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The potential impact of rising sea levels and subsidence on coastal flooding along the northern coast of Saint-Louis, Senegal.

Abstract In today's context of rising sea levels and subsiding land topography, coastal flooding is a major concern for coastal areas, both nationally, regionally, and internationally. The main objective of the present study is to contribute to the understanding of the impact of subsidence and sea-level rise on coastal flooding in Saint-Louis, and in particular the Langue de Barbarie, by producing a vulnerability map of submerged surfaces. To this end, the Synthetic Aperture Radar (SAR) interferometry technique is used to process a time series of Sentinel-1 images and estimate land subsidence in the Saint-Louis and Langue de Barbarie area. Interferometric SAR (InSAR) measurements are merged with RCP 2.6 sea-level rise scenarios to identify predicted flooded areas and provide a flood vulnerability map. At the Langue de Barbarie, topographic subsidence is estimated at between -6.4 and -0.4mm/year. In this study, we show that local land subsidence may increase vulnerability to flooding caused by sea-level rise based on 2100 projections. This may represent an increase in the flood zone in the study area. Based on the RCP 2.6 scenario and the subsidence rates obtained, a significant part of the St. Louis coastline and city would be subject to coastal and fluvial flooding for the years 2040 and 2100. For these dates, 29 to and 36 Km2 of the studied area would be occupied by water. Given this situation, research in Saint-Louis needs to focus on adaptation scenarios to coastal risks, to protect coastal communities and safeguard the city's historical heritage.

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The Surface Water and Ocean Topography Mission (SWOT) Prior Lake Database (PLD): Lake mask and operational auxiliaries

Lakes are the most prevalent and predominant water repositories on land surface. A primary objective of the Surface Water and Ocean Topography (SWOT) satellite mission is to monitor the surface water elevation, area, and storage change in Earth’s lakes. To meet this objective, prior information of global lakes, such as locations and benchmark extents, is required to organize SWOT’s KaRIn observations over time for computing lake storage variation. Here, we present the SWOT mission Prior Lake Database (PLD) to fulfill this requirement. This paper emphasizes the development of the “operational PLD”, which consists of (1) a high-resolution mask of ~6 million lakes and reservoirs with a minimum area of 1 ha, and (2) multiple operational auxiliaries to assist the lake mask in generating SWOT’s standard vector lake products. We built the prior lake mask by harmonizing the UCLA Circa-2015 Global Lake Dataset and several state-of-the-art reservoir databases. Operational auxiliaries were produced from multi-theme geospatial data to provide information necessary to embody the PLD function, including lake catchments and influence areas, ice phenology, relationship with SWOT-visible rivers, and spatiotemporal coverage by SWOT overpasses. Globally, over three quarters of the prior lakes are smaller than 10 ha. Nearly 96% of the lakes, constituting over half of the global lake area, are fully observed at least once per orbit cycle. The PLD will be recursively improved during the mission period and serves as a critical framework for organizing, processing, and interpreting SWOT observations over lacustrine environments with fundamental significance to lake system science.

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Virtual coastal altimetry tide gauges along the West African coast

Low-lying coastal regions are generally vulnerable to climate change, and particularly to sea level variations. Understanding how these variations affect the coastal population requires an access to sea level measurements. Good quality in-situ sea level data are seldom available, with most long, research quality data in Europe and North America. In contrast, satellite altimetry provides more than three decades of near-global, continuous and freely available sea level measurements. Thanks to recent advances in processing and instruments, these observations have now become reliable to a few kilometers from the coast. In this study, using the available in-situ tide gauge data as a reference, we explore the ability of the recent X-TRACK/ALES high-resolution coastal altimeter product to derive the ocean tide and the long-term sea level changes along the West African coast. This region was chosen because it is under-sampled in terms of in-situ observations and would benefit greatly from the availability of freely accessible satellite data sets. To select the altimetry observations closest to the coast, we first define virtual tide gauges as close as possible to the intersection between each satellite track and the land. Sea level anomalies derived from the virtual stations were observed to be similar to those from the corresponding tide gauge stations: correlation values are between 0.58 and 0.78, root mean square differences between 5.6 and 8.3 cm. The virtual stations reproduce the observed tide with errors less or equal to 6.5 cm (i.e. 5.8% or less than the sea level variations of the tide). We show that part of the differences in tides between the two datasets is explained by differences in position between tide gauges and virtual stations. The combined analysis of sea level trends derived from tide gauges and from virtual stations shows how it is an efficient strategy to correct their respective errors and progress towards increasingly accurate sea level trend estimates in a region with little or no research-quality tide gauge data suitable for long-term sea level studies. The conclusion from this study is that in coastal regions poorly covered by tide gauges, our altimetry-based approach can be used to study and monitor sea-level variations related to tides or to long-term sea level changes.

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Revisiting the Global Energy Budget Dynamics with a Multivariate Earth Energy Balance Model to Account for the Warming Pattern Effect

Abstract Climate feedbacks are sensitive to the geographical distribution of sea surface temperature (SST). This sensitivity, called the pattern effect, affects the amplitude of the Earth radiative response to anomalies in global mean surface temperature (GMST) and thus is essential in shaping the global energy budget dynamics. Zero-dimensional energy balance models (EBMs) are the simplest representation of the global energy budget dynamics. Many only depend on GMST anomalies and cannot account for the pattern effect explicitly. In EBMs, the pattern effect leads to apparent variations of the global climate feedback parameter λ. Assuming a variable λ in EBMs enables them to more accurately reproduce AOGCM simulations of the GMST anomalies but it leads to variations in λ of >+15%. These large variations mean λ is not a constant and the Taylor expansion underpinning EBMs’ formulation does not hold, casting doubts on the physical grounding of such EBMs. Here we propose a new EBM based on a multivariate linear Earth radiative response, which depends on both the GMST and the surface warming pattern. The resulting multilinear EBM accurately reproduces AOGCM simulations of anomalies in Earth radiative response and GMST under abrupt 4xCO2 forcing. When interpreted in terms of variable λ, the multivariate EBM leads to small variations in λ that are physically consistent with the underpinning Taylor expansion. We analyze with the multivariate framework the variations of the planetary heat uptake N as a function of the GMST and the pattern of warming through a 3D generalization of the Gregory plot. We show that the apparent nonlinear behavior of the radiative response of the Earth against GMST seen in classical monovariate EBMs (and in classical Gregory plots) can actually be explained by a bilinear dependance of the radiative response of the Earth on the GMST and the pattern of warming. The multivariate EBM further provides an explicit dependence of the global energy budget on the pattern of warming and on the climate state. It has important consequences on the expression of the climate sensitivity.

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Assessing seasonal and interannual changes in carbonate chemistry across two time-series sites in the North Western Mediterranean Sea

Sustained time-series measurements are crucial to understand changes in oceanic carbonate chemistry. In the North Western Mediterranean Sea, the temporal evolution of the carbonate system is here investigated based on two 10-year time-series (between January 2010 and December 2019) of monthly carbonate parameters measurements at two sampling sites in the Ligurian Sea (ANTARES and DYFAMED). At seasonal timescale, the seawater partial pressure of CO2 (pCO2) within the mixed layer is mostly driven by temperature at both sites, and biological processes as stated by the observed relationships between total inorganic carbon (CT), nitrate and temperature. This study suggests also that mixing and water masses advection could play a role in modulating the CT content. At decadal timescale, significant changes in ocean chemistry are observed with increasing trends in CT (+3.2 ± 0.9 µmol.kg−1.a−1 – ANTARES; +1.6 ± 0.8 µmol.kg−1.a−1 – DYFAMED), associated with increasing pCO2 trends and decreasing trends in pH. The magnitude of the increasing trend in CT at DYFAMED is consistent with the increase in atmospheric pCO2 and the anthropogenic carbon transport of water originating from the Atlantic Ocean, while the higher trends observed at the ANTARES site could be related to the hydrological variability induced by the variability of the Northern Current.

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