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  • 1
    Online Resource
    Online Resource
    Milton :Taylor & Francis Group,
    Keywords: Satellite geodesy-Technique. ; Electronic books.
    Description / Table of Contents: Satellite remote sensing, in particular by radar altimetry, is a crucial technique for observations of the ocean surface and of many aspects of land surfaces, and of paramount importance for climate and environmental studies. It provides a state-of-the-art overview of the satellite altimetry techniques and related missions.
    Type of Medium: Online Resource
    Pages: 1 online resource (645 pages)
    Edition: 1st ed.
    ISBN: 9781498743464
    Series Statement: Earth Observation of Global Changes Series
    DDC: 551.48
    Language: English
    Note: Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Editors -- Contributors -- Chapter 1: Satellite Radar AltimetryPrinciple, Accuracy, and Precision -- 1.1 Introduction -- 1.1.1 Satellite Altimetry Measurement Principle -- 1.1.2 Satellite Radar Altimetry Historical Perspective -- 1.1.2.1 Satellite Altimetry Missions -- 1.1.2.2 Geographical Perspective and International Cooperation -- 1.1.2.3 Altimetry Products: History of Continuous Progress -- 1.1.3 Altimetry System Requirements -- 1.2 Radar Instrument -- 1.2.1 Radar Altimeter Instrument Principles -- 1.2.2 Observation Geometry -- 1.2.3 Radar Operation -- 1.2.4 Transmitted Waveform -- 1.2.5 Instrument Architecture -- 1.2.6 Instrument Example: Poseidon-3 of Jason-2 Mission -- 1.2.6.1 Poseidon-3 Architecture -- 1.2.6.2 Poseidon-3 Main Characteristics -- 1.2.7 Key Instrument Performance -- 1.2.8 Echo Formation -- 1.3 Echo characterization and processing -- 1.3.1 Speckle Noise -- 1.3.2 Analytical and Numerical Models -- 1.3.3 Estimation Strategies -- 1.3.4 New Altimeters -- 1.3.5 Non-Ocean Surfaces -- 1.4 Precise Orbit Determination -- 1.4.1 Orbit Determination Technique -- 1.4.1.1 Performance Requirements -- 1.4.1.2 Radial Error Properties -- 1.4.2 Orbit Determination Measurement Systems -- 1.4.3 Satellite Trajectory Modeling and Parameterization -- 1.4.4 Major Modeling Evolution since the Beginning of the 1990s -- 1.4.5 Long-Term Orbit Error and Stability Budget -- 1.4.6 Foreseen Modeling Improvement -- 1.5 Geophysical Corrections -- 1.5.1 Sea State Bias Correction -- 1.5.1.1 Origins of the Sea State Effects and Correction -- 1.5.1.2 Theoretical Solutions -- 1.5.1.3 Empirical Solutions. , 1.5.2 Atmospheric Propagation Effect Corrections -- 1.5.2.1 Ionospheric Correction -- 1.5.2.2 Dry Tropospheric Correction -- 1.5.2.3 The Wet Tropospheric Correction -- 1.6 Altimetry Product Auxiliary Information: Reference Surfaces, Tides, and High-Frequency Signal -- 1.6.1 Reference Surfaces -- 1.6.2 Tides, High-Frequency Signals -- 1.6.2.1 The Tide Correction -- 1.6.2.2 The High-Frequency Correction -- 1.6.2.3 S1 and S2 Atmospheric and Ocean Signals -- 1.7 Altimetry Time and Space Sampling: Orbit Selection and Virtual Constellation Approach -- 1.7.1 Sampling Properties of a Single Altimeter Orbit -- 1.7.2 Orbit Sub-Cycles and Sampling Properties -- 1.7.3 Altimeter Virtual Constellation and Phasing -- 1.8 Altimetry error budget -- 1.8.1 Error Budget for Mesoscale Oceanography -- 1.8.2 Error Budget for Mean Sea Level Trend Monitoring -- 1.8.3 Error Budget for Sub-Mesoscale -- References -- Chapter 2: Wide-Swath AltimetryA Review -- 2.1 Introduction -- 2.2 Ocean and Hydrology Sampling Requirements -- 2.3 Approaches to Wide-Swath Altimetry -- 2.3.1 From Nadir Altimetry to Wide-Swath Altimetry: Three-Dimensional Geolocation -- 2.3.2 Wide-Swath Altimetry Using Waveform Tracking -- 2.3.3 Wide-Swath Altimetry Using Radar Interferometry -- 2.4 The Interferometric Error Budget -- 2.4.1 Roll Errors -- 2.4.2 Phase Errors -- 2.4.3 Range Errors -- 2.4.4 Baseline Errors -- 2.4.5 Finite Azimuth Footprint Biases -- 2.4.6 Radial Velocity Errors -- 2.4.7 Calibration Methods -- 2.5 Wide-Swath Altimetry Phenomenology -- 2.5.1 Water Brightness -- 2.5.2 Wave Effects -- 2.5.2.1 The "Surfboard Effect" -- 2.5.2.2 Temporal Correlation Effects -- 2.5.2.3 Wave Bunching -- 2.5.2.4 The EM Bias. , 2.5.3 Layover and Vegetation Effects -- 2.6 Wide-Swath Altimetry Mission Design -- 2.7 Summary and Prospects -- References -- Acknowledgments -- Chapter 3: In Situ Observations Needed to Complement, Validate, and Interpret Satellite Altimetry -- 3.1 Introduction -- 3.2 Sea Surface Heights Obtained from Tide Gauge/GNSS Networks -- 3.2.1 Sea Level Measurements before the Altimeter Era -- 3.2.2 Tide Gauge and Altimeter Data Complementarity -- 3.2.3 Tide Gauges Used for Altimeter Calibration -- 3.2.4 Tide Gauge and Altimeter Data in Combination in Studies of Long-Term Sea Level Change -- 3.2.5 GNSS Equipment at Tide Gauges -- 3.2.6 New Developments in Tide Gauges and Data Availability -- 3.2.7 Tide Gauges and Altimetry in the Future -- 3.3 Upper-Ocean (0 to 2000 decibars) Steric Variability: The XBT and Argo Networks -- 3.3.1 The Relationship of SSH Variability with Subsurface T and S-Steric Height -- 3.3.2 A Brief History of Systematic Ocean Sampling by the XBT and Argo Networks -- 3.3.3 Ocean Heat Content and Steric Sea Level -- 3.3.4 The Global Pattern of SSH and Upper-Ocean Steric Height -- 3.3.5 Geostrophic Ocean Circulation -- 3.3.6 Horizontal Scales of Variability in the Ocean: The Challenge of Resolution -- 3.4 Deep-Ocean (greater than 2000 m) Steric Variability: Repeat Hydrography and Deep Argo -- 3.4.1 Ventilating the Deep Ocean: Deep Water Production and the Global MOC -- 3.4.2 Monitoring Deep Steric Variability through Repeat Hydrography -- 3.4.3 The Deep Ocean Contribution to Steric Sea Level -- 3.4.4 Future of Deep Observing: Deep Argo -- 3.6 Dynamic Topography and Surface Velocity -- 3.6.1 Eulerian Velocity Measurements -- 3.6.2 Lagrangian Velocity Measurements -- 3.6.3 Geostrophic Currents and Mean Dynamic Topography. , 3.6.4 Ageostrophic Motions -- 3.7 The Technology Revolution and the Future of Ocean Observations -- References -- Acknowledgments -- Chapter 4: Auxiliary Space-Based Systems for Interpreting Satellite Altimetry -- 4.1 Introduction -- 4.2 Measurements: Mean Geoid and Sea Surface -- 4.2.1 Parameterizing Gravity and the Geoid -- 4.2.2 GRACE and GOCE -- 4.2.3 Surface Gravity Data and Combination Geoids -- 4.2.4 Mean Sea Surface Models -- 4.3 Measurements: Time-Variable Gravity -- 4.4 Applications: Dynamic Ocean Topography -- 4.4.1 Importance of Consistency between Geoid and MSS -- 4.4.2 Improvements in MDT with GRACE and GOCE Geoids -- 4.4.3 Toward a Higher Spatial Resolution MDT -- 4.5 Applications: Global and Regional Ocean Mass Variations -- 4.6 Conclusions and Future Prospects -- References -- Chapter 5: A 25-Year Satellite Altimetry-Based Global Mean Sea Level Record -- 5.1 Introduction -- 5.2 The Altimeter Mean Sea Level Record -- 5.2.1 Computing Global and Regional Mean Sea Level Time Series -- 5.2.2 Altimeter Missions -- 5.2.3 Altimeter Corrections -- 5.2.4 Intermission Biases -- 5.2.5 Averaging Process -- 5.2.6 Validation of the GMSL Record with Tide Gauge Measurements -- 5.2.7 Mean Sea Level Variation and Uncertainties -- 5.2.7.1 Global Scale Uncertainty -- 5.2.7.2 Regional Scales -- 5.3 Interpreting the Altimeter GMSL Record -- 5.3.1 Steric Sea Level Contribution -- 5.3.2 The Cryosphere Contributions to GMSL -- 5.3.3 The Land Water Storage Contributions to GMSL -- 5.3.3.1 Interannual Variations -- 5.3.3.2 Long-Term Variations -- 5.4 Closing the Sea Level Budget and Uncertainties -- 5.4.1 Glacial Isostatic Adjustment -- 5.4.2 Ocean Mass/Barystatic Sea Level from GRACE. , 5.4.3 Closure and Missing Components -- 5.5 How Altimetry Informs Us About the Future -- References -- Chapter 6: Monitoring and Interpreting Mid-Latitude Oceans by Satellite Altimetry -- 6.1 Introduction: Role of Mid-Latitude Oceans -- 6.2 Western Boundary Currents -- 6.3 Meridional Circulation and Interbasin Exchanges -- 6.4 Climate Change -- 6.5 Summary and Future Research -- References -- Acknowledgments -- Chapter 7: Monitoring and Interpreting the Tropical Oceans by Satellite Altimetry -- 7.1 Introduction -- 7.2 Tropical Atlantic Ocean -- 7.2.1 Intraseasonal and Eddy Activities -- 7.2.1.1 Eddy Structures -- 7.2.1.2 Tropical Instability Waves -- 7.2.2 The Seasonal Cycle -- 7.2.3 Equatorial Waves -- 7.2.4 Interannual Variability -- 7.3 Tropical Indo-Pacific Ocean -- 7.3.1 Tropical Pacific -- 7.3.1.1 Intraseasonal Variability -- 7.3.1.2 Seasonal Variability -- 7.3.1.3 Interannual and Decadal Variability -- 7.3.2 Tropical Indian Ocean -- 7.3.2.1 Intraseasonal Variability -- 7.3.2.2 Seasonal Cycle -- 7.3.2.3 Interannual Variability -- 7.3.2.4 Decadal and Multidecadal Changes -- 7.3.3 Indo-Pacific Linkage and Indonesian Throughflow -- 7.4 Summary -- References -- Acknowledgments -- Chapter 8: The High Latitude Seas and Arctic Ocean -- 8.1 Introduction -- 8.1.1 Satellite Altimetry in the High Latitude and Arctic Ocean -- 8.2 Mapping the Sea Ice Thickness in the Arctic Ocean -- 8.3 Sea Level Change -- 8.3.1 The Seasonal Cycle -- 8.3.2 Secular and Long-Term Sea Level Changes -- 8.3.3 Arctic Sea Level Budget -- 8.3.4 The Polar Gap and Accuracy Estimates -- 8.4 Mean Dynamic Topography -- 8.5 Ocean Circulation and Volume Transport -- 8.5.1 Surface Circulation -- 8.5.2 Volume Transport. , 8.6 Summary and Outlook.
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  • 2
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Meyssignac, B., Boyer, T., Zhao, Z., Hakuba, M. Z., Landerer, F. W., Stammer, D., Koehl, A., Kato, S., L'Ecuyer, T., Ablain, M., Abraham, J. P., Blazquez, A., Cazenave, A., Church, J. A., Cowley, R., Cheng, L., Domingues, C. M., Giglio, D., Gouretski, V., Ishii, M., Johnson, G. C., Killick, R. E., Legler, D., Llovel, W., Lyman, J., Palmer, M. D., Piotrowicz, S., Purkey, S. G., Roemmich, D., Roca, R., Savita, A., von Schuckmann, K., Speich, S., Stephens, G., Wang, G., Wijffels, S. E., & Zilberman, N. Measuring global ocean heat content to estimate the Earth energy Imbalance. Frontiers in Marine Science, 6, (2019): 432, doi: 10.3389/fmars.2019.00432.
    Description: The energy radiated by the Earth toward space does not compensate the incoming radiation from the Sun leading to a small positive energy imbalance at the top of the atmosphere (0.4–1 Wm–2). This imbalance is coined Earth’s Energy Imbalance (EEI). It is mostly caused by anthropogenic greenhouse gas emissions and is driving the current warming of the planet. Precise monitoring of EEI is critical to assess the current status of climate change and the future evolution of climate. But the monitoring of EEI is challenging as EEI is two orders of magnitude smaller than the radiation fluxes in and out of the Earth system. Over 93% of the excess energy that is gained by the Earth in response to the positive EEI accumulates into the ocean in the form of heat. This accumulation of heat can be tracked with the ocean observing system such that today, the monitoring of Ocean Heat Content (OHC) and its long-term change provide the most efficient approach to estimate EEI. In this community paper we review the current four state-of-the-art methods to estimate global OHC changes and evaluate their relevance to derive EEI estimates on different time scales. These four methods make use of: (1) direct observations of in situ temperature; (2) satellite-based measurements of the ocean surface net heat fluxes; (3) satellite-based estimates of the thermal expansion of the ocean and (4) ocean reanalyses that assimilate observations from both satellite and in situ instruments. For each method we review the potential and the uncertainty of the method to estimate global OHC changes. We also analyze gaps in the current capability of each method and identify ways of progress for the future to fulfill the requirements of EEI monitoring. Achieving the observation of EEI with sufficient accuracy will depend on merging the remote sensing techniques with in situ measurements of key variables as an integral part of the Ocean Observing System.
    Description: GJ was supported by the NOAA Research. MP and RK were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. JC was partially supported by the Centre for Southern Hemisphere Oceans Research, a joint research centre between QNLM and CSIRO. CD and AS were funded by the Australian Research Council (FT130101532 and DP160103130) and its Centre of Excellence for Climate Extremes (CLEX). IQuOD team members (TB, RC, LC, CD, VG, MI, MP, and SW) were supported by the Scientific Committee on Oceanic Research (SCOR) Working Group 148, funded by the National SCOR Committees and a grant to SCOR from the U.S. National Science Foundation (Grant OCE-1546580), as well as the Intergovernmental Oceanographic Commission of UNESCO/International Oceanographic Data and Information Exchange (IOC/IODE) IQuOD Steering Group. ZZ was supported by the National Aeronautics and Space Administration (NNX17AH14G). LC was supported by the National Key Research and Development Program of China (2017YFA0603200 and 2016YFC1401800).
    Keywords: Ocean heat content ; Sea level ; Ocean mass ; Ocean surface fluxes ; ARGO ; Altimetry ; GRACE ; Earth Energy Imbalance
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
    Publication Date: 2022-05-27
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Bongarts Lebbe, T., Rey-Valette, H., Chaumillon, E., Camus, G., Almar, R., Cazenave, A., Claudet, J., Rocle, N., Meur-Ferec, C., Viard, F., Mercier, D., Dupuy, C., Menard, F., Rossel, B. A., Mullineaux, L., Sicre, M.-A., Zivian, A., Gaill, F., & Euzen, A. Designing coastal adaptation strategies to tackle sea level rise. Frontiers in Marine Science, 8, (2021): 740602, https://doi.org/10.3389/fmars.2021.740602.
    Description: Faced with sea level rise and the intensification of extreme events, human populations living on the coasts are developing responses to address local situations. A synthesis of the literature on responses to coastal adaptation allows us to highlight different adaptation strategies. Here, we analyze these strategies according to the complexity of their implementation, both institutionally and technically. First, we distinguish two opposing paradigms – fighting against rising sea levels or adapting to new climatic conditions; and second, we observe the level of integrated management of the strategies. This typology allows a distinction between four archetypes with the most commonly associated governance modalities for each. We then underline the need for hybrid approaches and adaptation trajectories over time to take into account local socio-cultural, geographical, and climatic conditions as well as to integrate stakeholders in the design and implementation of responses. We show that dynamic and participatory policies can foster collective learning processes and enable the evolution of social values and behaviors. Finally, adaptation policies rely on knowledge and participatory engagement, multi-scalar governance, policy monitoring, and territorial solidarity. These conditions are especially relevant for densely populated areas that will be confronted with sea level rise, thus for coastal cities in particular.
    Description: This work was conducted as part of the project SEA’TIES led by the Ocean & Climate Platform. SEA’TIES is funded by the Prince Albert II Foundation (No. 3112), Veolia Foundation (No. 20EB2004), and Fondation de France, Monaco. It was coordinated by the CNRS, in the framework of the RTPi (International Multidisciplinary Thematic Network) which drives the scientific component of the SEA’TIES project.
    Keywords: climate change ; sea level rise ; adaptation ; governance ; nature-based solutions ; multidisciplinary approach ; vulnerability ; coastal cities
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ponte, R. M., Carson, M., Cirano, M., Domingues, C. M., Jevrejeva, S., Marcos, M., Mitchum, G., van de Wal, R. S. W., Woodworth, P. L., Ablain, M., Ardhuin, F., Ballu, V., Becker, M., Benveniste, J., Birol, F., Bradshaw, E., Cazenave, A., De Mey-Fremaux, P., Durand, F., Ezer, T., Fu, L., Fukumori, I., Gordon, K., Gravelle, M., Griffies, S. M., Han, W., Hibbert, A., Hughes, C. W., Idier, D., Kourafalou, V. H., Little, C. M., Matthews, A., Melet, A., Merrifield, M., Meyssignac, B., Minobe, S., Penduff, T., Picot, N., Piecuch, C., Ray, R. D., Rickards, L., Santamaria-Gomez, A., Stammer, D., Staneva, J., Testut, L., Thompson, K., Thompson, P., Vignudelli, S., Williams, J., Williams, S. D. P., Woppelmann, G., Zanna, L., & Zhang, X. Towards comprehensive observing and modeling systems for monitoring and predicting regional to coastal sea level. Frontiers in Marine Science, 6, (2019): 437, doi:10.3389/fmars.2019.00437.
    Description: A major challenge for managing impacts and implementing effective mitigation measures and adaptation strategies for coastal zones affected by future sea level (SL) rise is our limited capacity to predict SL change at the coast on relevant spatial and temporal scales. Predicting coastal SL requires the ability to monitor and simulate a multitude of physical processes affecting SL, from local effects of wind waves and river runoff to remote influences of the large-scale ocean circulation on the coast. Here we assess our current understanding of the causes of coastal SL variability on monthly to multi-decadal timescales, including geodetic, oceanographic and atmospheric aspects of the problem, and review available observing systems informing on coastal SL. We also review the ability of existing models and data assimilation systems to estimate coastal SL variations and of atmosphere-ocean global coupled models and related regional downscaling efforts to project future SL changes. We discuss (1) observational gaps and uncertainties, and priorities for the development of an optimal and integrated coastal SL observing system, (2) strategies for advancing model capabilities in forecasting short-term processes and projecting long-term changes affecting coastal SL, and (3) possible future developments of sea level services enabling better connection of scientists and user communities and facilitating assessment and decision making for adaptation to future coastal SL change.
    Description: RP was funded by NASA grant NNH16CT00C. CD was supported by the Australian Research Council (FT130101532 and DP 160103130), the Scientific Committee on Oceanic Research (SCOR) Working Group 148, funded by national SCOR committees and a grant to SCOR from the U.S. National Science Foundation (Grant OCE-1546580), and the Intergovernmental Oceanographic Commission of UNESCO/International Oceanographic Data and Information Exchange (IOC/IODE) IQuOD Steering Group. SJ was supported by the Natural Environmental Research Council under Grant Agreement No. NE/P01517/1 and by the EPSRC NEWTON Fund Sustainable Deltas Programme, Grant Number EP/R024537/1. RvdW received funding from NWO, Grant 866.13.001. WH was supported by NASA (NNX17AI63G and NNX17AH25G). CL was supported by NASA Grant NNH16CT01C. This work is a contribution to the PIRATE project funded by CNES (to TP). PT was supported by the NOAA Research Global Ocean Monitoring and Observing Program through its sponsorship of UHSLC (NA16NMF4320058). JS was supported by EU contract 730030 (call H2020-EO-2016, “CEASELESS”). JW was supported by EU Horizon 2020 Grant 633211, Atlantos.
    Keywords: Coastal sea level ; Sea-level trends ; Coastal ocean modeling ; Coastal impacts ; Coastal adaptation ; Observational gaps ; Integrated observing system
    Repository Name: Woods Hole Open Access Server
    Type: Article
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