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4. Global sea-level budget 1993–present

Author

Group, WCRP Global Sea Level Budget, Cazenave, Anny, Meyssignac, Benoit, Ablain, Michael, Balmaseda, Magdalena, Bamber, Jonathan, Barletta, Valentina Roberta, Beckley, Brian, Benveniste, Jérôme, Berthier, Etienne, Blazquez, Alejandro, Boyer , Tim, Caceres , Denise, Chambers, Don P., Champollion, Nicolas, Chao , Ben, Chen , Jianli, Cheng , Lijing, Church , John A., Chuter, Stephen, Cogley , J. Graham, Dangendorf , Soenke, Desbruyères , Damien, Döll , Petra, Domingues, Catia, Falk , Ulrike, Famiglietti , James, Fenoglio-Marc, Luciana, Forsberg, René, Galassi , Gaia, Gardner, Alex, Groh, Andreas, Hamlington , Benjamin, Hogg, Anna, Horwath, Martin, Humphrey , Vincent, Husson , Laurent, Ishii , Masayoshi, Jaeggi , Adrian, Jevrejeva , Svetlana, Johnson , Gregory, Kolodziejczyk , Nicolas, Kusche , Jürgen, Lambeck , Kurt, Landerer , Felix, Leclercq , Paul, Legresy , Benoit, Leuliette , Eric, Llovel, William, Longuevergne , Laurent, Loomis , Bryant D., Luthcke, Scott B, Marcos, Marta, Marzeion , Ben, Merchant , Chris, Merrifield , Mark, Milne, Glenn, Mitchum , Gary, Mohajerani, Yara, Monier , Maeva, Monselesan , Didier, Nerem , Steve, Palanisamy , Hindumathi, Paul, Frank, Pérez, Begona, Piecuch , Christopher G., Ponte , Rui M., Purkey , Sarah G., Reager , John T., Rietbroek , Roelof, Rignot, Eric, Riva, Riccardo, Roemmich , Dean H., Sørensen, Louise Sandberg, Sasgen, Ingo, Schram, E.J.O., Seneviratne , Sonia I., Shum, C.K., Spada, Giorgio, Stammer, Detlef, van de Wal , Roderic, Velicogna, Isabella, von Schuckmann, Karina, Wada, Yoshihide, Wang , Yiguo, Watson, Christopher S., Wiese, David, Wijffels , Susan, Westaway , Richard, Woppelmann, Guy, Wouters, Bert, Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), International Space Science Institute [Bern] (ISSI), Géosciences Rennes (GR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Collecte Localisation Satellites (CLS), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Centre National d'Études Spatiales [Toulouse] (CNES), European Centre for Medium-Range Weather Forecasts (ECMWF), University of New South Wales [Sydney] (UNSW), Universität Siegen [Siegen], Institut Français de Recherche pour l'Exploitation de la Mer - Brest (IFREMER Centre de Bretagne), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), National Oceanographic Centre [Liverpool] (NOC ), Australian National University (ANU), CSIRO Marine and Atmosphere Research [Hobart], Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Institut Mediterrani d'Estudis Avancats (IMEDEA), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)-Universidad de las Islas Baleares (UIB), University of Tasmania [Hobart, Australia] (UTAS), LIttoral ENvironnement et Sociétés - UMRi 7266 (LIENSs), Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS), Hubrecht Institute [Utrecht, Netherlands], University Medical Center [Utrecht]-Royal Netherlands Academy of Arts and Sciences (KNAW), Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Cazenave, Anny, Meyssignac, Benoit, Ablain, Michael, Balmaseda, Magdalena, Bamber, Jonathan, Barletta, Valentina, Beckley, Brian, Benveniste, Jérôme, Berthier, Etienne, Blazquez, Alejandro, Boyer, Tim, Caceres, Denise, Chambers, Don, Champollion, Nicola, Chao, Ben, Chen, Jianli, Cheng, Lijing, Church, John A., Chuter, S., Cogley, J., Dangendorf, Soenke, Desbruyères, Damien, Döll, Petra, Domingues, Catia, Falk, Ulrike, Famiglietti, Jame, Fenoglio-Marc, Luciana, Forsberg, Rene, Galassi, Gaia, Gardner, Alex, Groh, Andrea, Hamlington, Benjamin, Hogg, Anna, Horwath, Martin, Humphrey, Vincent, Husson, Laurent, Ishii, Masayoshi, Jaeggi, Adrian, Jevrejeva, Svetlana, Johnson, Gregory, Kolodziejczyk, Nicola, Kusche, Jürgen, Lambeck, Kurt, Landerer, Felix, Leclercq, Paul, Legresy, Benoit, Leuliette, Eric, Llovel, William, Longuevergne, Laurent, Loomis, Bryant D., Luthcke, Scott B., Marcos, Marta, Marzeion, Ben, Merchant, Chri, Merrifield, Mark, Milne, Glenn, Mitchum, Gary, Mohajerani, Yara, Monier, Maeva, Monselesan, Didier, Nerem, Steve, Palanisamy, Hindumathi, Paul, Frank, Perez, Begoña, Piecuch, Christopher G., Ponte, Rui M., Purkey, Sarah G., Reager, John T., Rietbroek, Roelof, Rignot, Eric, Riva, Riccardo, Roemmich, Dean H., Sandberg Sørensen, Louise, Sasgen, Ingo, Schrama, E. J. O., Seneviratne, Sonia I., Shum, C. K., Spada, Giorgio, Stammer, Detlef, van de Wal, Roderic, Velicogna, Isabella, von Schuckmann, Karina, Wada, Yoshihide, Wang, Yiguo, Watson, Christopher, Wiese, David, Wijffels, Susan, Westaway, Richard, Woppelmann, Guy, and Wouters, Bert

Subjects
010504 meteorology & atmospheric sciences, Climate change, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Context (language use), sea level, 010502 geochemistry & geophysics, 01 natural sciences, Deep sea, SDG 13 - Climate Action, sea level, sea level change, gauge records, 14. Life underwater, Altimeter, Sea level, ComputingMilieux_MISCELLANEOUS, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, lcsh:Environmental sciences, 0105 earth and related environmental sciences, lcsh:GE1-350, geography, geography.geographical_feature_category, 520 Astronomy, Global warming, lcsh:QE1-996.5, Glacier, lcsh:Geology, 13. Climate action, Climatology, gauge records, General Earth and Planetary Sciences, Environmental science, GlobalMass, Ice sheet, sea level change
Abstract

Global mean sea level is an integral of changes occurring in the climate system in response to unforced climate variability as well as natural and anthropogenic forcing factors. Its temporal evolution allows changes (e.g., acceleration) to be detected in one or more components. Study of the sea-level budget provides constraints on missing or poorly known contributions, such as the unsurveyed deep ocean or the still uncertain land water component. In the context of the World Climate Research Programme Grand Challenge entitledRegional Sea Level and Coastal Impacts, an international effort involving the sea-level community worldwide has been recently initiated with the objective of assessing the various datasets used to estimate components of the sea-level budget during the altimetry era (1993 to present). These datasets are based on the combination of a broad range of space-based and in situ observations, model estimates, and algorithms. Evaluating their quality, quantifying uncertainties and identifying sources of discrepancies between component estimates is extremely useful for various applications in climate research. This effort involves several tens of scientists from about 50 research teams/institutions worldwide (www.wcrp-climate.org/grand-challenges/gc-sea-level, last access: 22 August 2018). The results presented in this paper are a synthesis of the first assessment performed during 2017–2018. We present estimates of the altimetry-based global mean sea level (average rate of 3.1 ± 0.3 mm yr−1and acceleration of 0.1 mm yr−2over 1993–present), as well as of the different components of the sea-level budget (http://doi.org/10.17882/54854, last access: 22 August 2018). We further examine closure of the sea-level budget, comparing the observed global mean sea level with the sum of components. Ocean thermal expansion, glaciers, Greenland and Antarctica contribute 42 %, 21 %, 15 % and 8 % to the global mean sea level over the 1993–present period. We also study the sea-level budget over 2005–present, using GRACE-based ocean mass estimates instead of the sum of individual mass components. Our results demonstrate that the global mean sea level can be closed to within 0.3 mm yr−1(1σ). Substantial uncertainty remains for the land water storage component, as shown when examining individual mass contributions to sea level.

Published
2018

5. Seasonal Forecasting Skill of Sea‐Level Anomalies in a Multi‐Model Prediction Framework.

Author

Long, Xiaoyu, Widlansky, Matthew J., Spillman, Claire M., Kumar, Arun, Balmaseda, Magdalena, Thompson, Philip R., Chikamoto, Yoshimitsu, Smith, Grant A., Huang, Bohua, Shin, Chul‐Su, Merrifield, Mark A., Sweet, William V., Leuliette, Eric, Annamalai, H. S., Marra, John J., and Mitchum, Gary

Subjects
SEAWATER, CLIMATE change, OCEAN circulation, SEA level, RAINFALL anomalies
Abstract

Coastal high water level events are increasing in frequency and severity as global sea‐levels rise, and are exposing coastlines to risks of flooding. Yet, operational seasonal forecasts of sea‐level anomalies are not made for most coastal regions. Advancements in forecasting climate variability using coupled ocean‐atmosphere global models provide the opportunity to predict the likelihood of future high water events several months in advance. However, the skill of these models to forecast seasonal sea‐level anomalies has not been fully assessed, especially in a multi‐model framework. Here, we construct a 10‐model ensemble of retrospective forecasts with future lead times of up to 11 months. We compare predicted sea levels from bias‐corrected forecasts with 20 years of observations from satellite‐based altimetry and shore‐based tide gauges. Forecast skill, as measured by anomaly correlation, tends to be highest in the tropical and subtropical open oceans, whereas the skill is lower in the higher latitudes and along some continental coasts. For most locations, multi‐model averaging produces forecast skill that is comparable to or better than the best performing individual model. We find that the most skillful predictions typically come from forecast systems with more accurate initializations of sea level, which is generally achieved by assimilating altimetry data. Having relatively higher horizontal resolution in the ocean is also beneficial, as such models seem to better capture dynamical processes necessary for successful forecasts. The multi‐model assessment suggests that skillful seasonal sea‐level forecasts are possible in many, though not all, parts of the global ocean. Plain Language Summary: We assess 10 global climate forecasting systems to predict monthly and seasonal anomalies of local sea levels up to a year into the future. We find that skillful seasonal sea‐level forecasts are possible in many parts of the global ocean. Forecast skill is generally highest in the tropical and subtropical open oceans, whereas the skill is lower in the higher latitudes and along continental coasts. For most locations, multi‐model averaging improves the forecast skill, compared to considering the models individually. Overall, the most skillful predictions are from forecasting systems with more accurate initializations of sea level and higher horizontal resolutions of the ocean. Key Points: Prediction skill of seasonal sea‐level anomalies up to a year in the future is assessed in 10 global climate forecasting systemsSkillful seasonal sea‐level forecasts are found in the tropics, whereas the skill is lower in higher latitudes and along continental coastsThe most skillful predictions are from models with more accurate initializations of sea level and higher resolutions of the ocean [ABSTRACT FROM AUTHOR]

Published
2021
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6. Evaluating the Performance of Jason-2 Open-Loop and Closed-Loop Tracker Modes.

Author

Martin-Puig, Cristina, Leuliette, Eric, Lillibridge, John, and Roca, Mònica

Subjects
*ALTIMETERS, *DIGITAL elevation models, *CLOSED loop systems, *WIND speed, *EPHEMERIS Time
Abstract

The Poseidon-3 altimeter on board Jason-2 includes a significant new capability with respect to its predecessors, an open-loop [Détermination Immédiate d'Orbite par Doris Embarqué (DIODE)/digital elevation model (DEM)] tracker mode. This innovative mode is capable of successfully tracking the backscatter signal over rapidly varying terrains, and thus it overcomes one of the limitations of the closed-loop Poseidon-2 tracker on board Jason-1. DIODE/DEM achieves this improvement thanks to a predetermined DEM on board that, when combined with DIODE orbit ephemeris, provides improved acquisition timing and reduced data loss in the coastal zone. As a further enhancement, Jason-3 and the Sentinel-3 programs will be capable of autonomously switching to this innovative mode in selected regions. To help recommend how these missions should utilize DIODE/DEM, the authors studied the impact of the tracker mode on the accuracy and precision of wave heights and wind speed, the continuity of the sea level climate data record, and the coverage in coastal regions. The results show close agreement between the open- and closed-loop tracker modes over the open ocean with the exception of some differences at high-tidal variability areas, the coastal zone, and sea ice regions. The DIODE/DEM tracker shows better performance than the closed-loop tracker mode at the coast and in the presence of sea ice. Jason-2, when operating in open-loop mode, allows for an approximately 5% increase of successful acquisitions at the ocean-to-land transition. However, open-loop tracking exhibits more variability in regions of high tides than closed-loop. [ABSTRACT FROM AUTHOR]

Published
2016
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