Variability of the baroclinic Rossby radius in the Gulf of Finland

Alenius, Pekka; Некрасов, А. В.; Myrberg, Kai

doi:10.1016/s0278-4343(03)00004-9

Cited by 74 publications

(50 citation statements)

References 7 publications

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“…The correlation length scale, to some extent, depends on the dynamics of the basin, more precisely, on the Rossby radius of deformation, which varies from ∼200 km in the barotropic mode to ∼10 km or even less in the baroclinic mode (Alenius et al, 2003;Fennel et al, 1991). In every particular location of the North and Baltic Seas, the SST data error correlation length scale might be determined by the energy superposition of the baroclinic and barotropic flows.…”

Section: Observational Errorsmentioning

confidence: 99%

Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Inference about the data

Losa

Danilov

Schröter

et al. 2012

Journal of Marine Systems

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The operational ocean prediction model for the North and Baltic Seas of the German Maritime and Hydrographic Agency (BSH) is augmented with a multivariate data assimilation (DA) system. We report on the implementation and performance of the scheme which is based on ensemble forecasting. 2011. The quality of the predicted fields that were not assimilated (velocities, sea level and salinity) is preserved as is confirmed by independent in situ data.The results have required adjustment of the conditional data error statistics.The experiments conducted with different timing and frequency of data assimilation and variable forecasting periods show that the DA system corrects systematic model uncertainties and, due to memory to the corrections, improves prediction over periods of up to 5 days. The results also explicitly illustrate a lower quality of the AVHRR daytime product and reveal low informative influence of the data on the forecasting system when daytime SSTs are assimilated additionally to midnight observations.

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Section: Observational Errorsmentioning

confidence: 99%

Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Inference about the data

Losa

Danilov

Schröter

et al. 2012

Journal of Marine Systems

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“…Alenius et al 2003). The two-layer L R (Rossby 1938;Gill 1982) was calculated for each CTD cast station as…”

Section: Survey Area and Designmentioning

confidence: 99%

Vertical Distribution of Age‐0 Walleye Pollock during Late Summer: Environment or Ontogeny?

et al. 2015

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Variability in the late‐summer vertical distribution of age‐0 Walleye Pollock Gadus chalcogrammus in the southeastern Bering Sea has been attributed to a range of physical and biological factors. Using acoustic data (38 and 120 kHz) collected during the 2010 Bering Aleutian Salmon International Survey (BASIS) and dedicated high‐resolution surveys (HR1 and HR2), we evaluated whether late‐summer distributions could be explained by water column properties (environment) or whether sampling was likely occurring during the ontogenetic shift of age‐0 Walleye Pollock from near‐surface habitat to demersal habitat (ontogeny). Neither water column attributes (temperature, relative temperature, salinity, dissolved oxygen, and density gradient) nor the acoustic density of zooplankton prey strongly predicted the acoustic estimates of age‐0 Walleye Pollock vertical presence or density. At 6 of 10 paired BASIS–HR1 stations, age‐0 Walleye Pollock shifted deeper in the water column between BASIS sampling and the HR1 sampling conducted 8–34 d later. There were no consistent differences in FL (P > 0.05 for 2 of 4 station pairs) or energy density (P > 0.05 for 3 station pairs) between age‐0 Walleye Pollock caught in near‐surface trawls and those caught in midwater trawls. Our data suggest that the observation of both near‐surface and midwater age‐0 Walleye Pollock during late summer is likely due to an ontogenetic habitat shift; however, the causative factor was not clear given the limited sample sizes and explanatory variables. The timing of the ontogenetic shift, which appears to have begun before August 18, 2010, can ultimately affect survey strategies, and knowledge of this timing can provide additional insight into factors affecting the overwinter survival of age‐0 Walleye Pollock. Received December 5, 2014; accepted May 10, 2015

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“…the whole Gulf of Finland) with reasonable degree of approximation (Figure 2), it fails in resolving certain meso-scale hydrodynamic phenomena, such as upwelling and the related baroclinic coastal jets. The typical width (cross-section extension) of coastal upwelling is mainly determined by the barcoclinic (internal) Rossby radius, which in this part of the Baltic Sea ought to be (also depending on stratification conditions) around 1-5 km [11,12]. The width of the upwelling can be larger due to lateral spread of upwelled water and formation of filaments, though.…”

Section: Influence Of Hydrodynamic Situation On Oil Spillmentioning

confidence: 99%

Bayesian inference for oil spill related Net Environmental Benefit Analysis

Aps

Herkül

Kotta

et al. 2009

WIT Transactions on Ecology and the Environment

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This paper investigates the applicability of Bayesian inference to oil spill related situation assessment in order to facilitate the Net Environmental Benefit Analysis (NEBA) based decisions in evaluating the threat or probable overall environmental impact of the spill. Bayesian networks are believed to be useful in integrating the NEBA related information imported from 1) oil spill scene surveillance, 2) simulation results on an oil spill incident with human response, and 3) ecological sensitivity maps. This paper exemplifies the use of Bayesian Belief Networks in answering the questions: can the oil spill be combated at sea, and if it cannot then is the oil threatening a sensitive environment?

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Variability of the baroclinic Rossby radius in the Gulf of Finland

Cited by 74 publications

References 7 publications

Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Inference about the data

Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: Inference about the data

Vertical Distribution of Age‐0 Walleye Pollock during Late Summer: Environment or Ontogeny?

Bayesian inference for oil spill related Net Environmental Benefit Analysis

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