Articles | Volume 16, issue 12
https://doi.org/10.5194/tc-16-4985-2022
© 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/tc-16-4985-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Dec 2022
Research article |
| 16 Dec 2022
| 16 Dec 2022
Impacts of snow assimilation on seasonal snow and meteorological forecasts for the Tibetan Plateau
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan, China
Hubei Key Laboratory of Water System Science for Sponge City
Construction, Wuhan University, Wuhan, China
Jie Chen
CORRESPONDING AUTHOR
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan, China
Hubei Key Laboratory of Water System Science for Sponge City
Construction, Wuhan University, Wuhan, China
NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway
Yvan J. Orsolini
NILU – Norwegian Institute for Air Research, Kjeller, Norway
Yiheng Xiang
Institute of Heavy Rain, China Meteorological Administration (CMA),
Wuhan, China
Retish Senan
European Centre for Medium-Range Weather Forecasts (ECWMF), Reading, UK
Patricia de Rosnay
European Centre for Medium-Range Weather Forecasts (ECWMF), Reading, UK
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Hydrol. Earth Syst. Sci., 26, 6457–6476, https://doi.org/10.5194/hess-26-6457-2022, https://doi.org/10.5194/hess-26-6457-2022, 2022
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Reforestation can influence climate, but the sensitivity of summer rainfall to reforestation is rarely investigated. We take two reforestation scenarios to assess the impacts of reforestation on summer rainfall under different reforestation proportions and explore the potential mechanisms. This study concludes that reforestation increases summer rainfall amount and extremes through thermodynamics processes, and the effects are more pronounced in populated areas than over the whole basin.
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Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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Beena Balan-Sarojini, Steffen Tietsche, Michael Mayer, Magdalena Balmaseda, Hao Zuo, Patricia de Rosnay, Tim Stockdale, and Frederic Vitart
The Cryosphere, 15, 325–344, https://doi.org/10.5194/tc-15-325-2021, https://doi.org/10.5194/tc-15-325-2021, 2021
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Seidai Nara, Tomohiro O. Sato, Takayoshi Yamada, Tamaki Fujinawa, Kota Kuribayashi, Takeshi Manabe, Lucien Froidevaux, Nathaniel J. Livesey, Kaley A. Walker, Jian Xu, Franz Schreier, Yvan J. Orsolini, Varavut Limpasuvan, Nario Kuno, and Yasuko Kasai
Atmos. Meas. Tech., 13, 6837–6852, https://doi.org/10.5194/amt-13-6837-2020, https://doi.org/10.5194/amt-13-6837-2020, 2020
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Marie-Estelle Demory, Ségolène Berthou, Jesús Fernández, Silje L. Sørland, Roman Brogli, Malcolm J. Roberts, Urs Beyerle, Jon Seddon, Rein Haarsma, Christoph Schär, Erasmo Buonomo, Ole B. Christensen, James M. Ciarlo ̀, Rowan Fealy, Grigory Nikulin, Daniele Peano, Dian Putrasahan, Christopher D. Roberts, Retish Senan, Christian Steger, Claas Teichmann, and Robert Vautard
Geosci. Model Dev., 13, 5485–5506, https://doi.org/10.5194/gmd-13-5485-2020, https://doi.org/10.5194/gmd-13-5485-2020, 2020
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Clément Albergel, Yongjun Zheng, Bertrand Bonan, Emanuel Dutra, Nemesio Rodríguez-Fernández, Simon Munier, Clara Draper, Patricia de Rosnay, Joaquin Muñoz-Sabater, Gianpaolo Balsamo, David Fairbairn, Catherine Meurey, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 24, 4291–4316, https://doi.org/10.5194/hess-24-4291-2020, https://doi.org/10.5194/hess-24-4291-2020, 2020
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Wenyan Qi, Jie Chen, Lu Li, Chong-yu Xu, Jingjing Li, Yiheng Xiang, and Shaobo Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-127, https://doi.org/10.5194/hess-2020-127, 2020
Manuscript not accepted for further review
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Nazario Tartaglione, Thomas Toniazzo, Yvan Orsolini, and Odd Helge Otterå
Ann. Geophys., 38, 545–555, https://doi.org/10.5194/angeo-38-545-2020, https://doi.org/10.5194/angeo-38-545-2020, 2020
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It is often claimed that a relationship between atmospheric temperature and geomagnetic activity exists. The aim of this paper is to highlight how the use of statistical tests, used to establish such a relationship, can be prone to misinterpretation when temporal and spatial autocorrelations are not taken into account. When these autocorrelations are considered, the relationship between temperature and geomagnetic activity no longer exists.
Lu Li, Marie Pontoppidan, Stefan Sobolowski, and Alfonso Senatore
Hydrol. Earth Syst. Sci., 24, 771–791, https://doi.org/10.5194/hess-24-771-2020, https://doi.org/10.5194/hess-24-771-2020, 2020
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We assessed the impact of initial conditions on convection-permitting simulations of a flood event over mountainous terrain. The calibrated convection-permitting model performs better than the simpler conceptual model. Discharge is slightly more sensitive to spin-up time than precipitation due to the influence of soil moisture. A maximum of 0.5 m of snow is converted to runoff irrespective of the initial snow depth, and this snowmelt contributes to discharge mostly during peak flow period.
Yvan Orsolini, Martin Wegmann, Emanuel Dutra, Boqi Liu, Gianpaolo Balsamo, Kun Yang, Patricia de Rosnay, Congwen Zhu, Wenli Wang, Retish Senan, and Gabriele Arduini
The Cryosphere, 13, 2221–2239, https://doi.org/10.5194/tc-13-2221-2019, https://doi.org/10.5194/tc-13-2221-2019, 2019
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The Tibetan Plateau region exerts a considerable influence on regional climate, yet the snowpack over that region is poorly represented in both climate and forecast models due a large precipitation and snowfall bias. We evaluate the snowpack in state-of-the-art atmospheric reanalyses against in situ observations and satellite remote sensing products. Improved snow initialisation through better use of snow observations in reanalyses may improve medium-range to seasonal weather forecasts.
Lu Li, Mingxi Shen, Yukun Hou, Chong-Yu Xu, Arthur F. Lutz, Jie Chen, Sharad K. Jain, Jingjing Li, and Hua Chen
Hydrol. Earth Syst. Sci., 23, 1483–1503, https://doi.org/10.5194/hess-23-1483-2019, https://doi.org/10.5194/hess-23-1483-2019, 2019
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Christopher D. Roberts, Retish Senan, Franco Molteni, Souhail Boussetta, Michael Mayer, and Sarah P. E. Keeley
Geosci. Model Dev., 11, 3681–3712, https://doi.org/10.5194/gmd-11-3681-2018, https://doi.org/10.5194/gmd-11-3681-2018, 2018
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This paper presents climate model configurations of the European Centre for Medium-Range Weather Forecasts Integrated Forecast System (ECMWF-IFS) for different combinations of ocean and atmosphere resolution. These configurations are used to perform multi-decadal experiments following the protocols of the High Resolution Model Intercomparison Project (HighResMIP) and phase 6 of the Coupled Model Intercomparison Project (CMIP6).
Clement Albergel, Emanuel Dutra, Simon Munier, Jean-Christophe Calvet, Joaquin Munoz-Sabater, Patricia de Rosnay, and Gianpaolo Balsamo
Hydrol. Earth Syst. Sci., 22, 3515–3532, https://doi.org/10.5194/hess-22-3515-2018, https://doi.org/10.5194/hess-22-3515-2018, 2018
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ECMWF recently released the first 7-year segment of its latest atmospheric reanalysis: ERA-5 (2010–2016). ERA-5 has important changes relative to ERA-Interim including higher spatial and temporal resolutions as well as a more recent model and data assimilation system. ERA-5 is foreseen to replace ERA-Interim reanalysis. One of the main goals of this study is to assess whether ERA-5 can enhance the simulation performances with respect to ERA-Interim when it is used to force a land surface model.
Steffen Tietsche, Magdalena Alonso-Balmaseda, Patricia Rosnay, Hao Zuo, Xiangshan Tian-Kunze, and Lars Kaleschke
The Cryosphere, 12, 2051–2072, https://doi.org/10.5194/tc-12-2051-2018, https://doi.org/10.5194/tc-12-2051-2018, 2018
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We compare Arctic sea-ice thickness from L-band microwave satellite observations and an ocean–sea ice reanalysis. There is good agreement for some regions and times but systematic discrepancy in others. Errors in both the reanalysis and observational products contribute to these discrepancies. Thus, we recommend proceeding with caution when using these observations for model validation or data assimilation. At the same time we emphasise their unique value for improving sea-ice forecast models.
Nemesio J. Rodríguez-Fernández, Joaquin Muñoz Sabater, Philippe Richaume, Patricia de Rosnay, Yann H. Kerr, Clement Albergel, Matthias Drusch, and Susanne Mecklenburg
Hydrol. Earth Syst. Sci., 21, 5201–5216, https://doi.org/10.5194/hess-21-5201-2017, https://doi.org/10.5194/hess-21-5201-2017, 2017
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The new SMOS satellite near-real-time (NRT) soil moisture (SM) product based on a neural network is presented. The NRT SM product has been evaluated with respect to the SMOS Level 2 product and against a large number of in situ measurements showing performances similar to those of the Level 2 product but it is available in less than 3.5 h after sensing. The new product is distributed by the European Space Agency and the European Organisation for the Exploitation of Meteorological Satellites.
Martin Wegmann, Yvan Orsolini, Emanuel Dutra, Olga Bulygina, Alexander Sterin, and Stefan Brönnimann
The Cryosphere, 11, 923–935, https://doi.org/10.5194/tc-11-923-2017, https://doi.org/10.5194/tc-11-923-2017, 2017
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We investigate long-term climate reanalyses datasets to infer their quality in reproducing snow depth values compared to in situ measured data from meteorological stations that go back to 1900. We found that the long-term reanalyses do a good job in reproducing snow depths but have some questionable snow states early in the 20th century. Thus, with care, climate reanalyses can be a valuable tool to investigate spatial snow evolution in global warming and climate change studies.
Kazutoshi Sagi, Kristell Pérot, Donal Murtagh, and Yvan Orsolini
Atmos. Chem. Phys., 17, 1791–1803, https://doi.org/10.5194/acp-17-1791-2017, https://doi.org/10.5194/acp-17-1791-2017, 2017
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We assess and quantify the ozone loss driven by NOx, triggered by stratospheric warmings and the halogens-induced ozone loss, using data assimilation results over a decade.
To illustrate the difference between halogen-induced loss and NOx-induced loss, we compared a relatively cold and stable winter (2010/2011) with a composite calculation of four winters (2003/2004, 2005/2006, 2008/2009 and 2012/2013) which were all affected by a major mid-winter sudden stratospheric warming event.
Anaïs Barella-Ortiz, Jan Polcher, Patricia de Rosnay, Maria Piles, and Emiliano Gelati
Hydrol. Earth Syst. Sci., 21, 357–375, https://doi.org/10.5194/hess-21-357-2017, https://doi.org/10.5194/hess-21-357-2017, 2017
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L-band radiometry is considered to be one of the most suitable techniques for estimating surface soil moisture (SSM) by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm which yields SSM. This paper compares brightness temperatures measured by the SMOS mission to two different sets of modelled ones. It shows that models and remote-sensed values agree well in temporal variability, but not in their spatial structures.
Rasmus E. Benestad, Retish Senan, and Yvan Orsolini
Earth Syst. Dynam., 7, 851–861, https://doi.org/10.5194/esd-7-851-2016, https://doi.org/10.5194/esd-7-851-2016, 2016
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Seasonal predictions have been challenging for mid-latitude regions such as Europe, and we suspect that one reason may be due to subjective choices in how the forecast models are configured. We tested how (1) the inclusion and omission of the representation of the stratosphere affect the predictions and (2) the degree of detail in the sea-ice description. The test was carried out with a set of simulations (experiments) using a technique known as "factorial regression".
Christine Smith-Johnsen, Yvan Orsolini, Frode Stordal, Varavut Limpasuvan, and Kristell Pérot
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-758, https://doi.org/10.5194/acp-2016-758, 2016
Preprint withdrawn
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Mesospheric ozone enhancements during sudden stratospheric warmings in the northern hemisphere have been reported in the literature. In the southern hemisphere, only one warming event has occurred, and this paper is the first to explain the mesospheric ozone enhancement during this event in 2002, using both a whole atmosphere chemistry climate model and satellite observations from GOMOS.
G. Balsamo, C. Albergel, A. Beljaars, S. Boussetta, E. Brun, H. Cloke, D. Dee, E. Dutra, J. Muñoz-Sabater, F. Pappenberger, P. de Rosnay, T. Stockdale, and F. Vitart
Hydrol. Earth Syst. Sci., 19, 389–407, https://doi.org/10.5194/hess-19-389-2015, https://doi.org/10.5194/hess-19-389-2015, 2015
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ERA-Interim/Land is a global land surface reanalysis covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim and a precipitation bias correction based on GPCP. A selection of verification results show the added value in representing the terrestrial water cycle and its main land surface storages and fluxes.
Related subject area
Discipline: Snow | Subject: Climate Interactions
Projection of snowfall extremes in the French Alps as a function of elevation and global warming level
Changes in March mean snow water equivalent since the mid-20th century and the contributing factors in reanalyses and CMIP6 climate models
Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981–2019) using climate reanalyses and machine learning
Synoptic control over winter snowfall variability observed in a remote site of Apennine Mountains (Italy), 1884–2015
Land–atmosphere interactions in sub-polar and alpine climates in the CORDEX Flagship Pilot Study Land Use and Climate Across Scales (LUCAS) models – Part 2: The role of changing vegetation
Snow conditions in northern Europe: the dynamics of interannual variability versus projected long-term change
Anthropogenic climate change versus internal climate variability: impacts on snow cover in the Swiss Alps
Historical Northern Hemisphere snow cover trends and projected changes in the CMIP6 multi-model ensemble
Optimization of over-summer snow storage at midlatitudes and low elevation
An efficient surface energy–mass balance model for snow and ice
Spring snow albedo feedback over northern Eurasia: Comparing in situ measurements with reanalysis products
Erwan Le Roux, Guillaume Evin, Raphaëlle Samacoïts, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
The Cryosphere, 17, 4691–4704, https://doi.org/10.5194/tc-17-4691-2023, https://doi.org/10.5194/tc-17-4691-2023, 2023
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We assess projected changes in snowfall extremes in the French Alps as a function of elevation and global warming level for a high-emission scenario. On average, heavy snowfall is projected to decrease below 3000 m and increase above 3600 m, while extreme snowfall is projected to decrease below 2400 m and increase above 3300 m. At elevations in between, an increase is projected until +3 °C of global warming and then a decrease. These results have implications for the management of risks.
Jouni Räisänen
The Cryosphere, 17, 1913–1934, https://doi.org/10.5194/tc-17-1913-2023, https://doi.org/10.5194/tc-17-1913-2023, 2023
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Changes in snow amount since the mid-20th century are studied, focusing on the mechanisms that have changed the water equivalent of the snowpack (SWE). Both reanalysis and climate model data show a decrease in SWE in most of the Northern Hemisphere. The total winter precipitation has increased in most areas, but this has been compensated for by reduced snowfall-to-precipitation ratio and enhanced snowmelt. However, the details and magnitude of these trends vary between different data sets.
Matteo Guidicelli, Matthias Huss, Marco Gabella, and Nadine Salzmann
The Cryosphere, 17, 977–1002, https://doi.org/10.5194/tc-17-977-2023, https://doi.org/10.5194/tc-17-977-2023, 2023
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Spatio-temporal reconstruction of winter glacier mass balance is important for assessing long-term impacts of climate change. However, high-altitude regions significantly lack reliable observations, which is limiting the calibration of glaciological and hydrological models. We aim at improving knowledge on the spatio-temporal variations in winter glacier mass balance by exploring the combination of data from reanalyses and direct snow accumulation observations on glaciers with machine learning.
Vincenzo Capozzi, Carmela De Vivo, and Giorgio Budillon
The Cryosphere, 16, 1741–1763, https://doi.org/10.5194/tc-16-1741-2022, https://doi.org/10.5194/tc-16-1741-2022, 2022
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This work documents the snowfall variability observed from late XIX century to recent years in Montevergine (southern Italy) and discusses its relationship with large-scale atmospheric circulation. The main results lie in the absence of a trend until mid-1970s, in the strong reduction of the snowfall quantity and frequency from mid-1970s to 1990s and in the increase of both variables from early 2000s. In the past 50 years, the nivometric regime has been strongly modulated by AO and NAO indices.
Priscilla A. Mooney, Diana Rechid, Edouard L. Davin, Eleni Katragkou, Natalie de Noblet-Ducoudré, Marcus Breil, Rita M. Cardoso, Anne Sophie Daloz, Peter Hoffmann, Daniela C. A. Lima, Ronny Meier, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Toelle, and Marianne T. Lund
The Cryosphere, 16, 1383–1397, https://doi.org/10.5194/tc-16-1383-2022, https://doi.org/10.5194/tc-16-1383-2022, 2022
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We use multiple regional climate models to show that afforestation in sub-polar and alpine regions reduces the radiative impact of snow albedo on the atmosphere, reduces snow cover, and delays the start of the snowmelt season. This is important for local communities that are highly reliant on snowpack for water resources and winter tourism. However, models disagree on the amount of change particularly when snow is melting. This shows that more research is needed on snow–vegetation interactions.
Jouni Räisänen
The Cryosphere, 15, 1677–1696, https://doi.org/10.5194/tc-15-1677-2021, https://doi.org/10.5194/tc-15-1677-2021, 2021
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Interannual variability of snow amount in northern Europe is studied. In the coldest areas, total winter precipitation governs snow amount variability. In warmer regions, the fraction of snowfall that survives without melting is more important. Since winter temperature and precipitation are positively correlated, there is often more snow in milder winters in the coldest areas. However, in model simulations of a warmer future climate, snow amount decreases nearly everywhere in northern Europe.
Fabian Willibald, Sven Kotlarski, Adrienne Grêt-Regamey, and Ralf Ludwig
The Cryosphere, 14, 2909–2924, https://doi.org/10.5194/tc-14-2909-2020, https://doi.org/10.5194/tc-14-2909-2020, 2020
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Climate change will significantly reduce snow cover, but the extent remains disputed. We use regional climate model data as a driver for a snow model to investigate the impacts of climate change and climate variability on snow. We show that natural climate variability is a dominant source of uncertainty in future snow trends. We show that anthropogenic climate change will change the interannual variability of snow. Those factors will increase the vulnerabilities of snow-dependent economies.
Lawrence Mudryk, María Santolaria-Otín, Gerhard Krinner, Martin Ménégoz, Chris Derksen, Claire Brutel-Vuilmet, Mike Brady, and Richard Essery
The Cryosphere, 14, 2495–2514, https://doi.org/10.5194/tc-14-2495-2020, https://doi.org/10.5194/tc-14-2495-2020, 2020
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We analyze how well updated state-of-the-art climate models reproduce observed historical snow cover extent and snow mass and how they project that these quantities will change up to the year 2100. Overall the updated models better represent historical snow extent than previous models, and they simulate stronger historical trends in snow extent and snow mass. They project that spring snow extent will decrease by 8 % for each degree Celsius that the global surface air temperature increases.
Hannah S. Weiss, Paul R. Bierman, Yves Dubief, and Scott D. Hamshaw
The Cryosphere, 13, 3367–3382, https://doi.org/10.5194/tc-13-3367-2019, https://doi.org/10.5194/tc-13-3367-2019, 2019
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Climate change is devastating winter tourism. High-elevation, high-latitude ski centers have turned to saving snow over the summer. We present results of two field seasons to test and optimize over-summer snow storage at a midlatitude, low-elevation nordic ski center in the northeastern USA. In 2018, we tested coverings and found success overlaying 20 cm of wet woodchips with a reflective sheet. In 2019, we employed this strategy to a large pile and stored sufficient snow to open the ski season.
Andreas Born, Michael A. Imhof, and Thomas F. Stocker
The Cryosphere, 13, 1529–1546, https://doi.org/10.5194/tc-13-1529-2019, https://doi.org/10.5194/tc-13-1529-2019, 2019
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We present a new numerical model to simulate the surface energy and mass balance of snow and ice. While similar models exist and cover a wide range of complexity from empirical models to those that simulate the microscopic structure of individual snow grains, we aim to strike a balance between physical completeness and numerical efficiency. This new model will enable physically accurate simulations over timescales of hundreds of millennia, a key requirement of investigating ice age cycles.
Martin Wegmann, Emanuel Dutra, Hans-Werner Jacobi, and Olga Zolina
The Cryosphere, 12, 1887–1898, https://doi.org/10.5194/tc-12-1887-2018, https://doi.org/10.5194/tc-12-1887-2018, 2018
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An important factor for Earth's climate is the high sunlight reflectivity of snow. By melting, it reveals darker surfaces and sunlight is converted to heat. We investigate how well this process is represented in reanalyses data sets compared to observations over Russia. We found snow processes to be well represented, but reflectivity variability needs to be improved. Our results highlight the need for a better representation of this key climate change feedback process in modelled data.
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Short summary
Snow assimilation over the Tibetan Plateau (TP) may influence seasonal forecasts over this region. To investigate the impacts of snow assimilation on the seasonal forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer in 2018. The results show that snow assimilation can improve seasonal forecasts over the TP through the interaction between land and atmosphere.
Snow assimilation over the Tibetan Plateau (TP) may influence seasonal forecasts over this...
