Articles | Volume 6, issue 3
https://doi.org/10.5194/amt-6-649-2013
https://doi.org/10.5194/amt-6-649-2013
Research article
 | 
13 Mar 2013
Research article |  | 13 Mar 2013

Simulation of SEVIRI infrared channels: a case study from the Eyjafjallajökull April/May 2010 eruption

A. Kylling, R. Buras, S. Eckhardt, C. Emde, B. Mayer, and A. Stohl

Related authors

Estimating volcanic ash emissions using retrieved satellite ash columns and inverse ash transport modeling using VolcanicAshInversion v1.2.1, within the operational eEMEP (emergency European Monitoring and Evaluation Programme) volcanic plume forecasting system (version rv4_17)
André R. Brodtkorb, Anna Benedictow, Heiko Klein, Arve Kylling, Agnes Nyiri, Alvaro Valdebenito, Espen Sollum, and Nina Kristiansen
Geosci. Model Dev., 17, 1957–1974, https://doi.org/10.5194/gmd-17-1957-2024,https://doi.org/10.5194/gmd-17-1957-2024, 2024
Short summary
Total ozone trends at three northern high-latitude stations
Leonie Bernet, Tove Svendby, Georg Hansen, Yvan Orsolini, Arne Dahlback, Florence Goutail, Andrea Pazmiño, Boyan Petkov, and Arve Kylling
Atmos. Chem. Phys., 23, 4165–4184, https://doi.org/10.5194/acp-23-4165-2023,https://doi.org/10.5194/acp-23-4165-2023, 2023
Short summary
Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 2: Impact on NO2 retrieval and mitigation strategies
Huan Yu, Claudia Emde, Arve Kylling, Ben Veihelmann, Bernhard Mayer, Kerstin Stebel, and Michel Van Roozendael
Atmos. Meas. Tech., 15, 5743–5768, https://doi.org/10.5194/amt-15-5743-2022,https://doi.org/10.5194/amt-15-5743-2022, 2022
Short summary
Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 3: Bias estimate using synthetic and observational data
Arve Kylling, Claudia Emde, Huan Yu, Michel van Roozendael, Kerstin Stebel, Ben Veihelmann, and Bernhard Mayer
Atmos. Meas. Tech., 15, 3481–3495, https://doi.org/10.5194/amt-15-3481-2022,https://doi.org/10.5194/amt-15-3481-2022, 2022
Short summary
What caused a record high PM10 episode in northern Europe in October 2020?
Christine D. Groot Zwaaftink, Wenche Aas, Sabine Eckhardt, Nikolaos Evangeliou, Paul Hamer, Mona Johnsrud, Arve Kylling, Stephen M. Platt, Kerstin Stebel, Hilde Uggerud, and Karl Espen Yttri
Atmos. Chem. Phys., 22, 3789–3810, https://doi.org/10.5194/acp-22-3789-2022,https://doi.org/10.5194/acp-22-3789-2022, 2022
Short summary

Related subject area

Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Transport of the Hunga volcanic aerosols inferred from Himawari-8/9 limb measurements
Fred Prata
Atmos. Meas. Tech., 17, 3751–3764, https://doi.org/10.5194/amt-17-3751-2024,https://doi.org/10.5194/amt-17-3751-2024, 2024
Short summary
A near-global multiyear climate data record of the fine-mode and coarse-mode components of atmospheric pure dust
Emmanouil Proestakis, Antonis Gkikas, Thanasis Georgiou, Anna Kampouri, Eleni Drakaki, Claire L. Ryder, Franco Marenco, Eleni Marinou, and Vassilis Amiridis
Atmos. Meas. Tech., 17, 3625–3667, https://doi.org/10.5194/amt-17-3625-2024,https://doi.org/10.5194/amt-17-3625-2024, 2024
Short summary
Innovative aerosol hygroscopic growth study from Mie–Raman–fluorescence lidar and microwave radiometer synergy
Robin Miri, Olivier Pujol, Qiaoyun Hu, Philippe Goloub, Igor Veselovskii, Thierry Podvin, and Fabrice Ducos
Atmos. Meas. Tech., 17, 3367–3375, https://doi.org/10.5194/amt-17-3367-2024,https://doi.org/10.5194/amt-17-3367-2024, 2024
Short summary
Evaluation of calibration performance of a low-cost particulate matter sensor using collocated and distant NO2
Kabseok Ko, Seokheon Cho, and Ramesh R. Rao
Atmos. Meas. Tech., 17, 3303–3322, https://doi.org/10.5194/amt-17-3303-2024,https://doi.org/10.5194/amt-17-3303-2024, 2024
Short summary
Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
Daniel J. V. Robbins, Caroline A. Poulsen, Steven T. Siems, Simon R. Proud, Andrew T. Prata, Roy G. Grainger, and Adam C. Povey
Atmos. Meas. Tech., 17, 3279–3302, https://doi.org/10.5194/amt-17-3279-2024,https://doi.org/10.5194/amt-17-3279-2024, 2024
Short summary

Cited articles

Anderson, G., Clough, S., Kneizys, F., Chetwynd, J., and Shettle, E.: AFGL atmospheric constituent profiles (0–120 km), Tech. Rep. AFGL-TR-86-0110, Air Force Geophys. Lab., Hanscom Air Force Base, Bedford, Mass., 1986.
Borbas, E. E. and Ruston, B. C.: The RTTOV UWiremis IR land surface emissivity module., NWP SAF report, available at: http://research.metoffice.gov.uk/research/interproj/nwpsaf/vs_reports/nwpsaf-mo-vs-042.pdf (last access: 11 March 2013), 2010.
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.
Buras, R. and Mayer, B.: Efficient unbiased variance reduction techniques for Monte Carlo simulations of radiative transfer in cloudy atmospheres: the solution, J. Quant. Spectrosc. Ra., 112, 434–447, https://doi.org/10.1016/j.jqsrt.2010.10.005, 2011.
Buras, R., Dowling, T., and Emde, C.: New secondary-scattering correction in DISORT with increased effiency for forward scattering, J. Quant. Spectrosc. Ra., 112, 2028–2034, https://doi.org/10.1016/j.jqsrt.2011.03.019, 2011.
Download