Lasse H. Pettersson

Water quality remote sensing in the visible spectrum

The development of water quality retrieval algorithms is discussed in terms of causal dependence of the upwelling spectral radiance upon the water composition. Unlike clear marine/oceanic waters, for which linear regression retrieval relationships are valid, inland and coastal zone water masses with a high degree of optical complexity necessitate the development of more subtle retrieval approaches. At the basis of such approaches are models considering the conjoint optical impact of several co-existing aquatic components on the water leaving radiance spectral distribution. Such a model for Lake Ladoga is described. Monte Carlo simulations have been performed to analyse the spectral and angular variations of the upwelling radiance scattered by the water column into the atmosphere. Optimal conditions for conducting water quality remote sensing in case of natural waters of various optical complexity are explored and relevant recommendations are formulated.

Satellite earth observation in operational oceanography

The role and contribution of satellite data in operational oceanography is reviewed, with emphasis on northern European seas. The possibility to observe various ocean parameters and processes by existing satellite sensors, such as optical instruments, infrared radiometers, passive microwave radiometers, and active microwave systems (altimeter, scatterometer, SAR) is discussed. The basic parameters are: sea-surface temperature observed by infrared radiometers, ocean colour by spectrometers, sea-surface elevation by altimeters, and surface roughness by active and passive microwave systems, which can be used to derive surface wind and waves. A number of ocean processes can be derived from synoptic mapping of the basic parameters of larger sea areas, such as current patterns, fronts, eddies, water mass distribution, and various water quality parameters (chlorophyll, surface slicks, suspended sediments). The suitability of existing satellite data to fulfil the operational requirements for temporal and spatial coverage, data delivery in near-real-time, and long-term access to data is discussed in light of the fact that optical/infrared data in northern Europe are severely hampered by frequent cloud cover, while microwave techniques can provide useful data independent of weather and light conditions. Finally, the use of data assimilation in oceanographic models is briefly summarised, indicating that this technique is under development and will soon be adopted in operational oceanography.

An advanced algorithm for operational retrieval of water quality from satellite data in the visible

We present a new operational algorithm for the retrieval of water quality from optical remote sensing data for both clear and turbid waters. It contains an array of neural networks providing input for the Levenberg–Marquardt multivariate optimization procedure as the final retrieval tool. With a given accuracy threshold, the developed algorithm is sufficiently robust to data with noise up to 15% for certain hydro‐optical conditions. To avoid inadequate retrieval results, the algorithm identifies and eventually discards the pixels with inadequate atmospheric correction and/or water optical properties incompatible with the applied hydro‐optical model. This procedure also identifies coccolith expressions. Examples of practical applications of the developed algorithm are given.

Barents Sea seasonal ice zone features and processes from ERS 1 synthetic aperture radar: Seasonal Ice Zone Experiment 1992

Sea ice features and processes in the Barents Sea were studied during the Seasonal Ice Zone Experiment 1992 (SIZEX92), a dedicated ERS 1 satellite synthetic aperture radar (SAR) field campaign carried out in March 1992. SIZEX92 was based around the research vessels Polarsyssel and Hakon Mosby. In situ oceanographic, meteorological, and ice measurements were made, coordinated with low-altitude aerial observations and ERS 1 SAR data acquired in near real time. Fifty-eight low-and full-resolution SAR scenes were obtained during SIZEX92, which provided a validation data set for ERS 1 SAR backscatter under winter conditions in the Barents Sea. Analysis of SIZEX92 data has provided geophysical insights, including a better understanding of Barents Sea ice edge freezing processes and ice edge development in response to atmospheric forcings. In particular, areas of new ice formation were found to be related to bathymetric features through their influence on the circulation of Arctic and Atlantic water masses. ERS 1 SAR image sequences revealed rapid, mesoscale variations in new ice areas and the ice edge in response to wind conditions. In addition to geophysical insight, SIZEX92 demonstrated some of the technical capabilities and limitations of ERS 1 SAR to identify new ice areas, the ice edge, ice floes, and ice types. Mapping new ice areas using satellite SAR data may be considered the most promising new application. The limitations of ERS-1 SAR-derived ice classification and ice motion estimates in the marginal ice zone are identified.

Semi-empirical Algorithm for the Retrieval of Ecology-Relevant Water Constituents in Various Aquatic Environments

An advanced operational semi-empirical algorithm for processing satellite remote sensing data in the visible region is described. Based on the Levenberg-Marquardt multivariate optimization procedure, the algorithm is developed for retrieving major water colour producing agents: chlorophyll-a, suspended minerals and dissolved organics. Two assurance units incorporated by the algorithm are intended to flag pixels with inaccurate atmospheric correction and specific hydro-optical properties not covered by the applied hydro-optical model. The hydro-optical model is a set of spectral cross-sections of absorption and backscattering of the colour producing agents. The combination of the optimization procedure and a replaceable hydro-optical model makes the developed algorithm not specific to a particular satellite sensor or a water body. The algorithm performance efficiency is amply illustrated for SeaWiFS, MODIS and MERIS images over a variety of water bodies.

Inter-comparison of ocean colour data products during algal blooms in the Skagerrak

Several ocean colour (OC) Earth observation (EO) sensors are presently collecting data on an operational basis, including the Envisat MERIS sensor. This study aims at quantifying the differences in performance of the ocean colour EO sensors MERIS, MODIS/Aqua, and SeaWiFS for coastal monitoring and for the particular case of coastal algal bloom situations. The standard chlorophyll a, and radiance and reflectance products from the three sensors have been processed and compared for data acquired during the development of an early-spring algal bloom in 2004 in the eastern North Sea region. The study shows a high level of consistency between the Case 1 water Chl a products for all sensors. We conclude that the use of MERIS Chl a and other relevant products enable continued and possibly improved performance of an existing system for harmful algal bloom (HAB) detection and monitoring which up to December 2004 has been based on SeaWiFS.

SeaWiFS maps water quality parameters of the White Sea

SeaWiFS maps water quality parameters of the White Sea D. Pozdnyakov a , L. Pettersson b , O. M. Johannessen b , A. Liaskovski a , N. Filatov c & L. Bobylev a b a Nansen International Environmental and Remote Sensing Centre, 26/28 Bolshaya Monetnaya, 197101, St. Petersburg, Russia b Nansen Environmental and Remote Sensing Centre, Edvard Griegsvei 3A, N-5059 Bergen, Norway c Northern Water Problems Institute, Alexander Nevsky, 50, 183 030, Petrozavodsk, Russia

MODIS evidences the river run-off impact on the Kara Sea trophy

MODIS evidences the river run‐off impact on the Kara Sea trophy D. V. Pozdnyakov a , A. A. Korosov a , L. H. Pettersson b & O. M. Johannessen b c a Scientific Foundation ‘Nansen International Environmental and Remote Sensing Centre’, 26/28 Bolshaya Monetnaya, 197101 St Petersburg, Russia b Nansen Environmental and Remote Sensing Center, Thormolhensgate 47, N‐5006 Bergen, Norway c Mohn‐Sverdrup Center for Global Ocean Studies and Operational Oceanography, Thormolhensgate 47, N‐5006 Bergen, Norway

Cover ERS-1/2 SAR monitoring of dangerous ice phenomena along the western part of Northern Sea Route

The Northern Sea Route ( NSR) as a part of the Arctic Ocean is very important for sea transportation to the Siberean coastal and river settlements, as well as for future transportation between Europe and the Paci® c Ocean countries. Recent opening of the gigantic oil and gas deposits on the Siberean shelf will require the build-up of a specialeet for eA cient marine oil and gas operations in this area. However, round-the-year navigation as well other marine operations (® shery, mining, oil and gas reconnaissance, etc. ) at the diA erent parts of the Arctic Ocean is a very complicated problem and an optimal choiceof the concrete sea route directions depends on numerous environmental factors. Environmental conditions which determine the high-latitude navigation in the North Pole area depend on seasonal and mean-annual distribution of water masses in the Arctic Ocean. An important factor which inuences marine operations in the Arctic Ocean is the presence of round-the-year ice. This is a complicated regional and global-scale process which depends on the location and properties of basic oceanic massif ice regime, on patterns of seasonal and mean-annual distribution of the basic massif s spurs, on the behaviour of the local ice massifs which in each area of the Arctic Ocean have their own characteristic features of the seasonal and mean-annual variability. The location and drift of the basic oceanic ice massifs spurs are variable para- meters. These spurs consist of the residual ® rst-year ice, and the second-year and multi-year pack iceoes. The thickness of this ice can be more than 3m and its invasion in the NSR area creates an especially dangerous situation for marine operations. Control of this phenomenon by all-weather remote sensing instruments is therefore extremely desirable. Another signi® cant factor which creates the favourable inuence for the ice navigation in the Arctic Ocean is the round-the-year presence of the vast recurring

A new area-specific bio-optical algorithm for the Bay of Biscay and assessment of its potential for SeaWiFS and MODIS/Aqua data merging

Based on a feed-forward and error-back-propagated neural network (NN), a new bio-optical algorithm is developed for the Bay of Biscay. It is designed as a set of NNs individually dedicated to the retrieval of the phytoplankton chlorophyll (chl), and total suspended matter (tsm) from Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua data. The retrieved versus in situ measured concentrations of chl and tsm correlation coefficients for chl proved to be ∼0.8 (SeaWiFS) and 0.72 (MODIS), and for tsm 0.71 (SeaWiFS) and 0.74 (MODIS). The developed NN-based bio-optical algorithms are employed to assess the compatibility of SeaWiFS and MODIS data on chl and tsm in the coastal zone of the Bay of Biscay (case 2 waters). The value of the ratio between the concentration of chl and tsm derived from the same-day SeaWiFS and MODIS data (the overflight time difference, Δt is ≤2.5 hours) has in most cases values of approximately 1, however, in specific cases it varies appreciably. These results indicate that, unlike the reportedly very successful cases of merging of SeaWiFS and MODIS data on chl in open ocean waters (case 1 waters), the merging of chl (and tsm) data from these sensors collected over case 2 waters needs to be supervised at a level of a few pixels. At the same time, when averaged over the entire coastal zone of the Bay of Biscay, the retrieved monthly mean chl and tsm concentrations from SeaWiFS and MODIS practically coincide throughout the years (2002–2004) of contemporaneous operation of these two satellite sensors. Thus, even in the case of such dynamic and optically complex case 2 waters that are inherent in the Bay of Biscay, the potentials for ocean colour data merging are very good. The merging efficiency is assessed and illustrated via documenting the spatio-temporal dynamics of bottom sediment re-suspension in the bay occurring in winter – the season of heaviest cloudiness over the bay.