Articles | Volume 15, issue 7
https://doi.org/10.5194/tc-15-3035-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-15-3035-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Jul 2021
Research article |
| 02 Jul 2021
| 02 Jul 2021
Deriving Arctic 2 m air temperatures over snow and ice from satellite surface temperature measurements
Pia Nielsen-Englyst
CORRESPONDING AUTHOR
1DTU-Space, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
Research and Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
Jacob L. Høyer
Research and Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
Kristine S. Madsen
Research and Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
Rasmus T. Tonboe
Research and Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
Gorm Dybkjær
Research and Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
Sotirios Skarpalezos
Research and Development, Danish Meteorological Institute (DMI), 2100 Copenhagen Ø, Denmark
Related authors
Alexander Hayward, Nishka Dasgupta, Ronan McAdam, Mark R. Payne, Roshin P. Raj, Giulia Bonino, Sourav Chatterjee, Vincent Combes, Dimitra Denaxa, Francesco De Rovere, Pia Englyst, Veera Haapaniemi, Paul Hargous, Jacob Høyer, K. Ajith Joseph, Beatriz Lopes, Ana Oliveira, João Paixão, Fabiola Silva, Saradhy Surendran, Artemis Zegna-Rata, and Steffen Olsen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-590, https://doi.org/10.5194/essd-2025-590, 2025
Preprint under review for ESSD
Short summary
Short summary
We present a global marine heatwave dataset (1982–2024) based on satellite sea surface temperature. The dataset applies multiple definitions in parallel, varying baselines, thresholds, detrending, and event durations. It enables consistent comparisons of marine heatwave characterisation across methods and supports climate monitoring, model evaluation, and ecological impact studies.
Ioanna Karagali, Magnus Barfod Suhr, Ruth Mottram, Pia Nielsen-Englyst, Gorm Dybkjær, Darren Ghent, and Jacob L. Høyer
The Cryosphere, 16, 3703–3721, https://doi.org/10.5194/tc-16-3703-2022, https://doi.org/10.5194/tc-16-3703-2022, 2022
Short summary
Short summary
Ice surface temperature (IST) products were used to develop the first multi-sensor, gap-free Level 4 (L4) IST product of the Greenland Ice Sheet (GIS) for 2012, when a significant melt event occurred. For the melt season, mean IST was −15 to −1 °C, and almost the entire GIS experienced at least 1 to 5 melt days. Inclusion of the L4 IST to a surface mass budget (SMB) model improved simulated surface temperatures during the key onset of the melt season, where biases are typically large.
Emil Haaber Tellefsen, Rasmus Tage Tonboe, and Wiebke Margitta Kolbe
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-660, https://doi.org/10.5194/essd-2025-660, 2025
Preprint under review for ESSD
Short summary
Short summary
The Electrically Scanning Microwave Radiometer, the first spaceborne microwave instrument to map global sea ice, was launched aboard the NIMBUS 5 satellite in December 1972 and remained operational until May 1977. As part of the European Space Agency’s Climate Change Initiative, this dataset has been reprocessed and validated to provide a nearly complete global record of sea ice concentration, with only a few data gaps in 1973 and 1975.
Alexander Hayward, Nishka Dasgupta, Ronan McAdam, Mark R. Payne, Roshin P. Raj, Giulia Bonino, Sourav Chatterjee, Vincent Combes, Dimitra Denaxa, Francesco De Rovere, Pia Englyst, Veera Haapaniemi, Paul Hargous, Jacob Høyer, K. Ajith Joseph, Beatriz Lopes, Ana Oliveira, João Paixão, Fabiola Silva, Saradhy Surendran, Artemis Zegna-Rata, and Steffen Olsen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-590, https://doi.org/10.5194/essd-2025-590, 2025
Preprint under review for ESSD
Short summary
Short summary
We present a global marine heatwave dataset (1982–2024) based on satellite sea surface temperature. The dataset applies multiple definitions in parallel, varying baselines, thresholds, detrending, and event durations. It enables consistent comparisons of marine heatwave characterisation across methods and supports climate monitoring, model evaluation, and ecological impact studies.
Guisella Gacitúa, Jacob Lorentsen Høyer, Sten Schmidl Søbjærg, Hoyeon Shi, Sotirios Skarpalezos, Ioanna Karagali, Emy Alerskans, and Craig Donlon
Geosci. Instrum. Method. Data Syst., 13, 373–391, https://doi.org/10.5194/gi-13-373-2024, https://doi.org/10.5194/gi-13-373-2024, 2024
Short summary
Short summary
In spring 2021, a study compared sea surface temperature (SST) measurements from thermal infrared (IR) and passive microwave (PMW) radiometers on a ferry between Denmark and Iceland. The goal was to reduce atmospheric effects and directly compare IR and PMW measurements. A method was developed to convert PMW data to match IR data, with uncertainties analysed in the process. The findings provide insights to improve SST inter-comparisons and enhance the synergy between IR and PMW observations.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Elin Andrée, Jian Su, Morten Andreas Dahl Larsen, Martin Drews, Martin Stendel, and Kristine Skovgaard Madsen
Nat. Hazards Earth Syst. Sci., 23, 1817–1834, https://doi.org/10.5194/nhess-23-1817-2023, https://doi.org/10.5194/nhess-23-1817-2023, 2023
Short summary
Short summary
When natural processes interact, they may compound each other. The combined effect can amplify extreme sea levels, such as when a storm occurs at a time when the water level is already higher than usual. We used numerical modelling of a record-breaking storm surge in 1872 to show that other prior sea-level conditions could have further worsened the outcome. Our research highlights the need to consider the physical context of extreme sea levels in measures to reduce coastal flood risk.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Ruzica Dadic, Philip Rostosky, Michael Gallagher, Robbie Mallett, Andrew Barrett, Stefan Hendricks, Rasmus Tonboe, Michelle McCrystall, Mark Serreze, Linda Thielke, Gunnar Spreen, Thomas Newman, John Yackel, Robert Ricker, Michel Tsamados, Amy Macfarlane, Henna-Reetta Hannula, and Martin Schneebeli
The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022, https://doi.org/10.5194/tc-16-4223-2022, 2022
Short summary
Short summary
Impacts of rain on snow (ROS) on satellite-retrieved sea ice variables remain to be fully understood. This study evaluates the impacts of ROS over sea ice on active and passive microwave data collected during the 2019–20 MOSAiC expedition. Rainfall and subsequent refreezing of the snowpack significantly altered emitted and backscattered radar energy, laying important groundwork for understanding their impacts on operational satellite retrievals of various sea ice geophysical variables.
Ioanna Karagali, Magnus Barfod Suhr, Ruth Mottram, Pia Nielsen-Englyst, Gorm Dybkjær, Darren Ghent, and Jacob L. Høyer
The Cryosphere, 16, 3703–3721, https://doi.org/10.5194/tc-16-3703-2022, https://doi.org/10.5194/tc-16-3703-2022, 2022
Short summary
Short summary
Ice surface temperature (IST) products were used to develop the first multi-sensor, gap-free Level 4 (L4) IST product of the Greenland Ice Sheet (GIS) for 2012, when a significant melt event occurred. For the melt season, mean IST was −15 to −1 °C, and almost the entire GIS experienced at least 1 to 5 melt days. Inclusion of the L4 IST to a surface mass budget (SMB) model improved simulated surface temperatures during the key onset of the melt season, where biases are typically large.
Stefan Kern, Thomas Lavergne, Leif Toudal Pedersen, Rasmus Tage Tonboe, Louisa Bell, Maybritt Meyer, and Luise Zeigermann
The Cryosphere, 16, 349–378, https://doi.org/10.5194/tc-16-349-2022, https://doi.org/10.5194/tc-16-349-2022, 2022
Short summary
Short summary
High-resolution clear-sky optical satellite imagery has rarely been used to evaluate satellite passive microwave sea-ice concentration products beyond case-study level. By comparing 10 such products with sea-ice concentration estimated from > 350 such optical images in both hemispheres, we expand results of earlier evaluation studies for these products. Results stress the need to look beyond precision and accuracy and to discuss the evaluation data’s quality and filters applied in the products.
Ralf Weisse, Inga Dailidienė, Birgit Hünicke, Kimmo Kahma, Kristine Madsen, Anders Omstedt, Kevin Parnell, Tilo Schöne, Tarmo Soomere, Wenyan Zhang, and Eduardo Zorita
Earth Syst. Dynam., 12, 871–898, https://doi.org/10.5194/esd-12-871-2021, https://doi.org/10.5194/esd-12-871-2021, 2021
Short summary
Short summary
The study is part of the thematic Baltic Earth Assessment Reports – a series of review papers summarizing the knowledge around major Baltic Earth science topics. It concentrates on sea level dynamics and coastal erosion (its variability and change). Many of the driving processes are relevant in the Baltic Sea. Contributions vary over short distances and across timescales. Progress and research gaps are described in both understanding details in the region and in extending general concepts.
Rasmus T. Tonboe, Vishnu Nandan, John Yackel, Stefan Kern, Leif Toudal Pedersen, and Julienne Stroeve
The Cryosphere, 15, 1811–1822, https://doi.org/10.5194/tc-15-1811-2021, https://doi.org/10.5194/tc-15-1811-2021, 2021
Short summary
Short summary
A relationship between the Ku-band radar scattering horizon and snow depth is found using a radar scattering model. This relationship has implications for (1) the use of snow climatology in the conversion of satellite radar freeboard into sea ice thickness and (2) the impact of variability in measured snow depth on the derived ice thickness. For both 1 and 2, the impact of using a snow climatology versus the actual snow depth is relatively small.
Cited articles
Abermann, J., Hansen, B., Lund, M., Wacker, S., Karami, M., and Cappelen, J.: Hotspots and key periods of Greenland climate change during the past six decades, Ambio, 46, 3–11, https://doi.org/10.1007/s13280-016-0861-y, 2017.
Ackerman, T. P. and Stokes, G. M.: The Atmospheric Radiation Measurement Program, Phys. Today, 56, 38–44, https://doi.org/10.1063/1.1554135, 2003.
Adolph, A. C., Albert, M. R., and Hall, D. K.: Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures, The Cryosphere, 12, 907–920, https://doi.org/10.5194/tc-12-907-2018, 2018.
Ahlstrøm, A., van As, D., Citterio, M., Andersen, S., Fausto, R., Andersen, M., Forsberg, R., Stenseng, L., Lintz Christensen, E., and Kristensen, S. S.: A new Programme for Monitoring the Mass Loss of the Greenland Ice Sheet, Geol. Surv. Den. Greenl., 15, 61–64, 2008.
Amante, C. and Eakins, B. W.: ETOPO1 Global Relief Model converted to PanMap layer format, PANGAEA, https://doi.org/10.1594/PANGAEA.769615, 2009.
Atmospheric Radiation Measurement (ARM) Archive: ARM-standard Meteorological Instrumentation at Surface, https://doi.org/10.5439/1025220, 2018.
Batrak, Y. and Müller, M.: On the warm bias in atmospheric reanalyses induced by the missing snow over Arctic sea-ice, Nat. Commun., 10, 4170, https://doi.org/10.1038/s41467-019-11975-3, 2019.
Beesley, J. A. and Moritz, R. E.: Toward an explanation of the annual cycle of cloudiness over the Arctic Ocean, J. Climate, 12, 395–415, 1999.
Box, J. E., Colgan, W. T., Christensen, T. R., Schmidt, N. M., Lund, M., Parmentier, F.-J. W., Brown, R., Bhatt, U. S., Euskirchen, E. S., Romanovsky, V. E., Walsh, J. E., Overland, J. E., Wang, M., Corell, R. W., Meier, W. N., Wouters, B., Mernild, S., Mård, J., Pawlak, J., and Olsen, M. S.: Key indicators of Arctic climate change: 1971–2017, Environ. Res. Lett., 14, 045010, https://doi.org/10.1088/1748-9326/aafc1b, 2019.
Brümmer, B., Müller, G., Haller, M., Kriegsmann, A., Offermann, M., and Wetzel, C.: DAMOCLES 2007–2008 – Hamburg Arctic Ocean Buoy Drift Experiment: meteorological measurements of 16 autonomous drifting ice buoys, World Data Center for Climate (WDCC) at DKRZ, https://doi.org/10.1594/wdcc/uni_HH_MI_DAMOCLES2007, 2011a.
Brümmer, B., Müller, G., Lammert-Stockschläder, A., Jahnke-Bornemann, A., and Wetzel, C.: FRAMZY 2007 – Third Field Experiment on Fram Strait Cyclones and their Impact on Sea Ice: meteorological measurements of the research aircraft Falcon, 16 autonomous ice buoys and 13 autonomous water buoys, World Data Center for Climate (WDCC) at DKRZ, https://doi.org/10.1594/WDCC/UNI_HH_MI_FRAMZY2007, 2011b.
Brümmer, B., Müller, G., and Wetzel, C.: FRAMZY 2008 – Fourth Field Experiment on Fram Strait Cyclones and their Impact on Sea Ice: meteorological measurements of 7 autonomous ice buoys, World Data Center for Climate (WDCC) at DKRZ, https://doi.org/10.1594/WDCC/UNI_HH_MI_FRAMZY2008, 2011c.
Brümmer, B., Launiainen, J., Müller, G., Kirchgaessner, A., and Wetzel, C.: ACSYS 2003 – Arctic Atmospheric Boundary Layer and Sea Ice Interaction Study north of Spitsbergen: meteorological measurements of the research aircraft Falcon, 11 autonomous ice buoys and radiosoundings at the research vessels Aranda and Polarstern, World Data Center for Climate (WDCC) at DKRZ, https://doi.org/10.1594/WDCC/UNI_HH_MI_ACSYS2003, 2012a.
Brümmer, B., Launiainen, J., Müller, G., and Wetzel, C.: FRAMZY 2002 – Second Field Experiment on Fram Strait Cyclones and their Impact on Sea Ice: meteorological measurements of the research aircraft Falcon, 15 autonomous ice buoys and radiosoundings at the research vessel Aranda, World Data Center for Climate (WDCC) at DKRZ, https://doi.org/10.1594/WDCC/UNI_HH_MI_FRAMZY2002, 2012b.
Bulgin, C. E., Embury, O., and Merchant, C. J.: Sampling uncertainty in gridded sea surface temperature products and Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) data, Remote Sens. Environ., 177, 287–294, https://doi.org/10.1016/j.rse.2016.02.021, 2016.
Cappelen, J. (Ed.): Greenland – DMI Historical Climate Data Collection 1768-2020., DMI Rep. 21–02, Copenhagen, Denmark, Danish Meteorological Institute, Copenhagen, Denmark, 2021.
Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T., Friedlingstein, P., Gao, X., Gutowski, W. J., Johns, T., Krinner, G., Shongwe, M., Tebaldi, C., Weaver, A. J., and Wehner, M.: Long-term Climate Change: Projections, Commitments and Irreversibility, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1029–1136, https://doi.org/10.1017/CBO9781107415324.024, 2013.
Cowtan, K. and Way, R.: Update to “Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends”, Reconciling global temperature series, https://doi.org/10.13140/RG.2.1.4334.8564, 2014.
Curry, J. A., Schramm, J. L., Rossow, W. B., and Randall, D.: Overview of Arctic Cloud and Radiation Characteristics, J. Climate, 9, 1731–1764, https://doi.org/10.1175/1520-0442(1996)009<1731:OOACAR>2.0.CO;2, 1996.
Davy, R. and Outten, S.: The Arctic Surface Climate in CMIP6: Status and Developments since CMIP5, J. Climate, 33, 8047–8068, https://doi.org/10.1175/JCLI-D-19-0990.1, 2020.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Delhasse, A., Kittel, C., Amory, C., Hofer, S., van As, D., S. Fausto, R., and Fettweis, X.: Brief communication: Evaluation of the near-surface climate in ERA5 over the Greenland Ice Sheet, The Cryosphere, 14, 957–965, https://doi.org/10.5194/tc-14-957-2020, 2020.
DuVivier, A. K. and Cassano, J. J.: Evaluation of WRF Model Resolution on Simulated Mesoscale Winds and Surface Fluxes near Greenland, Mon. Weather Rev., 141, 941–963, https://doi.org/10.1175/MWR-D-12-00091.1, 2013.
Dybbroe, A., Karlsson, K.-G., and Thoss, A.: NWCSAF AVHRR Cloud Detection and Analysis Using Dynamic Thresholds and Radiative Transfer Modeling. Part I: Algorithm Description, J. Appl. Meteorol., 44, 39–54, https://doi.org/10.1175/JAM-2188.1, 2005a.
Dybbroe, A., Karlsson, K.-G., and Thoss, A.: NWCSAF AVHRR Cloud Detection and Analysis Using Dynamic Thresholds and Radiative Transfer Modeling. Part II: Tuning and Validation, J. Appl. Meteorol., 44, 55–71, https://doi.org/10.1175/JAM-2189.1, 2005b.
Dybkjær, G., Tonboe, R., and Høyer, J. L.: Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data, Ocean Sci., 8, 959–970, https://doi.org/10.5194/os-8-959-2012, 2012.
Dybkjær, G., Høyer, J. L., Tonboe, R., and Olsen, S. M.: Report on the documentation and description of the new Arctic Ocean dataset combining SST and IST, NACLIM Deliverable, D32.28, 2014.
Dybkjær, G., Eastwood, S., Borg, A. L., Høyer, J. L., and Tonboe, R.: Algorithm theoretical basis document (ATBD) for the OSI SAF Sea and Sea Ice Surface Temperature L2 processing chain, OSI205a and b, http://osisaf.met.no/docs/osisaf_cdop2_ss2_pum_ice-conc_v1p4.pdf, last access: 19 February 2018.
Fausto, R. S. and van As, D.: Programme for monitoring of the Greenland ice sheet (PROMICE): Automatic weather station data, Version: v03, Dataset published via Geological Survey of Denmark and Greenland, https://doi.org/10.22008/promice/data/aw, 2019.
Ghent, D. J., Corlett, G. K., Göttsche, F.-M., and Remedios, J. J.: Global Land Surface Temperature From the Along-Track Scanning Radiometers: Global LST from the ATSRs, J. Geophys. Res.-Atmos., 122, 12167–12193, https://doi.org/10.1002/2017JD027161, 2017.
GHRSST Science Team: The Recommended GHRSST Data Specification (GDS) 2.0, document revision 4, available from the GHRSST International Project Office, 2011, 123 pp., 2010.
Good, E.: Daily minimum and maximum surface air temperatures from geostationary satellite data: Satellite min and max air temperatures, J. Geophys. Res.-Atmos., 120, 2306–2324, https://doi.org/10.1002/2014JD022438, 2015.
Good, E. J., Ghent, D. J., Bulgin, C. E., and Remedios, J. J.: A spatiotemporal analysis of the relationship between near-surface air temperature and satellite land surface temperatures using 17 years of data from the ATSR series, J. Geophys. Res.-Atmos., 122, 9185–9210, https://doi.org/10.1002/2017JD026880, 2017.
Graham, R. M., Cohen, L., Ritzhaupt, N., Segger, B., Graversen, R. G., Rinke, A., Walden, V. P., Granskog, M. A., and Hudson, S. R.: Evaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early Summer, J. Climate, 32, 4121–4143, https://doi.org/10.1175/JCLI-D-18-0643.1, 2019.
Graversen, R. G., Mauritsen, T., Tjernström, M., Källén, E., and Svensson, G.: Vertical structure of recent Arctic warming, Nature, 451, 53–56, https://doi.org/10.1038/nature06502, 2008.
Griggs, J. A. and Bamber, J. L.: Assessment of Cloud Cover Characteristics in Satellite Datasets and Reanalysis Products for Greenland, J. Climate, 21, 1837–1849, https://doi.org/10.1175/2007JCLI1570.1, 2008.
Grisogono, B., Kraljević, L., and Jeričević, A.: The low-level katabatic jet height versus Monin-Obukhov height, Q. J. Roy. Meteor. Soc., 133, 2133–2136, https://doi.org/10.1002/qj.190, 2007.
Hall, D., Box, J., Casey, K., Hook, S., Shuman, C., and Steffen, K.: Comparison of satellite-derived and in-situ observations of ice and snow surface temperatures over Greenland, Remote Sens. Environ., 112, 3739–3749, https://doi.org/10.1016/j.rse.2008.05.007, 2008.
Hall, D. K., Key, J. R., Case, K. A., Riggs, G. A., and Cavalieri, D. J.: Sea ice surface temperature product from MODIS, IEEE T. Geosci. Remote, 42, 1076–1087, https://doi.org/10.1109/TGRS.2004.825587, 2004.
Hall, D. K., Comiso, J. C., DiGirolamo, N. E., Shuman, C. A., Key, J. R., and Koenig, L. S.: A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet, J. Climate, 25, 4785–4798, https://doi.org/10.1175/JCLI-D-11-00365.1, 2012.
Hanna, E., Cappelen, J., Fettweis, X., Mernild, S. H., Mote, T. L., Mottram, R., Steffen, K., Ballinger, T. J., and Hall, R. J.: Greenland surface air temperature changes from 1981 to 2019 and implications for ice-sheet melt and mass-balance change, Int. J. Climatol., 41, E1336–E1352, https://doi.org/10.1002/joc.6771, 2021.
Hansen, J., Ruedy, R., Sato, M., and Lo, K.: Global surface temperature change, Rev. Geophys., 48, RG4004, https://doi.org/10.1029/2010RG000345, 2010.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Holland, M. M. and Bitz, C. M.: Polar amplification of climate change in coupled models, Clim. Dynam., 21, 221–232, https://doi.org/10.1007/s00382-003-0332-6, 2003.
Høyer, J. L., Alerskans, E., Nielsen-Englyst, P., Thejll, P., Dybkjær, G., and Tonboe, R.: Detailed investigation of the uncertainty budget for non-recoverable IST observations and their SI traceability (ESA Tech. Rep. FRM4STS OP-70), available at: http://www.frm4sts.org/wp-content/uploads/sites/3/2018/08/OP-70-FRM4STS_option3_report_v1-signed.pdf (last access: 29 June 2021), 2017a.
Høyer, J. L., Lang, A. M., Tonboe, R., Eastwood, S., Wimmer, W., and Dybkjær, G.: Towards field inter-comparison experiment (FICE) for ice surface temperature (ESA Tech. Rep. FRM4STS OP-40), available at: http://www.frm4sts.org/wp-content/uploads/sites/3/2017/12/OFE-OP-40-TR-5-V1-Iss-1-Ver-1-Signed.pdf (last access: 29 June 2021), 2017b.
Høyer, J. L., Good, E., Nielsen-Englyst, P., Madsen, K. S., Woolway, I., and Kennedy, J.: Report on the relationship between satellite surface skin temperature and surface air temperature observations for oceans, land, sea ice, ice sheets, and lakes, available at: https://www.eustaceproject.org/eustace/static/media/uploads/d1.5_revised.pdf
(last access: 29 June 2021), 2018.
Høyer, J. L., Dybkjær, G., Eastwood, S., and Madsen, K. S.: EUSTACE/AASTI: Global clear-sky ice surface temperature data from the AVHRR series on the satellite swath with estimates of uncertainty components, v1.1, 2000–2009, Centre for Environmental Data Analysis,
https://doi.org/10.5285/60b820fa10804fca9c3f1ddfa5ef42a1, 2019.
Hudson, S. R. and Brandt, R. E.: A Look at the Surface-Based Temperature Inversion on the Antarctic Plateau, J. Climate, 18, 1673–1696, https://doi.org/10.1175/JCLI3360.1, 2005.
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp., https://doi.org/10.1017/CBO9781107415324, 2013.
Jakobson, E., Vihma, T., Palo, T., Jakobson, L., Keernik, H., and Jaagus, J.: Validation of atmospheric reanalyses over the central Arctic Ocean, Geophys. Res. Lett., 39, L10802, https://doi.org/10.1029/2012GL051591, 2012.
Jones, P. D., Lister, D. H., Osborn, T. J., Harpham, C., Salmon, M., and Morice, C. P.: Hemispheric and large-scale land-surface air temperature variations: An extensive revision and an update to 2010:, J. Geophys. Res.-Atmos., 117, D05127, https://doi.org/10.1029/2011JD017139, 2012.
Karlsson, K.-G. and Dybbroe, A.: Evaluation of Arctic cloud products from the EUMETSAT Climate Monitoring Satellite Application Facility based on CALIPSO-CALIOP observations, Atmos. Chem. Phys., 10, 1789–1807, https://doi.org/10.5194/acp-10-1789-2010, 2010.
Karlsson, K.-G., Riihelä, A., Müller, R., Meirink, J. F., Sedlar, J., Stengel, M., Lockhoff, M., Trentmann, J., Kaspar, F., Hollmann, R., and Wolters, E.: CLARA-A1: a cloud, albedo, and radiation dataset from 28 yr of global AVHRR data, Atmos. Chem. Phys., 13, 5351–5367, https://doi.org/10.5194/acp-13-5351-2013, 2013.
Karlsson, K.-G., Anttila, K., Trentmann, J., Stengel, M., Fokke Meirink, J., Devasthale, A., Hanschmann, T., Kothe, S., Jääskeläinen, E., Sedlar, J., Benas, N., van Zadelhoff, G.-J., Schlundt, C., Stein, D., Finkensieper, S., Håkansson, N., and Hollmann, R.: CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data, Atmos. Chem. Phys., 17, 5809–5828, https://doi.org/10.5194/acp-17-5809-2017, 2017.
Kennedy, J. J., Capponi, F., Ghent, D., Good, E. J., Høyer, J. L., Kent, E. C., Madsen, K. S., Mitchelson, J. R., Nielsen-Englyst, P., and Tonboe, R. T.: EUSTACE: Globally gridded clear-sky daily air temperature estimates from satellites with uncertainty estimates for land, ocean and ice, 1995–2016, Centre for Environmental Data Analysis, https://doi.org/10.5285/f883e197594f4fbaae6edebafb3fddb3, 2019.
Key, J. R., Collins, J. B., Fowler, C., and Stone, R. S.: High-latitude surface temperature estimates from thermal satellite data, Remote Sens. Environ., 61, 302–309, https://doi.org/10.1016/S0034-4257(97)89497-7, 1997.
Kindig, D.: Greenland Climate Network (GC-Net) Radiation for Arctic System Reanalysis, Version 1. Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/6S7UHUH2K5RI, 2010.
Knust, R.: Polar Research and Supply Vessel POLARSTERN operated by the Alfred-Wegener-Institute, Journal of Large-Scale Research Facilities JLSRF, 3, A119, https://doi.org/10.17815/jlsrf-3-163, 2017.
Koenig, L. S. and Hall, D. K.: Comparison of satellite, thermochron and air temperatures at Summit, Greenland, during the winter of 2008/09, J. Glaciol., 56, 735–741, https://doi.org/10.3189/002214310793146269, 2010.
König-Langlo, G., Loose, B., and Bräuer, B.: 25 Years of Polarstern Meteorology, WDC-MARE Rep., 4 (CD-ROM), 1–137, 2006a.
König-Langlo, G., Loose, B., and Bräuer, B.: 25 Years of Polarstern Meteorology, World Data Center for Marine Environmental Sciences, PANGAEA, https://doi.org/10.1594/PANGAEA.761654, 2006b.
Langen, P. L., Mottram, R. H., Christensen, J. H., Boberg, F., Rodehacke, C. B., Stendel, M., van As, D., Ahlstrøm, A. P., Mortensen, J., Rysgaard, S., Petersen, D., Svendsen, K. H., Aðalgeirsdóttir, G., and Cappelen, J.: Quantifying Energy and Mass Fluxes Controlling Godthåbsfjord Freshwater Input in a 5 km Simulation (1991–2012)., J. Climate, 28, 3694–3713, https://doi.org/10.1175/JCLI-D-14-00271.1, 2015.
Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49–78, https://doi.org/10.5194/tc-13-49-2019, 2019.
Lenssen, N. J. L., Schmidt, G. A., Hansen, J. E., Menne, M. J., Persin, A., Ruedy, R., and Zyss, D.: Improvements in the GISTEMP Uncertainty Model, J. Geophys. Res.-Atmos., 124, 6307–6326, https://doi.org/10.1029/2018JD029522, 2019.
Lindsay, R., Wensnahan, M., Schweiger, A., and Zhang, J.: Evaluation of Seven Different Atmospheric Reanalysis Products in the Arctic, J. Climate, 27, 2588–2606, https://doi.org/10.1175/JCLI-D-13-00014.1, 2014.
Lüpkes, C., Vihma, T., Jakobson, E., König-Langlo, G., and Tetzlaff, A.: Meteorological observations from ship cruises during summer to the central Arctic: A comparison with reanalysis data, Geophys. Res. Lett., 37, L09810, https://doi.org/10.1029/2010GL042724, 2010.
Masson-Delmotte, V., Swingedouw, D., Landais, A., Seidenkrantz, M.-S., Gauthier, E., Bichet, V., Massa, C., Perren, B., Jomelli, V., Adalgeirsdottir, G., Hesselbjerg Christensen, J., Arneborg, J., Bhatt, U., Walker, D. A., Elberling, B., Gillet-Chaulet, F., Ritz, C., Gallée, H., van den Broeke, M., Fettweis, X., de Vernal, A., and Vinther, B.: Greenland climate change: from the past to the future: Greenland climate change, WiRes. Clim. Change, 3, 427–449, https://doi.org/10.1002/wcc.186, 2012.
Menke, W.: Geophysical Data Analysis: Discrete Inverse Theory, Elsevier, New York, 1989.
Merchant, C. J. and Le Borgne, P.: Retrieval of Sea Surface Temperature from Space, Based on Modeling of Infrared Radiative Transfer: Capabilities and Limitations, J. Atmos. Ocean. Tech., 21, 1734–1746, https://doi.org/10.1175/JTECH1667.1, 2004.
Merchant, C. J., Harris, A. R., Murray, M. J., and Závody, A. M.: Toward the elimination of bias in satellite retrievals of sea surface temperature: 1. Theory, modeling and interalgorithm comparison, J. Geophys. Res.-Oceans, 104, 23565–23578, https://doi.org/10.1029/1999JC900105, 1999.
Merchant, C. J., Matthiesen, S., Rayner, N. A., Remedios, J. J., Jones, P. D., Olesen, F., Trewin, B., Thorne, P. W., Auchmann, R., Corlett, G. K., Guillevic, P. C., and Hulley, G. C.: The surface temperatures of Earth: steps towards integrated understanding of variability and change, Geosci. Instrum. Method. Data Syst., 2, 305–321, https://doi.org/10.5194/gi-2-305-2013, 2013.
Merchant, C. J., Paul, F., Popp, T., Ablain, M., Bontemps, S., Defourny, P., Hollmann, R., Lavergne, T., Laeng, A., de Leeuw, G., Mittaz, J., Poulsen, C., Povey, A. C., Reuter, M., Sathyendranath, S., Sandven, S., Sofieva, V. F., and Wagner, W.: Uncertainty information in climate data records from Earth observation, Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, 2017.
Miller, N. B., Turner, D. D., Bennartz, R., Shupe, M. D., Kulie, M. S., Cadeddu, M. P., and Walden, V. P.: Surface-based inversions above central Greenland, J. Geophys. Res.-Atmos., 118, 495–506, https://doi.org/10.1029/2012JD018867, 2013.
Morice, C. P., Kennedy, J. J., Rayner, N. A., and Jones, P. D.: Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set: The HADCRUT4 data set, J. Geophys. Res.-Atmos., 117, D08101, https://doi.org/10.1029/2011JD017187, 2012.
Morice, C. P., Capponi, F., Kennedy, J. J., Killick, R. E., Lindgren, F., Mitchelson, J. R., Rayner, N. A., and Winn, J. P.: EUSTACE: Global daily air temperature combining surface and satellite data, with uncertainty estimates, for 1850–2015, v1.0, Centre for Environmental Data Analysis, Centre for Environmental Data Analysis, https://doi.org/10.5285/468abcf18372425791a31d15a41348d9, 2019.
Nielsen-Englyst, P., Høyer, J. L., Madsen, K. S., Tonboe, R., Dybkjær, G., and Alerskans, E.: In situ observed relationships between snow and ice surface skin temperatures and 2 m air temperatures in the Arctic, The Cryosphere, 13, 1005–1024, https://doi.org/10.5194/tc-13-1005-2019, 2019.
Oltmanns, M., Straneo, F., Seo, H., and Moore, G. W. K.: The Role of Wave Dynamics and Small-Scale Topography for Downslope Wind Events in Southeast Greenland, J. Atmos. Sci., 72, 2786–2805, https://doi.org/10.1175/JAS-D-14-0257.1, 2015.
Østby, T. I., Schuler, T. V., and Westermann, S.: Severe cloud contamination of MODIS Land Surface Temperatures over an Arctic ice cap, Svalbard, Remote Sens. Environ., 142, 95–102, https://doi.org/10.1016/j.rse.2013.11.005, 2014.
Overland, J., Dunlea, E., Box, J. E., Corell, R., Forsius, M., Kattsov, V., Olsen, M. S., Pawlak, J., Reiersen, L.-O., and Wang, M.: The urgency of Arctic change, Polar Sci., 21, 6–13, https://doi.org/10.1016/j.polar.2018.11.008, 2018.
Perovich, D. K., Richter-Menge, J. A., and Polashenski, C. M.: Observing and understanding climate change: Monitoring the mass balance, motion, and thickness of Arctic sea ice, The CRREL-Dartmouth Mass Balance Buoy Program, CRREL-Dartmouth, available at:
http://imb-crrel-dartmouth.org, last access: 24 November 2016.
Pielke, R. A., Davey, C. A., Niyogi, D., Fall, S., Steinweg-Woods, J., Hubbard, K., Lin, X., Cai, M., Lim, Y.-K., Li, H., Nielsen-Gammon, J., Gallo, K., Hale, R., Mahmood, R., Foster, S., McNider, R. T., and Blanken, P.: Unresolved issues with the assessment of multidecadal global land surface temperature trends, J. Geophys. Res., 112, D24S08, https://doi.org/10.1029/2006JD008229, 2007.
Pithan, F. and Mauritsen, T.: Arctic amplification dominated by temperature feedbacks in contemporary climate models, Nat. Geosci., 7, 181–184, https://doi.org/10.1038/ngeo2071, 2014.
Rapaić, M., Brown, R., Markovic, M., and Chaumont, D.: An Evaluation of Temperature and Precipitation Surface-Based and Reanalysis Datasets for the Canadian Arctic, 1950–2010, Atmos. Ocean, 53, 283–303, https://doi.org/10.1080/07055900.2015.1045825, 2015.
Rasmussen, T. A. S., Høyer, J. L., Ghent, D., Bulgin, C. E., Dybkjær, G., Ribergaard, M. H., Nielsen-Englyst, P., and Madsen, K. S.: Impact of Assimilation of Sea-Ice Surface Temperatures on a Coupled Ocean and Sea-Ice Model, J. Geophys. Res.-Oceans, 123, 2440–2460, https://doi.org/10.1002/2017JC013481, 2018.
Rayner, N., Good, S., and Block, T.: SST CCI Product User Guide, Project Document, SST_CCI-PUG-UKMO-201, available at: https://climate.esa.int/media/documents/SST_CCI-PUG-UKMO-201-Issue_1-signed.pdf (last access: 29 June 2021), 2015.
Rayner, N. A.: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century, J. Geophys. Res., 108, 4407, https://doi.org/10.1029/2002JD002670, 2003.
Rayner, N. A., Auchmann, R., Bessembinder, J., Brönnimann, S., Brugnara, Y., Capponi, F., Carrea, L., Dodd, E. M. A., Ghent, D., Good, E., Høyer, J. L., Kennedy, J. J., Kent, E. C., Killick, R. E., van der Linden, P., Lindgren, F., Madsen, K. S., Merchant, C. J., Mitchelson, J. R., Morice, C. P., Nielsen-Englyst, P., Ortiz, P. F., Remedios, J. J., van der Schrier, G., Squintu, A. A., Stephens, A., Thorne, P. W., Tonboe, R. T., Trent, T., Veal, K. L., Waterfall, A. M., Winfield, K., Winn, J., and Woolway, R. I.: The EUSTACE Project: Delivering Global, Daily Information on Surface Air Temperature, B. Am. Meteorol. Soc., 101, E1924–E1947, https://doi.org/10.1175/BAMS-D-19-0095.1, 2020.
Reeves Eyre, J. E. J. and Zeng, X.: Evaluation of Greenland near surface air temperature datasets, The Cryosphere, 11, 1591–1605, https://doi.org/10.5194/tc-11-1591-2017, 2017.
Renfrew, I. A.: The dynamics of idealized katabatic flow over a moderate slope and ice shelf, Q. J. Roy. Meteor. Soc., 130, 1023–1045, https://doi.org/10.1256/qj.03.24, 2004.
Richter-Menge, J. A., Perovich, D. K., Elder, B. C., Claffey, K., Rigor, I., and Ortmeyer, M.: Ice mass-balance buoys: a tool for measuring and attributing changes in the thickness of the Arctic sea-ice cover, Ann. Glaciol., 44, 205–210, https://doi.org/10.3189/172756406781811727, 2006.
Richter-Menge, J. A., Overland, J., Mathis, J. T., and Osborne, E. (Eds.): Arctic Report Card 2017, 2017.
Screen, J. A. and Simmonds, I.: Increasing fall-winter energy loss from the Arctic Ocean and its role in Arctic temperature amplification, Geophys. Res. Lett., 37, L16707, https://doi.org/10.1029/2010GL044136, 2010.
Serreze, M. C., Box, J. E., Barry, R. G., and Walsh, J. E.: Characteristics of Arctic synoptic activity, 1952–1989, Meteorol. Atmos. Phys., 51, 147–164, https://doi.org/10.1007/BF01030491, 1993.
Shuman, C. A., Steffen, K., Box, J. E., and Stearns, C. R.: A Dozen Years of Temperature Observations at the Summit: Central Greenland Automatic Weather Stations 1987–99, J. Appl. Meteorol., 40, 741–752, https://doi.org/10.1175/1520-0450(2001)040<0741:ADYOTO>2.0.CO;2, 2001.
Shuman, C. A., Hall, D. K., DiGirolamo, N. E., Mefford, T. K., and Schnaubelt, M. J.: Comparison of Near-Surface Air Temperatures and MODIS Ice-Surface Temperatures at Summit, Greenland (2008–13), J. Appl. Meteorol. Clim., 53, 2171–2180, https://doi.org/10.1175/JAMC-D-14-0023.1, 2014.
Simmons, A. J. and Poli, P.: Arctic warming in ERA-Interim and other analyses: Arctic Warming in ERA-Interim and Other Analyses, Q. J. Roy. Meteor. Soc., 141, 1147–1162, https://doi.org/10.1002/qj.2422, 2014.
Smith, T. M., Reynolds, R. W., Peterson, T. C., and Lawrimore, J.: Improvements to NOAA's Historical Merged Land–Ocean Surface Temperature Analysis (1880–2006), J. Climate, 21, 2283–2296, https://doi.org/10.1175/2007JCLI2100.1, 2008.
Stamnes, K., Ellingson, R. G., Curry, J. A., Walsh, J. E., and Zak, B. D.: Review of Science Issues, Deployment Strategy, and Status for the ARM North Slope of Alaska-Adjacent Arctic Ocean Climate Research Site, J. Climate, 12, 46–63, https://doi.org/10.1175/1520-0442(1999)012<0046:ROSIDS>2.0.CO;2, 1999.
Steeneveld, G.-J.: Current challenges in understanding and forecasting stable boundary layers over land and ice, Frontiers in Environmental Science, 2, 41, https://doi.org/10.3389/fenvs.2014.00041, 2014.
Steffen, K.: Surface energy exchange at the equilibrium line on the Greenland ice sheet during onset of melt, Ann. Glaciol., 21, 13–18, https://doi.org/10.3189/S0260305500015536, 1995.
Steffen, K. and Box, J.: Surface climatology of the Greenland Ice Sheet: Greenland Climate Network 1995–1999, J. Geophys. Res.-Atmos., 106, 33951–33964, https://doi.org/10.1029/2001JD900161, 2001.
Sterk, H. A. M., Steeneveld, G. J., and Holtslag, A. A. M.: The role of snow-surface coupling, radiation, and turbulent mixing in modeling a stable boundary layer over Arctic sea ice, J. Geophys. Res.-Atmos., 118, 1199–1217, https://doi.org/10.1002/jgrd.50158, 2013.
The CRREL-Dartmouth Mass Balance Buoy Program: CRREL-Dartmouth, available at:
http://imb-crrel-dartmouth.org, last access: 24 November 2016.
Tonboe, R. T., Eastwood, S., Lavergne, T., Sørensen, A. M., Rathmann, N., Dybkjær, G., Pedersen, L. T., Høyer, J. L., and Kern, S.: The EUMETSAT sea ice concentration climate data record, The Cryosphere, 10, 2275–2290, https://doi.org/10.5194/tc-10-2275-2016, 2016.
van As, D.: Warming, glacier melt and surface energy budget from weather station observations in the Melville Bay region of northwest Greenland, J. Glaciol., 57, 208–220, https://doi.org/10.3189/002214311796405898, 2011.
van As, D., Fausto, R. S., Ahlstrøm, A., Andersen, S., Citterio, M., Edelvang, K., Graversen, P., Machguth, H., Nick, F., Nielsen, S., and Weidick, A.: Programme for Monitoring of the Greenland Ice Sheet (PROMICE): first temperature and ablation record., Geol. Surv. Den. Greenl., 23, 73–76, 2011.
Vihma, T. and Pirazzini, R.: On the Factors Controlling the Snow Surface and 2 m Air Temperatures Over the Arctic Sea Ice in Winter, Bound.-Lay. Meteorol., 117, 73–90, https://doi.org/10.1007/s10546-004-5938-7, 2005.
Vihma, T., Uotila, J., Cheng, B., and Launiainen, J.: Surface heat budget over the Weddell Sea: Buoy results and model comparisons, J. Geophys. Res., 107, 3013, https://doi.org/10.1029/2000JC000372, 2002.
Vihma, T., Jaagus, J., Jakobson, E., and Palo, T.: Meteorological conditions in the Arctic Ocean in spring and summer 2007 as recorded on the drifting ice station Tara, Geophys. Res. Lett., 35, L18706, https://doi.org/10.1029/2008GL034681, 2008.
Vose, R. S., Arndt, D., Banzon, V. F., Easterling, D. R., Gleason, B., Huang, B., Kearns, E., Lawrimore, J. H., Menne, M. J., Peterson, T. C., Reynolds, R. W., Smith, T. M., Williams, C. N., and Wuertz, D. B.: NOAA's Merged Land–Ocean Surface Temperature Analysis, B. Am. Meteorol. Soc., 93, 1677–1685, https://doi.org/10.1175/BAMS-D-11-00241.1, 2012.
Wang, C., Graham, R. M., Wang, K., Gerland, S., and Granskog, M. A.: Comparison of ERA5 and ERA-Interim near-surface air temperature, snowfall and precipitation over Arctic sea ice: effects on sea ice thermodynamics and evolution, The Cryosphere, 13, 1661–1679, https://doi.org/10.5194/tc-13-1661-2019, 2019.
Weng, W. and Taylor, P. A.: On Modelling the One-Dimensional Atmospheric Boundary Layer, Bound.-Lay. Meteorol., 107, 371–400, https://doi.org/10.1023/A:1022126511654, 2003.
Wesslén, C., Tjernström, M., Bromwich, D. H., de Boer, G., Ekman, A. M. L., Bai, L.-S., and Wang, S.-H.: The Arctic summer atmosphere: an evaluation of reanalyses using ASCOS data, Atmos. Chem. Phys., 14, 2605–2624, https://doi.org/10.5194/acp-14-2605-2014, 2014.
Westermann, S., Langer, M., and Boike, J.: Systematic bias of average winter-time land surface temperatures inferred from MODIS at a site on Svalbard, Norway, Remote Sens. Environ., 118, 162–167, https://doi.org/10.1016/j.rse.2011.10.025, 2012.
World Meteorological Organization: World Meteorological Organization (2014) Guide to Meteorological Instruments and Methods of Observation, WMO-No.8, 1128 pp., preprint, available at: http://hdl.handle.net/11329/365 (last access: 29 June 2021), 2014.
Zhang, W., Wang, Y., Smeets, P. C. J. P., Reijmer, C. H., Huai, B., Wang, J., and Sun, W.: Estimating near-surface climatology of multi-reanalyses over the Greenland Ice Sheet, Atmos. Res., 259, 105676, https://doi.org/10.1016/j.atmosres.2021.105676, 2021.
Zilitinkevich, S., Savijärvi, H., Baklanov, A., Grisogono, B., and Myrberg, K.: Forthcoming Meetings on Planetary Boundary-layer Theory, Modelling and Applications, Bound.-Lay. Meteorol., 119, 591–593, https://doi.org/10.1007/s10546-006-9069-1, 2006.
Short summary
The Arctic region is responding heavily to climate change, and yet, the air temperature of Arctic ice-covered areas is heavily under-sampled when it comes to in situ measurements. This paper presents a method for estimating daily mean 2 m air temperatures (T2m) in the Arctic from satellite observations of skin temperature, providing spatially detailed observations of the Arctic. The satellite-derived T2m product covers clear-sky snow and ice surfaces in the Arctic for the period 2000–2009.
The Arctic region is responding heavily to climate change, and yet, the air temperature of...
