Detection and Analysis of Fronts in the North Sea
Kirches, Grit¹; Paperin, Michael¹; Klein, Holger²; Brockmann, Carsten¹; Stelzer, Kerstin^1
1Brockmann Consult GmbH, GERMANY; ²Bundesamt für Seeschifffahrt und Hydrographie (Federal Maritime and Hydrographic Agency), GERMANY

Fronts in the ocean are important oceanographic structures, because of their role as boundaries between water masses with different properties and their strong influence on the local dynamic, the dispersion and concentration of substances. Changes in water temperature and density, as well as changes in the wind pattern caused by climate change are likely to influence water mass distribution and hence will be visible in statistical quantities of frontal structures. In the North Sea and in particular in the German Bight two types of fronts are dominant: River Plume Fronts (RPF) between the freshwater entries of the rivers and the intrinsic North Sea water, as well as Tidal Mixing Fronts (TMF) between the seasonally stratified water close to coast and saltier and therefore heavier North Sea water. Other front-like structures are the boundaries between the North Sea water and the Baltic outflow from the Skagerrak, as well as between the inflow of Atlantic water from the North and from the English Channel. A large German national project, KLIWAS, has been initiated by the Federal Ministry of Transport, Building and Urban Development in order to assess the impact of climate change on river, coastal and ocean water ways. The work presented here is part of this initiative and is focussing on evaluating long time series of satellite observations to establish a front climatology of the North Sea, and to study derived statistical quantities with respect to potential climate change impact. The development of algorithms which automatically detect frontal positions and gradients from earth observation (EO) data is an important pre-condition for the processing of long EO data time series which are used to establish a climatology for North Sea fronts. The characteristics of fronts have been used to develop an algorithm for front detection comprising pre-processing steps and the identification of fronts itself. The new proposed algorithm builds upon the state-of-art established Cayula and Cornillion (1992) as well as the Canny (1986) front detection algorithm. The investigation of the specific properties of both algorithms has shown that their combination and some refinements of their subroutines were useful for the front detection in the North Sea. By adjusting this combined algorithm w.r.t. thresholds and scaling, it may be applied to different ocean colour and SST sensors such as MERIS and MODIS for Ocean colour AATSR, AVHHR and MODIS for SST. Applying to sea surface temperature and ocean colour parameters opens the possibility of detecting and investigating frontal positions and gradients and of deriving reliable reference data to assess the impacts of climate change on fronts. The new algorithm has been validated on a synthetic data set and the results were controlled visually afterwards by an expert on selected satellite products. The second phase of the project concentrates on the processing and analysis of a climatological data set of front positions and gradients which can be used as a reference data set. Therefore, ten-year time series of AATSR, MERIS, MODIS and a twenty year time series of AVHRR data have been processed by applying the new algorithm for the North Sea. The proposed algorithm allows an automated processing of comprehensive EO data sets to produce a climatology for front positions and gradients in the North Sea and other shelf sea areas. They also enable the establishment of front maps as an operational downstream product which will help to monitor potential change due to climate change. Canny, 1986, A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6) , pp. 679-698 Cayula and Cornillon, 1992, Edge detection algorithm for SST images, Journal of Atmospheric and Oceanic Technology 9(1), pp. 67-80