Articles | Volume 8, issue 1
Earth Syst. Sci. Data, 8, 199–211, 2016
https://doi.org/10.5194/essd-8-199-2016
Earth Syst. Sci. Data, 8, 199–211, 2016
https://doi.org/10.5194/essd-8-199-2016

  12 May 2016

12 May 2016

A synthetic data set of high-spectral-resolution infrared spectra for the Arctic atmosphere

Christopher J. Cox et al.

Related authors

Controls on surface aerosol number concentrations and aerosol-limited cloud regimes over the central Greenland Ice Sheet
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-491,https://doi.org/10.5194/acp-2021-491, 2021
Preprint under review for ACP
Short summary
Measurements from the University of Colorado RAAVEN Uncrewed Aircraft System during ATOMIC
Gijs de Boer, Steven Borenstein, Radiance Calmer, Christopher Cox, Michael Rhodes, Christopher Choate, Jonathan Hamilton, Jackson Osborn, Dale Lawrence, Brian Argrow, and Janet Intrieri
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-175,https://doi.org/10.5194/essd-2021-175, 2021
Preprint under review for ESSD
Short summary
The De-Icing Comparison Experiment (D-ICE): a study of broadband radiometric measurements under icing conditions in the Arctic
Christopher J. Cox, Sara M. Morris, Taneil Uttal, Ross Burgener, Emiel Hall, Mark Kutchenreiter, Allison McComiskey, Charles N. Long, Bryan D. Thomas, and James Wendell
Atmos. Meas. Tech., 14, 1205–1224, https://doi.org/10.5194/amt-14-1205-2021,https://doi.org/10.5194/amt-14-1205-2021, 2021
Short summary
Toward autonomous surface-based infrared remote sensing of polar clouds: retrievals of cloud optical and microphysical properties
Penny M. Rowe, Christopher J. Cox, Steven Neshyba, and Von P. Walden
Atmos. Meas. Tech., 12, 5071–5086, https://doi.org/10.5194/amt-12-5071-2019,https://doi.org/10.5194/amt-12-5071-2019, 2019
Short summary
Supercooled liquid fogs over the central Greenland Ice Sheet
Christopher J. Cox, David C. Noone, Max Berkelhammer, Matthew D. Shupe, William D. Neff, Nathaniel B. Miller, Von P. Walden, and Konrad Steffen
Atmos. Chem. Phys., 19, 7467–7485, https://doi.org/10.5194/acp-19-7467-2019,https://doi.org/10.5194/acp-19-7467-2019, 2019
Short summary

Related subject area

Data, Algorithms, and Models
Coastal complexity of the Antarctic continent
Richard Porter-Smith, John McKinlay, Alexander D. Fraser, and Robert A. Massom
Earth Syst. Sci. Data, 13, 3103–3114, https://doi.org/10.5194/essd-13-3103-2021,https://doi.org/10.5194/essd-13-3103-2021, 2021
Short summary
UAV-based very high resolution point cloud, digital surface model and orthomosaic of the Chã das Caldeiras lava fields (Fogo, Cabo Verde)
Gonçalo Vieira, Carla Mora, Pedro Pina, Ricardo Ramalho, and Rui Fernandes
Earth Syst. Sci. Data, 13, 3179–3201, https://doi.org/10.5194/essd-13-3179-2021,https://doi.org/10.5194/essd-13-3179-2021, 2021
Short summary
AQ-Bench: a benchmark dataset for machine learning on global air quality metrics
Clara Betancourt, Timo Stomberg, Ribana Roscher, Martin G. Schultz, and Scarlet Stadtler
Earth Syst. Sci. Data, 13, 3013–3033, https://doi.org/10.5194/essd-13-3013-2021,https://doi.org/10.5194/essd-13-3013-2021, 2021
Short summary
Bias-corrected and spatially disaggregated seasonal forecasts: a long-term reference forecast product for the water sector in semi-arid regions
Christof Lorenz, Tanja C. Portele, Patrick Laux, and Harald Kunstmann
Earth Syst. Sci. Data, 13, 2701–2722, https://doi.org/10.5194/essd-13-2701-2021,https://doi.org/10.5194/essd-13-2701-2021, 2021
Short summary
The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2017
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021,https://doi.org/10.5194/essd-13-2307-2021, 2021
Short summary

Cited articles

Alvarado, M. J., Payne, V. H., Mlawer, E. J., Uymin, G., Shephard, M. W., Cady-Pereira, K. E., Delamere, J. S., and Moncet, J.-L.: Performance of the Line-By-Line Radiative Transfer Model (LBLRTM) for temperature, water vapor, and trace gas retrievals: recent updates evaluated with IASI case studies, Atmos. Chem. Phys., 13, 6687–6711, https://doi.org/10.5194/acp-13-6687-2013, 2013.
Baum, B. A., Kratz, D. P., Yang, P., Ou, S. C., Hu, Y., Soulen, P. F., and Tsay, S.-C. L.: Remote sensing of cloud properties using MODIS airborne simulator imagery during SUCCESS 1. Data and models, J. Geophys. Res., 105, 11767–11780, https://doi.org/10.1029/1999JD901089, 2000.
Beer, R.: Remote sensing by Fourier transform spectrometry, Wiley-Interscience, New York, 1992.
Bugliaro, L., Zinner, T., Keil, C., Mayer, B., Hollmann, R., Reuter, M., and Thomas, W.: Validation of cloud property retrievals with simulated satellite radiances: a case study for SEVIRI, Atmos. Chem. Phys., 11, 5603–5624, https://doi.org/10.5194/acp-11-5603-2011, 2011.
Chan, M. A. and Comiso, J. C.: Arctic cloud characteristics as derived from MODIS, CALIPSO, and CloudSat, J. Climate, 26, 3285–3306, https://doi.org/10.1175/JCLI-D-12-00204.1, 2013.
Download
Short summary
Observations of cloud properties are necessary to understand and model clouds. Observations are frequently retrieved using remotely sensed measurements of infrared cloud emission. To support development and validation of the retrieval algorithms, this work produced a synthetic high-spectral-resolution infrared data set based on atmospheric conditions typical of the Arctic. Advantages of the data set include a priori knowledge of cloud properties and control over measurement uncertainties.