The DOI matches its Crossref record.
The method Heliosat-2 for deriving shortwave solar radiation from satellite images
Abstract
This article presents the method Heliosat-2 that converts observations made by geostationary meteorological satellites into estimates of the global irradiation at ground level. This new version integrates the knowledge gained by various exploitations of the original method Heliosat and its varieties in a coherent and thorough way. It is based upon the same physical principles but the inputs to the method are calibrated radiances, instead of the digital counts output from the sensor. This change opens the possibilities of using known models of the physical processes in atmospheric optics, thus removing the need for empirically defined parameters and of pyranometric measurements to tune them. The ESRA models are used for modeling the clear-sky irradiation. The assessment of the ground albedo and the cloud albedo is based upon explicit formulations of the path radiance and the transmittance of the atmosphere. The method Heliosat-2 is applied to Meteosat images of Europe for the months of January 1995, April 1995 and July 1994. Pyranometric measurements performed by thirty-five meteorological stations are used to assess the performances that are close to those of Heliosat-1 found in the literature. Possible improvements are discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Solcast: Validation of a satellite-derived solar irradiance dataset
Bright, J. M. (2019) · Solar Energy · doi:10.1016/j.solener.2019.07.086 · Cited by 146
Trolliet, M., Walawender, J. P., Bourlès, B., Boilley, A., Trentmann, J., Blanc, P., Lefèvre, M., & Wald, L. (2018) · Ocean Science · doi:10.5194/os-14-1021-2018 · Cited by 51
Self-citation
Metadata
- Authors
- Rigollier, C., Lefèvre, M., & Wald, L.
- Venue
- Solar Energy
- Publisher
- Elsevier BV
- Published
- 2004
- Volume
- 77
- Issue
- 2
- Pages
- 159-169
- ISSN
- 0038-092X (ISSN-L)
- OpenAlex
- W2081322852
- Cited by
- 512
- References
- 0
- FWCI
- 4.74
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The method Heliosat-2 for deriving shortwave solar radiation from satellite images. https://app.cochat.ai/papers/10.1016/j.solener.2004.04.017
- The paper
- Rigollier, C., Lefèvre, M., & Wald, L. (2004). The method Heliosat-2 for deriving shortwave solar radiation from satellite images. Solar Energy. https://doi.org/10.1016/j.solener.2004.04.017
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.