Revisiting the greenhouse effect—a hydrological perspective

D. Koutsoyiannis, and C. Vournas, Revisiting the greenhouse effect—a hydrological perspective, Hydrological Sciences Journal, 69 (2), 151–164, doi:10.1080/02626667.2023.2287047, 2024.

[doc_id=2371]

[English]

Quantification of the greenhouse effect is a routine procedure in the framework of hydrological calculations of evaporation. According to the standard practice, this is made considering the water vapour in the atmosphere, without any reference to the concentration of carbon dioxide (CO2), which, however, in the last century has escalated from 300 to about 420 ppm. As the formulae used for the greenhouse effect quantification were introduced 50-90 years ago, we examine whether these are still representative or not, based on eight sets of observations, distributed in time across a century. We conclude that the observed increase of the atmospheric CO2 concentration has not altered, in a discernible manner, the greenhouse effect, which remains dominated by the quantity of water vapour in the atmosphere, and that the original formulae used in hydrological practice remain valid. Hence, there is no need for adaptation of the original formulae due to increased CO2 concentration.

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Our works referenced by this work:

1. D. Koutsoyiannis, A. Efstratiadis, N. Mamassis, and A. Christofides, On the credibility of climate predictions, Hydrological Sciences Journal, 53 (4), 671–684, doi:10.1623/hysj.53.4.671, 2008.
2. D. Koutsoyiannis, A. Christofides, A. Efstratiadis, G. G. Anagnostopoulos, and N. Mamassis, Scientific dialogue on climate: is it giving black eyes or opening closed eyes? Reply to “A black eye for the Hydrological Sciences Journal” by D. Huard, Hydrological Sciences Journal, 56 (7), 1334–1339, doi:10.1080/02626667.2011.610759, 2011.
3. D. Koutsoyiannis, Clausius-Clapeyron equation and saturation vapour pressure: simple theory reconciled with practice, European Journal of Physics, 33 (2), 295–305, doi:10.1088/0143-0807/33/2/295, 2012.
4. D. Koutsoyiannis, Hydrology and Change, Hydrological Sciences Journal, 58 (6), 1177–1197, doi:10.1080/02626667.2013.804626, 2013.
5. D. Koutsoyiannis, Reconciling hydrology with engineering, Hydrology Research, 45 (1), 2–22, doi:10.2166/nh.2013.092, 2014.
6. D. Koutsoyiannis, Entropy: from thermodynamics to hydrology, Entropy, 16 (3), 1287–1314, doi:10.3390/e16031287, 2014.
7. D. Koutsoyiannis, Time’s arrow in stochastic characterization and simulation of atmospheric and hydrological processes, Hydrological Sciences Journal, 64 (9), 1013–1037, doi:10.1080/02626667.2019.1600700, 2019.
8. D. Koutsoyiannis, Revisiting the global hydrological cycle: is it intensifying?, Hydrology and Earth System Sciences, 24, 3899–3932, doi:10.5194/hess-24-3899-2020, 2020.
9. D. Koutsoyiannis, and Z. W. Kundzewicz, Atmospheric temperature and CO₂: Hen-or-egg causality?, Sci, 2 (4), 83, doi:10.3390/sci2040083, 2020.
10. D. Koutsoyiannis, and N. Mamassis, From mythology to science: the development of scientific hydrological concepts in the Greek antiquity and its relevance to modern hydrology, Hydrology and Earth System Sciences, 25, 2419–2444, doi:10.5194/hess-25-2419-2021, 2021.
11. D. Koutsoyiannis, Rethinking climate, climate change, and their relationship with water, Water, 13 (6), 849, doi:10.3390/w13060849, 2021.
12. D. Koutsoyiannis, and A. Montanari, Bluecat: A local uncertainty estimator for deterministic simulations and predictions, Water Resources Research, 58 (1), e2021WR031215, doi:10.1029/2021WR031215, 2022.
13. D. Koutsoyiannis, and A. Montanari, Climate extrapolations in hydrology: The expanded Bluecat methodology, Hydrology, 9, 86, doi:10.3390/hydrology9050086, 2022.
14. D. Koutsoyiannis, C. Onof, A. Christofides, and Z. W. Kundzewicz, Revisiting causality using stochastics: 1.Theory, Proceedings of The Royal Society A, 478 (2261), 20210835, doi:10.1098/rspa.2021.0835, 2022.
15. D. Koutsoyiannis, C. Onof, A. Christofides, and Z. W. Kundzewicz, Revisiting causality using stochastics: 2. Applications, Proceedings of The Royal Society A, 478 (2261), 20210836, doi:10.1098/rspa.2021.0836, 2022.
16. D. Koutsoyiannis, Stochastics of Hydroclimatic Extremes - A Cool Look at Risk, Edition 3, ISBN: 978-618-85370-0-2, 391 pages, doi:10.57713/kallipos-1, Kallipos Open Academic Editions, Athens, 2023.
17. P.E. O’Connell, G. O’Donnell, and D. Koutsoyiannis, On the spatial scale dependence of long-term persistence in global annual precipitation data and the Hurst Phenomenon, Water Resources Research, 59 (4), e2022WR033133, doi:10.1029/2022WR033133, 2023.
18. D. Koutsoyiannis, T. Iliopoulou, A. Koukouvinos, N. Malamos, N. Mamassis, P. Dimitriadis, N. Tepetidis, and D. Markantonis, In search of climate crisis in Greece using hydrological data: 404 Not Found, Water, 15 (9), 1711, doi:10.3390/w15091711, 2023.
19. D. Koutsoyiannis, C. Onof, Z. W. Kundzewicz, and A. Christofides, On hens, eggs, temperatures and CO₂: Causal links in Earth’s atmosphere, Sci, 5 (3), 35, doi:10.3390/sci5030035, 2023.

Tagged under: Course bibliography: Hydrometeorology, Climate stochastics