Abstract
The United States Navy has two approaches for assimilating sea surface height anomaly (SSHA) data, both relying on climatology. One approach is indirect, with the construction of synthetic temperature (T) and salinity (S) profiles based on observationally-derived climatological covariances between SSHA, T, and S. The other approach is direct via a four-dimensional variational system, but it relies on a mean SSH (here, one constrained by observational climatology) to enable comparisons between observed SSHA and model SSH. Because the approaches rely on observational climatology, they can fail when data are outside that climatology. Such a case is reviewed here. A recent field experiment (Borrione et al. 2017) collected glider T/S profiles along altimeter tracks in the Ligurian Sea (northwest Mediterranean Sea). While SSHA data are similar to observational climatology, T/S data are warmer and saltier. In this study, SSHA and T/S data are independently assimilated in separate experiments. It is found that each experiment fits its assimilated data as expected, but the experiments fail to fit the withheld/unassimilated data. Assimilation mechanisms are found to work as designed. Impacts of climatology on results versus withheld data are discussed.
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References
Alberola C, Rousseau S, Millot C, Astraldi M, Font J, Garcialafuente J, Gasparini G-P, Send U, Vangriesheim A (1995) Tidal currents in the western Mediterranean sea. Oceanol Acta 18(2):273–284
Asselin R (1972) Frequency filter for time integrations. Mon Weather Rev 100(6):487–490
Barron CN, Smedstad LF (2002) Global river inflow with Navy Coastal Ocean Model. In: OCEANS’02 MTS/IEEE, Biloxi, MI, USA, vol 3, pp 1472–1479. https://doi.org/10.1109/OCEANS.2002.1191855
Barron CN, Birol Kara A, Martin PJ, Rhodes RC, Smedstad L (2006) Formulation, implementation and examination of vertical coordinate choices in the Global Navy Coastal Ocean Model (NCOM). Ocean Modell 11:347–375. https://doi.org/10.1016/j.ocemod.2005.01.004
Bauer R (1982) Functional description: master oceanographic data set (MOODS), Compass Systems Inc.
Bennett AF (1992) Inverse methods in physical oceanography. Cambridge University Press
Bennett AF (2002) Inverse modeling of the ocean and atmosphere. Cambridge University Press
Bleck R (2002) An oceanic general circulation model framed in hybrid isopycnic-Cartesian coordinates. Ocean Model 4(1):55–88. https://doi.org/10.1016/S1463-5003(01)00012-9
Borrione I, Oddo P, Russo A, Coelho E (2017) Interpreting operational altimetry signals in near-coastal areas using underwater autonomous vehicles and remotely sensed ocean colour data. Abstract EGU2017-19400, presented at the EGU General Assembly 2017, Vienna, Austria, 23–28 April 2017
Boyer TP, Antonov JI, Garcia HE, Johnson DR, Locarnini RA, Mishonov AV, Pitcher MT, Baranova OK, Smolyar IV (2006) World ocean database 2005. In: Levitus S (ed) NOAA Atlas NESDIS 60, U.S. Government Printing Office, Washington, D.C., 190 pp., DVDs
Calafat FM, Chambers DP, Tsimplis MN (2012) Mechanisms of decadal sea level variability in the eastern North Atlantic and the Mediterranean Sea. J Geophys Res 117:C09022. https://doi.org/10.1029/2012JC008285
Carnes MR, Mitchell JL, deWitt PW (1990) Synthetic temperature profiles derived from Geosat altimetry: comparison with air-dropped expendable bathythermograph profiles. J Geophys Res 95(C10):17979–17992. https://doi.org/10.1029/JC095iC10p17979
Carnes M, Helber RW, Barron CN, Dastugue JM (2010) Validation test report for GDEM4. NRL Report NRL/MR/7330—10-9271. https://apps.dtic.mil/dtic/tr/fulltext/u2/a530343.pdf. Accessed 7 December 2018
Carrier MJ, Ngodock HE, Muscarella P, Smith S (2016a) Impact of assimilating surface velocity observations on the model sea surface height using the NCOM-4DVAR. Mon Weather Rev 144:1051–1068. https://doi.org/10.1175/MWR-D-14-00285.1
Carrier MJ, Ngodock HE, Smith SR, Souopgui I, Bartels B (2016b) Examining the potential impact of SWOT observations in an ocean analysis-forecasting system. Mon Weather Rev 144. https://doi.org/10.1175/MWR-D-15-0361.1
Chapman DC (1985) Numerical treatment of cross-shelf open boundaries in a barotropic coastal ocean model. J Phys Oceanogr 15(8):1060–1075
Chua BS, Bennett AF (2001) An inverse ocean modeling system. Ocean Model 3(3–4):137–165
Cummings JA (2005) Operational multivariate ocean data assimilation. Quart J Roy Meteor Soc 131:3583–3604. https://doi.org/10.1256/qj.05.105
Cummings JA, Smedstad OM (2014) Ocean data impacts in global HYCOM. J Atmos Oceanic Tech 31(8):1771–1791
Daley R, Barker E (2001) NAVDAS: Formulation and diagnostics. Mon Weather Rev 129(4):869–883
Davis RE, Eriksen CE, Jones CP (2003) Autonomous Buoyancy-driven underwater gliders. In: Griffiths G (ed) Technology and applications of autonomous underwater vehicles, Chap. 3. Taylor and Francis, pp 37–58
Escudier R, Bouffard J, Pascual A, Poulain P-M, Pujol M-I (2013) Improvement of coastal and mesoscale observation from space: application to the northwestern Mediterranean sea. Geophys Res Lett 40:2148–2153. https://doi.org/10.1002/grl.50324
Flather RA (1976) A tidal model of the north-west European continental shelf. Mem Soc R Sci Liege 10:141–164
Fox DN, Teague WJ, Barron CN, Carnes MR, Lee CM (2002) The modular ocean data assimilation system (MODAS). J Atmos Oceanic Technol 19:240–252. https://doi.org/10.1175/1520-0426(2002)019,0240:TMODAS.2.0.CO;2
Fukumori I, Menemenlis D, Lee T (2007) A near-uniform basin-wide sea level fluctuation of the Mediterranean Sea. J Phys Oceanogr 37(2):338–358. https://doi.org/10.1175/JPO3016.1
Helber RW, Townsend TL, Barron CN, Dastugue JM, Carnes MR (2013) Validation test report for the improved synthetic ocean profile (ISOP) system, Part I: Synthetic profile methods and algorithm. NRL Memo. Report, NRL/MR/7320—13-9364
Hogan TF, Liu M, Ridout JA, Peng MS, Whitcomb TR, Ruston BC, Reynolds CA, Eckermann SD, Moskaitis JR, Baker NL, McCormack JP, Viner KC, McLay JG, Flatau MK, Xu L, Chen C, Chang SW (2014) The navy global environmental model. Oceanography 27(3):116–125
Jacobs GA, Barron CN, Fox DN, Whitmer KR, Klingenberger S, May D, Blaha JP (2002) Operational altimeter sea level products. Oceanography 15:13–21. https://doi.org/10.5670/oceanog.2002.32
Jugan MJ, Beresford H (1991) Editing approach for the Navy’s master oceanographic observation data set. In: Published in proceedings of MTS’91, An Ocean Cooperative: Industry, Government, and Academia, vol II
Landerer FW, Volkov DL (2013) The anatomy of recent large sea level fluctuations in the Mediterranean sea. Geophys Res Lett 40:553–557. https://doi.org/10.1002/grl.50140
Le Traon PY (2011) Satellites and operational oceanography. In: Schiller A, Brassington GB (eds) Operational oceanography for the 21st century, 2011, Chap. 2, pp 29–54. https://doi.org/10.1007/978-94-007-0332-2_2.
Le Traon PY, Dibarboure G, Jacobs G, Martin M, Rémy E, Schiller A (2017) Use of satellite altimetry for operational oceanography. In: Satellite altimetry over oceans and land surfaces. CRC Press, pp 581–608
Mellor GL, Yamada T (1982) Development of a turbulence closure model for geophysical fluid problems. Rev Geophys 20(4):851–875. https://doi.org/10.1029/RG020i004p00851
Metzger EJ, Smedstad OM, Thoppil PG, Hurlburt HE, Wallcraft AJ, Franklin DS, Shriver JF, Smedstad LF (2008) Validation test report for the global ocean prediction system V3.0 – 1/12° HYCOM/NCODA: Phase I. NRL Memorandum Report NRL/MR/7320—08-9148, 85 pp. https://apps.dtic.mil/dtic/tr/fulltext/u2/a490855.pdf. Accessed 7 December 2018
Metzger EJ, Smedstad OM, Thoppil PG, Hurlburt HE, Franklin DS, Peggion G, Shriver JF, Wallcraft AJ (2010) Validation test report for the global ocean forecast system V3.0–1/12° HYCOM/NCODA: Phase II. NRL Memorandum Report NRL/MR/7320—10-9236, 76 pp. https://apps.dtic.mil/dtic/tr/fulltext/u2/a518693.pdf. Accessed 7 December 2018
Metzger EJ, Helber RW, Hogan PJ, Posey PG, Thoppil PG, Townsend TL, Wallcraft AJ, Smedstad OM, Franklin DS, Zumudio-Lopez L, Phelps MW (2017) Global ocean forecast system 3.1 validation testing. NRL Report NRL/MR/7320—17-9722. https://apps.dtic.mil/dtic/tr/fulltext/u2/1034517.pdf. Accessed 7 December 2018
Ngodock H, Carrier M (2014a) A 4DVAR system for the navy coastal ocean model. Part I: System description and assimilation of synthetic observations in Monterey Bay. Mon Weather Rev 142(6):2085–2107
Ngodock H, Carrier M (2014b) A 4DVAR system for the navy coastal ocean model. Part II: Strong and weak constraint assimilation experiments with real observations in Monterey Bay. Mon Weather Rev 142(6):2108–2117
Ngodock H, Carrier M, Souopgui I, Smith S, Martin P, Muscarella P, Jacobs G (2016) On the direct assimilation of along-track sea-surface height observations into a free-surface ocean model using a weak constraints four-dimensional variational (4D-Var) method. Quart J Roy Meteor Soc 142:1160–1170. https://doi.org/10.1002/qj.2721
Ngodock H, Carrier M, Smith S, Souopgui I (2017) Weak and strong constraints variational data assimilation with the NCOM-4DVAR in the Agulhas region using the representer method. Mon Weather Rev 145:1755–1764. https://doi.org/10.1175/MWR-D-16-0264.1
NRL DBDB2—Global 2-Minute topography. http://www7320.nrlssc.navy.mil/DBDB2_WWW/. Accessed on 15 December 2018
Oke PR, Balmaseda MA, Benkiran M, Cummings JA, Dombrowsky E, Fujii Y, Guinehut S, Larnicol G, Le Traon P-Y, Martin MJ (2009) Observing system evaluations using GODAE systems. Oceanography 22(3):144–153. https://doi.org/10.5670/oceanog.2009.72
OSTM/Jason-2 Products Handbook, CNES: SALP-MU-M-OP-15815-CN, EUMETSAT: EUM/OPS-JAS/MAN/08/0041, JPL: OSTM-29-1237 NOAA/NESDIS: Polar Series/OSTM J400. Issue 1 rev 11, 13 Jan 2017. https://www.aviso.altimetry.fr/fileadmin/documents/data/tools/hdbk_j2.pdf
Rowley C, Mask A (2014) Regional and coastal prediction with the relocatable ocean nowcast/forecast system. Oceanography 27(3):44–55. https://doi.org/10.5670/oceanog.2014.67
Rudnick DL, Davis RE, Eriksen CE, Fratantoni DM, Perry MJ (2004) Underwater gliders for ocean research. Mar Technol Soc J 38(1):48–59
SARAL/AltiKa Products Handbook. CNES: SALP-MU-M-OP-15984-CN. Issue 2 rev 5m 1 July 2016. https://www.aviso.altimetry.fr/fileadmin/documents/data/tools/SARAL_Altika_products_handbook_01.pdf
Smagorinsky J (1963) General circulation experiments with the primitive equations: I. The basic experiment. Mon Weather Rev 91(3):99–164
Smith S, Ngodock H, Carrier M, Shriver J, Muscarella P, Suoupgui I (2017) Validation and operational implementation of the navy coastal ocean model four dimensional variational data assimilation system (NCOM 4DVAR) in the Okinawa trough. In: Park SK, Xu L (eds) Data assimilation for atmospheric, oceanic and hydrologic applications, vol III. Springer International Publishing
Tsimplis MN, Proctor R, Flather RA (1995) A two-dimensional tidal model for the Mediterranean Sea. J Geophys Res 100(C8):16223–16239. https://doi.org/10.1029/95JC01671
Verron J, Sengenes P, Lambin J, Noubel J, Steunou N, Guillot A, Picot N, Coutin-Faye S, Sharma R, Gairola RM, Raghava Murthy DVA, Richman JG, Griffin D, Pascual A, Rémy F, Gupta PK (2015) The SARAL/AltiKa altimetry satellite mission. Mar Geodesy 38(sup1):2–21. https://doi.org/10.1080/01490419.2014.1000471
Willmott CJ, Matsuura K (2005) Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim Res 30:79–82. https://doi.org/10.3354/cr030079
Willmott CJ, Robeson SM, Matsuura K (2017) Climate and other models may be more accurate than reported, Eos, 98. https://doi.org/10.1029/2017EO074939. Published on 21 June 2017. Accessed 30 Jan 2019
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Osborne, J.J., Carrier, M.J., Ngodock, H.E. (2022). Difficulty with Sea Surface Height Assimilation When Relying on an Unrepresentative Climatology. In: Park, S.K., Xu, L. (eds) Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV). Springer, Cham. https://doi.org/10.1007/978-3-030-77722-7_17
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