Articles | Volume 369
https://doi.org/10.5194/piahs-369-49-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/piahs-369-49-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Climate noise effect on uncertainty of hydrological extremes: numerical experiments with hydrological and climate models
A. N. Gelfan
CORRESPONDING AUTHOR
Water Problems Institute of RAS, Moscow, Russia
P.P. Shirshov Institute of Oceanology of RAS, Moscow, Russia
V. A. Semenov
A.M. Obukhov Institute of Atmospheric Physics of RAS, Moscow, Russia
Institute of Geography of RAS, Moscow, Russia
P.P. Shirshov Institute of Oceanology of RAS, Moscow, Russia
Yu. G. Motovilov
Water Problems Institute of RAS, Moscow, Russia
P.P. Shirshov Institute of Oceanology of RAS, Moscow, Russia
Related authors
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
Short summary
Short summary
Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
A. N. Gelfan, Yu. G. Motovilov, and V. M. Moreido
Proc. IAHS, 369, 115–120, https://doi.org/10.5194/piahs-369-115-2015, https://doi.org/10.5194/piahs-369-115-2015, 2015
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
Short summary
Short summary
Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
Short summary
Short summary
This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
A. Gelfan, V. A. Semenov, E. Gusev, Y. Motovilov, O. Nasonova, I. Krylenko, and E. Kovalev
Hydrol. Earth Syst. Sci., 19, 2737–2754, https://doi.org/10.5194/hess-19-2737-2015, https://doi.org/10.5194/hess-19-2737-2015, 2015
Short summary
Short summary
Our paper is one of very few studies where the influence of stochastic internal atmospheric variability (IAV) on the hydrological response is analyzed. On the basis of ensemble experiments with GCM and hydrological models, we found, e.g., that averaging over ensemble members filters the stochastic term related to IAV, and that a considerable portion of the simulated trend in annual Lena R. runoff can be explained by the externally forced signal (global SST and SIC changes in our experiments).
Y. Motovilov, V. Danilov-Danilyan, E. Dod, and A. Kalugin
Proc. IAHS, 370, 63–67, https://doi.org/10.5194/piahs-370-63-2015, https://doi.org/10.5194/piahs-370-63-2015, 2015
A. N. Gelfan, Yu. G. Motovilov, and V. M. Moreido
Proc. IAHS, 369, 115–120, https://doi.org/10.5194/piahs-369-115-2015, https://doi.org/10.5194/piahs-369-115-2015, 2015
V. A. Semenov, T. Martin, L. K. Behrens, and M. Latif
The Cryosphere Discuss., https://doi.org/10.5194/tcd-9-1077-2015, https://doi.org/10.5194/tcd-9-1077-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
The shrinking Arctic sea ice cover is probably the clearest manifestation of ongoing climate change. The last generation of climate models from World Climate Research Programme Coupled Model Intercomparison Project (CMIP3 and CMIP5) simulate consistent changes in the Sea Ice Area (SIA) seasonal cycle. On average, the sensitivity of SIA to external forcing is enhanced in the CMIP5 models. The Arctic SIA variability response to anthropogenic forcing is different in CMIP3 and CMIP5.
L. K. Behrens, T. Martin, V. A. Semenov, and M. Latif
The Cryosphere Discuss., https://doi.org/10.5194/tcd-6-5317-2012, https://doi.org/10.5194/tcd-6-5317-2012, 2012
Preprint withdrawn
Cited articles
Braun, M., Caya, D., Frigon, A., and Slivitzky, M.: Internal variability of Canadian RCM's hydrological variables at the basin scale in Quebec and Labrador, J. Hydrometeorol., 13, 443–462, 2012.
Cohen, J., Screen, J. A., Furtado, J. C., Barlow, M., Whittleston, D., Coumou, D., Francis, J., Dethloff, K., Entekhabi, D., Overland, J., and Jones, J.: Recent Arctic amplification and extreme mid-latitude weather, Nat. Geosci., 7, 627–637, https://doi.org/10.1038/ngeo2234, 2014.
Coumou, D. and Rahmstorf, S.: A decade of weather extremes, Nat. Clim. Change, 2, 491–496, 2012.
Gelfan, A., Motovilov, Yu., Krylenko, I., Moreido, V., and Zakharova, E.: Testing robustness of the physically-based ECOMAG model with respect to changing conditions, Hydrol. Sci. J., https://doi.org/10.1080/02626667.2014.935780, accepted, 2014.
Gelfan, A., Semenov, V. A., Gusev, E., Motovilov, Y., Nasonova, O., Krylenko, I., and Kovalev, E.: Large-basin hydrological response to climate model outputs: uncertainty caused by the internal atmospheric variability, Hydrol. Earth Syst. Sci. Discuss., 12, 2305–2348, https://doi.org/10.5194/hessd-12-2305-2015, 2015.
Hawkins, E. and Sutton, R.: The potential to narrow uncertainty in regional climate predictions, B. Am. Meteorol. Soc., 90, 1095–1107, https://doi.org/10.1175/2009BAMS2607.1, 2009.
Koutsoyiannis, D., Montanari, A., Lins, H. F., and Cohn, T. A.: Climate, hydrology and freshwater: towards an interactive incorporation of hydrological experience into climate research, Hydrol. Sci. J., 54, 394–405, 2009.
Krylenko, I., Motovilov, Yu., Antokhina, E., Ghuk, V., and Surkova, G.: Physically based distributed modelling of river runoff under changing climate conditions, Remote Sensing and GIS for Hydrology and Water Resources (Proceedings RSHS14 and ICGRHWE14), Guangzhou, China, 2014.
Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P., Mechler, R., Bouwer, L. M., Arnell, N., Mach, K., Muir-Wood, R., Brakenridge, G. R., Kron, W., Benito, G., Honda, Y., Takahashi, K., and Sherstyukov, B.: Flood risk and climate change: global and regional perspectives, Hydrol. Sci. J., https://doi.org/10.1080/02626667.2013.857411, 2013.
Merz, B., Vorogushyn, S., Uhlemann, S., Delgado, J., and Hundecha, Y.: HESS Opinions "More efforts and scientific rigour are needed to attribute trends in flood time series", Hydrol. Earth Syst. Sci., 16, 1379–1387, https://doi.org/10.5194/hess-16-1379-2012, 2012.
Motovilov, Yu. and Gelfan, A.: Assessing runoff sensitivity to climate change in the Arctic basin: empirical and modelling approaches, Cold and Mountain Region Hydrological Systems Under Climate Change: Towards Improved Projections, edited by: Gelfan, A., Yang, D., Gusev, E., and Kunstmann, H., IAHS Publications, 360, 105–112, 2013.
Motovilov, Yu., Gottschalk, L., Engeland, K., and Rodhe, A.: Validation of a distributed hydrological model against spatial observation, Agr. Forest Meteorol., 98–99, 257–277, 1999.
NRC Global Change and Extreme Hydrology: Testing Conventional Wisdom, the National Academies Press, Washington, D.C., 2011.
Olsen, J. R., Kiang, J., and Waskom, R. (Eds.): Workshop on Nonstationarity, Hydrologic Frequency Analysis, and Water Management, Colorado Water Institute, 109, 2010.
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century, J. Geophys. Res., 108, 4407, https://doi.org/10.1029/2002JD002670, 2003.
Refsgaard, J. C, Madsen, H., Andréassian, V., Arnbjerg-Nielsen, K., Davidson, T. A., Drews, M., Hamilton, D. P., Jeppesen, E., Kjellström, E., Olesen, J. E., Sonnenborg, T. O., Trolle, D., Willems, P., and Christensen, J. H.: A framework for testing the ability of models to project climate change and its impacts, Clim. Change, 122, 271–282, https://doi.org/10.1007/s10584-013-0990-2, 2014.
Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U., and Tompkins, A.: The atmospheric general circulation model ECHAM5. Part I: Model description, Max Planck Institute for Meteorology Rep. 349, 127, 2003.
Semenov, V. A.: Arctic warming favours extreme, Nat. Clim. Change, 2, 315–316, 2003.
Semenov, V. A. and Latif, M.: The early twentieth century warming and winter Arctic sea ice, The Cryosphere, 6, 1231–1237, https://doi.org/10.5194/tc-6-1231-2012, 2012.