Articles | Volume 17, issue 6
https://doi.org/10.5194/tc-17-2437-2023
© Author(s) 2023. 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-17-2437-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jun 2023
Research article |
| 22 Jun 2023
| 22 Jun 2023
Change in the potential snowfall phenology: past, present, and future in the Chinese Tianshan mountainous region, Central Asia
Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070,
China
National-Local Joint Engineering Research Center of Technologies and
Applications for National Geographic State Monitoring, Lanzhou 730070,
China
Gansu Provincial Engineering Laboratory for National Geographic State
Monitoring, Lanzhou 730070, China
Xinyu Liu
Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070,
China
National-Local Joint Engineering Research Center of Technologies and
Applications for National Geographic State Monitoring, Lanzhou 730070,
China
Gansu Provincial Engineering Laboratory for National Geographic State
Monitoring, Lanzhou 730070, China
Kaixin Zhao
Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070,
China
National-Local Joint Engineering Research Center of Technologies and
Applications for National Geographic State Monitoring, Lanzhou 730070,
China
Gansu Provincial Engineering Laboratory for National Geographic State
Monitoring, Lanzhou 730070, China
Xu Zhang
Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070,
China
National-Local Joint Engineering Research Center of Technologies and
Applications for National Geographic State Monitoring, Lanzhou 730070,
China
Gansu Provincial Engineering Laboratory for National Geographic State
Monitoring, Lanzhou 730070, China
Lanhai Li
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute
of Ecology and Geography, Chinese Academy of Sciences, Ürümqi 830011, China
Research Center for Ecology and Environment of Central Asia, Chinese
Academy of Sciences, Ürümqi 830011, China
Related authors
No articles found.
Jiansheng Hao, Farong Huang, Ditao Cheng, Shuyong Mu, and Lanhai Li
Geosci. Instrum. Method. Data Syst. Discuss., https://doi.org/10.5194/gi-2020-14, https://doi.org/10.5194/gi-2020-14, 2020
Revised manuscript not accepted
Related subject area
Discipline: Snow | Subject: Seasonal Snow
Which global reanalysis dataset has better representativeness in snow cover on the Tibetan Plateau?
Snow depth in high-resolution regional climate model simulations over southern Germany – suitable for extremes and impact-related research?
Snow water equivalent retrieval over Idaho – Part 2: Using L-band UAVSAR repeat-pass interferometry
A simple snow temperature index model exposes discrepancies between reanalysis snow water equivalent products
Spatiotemporal snow water storage uncertainty in the midlatitude American Cordillera
Evaluation of snow cover properties in ERA5 and ERA5-Land with several satellite-based datasets in the Northern Hemisphere in spring 1982–2018
Multi-decadal analysis of past winter temperature, precipitation and snow cover data in the European Alps from reanalyses, climate models and observational datasets
Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas
The benefits of homogenising snow depth series – Impacts on decadal trends and extremes for Switzerland
Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain
Impact of measured and simulated tundra snowpack properties on heat transfer
Homogeneity assessment of Swiss snow depth series: comparison of break detection capabilities of (semi-)automatic homogenization methods
Propagating information from snow observations with CrocO ensemble data assimilation system: a 10-years case study over a snow depth observation network
Evaluation of Northern Hemisphere snow water equivalent in CMIP6 models during 1982–2014
Multilayer observation and estimation of the snowpack cold content in a humid boreal coniferous forest of eastern Canada
Spatiotemporal distribution of seasonal snow water equivalent in High Mountain Asia from an 18-year Landsat–MODIS era snow reanalysis dataset
Local-scale variability of seasonal mean and extreme values of in situ snow depth and snowfall measurements
Observed snow depth trends in the European Alps: 1971 to 2019
Snow Ensemble Uncertainty Project (SEUP): quantification of snow water equivalent uncertainty across North America via ensemble land surface modeling
Quantification of the radiative impact of light-absorbing particles during two contrasted snow seasons at Col du Lautaret (2058 m a.s.l., French Alps)
Snow depth estimation and historical data reconstruction over China based on a random forest machine learning approach
Evaluation of long-term Northern Hemisphere snow water equivalent products
Towards a webcam-based snow cover monitoring network: methodology and evaluation
Simulated single-layer forest canopies delay Northern Hemisphere snowmelt
Converting snow depth to snow water equivalent using climatological variables
Avalanches and micrometeorology driving mass and energy balance of the lowest perennial ice field of the Alps: a case study
The optical characteristics and sources of chromophoric dissolved organic matter (CDOM) in seasonal snow of northwestern China
Brief Communication: Early season snowpack loss and implications for oversnow vehicle recreation travel planning
Multi-component ensembles of future meteorological and natural snow conditions for 1500 m altitude in the Chartreuse mountain range, Northern French Alps
Shirui Yan, Yang Chen, Yaliang Hou, Kexin Liu, Xuejing Li, Yuxuan Xing, Dongyou Wu, Jiecan Cui, Yue Zhou, Wei Pu, and Xin Wang
The Cryosphere, 18, 4089–4109, https://doi.org/10.5194/tc-18-4089-2024, https://doi.org/10.5194/tc-18-4089-2024, 2024
Short summary
Short summary
The snow cover over the Tibetan Plateau (TP) plays a role in climate and hydrological systems, yet there are uncertainties in snow cover fraction (SCF) estimations within reanalysis datasets. This study utilized the Snow Property Inversion from Remote Sensing (SPIReS) SCF data to assess the accuracy of eight widely used reanalysis SCF datasets over the TP. Factors contributing to uncertainties were analyzed, and a combined averaging method was employed to provide optimized SCF simulations.
Benjamin Poschlod and Anne Sophie Daloz
The Cryosphere, 18, 1959–1981, https://doi.org/10.5194/tc-18-1959-2024, https://doi.org/10.5194/tc-18-1959-2024, 2024
Short summary
Short summary
Information about snow depth is important within climate research but also many other sectors, such as tourism, mobility, civil engineering, and ecology. Climate models often feature a spatial resolution which is too coarse to investigate snow depth. Here, we analyse high-resolution simulations and identify added value compared to a coarser-resolution state-of-the-art product. Also, daily snow depth extremes are well reproduced by two models.
Zachary Hoppinen, Shadi Oveisgharan, Hans-Peter Marshall, Ross Mower, Kelly Elder, and Carrie Vuyovich
The Cryosphere, 18, 575–592, https://doi.org/10.5194/tc-18-575-2024, https://doi.org/10.5194/tc-18-575-2024, 2024
Short summary
Short summary
We used changes in radar echo travel time from multiple airborne flights to estimate changes in snow depths across Idaho for two winters. We compared our radar-derived retrievals to snow pits, weather stations, and a 100 m resolution numerical snow model. We had a strong Pearson correlation and root mean squared error of 10 cm relative to in situ measurements. Our retrievals also correlated well with our model, especially in regions of dry snow and low tree coverage.
Aleksandra Elias Chereque, Paul J. Kushner, Lawrence Mudryk, Chris Derksen, and Colleen Mortimer
EGUsphere, https://doi.org/10.5194/egusphere-2024-201, https://doi.org/10.5194/egusphere-2024-201, 2024
Short summary
Short summary
We look at three commonly used snow depth datasets that come from a complex combination of snow modeling and historical measurements. When compared with each other, these datasets have differences that arise for various reasons. We show that a simple snow model can be used to examine consistency and highlight issues with the complex datasets. This method indicates that one of the complex datasets should be excluded from further studies.
Yiwen Fang, Yufei Liu, Dongyue Li, Haorui Sun, and Steven A. Margulis
The Cryosphere, 17, 5175–5195, https://doi.org/10.5194/tc-17-5175-2023, https://doi.org/10.5194/tc-17-5175-2023, 2023
Short summary
Short summary
Using newly developed snow reanalysis datasets as references, snow water storage is at high uncertainty among commonly used global products in the Andes and low-resolution products in the western United States, where snow is the key element of water resources. In addition to precipitation, elevation differences and model mechanism variances drive snow uncertainty. This work provides insights for research applying these products and generating future products in areas with limited in situ data.
Kerttu Kouki, Kari Luojus, and Aku Riihelä
The Cryosphere, 17, 5007–5026, https://doi.org/10.5194/tc-17-5007-2023, https://doi.org/10.5194/tc-17-5007-2023, 2023
Short summary
Short summary
We evaluated snow cover properties in state-of-the-art reanalyses (ERA5 and ERA5-Land) with satellite-based datasets. Both ERA5 and ERA5-Land overestimate snow mass, whereas albedo estimates are more consistent between the datasets. Snow cover extent (SCE) is accurately described in ERA5-Land, while ERA5 shows larger SCE than the satellite-based datasets. The trends in snow mass, SCE, and albedo are mostly negative in 1982–2018, and the negative trends become more apparent when spring advances.
Diego Monteiro and Samuel Morin
The Cryosphere, 17, 3617–3660, https://doi.org/10.5194/tc-17-3617-2023, https://doi.org/10.5194/tc-17-3617-2023, 2023
Short summary
Short summary
Beyond directly using in situ observations, often sparsely available in mountain regions, climate model simulations and so-called reanalyses are increasingly used for climate change impact studies. Here we evaluate such datasets in the European Alps from 1950 to 2020, with a focus on snow cover information and its main drivers: air temperature and precipitation. In terms of variability and trends, we identify several limitations and provide recommendations for future use of these datasets.
Leon J. Bührle, Mauro Marty, Lucie A. Eberhard, Andreas Stoffel, Elisabeth D. Hafner, and Yves Bühler
The Cryosphere, 17, 3383–3408, https://doi.org/10.5194/tc-17-3383-2023, https://doi.org/10.5194/tc-17-3383-2023, 2023
Short summary
Short summary
Information on the snow depth distribution is crucial for numerous applications in high-mountain regions. However, only specific measurements can accurately map the present variability of snow depths within complex terrain. In this study, we show the reliable processing of images from aeroplane to large (> 100 km2) detailed and accurate snow depth maps around Davos (CH). We use these maps to describe the existing snow depth distribution, other special features and potential applications.
Moritz Buchmann, Gernot Resch, Michael Begert, Stefan Brönnimann, Barbara Chimani, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 17, 653–671, https://doi.org/10.5194/tc-17-653-2023, https://doi.org/10.5194/tc-17-653-2023, 2023
Short summary
Short summary
Our current knowledge of spatial and temporal snow depth trends is based almost exclusively on time series of non-homogenised observational data. However, like other long-term series from observations, they are susceptible to inhomogeneities that can affect the trends and even change the sign. To assess the relevance of homogenisation for daily snow depths, we investigated its impact on trends and changes in extreme values of snow indices between 1961 and 2021 in the Swiss observation network.
Zachary S. Miller, Erich H. Peitzsch, Eric A. Sproles, Karl W. Birkeland, and Ross T. Palomaki
The Cryosphere, 16, 4907–4930, https://doi.org/10.5194/tc-16-4907-2022, https://doi.org/10.5194/tc-16-4907-2022, 2022
Short summary
Short summary
Snow depth varies across steep, complex mountain landscapes due to interactions between dynamic natural processes. Our study of a winter time series of high-resolution snow depth maps found that spatial resolutions greater than 0.5 m do not capture the complete patterns of snow depth spatial variability at a couloir study site in the Bridger Range of Montana, USA. The results of this research have the potential to reduce uncertainty associated with snowpack and snow water resource analysis.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Melody Sandells, Chris Derksen, Branden Walker, Gabriel Hould Gosselin, Oliver Sonnentag, Richard Essery, Richard Kelly, Phillip Marsh, Joshua King, and Julia Boike
The Cryosphere, 16, 4201–4222, https://doi.org/10.5194/tc-16-4201-2022, https://doi.org/10.5194/tc-16-4201-2022, 2022
Short summary
Short summary
Measurements of the properties of the snow and soil were compared to simulations of the Community Land Model to see how well the model represents snow insulation. Simulations underestimated snow thermal conductivity and wintertime soil temperatures. We test two approaches to reduce the transfer of heat through the snowpack and bring simulated soil temperatures closer to measurements, with an alternative parameterisation of snow thermal conductivity being more appropriate.
Moritz Buchmann, John Coll, Johannes Aschauer, Michael Begert, Stefan Brönnimann, Barbara Chimani, Gernot Resch, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 16, 2147–2161, https://doi.org/10.5194/tc-16-2147-2022, https://doi.org/10.5194/tc-16-2147-2022, 2022
Short summary
Short summary
Knowledge about inhomogeneities in a data set is important for any subsequent climatological analysis. We ran three well-established homogenization methods and compared the identified break points. By only treating breaks as valid when detected by at least two out of three methods, we enhanced the robustness of our results. We found 45 breaks within 42 of 184 investigated series; of these 70 % could be explained by events recorded in the station history.
Bertrand Cluzet, Matthieu Lafaysse, César Deschamps-Berger, Matthieu Vernay, and Marie Dumont
The Cryosphere, 16, 1281–1298, https://doi.org/10.5194/tc-16-1281-2022, https://doi.org/10.5194/tc-16-1281-2022, 2022
Short summary
Short summary
The mountainous snow cover is highly variable at all temporal and spatial scales. Snow cover models suffer from large errors, while snowpack observations are sparse. Data assimilation combines them into a better estimate of the snow cover. A major challenge is to propagate information from observed into unobserved areas. This paper presents a spatialized version of the particle filter, in which information from in situ snow depth observations is successfully used to constrain nearby simulations.
Kerttu Kouki, Petri Räisänen, Kari Luojus, Anna Luomaranta, and Aku Riihelä
The Cryosphere, 16, 1007–1030, https://doi.org/10.5194/tc-16-1007-2022, https://doi.org/10.5194/tc-16-1007-2022, 2022
Short summary
Short summary
We analyze state-of-the-art climate models’ ability to describe snow mass and whether biases in modeled temperature or precipitation can explain the discrepancies in snow mass. In winter, biases in precipitation are the main factor affecting snow mass, while in spring, biases in temperature becomes more important, which is an expected result. However, temperature or precipitation cannot explain all snow mass discrepancies. Other factors, such as models’ structural errors, are also significant.
Achut Parajuli, Daniel F. Nadeau, François Anctil, and Marco Alves
The Cryosphere, 15, 5371–5386, https://doi.org/10.5194/tc-15-5371-2021, https://doi.org/10.5194/tc-15-5371-2021, 2021
Short summary
Short summary
Cold content is the energy required to attain an isothermal (0 °C) state and resulting in the snow surface melt. This study focuses on determining the multi-layer cold content (30 min time steps) relying on field measurements, snow temperature profile, and empirical formulation in four distinct forest sites of Montmorency Forest, eastern Canada. We present novel research where the effect of forest structure, local topography, and meteorological conditions on cold content variability is explored.
Yufei Liu, Yiwen Fang, and Steven A. Margulis
The Cryosphere, 15, 5261–5280, https://doi.org/10.5194/tc-15-5261-2021, https://doi.org/10.5194/tc-15-5261-2021, 2021
Short summary
Short summary
We examined the spatiotemporal distribution of stored water in the seasonal snowpack over High Mountain Asia, based on a new snow reanalysis dataset. The dataset was derived utilizing satellite-observed snow information, which spans across 18 water years, at a high spatial (~ 500 m) and temporal (daily) resolution. Snow mass and snow storage distribution over space and time are analyzed in this paper, which brings new insights into understanding the snowpack variability over this region.
Moritz Buchmann, Michael Begert, Stefan Brönnimann, and Christoph Marty
The Cryosphere, 15, 4625–4636, https://doi.org/10.5194/tc-15-4625-2021, https://doi.org/10.5194/tc-15-4625-2021, 2021
Short summary
Short summary
We investigated the impacts of local-scale variations by analysing snow climate indicators derived from parallel snow measurements. We found the largest relative inter-pair differences for all indicators in spring and the smallest in winter. The findings serve as an important basis for our understanding of uncertainties of commonly used snow indicators and provide, in combination with break-detection methods, the groundwork in view of any homogenization efforts regarding snow time series.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, https://doi.org/10.5194/tc-15-1343-2021, 2021
Short summary
Short summary
The first Alpine-wide assessment of station snow depth has been enabled by a collaborative effort of the research community which involves more than 30 partners, 6 countries, and more than 2000 stations. It shows how snow in the European Alps matches the climatic zones and gives a robust estimate of observed changes: stronger decreases in the snow season at low elevations and in spring at all elevations, however, with considerable regional differences.
Rhae Sung Kim, Sujay Kumar, Carrie Vuyovich, Paul Houser, Jessica Lundquist, Lawrence Mudryk, Michael Durand, Ana Barros, Edward J. Kim, Barton A. Forman, Ethan D. Gutmann, Melissa L. Wrzesien, Camille Garnaud, Melody Sandells, Hans-Peter Marshall, Nicoleta Cristea, Justin M. Pflug, Jeremy Johnston, Yueqian Cao, David Mocko, and Shugong Wang
The Cryosphere, 15, 771–791, https://doi.org/10.5194/tc-15-771-2021, https://doi.org/10.5194/tc-15-771-2021, 2021
Short summary
Short summary
High SWE uncertainty is observed in mountainous and forested regions, highlighting the need for high-resolution snow observations in these regions. Substantial uncertainty in snow water storage in Tundra regions and the dominance of water storage in these regions points to the need for high-accuracy snow estimation. Finally, snow measurements during the melt season are most needed at high latitudes, whereas observations at near peak snow accumulations are most beneficial over the midlatitudes.
François Tuzet, Marie Dumont, Ghislain Picard, Maxim Lamare, Didier Voisin, Pierre Nabat, Mathieu Lafaysse, Fanny Larue, Jesus Revuelto, and Laurent Arnaud
The Cryosphere, 14, 4553–4579, https://doi.org/10.5194/tc-14-4553-2020, https://doi.org/10.5194/tc-14-4553-2020, 2020
Short summary
Short summary
This study presents a field dataset collected over 30 d from two snow seasons at a Col du Lautaret site (French Alps). The dataset compares different measurements or estimates of light-absorbing particle (LAP) concentrations in snow, highlighting a gap in the current understanding of the measurement of these quantities. An ensemble snowpack model is then evaluated for this dataset estimating that LAPs shorten each snow season by around 10 d despite contrasting meteorological conditions.
Jianwei Yang, Lingmei Jiang, Kari Luojus, Jinmei Pan, Juha Lemmetyinen, Matias Takala, and Shengli Wu
The Cryosphere, 14, 1763–1778, https://doi.org/10.5194/tc-14-1763-2020, https://doi.org/10.5194/tc-14-1763-2020, 2020
Short summary
Short summary
There are many challenges for accurate snow depth estimation using passive microwave data. Machine learning (ML) techniques are deemed to be powerful tools for establishing nonlinear relations between independent variables and a given target variable. In this study, we investigate the potential capability of the random forest (RF) model on snow depth estimation at temporal and spatial scales. The result indicates that the fitted RF algorithms perform better on temporal than spatial scales.
Colleen Mortimer, Lawrence Mudryk, Chris Derksen, Kari Luojus, Ross Brown, Richard Kelly, and Marco Tedesco
The Cryosphere, 14, 1579–1594, https://doi.org/10.5194/tc-14-1579-2020, https://doi.org/10.5194/tc-14-1579-2020, 2020
Short summary
Short summary
Existing stand-alone passive microwave SWE products have markedly different climatological SWE patterns compared to reanalysis-based datasets. The AMSR-E SWE has low spatial and temporal correlations with the four reanalysis-based products evaluated and GlobSnow and perform poorly in comparisons with snow transect data from Finland, Russia, and Canada. There is better agreement with in situ data when multiple SWE products, excluding the stand-alone passive microwave SWE products, are combined.
Céline Portenier, Fabia Hüsler, Stefan Härer, and Stefan Wunderle
The Cryosphere, 14, 1409–1423, https://doi.org/10.5194/tc-14-1409-2020, https://doi.org/10.5194/tc-14-1409-2020, 2020
Short summary
Short summary
We present a method to derive snow cover maps from freely available webcam images in the Swiss Alps. With marginal manual user input, we can transform a webcam image into a georeferenced map and therewith perform snow cover analyses with a high spatiotemporal resolution over a large area. Our evaluation has shown that webcams could not only serve as a reference for improved validation of satellite-based approaches, but also complement satellite-based snow cover retrieval.
Markus Todt, Nick Rutter, Christopher G. Fletcher, and Leanne M. Wake
The Cryosphere, 13, 3077–3091, https://doi.org/10.5194/tc-13-3077-2019, https://doi.org/10.5194/tc-13-3077-2019, 2019
Short summary
Short summary
Vegetation is often represented by a single layer in global land models. Studies have found deficient simulation of thermal radiation beneath forest canopies when represented by single-layer vegetation. This study corrects thermal radiation in forests for a global land model using single-layer vegetation in order to assess the effect of deficient thermal radiation on snow cover and snowmelt. Results indicate that single-layer vegetation causes snow in forests to be too cold and melt too late.
David F. Hill, Elizabeth A. Burakowski, Ryan L. Crumley, Julia Keon, J. Michelle Hu, Anthony A. Arendt, Katreen Wikstrom Jones, and Gabriel J. Wolken
The Cryosphere, 13, 1767–1784, https://doi.org/10.5194/tc-13-1767-2019, https://doi.org/10.5194/tc-13-1767-2019, 2019
Short summary
Short summary
We present a new statistical model for converting snow depths to water equivalent. The only variables required are snow depth, day of year, and location. We use the location to look up climatological parameters such as mean winter precipitation and mean temperature difference (difference between hottest month and coldest month). The model is simple by design so that it can be applied to depth measurements anywhere, anytime. The model is shown to perform better than other widely used approaches.
Rebecca Mott, Andreas Wolf, Maximilian Kehl, Harald Kunstmann, Michael Warscher, and Thomas Grünewald
The Cryosphere, 13, 1247–1265, https://doi.org/10.5194/tc-13-1247-2019, https://doi.org/10.5194/tc-13-1247-2019, 2019
Short summary
Short summary
The mass balance of very small glaciers is often governed by anomalous snow accumulation, winter precipitation being multiplied by snow redistribution processes, or by suppressed snow ablation driven by micrometeorological effects lowering net radiation and turbulent heat exchange. In this study we discuss the relative contribution of snow accumulation (avalanches) versus micrometeorology (katabatic flow) on the mass balance of the lowest perennial ice field of the Alps, the Ice Chapel.
Yue Zhou, Hui Wen, Jun Liu, Wei Pu, Qingcai Chen, and Xin Wang
The Cryosphere, 13, 157–175, https://doi.org/10.5194/tc-13-157-2019, https://doi.org/10.5194/tc-13-157-2019, 2019
Short summary
Short summary
We first investigated the optical characteristics and potential sources of chromophoric dissolved organic matter (CDOM) in seasonal snow over northwestern China. The abundance of CDOM showed regional variation. At some sites strongly influenced by local soil, the absorption of CDOM cannot be neglected compared to black carbon. We found two humic-like and one protein-like fluorophores in snow. The major sources of snow CDOM were soil, biomass burning, and anthropogenic pollution.
Benjamin J. Hatchett and Hilary G. Eisen
The Cryosphere, 13, 21–28, https://doi.org/10.5194/tc-13-21-2019, https://doi.org/10.5194/tc-13-21-2019, 2019
Short summary
Short summary
We examine the timing of early season snowpack relevant to oversnow vehicle (OSV) recreation over the past 3 decades in the Lake Tahoe region (USA). Data from two independent data sources suggest that the timing of achieving sufficient snowpack has shifted later by 2 weeks. Increasing rainfall and more dry days play a role in the later onset. Adaptation strategies are provided for winter travel management planning to address negative impacts of loss of early season snowpack for OSV usage.
Deborah Verfaillie, Matthieu Lafaysse, Michel Déqué, Nicolas Eckert, Yves Lejeune, and Samuel Morin
The Cryosphere, 12, 1249–1271, https://doi.org/10.5194/tc-12-1249-2018, https://doi.org/10.5194/tc-12-1249-2018, 2018
Short summary
Short summary
This article addresses local changes of seasonal snow and its meteorological drivers, at 1500 m altitude in the Chartreuse mountain range in the Northern French Alps, for the period 1960–2100. We use an ensemble of adjusted RCM outputs consistent with IPCC AR5 GCM outputs (RCPs 2.6, 4.5 and 8.5) and the snowpack model Crocus. Beyond scenario-based approach, global temperature levels on the order of 1.5 °C and 2 °C above preindustrial levels correspond to 25 and 32% reduction of mean snow depth.
Cited articles
Aizen, V. B., Aizen, E. M., Melack, J. M., and Dozier, J.: Climatic and
hydrologic changes in the Tien Shan, central Asia, J. Climate, 10,
1393–1404, https://doi.org/10.1175/1520-0442(1997)010<1393:CAHCIT>2.0.CO;2, 1997.
Bai, L., Shi, C., Shi, Q., Li, L., Wu J., Yang, Y., Sun, S., and Zhang, F.:
Change in the spatiotemporal pattern of snowfall during the cold season
under climate change in a snow-dominated region of China, Int. J. Climatol.,
39, 5702–5719, https://doi.org/10.1002/joc.6182, 2019.
Baijnath-Rodino, J. A., Duguay, C. R., and Ledrew, E.: Climatological trends of
snowfall over the Laurentian Great Lakes Basin, Int. J. Climatol., 38,
3942–3962, https://doi.org/10.1002/joc.5546, 2018.
Barnett, T., Adam, J., and Lettenmaier, D.: Potential impacts of a warming
climate on water availability in snow-dominated regions, Nature, 438,
303–309, https://doi.org/10.1038/nature04141, 2005.
Bintanja, R. and Andry, O.: Towards a rain-dominated Arctic., Nat. Clim.
Change, 7, 263–267, https://doi.org/10.1038/nclimate3240, 2017.
Dai, A.: Temperature and pressure dependence of the rain-snow phase
transition over land and ocean, Geophys. Res. Lett., 35, 62–77,
https://doi.org/10.1029/2008GL033295, 2008.
Daloz, A. S., Mateling, M., L'Ecuyer, T., Kulie, M., Wood, N. B., Durand, M., Wrzesien, M., Stjern, C. W., and Dimri, A. P.: How much snow falls in the world's mountains? A first look at mountain snowfall estimates in A-train observations and reanalyses, The Cryosphere, 14, 3195–3207, https://doi.org/10.5194/tc-14-3195-2020, 2020.
Dedieu, J. P., Lessard-Fontaine, A., Ravazzani, G., Cremonese, E.,
Shalpykova, G., and Beniston, M.: Shifting mountain snow patterns in a changing
climate from remote sensing retrieval, Sci. Total. Environ., 493,
1267–1279, https://doi.org/10.1016/j.scitotenv.2014.04.078, 2014.
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,
https://doi.org/10.1016/j.jhydrol.2014.03.038, 2014.
Fan, X., Duan, Q., Shen, C., Wu, Y., and Xing, C.: Global surface air
temperatures in CMIP6: historical performance and future changes, Environ.
Res. Lett., 15, 104056, https://doi.org/10.1088/1748-9326/abb051, 2020.
Gao, L., Deng, H., Lei, X., Wei, J., Chen, Y., Li, Z., Ma, M., Chen, X., Chen, Y., Liu, M., and Gao, J.: Evidence of elevation-dependent warming from the Chinese Tian Shan, The Cryosphere, 15, 5765–5783, https://doi.org/10.5194/tc-15-5765-2021, 2021.
Guo, L. and Li, L.: Variation of the proportion of precipitation occurring as
snow in the Tian Shan Mountains, China, Int. J. Climatol., 35, 1379–1393,
https://doi.org/10.1002/joc.4063, 2015.
Han, W., Xiao, C., Dou, T., and Ding, M.: Changes in the proportion of
precipitation occurring as rain in northern Canada during spring–summer from
1979–2015, Adv. Atmos. Sci., 35, 31–38,
https://doi.org/10.1007/s00376-018-7226-3, 2018.
Harpold, A. A., Rajagopal, S., Crews, J. B., Winchell, T., and Schumer, R.:
Relative humidity has uneven effects on shifts from snow to rain over the
Western U.S., Geophys. Res. Lett., 44, 9742–9750,
https://doi.org/10.1002/2017GL075046, 2017.
Hock, R., Roberts, C., and Masson-Delmotte, V.: “High mountain areas” in IPCC
Special Report on the Ocean and Cryosphere in a Changing Climate, Cambridge
Univ. Press, 131–202, 2022.
Hu, R.: Physical Geography of the Tianshan Mountains in China, China
Environmental Science Press, Beijing, 139–142, 2004 (in Chinese).
Huss, M., Bookhagen, B., Huggel, C., Jacobsen, D., Bradley, R. S., Clague,
J. J., Vuille, M., Buytaert, W., Cayan, D. R., Greenwood, G., Mark, B. G.,
Milner, A. M., Weingartner, R., and Winder, M.: Toward mountains without
permanent snow and ice, Earths Future 5, 418–435,
https://doi.org/10.1002/2016EF000514, 2017.
Immerzeel, W. W., Lutz, A. F., Andrade, M., Bahl, A., Biemans, H., Bolch,
T., Hyde, S., Brumby, S., Davies, B. J., Elmore, A. C., Emmer, A., Feng, M.,
Fernández, A., Haritashya, U., Kargel, J. S., Koppes, M., Kraaijenbrink,
P. D. A., Kulkarni, A. V., Mayewski, P. A., Nepal, S., Pacheco, P., Painter,
T. H., Pellicciotti, F., Rajaram, H., Rupper, S., Sinisalo, A., Shrestha, A.
B., Viviroli, D., Wada, Y., Xiao, C., Yao, T., and Baillie, J. E. M.:
Importance and vulnerability of the world's water towers, Nature, 577,
364–369, https://doi.org/10.1038/s41586-019-1822-y, 2020.
Jennings, K. S. and Molotch, N. P.: The sensitivity of modeled snow accumulation and melt to precipitation phase methods across a climatic gradient, Hydrol. Earth Syst. Sci., 23, 3765–3786, https://doi.org/10.5194/hess-23-3765-2019, 2019.
Jennings, K. S., Winchell, T. S., Livneh, B., and Molotch, N. P.: Spatial
variation of the rain–snow temperature threshold across the Northern
Hemisphere, Nat. Commun., 9, 1–9, https://doi.org/10.1038/s41467-018-03629-7, 2018.
Jiang, F., Li, X., Wei, B., Hu, R., and Li, Z.: Observed trends of heating
and cooling degree-days in Xinjiang province, China, Theor. Appl. Climatol.,
97, 349–360, https://doi.org/10.1007/s00704-008-0078-5, 2009.
Jonas, T., Rixen, C., Sturm, M., and Stoeckli, V.: How alpine plant growth is
linked to snow cover and climate variability, J. Geophys. Res., 113,
G03013, https://doi.org/10.1029/2007JG000680, 2008.
Kapnick, S. B., Delworth, T. L., Ashfaq, M., Malyshev, S., and Milly, P. C.
D.: Snowfall less sensitive to warming in Karakoram than in Himalayas due to
a unique seasonal cycle, Nat. Geosci., 7, 834–840,
https://doi.org/10.1038/ngeo2269, 2014.
Kendall, M. G.: Rank correlation methods, Brit. J. Psychol., 25, 86–91,
1990.
Knowles, N., Dettinger, M., and Cayan, D.: Trends in snowfall versus
rainfall in the western United States, J. Climate, 19, 4545–4559,
https://doi.org/10.1175/JCLI3850.1, 2006.
Krasting, J. P.: Variations in Northern Hemisphere snowfall: an analysis of
historical trends and the projected response to anthropogenic forcing in the
twenty-first century, Doctor of Philosophy, Rutgers, The State University of
New Jersey, https://doi.org/10.7282/T3JH3MHJ, 2008.
Le Roux, E., Evin, G., Eckert, N., Blanchet, J., and Morin, S.: Elevation-dependent trends in extreme snowfall in the French Alps from 1959 to 2019, The Cryosphere, 15, 4335–4356, https://doi.org/10.5194/tc-15-4335-2021, 2021.
Li, X.: Climate change and its impact in the Chinese Tianshan mountainous
region, Publishing House of Electronics Industry, ISBN 978-7-121-42141-9, 2021 (in Chinese).
Li, X., Jiang, F., Li, L., and Wang, G.: Spatial and temporal variability of
precipitation concentration index, concentration degree and concentration
period in Xinjiang province, China, Int. J. Climatol., 31, 1679–1693,
https://doi.org/10.1002/joc.2181, 2011.
Li, X., Li, L., Yuan, S., Yan, H., and Wang, G.: Temporal and spatial
variation of 10-day mean air temperature in Northwestern China, Theor. Appl.
Climatol., 119, 285–298, https://doi.org/10.1007/s00704-014-1100-8, 2015.
Li, X., Gao, P., Li, Q., and Tang, H.: Muti-paths Impact from Climate Change on
Snow Cover in Tianshan Mountainous Area of China, Adv. Clim. Chang. Res.,
12, 303–312, https://doi.org/10.12006/j.issn.1673-1719.2015.184, 2016 (in
Chinese with English abstract).
Li, X., Simonovic, S. P., Li, L., Zhang, X., and Qin, Q.: Performance and
uncertainty analysis of a short-term climate reconstruction based on
multi-source data in the Tianshan Mountains region, China, J. Arid Land, 12,
374–396, https://doi.org/10.1007/s40333-020-0065-y, 2020.
Li, X., Zhang, B., Ren, R., Li, L., and Simonovic, S. P.: Spatio-temporal
Heterogeneity of Climate Warming in the Chinese Tianshan Mountainous Region,
Water, 14, 199, https://doi.org/10.3390/w14020199, 2022.
Li, Y., Chen, Y., and Li, Z.: Climate and topographic controls on snow phenology
dynamics in the Tienshan Mountains, Central Asia, Atmos. Res., 236, 104813,
https://doi.org/10.1016/j.atmosres.2019.104813, 2020.
Li, Z., Gong, X., Chen, J., Mills, J., Li, S., Zhu, X., Peng, T., and Hao, W.:
Functional Requirements of Systems for Visualization of Sustainable
Development Goal (SDG) Indicators, J. Geovis. Spat. Anal., 4, 5,
https://doi.org/10.1007/s41651-019-0046-x, 2020.
Lin, W. and Chen, H.: Changes in the spatial-temporal characteristics of daily
snowfall events over the Eurasian continent from 1980 to 2019, Int. J.
Climatol., 42, 1841–1853, https://doi.org/10.1002/joc.7339, 2022.
Loth, B., Graf, H. F., and Oberhuber, J. M.: Snow cover model for global climate
simulations, J. Geophys. Res.-Atmos., 98, 10451–10464, https://doi.org/10.1029/93JD00324, 1993.
Mankin, J. S., Viviroli, D., Singh, D., Hoekstra, A. Y., and Diffenbaugh, N.
S.: The potential for snow to supply human water demand in the present and
future, Environ. Res. Lett., 10, 114016,
https://doi.org/10.1088/1748-9326/10/11/114016, 2015.
Marshall, J., Plumb, R. A.: Atmosphere, ocean, and climate dynamics: an
introductory text, Chap. 2: The global energy balance, ISBN13 978-0-12-558691-7, 9–22, 2008.
McAfee, S., Walsh, J., and Rupp, S.: Statistically downscaled projections of
snow/rain partitioning for Alaska, Hydrol. Process., 28, 3930–3946,
https://doi.org/10.1002/hyp.9934, 2014.
Nazzareno, D., Büntgen, U., and Gianni, B.: Mediterranean winter snowfall
variability over the past millennium, Int. J. Climatol., 39, 384–394,
https://doi.org/10.1002/joc.5814, 2019.
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016.
Piazza, M., Boé, J., Terray, L., Pagé, C., Sanchez-Gomez, E., and
Déqué, M.: Projected 21st century snowfall changes over the French
Alps and related uncertainties, Clim. Change, 122, 583–594,
https://doi.org/10.1007/s10584-013-1017-8, 2014.
Räisänen, J.: Twenty-first century changes in snowfall climate in Northern
Europe in ENSEMBLES regional climate models, Clim. Dynam., 46, 339–353,
https://doi.org/10.1007/s00382-015-2587-0, 2016.
Ren, R., Li, X., Li, L., Qin, Q., and Huang, Y.: Discrimination of driving
factors of precipitation forms in Tianshan Mountains area of China, J. Arid
Land Res. Environ., 34, 112–117, 2020 (in Chinese with English
abstract).
Ren, R., Li, X., Li, Z., Li, L., and Huang, Y.: Projected change in
precipitation forms in the Chinese Tianshan Mountains based on the Back
Propagation Neural Network Model, J. Mt. Sci., 19, 689–703,
https://doi.org/10.1007/s11629-021-7076-9, 2022.
Sabine, B. R., Mathieu, G., Olivier, B., Miska, L., Carmen, C., Gregoire,
M., and Antoine, G.: From white to green: Snow cover loss and increased
vegetation productivity in the European Alps, Science, 376, 1119–1122,
https://doi.org/10.1126/science.abn6697, 2022.
Siirila-Woodburn, E. R., Rhoades, A. M., Hatchett, B. J., Huning, L. S.,
Szinai, J., Tague, C., Nico, P. S., Feldman, D. R., Jones, A. D., Collins,
W. D., and Kaatz, L.: A low-to-no snow future and its impacts on water
resources in the western United States, Nat. Rev. Earth Env., 2, 800–819,
https://doi.org/10.1038/s43017-021-00219-y, 2021.
Sorg, A., Bolch, T., Stoffel, M., Solomina, O. N., and Beniston, M.: Climate
change impacts on glaciers and runoff in Tien Shan (Central Asia), Nat.
Clim. Change, 2, 725–731, https://doi.org/10.1038/nclimate1592, 2012.
Sun, F., Hall, A., Schwartz, M., Walton, D. B., and Berg, N.:
Twenty-First-Century Snowfall and Snowpack Changes over the Southern
California Mountains, J. Climate, 29, 91–110,
https://doi.org/10.1175/JCLI-D-15-0199.1, 2016.
Takahashi, H. G.: Long-term trends in snowfall characteristics and extremes
in Japan from 1961 to 2012, Int. J. Climatol., 41, 2316–2329,
https://doi.org/10.1002/joc.6960, 2021.
Tamang, S. K., Ebtehaj, A. M., Prein, A. F., and Heymsifield, A. J.: Linking
global changes of snowfall and wet-bulb temperature, J. Climate, 33, 39–59,
https://doi.org/10.1175/JCLI-D-19-0254.1, 2020.
Tian, Y., Li, X., Li, Z., and Qin, Q.: Spatial and temporal variations of
different precipitation types in the Tianshan Mountains from 1850–2017, Arid
Land Geogr., 43, 308–318, 2020 (in Chinese with English abstract).
Trenberth, K. E.: Changes in precipitation with climate change, Clim. Res.,
47, 123–128, https://doi.org/10.3354/cr00953, 2011.
Yang, J., Fang, G., Chen, Y., and De-Maeyer, P.: Climate change in the
Tianshan and northern Kunlun Mountains based on GCM simulation ensemble with
Bayesian model averaging, J. Arid Land, 9, 622–634,
https://doi.org/10.1007/s40333-017-0100-9, 2017.
Yang, T., Li, Q., Ahmad, S., Zhou, H., and Li, L.: Changes in Snow Phenology
from 1979 to 2016 over the Tianshan Mountains, Central Asia, Remote Sens.,
11, 499, https://doi.org/10.3390/rs11050499, 2019.
Yang, T., Li, Q., Hamdi, R., Zou, Q., Chen, X., Maeyer, P., Cui, F., and Li, L.:
Snowfall climatology in the Tianshan Mountains based on 36 cold seasons of
WRF dynamical downscaling simulation, Atmos. Res., 270, 106057,
https://doi.org/10.1016/j.atmosres.2022.106057, 2022.
Zhang, L., Chen, X., and Xin, X.: Short commentary on CMIP6 Scenario Model
Intercomparison Project (ScenarioMIP), Clim. Chang. Res., 15, 519–525,
https://doi.org/10.12006/j.issn.1673-1719.2019.082, 2019.
Zhang, X., Li, X., Gao, P., Li, Q., and Tang, H.: Separation of
precipitation forms based on different methods in Tianshan Mountainous Area,
Northwest China, J. Glaciol. Geocryol., 39, 235–244, 2017 (in Chinese with
English abstract).
Zhang, X., Li, X., Li, L., Zhang, S., and Qin, Q.: Environmental factors
influencing snowfall and snowfall prediction in the Tianshan Mountains,
Northwest China, J. Arid Land, 11, 15–28,
https://doi.org/10.1007/s40333-018-0110-2, 2019.
Short summary
Quantifying change in the potential snowfall phenology (PSP) is an important area of research for understanding regional climate change past, present, and future. However, few studies have focused on the PSP and its change in alpine mountainous regions. We proposed three innovative indicators to characterize the PSP and its spatial–temporal variation. Our study provides a novel approach to understanding PSP in alpine mountainous regions and can be easily extended to other snow-dominated regions.
Quantifying change in the potential snowfall phenology (PSP) is an important area of research...
