MERIS Case II water processor comparison on coastal sites of the northern Baltic Sea

Attila, Jenni; Koponen, Sampsa; Kallio, Kari; Lindfors, Antti; Kaitala, Seppo; Ylöstalo, Pasi

doi:10.1016/j.rse.2012.07.009

Cited by 62 publications

(68 citation statements)

References 37 publications

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“…The satellite-derived surface concentration of CHL is an important measure of the amount of phytoplankton, but is known to have large errors in the Baltic Sea (Darecki and Stramski, 2004;Attila et al, 2013). This is due both to problems in the atmospheric correction procedures and in the separation of phytoplankton pigments from the CDOM.…”

Section: Near-surface Chlorophyll Amentioning

confidence: 99%

Changing seasonality of the Baltic Sea

2016

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Abstract. Changes in the phenology of physical and ecological variables associated with climate change are likely to have significant effect on many aspects of the Baltic ecosystem. We apply a set of phenological indicators to multiple environmental variables measured by satellite sensors for 17-36 years to detect possible changes in the seasonality in the Baltic Sea environment. We detect significant temporal changes, such as earlier start of the summer season and prolongation of the productive season, in several variables ranging from basic physical drivers to ecological status indicators. While increasing trends in the absolute values of variables like sea-surface temperature (SST), diffuse attenuation of light (Ked490) and satellite-detected chlorophyll concentration (CHL) are detectable, the corresponding changes in their seasonal cycles are more dramatic. For example, the cumulative sum of 30 000 W m −2 of surface incoming shortwave irradiance (SIS) was reached 23 days earlier in 2014 compared to the beginning of the time series in 1983. The period of the year with SST of at least 17 • C has almost doubled (from 29 days in 1982 to 56 days in 2014), and the period with Ked490 over 0.4 m −1 has increased from about 60 days in 1998 to 240 days in 2013 -i.e., quadrupled. The period with satellite-estimated CHL of at least 3 mg m −3 has doubled from approximately 110 days in 1998 to 220 days in 2013. While the timing of both the phytoplankton spring and summer blooms have advanced, the annual CHL maximum that in the 1980s corresponded to the spring diatom bloom in May has now shifted to the summer cyanobacteria bloom in July.

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Section: Near-surface Chlorophyll Amentioning

confidence: 99%

Changing seasonality of the Baltic Sea

2016

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“…Long-term data derived from ocean colour satellites, for instance, MODIS-Aqua, offer an unparalleled tool for synoptic surface chlorophyll-a concentration (chla) associated with high (near daily) sampling frequencies, thus providing data at the required resolution for improving ecosystem-based fisheries management [2,3]. However, effective use of these data has some challenges, including effective removal of atmospheric interference from at-sensor signals and development of robust satellite-based chla algorithms [4][5][6]. Many models are available for atmospheric correction (e.g., [7][8][9][10][11]) and chla retrieval (e.g., [4] for a review of several methods) from ocean colour images.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data

et al. 2017

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Abstract:There is an increasing need for satellite-derived accurate chlorophyll-a concentration (chla) products to improve fisheries management in coastal regions. However, the methods used to derive these products have to be evaluated, so the associated uncertainties are known. The performance of three atmospheric correction methods, the near infrared (NIR), the shortwave infrared (SWIR), and the Management Unit of the North Seas Mathematical Models with an additional modification (MUMM + SWIR), and derived chla products based on the Moderate Resolution Imaging Spectroradiometer AQUA (MODIS) images acquired from 2002 to 2014 over the west coast of Canada and the United States were evaluated. The atmospherically corrected products and above-water reflectance were compared with in situ AERONET (N~650) and above-water reflectance (N~34) data, and the Ocean Color 3 MODIS (OC3M)-derived chla were compared with in situ chla measurements (N~82). The statistical analysis indicated that the MUMM + SWIR method was the most appropriate for this region, with relatively good retrievals of the atmospheric products, improved retrieval of remote sensing reflectance with bias lower than 20% for the OC3M bands, and improved retrievals of chla (r = 0.83, slope = 0.89, log RMSE = 0.33 mg m −3 for ±1 h). The poorest chla retrievals were achieved with the SWIR and NIR methods. These results represent the most comprehensive satellite data analysis of MODIS retrievals for this region and provide a framework for the MUMM + SWIR method that can be further tested in other coastal regions of the world.

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“…In recent years, a number of algorithms have been devised to retrieve different water optical parameters, including water clarity, from satellite observations for coastal (ocean) and lake waters (Attila et al, 2013;Binding et al, 2007;Binding et al, 2015;Olmanson et al, 2013;Potes et al, 2012;Wu et al, 2009;Zhao et al, 2011;Zolfaghari and Duguay, 2016). Turbid inland and coastal waters are optically more complex compared to open ocean, and large optical gradients exist.…”

Section: Introductionmentioning

confidence: 99%

Satellite-derived light extinction coefficient and its impact on thermal structure simulations in a 1-D lake model

Zolfaghari

Duguay

Pour

2017

Hydrol. Earth Syst. Sci.

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Abstract.A global constant value of the extinction coefficient (K d ) is usually specified in lake models to parameterize water clarity. This study aimed to improve the performance of the 1-D freshwater lake (FLake) model using satellite-derived K d for Lake Erie. The CoastColour algorithm was applied to MERIS satellite imagery to estimate K d . The constant (0.2 m −1 ) and satellite-derived K d values as well as radiation fluxes and meteorological station observations were then used to run FLake for a meteorological station on Lake Erie. Results improved compared to using the constant K d value (0.2 m −1 ). No significant improvement was found in FLake-simulated lake surface water temperature (LSWT) when K d variations in time were considered using a monthly average. Therefore, results suggest that a timeindependent, lake-specific, and constant satellite-derived K d value can reproduce LSWT with sufficient accuracy for the Lake Erie station.A sensitivity analysis was also performed to assess the impact of various K d values on the simulation outputs. Results show that FLake is sensitive to variations in K d to estimate the thermal structure of Lake Erie. Dark waters result in warmer spring and colder fall temperatures compared to clear waters. Dark waters always produce colder mean water column temperature (MWCT) and lake bottom water temperature (LBWT), shallower mixed layer depth (MLD), longer ice cover duration, and thicker ice. The sensitivity of FLake to K d variations was more pronounced in the simulation of MWCT, LBWT, and MLD. The model was particularly sensitive to K d values below 0.5 m −1 . This is the first study to assess the value of integrating K d from the satellite-based CoastColour algorithm into the FLake model. Satellite-derived K d is found to be a useful input parameter for simulations with FLake and possibly other lake models, and it has potential for applicability to other lakes where K d is not commonly measured.

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MERIS Case II water processor comparison on coastal sites of the northern Baltic Sea

Cited by 62 publications

References 37 publications

Changing seasonality of the Baltic Sea

Changing seasonality of the Baltic Sea

Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data

Satellite-derived light extinction coefficient and its impact on thermal structure simulations in a 1-D lake model

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