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A New Climate Nowcasting Tool Based on Paleoclimatic Data

Author

Listed:
  • Costas Varotsos

    (Climate Research Group, Division of Environmental Physics and Meteorology, National and Kapodistrian University of Athens, Campus Bldg. Phys. V, 15784 Athens, Greece)

  • Yuri Mazei

    (Faculty of Biology, Lomonosov Moscow State University, Leninskiye Gory, 1, Moscow 199991, Russia
    A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninskiy Avenue, 33, Moscow 119071, Russia)

  • Elena Novenko

    (Institute of Geography, Russian Academy of Sciences, Staromonetny Lane 29, Moscow 119017, Russia
    Faculty of Geography, Lomonosov Moscow State University, Leninskiye Gory, 1, Moscow 199991, Russia)

  • Andrey N. Tsyganov

    (Faculty of Biology, Lomonosov Moscow State University, Leninskiye Gory, 1, Moscow 199991, Russia
    A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninskiy Avenue, 33, Moscow 119071, Russia)

  • Alexander Olchev

    (A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninskiy Avenue, 33, Moscow 119071, Russia
    Faculty of Geography, Lomonosov Moscow State University, Leninskiye Gory, 1, Moscow 199991, Russia)

  • Tatiana Pampura

    (Institute of Physicochemical and Biological Problems in Soil Science, Russian Academy of Sciences, Institutskaya, 2b, Pushchino, Moscow Region 142290, Russia)

  • Natalia Mazei

    (Faculty of Geography, Lomonosov Moscow State University, Leninskiye Gory, 1, Moscow 199991, Russia)

  • Yulia Fatynina

    (Department of Zoology and Ecology, Penza State University, Krasnaya Str., 40, Penza 440068, Russia)

  • Damir Saldaev

    (Faculty of Biology, Lomonosov Moscow State University, Leninskiye Gory, 1, Moscow 199991, Russia
    Faculty of Biology, Shenzhen MSU-BIT University, Shenzhen 518100, China)

  • Maria Efstathiou

    (Climate Research Group, Division of Environmental Physics and Meteorology, National and Kapodistrian University of Athens, Campus Bldg. Phys. V, 15784 Athens, Greece)

Abstract

Atmospheric pollutants and environmental indicators are often used to reconstruct historic atmospheric pollution from peat, as it accumulates over time by decomposing plant material, thus recording a history of air pollution. In the present study, three key parameters related to the peat bogs’ surface wetness dynamics in European Russia during the Holocene were investigated using modern statistical analysis. These parameters are: (i) the water table depth (WTD) in relation to the surface, which is reconstructed based on the community structure of the subfossil testate amoeba assemblages; (ii) the peat humification estimated as absorption of alkaline extract that directly reflects moisture at which the peat was formed; (iii) the Climate Moisture Index (CMI) and the Aridity Index derived from pollen-based reconstructions of the mean annual temperature and precipitation and classifying moisture conditions as the ratio between available annual precipitation and potential land surface evapotranspiration. All these parameters provide useful information about the paleoclimate (atmospheric moisture component) dynamics. High values of WTD and peat humification appear to comply with Gutenberg–Richter law. It is noteworthy that this law also seems to reproduce the high values of the modeled climate moisture and aridity indices. The validity of this new result is checked by replacing “conventional time” with “natural time”. On this basis, a new nowcasting tool is developed to more accurately estimate the average waiting time for the extreme values of these climate parameters. This will help to understand climate variability better to address emerging development needs and priorities by implementing empirical studies of the interactions between climatic effects, mitigation, adaptation, and sustainable growth.

Suggested Citation

  • Costas Varotsos & Yuri Mazei & Elena Novenko & Andrey N. Tsyganov & Alexander Olchev & Tatiana Pampura & Natalia Mazei & Yulia Fatynina & Damir Saldaev & Maria Efstathiou, 2020. "A New Climate Nowcasting Tool Based on Paleoclimatic Data," Sustainability, MDPI, vol. 12(14), pages 1-14, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:14:p:5546-:d:382485
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    References listed on IDEAS

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    1. Krapivin, Vladimir F. & Varotsos, Costas A. & Soldatov, Vladimir Yu., 2017. "Simulation results from a coupled model of carbon dioxide and methane global cycles," Ecological Modelling, Elsevier, vol. 359(C), pages 69-79.
    2. Thomas Frederikse & Maya K. Buchanan & Erwin Lambert & Robert E. Kopp & Michael Oppenheimer & D. J. Rasmussen & Roderik S. W. van de Wal, 2020. "Antarctic Ice Sheet and emission scenario controls on 21st-century extreme sea-level changes," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
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    Cited by:

    1. Pedro Macedo & Mara Madaleno, 2022. "Global Temperature and Carbon Dioxide Nexus: Evidence from a Maximum Entropy Approach," Energies, MDPI, vol. 16(1), pages 1-13, December.
    2. Costas Varotsos & Nicholas V. Sarlis & Yuri Mazei & Damir Saldaev & Maria Efstathiou, 2024. "A Composite Tool for Forecasting El Niño: The Case of the 2023–2024 Event," Forecasting, MDPI, vol. 6(1), pages 1-17, March.

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