Articles | Volume 9, issue 5
https://doi.org/10.5194/tc-9-1879-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-9-1879-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 Sep 2015
Research article |
| 24 Sep 2015
Satellite observations of changes in snow-covered land surface albedo during spring in the Northern Hemisphere
K. Atlaskina
CORRESPONDING AUTHOR
Department of Physics, University of Helsinki, Helsinki, Finland
F. Berninger
Department of Forest Sciences, University of Helsinki, Helsinki, Finland
G. de Leeuw
Department of Physics, University of Helsinki, Helsinki, Finland
Finnish Meteorological Institute, Helsinki, Finland
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Nick Schutgens, Oleg Dubovik, Otto Hasekamp, Omar Torres, Hiren Jethva, Peter J. T. Leonard, Pavel Litvinov, Jens Redemann, Yohei Shinozuka, Gerrit de Leeuw, Stefan Kinne, Thomas Popp, Michael Schulz, and Philip Stier
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Jianping Guo, Boming Liu, Wei Gong, Lijuan Shi, Yong Zhang, Yingying Ma, Jian Zhang, Tianmeng Chen, Kaixu Bai, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
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Kaisa Lakkala, Margit Aun, Ricardo Sanchez, Germar Bernhard, Eija Asmi, Outi Meinander, Fernando Nollas, Gregor Hülsen, Tomi Karppinen, Veijo Aaltonen, Antti Arola, and Gerrit de Leeuw
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Larisa Sogacheva, Thomas Popp, Andrew M. Sayer, Oleg Dubovik, Michael J. Garay, Andreas Heckel, N. Christina Hsu, Hiren Jethva, Ralph A. Kahn, Pekka Kolmonen, Miriam Kosmale, Gerrit de Leeuw, Robert C. Levy, Pavel Litvinov, Alexei Lyapustin, Peter North, Omar Torres, and Antti Arola
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The typical lifetime of a single satellite platform is on the order of 5–15 years; thus, for climate studies the usage of multiple satellite sensors should be considered.
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Giulia Saponaro, Moa K. Sporre, David Neubauer, Harri Kokkola, Pekka Kolmonen, Larisa Sogacheva, Antti Arola, Gerrit de Leeuw, Inger H. H. Karset, Ari Laaksonen, and Ulrike Lohmann
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Michael Boy, Erik S. Thomson, Juan-C. Acosta Navarro, Olafur Arnalds, Ekaterina Batchvarova, Jaana Bäck, Frank Berninger, Merete Bilde, Zoé Brasseur, Pavla Dagsson-Waldhauserova, Dimitri Castarède, Maryam Dalirian, Gerrit de Leeuw, Monika Dragosics, Ella-Maria Duplissy, Jonathan Duplissy, Annica M. L. Ekman, Keyan Fang, Jean-Charles Gallet, Marianne Glasius, Sven-Erik Gryning, Henrik Grythe, Hans-Christen Hansson, Margareta Hansson, Elisabeth Isaksson, Trond Iversen, Ingibjorg Jonsdottir, Ville Kasurinen, Alf Kirkevåg, Atte Korhola, Radovan Krejci, Jon Egill Kristjansson, Hanna K. Lappalainen, Antti Lauri, Matti Leppäranta, Heikki Lihavainen, Risto Makkonen, Andreas Massling, Outi Meinander, E. Douglas Nilsson, Haraldur Olafsson, Jan B. C. Pettersson, Nønne L. Prisle, Ilona Riipinen, Pontus Roldin, Meri Ruppel, Matthew Salter, Maria Sand, Øyvind Seland, Heikki Seppä, Henrik Skov, Joana Soares, Andreas Stohl, Johan Ström, Jonas Svensson, Erik Swietlicki, Ksenia Tabakova, Throstur Thorsteinsson, Aki Virkkula, Gesa A. Weyhenmeyer, Yusheng Wu, Paul Zieger, and Markku Kulmala
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Yuqin Liu, Jiahua Zhang, Putian Zhou, Tao Lin, Juan Hong, Lamei Shi, Fengmei Yao, Jun Wu, Huadong Guo, and Gerrit de Leeuw
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Larisa Sogacheva, Edith Rodriguez, Pekka Kolmonen, Timo H. Virtanen, Giulia Saponaro, Gerrit de Leeuw, Aristeidis K. Georgoulias, Georgia Alexandri, Konstantinos Kourtidis, and Ronald J. van der A
Atmos. Chem. Phys., 18, 16631–16652, https://doi.org/10.5194/acp-18-16631-2018, https://doi.org/10.5194/acp-18-16631-2018, 2018
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Understanding long-term trends in aerosol optical density (AOD) is essential for evaluating health and climate effects and the effectiveness of pollution control policies. A method to construct a combined AOD long time series (1995-2017) using ATSR and MODIS spaceborne instruments is introduced. The effect of changes in the emission regulation policy in China is seen in a gradual AOD decrease after 2011. The effect is more visible in highly populated and industrialized areas in southeast China.
Kaisa Lakkala, Alberto Redondas, Outi Meinander, Laura Thölix, Britta Hamari, Antonio Fernando Almansa, Virgilio Carreno, Rosa Delia García, Carlos Torres, Guillermo Deferrari, Hector Ochoa, Germar Bernhard, Ricardo Sanchez, and Gerrit de Leeuw
Atmos. Chem. Phys., 18, 16019–16031, https://doi.org/10.5194/acp-18-16019-2018, https://doi.org/10.5194/acp-18-16019-2018, 2018
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Solar UV irradiances were measured at Ushuaia (54° S) and Marambio (64° S) during 2000–2013. The measurements were part of the Antarctic NILU-UV network, which was maintained as a cooperation between Spain, Argentina and Finland. The time series of the network were analysed for the first time in this study. At both stations maximum UV indices and daily doses were measured when spring-time ozone loss episodes occurred. The maximum UV index was 13 and 12 in Ushuaia and Marambio, respectively.
Larisa Sogacheva, Gerrit de Leeuw, Edith Rodriguez, Pekka Kolmonen, Aristeidis K. Georgoulias, Georgia Alexandri, Konstantinos Kourtidis, Emmanouil Proestakis, Eleni Marinou, Vassilis Amiridis, Yong Xue, and Ronald J. van der A
Atmos. Chem. Phys., 18, 11389–11407, https://doi.org/10.5194/acp-18-11389-2018, https://doi.org/10.5194/acp-18-11389-2018, 2018
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Timo H. Virtanen, Pekka Kolmonen, Larisa Sogacheva, Edith Rodríguez, Giulia Saponaro, and Gerrit de Leeuw
Atmos. Meas. Tech., 11, 925–938, https://doi.org/10.5194/amt-11-925-2018, https://doi.org/10.5194/amt-11-925-2018, 2018
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We study the collocation mismatch uncertainty related to validating coarse-resolution satellite-based aerosol data against point-like ground based measurements. We use the spatial variability in the satellite data to estimate the upper limit for the uncertainty and study the effect of sampling parameters in the validation. We find that accounting for the collocation mismatch uncertainty increases the fraction of consistent data in the validation.
Gerrit de Leeuw, Larisa Sogacheva, Edith Rodriguez, Konstantinos Kourtidis, Aristeidis K. Georgoulias, Georgia Alexandri, Vassilis Amiridis, Emmanouil Proestakis, Eleni Marinou, Yong Xue, and Ronald van der A
Atmos. Chem. Phys., 18, 1573–1592, https://doi.org/10.5194/acp-18-1573-2018, https://doi.org/10.5194/acp-18-1573-2018, 2018
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The complementary use of two sensors, ATSR and MODIS, to provide aerosol information over two decades (1995–2015) is described. To this end, the AOD retrieved from both instruments had to be compared, showing that ATSR slightly underestimates and MODIS overestimates by a similar amount. Results show the increase of aerosols over the years, with an indication of the onset of a decrease in recent years. The AOD spatial distribution shows seasonal variations across China.
Emmanouil Proestakis, Vassilis Amiridis, Eleni Marinou, Aristeidis K. Georgoulias, Stavros Solomos, Stelios Kazadzis, Julien Chimot, Huizheng Che, Georgia Alexandri, Ioannis Binietoglou, Vasiliki Daskalopoulou, Konstantinos A. Kourtidis, Gerrit de Leeuw, and Ronald J. van der A
Atmos. Chem. Phys., 18, 1337–1362, https://doi.org/10.5194/acp-18-1337-2018, https://doi.org/10.5194/acp-18-1337-2018, 2018
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We provide a 3-D climatology of desert dust aerosols over South and East Asia, based on 9 years of CALIPSO observations and an EARLINET methodology. The results provide the horizontal, vertical and seasonal distribution of dust aerosols over SE Asia along with the change in dust transport pathways. The dataset is unique for its potential applications, including evaluation and assimilation activities in atmospheric simulations and the estimation of the climatic impact of dust aerosols.
Christopher J. Merchant, Frank Paul, Thomas Popp, Michael Ablain, Sophie Bontemps, Pierre Defourny, Rainer Hollmann, Thomas Lavergne, Alexandra Laeng, Gerrit de Leeuw, Jonathan Mittaz, Caroline Poulsen, Adam C. Povey, Max Reuter, Shubha Sathyendranath, Stein Sandven, Viktoria F. Sofieva, and Wolfgang Wagner
Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, https://doi.org/10.5194/essd-9-511-2017, 2017
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Climate data records (CDRs) contain data describing Earth's climate and should address uncertainty in the data to communicate what is known about climate variability or change and what range of doubt exists. This paper discusses good practice for including uncertainty information in CDRs for the essential climate variables (ECVs) derived from satellite data. Recommendations emerge from the shared experience of diverse ECV projects within the European Space Agency Climate Change Initiative.
Yuqin Liu, Gerrit de Leeuw, Veli-Matti Kerminen, Jiahua Zhang, Putian Zhou, Wei Nie, Ximeng Qi, Juan Hong, Yonghong Wang, Aijun Ding, Huadong Guo, Olaf Krüger, Markku Kulmala, and Tuukka Petäjä
Atmos. Chem. Phys., 17, 5623–5641, https://doi.org/10.5194/acp-17-5623-2017, https://doi.org/10.5194/acp-17-5623-2017, 2017
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The aerosol effects on warm cloud parameters over the Yangtze River Delta are systematically examined using multi-sensor retrievals. This study shows that the COT–CDR and CWP–CDR relationships are not unique, but are affected by atmospheric aerosol loading. CDR and cloud fraction show different behaviours for low and high AOD. Aerosol–cloud interaction (ACI) is stronger for clouds mixed with smoke aerosol than for clouds mixed with dust. Meteorological conditions play an important role in ACI.
Giulia Saponaro, Pekka Kolmonen, Larisa Sogacheva, Edith Rodriguez, Timo Virtanen, and Gerrit de Leeuw
Atmos. Chem. Phys., 17, 3133–3143, https://doi.org/10.5194/acp-17-3133-2017, https://doi.org/10.5194/acp-17-3133-2017, 2017
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The effect of aerosol upon cloud properties is studied over the Baltic Sea region, which presents a distinct contrast of aerosol loading between the clean Fennoscandia and the polluted area of central–eastern Europe. Statistically significant positive values are found over the Baltic Sea and Fennoscandia, while negative values are found over central–eastern Europe, contradicting the theory of aerosol indirect effect on clouds.
Larisa Sogacheva, Pekka Kolmonen, Timo H. Virtanen, Edith Rodriguez, Giulia Saponaro, and Gerrit de Leeuw
Atmos. Meas. Tech., 10, 491–505, https://doi.org/10.5194/amt-10-491-2017, https://doi.org/10.5194/amt-10-491-2017, 2017
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Clouds reflect solar light much more strongly than aerosol particles. Therefore, the retrieval of aerosol optical depth is usually only attempted over cloud-free areas. A very strict cloud detection scheme has to be applied to remove all cloudy pixels. However, often not all clouds are detected. To remove possibly cloud-contaminated pixels, a cloud post-processing algorithm has been designed, which effectively solves the problem and results in smoother AOD maps and improved validation results.
Anu Heikkilä, Jakke Sakari Mäkelä, Kaisa Lakkala, Outi Meinander, Jussi Kaurola, Tapani Koskela, Juha Matti Karhu, Tomi Karppinen, Esko Kyrö, and Gerrit de Leeuw
Geosci. Instrum. Method. Data Syst., 5, 531–540, https://doi.org/10.5194/gi-5-531-2016, https://doi.org/10.5194/gi-5-531-2016, 2016
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Lamp measurements used for the UV irradiance calibration of two Brewer spectrophotometers operated for 20 years in Jokioinen and Sodankylä, Finland, were examined. Temporal development of the responsivity after fixing the irradiance measurements into a specific scale was studied. Both long-term gradual decrease and abrupt changes in responsiveness were detected. Frequent-enough measurements of working standard lamps were found necessary to detect the short-term variations in responsiveness.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
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After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
Laura Riuttanen, Marja Bister, Veli-Matti Kerminen, Viju O. John, Anu-Maija Sundström, Miikka Dal Maso, Jouni Räisänen, Victoria A. Sinclair, Risto Makkonen, Filippo Xausa, Gerrit de Leeuw, and Markku Kulmala
Atmos. Chem. Phys., 16, 14331–14342, https://doi.org/10.5194/acp-16-14331-2016, https://doi.org/10.5194/acp-16-14331-2016, 2016
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Here we show observational evidence that aerosols increase upper tropospheric humidity (UTH) via changes in the microphysics of deep convection. Using remote sensing data over the ocean east of China in summer, we show that increased aerosol loads are associated with an UTH increase of 2.2 ± 1.5 in units of relative humidity. We show that humidification of aerosols or other meteorological covariation is very unlikely to be the cause for this result indicating relevance for the global climate.
Monique F. M. A. Albert, Magdalena D. Anguelova, Astrid M. M. Manders, Martijn Schaap, and Gerrit de Leeuw
Atmos. Chem. Phys., 16, 13725–13751, https://doi.org/10.5194/acp-16-13725-2016, https://doi.org/10.5194/acp-16-13725-2016, 2016
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Sea spray source functions (SSSFs) predict production of sea salt aerosol, important for climate. Sea spray originates from bubble bursting within whitecaps, mainly formed by wind speed (U). Using satellite-based whitecap fraction (W) data analyzed on global and regional scale and explicitly accounting for sea surface temperature (T) we derive a new W(U, T) parameterization. We use it to evaluate influence of secondary factors on a SSSF via W.
U. Frieß, H. Klein Baltink, S. Beirle, K. Clémer, F. Hendrick, B. Henzing, H. Irie, G. de Leeuw, A. Li, M. M. Moerman, M. van Roozendael, R. Shaiganfar, T. Wagner, Y. Wang, P. Xie, S. Yilmaz, and P. Zieger
Atmos. Meas. Tech., 9, 3205–3222, https://doi.org/10.5194/amt-9-3205-2016, https://doi.org/10.5194/amt-9-3205-2016, 2016
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This article describes the first direct comparison of aerosol extinction profiles from Multi-Axis DOAS measurements of the oxygen collision complex using five different retrieval algorithms. A comparison of the retrieved profiles with co-located aerosol measurements shows good agreement with respect to profile shape and aerosol optical thickness. This study shows that MAX-DOAS is a simple, versatile and cost-effective method for the measurement of aerosol properties in the lower troposphere.
Tero Mielonen, Anca Hienola, Thomas Kühn, Joonas Merikanto, Antti Lipponen, Tommi Bergman, Hannele Korhonen, Pekka Kolmonen, Larisa Sogacheva, Darren Ghent, Antti Arola, Gerrit de Leeuw, and Harri Kokkola
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-625, https://doi.org/10.5194/acp-2016-625, 2016
Revised manuscript not accepted
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We studied the temperature dependence of AOD and its radiative effects over the southeastern US. We used spaceborne observations of AOD, LST and tropospheric NO2 with simulations of ECHAM-HAMMOZ. The level of AOD in this region is governed by anthropogenic emissions but the temperature dependency is most likely caused by BVOC emissions. According to the observations and simulations, the regional clear-sky DRE for biogenic aerosols is −0.43 ± 0.88 W/m2/K and −0.86 ± 0.06 W/m2/K, respectively.
Jakke Sakari Mäkelä, Kaisa Lakkala, Tapani Koskela, Tomi Karppinen, Juha Matti Karhu, Vladimir Savastiouk, Hanne Suokanerva, Jussi Kaurola, Antti Arola, Anders Vilhelm Lindfors, Outi Meinander, Gerrit de Leeuw, and Anu Heikkilä
Geosci. Instrum. Method. Data Syst., 5, 193–203, https://doi.org/10.5194/gi-5-193-2016, https://doi.org/10.5194/gi-5-193-2016, 2016
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We describe the steps that are used at the Finnish Meteorological Institute (FMI) to process spectral ultraviolet (UV) radiation measurements made with its three Brewer spectrophotometers, located in Sodankylä (67° N) and Jokioinen (61° N). Multiple corrections are made to the data in near-real time and quality control is also performed automatically. Several data products are produced, including the near-real-time UV index and various daily dosages, and submitted to databases.
J. I. Peltoniemi, M. Gritsevich, T. Hakala, P. Dagsson-Waldhauserová, Ó. Arnalds, K. Anttila, H.-R. Hannula, N. Kivekäs, H. Lihavainen, O. Meinander, J. Svensson, A. Virkkula, and G. de Leeuw
The Cryosphere, 9, 2323–2337, https://doi.org/10.5194/tc-9-2323-2015, https://doi.org/10.5194/tc-9-2323-2015, 2015
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Light-absorbing impurities change the reflectance of snow in different ways. Some particles are heated by the Sun and they sink out of sight. During the process, snow may look darker than pure snow when observed by nadir, but at larger view zenith angles the snow may look as white as clean snow. Thus an observer on the ground may overestimate the albedo, while a satellite underestimates the albedo. Climate studies need to examine how the contaminants behave in snow, not only their total amounts.
E. Rodríguez, P. Kolmonen, T. H. Virtanen, L. Sogacheva, A.-M. Sundström, and G. de Leeuw
Atmos. Meas. Tech., 8, 3075–3085, https://doi.org/10.5194/amt-8-3075-2015, https://doi.org/10.5194/amt-8-3075-2015, 2015
P. Zieger, P. P. Aalto, V. Aaltonen, M. Äijälä, J. Backman, J. Hong, M. Komppula, R. Krejci, M. Laborde, J. Lampilahti, G. de Leeuw, A. Pfüller, B. Rosati, M. Tesche, P. Tunved, R. Väänänen, and T. Petäjä
Atmos. Chem. Phys., 15, 7247–7267, https://doi.org/10.5194/acp-15-7247-2015, https://doi.org/10.5194/acp-15-7247-2015, 2015
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The effect of water uptake (hygroscopicity) on aerosol light scattering properties is generally lower for boreal aerosol due to the dominance of organic substances. A columnar optical closure study using ground-based and airborne measurements of aerosol optical, chemical and microphysical properties was conducted and the implications and limitations are discussed.
A.-M. Sundström, A. Nikandrova, K. Atlaskina, T. Nieminen, V. Vakkari, L. Laakso, J. P. Beukes, A. Arola, P. G. van Zyl, M. Josipovic, A. D. Venter, K. Jaars, J. J. Pienaar, S. Piketh, A. Wiedensohler, E. K. Chiloane, G. de Leeuw, and M. Kulmala
Atmos. Chem. Phys., 15, 4983–4996, https://doi.org/10.5194/acp-15-4983-2015, https://doi.org/10.5194/acp-15-4983-2015, 2015
J. Svensson, A. Virkkula, O. Meinander, N. Kivekäs, H.-R. Hannula, O. Järvinen, J. I. Peltoniemi, M. Gritsevich, A. Heikkilä, A. Kontu, A.-P. Hyvärinen, K. Neitola, D. Brus, P. Dagsson-Waldhauserova, K. Anttila, T. Hakala, H. Kaartinen, M. Vehkamäki, G. de Leeuw, and H. Lihavainen
The Cryosphere Discuss., https://doi.org/10.5194/tcd-9-1227-2015, https://doi.org/10.5194/tcd-9-1227-2015, 2015
Revised manuscript not accepted
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Soot's (including black carbon and organics) negative effect on a natural snow pack is experimentally addressed in this paper through a series of experiments. Soot concentrations in the snow in the range of 200-200 000 ppb verify the negative effects on the albedo, the physical snow characteristics, as well as increasing the melt rate of the snow pack. Our experimental data generally agrees when compared with the Snow, Ice and Aerosol Radiation model.
L. Sogacheva, P. Kolmonen, T. H. Virtanen, E. Rodriguez, A.-M. Sundström, and G. de Leeuw
Atmos. Meas. Tech., 8, 891–906, https://doi.org/10.5194/amt-8-891-2015, https://doi.org/10.5194/amt-8-891-2015, 2015
A.-M. Sundström, A. Arola, P. Kolmonen, Y. Xue, G. de Leeuw, and M. Kulmala
Atmos. Chem. Phys., 15, 505–518, https://doi.org/10.5194/acp-15-505-2015, https://doi.org/10.5194/acp-15-505-2015, 2015
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In this work, a satellite-based approach to derive the aerosol direct shortwave (SW) radiative effect (ADRE) is studied. The method is based on using coincident satellite observations of SW fluxes and aerosol optical depths (AODs). The key findings of this study are that using normalized values of observed fluxes improves the estimates of ADRE and aerosol-free TOA fluxes as compared to a model. The method was applied over eastern China where the satellite-based mean ADRE of -5Wm-2 was obtained.
A.-I. Partanen, E. M. Dunne, T. Bergman, A. Laakso, H. Kokkola, J. Ovadnevaite, L. Sogacheva, D. Baisnée, J. Sciare, A. Manders, C. O'Dowd, G. de Leeuw, and H. Korhonen
Atmos. Chem. Phys., 14, 11731–11752, https://doi.org/10.5194/acp-14-11731-2014, https://doi.org/10.5194/acp-14-11731-2014, 2014
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New parameterizations for the sea spray aerosol source flux and its organic fraction were incorporated into a global aerosol-climate model. The emissions of sea salt were considerably less than previous estimates. This study demonstrates that sea spray aerosol may actually decrease the number of cloud droplets, which has a warming effect on climate. Overall, sea spray aerosol was predicted to have a global cooling effect due to the scattering of solar radiation from sea spray aerosol particles.
L. Wang, Y. Zhang, F. Berninger, and B. Duan
Biogeosciences, 11, 5595–5606, https://doi.org/10.5194/bg-11-5595-2014, https://doi.org/10.5194/bg-11-5595-2014, 2014
L. L. Mei, Y. Xue, A. A. Kokhanovsky, W. von Hoyningen-Huene, G. de Leeuw, and J. P. Burrows
Atmos. Meas. Tech., 7, 2411–2420, https://doi.org/10.5194/amt-7-2411-2014, https://doi.org/10.5194/amt-7-2411-2014, 2014
T. H. Virtanen, P. Kolmonen, E. Rodríguez, L. Sogacheva, A.-M. Sundström, and G. de Leeuw
Atmos. Meas. Tech., 7, 2437–2456, https://doi.org/10.5194/amt-7-2437-2014, https://doi.org/10.5194/amt-7-2437-2014, 2014
O. Meinander, A. Kontu, A. Virkkula, A. Arola, L. Backman, P. Dagsson-Waldhauserová, O. Järvinen, T. Manninen, J. Svensson, G. de Leeuw, and M. Leppäranta
The Cryosphere, 8, 991–995, https://doi.org/10.5194/tc-8-991-2014, https://doi.org/10.5194/tc-8-991-2014, 2014
A. Virkkula, J. Levula, T. Pohja, P. P. Aalto, P. Keronen, S. Schobesberger, C. B. Clements, L. Pirjola, A.-J. Kieloaho, L. Kulmala, H. Aaltonen, J. Patokoski, J. Pumpanen, J. Rinne, T. Ruuskanen, M. Pihlatie, H. E. Manninen, V. Aaltonen, H. Junninen, T. Petäjä, J. Backman, M. Dal Maso, T. Nieminen, T. Olsson, T. Grönholm, J. Aalto, T. H. Virtanen, M. Kajos, V.-M. Kerminen, D. M. Schultz, J. Kukkonen, M. Sofiev, G. De Leeuw, J. Bäck, P. Hari, and M. Kulmala
Atmos. Chem. Phys., 14, 4473–4502, https://doi.org/10.5194/acp-14-4473-2014, https://doi.org/10.5194/acp-14-4473-2014, 2014
D. C. S. Beddows, M. Dall'Osto, R. M. Harrison, M. Kulmala, A. Asmi, A. Wiedensohler, P. Laj, A.M. Fjaeraa, K. Sellegri, W. Birmili, N. Bukowiecki, E. Weingartner, U. Baltensperger, V. Zdimal, N. Zikova, J.-P. Putaud, A. Marinoni, P. Tunved, H.-C. Hansson, M. Fiebig, N. Kivekäs, E. Swietlicki, H. Lihavainen, E. Asmi, V. Ulevicius, P. P. Aalto, N. Mihalopoulos, N. Kalivitis, I. Kalapov, G. Kiss, G. de Leeuw, B. Henzing, C. O'Dowd, S. G. Jennings, H. Flentje, F. Meinhardt, L. Ries, H. A. C. Denier van der Gon, and A. J. H. Visschedijk
Atmos. Chem. Phys., 14, 4327–4348, https://doi.org/10.5194/acp-14-4327-2014, https://doi.org/10.5194/acp-14-4327-2014, 2014
M. Tjernström, C. Leck, C. E. Birch, J. W. Bottenheim, B. J. Brooks, I. M. Brooks, L. Bäcklin, R. Y.-W. Chang, G. de Leeuw, L. Di Liberto, S. de la Rosa, E. Granath, M. Graus, A. Hansel, J. Heintzenberg, A. Held, A. Hind, P. Johnston, J. Knulst, M. Martin, P. A. Matrai, T. Mauritsen, M. Müller, S. J. Norris, M. V. Orellana, D. A. Orsini, J. Paatero, P. O. G. Persson, Q. Gao, C. Rauschenberg, Z. Ristovski, J. Sedlar, M. D. Shupe, B. Sierau, A. Sirevaag, S. Sjogren, O. Stetzer, E. Swietlicki, M. Szczodrak, P. Vaattovaara, N. Wahlberg, M. Westberg, and C. R. Wheeler
Atmos. Chem. Phys., 14, 2823–2869, https://doi.org/10.5194/acp-14-2823-2014, https://doi.org/10.5194/acp-14-2823-2014, 2014
J. Ovadnevaite, A. Manders, G. de Leeuw, D. Ceburnis, C. Monahan, A.-I. Partanen, H. Korhonen, and C. D. O'Dowd
Atmos. Chem. Phys., 14, 1837–1852, https://doi.org/10.5194/acp-14-1837-2014, https://doi.org/10.5194/acp-14-1837-2014, 2014
G. Saponaro, P. Kolmonen, J. Karhunen, J. Tamminen, and G. de Leeuw
Atmos. Meas. Tech., 6, 2301–2309, https://doi.org/10.5194/amt-6-2301-2013, https://doi.org/10.5194/amt-6-2301-2013, 2013
T. Holzer-Popp, G. de Leeuw, J. Griesfeller, D. Martynenko, L. Klüser, S. Bevan, W. Davies, F. Ducos, J. L. Deuzé, R. G. Graigner, A. Heckel, W. von Hoyningen-Hüne, P. Kolmonen, P. Litvinov, P. North, C. A. Poulsen, D. Ramon, R. Siddans, L. Sogacheva, D. Tanre, G. E. Thomas, M. Vountas, J. Descloitres, J. Griesfeller, S. Kinne, M. Schulz, and S. Pinnock
Atmos. Meas. Tech., 6, 1919–1957, https://doi.org/10.5194/amt-6-1919-2013, https://doi.org/10.5194/amt-6-1919-2013, 2013
P. Kolmonen, A.-M. Sundström, L. Sogacheva, E. Rodriguez, T. Virtanen, and G. de Leeuw
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-6-4039-2013, https://doi.org/10.5194/amtd-6-4039-2013, 2013
Revised manuscript has not been submitted
S. J. Norris, I. M. Brooks, B. I. Moat, M. J. Yelland, G. de Leeuw, R. W. Pascal, and B. Brooks
Ocean Sci., 9, 133–145, https://doi.org/10.5194/os-9-133-2013, https://doi.org/10.5194/os-9-133-2013, 2013
L. Riuttanen, M. Dal Maso, G. de Leeuw, I. Riipinen, L. Sogacheva, V. Vakkari, L. Laakso, and M. Kulmala
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-4289-2013, https://doi.org/10.5194/acpd-13-4289-2013, 2013
Revised manuscript has not been submitted
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Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign
Sea ice transport and replenishment across and within the Canadian Arctic Archipelago, 2016–2022
SAR deep learning sea ice retrieval trained with airborne laser scanner measurements from the MOSAiC expedition
Lake ice break-up in Greenland: timing and spatiotemporal variability
Temperature-dominated spatiotemporal variability in snow phenology on the Tibetan Plateau from 2002 to 2022
MMSeaIce: a collection of techniques for improving sea ice mapping with a multi-task model
Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
Lead fractions from SAR-derived sea ice divergence during MOSAiC
Bayesian physical–statistical retrieval of snow water equivalent and snow depth from X- and Ku-band synthetic aperture radar – demonstration using airborne SnowSAr in SnowEx'17
A low-cost and open-source approach for supraglacial debris thickness mapping using UAV-based infrared thermography
Snow water equivalent retrieval over Idaho – Part 1: Using Sentinel-1 repeat-pass interferometry
Passive microwave remote-sensing-based high-resolution snow depth mapping for Western Himalayan zones using multifactor modeling approach
Mapping surface hoar from near-infrared texture in a laboratory
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Retrieval of snow water equivalent from dual-frequency radar measurements: using time series to overcome the need for accurate a priori information
Ice floe segmentation and floe size distribution in airborne and high-resolution optical satellite images: towards an automated labelling deep learning approach
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Annual to seasonal glacier mass balance in High Mountain Asia derived from Pléiades stereo images: examples from the Pamir and the Tibetan Plateau
Snow accumulation, albedo and melt patterns following road construction on permafrost, Inuvik–Tuktoyaktuk Highway, Canada
Co-registration and residual correction of digital elevation models: a comparative study
Sentinel-1 Detection of Ice Slabs on the Greenland Ice Sheet
Out-of-the-box calving-front detection method using deep learning
Mapping the extent of giant Antarctic icebergs with deep learning
Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data
Allometric scaling of retrogressive thaw slumps
Mapping Antarctic crevasses and their evolution with deep learning applied to satellite radar imagery
Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 1: Measurements, processing, and accuracy assessment
Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions
Evaluating Snow Microwave Radiative Transfer (SMRT) model emissivities with 89 to 243 GHz observations of Arctic tundra snow
Brief communication: Identification of tundra topsoil frozen/thawed state from SMAP and GCOM-W1 radiometer measurements using the spectral gradient method
New estimates of pan-Arctic sea ice–atmosphere neutral drag coefficients from ICESat-2 elevation data
GLAcier Feature Tracking testkit (GLAFT): a statistically and physically based framework for evaluating glacier velocity products derived from optical satellite image feature tracking
Evaluating the utility of active microwave observations as a snow mission concept using observing system simulation experiments
Relevance of warm air intrusions for Arctic satellite sea ice concentration time series
Observing the evolution of summer melt on multiyear sea ice with ICESat-2 and Sentinel-2
Estimating differential penetration of green (532 nm) laser light over sea ice with NASA’s Airborne Topographic Mapper: observations and models
Cast shadows reveal changes in glacier surface elevation
AutoTerm: an automated pipeline for glacier terminus extraction using machine learning and a “big data” repository of Greenland glacier termini
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Spaceborne thermal infrared observations of Arctic sea ice leads at 30 m resolution
Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data
How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?
Exploring the use of multi-source high-resolution satellite data for snow water equivalent reconstruction over mountainous catchments
Constraining regional glacier reconstructions using past ice thickness of deglaciating areas – a case study in the European Alps
Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice
Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR)
Bedfast and floating-ice dynamics of thermokarst lakes using a temporal deep-learning mapping approach: case study of the Old Crow Flats, Yukon, Canada
First observations of sea ice flexural–gravity waves with ground-based radar interferometry in Utqiaġvik, Alaska
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Steven J. Pestana, C. Chris Chickadel, and Jessica D. Lundquist
The Cryosphere, 18, 2257–2276, https://doi.org/10.5194/tc-18-2257-2024, https://doi.org/10.5194/tc-18-2257-2024, 2024
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We compared infrared images taken by GOES-R satellites of an area with snow and forests against surface temperature measurements taken on the ground, from an aircraft, and by another satellite. We found that GOES-R measured warmer temperatures than the other measurements, especially in areas with more forest and when the Sun was behind the satellite. From this work, we learned that the position of the Sun and surface features such as trees that can cast shadows impact GOES-R infrared images.
Stephen E. L. Howell, David G. Babb, Jack C. Landy, Isolde A. Glissenaar, Kaitlin McNeil, Benoit Montpetit, and Mike Brady
The Cryosphere, 18, 2321–2333, https://doi.org/10.5194/tc-18-2321-2024, https://doi.org/10.5194/tc-18-2321-2024, 2024
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The CAA serves as both a source and a sink for sea ice from the Arctic Ocean, while also exporting sea ice into Baffin Bay. It is also an important region with respect to navigating the Northwest Passage. Here, we quantify sea ice transport and replenishment across and within the CAA from 2016 to 2022. We also provide the first estimates of the ice area and volume flux within the CAA from the Queen Elizabeth Islands to Parry Channel, which spans the central region of the Northwest Passage.
Karl Kortum, Suman Singha, Gunnar Spreen, Nils Hutter, Arttu Jutila, and Christian Haas
The Cryosphere, 18, 2207–2222, https://doi.org/10.5194/tc-18-2207-2024, https://doi.org/10.5194/tc-18-2207-2024, 2024
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A dataset of 20 radar satellite acquisitions and near-simultaneous helicopter-based surveys of the ice topography during the MOSAiC expedition is constructed and used to train a variety of deep learning algorithms. The results give realistic insights into the accuracy of retrieval of measured ice classes using modern deep learning models. The models able to learn from the spatial distribution of the measured sea ice classes are shown to have a clear advantage over those that cannot.
Christoph Posch, Jakob Abermann, and Tiago Silva
The Cryosphere, 18, 2035–2059, https://doi.org/10.5194/tc-18-2035-2024, https://doi.org/10.5194/tc-18-2035-2024, 2024
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Radar beams from satellites exhibit reflection differences between water and ice. This condition, as well as the comprehensive coverage and high temporal resolution of the Sentinel-1 satellites, allows automatically detecting the timing of when ice cover of lakes in Greenland disappear. We found that lake ice breaks up 3 d later per 100 m elevation gain and that the average break-up timing varies by ±8 d in 2017–2021, which has major implications for the energy budget of the lakes.
Jiahui Xu, Yao Tang, Linxin Dong, Shujie Wang, Bailang Yu, Jianping Wu, Zhaojun Zheng, and Yan Huang
The Cryosphere, 18, 1817–1834, https://doi.org/10.5194/tc-18-1817-2024, https://doi.org/10.5194/tc-18-1817-2024, 2024
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Understanding snow phenology (SP) and its possible feedback are important. We reveal spatiotemporal heterogeneous SP on the Tibetan Plateau (TP) and the mediating effects from meteorological, topographic, and environmental factors on it. The direct effects of meteorology on SP are much greater than the indirect effects. Topography indirectly effects SP, while vegetation directly effects SP. This study contributes to understanding past global warming and predicting future trends on the TP.
Xinwei Chen, Muhammed Patel, Fernando J. Pena Cantu, Jinman Park, Javier Noa Turnes, Linlin Xu, K. Andrea Scott, and David A. Clausi
The Cryosphere, 18, 1621–1632, https://doi.org/10.5194/tc-18-1621-2024, https://doi.org/10.5194/tc-18-1621-2024, 2024
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This paper introduces an automated sea ice mapping pipeline utilizing a multi-task U-Net architecture. It attained the top score of 86.3 % in the AutoICE challenge. Ablation studies revealed that incorporating brightness temperature data and spatial–temporal information significantly enhanced model accuracy. Accurate sea ice mapping is vital for comprehending the Arctic environment and its global climate effects, underscoring the potential of deep learning.
Jinmei Pan, Michael Durand, Juha Lemmetyinen, Desheng Liu, and Jiancheng Shi
The Cryosphere, 18, 1561–1578, https://doi.org/10.5194/tc-18-1561-2024, https://doi.org/10.5194/tc-18-1561-2024, 2024
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We developed an algorithm to estimate snow mass using X- and dual Ku-band radar, and tested it in a ground-based experiment. The algorithm, the Bayesian-based Algorithm for SWE Estimation (BASE) using active microwaves, achieved an RMSE of 30 mm for snow water equivalent. These results demonstrate the potential of radar, a highly promising sensor, to map snow mass at high spatial resolution.
Luisa von Albedyll, Stefan Hendricks, Nils Hutter, Dmitrii Murashkin, Lars Kaleschke, Sascha Willmes, Linda Thielke, Xiangshan Tian-Kunze, Gunnar Spreen, and Christian Haas
The Cryosphere, 18, 1259–1285, https://doi.org/10.5194/tc-18-1259-2024, https://doi.org/10.5194/tc-18-1259-2024, 2024
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Leads (openings in sea ice cover) are created by sea ice dynamics. Because they are important for many processes in the Arctic winter climate, we aim to detect them with satellites. We present two new techniques to detect lead widths of a few hundred meters at high spatial resolution (700 m) and independent of clouds or sun illumination. We use the MOSAiC drift 2019–2020 in the Arctic for our case study and compare our new products to other existing lead products.
Siddharth Singh, Michael Durand, Edward Kim, and Ana P. Barros
The Cryosphere, 18, 747–773, https://doi.org/10.5194/tc-18-747-2024, https://doi.org/10.5194/tc-18-747-2024, 2024
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Seasonal snowfall accumulation plays a critical role in climate. The water stored in it is measured by the snow water equivalent (SWE), the amount of water released after completely melting. We demonstrate a Bayesian physical–statistical framework to estimate SWE from airborne X- and Ku-band synthetic aperture radar backscatter measurements constrained by physical snow hydrology and radar models. We explored spatial resolutions and vertical structures that agree well with ground observations.
Jérôme Messmer and Alexander Raphael Groos
The Cryosphere, 18, 719–746, https://doi.org/10.5194/tc-18-719-2024, https://doi.org/10.5194/tc-18-719-2024, 2024
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The lower part of mountain glaciers is often covered with debris. Knowing the thickness of the debris is important as it influences the melting and future evolution of the affected glaciers. We have developed an open-source approach to map variations in debris thickness on glaciers using a low-cost drone equipped with a thermal infrared camera. The resulting high-resolution maps of debris surface temperature and thickness enable more accurate monitoring and modelling of debris-covered glaciers.
Shadi Oveisgharan, Robert Zinke, Zachary Hoppinen, and Hans Peter Marshall
The Cryosphere, 18, 559–574, https://doi.org/10.5194/tc-18-559-2024, https://doi.org/10.5194/tc-18-559-2024, 2024
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The seasonal snowpack provides water resources to billions of people worldwide. Large-scale mapping of snow water equivalent (SWE) with high resolution is critical for many scientific and economics fields. In this work we used the radar remote sensing interferometric synthetic aperture radar (InSAR) to estimate the SWE change between 2 d. The error in the estimated SWE change is less than 2 cm for in situ stations. Additionally, the retrieved SWE using InSAR is correlated with lidar snow depth.
Dhiraj Kumar Singh, Srinivasarao Tanniru, Kamal Kant Singh, Harendra Singh Negi, and RAAJ Ramsankaran
The Cryosphere, 18, 451–474, https://doi.org/10.5194/tc-18-451-2024, https://doi.org/10.5194/tc-18-451-2024, 2024
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In situ techniques for snow depth (SD) measurement are not adequate to represent the spatiotemporal variability in SD in the Western Himalayan region. Therefore, this study focuses on the high-resolution mapping of daily snow depth in the Indian Western Himalayan region using passive microwave remote-sensing-based algorithms. Overall, the proposed multifactor SD models demonstrated substantial improvement compared to the operational products. However, there is a scope for further improvement.
James Dillon, Christopher Donahue, Evan Schehrer, Karl Birkeland, and Kevin Hammonds
EGUsphere, https://doi.org/10.5194/egusphere-2023-3133, https://doi.org/10.5194/egusphere-2023-3133, 2024
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Surface hoar crystals are snow grains that form when vapor deposits on the snow surface. They create a weak layer in the snowpack that can cause large avalanches to occur. Thus, determining when and where surface hoar forms is a lifesaving matter. Here, we developed a means of mapping surface hoar using remote sensing technologies. We found that surface hoar displayed heightened texture, hence the variability of brightness. Using this, we created surface hoar maps with accuracy upwards of 95 %.
Yungang Cao, Rumeng Pan, Meng Pan, Ruodan Lei, Puying Du, and Xueqin Bai
The Cryosphere, 18, 153–168, https://doi.org/10.5194/tc-18-153-2024, https://doi.org/10.5194/tc-18-153-2024, 2024
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This study built a glacial lake dataset with 15376 samples in seven types and proposed an automatic method by two-stage (the semantic segmentation network and post-processing) optimizations to detect glacial lakes. The proposed method for glacial lake extraction has achieved the best results so far, in which the F1 score and IoU reached 0.945 and 0.907, respectively. The area of the minimum glacial lake that can be entirely and correctly extracted has been raised to the 100 m2 level.
Michael Durand, Joel T. Johnson, Jack Dechow, Leung Tsang, Firoz Borah, and Edward J. Kim
The Cryosphere, 18, 139–152, https://doi.org/10.5194/tc-18-139-2024, https://doi.org/10.5194/tc-18-139-2024, 2024
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Seasonal snow accumulates each winter, storing water to release later in the year and modulating both water and energy cycles, but the amount of seasonal snow is one of the most poorly measured components of the global water cycle. Satellite concepts to monitor snow accumulation have been proposed but not selected. This paper shows that snow accumulation can be measured using radar, and that (contrary to previous studies) does not require highly accurate information about snow microstructure.
Qin Zhang and Nick Hughes
The Cryosphere, 17, 5519–5537, https://doi.org/10.5194/tc-17-5519-2023, https://doi.org/10.5194/tc-17-5519-2023, 2023
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To alleviate tedious manual image annotations for training deep learning (DL) models in floe instance segmentation, we employ a classical image processing technique to automatically label floes in images. We then apply a DL semantic method for fast and adaptive floe instance segmentation from high-resolution airborne and satellite images. A post-processing algorithm is also proposed to refine the segmentation and further to derive acceptable floe size distributions at local and global scales.
Isis Brangers, Hans-Peter Marshall, Gabrielle De Lannoy, Devon Dunmire, Christian Matzler, and Hans Lievens
EGUsphere, https://doi.org/10.5194/egusphere-2023-2927, https://doi.org/10.5194/egusphere-2023-2927, 2023
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To better understand the interactions between C-band radar waves and snow, a tower-based experiment was set up in the Idaho Rocky Mountains. The reflections were collected in the time domain to measure the backscatter profile from the various snowpack and ground surface layers. The results demonstrate that C-band radar is sensitive to seasonal patterns in snow accumulation, but that changes in microstructure, stratigraphy and snow wetness may complicate satellite-based snow depth retrievals.
Daniel Falaschi, Atanu Bhattacharya, Gregoire Guillet, Lei Huang, Owen King, Kriti Mukherjee, Philipp Rastner, Tandong Yao, and Tobias Bolch
The Cryosphere, 17, 5435–5458, https://doi.org/10.5194/tc-17-5435-2023, https://doi.org/10.5194/tc-17-5435-2023, 2023
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Because glaciers are crucial freshwater sources in the lowlands surrounding High Mountain Asia, constraining short-term glacier mass changes is essential. We investigate the potential of state-of-the-art satellite elevation data to measure glacier mass changes in two selected regions. The results demonstrate the ability of our dataset to characterize glacier changes of different magnitudes, allowing for an increase in the number of inaccessible glaciers that can be readily monitored.
Jennika Hammar, Inge Grünberg, Steven V. Kokelj, Jurjen van der Sluijs, and Julia Boike
The Cryosphere, 17, 5357–5372, https://doi.org/10.5194/tc-17-5357-2023, https://doi.org/10.5194/tc-17-5357-2023, 2023
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Roads on permafrost have significant environmental effects. This study assessed the Inuvik to Tuktoyaktuk Highway (ITH) in Canada and its impact on snow accumulation, albedo and snowmelt timing. Our findings revealed that snow accumulation increased by up to 36 m from the road, 12-day earlier snowmelt within 100 m due to reduced albedo, and altered snowmelt patterns in seemingly undisturbed areas. Remote sensing aids in understanding road impacts on permafrost.
Tao Li, Yuanlin Hu, Bin Liu, Liming Jiang, Hansheng Wang, and Xiang Shen
The Cryosphere, 17, 5299–5316, https://doi.org/10.5194/tc-17-5299-2023, https://doi.org/10.5194/tc-17-5299-2023, 2023
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Raw DEMs are often misaligned with each other due to georeferencing errors, and a co-registration process is required before DEM differencing. We present a comparative analysis of the two classical DEM co-registration and three residual correction algorithms. The experimental results show that rotation and scale biases should be considered in DEM co-registration. The new non-parametric regression technique can eliminate the complex systematic errors, which existed in the co-registration results.
Riley Culberg, Roger J. Michaelides, and Julie Z. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2023-2652, https://doi.org/10.5194/egusphere-2023-2652, 2023
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Ice slabs enhance meltwater runoff from the Greenland Ice Sheet. Therefore, it is important to understand their extent and how it changes with time. We present a method for mapping ice slabs and other refrozen ice using satellite radar imagery and apply this method to the whole ice sheet in winter 2016–2017. Our new map has significantly better spatial coverage and resolution than previous maps from airborne radar and lays the groundwork for long-term monitoring of ice slabs from space.
Oskar Herrmann, Nora Gourmelon, Thorsten Seehaus, Andreas Maier, Johannes J. Fürst, Matthias H. Braun, and Vincent Christlein
The Cryosphere, 17, 4957–4977, https://doi.org/10.5194/tc-17-4957-2023, https://doi.org/10.5194/tc-17-4957-2023, 2023
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Delineating calving fronts of marine-terminating glaciers in satellite images is a labour-intensive task. We propose a method based on deep learning that automates this task. We choose a deep learning framework that adapts to any given dataset without needing deep learning expertise. The method is evaluated on a benchmark dataset for calving-front detection and glacier zone segmentation. The framework can beat the benchmark baseline without major modifications.
Anne Braakmann-Folgmann, Andrew Shepherd, David Hogg, and Ella Redmond
The Cryosphere, 17, 4675–4690, https://doi.org/10.5194/tc-17-4675-2023, https://doi.org/10.5194/tc-17-4675-2023, 2023
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In this study, we propose a deep neural network to map the extent of giant Antarctic icebergs in Sentinel-1 images automatically. While each manual delineation requires several minutes, our U-net takes less than 0.01 s. In terms of accuracy, we find that U-net outperforms two standard segmentation techniques (Otsu, k-means) in most metrics and is more robust to challenging scenes with sea ice, coast and other icebergs. The absolute median deviation in iceberg area across 191 images is 4.1 %.
Livia Piermattei, Michael Zemp, Christian Sommer, Fanny Brun, Matthias H. Braun, Liss M. Andreassen, Joaquín M. C. Belart, Etienne Berthier, Atanu Bhattacharya, Laura Boehm Vock, Tobias Bolch, Amaury Dehecq, Inés Dussaillant, Daniel Falaschi, Caitlyn Florentine, Dana Floricioiu, Christian Ginzler, Gregoire Guillet, Romain Hugonnet, Matthias Huss, Andreas Kääb, Owen King, Christoph Klug, Friedrich Knuth, Lukas Krieger, Jeff La Frenierre, Robert McNabb, Christopher McNeil, Rainer Prinz, Louis Sass, Thorsten Seehaus, David Shean, Désirée Treichler, Anja Wendt, and Ruitang Yang
EGUsphere, https://doi.org/10.5194/egusphere-2023-2309, https://doi.org/10.5194/egusphere-2023-2309, 2023
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Satellites have made it possible to observe glacier elevation changes from all around the world. In the present study, we compared the results produced from two different types of satellite data between different research groups and against validation measurements from aeroplanes. We found a large spread between individual results but showed that the group ensemble can be used to reliably estimate glacier elevation changes and related errors from satellite data.
Jurjen van der Sluijs, Steven V. Kokelj, and Jon F. Tunnicliffe
The Cryosphere, 17, 4511–4533, https://doi.org/10.5194/tc-17-4511-2023, https://doi.org/10.5194/tc-17-4511-2023, 2023
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There is an urgent need to obtain size and erosion estimates of climate-driven landslides, such as retrogressive thaw slumps. We evaluated surface interpolation techniques to estimate slump erosional volumes and developed a new inventory method by which the size and activity of these landslides are tracked through time. Models between slump area and volume reveal non-linear intensification, whereby model coefficients improve our understanding of how permafrost landscapes may evolve over time.
Trystan Surawy-Stepney, Anna E. Hogg, Stephen L. Cornford, and David C. Hogg
The Cryosphere, 17, 4421–4445, https://doi.org/10.5194/tc-17-4421-2023, https://doi.org/10.5194/tc-17-4421-2023, 2023
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The presence of crevasses in Antarctica influences how the ice sheet behaves. It is important, therefore, to collect data on the spatial distribution of crevasses and how they are changing. We present a method of mapping crevasses from satellite radar imagery and apply it to 7.5 years of images, covering Antarctica's floating and grounded ice. We develop a method of measuring change in the density of crevasses and quantify increased fracturing in important parts of the West Antarctic Ice Sheet.
Anssi Rauhala, Leo-Juhani Meriö, Anton Kuzmin, Pasi Korpelainen, Pertti Ala-aho, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4343–4362, https://doi.org/10.5194/tc-17-4343-2023, https://doi.org/10.5194/tc-17-4343-2023, 2023
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Snow conditions in the Northern Hemisphere are rapidly changing, and information on snow depth is important for decision-making. We present snow depth measurements using different drones throughout the winter at a subarctic site. Generally, all drones produced good estimates of snow depth in open areas. However, differences were observed in the accuracies produced by the different drones, and a reduction in accuracy was observed when moving from an open mire area to forest-covered areas.
Leo-Juhani Meriö, Anssi Rauhala, Pertti Ala-aho, Anton Kuzmin, Pasi Korpelainen, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4363–4380, https://doi.org/10.5194/tc-17-4363-2023, https://doi.org/10.5194/tc-17-4363-2023, 2023
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Information on seasonal snow cover is essential in understanding snow processes and operational forecasting. We study the spatiotemporal variability in snow depth and snow processes in a subarctic, boreal landscape using drones. We identified multiple theoretically known snow processes and interactions between snow and vegetation. The results highlight the applicability of the drones to be used for a detailed study of snow depth in multiple land cover types and snow–vegetation interactions.
Kirsty Wivell, Stuart Fox, Melody Sandells, Chawn Harlow, Richard Essery, and Nick Rutter
The Cryosphere, 17, 4325–4341, https://doi.org/10.5194/tc-17-4325-2023, https://doi.org/10.5194/tc-17-4325-2023, 2023
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Satellite microwave observations improve weather forecasts, but to use these observations in the Arctic, snow emission must be known. This study uses airborne and in situ snow observations to validate emissivity simulations for two- and three-layer snowpacks at key frequencies for weather prediction. We assess the impact of thickness, grain size and density in key snow layers, which will help inform development of physical snow models that provide snow profile input to emissivity simulations.
Konstantin Muzalevskiy, Zdenek Ruzicka, Alexandre Roy, Michael Loranty, and Alexander Vasiliev
The Cryosphere, 17, 4155–4164, https://doi.org/10.5194/tc-17-4155-2023, https://doi.org/10.5194/tc-17-4155-2023, 2023
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A new all-weather method for determining the frozen/thawed (FT) state of soils in the Arctic region based on satellite data was proposed. The method is based on multifrequency measurement of brightness temperatures by the SMAP and GCOM-W1/AMSR2 satellites. The created method was tested at sites in Canada, Finland, Russia, and the USA, based on climatic weather station data. The proposed method identifies the FT state of Arctic soils with better accuracy than existing methods.
Alexander Mchedlishvili, Christof Lüpkes, Alek Petty, Michel Tsamados, and Gunnar Spreen
The Cryosphere, 17, 4103–4131, https://doi.org/10.5194/tc-17-4103-2023, https://doi.org/10.5194/tc-17-4103-2023, 2023
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In this study we looked at sea ice–atmosphere drag coefficients, quantities that help with characterizing the friction between the atmosphere and sea ice, and vice versa. Using ICESat-2, a laser altimeter that measures elevation differences by timing how long it takes for photons it sends out to return to itself, we could map the roughness, i.e., how uneven the surface is. From roughness we then estimate drag force, the frictional force between sea ice and the atmosphere, across the Arctic.
Whyjay Zheng, Shashank Bhushan, Maximillian Van Wyk De Vries, William Kochtitzky, David Shean, Luke Copland, Christine Dow, Renette Jones-Ivey, and Fernando Pérez
The Cryosphere, 17, 4063–4078, https://doi.org/10.5194/tc-17-4063-2023, https://doi.org/10.5194/tc-17-4063-2023, 2023
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We design and propose a method that can evaluate the quality of glacier velocity maps. The method includes two numbers that we can calculate for each velocity map. Based on statistics and ice flow physics, velocity maps with numbers close to the recommended values are considered to have good quality. We test the method using the data from Kaskawulsh Glacier, Canada, and release an open-sourced software tool called GLAcier Feature Tracking testkit (GLAFT) to help users assess their velocity maps.
Eunsang Cho, Carrie M. Vuyovich, Sujay V. Kumar, Melissa L. Wrzesien, and Rhae Sung Kim
The Cryosphere, 17, 3915–3931, https://doi.org/10.5194/tc-17-3915-2023, https://doi.org/10.5194/tc-17-3915-2023, 2023
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As a future snow mission concept, active microwave sensors have the potential to measure snow water equivalent (SWE) in deep snowpack and forested environments. We used a modeling and data assimilation approach (a so-called observing system simulation experiment) to quantify the usefulness of active microwave-based SWE retrievals over western Colorado. We found that active microwave sensors with a mature retrieval algorithm can improve SWE simulations by about 20 % in the mountainous domain.
Philip Rostosky and Gunnar Spreen
The Cryosphere, 17, 3867–3881, https://doi.org/10.5194/tc-17-3867-2023, https://doi.org/10.5194/tc-17-3867-2023, 2023
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During winter, storms entering the Arctic region can bring warm air into the cold environment. Strong increases in air temperature modify the characteristics of the Arctic snow and ice cover. The Arctic sea ice cover can be monitored by satellites observing the natural emission of the Earth's surface. In this study, we show that during warm air intrusions the change in the snow characteristics influences the satellite-derived sea ice cover, leading to a false reduction of the estimated ice area.
Ellen M. Buckley, Sinéad L. Farrell, Ute C. Herzfeld, Melinda A. Webster, Thomas Trantow, Oliwia N. Baney, Kyle A. Duncan, Huilin Han, and Matthew Lawson
The Cryosphere, 17, 3695–3719, https://doi.org/10.5194/tc-17-3695-2023, https://doi.org/10.5194/tc-17-3695-2023, 2023
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In this study, we use satellite observations to investigate the evolution of melt ponds on the Arctic sea ice surface. We derive melt pond depth from ICESat-2 measurements of the pond surface and bathymetry and melt pond fraction (MPF) from the classification of Sentinel-2 imagery. MPF increases to a peak of 16 % in late June and then decreases, while depth increases steadily. This work demonstrates the ability to track evolving melt conditions in three dimensions throughout the summer.
Michael Studinger, Benjamin E. Smith, Nathan Kurtz, Alek Petty, Tyler Sutterley, and Rachel Tilling
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-126, https://doi.org/10.5194/tc-2023-126, 2023
Revised manuscript accepted for TC
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We use green lidar data and natural color imagery over sea ice to quantify elevation biases potentially impacting estimates of change in ice thickness of the polar regions. We complement our analysis using a model of scattering of light in snow and ice that predicts the shape of lidar waveforms reflecting from snow and ice surfaces based on the shape of the transmitted pulse. We find that biased elevations exist in airborne and spaceborne data products from green lidars.
Monika Pfau, Georg Veh, and Wolfgang Schwanghart
The Cryosphere, 17, 3535–3551, https://doi.org/10.5194/tc-17-3535-2023, https://doi.org/10.5194/tc-17-3535-2023, 2023
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Cast shadows have been a recurring problem in remote sensing of glaciers. We show that the length of shadows from surrounding mountains can be used to detect gains or losses in glacier elevation.
Enze Zhang, Ginny Catania, and Daniel T. Trugman
The Cryosphere, 17, 3485–3503, https://doi.org/10.5194/tc-17-3485-2023, https://doi.org/10.5194/tc-17-3485-2023, 2023
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Glacier termini are essential for studying why glaciers retreat, but they need to be mapped automatically due to the volume of satellite images. Existing automated mapping methods have been limited due to limited automation, lack of quality control, and inadequacy in highly diverse terminus environments. We design a fully automated, deep-learning-based method to produce termini with quality control. We produced 278 239 termini in Greenland and provided a way to deliver new termini regularly.
Guanyu Li, Mingyang Lv, Duncan J. Quincey, Liam S. Taylor, Xinwu Li, Shiyong Yan, Yidan Sun, and Huadong Guo
The Cryosphere, 17, 2891–2907, https://doi.org/10.5194/tc-17-2891-2023, https://doi.org/10.5194/tc-17-2891-2023, 2023
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Kyagar Glacier in the Karakoram is well known for its surge history and its frequent blocking of the downstream valley, leading to a series of high-magnitude glacial lake outburst floods. Using it as a test bed, we develop a new approach for quantifying surge behaviour using successive digital elevation models. This method could be applied to other surge studies. Combined with the results from optical satellite images, we also reconstruct the surge process in unprecedented detail.
Yujia Qiu, Xiao-Ming Li, and Huadong Guo
The Cryosphere, 17, 2829–2849, https://doi.org/10.5194/tc-17-2829-2023, https://doi.org/10.5194/tc-17-2829-2023, 2023
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Spaceborne thermal infrared sensors with kilometer-scale resolution cannot support adequate parameterization of Arctic leads. For the first time, we applied the 30 m resolution data from the Thermal Infrared Spectrometer (TIS) on the emerging SDGSAT-1 to detect Arctic leads. Validation with Sentinel-2 data shows high accuracy for the three TIS bands. Compared to MODIS, the TIS presents more narrow leads, demonstrating its great potential for observing previously unresolvable Arctic leads.
César Deschamps-Berger, Simon Gascoin, David Shean, Hannah Besso, Ambroise Guiot, and Juan Ignacio López-Moreno
The Cryosphere, 17, 2779–2792, https://doi.org/10.5194/tc-17-2779-2023, https://doi.org/10.5194/tc-17-2779-2023, 2023
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The estimation of the snow depth in mountains is hard, despite the importance of the snowpack for human societies and ecosystems. We measured the snow depth in mountains by comparing the elevation of points measured with snow from the high-precision altimetric satellite ICESat-2 to the elevation without snow from various sources. Snow depths derived only from ICESat-2 were too sparse, but using external airborne/satellite products results in spatially richer and sufficiently precise snow depths.
Edward H. Bair, Jeff Dozier, Karl Rittger, Timbo Stillinger, William Kleiber, and Robert E. Davis
The Cryosphere, 17, 2629–2643, https://doi.org/10.5194/tc-17-2629-2023, https://doi.org/10.5194/tc-17-2629-2023, 2023
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To test the title question, three snow cover products were used in a snow model. Contrary to previous work, higher-spatial-resolution snow cover products only improved the model accuracy marginally. Conclusions are as follows: (1) snow cover and albedo from moderate-resolution sensors continue to provide accurate forcings and (2) finer spatial and temporal resolutions are the future for Earth observations, but existing moderate-resolution sensors still offer value.
Valentina Premier, Carlo Marin, Giacomo Bertoldi, Riccardo Barella, Claudia Notarnicola, and Lorenzo Bruzzone
The Cryosphere, 17, 2387–2407, https://doi.org/10.5194/tc-17-2387-2023, https://doi.org/10.5194/tc-17-2387-2023, 2023
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The large amount of information regularly acquired by satellites can provide important information about SWE. We explore the use of multi-source satellite data, in situ observations, and a degree-day model to reconstruct daily SWE at 25 m. The results show spatial patterns that are consistent with the topographical features as well as with a reference product. Being able to also reproduce interannual variability, the method has great potential for hydrological and ecological applications.
Christian Sommer, Johannes J. Fürst, Matthias Huss, and Matthias H. Braun
The Cryosphere, 17, 2285–2303, https://doi.org/10.5194/tc-17-2285-2023, https://doi.org/10.5194/tc-17-2285-2023, 2023
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Knowledge on the volume of glaciers is important to project future runoff. Here, we present a novel approach to reconstruct the regional ice thickness distribution from easily available remote-sensing data. We show that past ice thickness, derived from spaceborne glacier area and elevation datasets, can constrain the estimated ice thickness. Based on the unique glaciological database of the European Alps, the approach will be most beneficial in regions without direct thickness measurements.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023, https://doi.org/10.5194/tc-17-2211-2023, 2023
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We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
wind-redistributed snow needs to be accounted for to improve snow depth estimates on sea ice from satellite radars.
Jack Tarricone, Ryan W. Webb, Hans-Peter Marshall, Anne W. Nolin, and Franz J. Meyer
The Cryosphere, 17, 1997–2019, https://doi.org/10.5194/tc-17-1997-2023, https://doi.org/10.5194/tc-17-1997-2023, 2023
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Mountain snowmelt provides water for billions of people across the globe. Despite its importance, we cannot currently measure the amount of water in mountain snowpacks from satellites. In this research, we test the ability of an experimental snow remote sensing technique from an airplane in preparation for the same sensor being launched on a future NASA satellite. We found that the method worked better than expected for estimating important snowpack properties.
Maria Shaposhnikova, Claude Duguay, and Pascale Roy-Léveillée
The Cryosphere, 17, 1697–1721, https://doi.org/10.5194/tc-17-1697-2023, https://doi.org/10.5194/tc-17-1697-2023, 2023
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We explore lake ice in the Old Crow Flats, Yukon, Canada, using a novel approach that employs radar imagery and deep learning. Results indicate an 11 % increase in the fraction of lake ice that grounds between 1992/1993 and 2020/2021. We believe this is caused by widespread lake drainage and fluctuations in water level and snow depth. This transition is likely to have implications for permafrost beneath the lakes, with a potential impact on methane ebullition and the regional carbon budget.
Dyre Oliver Dammann, Mark A. Johnson, Andrew R. Mahoney, and Emily R. Fedders
The Cryosphere, 17, 1609–1622, https://doi.org/10.5194/tc-17-1609-2023, https://doi.org/10.5194/tc-17-1609-2023, 2023
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We investigate the GAMMA Portable Radar Interferometer (GPRI) as a tool for evaluating flexural–gravity waves in sea ice in near real time. With a GPRI mounted on grounded ice near Utqiaġvik, Alaska, we identify 20–50 s infragravity waves in landfast ice with ~1 mm amplitude during 23–24 April 2021. Observed wave speed and periods compare well with modeled wave propagation and on-ice accelerometers, confirming the ability to track propagation and properties of waves over hundreds of meters.
Ugo Nanni, Dirk Scherler, Francois Ayoub, Romain Millan, Frederic Herman, and Jean-Philippe Avouac
The Cryosphere, 17, 1567–1583, https://doi.org/10.5194/tc-17-1567-2023, https://doi.org/10.5194/tc-17-1567-2023, 2023
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Surface melt is a major factor driving glacier movement. Using satellite images, we have tracked the movements of 38 glaciers in the Pamirs over 7 years, capturing their responses to rapid meteorological changes with unprecedented resolution. We show that in spring, glacier accelerations propagate upglacier, while in autumn, they propagate downglacier – all resulting from changes in meltwater input. This provides critical insights into the interplay between surface melt and glacier movement.
Sara E. Darychuk, Joseph M. Shea, Brian Menounos, Anna Chesnokova, Georg Jost, and Frank Weber
The Cryosphere, 17, 1457–1473, https://doi.org/10.5194/tc-17-1457-2023, https://doi.org/10.5194/tc-17-1457-2023, 2023
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We use synthetic-aperture radar (SAR) and optical observations to map snowmelt timing and duration on the watershed scale. We found that Sentinel-1 SAR time series can be used to approximate snowmelt onset over diverse terrain and land cover types, and we present a low-cost workflow for SAR processing over large, mountainous regions. Our approach provides spatially distributed observations of the snowpack necessary for model calibration and can be used to monitor snowmelt in ungauged basins.
Cited articles
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Short summary
Snow cover explained most of the spring surface albedo changes in the Northern Hemisphere in the years 2000−2012. However, there are vast areas where albedo changed up to ±0.2 under full snow-covered conditions. We found that if in these areas, the mean monthly air temperature exceeds a value between -15°C and -10°C, depending on the region, albedo decreases with an increase of the temperature. The complexity of processes involved in surface albedo changes is discussed.
Snow cover explained most of the spring surface albedo changes in the Northern Hemisphere in the...
