Change search
Refine search result
1 - 11 of 11
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Axell, Lars
    et al.
    SMHI, Research Department, Oceanography.
    Liu, Ye
    SMHI, Research Department, Oceanography.
    Application of 3-D ensemble variational data assimilation to a Baltic Sea reanalysis 1989-20132016In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 68, article id 24220Article in journal (Refereed)
    Abstract [en]

    A 3-D ensemble variational (3DEnVar) data assimilation method has been implemented and tested for oceanographic data assimilation of sea surface temperature (SST), sea surface salinity (SSS), sea ice concentration (SIC), and salinity and temperature profiles. To damp spurious long-range correlations in the ensemble statistics, horizontal and vertical localisation was implemented using empirical orthogonal functions. The results show that the 3DEnVar method is indeed possible to use in oceanographic data assimilation. So far, only a seasonally dependent ensemble has been used, based on historical model simulations. Near-surface experiments showed that the ensemble statistics gave inhomogeneous and anisotropic horizontal structure functions, and assimilation of real SST and SIC fields gave smooth, realistic increment fields. The implementation was multivariate, and results showed that the cross-correlations between variables work in an intuitive way, for example, decreasing SST where SIC was increased and vice versa. The profile data assimilation also gave good results. The results from a 25-year reanalysis showed that the vertical salinity and temperature structure were significantly improved, compared to both dependent and independent data.

  • 2.
    Dieterich, Christian
    et al.
    SMHI, Research Department, Oceanography.
    Schimanke, Semjon
    SMHI, Research Department, Oceanography.
    Wang, Shiyu
    SMHI, Research Department, Climate research - Rossby Centre.
    Väli, Germo
    SMHI, Research Department, Oceanography.
    Liu, Ye
    SMHI, Research Department, Oceanography.
    Hordoir, Robinson
    SMHI, Research Department, Oceanography.
    Höglund, Anders
    SMHI, Research Department, Oceanography.
    Meier, Markus
    SMHI, Research Department, Oceanography.
    Evaluation of the SMHI coupled atmosphere-ice-ocean model RCA4-NEMO2013Report (Other academic)
    Abstract [en]

    AbstractThe regional, coupled atmosphere-ice-ocean model RCA4-NEMO developed at the SMHI is evaluated on the basis of an ERA40 hindcast. While the development of the regional climate model is continuing a first assessment is presented here to allow for an orientation about the status guo. RCA4-NEMO in its present form consists of two model components. The regional atmosphere model RCA4 covers the whole of Europe and is interactvely coupled to a North Sea and Baltic Sea ice-ocean model based on NEMO. RCA4-NEMO is currently being used to downscale CMIP5 scenarios for the North Sea and Baltic Sea region for this century. As a part of the validation of RCA4-NEMO we present an analysis and discussion of the hindcast period 1970-1999. The model realization is compared to observational records. Near surface temperatures and heat fluxes compare reasonably well with records of in-situ measurments and satellite derived estimates. For salinities and freshwater fluxes the agreement with observations in not satisfactory yet. The momentum fluxes transferred from the atmosphere to the ice-ocean model are identified as on of the sensitive processes in the coupling of both model components. Except for the freshwater exchange between atmosphere and ocean the climatological near surface properties and corresponding fluxes compare well with climatological estimates for the period 1970-1999.

  • 3.
    Dieterich, Christian
    et al.
    SMHI, Research Department, Oceanography.
    Wang, Shiyu
    SMHI, Research Department, Climate research - Rossby Centre.
    Schimanke, Semjon
    SMHI, Research Department, Oceanography.
    Groger, Matthias
    SMHI, Research Department, Oceanography.
    Klein, Birgit
    Hordoir, Robinson
    SMHI, Research Department, Oceanography.
    Samuelsson, Patrick
    SMHI, Research Department, Climate research - Rossby Centre.
    Liu, Ye
    SMHI, Research Department, Oceanography.
    Axell, Lars
    SMHI, Research Department, Oceanography.
    Höglund, Anders
    SMHI, Research Department, Oceanography.
    Meier, Markus
    SMHI, Research Department, Oceanography.
    Surface Heat Budget over the North Sea in Climate Change Simulations2019In: Atmosphere, ISSN 2073-4433, E-ISSN 2073-4433, Vol. 10, no 5, article id 272Article in journal (Refereed)
  • 4.
    Hordoir, Robinson
    et al.
    SMHI, Research Department, Oceanography.
    Axell, Lars
    SMHI, Research Department, Oceanography.
    Höglund, Anders
    SMHI, Research Department, Oceanography.
    Dieterich, Christian
    SMHI, Research Department, Oceanography.
    Fransner, Filippa
    Groger, Matthias
    SMHI, Research Department, Oceanography.
    Liu, Ye
    SMHI, Research Department, Oceanography.
    Pemberton, Per
    SMHI, Research Department, Oceanography.
    Schimanke, Semjon
    SMHI, Research Department, Oceanography.
    Andersson, Helén
    SMHI, Research Department, Oceanography.
    Ljungemyr, Patrik
    SMHI, Core Services.
    Nygren, Petter
    SMHI, Core Services.
    Falahat, Saeed
    SMHI, Core Services.
    Nord, Adam
    SMHI, Core Services.
    Jönsson, Anette
    SMHI, Core Services.
    Lake, Irene
    SMHI, Core Services. SMHI, Research Department, Climate research - Rossby Centre.
    Doos, Kristofer
    Hieronymus, Magnus
    SMHI, Research Department, Oceanography.
    Dietze, Heiner
    Loeptien, Ulrike
    Kuznetsov, Ivan
    Westerlund, Antti
    Tuomi, Laura
    Haapala, Jari
    Nemo-Nordic 1.0: a NEMO-based ocean model for the Baltic and North seas - research and operational applications2019In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 12, no 1, p. 363-386Article in journal (Refereed)
  • 5.
    Liu, Ye
    et al.
    SMHI, Research Department, Oceanography.
    Fu, Weiwei
    Assimilating high-resolution sea surface temperature data improves the ocean forecast potential in the Baltic Sea2018In: Ocean Science, ISSN 1812-0784, E-ISSN 1812-0792, Vol. 14, no 3, p. 525-541Article in journal (Refereed)
  • 6.
    Liu, Ye
    et al.
    SMHI, Research Department, Oceanography.
    Meier, Markus
    SMHI, Research Department, Oceanography.
    Axell, Lars
    SMHI, Research Department, Oceanography.
    Reanalyzing temperature and salinity on decadal time scales using the ensemble optimal interpolation data assimilation method and a 3D ocean circulation model of the Baltic Sea2013In: JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, ISSN 2169-9275, Vol. 118, no 10, p. 5536-5554Article in journal (Refereed)
    Abstract [en]

    A 30-year (1970-1999) reanalysis of temperature and salinity is conducted by assimilating temperature and salinity profiles into an ocean model of the Baltic Sea with ensemble optimal interpolation approach. Some configurations of the reanalysis are presented. For example, the samples are chosen from the same season as the analysis time to address the strong seasonal variability. The impact of different observation time windows on the analysis results is also discussed. A locally determined alpha is adopted for the long-time-scale simulation. To assess the accuracy of the reanalysis, a set of comparisons between the reanalysis results and the free run results was performed. The root mean square deviations (RMSDs) between the reanalysis results and not-yet-assimilated observations at all levels show that, compared to the free run, temperature and salinity have been improved significantly, that is, by 31.1 and 38.8%, respectively. The vertical structure of the reanalyzed fields is also adjusted. The reanalysis results show that the improvements in both temperature and salinity are smaller at greater water depths. Comparison with independent CTD data, the reanalysis significantly improved temperatures and salinities in all layers relative to the free run. For temperature and salinity during the period of ship voyages, the RMSDs are reduced by 32.9 and 25.5%, respectively. The temporal variations of the deep-water salinity caused by saltwater inflows are better captured by the reanalysis than by the free run. Moreover, the reanalysis improved the estimation of the depth of the halocline and thermocline, which are overestimated in the simulation without data assimilation.

  • 7.
    Liu, Ye
    et al.
    SMHI, Research Department, Oceanography.
    Meier, Markus
    SMHI, Research Department, Oceanography.
    Eilola, Kari
    SMHI, Research Department, Oceanography.
    Improving the multiannual, high-resolution modelling of biogeochemical cycles in the Baltic Sea by using data assimilation2014In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 66, article id 24908Article in journal (Refereed)
    Abstract [en]

    The impact of assimilating temperature, salinity, oxygen, phosphate and nitrate observations on marine ecosystem modelling is assessed. For this purpose, two 10-yr (1970-1979) reanalyses of the Baltic Sea are carried out using the ensemble optimal interpolation (EnOI) method and a coupled physical-biogeochemical model of the Baltic Sea. To evaluate the reanalyses, climatological data and available biogeochemical and physical in situ observations at monitoring stations are compared with results from simulations with and without data assimilation. In the first reanalysis, only observed temperature and salinity profiles are assimilated, whereas biogeochemical observations are unused. Although simulated temperature and salinity improve considerably as expected, the quality of simulated biogeochemical variables does not improve and deep water nitrate concentrations even worsen. This unexpected behaviour is explained by a lowering of the halocline in the Baltic proper due to the assimilation causing increased oxygen concentrations in the deep water and consequently altered nutrient fluxes. In the second reanalysis, both physical and biogeochemical observations are assimilated and good quality in all variables is found. Hence, we conclude that if a data assimilation method like the EnOI is applied, all available observations should be used to perform reanalyses of high quality for the Baltic Sea biogeochemical state estimates.

  • 8.
    Liu, Ye
    et al.
    SMHI, Research Department, Oceanography.
    Meier, Markus
    SMHI, Research Department, Oceanography.
    Eilola, Kari
    SMHI, Research Department, Oceanography.
    Nutrient transports in the Baltic Sea - results from a 30-year physical-biogeochemical reanalysis2017In: Biogeosciences, ISSN 1726-4170, E-ISSN 1726-4189, Vol. 14, no 8, p. 2113-2131Article in journal (Refereed)
  • 9.
    Meier, Markus
    et al.
    SMHI, Research Department, Oceanography.
    Eilola, Kari
    SMHI, Research Department, Oceanography.
    Almroth-Rosell, E.
    Schimanke, Semjon
    SMHI, Research Department, Oceanography.
    Kniebusch, M.
    Höglund, Anders
    SMHI, Research Department, Oceanography.
    Pemberton, Per
    SMHI, Research Department, Oceanography.
    Liu, Ye
    SMHI, Research Department, Oceanography.
    Väli, Germo
    SMHI, Research Department, Oceanography.
    Saraiva, S.
    Disentangling the impact of nutrient load and climate changes on Baltic Sea hypoxia and eutrophication since 1850 (vol 53, pg 1145, 2019)2019In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 53, no 1-2, p. 1167-1169Article in journal (Refereed)
  • 10.
    Meier, Markus
    et al.
    SMHI, Research Department, Oceanography.
    Eilola, Kari
    SMHI, Research Department, Oceanography.
    Almroth-Rosell, Elin
    SMHI, Research Department, Oceanography.
    Schimanke, Semjon
    SMHI, Research Department, Oceanography.
    Kniebusch, M.
    Höglund, Anders
    SMHI, Research Department, Oceanography.
    Pemberton, Per
    SMHI, Research Department, Oceanography.
    Liu, Ye
    SMHI, Research Department, Oceanography.
    Väli, Germo
    SMHI, Research Department, Oceanography.
    Saraiva, S.
    Disentangling the impact of nutrient load and climate changes on Baltic Sea hypoxia and eutrophication since 18502019In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 53, no 1-2, p. 1145-1166Article in journal (Refereed)
  • 11. Placke, Manja
    et al.
    Meier, Markus
    SMHI, Research Department, Oceanography.
    Graewe, Ulf
    Neumann, Thomas
    Frauen, Claudia
    Liu, Ye
    SMHI, Research Department, Oceanography.
    Long-Term Mean Circulation of the Baltic Sea as Represented by Various Ocean Circulation Models2018In: Frontiers in Marine Science, E-ISSN 2296-7745, Vol. 5, article id UNSP 287Article in journal (Refereed)
1 - 11 of 11
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.35.7
|