The secondary parameters produced by only osi SAF are the surface temperature, the water vapour content of the atmosphere and the relative humidity. They are produced with the ARPEGE model from Météo-France. In the same way than for the main components, they can be evaluated against ground measurements through scatter plots, frequency of occurrence and statistics.
Temperature, water vapor and relative humidity are simultaneously acquired and modelled for 3 data banks, and the sole relative humidity for the station of Lyon.
Figure 38 is an illustration of the dry bulb temperature validation for the station of
University of Geneva - 27 - Pierre Ineichen Figure 39 Dry bulb temperature model-measurements bias versus solar time for the station of Carpentras.
Figure 40 Modelled atmospheric water vapour content versus the c o r r e s p o n d i n g measurements for the sta-tion of Lyon.
Figure 38 Modelled dry bulb temperature versus the c o r r e s p o n d i n g measurements for the sta-tion of Lindenberg.
University of Geneva - 28 - Pierre Ineichen Table VI Statistical comparison of the osi SAF climatic products with the ground
measurements, by stations, and average.
Water vapour
ground average 1.75 10.5 81
nb 2775 2770 2786
abs. difference 0.19 1.4 9
MBD -0.03 -0.6 7
RMSD 0.27 1.8 12
ground average 1.70 14.7 63
nb 2491 2636 2636
abs. difference 0.28 3.0 15
MBD 0.13 -2.7 13
RMSD 0.38 3.5 18
ground average 2.08 11.8 81
nb 1477 1813 2106
abs. difference 0.24 1.4 7
MBD 0.00 -0.6 2
ground average 1.72 12.4 75
nb 9639 7219 7528
abs. difference 0.29 2.0 10
MBD 0.14 -1.4 8
Lindenberg. The statistics are given in Table VI for the 3 climatic parameters. The plots for the 3 stations are given in the appendix (Figures a-13.1, a-13.3 and a-13.5). It can be seen on the Figure for Carpentras that for high temperatures corresponding to a high level of insolation, the modelled temperature is underestimated. This is assessed by the higher negative bias and its correlation with the surface solar irradiance as shown on Figure 39, where the bias is plotted against the solar time. The underestimation happens clearly during the daytime.
The water vapour content of the atmosphere is a secondary input parameter for the radiative transfert models. Its knowledge in conjonction with the atmospheric aerosol optical depth is nevertheless important in order to improve the precision of the clear sky model, which is used as normalization for the solar irradiance evaluation. An example is given on Figure 40 for the station of Lyon, the Figures for the other stations are given in the appendix.
Not only the water vapour content of the atmosphere is a secondary input parameter for the RTM, but also the relative humidity. It is a normalized with the temperature water content, and has its importance in the condensation of the aerosols, and therefore in the atmospheric transmitivity. Figure 41 illustrates the modelled values for the station of Lindenberg, the other graphs are given in the appendix (Figure 16.1, 16.3 and a-16.5)
In conclusion, the secondary parameters are retrieved with a relatively satisfying precision,
University of Geneva - 29 - Pierre Ineichen Figure 41 Modelled relative humidity versus the c o r r e s p o n d i n g measurements for the sta-tion of Lindenberg.
taking into account the difficulty to evaluate them and their relative importance in the main model inputs.
13. Conclusions
A complete comparison and validation over 4 representative months and data from eight european ground stations was conducted. The general conclusion is that the products from the different SAFs have comparable biases and precisions. If some trends appear for specific sites or SAFs, they are difficult to isolate and are much smaller than the dispersion. The overall precision is of the order of 80-100 [W/m2] for the solar surface irradiance with a negligible bias, and of 25 [W/m2] with a slight negative bias for the downward longwave irradiance.
Concerning thesurface solar irradiance, a slight correlation of the bias with the modified clearness index and the solar elevation could be underlined, but these trends are very small compared to the dispersion. An improvement of the results could come from a better knowledge of the secondary atmopsheric transmission models’ inputs, like the atmospheric turbidity. It becomes important if the global component has to be splitted into its two components: the beam and diffuse.
Furthermore, due to the methodology, particular conditions like broken clouds are not taken into account in the different models; therefore in climates where intermediate conditions predominate like in Geneva or Lyon, the dispersion is higher.
For the downward longwave irradiance, despite the fact that a quality control is difficult to apply and that some strange pattern are present on the graphs, the modelled downward longwave irradiance is of good quality, with a small negative bias and a root mean square difference of less than 8%. Except a slight dependence with the cloud top height, no particular effect was found.
The secondary parameterslike the dry bulb temperature and the water vapour con-tent of the atmosphere are retrieved with a relatively satisfying precision. They are mainly used as input to the radiation models.
University of Geneva - 30 - Pierre Ineichen 15. Nomenclature
Io extraterrestrial normal (on a plane perpendicular to the sun rays) irradiance expressed in [W/m2]
Gh global or solar surface irradiance on a horizontal plane in [W/m2] Ghc clear sky global or solar surface irradiance on a horizontal plane
in [W/m2]
Kt global or solar surface irradiance clearness index
K’t modified global or solar surface irradiance clearness index
SSI solar surface or global irradiance on a horizontal plane in [W/m2] Ir downward longwave irradiance on a horizontal plane and
expressed in [W/m2]
Irup upward or outgoing longwave irradiance on a horizontal plane in [W/m2]
DLI downward longwave irradiance on a horizontal plane and expressed in [W/m2]
OLR upward or outgoing longwave irradiance on a horizontal plane in [W/m2]
CFI Cloud Free Index as defined in Dürr [2004]
CFIsat normalized CFI [Dürr 2006]
h solar elevation or altitude angle in [°]
am optical air mass
α surface albedo coefficient
ε longwave surface emissivity coefficient σ Stefan Boltzmann constant
Ta dry bulb or ambient temperature in [°] or K Ts surface temperature in [°] or K
Tc corrected temperature in [°] or K as input for the Stefan Boltzman law
mbd mean bias difference
ambd absolute mean bias difference rmsd root mean square difference 14. Acknowledgements
This study could be done thanks to the data provided by Carla Sofia Baroso (Institute of Meteorology of Portugal), Anne Marsouin, Catherine Meurey and Bernhard Geiger (Meteo France), Rainer Hollmann and Richard Müller (Deutscher Wetter Dienst), Dominique Dumortier (LASH - Ecole Nationale des Travaux publics, Lyon), and Bruno Dürr, Laurent Vuilleumier and Antoine Zelenka (Meteo Suisse).
University of Geneva - 31 - Pierre Ineichen 16. References
Black J.N., Bonython C.W., Prescott J.A. (1954)Solar radiation and the duration of sunshine.
Quart. J. Roy. Met. Soc. 80, pp231-235
Dürr B., Philipona R, (2004) Automatic cloud amount detection by surface longwave downward radiation measurements. J. Geoph. Res., Vol 109
Dürr B. (2006) , personal communication
ESRA (2000) The european solar radiation atlas. Coordinators : K. Scharmer, J. Greif, ISBN : 2-911762-21-5
Ineichen P., Gremaud J.M., Guisan O., Mermoud A. (1984)Infrared sky radiation in Geneva.
Solar Energy, Vol 32, N° 4, pp 537-545.
Ineichen P, Perez R. (2002) A new airmass independent formulation for the Linke turbidity coefficient. Solar Energy Vol. 73, No. 3, pp. 151–157
Ineichen P. (2006)Comparison of eight clear sky broadband models against 16 independent data banks. Solar Energy 80,pp. 468–478
Kasten F. (1980)A simple parameterization of two pyrheliometric formulae for determining the Linke turbidity factor. Meteor. Rdsch. 33, 124–127.
Marsouin A. (2006) Second comparison of the radiative fluxes of the climate and osi SAF’s. Meteofrance DP CMS. Lanion France
Meteonorm 5.1 (2006) Global Meteorological Database for Solar Energy and Applied Meteorology. www.meteotest.ch
Müller R., Dagestad K.F., Ineichen P., Schroedter-Homscheidt M., Cros S., Dumortier D., Kuhlemann R., Olseth J.A., Piernavieja G., Reise C., Wald L., Heinemann D. (2004) Rethinking satellite-based solar irradiance modelling. The SOLIS clear-sky module.Remote Ses. Env., Vol 91, pp 160-174.
Perez R., Ineichen P., Seals R., Michalsky J., Stewart R. (1990), Modelling daylight availability and irradiance components from direct and global irradiance. Solar Energy, Vol. 44, N° 5, pp. 271-289.
Perez R., Ineichen P., Seals R., Zelenka A. (1990) Making full use of the clearness index for parametrizing hourly insolation conditions. Solar Energy, Vol. 45, N° 2, pp. 111-114.
Vuilleumier L. (2006).Spectral and broadband beam measurements from the MeteoSwiss Payerne station of the Baseline Surface Radiation Network.MeteoSwiss, private commu-nication.
University of Geneva - 32 - Pierre Ineichen
University of Geneva Annexe I - 1 Pierre Ineichen Annexe I
Table of content
The OLR Model 2.
Clear sky solar irradiance and aerosol optical depth 4.
The Cabauw downward long wave irradiance correction 6.
Aerosol optical depth 8.
Surface solar irradiance 12.
Clearness index 20.
Parameter dependence 37.
Frequency of occurrence 38.
Cloud free index saturation CFIsat 55.
Downward longwave irradiance 56.
Frequency of occurence 62
Parameter dependence 68.
Outgoing longwave irradiance 70.
Secondary parameter 72.
University of Geneva Annexe I - 2 Pierre Ineichen The OLR model
The outgoing longwave irradiance can be evaluated from the surface temperature by the help of the Stefan Boltzman law:
Irup= ε σ Ts4 in [W/m2]
whereε is the ground emissivitiy and can be taken as unity,σis the Boltzmann constant (σ= 5.67 10-8[m2/K4]) and Tsthe surface temperature in Kelvin. This quantity if plotted on Figure a-0.a for measurements acquired at the station of Cabauw. The modelled values are underestimated for high values of irradiances (i.e. high dry bulb temperatures).
This is due to the shortwave solar irradiance and a correction can be applied to take this effect into account. The correction is done on the dry bulb temperature, it is proportionnal to the surface solar irradiance and has the following form:
Tcr = Ta+α 0.04 Gh
where Gh is the surface solar irradiance in [W/m2] and α the surface albedo coefficient.
The Stefan Boltzman law (SB) is then applied with this corrected temperature as illustrated Figure a-0.a
Outgoing infrared radiation calculated from Tawith the Stefan-Boltzman law versus measurements for the sta-tion of Cabauw.
Figure a-0.b
The blue dots are the same than on Figure a-0.a, and the red dots are calculated from Tcr (irradiance corrected) temperature versus the corresponding measurements.
University of Geneva Annexe I - 3 Pierre Ineichen on Figure a-0.b. If the correction is efficient for high values of outgoing irradiance, an overestimation for low values remains on the graph. This deviation is correlated with the water vapour content of the atmosphere and the following correction can be applied:
Tc = Ta+ Tcr + Tcw where Tcw= 0.25 w - 0.4
where w is the atmosheric water vapour column expressed in [cm]. The effect of the water vapour correction is illustrated on Figure a-0.c.
Finally, the comparison between the irradiance obtained from the Stefan-Boltzman law on the basis of the dry bulb temperature and the values obtained with the model are given on Figure a-0.d for the station of Cabauw.
Figure a-0.c
The blue dots are calculated with SB on the basis of Tcr (irradiance corrected), and the red dots on the basis of Tc (irradiance and water vapour corrected).
Figure a-0.d
Comparison of the outgoing infrared radiation calculated with the Stefan-Boltzman law with Ta as input (blue dots) and Tc (red dots) versus measurements for the station of Cabauw.
University of Geneva Annexe I - 4 Pierre Ineichen Clear sky solar irradiance and aerosol optical depth
With the knowledge of the water vapor content of the atmosphere and the aerosol optical depth, and with the help of an atmospheric radiative transfer model, it is possible to calculate the clear sky surface solar irradiance reaching the ground.
Climate SAF and ocean and sea ice SAF provided the clear sky surface solar irradiance on a horizontal surface and evaluated on the basis of their own input parameters. In order to have a comparable aerosol optical depth obtained in the same conditions for the two SAFs and the ground measurements, a retro-calculation is done from the clear sky sur-face solar irradiance and the measured atmospheric water vapor column obtained from ground measurements. The steps are the following:
- the measured water vapor content is used as input in the RTM calculation,
- the clear sky surface solar irradiance is calculated for urban aerosol and a optical depths varying up to 0.5 with a step of 0.005 with the help ofthe Solis model [Müller 2004],
- a best fit is done between the SAF surface solar irradiance and the different RTM calculated curves with the limitation to sin h > 0.5 sin hmax in order to avoid bord effects,
- the corresponding aod is kept and attributed to the daily value.
The method is illustrated on Figure a-0.e
The clear sky surface solar irradiance is generally used as a normalization coefficient in the satellite data process. Therefore, the error done on the clear sky is then reported on the produced surface solar irradiance. Figure a-0.f illustrates the order of magnitude of the irradiance variation with the aod. Here, it can be seen that a 0.15 aerosol optical depth variation conduts to a 6% difference in the surface solar irradiance when doing the RTM calculation.
Figure a-0.e
Clear sky surface solar irradiance versus solar time. In blue the RTM calculation with different aod, and in red the values provided by the SAF. The red dashed line are the limit of application of the best fit.
University of Geneva Annexe I - 5 Pierre Ineichen Figure a-0.f
Clear sky surface solar irradiance versus the solar time for 4 different aerosol optical depths and calculated with the Solis model.
University of Geneva Annexe I - 6 Pierre Ineichen The Cabauw downward long wave irradiance correction
The quality control of the data from Cabauw pointed out some measurements artefacts.
This can be seen on Figure a-0.g where the CFIsat is represented versus the modified clearness index K’t. Following Dürr, the cloudless conditions should show CFIsat values up to -25% and should be negative. It is not the case here.
After verifications, the data acquired during the months of october 2005, January and April 2006 were done with a unshaded Eppley pyrgeometer. Following a study made by Ineichen [1984] on data from Geneva, it is possible to apply a correction proportional to the surface solar irradiance. It has the following form:
Ird(corrected) = Ird(meas.) - .018 Gh
The correction is illustrated on Figure a-0.h where the downward long wave irradiance is represented versus the time of the day for August 21, 1981. The shaded, unshaded and corrected measurements are plotted.
Applying such a correction on the data from the 3 concerned months show a much better Figure a-0.g
CFIsat calculated with raw data versus the modified clearness index K’t.
Figure a-0.h
Shaded, unshaded and corrected downward long wave irradiance versus the time of the day.
University of Geneva Annexe I - 7 Pierre Ineichen CFIsat representation versus the clearness index as illustrated on Figure a-0.i.
Figure a-0.i
CFIsat calculated with corrected data versus the modified clearness index K’t.
University of Geneva Annexe I - 8 Pierre Ineichen Figure a-1.2
Daily aerosol optical depth at 550 nm obtained from ground measurements, cm-SAF and osi-cm-SAF versus the day of the year in Camborne.
Figure a-1.3
Daily aerosol optical depth at 550 nm obtained from ground measurements, cm-SAF and osi-cm-SAF versus the day of the year in Carpentras.
Figure a-1.4
Daily aerosol optical depth at 550 nm obtained from ground measurementsand cm-SAF versus the day of the year in Geneva.
University of Geneva Annexe I - 9 Pierre Ineichen Figure a-1.5
Daily aerosol optical depth at 550 nm obtained from ground measurements, cm-SAF and osi-cm-SAF versus the day of the year in Lindenberg.
Figure a-1.7
Daily aerosol optical depth at 550 nm obtained from ground depth at 550 nm obtained from ground measurements, cm-SAF and osi-cm-SAF versus the day of the year in Lyon.
University of Geneva Annexe I - 10 Pierre Ineichen Figure a-1.8
Daily aerosol optical depth at 550 nm obtained from ground measurements and cm-SAF versus the day of the year in Toravere.
University of Geneva Annexe I - 11 Pierre Ineichen
University of Geneva Annexe I - 12 Pierre Ineichen Figure a-2.1
Modelled surface solar irradiance versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Cabauw.
University of Geneva Annexe I - 13 Pierre Ineichen Figure a-2.2
Modelled surface solar irradiance versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Camborne.
University of Geneva Annexe I - 14 Pierre Ineichen Figure a-2.3
Modelled surface solar irradiance versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Carpen-tras.
University of Geneva Annexe I - 15 Pierre Ineichen Figure a-2.4
Modelled surface solar irradiance versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Geneva.
University of Geneva Annexe I - 16 Pierre Ineichen Figure a-2.5
Modelled surface solar irradiance versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Lindenberg.
University of Geneva Annexe I - 17 Pierre Ineichen Figure a-2.6
Modelled surface solar irradiance versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Lyon.
University of Geneva Annexe I - 18 Pierre Ineichen Figure a-2.7
Modelled surface solar irradiance versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Payerne.
University of Geneva Annexe I - 19 Pierre Ineichen Figure a-2.8
Modelled surface solar irradiance versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Toravere.
University of Geneva Annexe I - 20 Pierre Ineichen Figure a-3.1
Modelled surface solar irradiance modified clearness index K’t versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Cabauw.
University of Geneva Annexe I - 21 Pierre Ineichen Figure a-3.2
Modelled surface solar irradiance modified clearness index K’t versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Camborne.
University of Geneva Annexe I - 22 Pierre Ineichen Figure a-3.3
Modelled surface solar irradiance modified clearness index K’t versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Carpen-tras.
University of Geneva Annexe I - 23 Pierre Ineichen Figure a-3.4
Modelled surface solar irradiance modified clearness index K’t versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Geneva.
University of Geneva Annexe I - 24 Pierre Ineichen Figure a-3.5
Modelled surface solar irradiance modified clearness index K’t versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Lindenberg.
University of Geneva Annexe I - 25 Pierre Ineichen Figure a-3.6
Modelled surface solar irradiance modified clearness index K’t versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Lyon.
University of Geneva Annexe I - 26 Pierre Ineichen Figure a-3.7
Modelled surface solar irradiance modified clearness index K’t versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Payerne.
University of Geneva Annexe I - 27 Pierre Ineichen Figure a-3.8
Modelled surface solar irradiance modified clearness index K’t versus the c o r r e s p o n d i n g
g r o u n d
measurements for the station of Toravere.
University of Geneva Annexe I - 28 Pierre Ineichen Figure a-4.1
Model-measurements mean bias difference versus the modified clearness index for the station of Cabauw.
University of Geneva Annexe I - 29 Pierre Ineichen Figure a-4.2
Model-measurements mean bias difference versus the modified clearness index for the station of Camborne.
University of Geneva Annexe I - 30 Pierre Ineichen Figure a-4.3
Model-measurements mean bias difference versus the modified clearness index for the station of Carpen-tras.
University of Geneva Annexe I - 31 Pierre Ineichen Figure a-4.4
Model-measurements mean bias difference versus the modified clearness index for the station of Geneva.
University of Geneva Annexe I - 32 Pierre Ineichen Figure a-4.5
Model-measurements mean bias difference versus the modified clearness index for the station of Lindenberg.
University of Geneva Annexe I - 33 Pierre Ineichen Figure a-4.6
Model-measurements mean bias difference versus the modified clearness index for the station of Lyon.
University of Geneva Annexe I - 34 Pierre Ineichen Figure a-4.7
Model-measurements mean bias difference versus the modified clearness index for the station of Payerne.
University of Geneva Annexe I - 35 Pierre Ineichen Figure a-4.8
Model-measurements mean bias difference versus the modified clearness index for the station of Toravere.
University of Geneva Annexe I - 36 Pierre Ineichen
University of Geneva Annexe I - 37 Pierre Ineichen Figure a-5
Model-measurements mean bias difference versus the solar elevation angle anf for the land-SAF solar surface irradiance.
University of Geneva Annexe I - 38 Pierre Ineichen Figure a-6.1
Relative frequency of occurence of the sur-face solar irradiance at the station of Cabauw
University of Geneva Annexe I - 39 Pierre Ineichen Figure a-6.2
Relative frequency of occurence of the sur-face solar irradiance at the station of Camborne.
University of Geneva Annexe I - 40 Pierre Ineichen Figure a-6.3
Relative frequency of occurence of the sur-face solar irradiance at the station of Car-pentras.
University of Geneva Annexe I - 41 Pierre Ineichen Figure a-6.4
Relative frequency of occurence of the sur-face solar irradiance at the station of Geneva.
University of Geneva Annexe I - 42 Pierre Ineichen Figure a-6.5
Relative frequency of occurence of the sur-face solar irradiance at the station of Lindenberg.
University of Geneva Annexe I - 43 Pierre Ineichen Figure a-6.6
Relative frequency of occurence of the sur-face solar irradiance at the station of Lyon.
University of Geneva Annexe I - 44 Pierre Ineichen Figure a-6.7
Relative frequency of occurence of the sur-face solar irradiance
Relative frequency of occurence of the sur-face solar irradiance