Browsing by Author "Edwing, Deanna"
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Item Characterizing Delaware Bay coastal inundation using Sentinel-1 SAR imagery and deep learning(University of Delaware, 2023) Edwing, DeannaRegions around Delaware Bay are vulnerable to coastal flooding due to their flat topography, low mean elevations, and high land subsidence rates. This, combined with rising sea levels and increased storm activity under climate change conditions, is prompting questions about coastal flooding in a region which has historically been protected from frequent and intense storm activity. Therefore, this study aimed to characterize Delaware Bay coastal flooding from 2017-2021 using a neural network trained in water segmentation on Sentinel-1 SAR imagery. Identified flood waters were compared with ancillary geospatial and oceanographic data to determine land cover impacts and potential mechanisms behind the largest flooding events. A novel product is introduced to remove daily tidal inundation from flood maps, improving flood estimates in heavily tidally influenced regions. Results show that most flood events were less than 2 km2 per coastal county; however, larger events produced upwards of 10 km2. Case study analysis revealed that the largest flood events primarily arose from a combination of multi-day precipitation and high water levels. The dominant flooded land cover was primarily agricultural regions, except Cape May which was marsh-dominated most likely because of lower agricultural land cover density. This study provides a baseline understanding of Delaware Bay coastal flooding amidst a changing climate; therefore, this study has important implications for future flooding conditions.Item Quasi-Decadal Temperature Variability in the Intermediate Layer of Subtropical South Indian Ocean During the Argo Period(Journal of Geophysical Research: Oceans, 2023-07-28) Huang, Lei; Zhuang, Wei; Wu, Zelun; Zhang,Yang; Meng, Lingsheng; Edwing, Deanna; Yan, Xiao-HaiIt has been reported that the subtropical South Indian Ocean (SIO) has been rapidly warming over the past two decades and can therefore be characterized as one of the major heat accumulators among the oceanic basins. However, this strong warming is not uniformly distributed in the vertical direction. In comparison to the decade-long warming in the upper layer (0–300 m) in 2004–2013, the intermediate layer (300–1,000 m) displays a shorter warming during 2004–2009 and an intense cooling during 2010–2016. By decomposing temperature variations into heaving and spice components, and performing a heat budget analysis, we show that temperature variations in the intermediate layer during these two periods are primarily contributed by isopycnal migrations driven by local wind forcing. Local wind change in the subtropical SIO can be explained by the Indian Ocean Dipole and El Niño–Southern Oscillation during 2004–2016, while Southern Annular Mode (SAM) favors anomalous wind change in mid-latitudes and the formation of basin-wide wind change in the SIO. Additionally, wind forcing in the Subantarctic Mode Water (SAMW) formation region, which is closely linked to the SAM, modulates the anomalous spreading of SAMW into the interior of the subtropical SIO. This, therefore, leads to the SAMW intrusion being of secondary importance to the quasi-decadal temperature variability. Our findings demonstrate the independence of wind-driven temperature changes on the quasi-decadal scale in the intermediate layer of the subtropical SIO under the overall warming background of SIO waters. Key Points - Quasi-decadal temperature variations occur in the intermediate layer (300–1,000 m) of subtropical South Indian Ocean (SIO) - Local wind-driven heaving process is the major driver, spice component arising from the Subantarctic Mode Water intrusion is of secondary importance - The local wind change in the subtropical SIO can be well explained by the combined effects of El Niño–Southern Oscillation, Indian Ocean Dipole and Southern Annular Mode Plain Language Summary Compared to the decade-long warming in the upper layer of the South Indian Ocean (SIO), which has been studied extensively, our understanding of temperature change in the intermediate layer is relatively limited. This study reveals a quasi-decadal temperature cycle in the intermediate layer of the subtropical SIO during the Argo period, which is characterized by a shorter warming period during 2004–2009 and subsequent cooling during 2010–2016. Decomposition of temperature changes suggests that this quasi-decadal temperature variability is primarily driven by the heaving component, which is tightly associated with local wind variability driven by local and remote forcings, whereas the spice change largely contributed by the SAM-related water mass transmission from higher latitudes, is of secondary importance. Thus, this study expands our knowledge of temperature variability in the SIO and demonstrates that the quasi-decadal variability of intermediate layer temperatures in the subtropical SIO serves as a crucial archive for both global and local climate change.Item Rapid Sea Level Rise in the Tropical Southwest Indian Ocean in the Recent Two Decades(Geophysical Research Letters, 2023-12-27) Huang, Lei; Zhuang, Wei; Lu, Wenfang; Zhang, Yang; Edwing, Deanna; Yan, Xiao-HaiIt has been reported that the sea level falls in the tropical Southwest Indian Ocean (SWIO) from the 1960s to the early 2000s. However, a rising trend of 4.05 ± 0.56 cm/decade has occurred during the recent two decades with our analysis showing that manometric sea level contributes 41% to this sea level rise. 30% of this rise is due to steric sea level (SSL) change in the upper 2,000 m with SSL rise in the upper 300 m of secondary importance. Conversely, thermal expansion below the thermocline (300–2,000 m), likely caused by water mass spread from the Southern Ocean, induces major contribution to SSL changes. Compared to existing studies demonstrating the contribution of thermal variations above the thermocline to sea level variability in the tropical SWIO, this study emphasizes the importance of ocean mass and deeper ocean changes in a warming climate. Key Points - Rapid sea level rise occurs in the tropical Southwest Indian Ocean (SWIO) since the early 2000s - The ocean mass addition and the upper 2,000 m ocean warming contribute significantly to the total sea level rise - The upper 2,000 m ocean warming is primarily attributed to thermal expansion below the thermocline associated with the spread of water masses Plain Language Summary Global ocean sea level change is spatially and temporally nonuniform due to oceanic and atmospheric dynamics. The tropical Southwest Indian Ocean (SWIO) experienced a sea level fall from the 1960s to the early 2000s. However, a rapid sea level rise has occurred over the last two decades in the tropical SWIO that is faster than the global average. The ocean mass increase due to extra water input leads to an essential impact on sea level rise in the tropical SWIO. Compared to previous studies demonstrating the effect of thermal expansion in the upper 300 m, this study shows larger contributions from deeper ocean (300–2,000 m) warming over the past two decades. Overall, this study highlights the importance of ocean mass and deeper water thermal structure in regulating tropical SWIO sea level rise in a changing climate, as well as the need for observations and direct assessment of the abyssal ocean beneath 2,000 m.Item Retrieving Ocean Surface Winds and Waves from Augmented Dual-Polarization Sentinel-1 SAR Data Using Deep Convolutional Residual Networks(Atmosphere, 2023-08-11) Xue, Sihan; Meng, Lingsheng; Geng, Xupu; Sun, Haiyang; Edwing, Deanna; Yan, Xiao-HaiSea surface winds and waves are very important phenomena that exist in the air–sea boundary layer. With the advent of climate change, cascade effects are bringing more attention to these phenomena as warmer sea surface temperatures bring about stronger winds, thereby altering global wave conditions. Synthetic aperture radar (SAR) is a powerful sensor for high-resolution surface wind and wave observations and has accumulated large quantities of data. Furthermore, deep learning methods have been increasingly utilized in geoscience, especially the inversion of ocean information from SAR imagery. Here, we propose a method to invert various parameters of ocean surface winds and waves using Sentinel-1 SAR IW mode data. To ensure this method is more robust and scalable, we augmented the input data with dual-polarized SAR imagery, an incident angle, and a more constrained homogeneity test. This method adopts a deeper structure in order to retrieve more wind and wave parameters, and the use of residual networks can accelerate training convergence and improve regression accuracy. Using 1600 training samples filtered by a novel homogeneity test and with significant wave heights between 0 and 10 m, results from error parameters including the root mean square error (RMSE), scatter index (SI), and correlation coefficient (COR) show the great performance of this proposed method. The RMSE is 0.45 m, 0.76 s, and 1.90 m/s for the significant wave height, mean wave period, and wind speed, respectively. Furthermore, the temporal variation and spatial distribution of the estimates are consistent with China–France Oceanography Satellite (CFOSAT) observations, buoy measurements, WaveWatch3 regional model data, and ERA5 reanalysis data.