Following publications have been announced by our department Hydrodynamics and Data Assimilation. For further information please contact Dr Joanna Staneva, co-author of the publications:
Abdalla, S., Abdeh Kolahchi, A., Ablain, M., …, Stanev, E., Staneva, J., et al. (2021): Altimetry for the future: Building on 25 years of progress. International Altimetry Team in: Advances in Space Research, 2021, doi:10.1016/j.asr.2021.01.022
Abstract:
In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology.
The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion.
Chen, W., Schulz-Stellenfleth, J., Grayek, S., & Staneva, J. (2021): Impacts of the assimilation of satellite sea surface temperature data on volume and heat budget estimates for the North Sea. Journal of Geophysical Research: Oceans, 126, e2020JC017059, doi:10.1029/2020JC017059
Abstract:
Mechanisms controlling the heat budget of the North Sea are investigated based on a combination of satellite sea surface temperature measurements and numerical model simulations. Lateral heat fluxes across the shelf edge and into the Baltic Sea as well as vertical ocean-atmosphere heat exchange are considered. A 3-D variational (3DVAR) data assimilation (DA) scheme is applied, which contains assumed model error correlations that depend on the mixed layer depth derived from a coupled circulation/ocean wave model. The analysis balances pressure gradients introduced by temperature modifications. Significant hydrodynamic model response to DA was found, which should be considered in the heat budget estimations. The observed change of the current velocity field decreases the lateral advective volume/heat exchanges between the North Sea and the Atlantic, yielding an increased heat flux from the Atlantic into the North Sea and more heat flux from the sea to the atmosphere. The largest DA impact on volume/heat transport is in the Norwegian Channel, where the dominant process is Eulerian transport, followed by tidal pumping and wind pumping. Further analysis reveals an acceleration of the along-shelf current at the northern edge of the North Sea, a decrease in the horizontal pressure gradient from the Atlantic to the North Sea, and a reduction of the Eulerian transport of volume/heat outward the North Sea. Furthermore, the coupling between the circulation model and the wave model has significant impacts on lateral heat advection in the DA run, which is due to the wave impact on the mixed layer depth.
Plain Language Summary:
Seawater temperature simulations are important for climate change research, fishery management, coastline protection, ecological balance maintenance, and weather predictions. To improve the seawater temperature prediction capability, a data assimilation (DA) scheme is often applied to combine data from measurements, such as from satellites, buoys, and ships, with data provided by climate models that consider circulation, wave, atmosphere, and ice components. For decades, various DA methods have been developed with a focus on implementing sophisticated mathematical techniques. However, few studies have focused on the impacts of DA on physical processes and the secondary effects of DA. We used a model and satellite data to investigate the impacts of sea surface temperature (SST) assimilations on the volume and heat budgets over the North Sea. We found that DA improved SST modeling, thereby modifying the volume and heat budgets between the North Sea and the Atlantic. The largest change occurs at the Norwegian Channel, where the total water/heat transport from the North Sea outward is reduced. Moreover, SST assimilation also changes the air-sea heat exchange. This study improves our understanding of the relations between model physics and DA.