Articles | Volume 16, issue 12
https://doi.org/10.5194/amt-16-3257-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-3257-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Jun 2023
Research article |
| 29 Jun 2023
| 29 Jun 2023
Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data
Meteorologisches Institut, Ludwig-Maximilians-Universität München, Munich, Germany
Tobias Zinner
Meteorologisches Institut, Ludwig-Maximilians-Universität München, Munich, Germany
Fabian Jakub
Meteorologisches Institut, Ludwig-Maximilians-Universität München, Munich, Germany
Bernhard Mayer
Meteorologisches Institut, Ludwig-Maximilians-Universität München, Munich, Germany
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Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer
Atmos. Meas. Tech., 16, 645–667, https://doi.org/10.5194/amt-16-645-2023, https://doi.org/10.5194/amt-16-645-2023, 2023
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In this work, we analyze polarized cloudbow observations by the airborne camera system specMACS to retrieve the cloud droplet size distribution defined by the effective radius (reff) and the effective variance (veff). Two case studies of trade-wind cumulus clouds observed during the EUREC4A field campaign are presented. The results are combined into maps of reff and veff with a very high spatial resolution (100 m × 100 m) that allow new insights into cloud microphysics.
Behrooz Keshtgar, Aiko Voigt, Corinna Hoose, Michael Riemer, and Bernhard Mayer
Weather Clim. Dynam., 4, 115–132, https://doi.org/10.5194/wcd-4-115-2023, https://doi.org/10.5194/wcd-4-115-2023, 2023
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Linda Forster and Bernhard Mayer
Atmos. Chem. Phys., 22, 15179–15205, https://doi.org/10.5194/acp-22-15179-2022, https://doi.org/10.5194/acp-22-15179-2022, 2022
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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
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In this study, we have investigated the impact of 3D clouds on the tropospheric NO2 retrieval from UV–visible sensors. We applied standard NO2 retrieval methods including cloud corrections to synthetic data generated by the 3D radiative transfer model. A sensitivity study was done for synthetic data, and dependencies on various parameters were investigated. Possible mitigation strategies were investigated and compared based on 3D simulations and observed data.
Eleni Tetoni, Florian Ewald, Martin Hagen, Gregor Köcher, Tobias Zinner, and Silke Groß
Atmos. Meas. Tech., 15, 3969–3999, https://doi.org/10.5194/amt-15-3969-2022, https://doi.org/10.5194/amt-15-3969-2022, 2022
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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
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Atmospheric trace gases such as nitrogen dioxide (NO2) may be measured by satellite instruments sensitive to solar ultraviolet–visible radiation reflected from Earth and its atmosphere. For a single pixel, clouds in neighbouring pixels may affect the radiation and hence the retrieved trace gas amount. We found that for a solar zenith angle less than about 40° this cloud-related NO2 bias is typically below 10 %, while for larger solar zenith angles the NO2 bias is on the order of tens of percent.
Luca Bugliaro, Dennis Piontek, Stephan Kox, Marius Schmidl, Bernhard Mayer, Richard Müller, Margarita Vázquez-Navarro, Daniel M. Peters, Roy G. Grainger, Josef Gasteiger, and Jayanta Kar
Nat. Hazards Earth Syst. Sci., 22, 1029–1054, https://doi.org/10.5194/nhess-22-1029-2022, https://doi.org/10.5194/nhess-22-1029-2022, 2022
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The monitoring of ash dispersion in the atmosphere is an important task for satellite remote sensing since ash represents a threat to air traffic. We present an AI-based method that retrieves the spatial extension and properties of volcanic ash clouds with high temporal resolution during day and night by means of geostationary satellite measurements. This algorithm, trained on realistic observations simulated with a radiative transfer model, runs operationally at the German Weather Service.
Claudia Emde, Huan Yu, Arve Kylling, Michel van Roozendael, Kerstin Stebel, Ben Veihelmann, and Bernhard Mayer
Atmos. Meas. Tech., 15, 1587–1608, https://doi.org/10.5194/amt-15-1587-2022, https://doi.org/10.5194/amt-15-1587-2022, 2022
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Retrievals of trace gas concentrations from satellite observations can be affected by clouds in the vicinity, either by shadowing or by scattering of radiation from clouds in the clear region. We used a Monte Carlo radiative transfer model to generate synthetic satellite observations, which we used to test retrieval algorithms and to quantify the error of retrieved NO2 vertical column density due to cloud scattering.
Gregor Köcher, Tobias Zinner, Christoph Knote, Eleni Tetoni, Florian Ewald, and Martin Hagen
Atmos. Meas. Tech., 15, 1033–1054, https://doi.org/10.5194/amt-15-1033-2022, https://doi.org/10.5194/amt-15-1033-2022, 2022
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We present a setup for systematic characterization of differences between numerical weather models and radar observations for convective weather situations. Radar observations providing dual-wavelength and polarimetric variables to infer information about hydrometeor shapes and sizes are compared against simulations using microphysics schemes of varying complexity. Differences are found in ice and liquid phase, pointing towards issues of some schemes in reproducing particle size distributions.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
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The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Heike Konow, Florian Ewald, Geet George, Marek Jacob, Marcus Klingebiel, Tobias Kölling, Anna E. Luebke, Theresa Mieslinger, Veronika Pörtge, Jule Radtke, Michael Schäfer, Hauke Schulz, Raphaela Vogel, Martin Wirth, Sandrine Bony, Susanne Crewell, André Ehrlich, Linda Forster, Andreas Giez, Felix Gödde, Silke Groß, Manuel Gutleben, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Theresa Lang, Bernhard Mayer, Mario Mech, Marc Prange, Sabrina Schnitt, Jessica Vial, Andreas Walbröl, Manfred Wendisch, Kevin Wolf, Tobias Zinner, Martin Zöger, Felix Ament, and Bjorn Stevens
Earth Syst. Sci. Data, 13, 5545–5563, https://doi.org/10.5194/essd-13-5545-2021, https://doi.org/10.5194/essd-13-5545-2021, 2021
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The German research aircraft HALO took part in the research campaign EUREC4A in January and February 2020. The focus area was the tropical Atlantic east of the island of Barbados. We describe the characteristics of the 15 research flights, provide auxiliary information, derive combined cloud mask products from all instruments that observe clouds on board the aircraft, and provide code examples that help new users of the data to get started.
Marc Schwaerzel, Dominik Brunner, Fabian Jakub, Claudia Emde, Brigitte Buchmann, Alexis Berne, and Gerrit Kuhlmann
Atmos. Meas. Tech., 14, 6469–6482, https://doi.org/10.5194/amt-14-6469-2021, https://doi.org/10.5194/amt-14-6469-2021, 2021
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NO2 maps from airborne imaging remote sensing often appear much smoother than one would expect from high-resolution model simulations of NO2 over cities, despite the small ground-pixel size of the sensors. Our case study over Zurich, using the newly implemented building module of the MYSTIC radiative transfer solver, shows that the 3D effect can explain part of the smearing and that building shadows cause a noticeable underestimation and noise in the measured NO2 columns.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
Short summary
Short summary
The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Florian Ewald, Silke Groß, Martin Wirth, Julien Delanoë, Stuart Fox, and Bernhard Mayer
Atmos. Meas. Tech., 14, 5029–5047, https://doi.org/10.5194/amt-14-5029-2021, https://doi.org/10.5194/amt-14-5029-2021, 2021
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In this study, we show how solar radiance observations can be used to validate and further constrain ice cloud microphysics retrieved from the synergy of radar–lidar measurements. Since most radar–lidar retrievals rely on a global assumption about the ice particle shape, ice water content and particle size biases are to be expected in individual cloud regimes. In this work, we identify and correct these biases by reconciling simulated and measured solar radiation reflected from these clouds.
Nina Črnivec and Bernhard Mayer
Geosci. Model Dev., 14, 3663–3682, https://doi.org/10.5194/gmd-14-3663-2021, https://doi.org/10.5194/gmd-14-3663-2021, 2021
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This study aims to advance the cloud–radiation interplay treatment in global weather and climate prediction, focusing on cloud horizontal inhomogeneity misrepresentation. We explore the potential of the Tripleclouds method for diverse cloud types, namely the stratocumulus, cirrus and cumulonimbus. The validity of global cloud variability estimate with various condensate distribution assumptions is assessed. Optimizations for overcast and extremely heterogeneous cloudiness are further endorsed.
Cited articles
Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., and Süsstrunk,
S.: SLIC Superpixels Compared to State-of-the-Art Superpixel Methods, IEEE T. Pattern. Anal., 34, 2274–2282,
https://doi.org/10.1109/TPAMI.2012.120, 2012. a
Anderson, G. P., Clough, S. A., Kneizys, F. X., Chetwynd, J. H., and Shettle,
E. P.: AFGL atmospheric constituent profiles (0–120 km), Tech. Rep. 954,
Air Force Geophysics Lab Hanscom AFB MA, https://apps.dtic.mil/sti/citations/ADA175173 (last access: 22 June 2023), 1986. a
Beekmans, C., Schneider, J., Läbe, T., Lennefer, M., Stachniss, C., and Simmer, C.: Cloud photogrammetry with dense stereo for fisheye cameras, Atmos. Chem. Phys., 16, 14231–14248, https://doi.org/10.5194/acp-16-14231-2016, 2016. a
Blum, N. B., Nouri, B., Wilbert, S., Schmidt, T., Lünsdorf, O., Stührenberg, J., Heinemann, D., Kazantzidis, A., and Pitz-Paal, R.: Cloud height measurement by a network of all-sky imagers, Atmos. Meas. Tech., 14, 5199–5224, https://doi.org/10.5194/amt-14-5199-2021, 2021. a, b
Blum, N. B., Wilbert, S., Nouri, B., Stührenberg, J., Lezaca Galeano,
J. E., Schmidt, T., Heinemann, D., Vogt, T., Kazantzidis, A., and Pitz-Paal,
R.: Analyzing Spatial Variations of Cloud Attenuation by a Network of
All-Sky Imagers, Remote Sens., 14, 5685, https://doi.org/10.3390/rs14225685, 2022. a, b
Boudreault, L.-É., Liandrat, O., Braun, A., Buessler, É., Lafuma,
M., Cros, S., Gomez, A., Sas, R., and Delmas, J.: Sky-Imager Forecasting for
Improved Management of a Hybrid Photovoltaic-Diesel System, 3rd
International Hybrid Power Systems Workshop, 1–6, https://hybridpowersystems.org/wp-content/uploads/sites/9/2018/05/6A_1_TENE18_049_paper_Boudreault_Louis-Etienne.pdf (last access: 22 June 2023), 2018. a
Bradski, G.: The OpenCV Library, Dr. Dobb's Journal of Software Tools, https://github.com/opencv/opencv (last access: 22 June 2023), 2000. a
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. a
Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F., and Adam, H.:
Encoder-Decoder with Atrous Separable Convolution for Semantic Image
Segmentation, Lecture Notes in Computer Science (including subseries Lecture
Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11211
LNCS, 833–851, https://doi.org/10.48550/arXiv.1802.02611, 2018. a, b
Chen, X., Du, Y., Lim, E., Fang, L., and Yan, K.: Towards the applicability of
solar nowcasting: A practice on predictive PV power ramp-rate control,
Renew. Energ., 195, 147–166, https://doi.org/10.1016/j.renene.2022.05.166, 2022. a
Chow, C. W., Urquhart, B., Lave, M., Dominguez, A., Kleissl, J., Shields, J.,
and Washom, B.: Intra-hour forecasting with a total sky imager at the UC San
Diego solar energy testbed, Solar Energ., 85, 2881–2893,
https://doi.org/10.1016/j.solener.2011.08.025, 2011. a, b, c
Dev, S., Manandhar, S., Lee, Y. H., and Winkler, S.: Multi-label Cloud
Segmentation Using a Deep Network, 2019 USNC-URSI Radio Science Meeting
(Joint with AP-S Symposium), USNC-URSI 2019 – Proceedings, 113–114,
https://doi.org/10.1109/USNC-URSI.2019.8861850, 2019. a, b, c
Fabel, Y., Nouri, B., Wilbert, S., Blum, N., Triebel, R., Hasenbalg, M., Kuhn, P., Zarzalejo, L. F., and Pitz-Paal, R.: Applying self-supervised learning for semantic cloud segmentation of all-sky images, Atmos. Meas. Tech., 15, 797–809, https://doi.org/10.5194/amt-15-797-2022, 2022. a, b, c, d
Hasenbalg, M., Kuhn, P., Wilbert, S., Nouri, B., and Kazantzidis, A.:
Benchmarking of six cloud segmentation algorithms for ground-based all-sky
imagers, Solar Energ., 201, 596–614, https://doi.org/10.1016/j.solener.2020.02.042,
2020. a
He, K., Zhang, X., Ren, S., and Sun, J.: Deep Residual Learning for Image
Recognition, Proceedings of the IEEE Computer Society Conference on Computer
Vision and Pattern Recognition, Vol. 2016-December, 770–778,
https://doi.org/10.1109/CVPR.2016.90, 2015. a
Hillaire, S.: Physically Based Sky, Atmosphere and Cloud Rendering in
Frostbite, SIGGRAPH 2016 Course,
https://www.ea.com/frostbite/news/physically-based-sky-atmosphere-and-cloud-rendering (last access: 22 June 2023),
2016. a
Hu, Y., Song, R., and Li, Y.: Efficient Coarse-to-Fine Patch Match for Large
Displacement Optical Flow, in: 2016 IEEE Conference on Computer Vision and
Pattern Recognition (CVPR), Vol. 2016-December, 5704–5712, IEEE,
https://doi.org/10.1109/CVPR.2016.615, 2016. a
Jakub, F. and Gregor, P.: UCLA-LES shallow cumulus dataset with 3D cloud
output data, LMU Munich, Faculty of Physics [data set], https://doi.org/10.57970/5d0k9-q2n86, 2022. a, b, c
Katiraei, F. and Agüero, J. R.: Solar PV integration challenges,
IEEE Power Energy M., 9, 62–71, https://doi.org/10.1109/MPE.2011.940579, 2011. a
Kazantzidis, A., Tzoumanikas, P., Blanc, P., Massip, P., Wilbert, S., and
Ramirez-Santigosa, L.: Short-term forecasting based on all-sky cameras,
Ccd, Elsevier Ltd, https://doi.org/10.1016/B978-0-08-100504-0.00005-6, 2017. a
Kingma, D. P. and Ba, J.: Adam: A Method for Stochastic Optimization, 3rd
International Conference on Learning Representations, ICLR 2015 – Conference
Track Proceedings, 1–15, http://arxiv.org/abs/1412.6980 (last access: 22 June 2023),
2014. a
Kölling, T., Zinner, T., and Mayer, B.: Aircraft-based stereographic reconstruction of 3-D cloud geometry, Atmos. Meas. Tech., 12, 1155–1166, https://doi.org/10.5194/amt-12-1155-2019, 2019. a
Kuhn, P., Wilbert, S., Prahl, C., Schüler, D., Haase, T., Hirsch, T.,
Wittmann, M., Ramirez, L., Zarzalejo, L., Meyer, A., Vuilleumier, L., Blanc,
P., and Pitz-Paal, R.: Shadow camera system for the generation of solar
irradiance maps, Solar Energ., 157, 157–170,
https://doi.org/10.1016/j.solener.2017.05.074, 2017a. a
Kuhn, P., Wilbert, S., Schüler, D., Prahl, C., Haase, T., Ramirez, L.,
Zarzalejo, L., Meyer, A., Vuilleumier, L., Blanc, P., Dubrana, J.,
Kazantzidis, A., Schroedter-Homscheidt, M., Hirsch, T., and Pitz-Paal, R.:
Validation of spatially resolved all sky imager derived DNI nowcasts, in:
AIP Conference Proceedings, Vol. 1850, p. 140014, https://doi.org/10.1063/1.4984522,
2017b. a
Kuhn, P., Nouri, B., Wilbert, S., Prahl, C., Kozonek, N., Schmidt, T., Yasser,
Z., Ramirez, L., Zarzalejo, L., Meyer, A., Vuilleumier, L., Heinemann, D.,
Blanc, P., and Pitz-Paal, R.: Validation of an all-sky imager–based
nowcasting system for industrial PV plants, Prog. Photovoltaics:
Research and Applications, 26, 608–621, https://doi.org/10.1002/pip.2968,
2018a. a
Kuhn, P., Wirtz, M., Killius, N., Wilbert, S., Bosch, J., Hanrieder, N., Nouri,
B., Kleissl, J., Ramirez, L., Schroedter-Homscheidt, M., Heinemann, D.,
Kazantzidis, A., Blanc, P., and Pitz-Paal, R.: Benchmarking three low-cost,
low-maintenance cloud height measurement systems and ECMWF cloud heights
against a ceilometer, Solar Energ., 168, 140–152,
https://doi.org/10.1016/j.solener.2018.02.050, 2018b. a
Kuhn, P., Nouri, B., Wilbert, S., Hanrieder, N., Prahl, C., Ramirez, L.,
Zarzalejo, L., Schmidt, T., Yasser, Z., Heinemann, D., Tzoumanikas, P.,
Kazantzidis, A., Kleissl, J., Blanc, P., and Pitz-Paal, R.: Determination of
the optimal camera distance for cloud height measurements with two all-sky
imagers, Solar Energ., 179, 74–88, https://doi.org/10.1016/j.solener.2018.12.038,
2019. a
Kurtz, B., Mejia, F., and Kleissl, J.: A virtual sky imager testbed for solar
energy forecasting, Solar Energ., 158, 753–759,
https://doi.org/10.1016/j.solener.2017.10.036, 2017. a
Kylling, A., Stamnes, K., and Tsay, S. C.: A reliable and efficient two-stream
algorithm for spherical radiative transfer: Documentation of accuracy in
realistic layered media, J. Atmos. Chem., 21, 115–150,
https://doi.org/10.1007/BF00696577, 1995. a
Law, E. W., Kay, M., and Taylor, R. A.: Evaluating the benefits of using
short-term direct normal irradiance forecasts to operate a concentrated solar
thermal plant, Solar Energ., 140, 93–108,
https://doi.org/10.1016/j.solener.2016.10.037, 2016. a
Le Dimet, F.-X. and Talagrand, O.: Variational algorithms for analysis and
assimilation of meteorological observations: theoretical aspects,
Tellus A, 38, 97–110,
https://doi.org/10.3402/tellusa.v38i2.11706, 1986. a
Li, Q., Lu, W., and Yang, J.: A hybrid thresholding algorithm for cloud
detection on ground-based color images, J. Atmos. Ocean.
Technol., 28, 1286–1296, https://doi.org/10.1175/JTECH-D-11-00009.1, 2011. a
Masuda, R., Iwabuchi, H., Schmidt, K. S., Damiani, A., and Kudo, R.: Retrieval
of Cloud Optical Thickness from Sky-View Camera Images using a Deep
Convolutional Neural Network based on Three-Dimensional Radiative Transfer,
Remote Sens., 11, 1962, https://doi.org/10.3390/rs11171962, 2019. a
Mayer, B.: Radiative transfer in the cloudy atmosphere,
The Euro. Phys. J. Conf., 1, 75–99, https://doi.org/10.1140/epjconf/e2009-00912-1, 2009. a
Nguyen, D. A. and Kleissl, J.: Stereographic methods for cloud base height
determination using two sky imagers, Solar Energ., 107, 495–509,
https://doi.org/10.1016/j.solener.2014.05.005, 2014. a, b
Nouri, B., Kuhn, P., Wilbert, S., Prahl, C., Pitz-Paal, R., Blanc, P., Schmidt,
T., Yasser, Z., Santigosa, L. R., and Heineman, D.: Nowcasting of DNI maps
for the solar field based on voxel carving and individual 3D cloud objects
from all sky images, AIP Conf. Proc., 2033,
https://doi.org/10.1063/1.5067196, 2018. a
Nouri, B., Wilbert, S., Kuhn, P., Hanrieder, N., Schroedter-Homscheidt, M.,
Kazantzidis, A., Zarzalejo, L., Blanc, P., Kumar, S., Goswami, N., Shankar,
R., Affolter, R., and Pitz-Paal, R.: Real-time uncertainty specification of
all sky imager derived irradiance nowcasts, Remote Sens., 11, 1059,
https://doi.org/10.3390/rs11091059, 2019. a
Nouri, B., Blum, N., Wilbert, S., and Zarzalejo, L. F.: A Hybrid Solar
Irradiance Nowcasting Approach: Combining All Sky Imager Systems and
Persistence Irradiance Models for Increased Accuracy, Solar RRL, 6, 1–12,
https://doi.org/10.1002/solr.202100442, 2022. a, b, c, d
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen,
T., Lin, Z., Gimelshein, N., Antiga, L., Desmaison, A., Kopf, A., Yang, E.,
DeVito, Z., Raison, M., Tejani, A., Chilamkurthy, S., Steiner, B., Fang, L.,
Bai, J., and Chintala, S.: PyTorch: An Imperative Style, High-Performance
Deep Learning Library, in: Advances in Neural Information Processing Systems
32, edited by Wallach, H., Larochelle, H., Beygelzimer, A.,
d'Alché-Buc, F., Fox, E., and Garnett, R.,
8024–8035, Curran Associates, Inc.,
http://papers.neurips.cc/paper/9015-pytorch-an-imperative (last access: 22 June 2023),
2019. a
Peng, Z., Yu, D., Huang, D., Heiser, J., Yoo, S., and Kalb, P.: 3D cloud
detection and tracking system for solar forecast using multiple sky imagers,
Solar Energ., 118, 496–519, https://doi.org/10.1016/j.solener.2015.05.037, 2015. a, b, c
Rodríguez-Benítez, F. J., López-Cuesta, M., Arbizu-Barrena,
C., Fernández-León, M. M., Pamos-Ureña, M. Á.,
Tovar-Pescador, J., Santos-Alamillos, F. J., and Pozo-Vázquez, D.:
Assessment of new solar radiation nowcasting methods based on sky-camera and
satellite imagery, Appl. Energ., 292, 116838,
https://doi.org/10.1016/j.apenergy.2021.116838, 2021. a
Ronneberger, O., Fischer, P., and Brox, T.: U-Net: Convolutional Networks for
Biomedical Image Segmentation, IEEE Access, 9, 16591–16603,
https://doi.org/10.1109/ACCESS.2021.3053408, 2015. a
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z.,
Karpathy, A., Khosla, A., Bernstein, M., Berg, A. C., and Fei-Fei, L.:
ImageNet Large Scale Visual Recognition Challenge,
http://arxiv.org/abs/1409.0575 (last access: 22 June 2023), 2014. a
Saleh, M., Meek, L., Masoum, M. A., and Abshar, M.: Battery-less short-term
smoothing of photovoltaic generation using sky camera,
IEEE T. Ind. Inform., 14, 403–414, https://doi.org/10.1109/TII.2017.2767038, 2018. a
Samu, R., Calais, M., Shafiullah, G. M., Moghbel, M., Shoeb, M. A., Nouri, B.,
and Blum, N.: Applications for solar irradiance nowcasting in the control of
microgrids: A review, Renew. Sust. Energ. Rev., 147,
111187, https://doi.org/10.1016/j.rser.2021.111187, 2021. a
Schmidt, T., Kalisch, J., Lorenz, E., and Heinemann, D.: Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts, Atmos. Chem. Phys., 16, 3399–3412, https://doi.org/10.5194/acp-16-3399-2016, 2016. a, b, c, d
Shields, J., Karr, M., Burden, A., Johnson, R., Mikuls, V., Streeter, J., and
Hodgkiss, W.: Research toward Multi-site Characterization of Sky Obscuration
by Clouds, Final Report for GrantN00244-07-1-009, Tech. rep., Marine
Physical Laboratory, Scripps Institution of Oceanography, University of
California, San Diego, USA, https://apps.dtic.mil/sti/citations/ADA547055 (last access: 22 June 2023), 2009. a
Stevens, B., Moeng, C.-H., Ackerman, A. S., Bretherton, C. S., Chlond, A.,
de Roode, S., Edwards, J., Golaz, J.-C., Jiang, H., Khairoutdinov, M.,
Kirkpatrick, M. P., Lewellen, D. C., Lock, A., Müller, F., Stevens,
D. E., Whelan, E., and Zhu, P.: Evaluation of Large-Eddy Simulations via
Observations of Nocturnal Marine Stratocumulus, Mon. Weather Rev., 133,
1443–1462, https://doi.org/10.1175/MWR2930.1, 2005. a, b
Tola, E., Lepetit, V., and Fua, P.: DAISY: An Efficient Dense Descriptor
Applied to Wide-Baseline Stereo, IEEE T. Pattern Anal., 32, 815–830, https://doi.org/10.1109/TPAMI.2009.77, 2010. a
West, S. R., Rowe, D., Sayeef, S., and Berry, A.: Short-term irradiance
forecasting using skycams: Motivation and development, Solar Energ., 110,
188–207, https://doi.org/10.1016/j.solener.2014.08.038, 2014. a
Xie, W., Liu, D., Yang, M., Chen, S., Wang, B., Wang, Z., Xia, Y., Liu, Y., Wang, Y., and Zhang, C.: SegCloud: a novel cloud image segmentation model using a deep convolutional neural network for ground-based all-sky-view camera observation, Atmos. Meas. Tech., 13, 1953–1961, https://doi.org/10.5194/amt-13-1953-2020, 2020. a, b
Ye, L., Cao, Z., and Xiao, Y.: DeepCloud: Ground-Based Cloud Image
Categorization Using Deep Convolutional Features, IEEE Trans.
Geosci. Remote Sens., 55, 5729–5740,
https://doi.org/10.1109/TGRS.2017.2712809, 2017. a
Zhu, C., Byrd, R. H., Lu, P., and Nocedal, J.: Algorithm 778: L-BFGS-B, ACM
Trans. Mathe. Softw., 23, 550–560,
https://doi.org/10.1145/279232.279236, 1997. a
Short summary
This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar...
