A New Climate Nowcasting Tool Based on Paleoclimatic Data

Costas Varotsos, Yuri Mazei, Elena Novenko, Andrey N. Tsyganov, Alexander Olchev, Tatiana Pampura, Natalia Mazei, Yulia Fatynina, Damir Saldaev and Maria Efstathiou
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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
Elena Novenko: Institute of Geography, Russian Academy of Sciences, Staromonetny Lane 29, Moscow 119017, Russia
Andrey N. Tsyganov: Faculty of Biology, Lomonosov Moscow State University, Leninskiye Gory, 1, Moscow 199991, Russia
Alexander Olchev: A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninskiy Avenue, 33, Moscow 119071, 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
Maria Efstathiou: Climate Research Group, Division of Environmental Physics and Meteorology, National and Kapodistrian University of Athens, Campus Bldg. Phys. V, 15784 Athens, Greece

Sustainability, 2020, vol. 12, issue 14, 1-14

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.

Keywords: nowcasting; paleoclimate; Climate Moisture Index; Aridity Index; Gutenberg–Richter law (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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