|Last update: Mar. 2018|
- Evaluate the performance of the two methods of Wandji Nyamsi et al. 2015 (respectively named "weighted_kato" and the most performing one "discretized_Kato") against three other methods: Udo et Aro (1999), Jacovides et al. (2004), Sceicz (1974).
- Develop an operational service for discretized_Kato in all-sky conditions in the geographical coverage of the Meteosat Second Generation satellite since Feb. 2004 onwards, from 1 min to 1 month time step. This service will deliver time series of spectral radiation values in the spectral band interval required by the user.
Framework - collaboration
University of East Anglia. Comparison of the PAR data provided by the 5 methods against the measurements of:
- Aberystwyth University (30 min means, middle of interval UTC)
- Abbotts Hall (idem)
- Cartmels Sands (idem)
- and the updated measurements from 4 soft fruit farms from Apr. 2018.
To do: give the validation results for the three sites with long-term measurements + upload poster EMS 2018
(reverse chronological order)
29 Nov. 2017: rdv au CIEMAT. Discussion with the team about spectral developments
Oct. 2017: McClear v2 to McClear v3 => Stéphane is checking if ok. Correction of compute_gc_mcclear to correct the use of E0 (broadband instead of Kato)
Sept. 2017: McClear in real time
Aug. 2017: Self validation and first delivery of spectral radiation datasets to a user. Validation against in situ measurements is not yet carried out.
July: Bug in McClear v2 (change of atmospheric profile during the day generating sharp steps of radiation values). This has been corrected during the maintenance operation that occurred on 31st July 2017 (information not available in the release not as it impacted only the spectral data which is not an operational service).
Spring 2017: First developments of a precursor of service in Matlab following the work of William
2016 and before: research carried out by William Wandji, a PhD student from MINES ParisTech
Monthly and daily PAR from 2000-2016 : http://environment.snu.ac.kr/bess_rad/
Result from a radiation model transfer + neural networks with forcings from MODIS atmospheric products
Huete et al (2002) explique que l'indice EVI est plus adapté pour décrire l'activité photosynthétique des forêts tropicales (high-biomass forests) que le NDVI. (See Wikipedia for EVI - the values of coefficients for MODIS-EVI algorithm are; L=1, C1 = 6, C2 = 7.5, and G (gain factor) = 2.5)
PAR sensor, PSQ1 INRA Bornet June 2018: "A standardised PAR spectral response in the visible light range between 400nm and 700nm wavelength was defined by McCree (1972) such that each photon within this region is equally absorbed. ‘Blue' photons of shorter wavelength (higher frequency) have more energy than ‘Red' photons of longer wavelength. The amount of PAR is commonly expressed as Photosynthetic Photon Flux Density (PPFD) with a unit of µmol/m²·s."
Need for an online tool to convert µmol/m2/s into W/m2 or Wh/m2.
(In alphabetic order and and reverse chronological order)
|Aculinin et al. 2016||Aculinin A., C. Brogniez, M. Bengulescu, D. Gillotay, et al. 2016. "Assessment of Several Empirical Relationships for Deriving Daily Means of UV-A Irradiance from Meteosat-Based Estimates of the Total Irradiance" Remote Sensing, MDPI, 2016, 8 (7), pp.537.||UV-A from broadband|
|Jacovides et al. 2004||Jacovides, C. P., Timvios, F. S., Papaioannou, G., Asimakopoulos, D. N., and Theofilou, C. M.: Ratio of PAR to broadband solar radiation measured in Cyprus, Agr. Forest. Meteorol., 121, 135– 140, 2004.||PAR from HC3|
|Kato et al. 1999||Kato S., T. Ackerman, J. Mather, E. Clothiaux, 1999. "The k-distribution method and correlated-k approximation for shortwave radiative transfer model" Journal of Quantitative Spectroscopy and Radiative Transfer 62, 109-121. DOI:10.1016/S0022-4073(98)00075-2.||Kato|
|Kravietz et al. 2017||Kravietz A., S. Ka, L. Wald, A. Dugravot, A. Singh-Manoux, F. Moisan, A. Elbaz, 2017. "Association of UV radiation with Parkinson disease incidence: a nationwide French ecologic study" Environmental Research, 154, 50 - 56, doi: 10.1016/j.envres.2016.12.008||UV and Parkinson desease|
|Lefèvre et al. 2013||Lefèvre M., A. Oumbe, P. Blanc, B. Espinar, B. Gschwind, Z. Qu, L. Wald, M. Schroedter-Homscheidt, C. Hoyer-Klick, A. Arola, A. Benedetti, J. W. Kaiser, and J.-J. Morcrette, 2013. "McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions", Atmos. Meas. Tech., 6, 2403-2418, doi:10.5194/amt-6-2403-2013.||McClear|
Content: in addition to the description of CAMS McClear, this article provides a very restrictive algorithm to select clear sky instants. It consists of two successive filters. The first one is a constraint on the amount of diffuse irradiance with respect to the global irradiance since the direct irradiance is usually prominent in the case of clear sky. The second filter analyses the temporal variability of the global irradiance. If there is no cloud, the sky should be clear and steady for a long period.
|McCree 1972||McCree, K. J., 1972. "Test of current definitions of photosynthetically active radiation against leaf photosynthesis data", Agric. Meteorol., 10, 443–453, 1972||conversion factor from µmol/m2/s into W/m2|
|Udo et Aro 1999||Udo, S. O. and Aro, T. O., 1999. "Global PAR related to global solar radiation for central Nigeria", Agr. Forest. Meteorol, 97, 21–31, 1999.||PAR from broadband|
|Wald 2018||Lucien Wald, 2018. "A simple algorithm for the computation of the spectral distribution of the solar irradiance at surface" [Research Report] MINES ParisTech. 2018.||Spectral from broadband|
|Wald 2012||Wald L., 2012. "Elements on the Computation of UV Maps in the Eurosun Database" Internal Report. 2012.||UV from broadband|
|Wandji Nyamsi et al. 2018||Wandji Nyamsi W., P. Blanc, J.A. Augustine, A. Arola, and L. Wald, 2018. "Deriving Photosynthetically Active Radiation at ground level in cloud-free conditions from Copernicus Atmospheric Monitoring Service (CAMS) products", Biogeosciences Discussion, doi: 10.5194/bg-2017-512.||PAR from Kato|
|Wandji Nyamsi et al. 2017||Wandji Nyamsi W., M. R. A. Pitkänen, Y. Aoun, P. Blanc, A. Heikkilä, K. Lakkala, G. Bernhard, T. Koskela, A. V. Lindfors, A. Arola, et al., 2017. "A new method for estimating UV fluxes at ground level in cloud-free conditions" Atmospheric Measurement Techniques, European Geosciences Union, 2017, 10 (12), pp.4965-4978. DOI:10.5194/amt-10-4965- 2017.||UV from Kato|
|Wandji Nyamsi 2015|| |
Thèse de William Wandji Nyamsi W., 2015. "Vers une méthode automatique d'estimation de la distribution spectrale du rayonnement solaire. Cas du ciel clair. : Applications à la lumière du jour, photosynthèse et ultraviolet". Soutenue le 6 novembre 2015. MINES ParisTech, spécialité « énergétique et procédés », 124 p.
|PAR et UV from Kato|
|Wandji Nyamsi et al. 2015|| |
Wandji Nyamsi W., B. Espinar, P. Blanc, and L. Wald, 2015. "Estimating the photosynthetically active radiation under clear skies by means of a new approach" Advances in Science and Research, Copernicus Publications, 12, pp.5–10. DOI: 10.5194/asr-12-5-2015
|PAR from Kato|
Content: the Kato bands do not exactly fit the PAR spectral ranges and a spectral resampling is necessary. The authors have developed a resampling method which determine several 1-nm spectral bands whose atmospheric transmissivities are correlated to those of the Kato bands and then use these transmissivities in a linear interpolation process to compute the PAR irradiance. The technique has been numerically validated. The authors conclude that the technique estimates direct and global with very high accuracy.
|Wandji Nyamsi et al. 2014||Wandji Nyamsi W., B. Espinar, P. Blanc, and L. Wald, 2014. "How close to detailed spectral calculations is the k-distribution method and correlated-k approximation of Kato et al. (1999) in each spectral interval?" Meteorologische Zeitschrift, Borntraeger Science Publishers, 2014, 23, pp.547-556. DOI: 10.1127/metz/2014/0607.||Kato|
Content: authors compared atmospheric transmissivities obtained by the Kato et al. approach against those obtained by spectrally resolved computations using two Radiative Transfer Models (RTMs) in each of the 32 Kato Bands. These calculations were performed for a set of 200 000 realistic atmospheres and clouds. These authors found that the Kato et al. approach offers very accurate estimates of irradiances in all 12 Kato bands covering PAR-range.