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  • 1
    In: Ocean Science, Copernicus GmbH, Vol. 14, No. 5 ( 2018-09-25), p. 1093-1126
    Abstract: Abstract. Since 19 October 2016, and in the framework of Copernicus Marine Environment Monitoring Service (CMEMS), Mercator Ocean has delivered real-time daily services (weekly analyses and daily 10-day forecasts) with a new global 1∕12∘ high-resolution (eddy-resolving) monitoring and forecasting system. The model component is the NEMO platform driven at the surface by the IFS ECMWF atmospheric analyses and forecasts. Observations are assimilated by means of a reduced-order Kalman filter with a three-dimensional multivariate modal decomposition of the background error. Along-track altimeter data, satellite sea surface temperature, sea ice concentration, and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for numerical ocean forecasting. A 3D-VAR scheme provides a correction for the slowly evolving large-scale biases in temperature and salinity. This paper describes the recent updates applied to the system and discusses the importance of fine tuning an ocean monitoring and forecasting system. It details more particularly the impact of the initialization, the correction of precipitation, the assimilation of climatological temperature and salinity in the deep ocean, the construction of the background error covariance and the adaptive tuning of observation error on increasing the realism of the analysis and forecasts. The scientific assessment of the ocean estimations are illustrated with diagnostics over some particular years, assorted with time series over the time period 2007–2016. The overall impact of the integration of all updates on the product quality is also discussed, highlighting a gain in performance and reliability of the current global monitoring and forecasting system compared to its previous version.
    Type of Medium: Online Resource
    ISSN: 1812-0792
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2018
    detail.hit.zdb_id: 2183769-7
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  • 2
    In: Natural Hazards and Earth System Sciences, Copernicus GmbH, Vol. 22, No. 4 ( 2022-04-12), p. 1301-1324
    Abstract: Abstract. To improve high-resolution numerical environmental prediction, it is essential to represent ocean–atmosphere interactions properly, which is not the case in current operational regional forecasting systems used in western Europe. The objective of this paper is to present a new forecast-oriented coupled ocean–atmosphere system. This system uses the state-of-the-art numerical models AROME (cy43t2) and NEMO (v3.6) with a horizontal resolution of 2.5 km. The OASIS coupler (OASIS3MCT-4.0), implemented in the SurfEX surface scheme and in NEMO, is used to perform the communications between models. A sensitivity study of this system is carried out using 7 d simulations from 12 to 19 October 2018, characterized by extreme weather events (storms and heavy precipitation) in the area of interest. Comparisons with in situ and L3 satellite observations show that the fully coupled simulation reproduces the spatial and temporal evolution of the sea surface temperature and 10 m wind speed quantitatively well. Sensitivity analysis of ocean–atmosphere coupling shows that the use of an interactive and high-resolution sea surface temperature (SST), in contrast to actual numerical weather prediction (NWP) where SST is constant, modifies the atmospheric circulation and the location of heavy precipitation. Simulated oceanic fields show a large sensitivity to coupling when compared to the operational ocean forecast. The comparison to two distinct forced ocean simulations highlights that this sensitivity is mainly controlled by the change in the atmospheric model used to drive NEMO (AROME vs. IFS operational forecast), and less by the interactive air–sea exchanges. In particular, the oceanic boundary layer depths can vary by more than 40  % locally, between the two ocean-only experiments. This impact is amplified by the interactive coupling and is attributed to positive feedback between sea surface cooling and evaporation.
    Type of Medium: Online Resource
    ISSN: 1684-9981
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2069216-X
    detail.hit.zdb_id: 2064587-9
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  • 3
    Online Resource
    Online Resource
    Copernicus GmbH ; 2018
    In:  Ocean Science Vol. 14, No. 6 ( 2018-11-16), p. 1405-1421
    In: Ocean Science, Copernicus GmbH, Vol. 14, No. 6 ( 2018-11-16), p. 1405-1421
    Abstract: Abstract. The impact of forthcoming wide-swath altimetry missions on the ocean analysis and forecasting system was investigated by means of OSSEs (observing system simulation experiments). These experiments were performed with a regional data assimilation system, implemented in the Iberian–Biscay–Ireland (IBI) region, at 1∕12∘ resolution using simulated observations derived from a fully eddy-resolving free simulation at 1∕36∘ resolution over the same region. The objective of the experiments was to assess the ability of different satellite constellations to constrain the ocean analyses and forecasts, considering both along-track altimeters and future wide-swath missions; consequently, the capability of the data assimilation techniques used in the Mercator Ocean operational system to effectively combine the different kinds of measurements was also investigated. These assessments were carried out as part of a European Space Agency (ESA) study on the potential role of wide-swath altimetry in future versions of the European Union Copernicus programme. The impact of future wide-swath altimetry data is evident for investigating the reliability of sea level values in OSSEs. The most significant results were obtained when looking at the sensitivity of the system to wide-swath instrumental error: considering a constellation of three nadir and two “accurate” (small instrumental error) wide-swath altimeters, the error in ocean analysis was reduced by up to 50 % compared to conventional altimeters. Investigating the impact of the repetitivity of the future measurements, the results showed that two wide-swath missions had a major impact on sea-level forecasting – increasing the accuracy over the entire time window of the 5-day forecasts – compared with a single wide-swath instrument. A spectral analysis underlined that the contributions of wide-swath altimetry data observed in ocean analyses and forecast statistics were mainly due to the more accurate resolution, compared with along-track data, of ocean variability at spatial scales smaller than 100 km. Considering the ocean currents, the results confirmed that the information provided by wide-swath measurements at the surface is propagated down the water column and has a considerable impact (30 %) on ocean currents (up to a depth of 300 m), compared with the present constellation of altimeters. The ocean analysis and forecasting systems used here are those currently used by the Copernicus Marine Environment and Monitoring Service (CMEMS) to provide operational services and ocean reanalysis. The results obtained in the OSSEs considering along-track altimeters were consistent with those derived from real data (observing system experiments, OSEs). OSSEs can also be used to assess the potential of new observing systems, and in this study the results showed that future constellations of altimeters will have a major impact on constraining the CMEMS ocean analysis and forecasting systems and their applications.
    Type of Medium: Online Resource
    ISSN: 1812-0792
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2018
    detail.hit.zdb_id: 2183769-7
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  • 4
    In: The Cryosphere, Copernicus GmbH, Vol. 15, No. 12 ( 2021-12-10), p. 5483-5512
    Abstract: Abstract. Although snow depth on sea ice is a key parameter for sea ice thickness (SIT) retrieval, there currently does not exist reliable estimations. In the Arctic, nearly all SIT products use a snow depth climatology (the modified Warren-99 climatology, W99m) constructed from in situ data obtained prior to the first significant impacts of climate change. In the Antarctic, the lack of information on snow depth remains a major obstacle in the development of reliable SIT products. In this study, we present the latest version of the altimetric snow depth (ASD) product computed over both hemispheres from the difference of the radar penetration into the snow pack between the Ka-band frequency SARAL/Altika and the Ku-band frequency CryoSat-2. The ASD solution is compared against a wide range of snow depth products including model data (Pan-Arctic Ice-Ocean Modelling and Assimilation System (PIOMAS) or its equivalent in the Antarctic the Global Ice-Ocean Modeling and Assimilation System (GIOMAS), the MERCATOR model, and NASA's Eulerian Snow On Sea Ice Model (NESOSIM, only in the Arctic)), the Advanced Microwave Scanning Radiometer-2 (AMSR2) passive radiometer data, and the Dual-altimeter Snow Thickness (DuST) Ka–Ku product (only in the Arctic). The ASD product is further validated in the Arctic against the ice mass balance (IMB) buoys, the CryoSat Validation Experiment (CryoVEx) and Operation Ice Bridge's (OIB) airborne measurements. These comparisons demonstrate that ASD is a relevant snow depth solution, with spatiotemporal patterns consistent with those of the alternative Ka–Ku DuST product but with a mean bias of about 6.5 cm. We also demonstrate that ASD is consistent with the validation data: comparisons with OIB's airborne snow radar in the Arctic during the period of 2014–2018 show a correlation of 0.66 and a RMSE of about 6 cm. Furthermore, a first-guess monthly climatology has been constructed in the Arctic from the ASD product, which shows a good agreement with OIB during 2009–2012. This climatology is shown to provide a better solution than the W99m climatology when compared with validation data. Finally, we have characterised the SIT uncertainty due to the snow depth from an ensemble of SIT solutions computed for the Arctic by using the different snow depth products previously used in the comparison with the ASD product. During the period of 2013–2019, we found a spatially averaged SIT mean standard deviation of 20 cm. Deviations between SIT estimations due to snow depths can reach up to 77 cm. Using the ASD data instead of W99m to estimate SIT over this time period leads to a reduction in the average SIT of about 30 cm.
    Type of Medium: Online Resource
    ISSN: 1994-0424
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
    detail.hit.zdb_id: 2393169-3
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