Articles | Volume 8, issue 2
https://doi.org/10.5194/ascmo-8-155-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-8-155-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
01 Sep 2022
| 01 Sep 2022
Statistical reconstruction of European winter snowfall in reanalysis and climate models based on air temperature and total precipitation
Flavio Maria Emanuele Pons
CORRESPONDING AUTHOR
LSCE-IPSL, CEA Saclay l'Orme des Merisiers, CNRS UMR 8212 CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
Davide Faranda
LSCE-IPSL, CEA Saclay l'Orme des Merisiers, CNRS UMR 8212 CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
London Mathematical Laboratory, 14 Buckingham Street, London WC2N 6DF, UK
Related authors
Valerio Lembo, Gabriele Messori, Davide Faranda, Vera Melinda Galfi, Rune Grand Graversen, and Flavio Emanuele Pons
EGUsphere, https://doi.org/10.5194/egusphere-2025-2189, https://doi.org/10.5194/egusphere-2025-2189, 2025
Short summary
Short summary
Hemispheric heatwaves have fundamental implications for ecosystems and societies. They are studied together with the large-scale atmospheric dynamics, through the lens of the poleward heat transports by planetary-scale waves. Extremely weak transports of heat towards the Poles are found to be associated with hemispheric heatwaves in the Northern Hemisphere mid-latitudes. Therefore, we conclude that heat transports are a clear indicator, and possibly a precursor of hemispehric heatwaves.
Davide Faranda, Gabriele Messori, Erika Coppola, Tommaso Alberti, Mathieu Vrac, Flavio Pons, Pascal Yiou, Marion Saint Lu, Andreia N. S. Hisi, Patrick Brockmann, Stavros Dafis, Gianmarco Mengaldo, and Robert Vautard
Weather Clim. Dynam., 5, 959–983, https://doi.org/10.5194/wcd-5-959-2024, https://doi.org/10.5194/wcd-5-959-2024, 2024
Short summary
Short summary
We introduce ClimaMeter, a tool offering real-time insights into extreme-weather events. Our tool unveils how climate change and natural variability affect these events, affecting communities worldwide. Our research equips policymakers and the public with essential knowledge, fostering informed decisions and enhancing climate resilience. We analysed two distinct events, showcasing ClimaMeter's global relevance.
Davide Faranda, Stella Bourdin, Mireia Ginesta, Meriem Krouma, Robin Noyelle, Flavio Pons, Pascal Yiou, and Gabriele Messori
Weather Clim. Dynam., 3, 1311–1340, https://doi.org/10.5194/wcd-3-1311-2022, https://doi.org/10.5194/wcd-3-1311-2022, 2022
Short summary
Short summary
We analyze the atmospheric circulation leading to impactful extreme events for the calendar year 2021 such as the Storm Filomena, Westphalia floods, Hurricane Ida and Medicane Apollo. For some of the events, we find that climate change has contributed to their occurrence or enhanced their intensity; for other events, we find that they are unprecedented. Our approach underscores the importance of considering changes in the atmospheric circulation when performing attribution studies.
Miriam D'Errico, Flavio Pons, Pascal Yiou, Soulivanh Tao, Cesare Nardini, Frank Lunkeit, and Davide Faranda
Earth Syst. Dynam., 13, 961–992, https://doi.org/10.5194/esd-13-961-2022, https://doi.org/10.5194/esd-13-961-2022, 2022
Short summary
Short summary
Climate change is already affecting weather extremes. In a warming climate, we will expect the cold spells to decrease in frequency and intensity. Our analysis shows that the frequency of circulation patterns leading to snowy cold-spell events over Italy will not decrease under business-as-usual emission scenarios, although the associated events may not lead to cold conditions in the warmer scenarios.
Flavio Maria Emanuele Pons and Davide Faranda
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-352, https://doi.org/10.5194/nhess-2020-352, 2020
Preprint withdrawn
Short summary
Short summary
The objective motivating this study is the assessment of the impacts of winter climate extremes, which requires accurate simulation of snowfall. However, climate simulation models contain physical approximations, which result in biases that must be corrected using past data as a reference. We show how to exploit simulated temperature and precipitation to estimate snowfall from already bias-corrected variables, without requiring the elaboration of complex, multivariate bias adjustment techniques.
Kerry Emanuel, Tommaso Alberti, Stella Bourdin, Suzana J. Camargo, Davide Faranda, Emmanouil Flaounas, Juan Jesus Gonzalez-Aleman, Chia-Ying Lee, Mario Marcello Miglietta, Claudia Pasquero, Alice Portal, Hamish Ramsay, Marco Reale, and Romualdo Romero
Weather Clim. Dynam., 6, 901–926, https://doi.org/10.5194/wcd-6-901-2025, https://doi.org/10.5194/wcd-6-901-2025, 2025
Short summary
Short summary
Storms strongly resembling hurricanes are sometimes observed to form well outside the tropics, even in polar latitudes. They behave capriciously, developing very rapidly and then dying just as quickly. We show that strong dynamical processes in the atmosphere can sometimes cause it to become much colder locally than the underlying ocean, creating the conditions for hurricanes to form but only over small areas and for short times. We call the resulting storms "CYCLOPs".
Davide Faranda, Lucas Taligrot, Pascal Yiou, and Nada Caud
EGUsphere, https://doi.org/10.5194/egusphere-2025-2222, https://doi.org/10.5194/egusphere-2025-2222, 2025
This preprint is open for discussion and under review for Geoscience Communication (GC).
Short summary
Short summary
We developed a free online game called ClimarisQ to help people better understand climate change and extreme weather. By playing the game, users learn how decisions about the environment, money, and public opinion affect future risks. We studied how players reacted and found that the game makes climate issues easier to grasp and encourages discussion. This shows that interactive tools like games can support learning and action on climate and environmental challenges.
Robin Noyelle, Davide Faranda, Yoann Robin, Mathieu Vrac, and Pascal Yiou
Weather Clim. Dynam., 6, 817–839, https://doi.org/10.5194/wcd-6-817-2025, https://doi.org/10.5194/wcd-6-817-2025, 2025
Short summary
Short summary
Properties of extreme meteorological and climatological events are changing under human-caused climate change. Extreme event attribution methods seek to estimate the contribution of global warming in the probability and intensity changes of extreme events. Here we propose a procedure to estimate these quantities for the flow analogue method, which compares the observed event to similar events in the past.
Valerio Lembo, Gabriele Messori, Davide Faranda, Vera Melinda Galfi, Rune Grand Graversen, and Flavio Emanuele Pons
EGUsphere, https://doi.org/10.5194/egusphere-2025-2189, https://doi.org/10.5194/egusphere-2025-2189, 2025
Short summary
Short summary
Hemispheric heatwaves have fundamental implications for ecosystems and societies. They are studied together with the large-scale atmospheric dynamics, through the lens of the poleward heat transports by planetary-scale waves. Extremely weak transports of heat towards the Poles are found to be associated with hemispheric heatwaves in the Northern Hemisphere mid-latitudes. Therefore, we conclude that heat transports are a clear indicator, and possibly a precursor of hemispehric heatwaves.
Lia Rapella, Tommaso Alberti, Davide Faranda, and Philippe Drobinski
EGUsphere, https://doi.org/10.5194/egusphere-2025-1219, https://doi.org/10.5194/egusphere-2025-1219, 2025
Short summary
Short summary
Extreme weather events pose increasing challenges for aviation, including flight disruptions and infrastructure damage. This study examines the influence of anthropogenic climate change on four recent major storms across Europe, the USA, and East Asia. Our research underscores the growing intensity of extreme storms, driven by human-induced climate change, underscoring the need to adapt aviation strategies to an increasingly hazardous environment.
Pradeebane Vaittinada Ayar, Stella Bourdin, Davide Faranda, and Mathieu Vrac
EGUsphere, https://doi.org/10.5194/egusphere-2025-252, https://doi.org/10.5194/egusphere-2025-252, 2025
Short summary
Short summary
The tracking of Tropical cyclones (TCs) remains a matter of interest for the investigation of observed and simulated tropical cyclones. In this study, Random Forest (RF), a machine learning approach, is considered to track TCs. RF associates TC occurrence or absence to different atmospheric configurations. Compared to trackers found in the literature, it shows similar performance for tracking TCs, better control over false alarm, more flexibility and reveal key variables allowing to detect TCs.
Ferran Lopez-Marti, Mireia Ginesta, Davide Faranda, Anna Rutgersson, Pascal Yiou, Lichuan Wu, and Gabriele Messori
Earth Syst. Dynam., 16, 169–187, https://doi.org/10.5194/esd-16-169-2025, https://doi.org/10.5194/esd-16-169-2025, 2025
Short summary
Short summary
Explosive cyclones and atmospheric rivers are two main drivers of extreme weather in Europe. In this study, we investigate their joint changes in future climates over the North Atlantic. Our results show that both the concurrence of these events and the intensity of atmospheric rivers increase by the end of the century across different future scenarios. Furthermore, explosive cyclones associated with atmospheric rivers last longer and are deeper than those without atmospheric rivers.
Emmanouil Flaounas, Stavros Dafis, Silvio Davolio, Davide Faranda, Christian Ferrarin, Katharina Hartmuth, Assaf Hochman, Aristeidis Koutroulis, Samira Khodayar, Mario Marcello Miglietta, Florian Pantillon, Platon Patlakas, Michael Sprenger, and Iris Thurnherr
EGUsphere, https://doi.org/10.5194/egusphere-2024-2809, https://doi.org/10.5194/egusphere-2024-2809, 2024
Short summary
Short summary
Storm Daniel (2023) is one of the most catastrophic ones ever documented in the Mediterranean. Our results highlight the different dynamics and therefore the different predictability skill of precipitation, its extremes and impacts that have been produced in Greece and Libya, the two most affected countries. Our approach concerns a holistic analysis of the storm by articulating dynamics, weather prediction, hydrological and oceanographic implications, climate extremes and attribution theory.
Davide Faranda, Gabriele Messori, Erika Coppola, Tommaso Alberti, Mathieu Vrac, Flavio Pons, Pascal Yiou, Marion Saint Lu, Andreia N. S. Hisi, Patrick Brockmann, Stavros Dafis, Gianmarco Mengaldo, and Robert Vautard
Weather Clim. Dynam., 5, 959–983, https://doi.org/10.5194/wcd-5-959-2024, https://doi.org/10.5194/wcd-5-959-2024, 2024
Short summary
Short summary
We introduce ClimaMeter, a tool offering real-time insights into extreme-weather events. Our tool unveils how climate change and natural variability affect these events, affecting communities worldwide. Our research equips policymakers and the public with essential knowledge, fostering informed decisions and enhancing climate resilience. We analysed two distinct events, showcasing ClimaMeter's global relevance.
Lucas Fery and Davide Faranda
Weather Clim. Dynam., 5, 439–461, https://doi.org/10.5194/wcd-5-439-2024, https://doi.org/10.5194/wcd-5-439-2024, 2024
Short summary
Short summary
In this study, we analyse warm-season derechos – a type of severe convective windstorm – in France between 2000 and 2022, identifying 38 events. We compare their frequency and features with other countries. We also examine changes in the associated large-scale patterns. We find that convective instability has increased in southern Europe. However, the attribution of these changes to natural climate variability, human-induced climate change or a combination of both remains unclear.
Emma Holmberg, Gabriele Messori, Rodrigo Caballero, and Davide Faranda
Earth Syst. Dynam., 14, 737–765, https://doi.org/10.5194/esd-14-737-2023, https://doi.org/10.5194/esd-14-737-2023, 2023
Short summary
Short summary
We analyse the duration of large-scale patterns of air movement in the atmosphere, referred to as persistence, and whether unusually persistent patterns favour warm-temperature extremes in Europe. We see no clear relationship between summertime heatwaves and unusually persistent patterns. This suggests that heatwaves do not necessarily require the continued flow of warm air over a region and that local effects could be important for their occurrence.
Davide Faranda, Stella Bourdin, Mireia Ginesta, Meriem Krouma, Robin Noyelle, Flavio Pons, Pascal Yiou, and Gabriele Messori
Weather Clim. Dynam., 3, 1311–1340, https://doi.org/10.5194/wcd-3-1311-2022, https://doi.org/10.5194/wcd-3-1311-2022, 2022
Short summary
Short summary
We analyze the atmospheric circulation leading to impactful extreme events for the calendar year 2021 such as the Storm Filomena, Westphalia floods, Hurricane Ida and Medicane Apollo. For some of the events, we find that climate change has contributed to their occurrence or enhanced their intensity; for other events, we find that they are unprecedented. Our approach underscores the importance of considering changes in the atmospheric circulation when performing attribution studies.
Miriam D'Errico, Flavio Pons, Pascal Yiou, Soulivanh Tao, Cesare Nardini, Frank Lunkeit, and Davide Faranda
Earth Syst. Dynam., 13, 961–992, https://doi.org/10.5194/esd-13-961-2022, https://doi.org/10.5194/esd-13-961-2022, 2022
Short summary
Short summary
Climate change is already affecting weather extremes. In a warming climate, we will expect the cold spells to decrease in frequency and intensity. Our analysis shows that the frequency of circulation patterns leading to snowy cold-spell events over Italy will not decrease under business-as-usual emission scenarios, although the associated events may not lead to cold conditions in the warmer scenarios.
Bérengère Dubrulle, François Daviaud, Davide Faranda, Louis Marié, and Brice Saint-Michel
Nonlin. Processes Geophys., 29, 17–35, https://doi.org/10.5194/npg-29-17-2022, https://doi.org/10.5194/npg-29-17-2022, 2022
Short summary
Short summary
Present climate models discuss climate change but show no sign of bifurcation in the future. Is this because there is none or because they are in essence too simplified to be able to capture them? To get elements of an answer, we ran a laboratory experiment and discovered that the answer is not so simple.
Davide Faranda, Mathieu Vrac, Pascal Yiou, Flavio Maria Emanuele Pons, Adnane Hamid, Giulia Carella, Cedric Ngoungue Langue, Soulivanh Thao, and Valerie Gautard
Nonlin. Processes Geophys., 28, 423–443, https://doi.org/10.5194/npg-28-423-2021, https://doi.org/10.5194/npg-28-423-2021, 2021
Short summary
Short summary
Machine learning approaches are spreading rapidly in climate sciences. They are of great help in many practical situations where using the underlying equations is difficult because of the limitation in computational power. Here we use a systematic approach to investigate the limitations of the popular echo state network algorithms used to forecast the long-term behaviour of chaotic systems, such as the weather. Our results show that noise and intermittency greatly affect the performances.
Gabriele Messori and Davide Faranda
Clim. Past, 17, 545–563, https://doi.org/10.5194/cp-17-545-2021, https://doi.org/10.5194/cp-17-545-2021, 2021
Short summary
Short summary
The palaeoclimate community must both analyse large amounts of model data and compare very different climates. Here, we present a seemingly very abstract analysis approach that may be fruitfully applied to palaeoclimate numerical simulations. This approach characterises the dynamics of a given climate through a small number of metrics and is thus suited to face the above challenges.
Gabriele Messori, Nili Harnik, Erica Madonna, Orli Lachmy, and Davide Faranda
Earth Syst. Dynam., 12, 233–251, https://doi.org/10.5194/esd-12-233-2021, https://doi.org/10.5194/esd-12-233-2021, 2021
Short summary
Short summary
Atmospheric jets are a key component of the climate system and of our everyday lives. Indeed, they affect human activities by influencing the weather in many mid-latitude regions. However, we still lack a complete understanding of their dynamical properties. In this study, we try to relate the understanding gained in idealized computer simulations of the jets to our knowledge from observations of the real atmosphere.
Flavio Maria Emanuele Pons and Davide Faranda
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-352, https://doi.org/10.5194/nhess-2020-352, 2020
Preprint withdrawn
Short summary
Short summary
The objective motivating this study is the assessment of the impacts of winter climate extremes, which requires accurate simulation of snowfall. However, climate simulation models contain physical approximations, which result in biases that must be corrected using past data as a reference. We show how to exploit simulated temperature and precipitation to estimate snowfall from already bias-corrected variables, without requiring the elaboration of complex, multivariate bias adjustment techniques.
Cited articles
Agresti, A.: Foundations of linear and generalized linear models, John Wiley &
Sons, ISBN-13 978-1118730034,
ISBN-10 1118730038, 2015. a
Atchison, J. and Shen, S. M.: Logistic-normal distributions: Some properties
and uses, Biometrika, 67, 261–272, 1980. a
Auer, I., Böhm, R., Jurković, A., Orlik, A., Potzmann, R., Schöner,
W., Ungersböck, M., Brunetti, M., Nanni, T., Maugeri, M., Briffa, K., Jones, P., Efthymiadis, D., Mestre, O., Moisselin, J. M.,
Begert, M., Brazdil, R., Bochnicek, O., Cegnar, T., Gajic-Capka, M., Zaninovic, K., Majstorovic, Z.,
Szalai, S., Szentimrey, T., and Mercalli, L.: A new
instrumental precipitation dataset for the greater alpine region for the
period 1800–2002,
Int. J. Climatol., 25, 139–166, 2005. a
Auer Jr., A. H.: The rain versus snow threshold temperatures, Weatherwise, 27,
67–67, 1974. a
Ayar, P. V., Vrac, M., Bastin, S., Carreau, J., Déqué, M., and
Gallardo, C.: Intercomparison of statistical and dynamical downscaling models
under the EURO-and MED-CORDEX initiative framework: present climate
evaluations, Clim. Dynam., 46, 1301–1329, 2016. a
Bai, J.: Least squares estimation of a shift in linear processes,
J. Time Ser. Anal., 15, 453–472, 1994. a
Bai, J. and Perron, P.: Estimating and testing linear models with multiple
structural changes, Econometrica, 47–78, https://doi.org/10.2307/2998540, 1998. a
Basu, A., Shioya, H., and Park, C.: Statistical inference: the minimum distance
approach, CRC press, https://doi.org/10.1201/b10956, 2011. a
Beaumet, J., Menegoz, M., Gallée, H., Vionnet, V., Fettweis, X., Morin, S.,
Blanchet, J., Jourdain, N., Wilhelm, B., and Anquetin, S.: Detection of
precipitation and snow cover trends in the the European Alps over the last
century using model and observational data, in: EGU General Assembly
Conference Abstracts, 4–8 May 2020, EGU2020-18274,
https://doi.org/10.5194/egusphere-egu2020-18274, 2020. a
Behrangi, A., Yin, X., Rajagopal, S., Stampoulis, D., and Ye, H.: On
distinguishing snowfall from rainfall using near-surface atmospheric
information: C omparative analysis, uncertainties and hydrologic importance,
Q. J. Roy. Meteor. Soc., 144, 89–102, 2018. a
Benjamini, Y. and Hochberg, Y.: Controlling the false discovery rate: a
practical and powerful approach to multiple testing,
J. R. Stat. Soc. B, 57, 289–300, 1995. a
Bergström, S. and Singh, V.: Computer models of watershed hydrology, The
HBV Model, ISBN 9780918334916, 443–476, 1995. a
Bland, J. M. and Altman, D. G.: The odds ratio, Bmj, 320, 1468,
https://doi.org/10.1136/bmj.320.7247.1468, 2000. a
Bonelli, P., Lacavalla, M., Marcacci, P., Mariani, G., and Stella, G.: Wet snow hazard for power lines: a forecast and alert system applied in Italy, Nat. Hazards Earth Syst. Sci., 11, 2419–2431, https://doi.org/10.5194/nhess-11-2419-2011, 2011. a
Bonferroni, C.: Teoria statistica delle classi e calcolo delle probabilita,
Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commericiali
di Firenze, 8, 3–62, https://doi.org/10.1007/978-1-4613-0179-0_88, 1936. a
Copernicus Climate Change Service: ERA5: Fifth generation of ECMWF
atmospheric reanalyses of the global climate, https://doi.org/10.24381/cds.adbb2d47, 2017. a, b
Coppola, E., Nogherotto, R., Ciarlo', J. M., Giorgi, F., van Meijgaard, E.,
Kadygrov, N., Iles, C., Corre, L., Sandstad, M., Somot, S., Nabat, P., Vautard, R.,
Levavasseur, G., Schwingshackl, C., Sillmann, J., Kjellström, E., Nikulin, G., Aalbers, E.,
Lenderink, G., Christensen, O. B., Boberg, F., Sørland, S. L., Demory, M., Bülow, K.,
Teichmann, C., Warrach-Sagi, K., and Wulfmeyer, V.:
Assessment of the European climate projections as simulated by the large
EURO-CORDEX regional and global climate model ensemble, J.
Geophys. Res.-Atmos., 126, e2019JD032356, https://doi.org/10.1029/2019JD032356,, 2021. a
Darling, D. A.: The kolmogorov-smirnov, cramer-von mises tests, Ann.
Math. Stat., 28, 823–838, 1957. a
de Vries, H., Lenderink, G., and van Meijgaard, E.: Future snowfall in western
and central Europe projected with a high-resolution regional climate model
ensemble, Geophys. Res. Lett., 41, 4294–4299, 2014. a
Ding, B., Yang, K., Qin, J., Wang, L., Chen, Y., and He, X.: The dependence of
precipitation types on surface elevation and meteorological conditions and
its parameterization, J. Hydrol., 513, 154–163, 2014. a
Ducloux, H. and Nygaard, B. E.: 50-year return-period wet-snow load estimation based on weather station data for overhead line design in France, Nat. Hazards Earth Syst. Sci., 14, 3031–3041, https://doi.org/10.5194/nhess-14-3031-2014, 2014. a
Fox, J.: Applied regression analysis and generalized linear models, Sage
Publications, ISBN-13 978-1452205663,
ISBN-10: 1452205663, 2015. a
François, B., Vrac, M., Cannon, A. J., Robin, Y., and Allard, D.: Multivariate bias corrections of climate simulations: which benefits for which losses?, Earth Syst. Dynam., 11, 537–562, https://doi.org/10.5194/esd-11-537-2020, 2020. a
Frei, P., Kotlarski, S., Liniger, M. A., and Schär, C.: Future snowfall in the Alps: projections based on the EURO-CORDEX regional climate models, The Cryosphere, 12, 1–24, https://doi.org/10.5194/tc-12-1-2018, 2018. a
Gay, D. M.: Usage summary for selected optimization routines,
Computing science technical report, 153, 1–21, 1990. a
Grouillet, B., Ruelland, D., Vaittinada Ayar, P., and Vrac, M.: Sensitivity analysis of runoff modeling to statistical downscaling models in the western Mediterranean, Hydrol. Earth Syst. Sci., 20, 1031–1047, https://doi.org/10.5194/hess-20-1031-2016, 2016. a
Harrell Jr., F. E.: Regression modeling strategies: with applications to linear
models, logistic and ordinal regression, and survival analysis, Springer,
ISBN 978-3-319-19425-7, 2015. a
Hinde, J.: Logistic Normal Distribution, in: International Encyclopedia of
Statistical Science, ISBN 978-3-642-04898-2, 2011. a
Isotta, F. A., Frei, C., Weilguni, V., Perčec Tadić, M., Lassegues,
P., Rudolf, B., Pavan, V., Cacciamani, C., Antolini, G., Ratto, S. M.,
Maraldo, L., Micheletti, S., Bonati, V., Lussana, C.,
Ronchi, C.,Panettieri, E., Marigo, G., and Vertacnik, G.: The climate of daily precipitation in the Alps: development and
analysis of a high-resolution grid dataset from pan-Alpine rain-gauge data,
Int. J. Climatol., 34, 1657–1675, 2014. a
Kite, G.: The SLURP model, in: Computer models of watershed hydrology,
edited by: Singh, V. P., Water Resources Publications,
521–562, 1995. a
Kleiber, C., Hornik, K., Leisch, F., and Zeileis, A.: strucchange: An r package
for testing for structural change in linear regression models, J.
Stat. Softw., 7, 1–38, 2002. a
Krasting, J. P., Broccoli, A. J., Dixon, K. W., and Lanzante, J. R.: Future
changes in Northern Hemisphere snowfall, J. Climate, 26, 7813–7828,
2013. a
Lange, S.: Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0), Geosci. Model Dev., 12, 3055–3070, https://doi.org/10.5194/gmd-12-3055-2019, 2019. a
L'hôte, Y., Chevallier, P., Coudrain, A., Lejeune, Y., and Etchevers, P.:
Relationship between precipitation phase and air temperature: comparison
between the Bolivian Andes and the Swiss Alps/Relation entre phase de
précipitation et température de l'air: comparaison entre les Andes
Boliviennes et les Alpes Suisses, Hydrological Sciences Journal, 50, https://doi.org/10.1623/hysj.2005.50.6.989, 2005. a
Llasat, M. C., Turco, M., Quintana-Seguí, P., and Llasat-Botija, M.: The snow storm of 8 March 2010 in Catalonia (Spain): a paradigmatic wet-snow event with a high societal impact, Nat. Hazards Earth Syst. Sci., 14, 427–441, https://doi.org/10.5194/nhess-14-427-2014, 2014. a
Maraun, D.: Bias correcting climate change simulations-a critical review,
Current Climate Change Reports, 2, 211–220, 2016. a
McAfee, S. A., Walsh, J., and Rupp, T. S.: Statistically downscaled projections
of snow/rain partitioning for Alaska, Hydrol. Process., 28, 3930–3946,
2014. a
McCabe, G. J. and Wolock, D. M.: Joint variability of global runoff and global
sea surface temperatures, J. Hydrometeorol., 9, 816–824, 2008. a
McCabe, G. J. and Wolock, D. M.: Recent declines in western US snowpack in the
context of twentieth-century climate variability, Earth Interact., 13,
1–15, 2009. a
Meyer, J., Kohn, I., Stahl, K., Hakala, K., Seibert, J., and Cannon, A. J.: Effects of univariate and multivariate bias correction on hydrological impact projections in alpine catchments, Hydrol. Earth Syst. Sci., 23, 1339–1354, https://doi.org/10.5194/hess-23-1339-2019, 2019. a
Muggeo, V. M.: Segmented: an R package to fit regression models with
broken-line relationships, R news, 8, 20–25, 2008. a
Nikolov, D. and Wichura, B.: Analysis of spatial and temporal distribution of
wet snow events in Germany, in: XIII International Workshop on Atmospheric
Icing of Structures (IWAIS), IWAIS XIII, Andermatt, Switzerland, 8–11 September 2009, 2009. a
Pan, X., Yang, D., Li, Y., Barr, A., Helgason, W., Hayashi, M., Marsh, P., Pomeroy, J., and Janowicz, R. J.: Bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada, The Cryosphere, 10, 2347–2360, https://doi.org/10.5194/tc-10-2347-2016, 2016. a
Pardo, L.: Statistical inference based on divergence measures, CRC press, ISBN 9780429148521, 2018. a
Pons, F. and Faranda, D.: Statistical reconstruction of European winter snowfall
in reanalysis and climate models based on air temperature and total precipitation, figshare [data set], https://doi.org/10.6084/m9.figshare.20552745.v1, 2022. a
Rasmussen, R., Baker, B., Kochendorfer, J., Meyers, T., Landolt, S., Fischer,
A. P., Black, J., Thériault, J. M., Kucera, P., Gochis, D., Smith, C., Nitu, R., Hall, M., Ikeda, K., and
Gutmann, E.: How
well are we measuring snow: The NOAA/FAA/NCAR winter precipitation test bed,
B. Am. Meteorol. Soc., 93, 811–829, 2012. a
Scherrer, S. C. and Appenzeller, C.: Swiss Alpine snow pack variability: major
patterns and links to local climate and large-scale flow, Clim. Res.,
32, 187–199, 2006. a
Schmucki, E., Marty, C., Fierz, C., and Lehning, M.: Simulations of 21st
century snow response to climate change in Switzerland from a set of RCMs,
Int. J. Climatol., 35, 3262–3273, 2015. a
Teutschbein, C. and Seibert, J.: Bias correction of regional climate model
simulations for hydrological climate-change impact studies: Review and
evaluation of different methods, J. Hydrol., 456, 12–29, 2012. a
Teutschbein, C. and Seibert, J.: Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions?, Hydrol. Earth Syst. Sci., 17, 5061–5077, https://doi.org/10.5194/hess-17-5061-2013, 2013. a, b
US Army Corps of Engineers: Snow hydrology: Summary report of the snow
investigations, North Pacific Division Portland, OR, https://doi.org/10.3189/S0022143000024503, 1956. a, b, c
Vautard, R., Kadygrov, N., Iles, C., Boberg, F., Buonomo, E., Bülow, K.,
Coppola, E., Corre, L., van Meijgaard, E., Nogherotto, R., Sandstad, M., Schwingshakl, C.,
Somot, S., Aal-bers, E. E., Christensen, O., Ciarlo, J., Demory, M.-E., Giorgi,F., Jacob, D.,
Jones, R. G., Keuler, K., Kjellström, E., Lenderink,G., Levavasseur, G., Nikulin, G., Sillmann,
J., Solidoro, C., Sørland, S., Steger, C., Teichmann, C., Warrach-Sagi, K., and Wulfmeyer, V.: Evaluation
of the large EURO-CORDEX regional climate model ensemble, J.
Geophys. Res., 125, e2019JD032344, https://doi.org/10.1029/2019JD032344, 2020. a
Vrac, M.: Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R2D2) bias correction, Hydrol. Earth Syst. Sci., 22, 3175–3196, https://doi.org/10.5194/hess-22-3175-2018, 2018.
a
Vrac, M. and Friederichs, P.: Multivariate-intervariable, spatial, and
temporal-bias correction, J. Climate, 28, 218–237, 2015. a
Vrac, M., Drobinski, P., Merlo, A., Herrmann, M., Lavaysse, C., Li, L., and Somot, S.: Dynamical and statistical downscaling of the French Mediterranean climate: uncertainty assessment, Nat. Hazards Earth Syst. Sci., 12, 2769–2784, https://doi.org/10.5194/nhess-12-2769-2012, 2012. a
Wilcoxon, F.: Individual comparisons by ranking methods, in: Breakthroughs in
statistics, 196–202, Springer, https://doi.org/10.1007/978-1-4612-4380-9_16, 1992. a, b
Wood, S. N.: Generalized additive models: an introduction with R, CRC press,
https://doi.org/10.1201/9781315370279, 2017. a
Zubler, E. M., Scherrer, S. C., Croci-Maspoli, M., Liniger, M. A., and
Appenzeller, C.: Key climate indices in Switzerland; expected changes in a
future climate, Climatic Change, 123, 255–271, 2014. a
Short summary
The objective motivating this study is the assessment of the impacts of winter climate extremes, which requires accurate simulation of snowfall. However, climate simulation models contain physical approximations, which result in biases that must be corrected using past data as a reference. We show how to exploit simulated temperature and precipitation to estimate snowfall from already bias-corrected variables, without requiring the elaboration of complex, multivariate bias adjustment techniques.
The objective motivating this study is the assessment of the impacts of winter climate extremes,...
