Articles | Volume 7, issue 4
https://doi.org/10.5194/gmd-7-1661-2014
https://doi.org/10.5194/gmd-7-1661-2014
Model description paper
 | 
14 Aug 2014
Model description paper |  | 14 Aug 2014

Decoupling the effects of clear atmosphere and clouds to simplify calculations of the broadband solar irradiance at ground level

A. Oumbe, Z. Qu, P. Blanc, M. Lefèvre, L. Wald, and S. Cros

Related authors

Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023,https://doi.org/10.5194/amt-16-4165-2023, 2023
Short summary
Further validation of the estimates of the downwelling solar radiation at ground level in cloud-free conditions provided by the McClear service: the case of Sub-Saharan Africa and the Maldives Archipelago
William Wandji Nyamsi, Yves-Marie Saint-Drenan, Antti Arola, and Lucien Wald
Atmos. Meas. Tech., 16, 2001–2036, https://doi.org/10.5194/amt-16-2001-2023,https://doi.org/10.5194/amt-16-2001-2023, 2023
Short summary
An alternative cloud index for estimating downwelling surface solar irradiance from various satellite imagers in the framework of a Heliosat-V method
Benoît Tournadre, Benoît Gschwind, Yves-Marie Saint-Drenan, Xuemei Chen, Rodrigo Amaro E Silva, and Philippe Blanc
Atmos. Meas. Tech., 15, 3683–3704, https://doi.org/10.5194/amt-15-3683-2022,https://doi.org/10.5194/amt-15-3683-2022, 2022
Short summary
Performance of CAMS Radiation Service and HelioClim-3 databases of solar radiation at surface: evaluating the spatial variation in Germany
Mathilde Marchand, Yves-Marie Saint-Drenan, Laurent Saboret, Etienne Wey, and Lucien Wald
Adv. Sci. Res., 17, 143–152, https://doi.org/10.5194/asr-17-143-2020,https://doi.org/10.5194/asr-17-143-2020, 2020
Short summary
Assessment of five different methods for the estimation of surface photosynthetically active radiation from satellite imagery at three sites – application to the monitoring of indoor soft fruit crops in southern UK
Claire Thomas, Stephen Dorling, William Wandji Nyamsi, Lucien Wald, Stéphane Rubino, Laurent Saboret, Mélodie Trolliet, and Etienne Wey
Adv. Sci. Res., 16, 229–240, https://doi.org/10.5194/asr-16-229-2019,https://doi.org/10.5194/asr-16-229-2019, 2019
Short summary

Related subject area

Atmospheric sciences
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025,https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025,https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025,https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025,https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025,https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary

Cited articles

Beyer, H. G., Costanzo, C., and Heinemann, D.: Modifications of the Heliosat procedure for irradiance estimates from satellite images, Solar Energy, 56, 207–212, https://doi.org/10.1016/0038-092X(95)00092-6, 1996.
Blanc, P., Gschwind, B., Lefevre, M., and Wald, L.: The HelioClim project: Surface solar irradiance data for climate applications, Remote Sens., 3, 343–361, https://doi.org/10.3390/rs3020343, 2011.
Calbo, J., Pages, D., and Gonzalez, J.-A.: Empirical studies of cloud effects on UV radiation: A review, Rev. Geophys., 43, RG2002, https://doi.org/10.1029/2004RG000155, 2005.
Deneke, H. M., Feijt, A. J., and Roebeling, R. A.: Estimating surface solar irradiance from Meteosat SEVIRI-derived cloud properties, Remote Sens. Environ., 12, 3131–3141, https://doi.org/10.1016/j.rse.2008.03.012, 2008.
den Outer, P. N., Slaper, H., Kaurola, J., Lindfors, A., Kazantzidis, A., Bais, A. F. , Feister, U., Junk, J., Janouch, M., and Josefsson, W.: Reconstructing of erythemal ultraviolet radiation levels in Europe for the past 4 decades, J. Geophys. Res. Atmos., 115, D10102, https://doi.org/10.1029/2009JD012827, 2010.
Download

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Share