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Vertical land motion in the Iberian Atlantic coast and its implications for sea level change evaluation

  • V. B. Mendes ORCID logo EMAIL logo , S. M. Barbosa and D. Carinhas

Abstract

In this study, we estimate vertical land motion for 35 stations primarily located along the coastline of Portugal and Spain, using GPS time series with at least eight years of observations. Based on this set of GPS stations, our results show that vertical land motion along the Iberian coastline is characterized, in general, by a low to moderate subsidence, ranging from −2.2 mm yr−1 to 0.4 mm yr−1, partially explained by the glacial isostatic adjustment geophysical signal. The estimates of vertical land motion are subsequently applied in the analysis of tide gauge records and compared with geocentric estimates of sea level change. Geocentric sea level for the Iberian Atlantic coast determined from satellite altimetry for the last three decades has a mean of 2.5 ± 0.6 mm yr−1, with a significant range, as seen for a subset of grid points located in the vicinity of tide gauge stations, which present trends varying from 1.5 mm yr−1 to 3.2 mm yr−1. Relative sea level determined from tide gauges for this region shows a high degree of spatial variability, that can be partially explained not only by the difference in length and quality of the time series, but also for possible undocumented datum shifts, turning some trends unreliable. In general, tide gauges corrected for vertical land motion produce smaller trends than satellite altimetry. Tide gauge trends for the last three decades not corrected for vertical land motion range from 0.3 mm yr−1 to 5.0 mm yr−1 with a mean of 2.6 ± 1.4 mm yr−1, similar to that obtained from satellite altimetry. When corrected for vertical land motion, we observe a reduction of the mean to ∼1.9 ± 1.4 mm yr−1. Actions to improve our knowledge of vertical land motion using space geodesy, such as establishing stations in co-location with tide gauges, will contribute to better evaluate sea level change and its impacts on coastal regions.

Award Identifier / Grant number: UIDB/50019/2020 – IDL

Award Identifier / Grant number: UIDB/50014/2020

Funding statement: This work is financed by National Funds through the Portuguese funding agency, FCT – Fundação para a Ciência e a Tecnologia within projects UIDB/50019/2020 – IDL and UIDB/50014/2020.

Acknowledgment

The authors would like to thank Alvaro Santamaría-Gómez and an anonymous reviewer for their insightful suggestions and careful reading of the manuscript. We thank all institutions providing access to GPS data. We thank the Portuguese Instituto Hidrográfico and Direção-Geral do Território for making available unpublished tide gauge data. Tide gauge data from the Permanent Service for Mean Sea Level and the University of Hawaii Sea Level Center and satellite altimetry data provided by the Radar Altimeter Database (RADS) are also gratefully acknowledged. Maps were created using Generic Mapping Tools [91] and R [92].

References

[1] Cazenave A, Le Cozannet G. Sea level rise and its coastal impactset. Earth’s Future 2, 15–34, doi:10.1002/2013EF000188, 2013.Search in Google Scholar

[2] Ponte RM, Carson M, Cirano M, et al. Towards comprehensive observing and modeling systems for monitoring and predicting regional to coastal sea level. Frontiers in Marine Science 6, 437, doi: 10.3389/fmars.2019.00437, 2019.Search in Google Scholar

[3] Eurostat. Eurostat regional yearbook 2011. Publications Office of the European Union, Luxembourg, doi:10.2785/1392, 2011.Search in Google Scholar

[4] Pfeffer J, Allemand P. The key role of vertical land motions in coastal sea level variations: A global synthesis of multisatellite altimetry, tide gauge data and GPS measurements. Earth and Planetary Science Letters 439, 39–47, doi:10.1016/j.epsl.2016.01.027, 2016.Search in Google Scholar

[5] Wöppelmann G, Martin Miguez B, Bouin M-N, Altamimi Z. Geocentric sea-level trend estimates from GPS analyses at relevant tide gauges world-wide. Global and Planetary Change 57(3-4), 396–406, doi:10.1016/j.gloplacha.2007.02.002, 2007.Search in Google Scholar

[6] Wöppelmann G, Marcos M. Vertical land motion as a key to understanding sea level change and variability. Reviews of Geophysics 54(1), 64–92, doi:10.1002/2015RG000502, 2016.Search in Google Scholar

[7] Cazenave A, Dominh K, Ponchaut F, Soudarin L, Crétaux J-F, Provost CL. Sea level changes from Topex-Poseidon altimetry and tide gauges, and vertical crustal motions from DORIS. Geophysical Research Letters 26, 2077–2080, doi:10.1029/1999GL900472, 1999.Search in Google Scholar

[8] Ray R, Beckley B, Lemoine F. Vertical crustal motion derived from satellite altimetry and tide gauges, and comparisons with DORIS measurements. Advances in Space Research 45, 1510–1522, doi:10.1016/j.asr.2010.02.020, 2010.Search in Google Scholar

[9] Raucoules D, Le Cozannet G, Wöppelmann G, de Michele M, Gravelle M, Daag A, Marcos M. High nonlinear urban ground motion in Manila (Philippines) from 1993 to 2010 observed by DInSAR: implications for sea-level measurement. Remote Sensing of Environment 139, 386–397, doi:10.1016/j.rse.2013.08.021, 2013.Search in Google Scholar

[10] Poitevin C, Wöppelmann G, Raucoules D, Le Cozannet G, Marcos M, Testut L. Vertical land motion and relative sea level changes along the coastline of Brest (France) from combined space-borne geodetic methods. Remote Sensing of Environment 222, 275–285, doi:10.1016/j.rse.2018.12.035, 2019.Search in Google Scholar

[11] Santamaría-Gómez A, Gravelle M, Collilieux X, Guichard M, Martín Míguez B, Tiphaneau P, Wöppelmann G. Mitigating the effects of vertical land motion in tide gauge records using a state-of-the-art GPS velocity field. Global and Planetary Change 98-99, 6–17, doi:10.1016/j.gloplacha.2012.07.007, 2012.Search in Google Scholar

[12] Bouin MN, Wöppelmann G. Land motion estimates from GPS at tide gauges: a geophysical evaluation. Geophysical Journal International 180, 193–209, doi:10.1111/j.1365-246X.2009.04411.x, 2010.Search in Google Scholar

[13] Santamaría-Gómez A, Bouin M-N, Collilieux X, Wöppelmann G. Correlated errors in GPS position time series: implications for velocity estimates. Journal of Geophysical Research 116, B01405, doi:10.1029/2010JB007701, 2011.Search in Google Scholar

[14] Mendes VB, Barbosa SM, Romero I, Madeira J, Brum da Silveira A. Vertical land motion and sea level change in Macaronesia. Geophysical Journal International 210(2), 1264–1280, doi:10.1093/gji/ggx229, 2017.Search in Google Scholar

[15] Montillet J-P, Melbourne TI, Szeliga WM. GPS vertical land motion corrections to sea-level rise estimates in the Pacific Northwest. Journal of Geophysical Research Oceans 123, 1196–1212, doi:10.1002/2017JC013257, 2018.Search in Google Scholar

[16] Martínez-Asensio A, Wöppelmann G, Ballu V, et al. Relative sea-level rise and the influence of vertical land motion at Tropical Pacific Islands. Global and Planetary Change 176, 132–143, doi:10.1016/j.gloplacha.2019.03.008, 2019.Search in Google Scholar

[17] Yang L, Francis OP. Sea-level rise and vertical land motion on the islands of Oahu and Hawaii, Hawaii. Advances in Space Research, doi:10.1016/j.asr.2019.08.028, 2019.Search in Google Scholar

[18] Bevis M, Scherer W, Merrifield M. Technical issues and recommendations related to the installation of continuous GPS stations at tide gauges. Marine Geodesy 25, 87–99, 2002.10.1080/014904102753516750Search in Google Scholar

[19] Woodworth PL, Wöppelmann G, Marcos M, Gravelle M, Bingley RM. Why we must tie satellite positioning to tide gauge data. EOS 98, doi:10.1029/2017EO064037, 2017.Search in Google Scholar

[20] Wöppelmann G, Marcos M. Coastal sea level rise in southern Europe and the nonclimate contribution of vertical land motion. Journal of Geophysical Research 117, C01007, doi:10.1029/2011JC007469, 2012.Search in Google Scholar

[21] García F, Vigo M, García-García D, Sánchez-Reales J. Combination of multisatellite altimetry and tide gauge data for determining vertical crustal movements along northern Mediterranean coast. Pure and Applied Geophysics 169(8), 1411–1423, doi:10.1007/s00024-011-0400-5, 2012.Search in Google Scholar

[22] Grgić M, Nerem RS, Bašić T. Absolute sea level surface modeling for the Mediterranean from satellite altimeter and tide gauge measurements. Marine Geodesy 40(4), 239–258, doi:10.1080/01490419.2017.1342726, 2017.Search in Google Scholar

[23] Fenoglio-Marc L, Fehlau M, Ferri L, Becker M, Gao Y, Vignudelli S. Coastal sea surface heights from improved altimeter data in the Mediterranean Sea. In: Mertikas S (eds) Gravity, Geoid and Earth Observation. International Association of Geodesy Symposia, vol 135. Springer, Berlin, Heidelberg, 2010.10.1007/978-3-642-10634-7_33Search in Google Scholar

[24] Cazenave A, Palanisamy H, Ablain M. Contemporary sea level changes from satellite altimetry: What have we learned? What are the new challenges? Advances in Space Research 62(7), 1639–1653, doi:10.1016/j.asr.2018.07.017, 2018.Search in Google Scholar

[25] Fernandes MJ, Lázaro C, Ablain M, Pires N. Improved wet path delays for all ESA and reference altimetric missions. Remote Sensing of Environment 169, 50–74, doi:10.1016/j.rse.2015.07.023, 2015.Search in Google Scholar

[26] Cipollini P, Birol F, Fernandes MJ, et al. Satellite altimetry in coastal regions. In: Stammer D, Cazenave A (eds) Satellite Altimetry Over Oceans and Land Surfaces. 1st Edition, CRC Press, Taylor & Francis, Boca Raton, 2017.10.1201/9781315151779-11Search in Google Scholar

[27] Cipollini P, Calafat FM, Jevrejeva S, Melet A, Prandi P. Monitoring sea level in the coastal zone with satellite altimetry and tide gauges. Surveys in Geophysics 38(1), 33–57, doi:10.1007/s10712-016-9392-0, 2017.Search in Google Scholar PubMed PubMed Central

[28] Benveniste J, Cazenave A, Vignudelli S, et al. Requirements for a Coastal Hazard Observing System. Front. Mar. Sci. 6, 348, doi:10.3389/fmars.2019.00348, 2019.Search in Google Scholar

[29] Jevrejeva S, Grinsted A, Moore JC, Holgate S. Nonlinear trends and multiyear cycles in sea level records. Journal of Geophysical Research 111, C09012, doi:10.1029/2005JC003229, 2006.Search in Google Scholar

[30] Nerem RS, Chambers DP, Choe C, Mitchum GT. Estimating Mean Sea Level Change from the TOPEX and Jason Altimeter Missions. Marine Geodesy 33(sup1), 435–446, doi:10.1080/01490419.2010.491031, 2010.Search in Google Scholar

[31] Zhang X, Church JA. Sea level trends, interannual and decadal variability in the Pacific Ocean. Geophysical Research Letters 39, L21701, doi:10.1029/2012GL053240, 2012.Search in Google Scholar

[32] Cheng X, Xie S-P, Du Y, Wang J, Chen X, Wang J. Interannual-to-decadal variability and trends of sea level in the South China Sea. Climate Dynamics 46(9-10), 3113–3126, doi:10.1007/s00382-015-2756-1, 2016.Search in Google Scholar

[33] Karabil S, Zorita E, Hünicke B. Mechanisms of variability in decadal sea-level trends in the Baltic Sea over the 20th century. Earth System Dynamics 8, 1031–1046, doi:10.5194/esd-8-1031-2017, 2017.Search in Google Scholar

[34] Holgate SJ, Matthews A, Woodworth PL, et al. New data systems and products at the Permanent Service for Mean Sea Level. Journal of Coastal Research 29(3), 493–504, doi:10.2112/JCOASTRES-D-12-00175.1, 2013.Search in Google Scholar

[35] Permanent Service for Mean Sea Level (PSMSL). Tide gauge data, Retrieved Aug 2019 from http://www.psmsl.org/data/obtaining/, 2019.Search in Google Scholar

[36] Caldwell PC, Merrifield MA, Thompson PR. Sea level measured by tide gauges from global oceans – the Joint Archive for Sea Level holdings (NCEI Accession 0019568), Version 5.5, NOAA National Centers for Environmental Information, Dataset, doi:10.7289/V5V40S7W, 2015.10.7289/V5V40S7WSearch in Google Scholar

[37] Miller L, Douglas BC. Mass and volume contributions to twentieth-century global sea level rise. Nature 428, 406–409, doi:10.1038/nature02309, 2004.Search in Google Scholar PubMed

[38] Marcos M, Tsimplis MN. Coastal sea level trends in Southern Europe. Geophysical Journal International 175(1), 70–82, doi:10.1111/j.1365-246X.2008.03892.x, 2018.Search in Google Scholar

[39] Antunes C, Taborda R. Sea level at Cascais tide gauge: data, analysis and results. Journal of Coastal Research, 218–222, http://www.jstor.org/stable/25737569, 2009.Search in Google Scholar

[40] Scharroo R, Leuliette E, Naeije M, Martin-Puig C, Pires N. RADS Version 4: an efficient way to analyse the multi-mission altimeter database. In: Ouwehand L (ed) Proceedings of the ESA Living Planet Symposium, 9–13 May 2016, Prague, Czech Republic, ESA Special Publication SP-740, 2016.Search in Google Scholar

[41] Scharroo R. RADS Data Manual version 4.2.10., 2/2018, 2018.Search in Google Scholar

[42] Johnston G, Riddell A, Hausler G. The International GNSS Service. In: Teunissen PJG, Montenbruck O (eds) Springer Handbook of Global Navigation Satellite Systems, 1st Edition, Springer International Publishing, Cham, Switzerland, 967–982, 2017.10.1007/978-3-319-42928-1_33Search in Google Scholar

[43] Bruyninx C, Habrich H, Söhne W, Kenyeres A, Stangl G, Völksen C. Enhancement of the EUREF Permanent Network Services and Products. In: Kenyon S, Pacino M, Marti U (eds) Geodesy for Planet Earth. International Association of Geodesy Symposia, vol 136. Springer, Berlin, Heidelberg, 2012.10.1007/978-3-642-20338-1_12Search in Google Scholar

[44] Herring TA, King RW, Floyd MA, McClusky SC. GAMIT Reference Manual, Release 10.6. Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, 2015.Search in Google Scholar

[45] Herring TA, King RW, Floyd MA, McClusky SC. GLOBK Reference Manual, Release 10.6. Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, 2015.Search in Google Scholar

[46] Lyard F, Lefèvre F, Letellier T, Francis O. Modelling the global ocean tides: modern insights from FES2004. Ocean Dynamics 56(5-6), 394–415, doi:10.1007/s10236-006-0086-x, 2006.Search in Google Scholar

[47] Petit G, Luzum B (eds.). IERS Conventions (2010), IERS Technical Note 36, Frankfurt am Main: Verlag des Bundesamts für Kartographie und Geodäsie, 179 pp, 2010.Search in Google Scholar

[48] Lagler K, Schindelegger M, Böhm J, Krásná H, Nilsson T. GPT2: Empirical slant delay model for radio space geodetic techniques. Geophysical Research Letters 40, 1069–1073, doi:10.1002/grl.50288, 2013.Search in Google Scholar

[49] Boehm J, Werl B, Schuh H. Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data. Journal of Geophysical Research 111, B02406, doi:10.1029/2005JB003629, 2006.Search in Google Scholar

[50] Altamimi Z, Collilieux X, Métivier L. ITRF2008: An improved solution of the International Terrestrial Reference Frame. Journal of Geodesy 85(8), 457–473, 2011.10.1007/s00190-011-0444-4Search in Google Scholar

[51] Zeileis A, Kleiber C, Krämer W, Hornik K. Testing and dating of structural changes in practice. Computational Statistics & Data Analysis 44(1-2), 109–123, doi:10.1016/S0167-9473(03)00030-6, 2003.Search in Google Scholar

[52] Killick R, Eckley I. Changepoint: An R Package for changepoint analysis. Journal of Statistical Software 58(3), 1–19, doi:10.18637/jss.v058.i03, 2014.Search in Google Scholar

[53] Ross GJ. Parametric and nonparametric sequential change detection in R: The cpm package. Journal of Statistical Software 66(3), 1–20, doi:10.18637/jss.v066.i03, 2015.Search in Google Scholar

[54] Ploberger W, Krämer W. The CUSUMtest with OLS residuals. Econometrica 60(2), 271–285, doi:10.2307/2951597, 1992.Search in Google Scholar

[55] Andrews DWK, Ploberger W. Optimal tests when a nuisance parameter is present only under the alternative. Econometrica 62(6), 1383–1414, 1994.10.2307/2951753Search in Google Scholar

[56] Araújo IB, Bos MS, Bastos LC, Cardoso MM. Analysing the hundred year sea level record of Leixões, Portugal. Journal of Hydrology 481:76–84, 2013.10.1016/j.jhydrol.2012.12.019Search in Google Scholar

[57] Piecuch CG, Bittermann K, Kemp AC, Ponte RM, Little CM, Engelhart SE, Lentz SJ. River-discharge effects on United States Atlantic and Gulf coast sea-level changes. Proceedings of the National Academy of Sciences 115(30), 7729–7734, 2018.10.1073/pnas.1805428115Search in Google Scholar PubMed PubMed Central

[58] Woodworth PL, Melet A, Marcos M, et al. Forcing Factors Affecting Sea Level Changes at the Coast. Surveys in Geophysics 40, 1351–1397, doi:10.1007/s10712-019-09531-1, 2019.Search in Google Scholar

[59] Laiz I, Ferrer L, Plomaritis TA, Charria G. Effect of river runoff on sea level from in-situ measurements and numerical models in the Bay of Biscay. Deep Sea Res. Part II: Topical Stud. Oceanogr. 106, 49–67, 2014.10.1016/j.dsr2.2013.12.013Search in Google Scholar

[60] Barbosa SM, Fernandes MJ, Silva ME. Nonlinear sea level trends from European tide gauge records. Ann. Geophys. 22, 1465–1472, doi:10.5194/angeo-22-1465-2004, 2004.Search in Google Scholar

[61] Bos MS, Fernandes RMS, Williams SDP, Bastos L. Fast Error Analysis of Continuous GNSS Observations with Missing Data. J. Geod. 87(4), 351–360, doi:10.1007/s00190-012-0605-0, 2013.Search in Google Scholar

[62] Williams S. The effect of coloured noise on the uncertainties of rates estimated from geodetic time series. Journal of Geodesy 76, 483–494, doi:10.1007/s00190-002-0283-4, 2003.Search in Google Scholar

[63] Amiri-Simkooei AR, Tiberius CCJM, Teunissen PJG. Assessment of noise in GPS coordinate time series: Methodology and results. Journal of Geophysical Research 112, B07413, doi:10.1029/2006JB004913, 2007.Search in Google Scholar

[64] Langbein J. Noise in GPS displacement measurements from Southern California and Southern Nevada. Journal of Geophysical Research 113, B05405, doi:10.1029/2007JB005247, 2008.Search in Google Scholar

[65] Santamaría-Gómez A, Bouin M-N, Collilieux X, Wöppelmann G. Correlated errors in GPS position time series: Implications for velocity estimates. Journal of Geophysical Research 116, B01405, doi:10.1029/2010JB007701, 2011.Search in Google Scholar

[66] Langbein J. Estimating rate uncertainty with maximum likelihood: differences between power-law and flicker–random-walk models. Journal of Geodesy 86, 775–783, doi:10.1007/s00190-012-0556-5, 2012.Search in Google Scholar

[67] He X, Bos MS, Montillet JP, et al. Investigation of the noise properties at low frequencies in long GNSS time series. Journal of Geodesy 93, 1271–1282, doi:10.1007/s00190-019-01244-y, 2019.Search in Google Scholar

[68] Marcos M, Gomis D, Monserrat S, Álvarez-Fanjul E, Pérez B, García-Lafuente J. Consistency of long sea level time series in the northern coast of Spain. Journal of Geophysical Research 110, C03008, doi:10.1029/2004JC002522, 2005.Search in Google Scholar

[69] García MJ, Tel E, Moliner J. Sea-level variations on the north and northwest coasts of Spain. ICES Journal of Marine Science 69, 720–727, 2012.10.1093/icesjms/fss058Search in Google Scholar

[70] Dodet G, Bertin X, Bouchette F, Gravelle M, Testut L, Wöppelmann G. Characterization of sea-level variations along the metropolitan coasts of France: Waves, tides, storm surges and long-term changes. Journal of Coastal Research, 88(Special Issue), 10–24, 2019. In: Castelle B, Chaumillon E (eds) Coastal Evolution under Climate Change along the Tropical Overseas and Temperate Metropolitan France. Coconut Creek (Florida), ISSN 0749-0208.10.2112/SI88-003.1Search in Google Scholar

[71] Armitage P, Berry G, Matthews JNS. Statistical methods in medical research, 4th Edition, Wiley-Blackwell, 2002.10.1002/9780470773666Search in Google Scholar

[72] Pérez B, Payo A, López D, Woodworth PL, Alvarez Fanjul E. Overlapping sea level time series measured using different technologies: an example from the REDMAR Spanish network. Natural Hazards and Earth System Sciences 14, 589–610, doi:10.5194/nhess-14-589-2014, 2014.Search in Google Scholar

[73] Jollife I. Principal component analysis, 2nd Edition, Springer, New York, 2002.Search in Google Scholar

[74] Barbosa SM, Fernandes MJ, Silva ME. Space-time analysis of sea level in the North Atlantic from TOPEX/Poseidon satellite altimetry. In: Jekeli C, Bastos L, Fernandes J (eds) Gravity, Geoid and Space Missions. International Association of Geodesy Symposia, vol 129. Springer, Berlin, Heidelberg, 2005.Search in Google Scholar

[75] Yan Z, Tsimplis MN, Woolf D. Analysis of the relationship between the North Atlantic oscillation and sea level changes in northwest Europe. International Journal of Climatology 24, 743–758, doi:10.1002/joc.1035, 2004.Search in Google Scholar

[76] Gomis D, Ruiz S, Sotillo MG, Álvarez-Fanjul E, Terradas J. Low frequency Mediterranean sea level variability: The contribution of atmospheric pressure and wind. Global and Planetary Change 63(2), 215–229, doi:10.1016/j.gloplacha.2008.06.005, 2008.Search in Google Scholar

[77] Barbosa SM. Atmospheric correction of satellite altimetry observations and sea-level variability in the NE Atlantic. Advances in Space Research 50(8), 1077–1084, 2012.10.1016/j.asr.2011.09.013Search in Google Scholar

[78] Jung T, Vitart F, Ferranti L, Morcrette J-J. Origin and predictability of the extreme negative NAO winter of 2009/10. Geophysical Research Letters 38, L07701, doi:10.1029/2011GL046786, 2011.Search in Google Scholar

[79] Buchan J, Hirschi JJ-M, Blaker AT, Sinha B. North Atlantic SST anomalies and the cold north European weather events of winter 2009/10 and December 2010. Monthly Weather Review 142(2), 922–932, 2014.10.1175/MWR-D-13-00104.1Search in Google Scholar

[80] Goddard PB, Yin J, Griffies SM, Zhang S. An extreme event of sea-level rise along the northeast coast of north America in 2009–2010. Nature Communications 6, 6346, doi:10.1038/ncomms7346, 2015.Search in Google Scholar PubMed

[81] Hurrell JW, Kushnir Y, Ottersen G, Visbeck M. An overview of the North Atlantic Oscillation. In: Hurrell JW, Kushnir Y, Ottersen G, Visbeck M (eds) The North Atlantic Oscillation Climatic Significance and Environmental Impact. Washington D.C. Geophysical Monograph, vol 134, 1–35, doi:10.1029/134GM01, 2003.Search in Google Scholar

[82] Argus DF, Peltier WR, Drummond R, Moore AW. The Antarctica component of postglacial rebound model ICE-6G_C (VM5a) based upon GPS positioning, exposure age dating of ice thicknesses, and relative sea level histories. Geophysical Journal International 198(1), 537–563, 2014.10.1093/gji/ggu140Search in Google Scholar

[83] Peltier WR, Argus DF, Drummond R. Space geodesy constrains ice-age terminal deglaciation: The global ICE-6G_C (VM5a) model. Journal of Geophysical Research 120, 450–487, doi:10.1002/2014JB011176, 2015.Search in Google Scholar

[84] Altamimi Z, Rebischung P, Métivier L, Collilieux X. ITRF2014: A new release of the International Terrestrial Reference Frame modeling nonlinear station motions. Journal of Geophysical Research Solid Earth 121, 6109–6131, 2016.10.1002/2016JB013098Search in Google Scholar

[85] Ballu V, Gravelle M, Wöppelmann G, et al. Vertical land motion in the Southwest and Central Pacific from available GNSS solutions and implications for relative sea levels. Geophysical Journal International 218(3), 1537–1551, doi:10.1093/gji/ggz247, 2019.Search in Google Scholar

[86] Santamaría-Gómez A, Gravelle M, Dangendorf S, Marcos M, Spada G, Wöppelmann G. Uncertainty of the 20th century sea-level rise due to vertical land motion errors. Earth and Planetary Science Letters 473, 24–32, doi:10.1016/j.epsl.2017.05.038, 2017.Search in Google Scholar

[87] Blewitt G, Hammond WC, Kreemer C. Harnessing the GPS data explosion for interdisciplinary science, EOS 99, doi:10.1029/2018EO104623, 2018.Search in Google Scholar

[88] Vinogradov SV, Ponte RM. Low-frequency variability in coastal sea level from tide gauges and altimetry. Journal of Geophysical Research 116, C07006, doi:10.1029/2011JC007034, 2011.Search in Google Scholar

[89] Bonaduce A, Pinardi N, Oddo P, Spada G, Larnicol G. Sea-level variability in the Mediterranean Sea from altimetry and tide gauges. Climate Dynamics, 47(9-10), 2851–2866, doi:10.1007/s0038, 2016.Search in Google Scholar

[90] Dieng HB, Dadou I, Léger F, Morel Y, Jouanno J, Lyard F, Allain D. Sea level anomalies using altimetry, model and tide gauges along the African coasts in the Eastern Tropical Atlantic Ocean: Inter-comparison and temporal variability. Advances in Space Research, doi:10.1016/j.asr.2019.10.019, 2019.Search in Google Scholar

[91] Wessel P, Smith WHF, Scharroo R, Luis JF, Wobbe F. Generic Mapping Tools: Improved version released. EOS Trans. AGU, 94, 409–410, 2013.10.1002/2013EO450001Search in Google Scholar

[92] R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org/, 2018.Search in Google Scholar


Supplemental Material

The online version of this article offers supplementary material (https://doi.org/10.1515/jag-2020-0012).


Received: 2020-02-26
Accepted: 2020-05-19
Published Online: 2020-06-04
Published in Print: 2020-07-26

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