Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 3.400 IF 3.400
  • IF 5-year value: 3.841 IF 5-year
    3.841
  • CiteScore value: 3.71 CiteScore
    3.71
  • SNIP value: 1.472 SNIP 1.472
  • IPP value: 3.57 IPP 3.57
  • SJR value: 1.770 SJR 1.770
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 70 Scimago H
    index 70
  • h5-index value: 49 h5-index 49
Volume 10, issue 2
Atmos. Meas. Tech., 10, 409–429, 2017
https://doi.org/10.5194/amt-10-409-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 10, 409–429, 2017
https://doi.org/10.5194/amt-10-409-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 02 Feb 2017

Research article | 02 Feb 2017

Cloud and DNI nowcasting with MSG/SEVIRI for the optimized operation of concentrating solar power plants

Tobias Sirch et al.

Related authors

Analysis of properties of the 19 February 2018 volcanic eruption of Mount Sinabung in S5P/TROPOMI and Himawari-8 satellite data
Adrianus de Laat, Margarita Vazquez-Navarro, Nicolas Theys, and Piet Stammes
Nat. Hazards Earth Syst. Sci., 20, 1203–1217, https://doi.org/10.5194/nhess-20-1203-2020,https://doi.org/10.5194/nhess-20-1203-2020, 2020
Short summary
Synergy of Active- and Passive Remote Sensing: An Approach to Reconstruct Three-Dimensional Cloud Macro- and Microphysics
Lucas Höppler, Felix Gödde, Manuel Gutleben, Tobias Kölling, Bernhard Mayer, and Tobias Zinner
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-49,https://doi.org/10.5194/amt-2020-49, 2020
Preprint under review for AMT
The challenge of simulating the sensitivity of the Amazonian cloud microstructure to cloud condensation nuclei number concentrations
Pascal Polonik, Christoph Knote, Tobias Zinner, Florian Ewald, Tobias Kölling, Bernhard Mayer, Meinrat O. Andreae, Tina Jurkat-Witschas, Thomas Klimach, Christoph Mahnke, Sergej Molleker, Christopher Pöhlker, Mira L. Pöhlker, Ulrich Pöschl, Daniel Rosenfeld, Christiane Voigt, Ralf Weigel, and Manfred Wendisch
Atmos. Chem. Phys., 20, 1591–1605, https://doi.org/10.5194/acp-20-1591-2020,https://doi.org/10.5194/acp-20-1591-2020, 2020
Short summary
Cloud geometry from oxygen-A-band observations through an aircraft side window
Tobias Zinner, Ulrich Schwarz, Tobias Kölling, Florian Ewald, Evelyn Jäkel, Bernhard Mayer, and Manfred Wendisch
Atmos. Meas. Tech., 12, 1167–1181, https://doi.org/10.5194/amt-12-1167-2019,https://doi.org/10.5194/amt-12-1167-2019, 2019
Remote sensing of cloud droplet radius profiles using solar reflectance from cloud sides – Part 1: Retrieval development and characterization
Florian Ewald, Tobias Zinner, Tobias Kölling, and Bernhard Mayer
Atmos. Meas. Tech., 12, 1183–1206, https://doi.org/10.5194/amt-12-1183-2019,https://doi.org/10.5194/amt-12-1183-2019, 2019
Short summary

Related subject area

Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
SegCloud: a novel cloud image segmentation model using a deep convolutional neural network for ground-based all-sky-view camera observation
Wanyi Xie, Dong Liu, Ming Yang, Shaoqing Chen, Benge Wang, Zhenzhu Wang, Yingwei Xia, Yong Liu, Yiren Wang, and Chaofang Zhang
Atmos. Meas. Tech., 13, 1953–1961, https://doi.org/10.5194/amt-13-1953-2020,https://doi.org/10.5194/amt-13-1953-2020, 2020
Spatial distribution of cloud droplet size properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) measurements
Brent A. McBride, J. Vanderlei Martins, Henrique M. J. Barbosa, William Birmingham, and Lorraine A. Remer
Atmos. Meas. Tech., 13, 1777–1796, https://doi.org/10.5194/amt-13-1777-2020,https://doi.org/10.5194/amt-13-1777-2020, 2020
Short summary
Towards objective identification and tracking of convective outflow boundaries in next-generation geostationary satellite imagery
Jason M. Apke, Kyle A. Hilburn, Steven D. Miller, and David A. Peterson
Atmos. Meas. Tech., 13, 1593–1608, https://doi.org/10.5194/amt-13-1593-2020,https://doi.org/10.5194/amt-13-1593-2020, 2020
Short summary
Cloud detection over snow and ice with oxygen A- and B-band observations from the Earth Polychromatic Imaging Camera (EPIC)
Yaping Zhou, Yuekui Yang, Meng Gao, and Peng-Wang Zhai
Atmos. Meas. Tech., 13, 1575–1591, https://doi.org/10.5194/amt-13-1575-2020,https://doi.org/10.5194/amt-13-1575-2020, 2020
Short summary
Ground-based observations of cloud and drizzle liquid water path in stratocumulus clouds
Maria P. Cadeddu, Virendra P. Ghate, and Mario Mech
Atmos. Meas. Tech., 13, 1485–1499, https://doi.org/10.5194/amt-13-1485-2020,https://doi.org/10.5194/amt-13-1485-2020, 2020
Short summary

Cited articles

Accadia, C., Mariani, S., Casaioli, M., Lavagnini, A., and Speranza, A.: Sensitivity of Precipitation Forecast Skill Scores to Bilinear Interpolation and a Simple Nearest-Neighbor Average Method on High-Resolution Verification Grids, Weather Forecast., 18, 918–932, https://doi.org/10.1175/1520-0434(2003)018<0918:SOPFSS>2.0.CO;2, 2003.
Anderson, G., Clough, S., Kneizys, F., Chetwynd, J., and Shettle, E.: AFGL Atmospheric Constituent Profiles (0–120 km), Tech. Rep. AFGL-TR-86-0110, AFGL (OPI), Hanscom AFB, MA 01736, 1986.
Baum, B., Uttal, T., Poellot, M., Ackermann, T., Alvarez, J., Intrieri, J., Starr, D., Titlow, J., Tovinkere, V., and Clothiaux, E.: Satellite remote sensing of multiple cloud layers, J. Atmos. Sci., 52, 4210–4230, 1995.
Baum, B., Heymsfield, A., Yang, P., and Bedka, S.: Bulk scattering models for the remote sensing of ice clouds. Part 1: Microphysical data and models, J. Appl. Meteor., 44, 1885–1895, https://doi.org/10.1175/JAM2308.1, 2005.
Blanc, P., Espinar, B., Geuder, N., Gueymard, C., Meyer, R., Pitz-Paal, R., Reinhardt, B., Renne, D., Sengupta, M., Wald, L., and Wilbert, S.: Direct normal irradiance related definitions and applications: The circumsolar issue, Sol. Energy, 110, 561–577, 2014.
Publications Copernicus
Download
Short summary
A novel approach for the nowcasting of clouds and direct normal irradiance (DNI) based on the geostationary satellite MSG is presented. The basis of the algorithm is an optical flow method to derive cloud motion vectors for low and high level clouds separately. DNI is calculated from the forecasted optical thickness of the clouds. Validation against MSG observations shows good performance: compared to persistence an improvement of forecast horizon by a factor of 2 is reached for 2 h forecasts.
A novel approach for the nowcasting of clouds and direct normal irradiance (DNI) based on the...
Citation