Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-781-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-14-781-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
21 Feb 2022
Data description paper |
| 21 Feb 2022
| 21 Feb 2022
A new Greenland digital elevation model derived from ICESat-2 during 2018–2019
Yubin Fan
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, Key Laboratory for Land Satellite Remote Sensing
Applications of Ministry of Natural Resources, School of Geography and Ocean
Science, Nanjing University, Nanjing, 210023, China
Collaborative Innovation Center of Novel Software Technology and
Industrialization, Nanjing University, Nanjing, 210023, China
Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing,
210023, China
Chang-Qing Ke
CORRESPONDING AUTHOR
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, Key Laboratory for Land Satellite Remote Sensing
Applications of Ministry of Natural Resources, School of Geography and Ocean
Science, Nanjing University, Nanjing, 210023, China
Collaborative Innovation Center of Novel Software Technology and
Industrialization, Nanjing University, Nanjing, 210023, China
Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing,
210023, China
Xiaoyi Shen
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, Key Laboratory for Land Satellite Remote Sensing
Applications of Ministry of Natural Resources, School of Geography and Ocean
Science, Nanjing University, Nanjing, 210023, China
Collaborative Innovation Center of Novel Software Technology and
Industrialization, Nanjing University, Nanjing, 210023, China
Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing,
210023, China
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Yubin Fan, Chang-Qing Ke, Xiaoyi Shen, Yao Xiao, Stephen J. Livingstone, and Andrew J. Sole
The Cryosphere, 17, 1775–1786, https://doi.org/10.5194/tc-17-1775-2023, https://doi.org/10.5194/tc-17-1775-2023, 2023
Short summary
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We used the new-generation ICESat-2 altimeter to detect and monitor active subglacial lakes in unprecedented spatiotemporal detail. We created a new inventory of 18 active subglacial lakes as well as their elevation and volume changes during 2019–2020, which provides an improved understanding of how the Greenland subglacial water system operates and how these lakes are fed by water from the ice surface.
Xiaoyi Shen, Chang-Qing Ke, Yubin Fan, and Lhakpa Drolma
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-204, https://doi.org/10.5194/tc-2021-204, 2021
Manuscript not accepted for further review
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Obtaining the detailed surface topography in Antarctica is essential for human fieldwork planning, ice surface height changes and mass balance estimations. A definite time-stamped and fine-scale DEM for Antarctica with a modal resolution of 250 m is presented based on the surface height measurements from ICESat-2 by using a model fitting method, which is more valuable for further scientific applications, e.g., land ice height and mass balance estimations.
Yu Cai, Jingjing Wang, Yao Xiao, Zifei Wang, Xiaoyi Shen, Haili Li, and Chang-Qing Ke
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-441, https://doi.org/10.5194/essd-2023-441, 2024
Revised manuscript under review for ESSD
Short summary
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In this study, we re-explored the potential of passive microwaves in extracting lake ice freeze-thaw events. Brightness temperature and air temperature data were used to extract freeze-up and break-up records of 194 lakes on the Tibetan Plateau, providing complete lake ice records for a large number of small and medium-sized lakes for the first time. The dataset will provide valuable data for users interested in lake ice cover on the Tibetan Plateau over the last decade.
Yubin Fan, Chang-Qing Ke, Xiaoyi Shen, Yao Xiao, Stephen J. Livingstone, and Andrew J. Sole
The Cryosphere, 17, 1775–1786, https://doi.org/10.5194/tc-17-1775-2023, https://doi.org/10.5194/tc-17-1775-2023, 2023
Short summary
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We used the new-generation ICESat-2 altimeter to detect and monitor active subglacial lakes in unprecedented spatiotemporal detail. We created a new inventory of 18 active subglacial lakes as well as their elevation and volume changes during 2019–2020, which provides an improved understanding of how the Greenland subglacial water system operates and how these lakes are fed by water from the ice surface.
Yu Cai, Claude R. Duguay, and Chang-Qing Ke
Earth Syst. Sci. Data, 14, 3329–3347, https://doi.org/10.5194/essd-14-3329-2022, https://doi.org/10.5194/essd-14-3329-2022, 2022
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Seasonal ice cover is one of the important attributes of lakes in middle- and high-latitude regions. This study used passive microwave brightness temperature measurements to extract the ice phenology for 56 lakes across the Northern Hemisphere from 1979 to 2019. A threshold algorithm was applied according to the differences in brightness temperature between lake ice and open water. The dataset will provide valuable information about the changing ice cover of lakes over the last 4 decades.
Xiaoyi Shen, Chang-Qing Ke, Yubin Fan, and Lhakpa Drolma
Earth Syst. Sci. Data, 14, 3075–3089, https://doi.org/10.5194/essd-14-3075-2022, https://doi.org/10.5194/essd-14-3075-2022, 2022
Short summary
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Obtaining the detailed surface topography in Antarctica is essential for fieldwork planning, surface height change and mass balance estimations. A new and reliable DEM for Antarctica with a modal resolution of 500 m is presented based on the surface height measurements from ICESat-2 by using a model fitting method. The high accuracy of elevations and the possibility for annual updates make the ICESat-2 DEM an addition to the existing Antarctic DEM groups.
Xiaoyi Shen, Chang-Qing Ke, and Haili Li
Earth Syst. Sci. Data, 14, 619–636, https://doi.org/10.5194/essd-14-619-2022, https://doi.org/10.5194/essd-14-619-2022, 2022
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Snow over Antarctic sea ice controls energy budgets and thus has essential effects on the climate. Here, we estimated snow depth using microwave radiometers and a newly constructed, robust method by incorporating lower frequencies, which have been available from AMSR-E and AMSR-2. Comparing the new retrieval with in situ and shipborne snow depth measurements showed that this method outperformed the previously available method.
Haili Li, Chang-Qing Ke, Qinghui Zhu, and Xiaoyi Shen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-271, https://doi.org/10.5194/tc-2021-271, 2021
Revised manuscript not accepted
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Here, we employ particle filter assimilation to combine snow depth values retrieved from remote sensing with those obtained from reanalysis reconstructions, and INESOSIM-PF is proposed. The results indicate that the proposed method improves the modeled snow depth, and the monthly and seasonal changes in the snow depth are consistent with those in the snow depth determined with two existing snow depth algorithms.
Xiaoyi Shen, Chang-Qing Ke, Yubin Fan, and Lhakpa Drolma
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-204, https://doi.org/10.5194/tc-2021-204, 2021
Manuscript not accepted for further review
Short summary
Short summary
Obtaining the detailed surface topography in Antarctica is essential for human fieldwork planning, ice surface height changes and mass balance estimations. A definite time-stamped and fine-scale DEM for Antarctica with a modal resolution of 250 m is presented based on the surface height measurements from ICESat-2 by using a model fitting method, which is more valuable for further scientific applications, e.g., land ice height and mass balance estimations.
Chang-Qing Ke, Xiu-Cang Li, Hongjie Xie, Dong-Hui Ma, Xun Liu, and Cheng Kou
Hydrol. Earth Syst. Sci., 20, 755–770, https://doi.org/10.5194/hess-20-755-2016, https://doi.org/10.5194/hess-20-755-2016, 2016
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The heavy snow years in China include 1955, 1957, 1964, and 2010, and light snow years include 1953, 1965, 1999, 2002, and 2009. The reduction in number of days with temperature below 0 °C and increase in mean air temperature are the main reasons for the delay of snow cover onset date and advance of snow cover end date. This explains why only 15 % of the stations show significant shortening of snow cover days and differ with the overall shortening of the snow period in the Northern Hemisphere.
J. Chen, C. Q. Ke, and Z. D. Shao
The Cryosphere Discuss., https://doi.org/10.5194/tcd-8-5875-2014, https://doi.org/10.5194/tcd-8-5875-2014, 2014
Revised manuscript not accepted
H. Xie, R. Lei, C. Ke, H. Wang, Z. Li, J. Zhao, and S. F. Ackley
The Cryosphere, 7, 1057–1072, https://doi.org/10.5194/tc-7-1057-2013, https://doi.org/10.5194/tc-7-1057-2013, 2013
Related subject area
Snow and Sea Ice
Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972–1977
A climate data record of year-round global sea-ice drift from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF)
MODIS Daily Cloud-gap-filled Fractional Snow Cover Dataset of the Asian Water Tower Region (2000–2022)
Snow accumulation and ablation measurements in a midlatitude mountain coniferous forest (Col de Porte, France, 1325 m altitude): the Snow Under Forest (SnoUF) field campaign data set
A new sea ice concentration product in the polar regions derived from the FengYun-3 MWRI sensors
NH-SWE: Northern Hemisphere Snow Water Equivalent dataset based on in situ snow depth time series
IT-SNOW: a snow reanalysis for Italy blending modeling, in situ data, and satellite observations (2010–2021)
HMRFS–TP: long-term daily gap-free snow cover products over the Tibetan Plateau from 2002 to 2021 based on hidden Markov random field model
Large ensemble of downscaled historical daily snowfall from an earth system model to 5.5 km resolution over Dronning Maud Land, Antarctica
The S2M meteorological and snow cover reanalysis over the French mountainous areas: description and evaluation (1958–2021)
Reconstruction of a daily gridded snow water equivalent product for the land region above 45° N based on a ridge regression machine learning approach
Snow depth product over Antarctic sea ice from 2002 to 2020 using multisource passive microwave radiometers
The NIEER AVHRR snow cover extent product over China – a long-term daily snow record for regional climate research
Canadian historical Snow Water Equivalent dataset (CanSWE, 1928–2020)
Meteorological, snow and soil data (2013–2019) from a herb tundra permafrost site at Bylot Island, Canadian high Arctic, for driving and testing snow and land surface models
Inter-annual variation in lake ice composition in the European Arctic: observations based on high-resolution thermistor strings
Daily Terra–Aqua MODIS cloud-free snow and Randolph Glacier Inventory 6.0 combined product (M*D10A1GL06) for high-mountain Asia between 2002 and 2019
High-resolution mapping of circum-Antarctic landfast sea ice distribution, 2000–2018
Laboratory, field, mast-borne and airborne spectral reflectance measurements of boreal landscape during spring
An improved Terra–Aqua MODIS snow cover and Randolph Glacier Inventory 6.0 combined product (MOYDGL06*) for high-mountain Asia between 2002 and 2018
Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China
Meteorological and evaluation datasets for snow modelling at 10 reference sites: description of in situ and bias-corrected reanalysis data
Hydrometeorological data from Marmot Creek Research Basin, Canadian Rockies
Wiebke Margitta Kolbe, Rasmus T. Tonboe, and Julienne Stroeve
Earth Syst. Sci. Data, 16, 1247–1264, https://doi.org/10.5194/essd-16-1247-2024, https://doi.org/10.5194/essd-16-1247-2024, 2024
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Current satellite-based sea-ice climate data records (CDRs) usually begin in October 1978 with the first multichannel microwave radiometer data. Here, we present a sea ice dataset based on the single-channel Electrical Scanning Microwave Radiometer (ESMR) that operated from 1972-1977 onboard NASA’s Nimbus 5 satellite. The data were processed using modern methods and include uncertainty estimations in order to provide an important, easy-to-use reference period of good quality for current CDRs.
Thomas Lavergne and Emily Down
Earth Syst. Sci. Data, 15, 5807–5834, https://doi.org/10.5194/essd-15-5807-2023, https://doi.org/10.5194/essd-15-5807-2023, 2023
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Sea ice in the Arctic and Antarctic can move several tens of kilometers per day due to wind and ocean currents. By analysing thousands of satellite images, we measured how sea ice has been moving every single day from 1991 through to 2020. We compare our data to how buoys attached to the ice moved and find good agreement. Other scientists will now use our data to better understand if climate change has modified the way sea ice moves and in what way.
Fangbo Pan, Lingmei Jiang, Gongxue Wang, Jinmei Pan, Jinyu Huang, Cheng Zhang, Huizhen Cui, Jiangwei Yang, Zhaojun Zheng, Shengli Wu, and Jiancheng Shi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-250, https://doi.org/10.5194/essd-2023-250, 2023
Revised manuscript accepted for ESSD
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It is important to strengthen the continuous monitoring of snow cover as a key indicator of imbalance in the Asian Water Tower (AWT) region. We generate long-term daily gap-free fractional snow cover products over the AWT at 0.005° resolution from 2000 to 2022 based on the multiple endmember spectral mixture analysis algorithm and the gap-filling algorithm. It can provide highly accurate, quantitative fractional snow cover information for subsequent studies such as hydrology and climate.
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
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Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
Ying Chen, Ruibo Lei, Xi Zhao, Shengli Wu, Yue Liu, Pei Fan, Qing Ji, Peng Zhang, and Xiaoping Pang
Earth Syst. Sci. Data, 15, 3223–3242, https://doi.org/10.5194/essd-15-3223-2023, https://doi.org/10.5194/essd-15-3223-2023, 2023
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The sea ice concentration product derived from the Microwave Radiation Image sensors on board the FengYun-3 satellites can reasonably and independently identify the seasonal and long-term changes of sea ice, as well as extreme cases of annual maximum and minimum sea ice extent in polar regions. It is comparable with other sea ice concentration products and applied to the studies of climate and marine environment.
Adrià Fontrodona-Bach, Bettina Schaefli, Ross Woods, Adriaan J. Teuling, and Joshua R. Larsen
Earth Syst. Sci. Data, 15, 2577–2599, https://doi.org/10.5194/essd-15-2577-2023, https://doi.org/10.5194/essd-15-2577-2023, 2023
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We provide a dataset of snow water equivalent, the depth of liquid water that results from melting a given depth of snow. The dataset contains 11 071 sites over the Northern Hemisphere, spans the period 1950–2022, and is based on daily observations of snow depth on the ground and a model. The dataset fills a lack of accessible historical ground snow data, and it can be used for a variety of applications such as the impact of climate change on global and regional snow and water resources.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Flavio Pignone, Giulia Bruno, Luca Pulvirenti, Giuseppe Squicciarino, Elisabetta Fiori, Lauro Rossi, Silvia Puca, Alexander Toniazzo, Pietro Giordano, Marco Falzacappa, Sara Ratto, Hervè Stevenin, Antonio Cardillo, Matteo Fioletti, Orietta Cazzuli, Edoardo Cremonese, Umberto Morra di Cella, and Luca Ferraris
Earth Syst. Sci. Data, 15, 639–660, https://doi.org/10.5194/essd-15-639-2023, https://doi.org/10.5194/essd-15-639-2023, 2023
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Snow cover has profound implications for worldwide water supply and security, but knowledge of its amount and distribution across the landscape is still elusive. We present IT-SNOW, a reanalysis comprising daily maps of snow amount and distribution across Italy for 11 snow seasons from September 2010 to August 2021. The reanalysis was validated using satellite images and snow measurements and will provide highly needed data to manage snow water resources in a warming climate.
Yan Huang, Jiahui Xu, Jingyi Xu, Yelei Zhao, Bailang Yu, Hongxing Liu, Shujie Wang, Wanjia Xu, Jianping Wu, and Zhaojun Zheng
Earth Syst. Sci. Data, 14, 4445–4462, https://doi.org/10.5194/essd-14-4445-2022, https://doi.org/10.5194/essd-14-4445-2022, 2022
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Reliable snow cover information is important for understating climate change and hydrological cycling. We generate long-term daily gap-free snow products over the Tibetan Plateau (TP) at 500 m resolution from 2002 to 2021 based on the hidden Markov random field model. The accuracy is 91.36 %, and is especially improved during snow transitional period and over complex terrains. This dataset has great potential to study climate change and to facilitate water resource management in the TP.
Nicolas Ghilain, Stéphane Vannitsem, Quentin Dalaiden, Hugues Goosse, Lesley De Cruz, and Wenguang Wei
Earth Syst. Sci. Data, 14, 1901–1916, https://doi.org/10.5194/essd-14-1901-2022, https://doi.org/10.5194/essd-14-1901-2022, 2022
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Modeling the climate at high resolution is crucial to represent the snowfall accumulation over the complex orography of the Antarctic coast. While ice cores provide a view constrained spatially but over centuries, climate models can give insight into its spatial distribution, either at high resolution over a short period or vice versa. We downscaled snowfall accumulation from climate model historical simulations (1850–present day) over Dronning Maud Land at 5.5 km using a statistical method.
Matthieu Vernay, Matthieu Lafaysse, Diego Monteiro, Pascal Hagenmuller, Rafife Nheili, Raphaëlle Samacoïts, Deborah Verfaillie, and Samuel Morin
Earth Syst. Sci. Data, 14, 1707–1733, https://doi.org/10.5194/essd-14-1707-2022, https://doi.org/10.5194/essd-14-1707-2022, 2022
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This paper introduces the latest version of the freely available S2M dataset which provides estimates of both meteorological and snow cover variables, as well as various avalanche hazard diagnostics at different elevations, slopes and aspects for the three main French high-elevation mountainous regions. A complete description of the system and the dataset is provided, as well as an overview of the possible uses of this dataset and an objective assessment of its limitations.
Donghang Shao, Hongyi Li, Jian Wang, Xiaohua Hao, Tao Che, and Wenzheng Ji
Earth Syst. Sci. Data, 14, 795–809, https://doi.org/10.5194/essd-14-795-2022, https://doi.org/10.5194/essd-14-795-2022, 2022
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The temporal series and spatial distribution discontinuity of the existing snow water equivalent (SWE) products in the pan-Arctic region severely restricts the use of SWE data in cryosphere change and climate change studies. Using a ridge regression machine learning algorithm, this study developed a set of spatiotemporally seamless and high-precision SWE products. This product could contribute to the study of cryosphere change and climate change at large spatial scales.
Xiaoyi Shen, Chang-Qing Ke, and Haili Li
Earth Syst. Sci. Data, 14, 619–636, https://doi.org/10.5194/essd-14-619-2022, https://doi.org/10.5194/essd-14-619-2022, 2022
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Snow over Antarctic sea ice controls energy budgets and thus has essential effects on the climate. Here, we estimated snow depth using microwave radiometers and a newly constructed, robust method by incorporating lower frequencies, which have been available from AMSR-E and AMSR-2. Comparing the new retrieval with in situ and shipborne snow depth measurements showed that this method outperformed the previously available method.
Xiaohua Hao, Guanghui Huang, Tao Che, Wenzheng Ji, Xingliang Sun, Qin Zhao, Hongyu Zhao, Jian Wang, Hongyi Li, and Qian Yang
Earth Syst. Sci. Data, 13, 4711–4726, https://doi.org/10.5194/essd-13-4711-2021, https://doi.org/10.5194/essd-13-4711-2021, 2021
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Long-term snow cover data are not only of importance for climate research. Currently China still lacks a high-quality snow cover extent (SCE) product for climate research. This study develops a multi-level decision tree algorithm for cloud and snow discrimination and gap-filled technique based on AVHRR surface reflectance data. We generate a daily 5 km SCE product across China from 1981 to 2019. It has high accuracy and will serve as baseline data for climate and other applications.
Vincent Vionnet, Colleen Mortimer, Mike Brady, Louise Arnal, and Ross Brown
Earth Syst. Sci. Data, 13, 4603–4619, https://doi.org/10.5194/essd-13-4603-2021, https://doi.org/10.5194/essd-13-4603-2021, 2021
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Water equivalent of snow cover (SWE) is a key variable for water management, hydrological forecasting and climate monitoring. A new Canadian SWE dataset (CanSWE) is presented in this paper. It compiles data collected by multiple agencies and companies at more than 2500 different locations across Canada over the period 1928–2020. Snow depth and derived bulk snow density are also included when available.
Florent Domine, Georg Lackner, Denis Sarrazin, Mathilde Poirier, and Maria Belke-Brea
Earth Syst. Sci. Data, 13, 4331–4348, https://doi.org/10.5194/essd-13-4331-2021, https://doi.org/10.5194/essd-13-4331-2021, 2021
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Current sophisticated snow physics models were mostly designed for alpine conditions and cannot adequately simulate the physical properties of Arctic snowpacks. New snow models will require Arctic data sets for forcing and validation. We provide an extensive driving and testing data set from a high Arctic herb tundra site in Canada. Unique validating data include continuous time series of snow and soil thermal conductivity and temperature profiles. Field observations in spring are provided.
Bin Cheng, Yubing Cheng, Timo Vihma, Anna Kontu, Fei Zheng, Juha Lemmetyinen, Yubao Qiu, and Jouni Pulliainen
Earth Syst. Sci. Data, 13, 3967–3978, https://doi.org/10.5194/essd-13-3967-2021, https://doi.org/10.5194/essd-13-3967-2021, 2021
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Climate change strongly impacts the Arctic, with clear signs of higher air temperature and more precipitation. A sustainable observation programme has been carried out in Lake Orajärvi in Sodankylä, Finland. The high-quality air–snow–ice–water temperature profiles have been measured every winter since 2009. The data can be used to investigate the lake ice surface heat balance and the role of snow in lake ice mass balance and parameterization of snow-to-ice transformation in snow/ice models.
Sher Muhammad and Amrit Thapa
Earth Syst. Sci. Data, 13, 767–776, https://doi.org/10.5194/essd-13-767-2021, https://doi.org/10.5194/essd-13-767-2021, 2021
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Snow is a dominant water resource in high-mountain Asia and crucial for mountain communities and downstream populations. The present MODIS snow products are significantly uncertain and not useful for observation and simulation of climate, hydrology, and other water-related studies. This study reduces uncertainty in the daily MODIS snow data and generates a MODIS Terra–Aqua combined product reducing uncertainties due to cloud cover, data gaps, and other errors caused by sensor limitations.
Alexander D. Fraser, Robert A. Massom, Kay I. Ohshima, Sascha Willmes, Peter J. Kappes, Jessica Cartwright, and Richard Porter-Smith
Earth Syst. Sci. Data, 12, 2987–2999, https://doi.org/10.5194/essd-12-2987-2020, https://doi.org/10.5194/essd-12-2987-2020, 2020
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Landfast ice, or
fast ice, is a form of sea ice which is mechanically fastened to stationary parts of the coast. Long-term and accurate knowledge of its extent around Antarctica is critical for understanding a number of important Antarctic coastal processes, yet no accurate, large-scale, long-term dataset of its extent has been available. We address this data gap with this new dataset compiled from satellite imagery, containing high-resolution maps of Antarctic fast ice from 2000 to 2018.
Henna-Reetta Hannula, Kirsikka Heinilä, Kristin Böttcher, Olli-Pekka Mattila, Miia Salminen, and Jouni Pulliainen
Earth Syst. Sci. Data, 12, 719–740, https://doi.org/10.5194/essd-12-719-2020, https://doi.org/10.5194/essd-12-719-2020, 2020
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We publish and describe a surface spectral reflectance data record of seasonal snow (dry, wet, shadowed), forest ground (lichen, moss) and forest canopy (spruce and pine, branches) constituting the main elements of the boreal landscape and collected at four scales. The data record describes the characteristics and variability of the satellite scene reflectance contributors in boreal landscape, thus enabling the development of improved optical satellite snow mapping methods for forested areas.
Sher Muhammad and Amrit Thapa
Earth Syst. Sci. Data, 12, 345–356, https://doi.org/10.5194/essd-12-345-2020, https://doi.org/10.5194/essd-12-345-2020, 2020
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Snow is the major water resource in high-mountain Asia; therefore, it is crucial to continuously monitor it. Currently, remote sensing, mainly MODIS, is used for snow monitoring. However, the available MODIS snow product is not useful for various applications without postprocessing and improvement. This study reduces uncertainty in the MODIS snow data. We found approximately 50% underestimation and overestimation of snow cover by MODIS Terra–Aqua products, which were improved in this study.
Tao Che, Xin Li, Shaomin Liu, Hongyi Li, Ziwei Xu, Junlei Tan, Yang Zhang, Zhiguo Ren, Lin Xiao, Jie Deng, Rui Jin, Mingguo Ma, Jian Wang, and Xiaofan Yang
Earth Syst. Sci. Data, 11, 1483–1499, https://doi.org/10.5194/essd-11-1483-2019, https://doi.org/10.5194/essd-11-1483-2019, 2019
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The paper presents a suite of datasets consisting of long-term hydrometeorological, snow cover and frozen ground data for investigating watershed science and functions from an integrated, distributed and multiscale observation network in the upper reaches of the Heihe River Basin in China. These data are expected to serve as a testing platform to provide accurate forcing data and validate and evaluate remote-sensing products and hydrological models in cold regions for a broader community.
Cécile B. Ménard, Richard Essery, Alan Barr, Paul Bartlett, Jeff Derry, Marie Dumont, Charles Fierz, Hyungjun Kim, Anna Kontu, Yves Lejeune, Danny Marks, Masashi Niwano, Mark Raleigh, Libo Wang, and Nander Wever
Earth Syst. Sci. Data, 11, 865–880, https://doi.org/10.5194/essd-11-865-2019, https://doi.org/10.5194/essd-11-865-2019, 2019
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This paper describes long-term meteorological and evaluation datasets from 10 reference sites for use in snow modelling. We demonstrate how data sharing is crucial to the identification of errors and how the publication of these datasets contributes to good practice, consistency, and reproducibility in geosciences. The ease of use, availability, and quality of the datasets will help model developers quantify and reduce model uncertainties and errors.
Xing Fang, John W. Pomeroy, Chris M. DeBeer, Phillip Harder, and Evan Siemens
Earth Syst. Sci. Data, 11, 455–471, https://doi.org/10.5194/essd-11-455-2019, https://doi.org/10.5194/essd-11-455-2019, 2019
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Meteorological, snow survey, streamflow, and groundwater data are presented from Marmot Creek Research Basin, a small alpine-montane forest headwater catchment in the Alberta Rockies. It was heavily instrumented, experimented upon, and operated by several federal government agencies between 1962 and 1986 and was re-established starting in 2004 by the University of Saskatchewan Centre for Hydrology. These long-term legacy data serve to advance our knowledge of hydrology of the Canadian Rockies.
Cited articles
Abdullahi, S., Wessel, B., Huber, M., Wendleder, A., and Kuenzer, C.:
Estimating Penetration-Related X-Band InSAR Elevation Bias: A Study over the
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Short summary
A new digital elevation model of Greenland was provided based on the ICESat-2 observations acquired from November 2018 to November 2019. A model fit method was applied within the grid cells at different spatial resolutions to estimate the surface elevations with a modal resolution of 500 m. We estimated the uncertainty with a median difference of −0.48 m for all of Greenland, which can benefit studies of elevation change and mass balance in Greenland.
A new digital elevation model of Greenland was provided based on the ICESat-2 observations...
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