Publications
Following publications have been announced by our Institute of Coastal Systems – Analysis and Modeling. For further information please contact the marked authors of the publications:
Lin, L., von Storch, H., Guo, D., Tang, S., Zheng, P., & Chen, X. (2022): The effect of tides on internal variability in the Bohai and Yellow Sea. Dynamics of Atmospheres and Oceans, Volume 98, 101301, doi:10.1016/j.dynatmoce.2022.101301
Abstract:
The hydrodynamics of marginal seas exhibit internal variability unprovoked by external forcing. To date, the role of tides in reducing this “noise” has not been evaluated. We investigated the effect of tides on internal variability in the Bohai and Yellow Sea. To do so, we conducted three ensembles of numerical experiments using the three-dimensional Finite-Volume Coastal Ocean Model (FVCOM) with tidal forcing, with “half-tidal” forcing, and without tidal forcing, while everything else was unchanged, and determined the intensity of the signal-to-noise ratio (hereinafter referred to as the S/N ratio), with the “signal” represented by the variance of the coherent variations of the different simulations subject to the same atmospheric variability and the noise represented by the intra-ensemble variance. The S/N ratio was determined for depth-averaged velocities, surface temperature, and surface salinity. The first result was that in all three ensembles, noise emerged but with different intensities. In the ensemble with tidal forcing, unprovoked variability emerged primarily at smaller scales. When the tides were weakened or turned off, the S/N ratios were reduced, more so in the Yellow Sea than in the Bohai. The increase in the S/N ratio was largest for large scales and for depth-averaged velocity. The reduction in tidal forcing resulted in an approximately 30% increase in S/N ratios in the Bohai at large scales. Thus, the absence of tidal forcing favored the emergence of increased unprovoked variability at large and medium scales but not at small scales. A hypothesis for explaining this scale-selective effect of tides, based on the stochastic climate model, is suggested.
Wahl, E., Zorita, E., & Hoell, A. (2022): The Kalman Filter as Post-Processor for Analog Data-Model Assimilation in Paleoclimate Reconstruction. Journal of Climate, doi:10.1175/JCLI-D-21-0454.1
Abstract:
We present an off-line paleo-data assimilation methodology that formally combines the analog assimilation method (AA) and the Kalman Filter (KF), utilizing the KF as a post-processor of the AA output. This methodology can be applied to reconstruct climate fields that are spatially separated from proxy-based reconstructions by using the spatial co-variability generated by a climate model. Our method is applied to a set of spatially resolved and spatially consistent climate reconstructions of several variables reflecting different seasons, incorporating the application of methodological variants that have undergone rigorous testing in terms of both improving statistical methodology and physical interpretation. This contrasts with applications primarily based on transfer relationships of annual means of local, single variable or bivariate, climate model priors into paleo proxy states. The gains from adding the KF post-processor are modest in our test case of reconstructing sea level pressure (SLP) geopotential height fields in the northeast Pacific, utilizing paleoclimatic temperature and moisture reconstructions in western North America. Notably, SLP reconstruction skill is enhanced in the oceanic region south of Alaska that is strongly associated with wet winters in western North America. The results suggest the AA method is approaching optimality in this test case, driven by the quality of the paleoreconstruction information used to drive the AA process, along with the realism of the climate model employed, to which the KF post-processing step is added. The derived reconstructions are then used for evaluation of the relationship between winter SLP and precipitation in California over the past ∼450 years.
Thewes, D., Stanev, E.V., & Zielinski, O. (2022): Steps Toward Modelling the Past and Future North Sea Ecosystem With a Focus on Light Climate. Front. Mar. Sci., 9:818383, doi:10.3389/fmars.2022.818383
Abstract:
With ongoing manmade climate change, it is important to understand its impact on regional ecosystems. Furthermore, it is known that the North Sea light climate is subject to ongoing change. The combined effects of climate change and coastal darkening are investigated in this work. We used a three-dimensional ecosystem model, forced with data from a climate model, to project three plausible biogeochemical states for the years 2050–2054, following three representative concentration and shared socioeconomic pathways (RCP2.6-SSP1, RCP4.5-SSP2 and RCP8.5-SSP5). We also performed a historic experiment for the years 1950–1954 and 2000–2004 for comparison. Our results suggest significant reductions of phytoplankton biomass as a consequence of sinking nutrient levels for all future scenarios. Additionally, a modelling study was carried out, in which we raised background SPM levels by 40% to reflect potential changes in the future. This revealed that for RCP2.6-SSP1, the ecosystem is more sensitive to changes in the light climate than for the other scenarios, due to higher nutrient availability.
