurge_Isabel_inundation_medium_median_ssp585 SLR_SUB_inundation_medium_median_ssp119 SLR_SUB_inundation_medium_median_ssp126 SLR_SUB_inundation_medium_median_ssp245 SLR_SUB_inundation_medium_median_ssp370 SLR_SUB_inundation_medium_median_ssp585 SLR_SUB_StormSurge_Isabel_inundation_medium_median_ssp585 SLR_SUB_inundation_medium_lowerbound_ssp119 SLR_SUB_inundation_medium_lowerbound_ssp370 SLR_SUB_inundation_medium_lowerbound_ssp585 SLR_SUB_StormSurge_Isabel_inundation_lowerbound_median_ssp585 SLR_SUB_inundation_medium_upperbound_ssp119 SLR_SUB_inundation_medium_upperbound_ssp370 SLR_SUB_inundation_medium_upperbound_ssp585 SLR_SUB_StormSurge_Isabel_inundation_upperbound_median_ssp585 SLR_SUB_inundation_low_lowerbound_ssp126 SLR_SUB_inundation_low_lowerbound_ssp585 SLR_SUB_inundation_low_upperbound_ssp126 SLR_SUB_inundation_low_upperbound_ssp585 Each folder consists of three CSV files for three time periods 2030,2050, 2100 and respective png images and Matlab file to plot the dataset. <br> For example, in a folder "SLR_SUB_inundation_medium_median_ssp119", it consists of following: SLR_SUB_Inundation_Map_SSP119_2030.csv (for e.g.) column #1: longitude(deg), column #2: Latitude(deg) : Locations of the inundation area for 2030 in SSP 119 while considering both sea level rise (SLR) and Subsidence (SUB). CB_inundation_plot.m: MATLAB script to plot the dataset SLR_SUB_Inundation_Map_SSP119_2030.png <br> This is available for all SSPs at medium confidence, median values and likely ranges for selected SSPs at low confidence (see above). <br> <strong>Cite this as: </strong> Sherpa, S. F., Shirzaei, M., &amp; Ojha, C. (2022, Under review). Disruptive Role of Vertical Land Motion in Future Assessments of Climate Change-Driven Sea Level Rise and Coastal Flooding Hazards in the Chesapeake Bay. <em>Earth's Future.</em> <br> <br> Also see citations below for details. Blackwell, E., Shirzaei, M., Ojha, C., &amp; Werth, S. (2020). Tracking California’s sinking coast from space: Implications for relative sea-level rise. Science Advances. https://doi.org/10.1126/sciadv.aba4551 Fox-Kemper, B., Hewitt, H. T., Aðalgeirsdóttir, G., Drijfhout, S. S., Edwards, T. L., Golledge, N. R., et al. (2021). Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change e [MassonDelmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press. In Press. Garner, G. G., Hermans, T., Kopp, R. E., Slangen, A. B. A., Edwards, T. L., Levermann, S., et al. (2021). IPCC AR6 Sea-Level Rise Projections. Version 20210809. PO.DAAC, CA, USA. Garner, G. G., Kopp, R. E., Hermans, T., Slangen, A. B. A., Koubbe, M., Turilli, M., et al. (In prep). Framework for Assessing Changes To Sea-level (FACTS). Geoscientific Model Development. Sherpa, S. F., Shirzaei, M., &amp; Ojha, C. (2022, April 26). Disruptive Role of Vertical Land Motion in Future Assessments of Climate Change-Driven Sea Level Rise and Coastal Flooding Hazards in the Chesapeake Bay. Earth and Space Science Open Archive. https://doi.org/10.1002/essoar.10511192.1 Shirzaei, M. (2013). A Wavelet-Based Multitemporal DInSAR Algorithm for Monitoring Ground Surface Motion. IEEE Geoscience and Remote Sensing Letters, 10(3), 456–460. https://doi.org/10.1109/LGRS.2012.2208935 Shirzaei, M., &amp; Bürgmann, R. (2012). Topography correlated atmospheric delay correction in radar interferometry using wavelet transforms. Geophysical Research Letters, 39(1). https://doi.org/10.1029/2011GL049971 Shirzaei, M., Bürgmann, R., &amp; Fielding, E. J. (2017). Applicability of Sentinel-1 Terrain Observation by Progressive Scans multitemporal interferometry for monitoring slow ground motions in the San Francisco Bay Area. Geophysical Research Letters, 44(6), 2733–2742. https://doi.org/10.1002/2017GL072663 Shirzaei, M., &amp; Bürgmann, R. (2018). Global climate change and local land subsidence exacerbate inundation risk to the San Francisco Bay Area. Science Advances, 4(3), eaap9234. https://doi.org/10.1126/sciadv.aap9234 Miller, M. M., &amp; Shirzaei, M. (2021). Assessment of future flood hazards for southeastern Texas: Synthesizing subsidence, sea‐level rise, and storm surge scenarios. Geophysical Research Letters, 48(8), e2021GL092544. Anyone wishing to use this dataset should cite Sherpa et al. 2022) and contact Sonam Futi Sherpa at [e-mail] for any questions with details of their work, so that we may offer guidance in regards to the best usage of our produced inundation scenarios dataset. <br>