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McClear: a New Model Estimating Downwelling Solar Radiation at Ground Level in Clear-sky Conditions : Volume 6, Issue 9 (17/09/2013)

By Lefèvre, M.

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Book Id: WPLBN0003999179
Format Type: PDF Article :
File Size: Pages 16
Reproduction Date: 2015

Title: McClear: a New Model Estimating Downwelling Solar Radiation at Ground Level in Clear-sky Conditions : Volume 6, Issue 9 (17/09/2013)  
Author: Lefèvre, M.
Volume: Vol. 6, Issue 9
Language: English
Subject: Science, Atmospheric, Measurement
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2013
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

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Arola, A., Wald, L., Morcrette, J., Lefèvre, M., Schroedter-Homscheidt, M., Espinar, B.,...Qu, Z. (2013). McClear: a New Model Estimating Downwelling Solar Radiation at Ground Level in Clear-sky Conditions : Volume 6, Issue 9 (17/09/2013). Retrieved from http://www.ebooklibrary.org/


Description
Description: MINES ParisTech, CS10207, 06904 Sophia Antipolis, France. A new fast clear-sky model called McClear was developed to estimate the downwelling shortwave direct and global irradiances received at ground level under clear skies. It is a fully physical model replacing empirical relations or simpler models used before. It exploits the recent results on aerosol properties, and total column content in water vapour and ozone produced by the MACC project (Monitoring Atmosphere Composition and Climate). It accurately reproduces the irradiance computed by the libRadtran reference radiative transfer model with a computational speed approximately 105 times greater by adopting the abaci, or look-up table, approach combined with interpolation functions. It is therefore suited for geostationary satellite retrievals or numerical weather prediction schemes with many pixels or grid points, respectively. McClear irradiances were compared to 1 min measurements made in clear-sky conditions at several stations within the Baseline Surface Radiation Network in various climates. The bias for global irradiance comprises between −6 and 25 W m−2. The RMSE ranges from 20 W m−2 (3% of the mean observed irradiance) to 36 W m−2 (5%) and the correlation coefficient ranges between 0.95 and 0.99. The bias for the direct irradiance comprises between −48 and +33 W m−2. The root mean square error (RMSE) ranges from 33 W m−2 (5%) to 64 W m−2 (10%). The correlation coefficient ranges between 0.84 and 0.98. This work demonstrates the quality of the McClear model combined with MACC products, and indirectly the quality of the aerosol properties modelled by the MACC reanalysis.

Summary
McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions

Excerpt
Ba, M., Frouin, R., Nicholson, S., and Dedieu, G.: Satellite-derived surface radiation budget over the African continent. Part I: Estimation of downward solar irradiance and albedo, J. Climate, 14, 60–76, 2001.; Benedetti, A., Morcrette, J.-J., Boucher, O., Dethof, A., Engelen, R. J., Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S., Manglold, A., Razinger, M., Simmons, A. J., and Suttie, M.: Aerosol analysis and forecast in the European Centre for Medium-Range Weather Forecasts Integrated Forecast System: 2. Data assimilation, J. Geophys. Res., 114, D13205, doi:10.1029/2008JD011115, 2009.; Blanc, P. and Wald, L.: The SG2 algorithm for a fast and accurate computation of the position of the Sun, Sol. Energy, 86, 3072–3083, doi:10.1016/j.solener.2012.07.018, 2012.; Blanc, P., Gschwind, B., Lefèvre, M., and Wald, L.: The HelioClim project: Surface solar irradiance data for climate applications, Remote Sens., 3, 343–361, doi:10.3390/rs3020343, 2010.; Gueymard, C.: Importance of atmospheric turbidity and associated uncertainties in solar radiation and luminous efficacy modelling, Energy, 30, 1603–1621, 2005.; Cano, D., Monget, J. M., Albuisson, M., Guillard, H., Regas, N., and Wald, L.: A method for the determination of the global solar radiation from meteorological satellites data, Sol. Energy, 37, 31–39, 1986.; Darnell, W. L., Staylor, W. F., Ritchey, N. A., Gupta, S. K., and Wilber, A. C.: Surface radiation budget: A long-term global dataset of shortwave and longwave fluxes, EOS T. Am. Geophys. Un., available at: http://www.agu.org/eos_elec/95206.html (last access: 17 September 2013), 27 February 1996.; Deepshikha, S., Satheesh, S. K., and Srinivasan, J.: Dust aerosols over India and adjacent continents retrieved using METEOSAT infrared radiance Part I: sources and regional distribution, Ann. Geophys., 24, 37–61, doi:10.5194/angeo-24-37-2006, 2006.; 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, 2008.; Diabaté, L., Demarcq, H., Michaud-Regas, N., and Wald, L.: Estimating incident solar radiation at the surface from images of the Earth transmitted by geostationary satellites: the Heliosat Project, Int. J. Solar Energy, 5, 261–278, 1988.; Elias, T. and Roujean, J.-L.: Estimation of the aerosol radiative forcing at ground level, over land, and in cloudless atmosphere, from METEOSAT-7 observation: method and case study, Atmos. Chem. Phys., 8, 625–636, doi:10.5194/acp-8-625-2008, 2008.; Espinar, B., Wald, L., Blanc, P., Lefèvre, M., Gschwind, B., Ménard, L., Wey, E., Thomas, C., and Saboret, L.: HELIOCLIM-3: A near-real time and long-term surface solar irradiance database, Workshop on Remote Sensing Measurements for Renewable Energy, 22–23 May 2012, available at: http://hal-ensmp.archives-ouvertes.fr/docs/00/74/15/64/PDF/2012_COST_WIRE_HC3_extended_abstract_v2.pdf (last access: 24 January 2013), Risoe, Denmark, 2012.; FAO: Koeppen climate classification map, available at: www.fao.org/sd/EIdirect/climate/EIsp0002.htm (last access: 21 December 2012), 1997.; GCOS – Global Climate Observing System Essential Climate Variables: available at: www.wmo.int/pages/prog/gcos/index.php?name=EssentialClimateVariables, last access: 16

 

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