Interannual and intra-annual cycles of satellite-derived chlorophyll-a concentrations in the Caspian Sea |
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| Affiliation: | 1. School of Natural Resources & Environment, Lake Superior State University, 650 W. Easterday Ave., Sault Ste. Marie, MI 49783, USA;2. Center for Freshwater Research and Education, Lake Superior State University, 650 W. Easterday Ave., Sault Ste. Marie, MI 49783, USA;1. Limnological Institute, Siberian Branch, Russian Academy of Sciences, 3, Ulan-Batorskaya St., 664033 Irkutsk, Russia;2. Winogradsky Institute of Microbiology, Research Center for Biotechnology, Russian Academy of Sciences, 60 let Oktjabrja pr-t, 7, bld. 2, 119071 Moscow, Russia;1. Hobart and William Smith Colleges, Department of Biology, 300 Pulteney Street, Geneva, NY 14456, USA;2. Finger Lakes Institute, Hobart and William Smith Colleges, Geneva, NY, USA;3. State University of New York College of Environmental Science and Forestry, Department of Environmental Biology, Syracuse, NY, USA;1. Illinois State Geological Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, 701 North Point Drive, Winthrop Harbor, IL 60096, USA;2. Department of Geography, Environment, and Spatial Sciences, Michigan State University, 673 Auditorium Rd., East Lansing, MI 48824;3. Department of Geography and the Environment, Suite G67, Mendel Science Center, Villanova University, 800 E. Lancaster Avenue, Villanova, PA 19085;1. Illinois State Geological Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, 701 North Point Drive, Winthrop Harbor, IL 60096, United States;2. Department of Geography, Michigan State University, 673 Auditorium Rd., Rm 122, East Lansing, MI 48824, United States |
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| Abstract: | Variability of phytoplankton in the Caspian Sea (CS) is related to the complex orography, the variety of physical and chemical processes, and climatic indices. Here, interannual and intra-annual variability of satellite-derived chlorophyll-a concentrations (Chl-a) were studied using wavelet analysis during 2002–2019 in different regions of the CS. Self-Organizing Maps (SOM) analysis performed to classify the CS into the areas of similar variability of satellite-derived Chl-a. Wavelet spectral analysis showed that the Chl-a variability regulated by four primary periodic cycles: 0.5-year, 1-year, 2 to 2.5-year, and 3 to 5-year. The 0.5 and 1-year wavelet cycles mostly depicted the intensity of seasonality patterns. The 2–2.5-year and 3–5-year cycles of Chl-a showed non-stationary coherence with corresponding low-frequency cycles of NAO and ENSO. The 3–5-year wavelet amplitudes of Chl-a strongly correlated with NAO and ENSO in the southern CS. Weak correlations of 2–2.5-year cycle wavelet amplitudes of Chl-a with NAO and ENSO suggested that variations do not always directly translate to a biological response. A negative anomaly in the Chl-a autumn peaks observed during 2011–2016 in the middle and southern CS, when NAO phases were persistently positive. The interannual variations of summer peaks in the northern CS, and autumn peaks in the middle and southern CS were broadly related to the precipitation. SST and wind stress. Moreover, it was shown that the Volga discharge has a significant influence on Chl-a variability in the northern CS. |
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| Keywords: | Phytoplankton Self-organizing map Wavelet transform NAO ENSO MODIS |
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