HelioClim-1 (HC1) overview
|Last update: Jul. 2018|
|HELIOCLIM-1 IDENTITY CARD|
|Type of ressource||Online solar radiation satellite-derived database|
|Access||Via the SoDa website (for free) / automatic (for pay)|
|Provider||MINES ParisTech / ARMINES / TRANSVALOR S.A.|
|Parameters||All radiation components over a horizontal plane for the monthly and daily time step. Also available over a normal plane, but only for the monthly time step.|
|Spatial coverage|| |
|Temporal coverage||1st Jan. 1985 to 31 Dec. 2005|
|Spatial resolution||Approx. 20 km (see explanations below)|
|Main publication||Lefèvre et al. 2007 (See below for more publications)|
The temporal resolution
The HelioClim-1 (HC1) database has been estimated by applying the Heliosat-2 method on the a reduced dataset from the Meteosat First Generation satellite (Lefèvre et al. 2007). Indeed, in the past, Meteosat images were for pay and very expensive. As well, all the images at full resolution represented a large volume of data to store, so MINES ParisTech decided to work on a reduced set. Only one every 6 images was conserved, increasing the temporal resolution from 30 min up to 3 hours, from which only the daily means have been conserved and provided to the users.
The spatial resolution: the B2 image dataset
The pixel of the Meteosat First Generation satellite image in the visible range is 2.5 km at nadir (against 3 km for Meteosat Second Generation, the map of MSG is identical for MFG if it is multiplied by 2.5/3). The thermal channel (Water Vapor) of MFG has a pixel size of 5 km at nadir. There is a perfect superposition between this "big pixel" of this channel and the 4 pixels in the visible range. In the literature, one can regularly find in the literature a reference to 5 km images in the visible ranges, which correspond to an average of these 4 pixels which are coincident with the thermal range ones.
From these 5 km images in the visible ranges, degraded version images have been derived, named B2; this set has been built taking one pixel every 6 in lines and columns. These images are referred as (20 or) 30 km images. HelioClim-1 has been built from these images B2.
As a consequence, the spatial resolution was reduced from 2.5 km down to approx. 20-30 km.
What is stored in the database?
The database contained the daily GHI values. Decomposition models and post-processing layers provide additional data. In particular, to derive the monthly HelioClim-1 values over a normal plane (HC1monthDNI) from the original daily HelioClim-1 values (HC1day) values, the algorithm of Collares-Peirera and Rabl (1979) is used to obtain intra-day radiation values over the horizontal plane. Then another model is applied to obtain the components of the radiation over the normal surface, before aggregation to obtain the monthly values.
The results of the quality assessment of HC1 versus several in-situ measurements have been published in several peer-reviewed articles.
Missing values in HC1: Several slots (or images) were regularly missed, due to internal shortage or interruption of service by Eumetsat. Except is the whole images of a day are missing, this is totally invisible for the users since the images of a day are interpolated if at least one image is available. For you information, the missing slots are available on this page with the corresponding information, if available (missing value in HelioClim: -999). Please note that the field of view is restricted to the pixels belonging to the Earth and for which the elevation angle of the sun above horizon is larger than 12 degrees.
Hypothesis "end of time integration": the date or instant given for each value corresponds to the end of the summarization/time integration. I.e. 24/04/2010 08:00 means that the associated irradiation or irradiance value has been measured between 07:00 and 08:00. This convention addresses the standard recommanded by the WMO (World Meteorological Organisation).
HelioClim-1 and Digital Elevation Model
Topography impacts the solar radiation values at ground levels in two ways: the variation of the optical path length and the shadowing effect due to the horizon. Indeed, according to the atmospheric layer tickness crossed by sun rays when reaching the ground, the radiation is modulated: the higher the elevation of a point, the narrower the atmospheric optical layer, and finally the higher the radiation. Each HelioClim-1 value is stored using the default elevation database TerrainBase 5' (worlwide database, spatial resolution of 5' of arc, equivalent to approx. 10 km). No correction in height is applied to take into account the exact height of the point requested by the user. It is also not possible to take into account the shadowing effect due to the far horizon.
The access to HelioClim-1 via the website is for free and unlimited. The automatic access is so far restricted to users having subscribed an annual subscription to HelioClim-3. We will be proposed shortly to automatically access HC1 against a limited fee.
|Last update: Jul. 2018|
(In alphabetic order and and reverse chronological order)
|Abdel Wahab et al. 2009||Abdel Wahab M., El-Metwally M., Hassan R., Lefèvre M., Oumbe A. and Wald L., 2009. "Assessing surface solar irradiance in Northern Africa desert climate and its long-term variations from Meteosat images", International Journal of Remote Sensing , 31(01) , 261 - 280 . doi: 10.108 0/01431160902882645||Heliosat-2, HelioClim-1|
Content: Correction of the irradiation with altitude (SRTM).
|Blanc et al. 2011|| |
Blanc, Ph., Gschwind, B., Lefèvre, M., Wald, F., Wald, L., 2011. "Validating Meteosat-derived surface solar irradiance in Mozambique". In Proceedings of the 30th Symposium of the European Association of Remote Sensing Laboratories, Ed. Halounova L., held in Prague, Czech Republic, 30 May – 2 June 2011, available at http://www.earsel.org/symposia//2011-symposium-Prague/Proceedings/, vol. ‘Thermal Remote Sensing', pp. 561-568.
|Bois et al. 2008|| |
Bois B., Wald L., Pieri P., Van Leeuwen C., Commagnac L., Chery Ph., Christen M., Gaudillère J.-P., Saur E., 2008. "Estimating spatial and temporal variations in solar radiation within bordeaux winegrowing region using remotely sensed data". Journal International des Sciences de la Vigne et du Vin, 42, 15-25.
|Bois et al. 2008|| |
Bois B., Pieri P., Van Leeuwen C., Wald L., Huard F., Gaudillère J.-P., Saur E., 2008. "Using remotely sensed solar radiation data for reference evapotranspiration estimation at daily time step". Agricultural and Forest Meteorology, 148, 619-630, 2008, doi: 10.1016/j.agrformet.2007.11.005.
|Lefèvre et al. 2014||Lefèvre M., Blanc P., Espinar B., Gschwind B., Ménard L., Ranchin T., Wald L., Saboret L., Thomas C., Wey E., 2014. "The HelioClim-1 database of daily solar radiation at Earth surface: an example of the benefits of GEOSS Data-CORE". IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(5), 1745-1753, 2014, doi:10.1109/JSTARS.2013.2283791.||HelioClim-1|
|Lefèvre et al. 2007||Lefèvre M., Wald L., Diabaté L., 2007. "Using reduced data sets ISCCP-B2 from the Meteosat satellites to assess surface solar irradiance". Solar Energy, 81, 240-253. doi:10.1016/j.solener.2006.03.008|| |
|Scharmer et al. 2000||Scharmer K., J.K. Page. L. Wald, M. Albuisson, G. Czeplak, B. Bourges, H. Lund, A. Joukoff, U.Terzenbach, H.G. Beyer, E.P. Borisenkov, 2000. "European Solar Radiation Atlas", 4th ed., Presses de l'Ecole des Mines de Paris: Paris, France, Volumes 1 and 2.||ESRA (clear-sky model and Linke)|
|Solar Radiation Atlas of Africa 1991|| |
Solar Radiation Atlas of Africa, 1991. Edited by E. Raschke, R. Stuhlmann, W. Palz, T. C. Steemers. Published for the Commission of the European Communities by A. A. Balkema, Rotterdam, 155 p.
|Wald 2013|| |
Wald L., 2013, "HelioClim-1: 21-years of daily values in solar radiation in one-click". In Proceedings of the 27th Conference on Environmental Informatics - Informatics for Environmental Protection, Sustainable Development and Risk Management, p. 143, Eds Bernd Page, Andreas G. Fleischer, Johannes Göbel, Volker Wohlgemuth, Hamburg, 2-4 September 2013, Germany.
|Wald et al. 2011||Wald L., Blanc Ph., Lefèvre M., Gschwind B., 2011. "The performances of the HelioClim databases in Mozambique". In Proceedings ISES Solar World Congress 2011, 28 August – 2 September 2011, Kassel, Germany. Vol "Resource Assessment", pp. 268-275.||HelioClim-1|