Hydrological and climatic characteristics of the caspian sea during the last glacial maximum, mid-holocene and pre-industrial conditions according to numerical modelling data

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Components of the water balance of the Caspian Sea are calculated for a wide range of lake levels (–85– 50 m. a. s. l.) and for the two most contrasting climatic epochs over the last several tens of thousands of years: the middle Holocene (6 ka b. p.) and the Last Glacial Maximum (21 ka b. p.), as well as for the pre-industrial conditions (~1850). The eddy-resolving ocean general circulation model INMIO coupled with the CICE ice model are used for the calculations. Climate data of the INM–CM4.8 model for the indicated periods are used as boundary conditions. It is found that the volumes of river inflow required to maintain the lake level at various marks for the Holocene era are lower than the corresponding pre-industrial values by 6–7%. For the Last Glacial Maximum this decrease is 13–14% for regressive states and 20–21% for transgressive ones. Sensitivity of the results is studied to the temporal resolution of boundary meteorological data and to the locations of fresh water inflow into the Caspian Sea. It is shown that excluding the diurnal and intramonthly variability in input data leads to an underestimation of evaporation from the surface of the sea. The greatest influence on this value is exerted by the exclusion of intramonthly variability of the dynamic wind field: this leads to a decrease in the equilibrium runoff by 35%. To correctly simulate the duration of the ice coverage season, it is necessary to take into account the diurnal cycle of incoming radiation and air temperature. The melting period is significantly lengthened when using data at daily or monthly resolution, which has the greatest impact during transgressive states of the Caspian Sea. The redistribution of river mouth locations along the coast does not significantly affect the value of the total equilibrium inflow, which makes it possible to most likely exclude the uncertainty of this value associated with the lack of data on the mutual ratio of discharge of ancient rivers. In addition, estimates of hydroclimatic characteristics of the Caspian region for the middle Holocene and late Pleistocene are provided based on climate modeling carried out within the framework of the PMIP4 project.

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Sobre autores

P. Morozova

Institute of Geography RAS

Autor responsável pela correspondência
Email: morozova_polina@mail.ru
Rússia, Moscow

K. Ushakov

Shirshov Institute of Oceanology RAS

Email: morozova_polina@mail.ru
Rússia, Moscow

V. Semenov

Institute of Geography RAS; Obukhov Institute of Atmospheric Physics RAS

Email: morozova_polina@mail.ru
Rússia, Moscow; Moscow

E. Volodin

Marchuk Institute of Numerical Mathematics RAS

Email: morozova_polina@mail.ru
Rússia, Moscow

R. Ibrayev

Shirshov Institute of Oceanology RAS; Marchuk Institute of Numerical Mathematics RAS

Email: morozova_polina@mail.ru
Rússia, Moscow; Moscow

Bibliografia

  1. Argus D.F., Peltier W.R., Drummond R. et al. (2014). The Antarctic component of postglacial rebound Model ICE-6G_C (VM5a) based upon GPS positioning, exposure age dating of ice thicknesses and sea level histories. Geophys. J. Int. Vol. 198. No. 1. P. 537–563. https://doi.org/10.1093/gji/ggu140
  2. Brierley C.M., Zhao A., Harrison S.P. et al. (2020). Large-scale features and evaluation of the PMIP4–CMIP6 mid-Holocene simulations. Climate of the Past. Vol. 16. Iss. 5. P. 1847–1872. https://doi.org/10.5194/cp-16-1847-2020
  3. Elguindi N., Somot S., Deque M. et al. (2011). Climate change evolution of the hydrological balance of the Mediterranean, Black and Caspian Seas: impact of climate model resolution. Climate Dynamics. Vol. 36. P. 205–228. https://doi.org/10.1007/s00382-009-0715-4
  4. Fadeev R., Ushakov K., Tolstykh M. et al. (2018). Design and development of the SLAV–INMIO–CICE coupled model for seasonal prediction and climate research. Russian J. of Numerical Analysis and Mathematical Modelling. Vol. 33. No. 6. P. 333–340. https://doi.org/10.1515/rnam-2018-0028
  5. Garstang M. (1967). Sensible and latent heat exchange in low latitude synoptic scale systems. Tellus. Vol. 19. Iss. 3. P. 492–508. https://doi.org/10.1111/j.2153-3490.1967.tb01504.x
  6. Gelfan A., Panin A., Kalugin A. et al. (2024). Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments. Hydrol. Earth Syst. Sci. Vol. 28. Iss. 1. P. 241–259. https://doi.org/10.5194/hess-28-241-2024
  7. Giorgi F. (2019). Thirty years of regional climate modeling: Where are we and where are we going next? J. Geophys. Res.: Atmos. Vol. 124. P. 5696–5723. https://doi.org/10.1029/2018JD030094
  8. Griffies S.M., Biastoch A., Böning C. et al. (2009). Coordinated Ocean-ice Reference Experiments (COREs). Ocean Modelling. Vol. 26. Iss. 1-2. P. 1–46 https://doi.org/10.1016/j.ocemod.2008.08.007
  9. Hajima T., Watanabe M., Yamamoto A. et al. (2020). Development of the MIROC-ES2L Earth system model and the evaluation of biogeochemical processes and feedbacks. Geosci. Model Dev. Vol. 13. Iss. 5. P. 2197–2244. https://doi.org/10.5194/gmd-13-2197-2020
  10. Hunke E.C., Lipscomb W.H., Turner A.K. et al. (2015). CICE: the Los Alamos Sea Ice Model. Documentation and Software User’s Manual Version 5.1. Los Alamos National Laboratory. 116 p. http://www.ccpo.odu.edu/~klinck/Reprints/PDF/cicedoc2015.pdf (access date: 04.04.2024).
  11. Kageyama M., Albani S., Braconnot P. et al. (2017). The PMIP4 contribution to CMIP6 – Part 4: Scientific objectives and experimental design of the PMIP4–CMIP6 Last Glacial Maximum experiments and PMIP4 sensitivity experiments. Geosci. Model Dev. Vol. 10. Iss. 11. P. 4035–4055. https://doi.org/10.5194/gmd-10-4035-2017
  12. Kageyama M., Harrison S.P., Kapsch M.-L. et al. (2021). The PMIP4 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3 simulations. Climate of the Past. Vol. 17. Iss. 3. P. 1065–1089. https://doi.org/10.5194/cp-17-1065-2021
  13. Kalmykov V.V., Ibrayev R.A., Kaurkin M.N. et al. (2018). Compact Modeling Framework v3.0 for high-resolution global ocean–ice–atmosphere models. Geosci. Model Dev. Vol. 11. Iss. 10. P. 3983–3997. https://doi.org/10.5194/gmd-11-3983-2018
  14. Kislov A., Toropov P. (2011). Modeling extreme Black Sea and Caspian Sea levels of the past 21000 years with general circulation models. Geological Society of America Special Papers. P. 27–32. https://doi.org/10.1130/2011.2473(02)
  15. Koriche S.A., Singarayer J.S., Cloke H.L. et al. (2022). What are the drivers of Caspian Sea level variation during the late Quaternary? Quat. Sci. Rev. Vol. 283. 107457. https://doi.org/10.1016/j.quascirev.2022.107457
  16. Kurbanov R., Murray A., Thompson W. et al. (2021). First reliable chronology for the Early Khvalynian Caspian Sea transgression in the Lower Volga River valley. Boreas. Vol. 50. P. 134–146. https://doi.org/10.1111/bor.12478
  17. Launiainen J., Vihma T. (1990). Derivation of turbulent surface fluxes – an iterative flux–profile method allowing arbitrary observing heights. Environmental Software. Vol. 5. No. 3. P. 113–124. https://doi.org/10.1016/0266-9838(90)90021-W
  18. Mauritsen T., Bader J., Becker T. et al. (2019). Developments in the MPI–M Earth System Model version 1.2 (MPI–ESM1.2) and its response to increasing CO2. J. of Advances in Modeling Earth Systems. Vol. 11. Iss. 4. P. 998–1038. https://doi.org/10.1029/2018MS001400
  19. Morozova P.A., Ushakov K.V., Semenov V.A. et al. (2021). Water Budget of the Caspian Sea in the Last Glacial Maximum by Data of Experiments with Mathematical Models. Water resources. Vol. 48. No. 6. P. 823–830. https://doi.org/10.1134/S0097807821060130
  20. Morozova P.A., Ushakov K.V., Semenov V.A. et al. (2024). Water Balance of the Caspian Sea in the Last Glacial Maximum and Pre-Industrial Conditions Based on the Experiments with the INMIO–CICE General Sea Circulation Model. Dokl. Earth Sci. Vol. 515. Part 2. P. 675–679. https://doi.org/10.1134/S1028334X23603620
  21. Nesterov E.S. (Ed.). (2016). Vodnyi balans i kolebaniya urovnya Kaspiiskogo morya: modelirovanie i prognoz (Water balance and level fluctuations of the Caspian Sea. Modeling and prediction). Moscow: Triada ltd (Publ.). 378 p. (in Russ.).
  22. Panin G.N. (1987). Isparenie i teploobmen Kaspiiskogo morya (Evaporation and heat exchange of the Caspian Sea). Moscow: Nauka (Publ.). 88 p. (in Russ.).
  23. Peltier W.R., Argus D.F., Drummond R. (2015). Space geodesy constrains ice age terminal deglaciation: The global ICE-6G_C (VM5a) model. J. Geophys. Res.: Solid Earth. Vol. 120. Iss. 1. P. 450–487. https://doi.org/10.1002/2014JB011176
  24. PMIP4. https://pmip4.lsce.ipsl.fr/doku.php/exp_design: index (access date: 04.04.2024).
  25. Sidorenko D., Rackow T., Jung T. et al. (2015). Towards multi-resolution global climate modeling with ECHAM6–FESOM. Part I: model formulation and mean climate. Climate Dynamics. Vol. 44. P. 757–780. https://doi.org/10.1007/s00382-014-2290-6
  26. Tujilkin N.S., Kosarev A.N., Arkhipkin V.S., Nikonova R.E. (2011). Long-term variations of the hydrological regime of the Caspian Sea. Vestnik Moskovskogo universiteta. Seriya 5. Geografiya. No. 2. Р. 62–71. (in Russ.).
  27. Ushakov K.V., Ibrayev R.A. (2018). Assessment of mean world ocean meridional heat transport characteristics by a high-resolution model. Russ. J. Earth Sci. Vol. 18. ES1004. https://doi.org/10.2205/2018ES000616
  28. Volodin E.M., Mortikov E.V., Kostrykin S.V. et al. (2018). Simulation of the modern climate using the INM–CM4.8 climate model. Russian J. of Numerical Analysis and Mathematical Modelling. Vol. 33. No. 6. P. 367–374. https://doi.org/10.1515/rnam-2018-0032
  29. Yanina T. (2020). Environmental variability of the Ponto-Caspian and Mediterranean basins during the last climatic macrocycle. Geography, Environment, Sustainability. Vol. 13. No. 4. P. 6–23. https://doi.org/10.24057/2071-9388-2020-120
  30. Yanina T.A., Sorokin V., Bezrodnykh Yu. et al. (2018). Late Pleistocene climatic events reflected in the Caspian Sea geological history (based on drilling data). Quat. Int. Vol. 465. Part A. P. 130–141. https://doi.org/10.1016/j.quaint.2017.08.003

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2. Fig. 1. Model data and observations of Caspian Sea water balance components and morphometric characteristics: (а) – dependence of the Caspian area on the level; (б) – annual precipitation averaged over the sea area (mm/year); (в) – annual evaporation layer averaged over the sea area (mm/year); (г) – annual layer of visible evaporation, averaged over the sea area, mm/year [1 – piControl, 2 – AWI_piControl, 3 – INMCM_piControl, 4 – MIROC_piControl, 5 – МPI_piControl; 6 – mid-Holocene, 7 – AWI_mid-Holocene, 8 – INMCM_mid-Holocene, 9 – MIROC_mid-Holocene, 10 – MPI_mid-Holocene; 11 – LGM, 12 – AWI_LGM, 13 – INMCM_LGM, 14 – MIROC_LGM, 15 – MPI_LGM; evaporation: 16 – observations of 1901–1920, 17 – observations of 1901–1996, 18 – effective (observations of 20th century); 19 – precipitation (observations of 20th century)]; (д) – equilibrium runoff, km3/year (1 – piControl, 2 – mid-Holocene, 3 – LGM, 4 – runoff_init).

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3. Fig. 2. Hydroclimatic characteristics of the Caspian Sea for a level of +50 m. a. s. l. according to coupled experiments with the climate model INM-CM4.8 and ocean model INMIO–CICE (from left to right: PI period, mid-Holocene, LGM): (а) – the fraction of a cell covered with ice (average values for November–March); (б) – average annual surface air temperature, °C; (в) – average annual precipitation, mm/year; (г) – average annual evaporation layer, mm/year.

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4. Fig. 3. Change in the layer of visible evaporation in the mid-Holocene (а) and LGM (б) compared to the preindustrial period (mm/year) for the Caspian Sea level +50 m. a. s. l.

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5. Fig. 4. Equilibrium river runoff at different levels of the Caspian Sea in the control experiment and in experiments with various time-averaging of input atmospheric and radiation data.

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6. Fig. 5. Intra-annual variability in the average heat balance characteristics over the sea area at a level of +50 m. a. s. l. in the control experiment, with monthly average forcing experiment and with the average daily thermodynamic component of forcing (3-year excerpt from the stage of calculating the equilibrium runoff).

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7. Fig. 6. Change in evaporation (mm/month) for the Caspian Sea level +50 m. a. s. l. in the LGM (on the right) and mid-Holocene (on the left) in experiments: (а) – Var5а; (б) – Var5b compared to the basic experiments (in which the runoff was set at points corresponding to the position of the Volga mouth) for the same periods.

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