Marcel Suri
email: marcel.suri@jrc.it

Thomas A Huld
email: thomas.huld@jrc.it

Ewan D Dunlop
email: ewan.dunlop@ec.europa.eu

Michel Albuisson
email: michel.albuisson@ensmp.fr

Lucien Wald
email: lucien.wald@ensmp.fr

M Šúri

Online data and tools for estimation of solar electricity in Africa: the PVGIS approach

Keywords: HelioClim, PVGIS, geographical information system, solar radiation, PV system

come

INTRODUCTION

This paper presents interactive web applications for map-based query of a solar radiation database and for performance assessment of photovoltaic systems. The high-resolution database covers the Mediterranean Basin, Africa and South-West Asia. This satellite-derived database was developed to complement the existing radiometric ground network which consists of small number of heterogeneously distributed stations and which is not sufficient for developing detailed maps of solar energy resource.

At the Ecole des Mines de Paris/Armines, the Heliosat-2 method was developed to calculate global horizontal radiation from Meteosat satellite images. The database known as HelioClim-1 was created using Heliosat-2, and it can be accessed through the SoDa intelligent web system.

At the Joint Research Centre, the PVGIS (Photovoltaic Geographical Information System) has been developed and implemented for the European subcontinent. PVGIS integrates a geographical database with a solar radiation model and with tools designed for technical and economic assessment of the performance of solar photovoltaic systems.

The collaboration between Ecole des Mines de Paris and Joint Research Centre has brought an added-value to renewable energy users by an integration of a subset of the HelioClim-1 data into PVGIS, by their further processing and providing the geographical extension.

In this paper we present the PVGIS internet applications that give access to the subset of HelioClim-1 data by the means of map-based query and that enable a simple assessment of solar electricity generation for a chosen location. Besides the African continent, PVGIS covers also regions of the Mediterranean Basin and South-West Asia.

SOLAR RADIATION DATA IN THE PVGIS DATABASE

HelioClim-1 is a solar radiation database that was developed from Meteosat satellite images by the application of the Heliosat-2 method [1,2]. This database consists of daily values of global horizontal irradiation that were systematically calculated over the period 1985-2005. The spatial extent of the HelioClim-1 database corresponds to the field of view of the Meteosat Prime disc (the satellite being centered at latitude 0° and longitude 0°). The primary spatial resolution is about 15 arc minute, i.e. a grid cell close to the equator represents an area of about 30x30 km². The accuracy of the HelioClim-1 was assessed by comparisons with measurements of the WMO radiometric network in Europe (55 sites) and Africa (35 sites) for the period 1994-1997. The RMS error is 35 W.m -2 (17%) for daily mean irradiance, 25 W.m -2 (12%) for monthly mean irradiance, and bias is less than 1 W.m -2 for the whole data set.

The primary HelioClim-1 data (daily values and monthly averages) can be accessed through the SoDa web system [3]. However in such a form they can be used only by a limited number of experts. Therefore the HelioClim-1 data were integrated into PVGIS and processed to provide enhanced information and functionality.

The processing took place in the year 2005, therefore the PVGIS database includes values representing time period of 1985-2004. The solar radiation database for Africa consists of two segments:

Monthly and yearly averages

The first data segment contains HelioClim-1 long-term monthly and yearly averages of daily sums of global horizontal irradiation that were calculated from 20-years time series of daily values. The original data were converted to Lambert azimuthal map projection and their spatial resolution was enhanced using SRTM-30 digital elevation model [START_REF]SRTM30: 30-Arc-Second Elevation Data Set[END_REF] to 2x2 km 2 . The method is based on the use of solar radiation model r.sun, spatial interpolation and other tools implemented in the open source geographical information system GRASS [START_REF] Neteler | Open Source GIS: A GRASS GIS Approach[END_REF]. The data account for terrain shadowing by mountains as simulated in the 2-km grid resolution. More information about the methodology can be consulted in our previous publications [START_REF] Šúri | [END_REF]7,[START_REF] Huld | 20 th European Photovoltaic Solar Energy Conference and Exhibition[END_REF].

To allow for calculation of solar electricity from PV modules at arbitrary inclination and orientation, the diffuse component is needed. To estimate it, we have implemented the Page model [START_REF] Page | United Nations Conference on New Sources of Energy; Solar Energy, Wind Power and Geothermal Energy[END_REF]: We took the point values of the clearness index from the NASA SSE (Surface meteorology and Solar Energy) reference sites [START_REF] Chandler | [END_REF] and interpolated them over the region. This resulted in grid data layers with 2-km grid resolution representing monthly averages of diffuse horizontal irradiation. However it should be noted, that due to uneven distribution of the input data and their absence over the ocean, the Page model provides only approximate estimation of the diffuse component of global irradiation.

An example of the solar radiation database is shown in Figure 1 that shows yearly average of daily global horizontal irradiation, optimum inclination angle of equator-facing PV modules to maximize energy yield, and the average daily global irradiation at this angle.

Probability distribution statistics

The second segment contains probability distribution statistics of daily global horizontal irradiation for each month and year. It is kept in the geographical longitude/latitude coordinate systems with 15 arc-minute grid resolution. These data were calculated from the original HelioClim-1 daily values by categorizing them into bins, each with a width of 500 Wh m -2 . The distribution statistics makes it possible to derive a histogram for each location in the region for the whole year or the chosen month. The values represent larger areas (about 30x30 km² at the equator) without considering the possible shadowing by local terrain. Therefore in a complex terrain the local variation may differ from the regional pattern represented in this segment of the database.

PVGIS outputs

The database, in combination with developed tools, is used for calculation of various outputs related to solar electricity generation. The values represent long-term monthly and yearly averages of the period 1985-2004: • global irradiation for horizontal and inclined surfaces and its beam, diffuse and reflected components; • clear-sky and real-sky daily profiles of irradiances for each month for arbitrary inclined and oriented surface (considering also terrain shadowing); • electricity generation from fixed and tracking PV systems; • display of local horizon;

• optimum inclination and orientation of fixed PV modules to maximize solar energy yield; • cumulative yearly and seasonal histograms showing probability distribution of daily global radiation. Besides the above mentioned climatic data, the system also contains other geographical data, such as digital elevation model, Global Land Cover 2000 [START_REF]European Commission[END_REF], and basic vector layers of administrative boundaries, cities, and rivers. These data were also used for preparing maps to facilitate location and selection of a suitable site for solar energy systems, using the online web tools.

ONLINE TOOLS FOR SOLAR ELECTRICITY ESTIMATIONS

To provide access to the PVGIS data and software over the Internet we have developed a set of interactive applications. The web interface is designed to give information on solar radiation and PV electricity generation in the form of maps, graphs and tables for any location in the region. A location can be chosen either by browsing/zooming and clicking on a map, choosing a country and a settlement from the list, or directly by setting latitude/longitude values. The output data are 3 displayed in a separate window. The elevation and landcover maps, as well as climatic and PV-potential maps provide an overview of the spatial variability of the data. The web interface is organized into three separate applications.

Querying maps of solar irradiation and related climatic data

This application provides long-term monthly and yearly averages of global irradiation at horizontal and inclined surfaces, as well as Linke turbidity, ratio diffuse/global irradiation and the estimation of optimum inclination angle of the PV modules to maximize yearly energy yield. For a chosen location, an estimation of the relative deficit in yearly horizontal irradiation due to terrain shadowing is also displayed. The data displayed represent a grid cell with 2-km spatial resolution.

Upon request, the application generates on-the-fly cumulative probability distribution of daily global horizontal irradiation for the whole year as well as for March, June, September and December. As these data are processed at lower spatial resolution (grid cell 15-arc minutes), the histograms outline the distribution of values within a larger area and do not take into account local differences in the terrain elevation and shadowing.

Estimation of the average daily variation of global irradiance

For a chosen inclination and orientation of a module, the user can request an average daily profile of clear-sky and real-sky irradiances for a chosen month. As an option the system can also display the daily irradiance profile received by a 2-axis sun-tracking system. The calculation of the daily variation in solar irradiance is performed on request by a separate program running on the server. The calculation also takes into account the shadowing by local terrain features (at the 2-km data resolution).

Estimation of potential solar electricity generation

This application calculates the yearly potential electricity generation E [kWh] from a PV system with fixed-mounted modules at chosen inclination/orientation, and alternatively for 2-axis tracking systems, using the formula:

E = 365 P k r p H h,i

where P k (kW) is the peak power installed, r p is the system performance ratio (a typical value for a system with modules from mono-or polycrystalline silicon is 0.75) and H h,i is the monthly or yearly average of daily global irradiation on the horizontal or inclined surface. The system performance ratio of 0.75 assumes system losses 25% as default, where 9% is assumed as an 'average' loss due to temperature effects and the remaining 16% can be modified by the user.

Upon request, the calculator calculates the optimum inclination/orientation of the PV modules to harvest maximum electricity over the whole year. It also provides estimates for 2-axis tracking systems. For the chosen location, the system outputs a graph of the local horizon outline (based on the 2-km digital elevation model).

Other technical aspects

At present, the interactive system communicates in five languages -English, French, German, Italian and Slovak. For all three applications the maps have been calculated beforehand while the calculations for a single (user-defined) location are performed upon request. Since these calculations are rather computing-intensive, a number of steps have been implemented to optimize their speed. Calculations are performed by stand-alone programs written in the C language on the web server, thus the calculation times do not depend on the speed of the users' computer. This makes it much faster than if the program was written in one of the scripting languages for the web (such as PHP or Perl). The data are stored in binary form with a constant record length for each grid point. In this way, the reading of input data is an O(1) operation, independent of the size of the data set. The total amount of database is approximately 7 GB for the present dataset with ~20 million grid points. Apart from the programs calculating the irradiance and irradiation, most parts of the web applications are written using server-side scripting, primarily PHP. The use of client-side scripting (JavaScript) is kept to a minimum to enable access also to users with limited computing resources.

APPLICATION OF PVGIS

Although the original HelioClim-1 data are accessible from the SoDa web site, the PVGIS database and the map-based approach provides an improved understanding of the spatial variability of the solar energy resource and PV performance in regions. Figure 1 shows that the latitudinal trends in global irradiation are modulated by patterns of atmospheric turbidity, cloud structures, and terrain elevation (including shadowing). There is a significant geographical and seasonal variation of global irradiation over the African continent and South West Asia, with values varying by almost a factor of 2. Thus, besides geographical latitude the variation is strongly determined by regional climatic features (compare to [START_REF] Diabaté | [END_REF]). In dry regions, such as the Sahara and Kalahari deserts, or parts of the Arabian Peninsula, the irradiation is very high, while in the tropical rainforest regions (such as the Monthly averages of daily global irradiation are used for the estimation of the PV electricity output (Figure 2). For example, assuming a small 100 W p stand-alone PV installation with a battery and battery charger, together with a performance ratio of 0.75, the power production ranges from about 300 to 600 Wh per day in most locations in Africa and South West Asia, except in winter seasons in the extreme North and South. This energy is sufficient to drive 3 energy-efficient lights for 6 hours per day, or 3 energy efficient lights for 4 hours plus a radio, or a pump to deliver 3000 litres of water from a depth of 20 meters. Note that this calculation does not take into account possible losses due to the saturation of the battery capacity.

The seasonal variation of PV electricity is locationdependent. In regions with dry climate, the energy produced is generally higher but with higher seasonal variation, especially in the northernmost and southernmost latitudes. On the other hand, in humid equatorial climates, such as the Congo River Basin, the level of production is lower with low seasonal variation.

For design of stand-alone PV systems in a chosen location, the seasonal variation must be considered to avoid periods of insufficient power production. The cumulative probability distribution of daily irradiation, can be used to assess the probability of reaching the satisfactory level of irradiation input each month. As shown on the example (Figure 3), in Aswan the seasonal effects are well pronounced and it is much more likely that the daily irradiation will be near the maximum (clear-sky) irradiation in each season of year. In contrast, in Kinshasa very high irradiances are rare and the distribution of daily irradiation values within the year is rather broad with a very stable seasonal pattern. The availability of daily irradiation values in the original HelioClim-1 database makes it possible to optimize PV system components. For example, assuming a certain daily energy consumption, it is possible to estimate the optimum size of the PV module and the size of the battery as demonstrated in a previous paper [7]. However this option of the system sizing is not yet accessible via the web interface.

CONCLUSIONS

PVGIS provides an interface to a geographical database and tools designed for the assessment of photovoltaic systems. The solar radiation data derived from satellite images and processed in GIS open new horizons to a better understanding of spatial and time variability of the solar energy resource and pathways of its exploitation for satisfying growing energy needs.

Enhancement of the original HelioClim-1 data and web access provides opportunities for improved optimization of the design of the stand-alone and gridconnected systems for any chosen location in the region. The tools can be used by decision-makers, local professionals, or international aid agencies to improve the use of the financial resources for rural electrification.

PVGIS provides only overview information about PV system performance. Those interested in more detailed system design, can use the PVGIS solar radiation data as an input into available software tools, such as RETscreen [START_REF]RETScreen International Clean Energy Decision Support Centre[END_REF]. Professional applications need more detailed data analysis that can be requested at the SoDa web site [3].

More information on the methodology, accuracy, static maps and animations and other resources can be found on the PVGIS web site [14].

Figure 1 :

 1 Figure 1: a) yearly average of daily global horizontal irradiation (Wh m -2 ); b) optimum inclination angle of fixed equatorfacing PV modules to maximize energy yield (degrees); c) yearly average of daily global irradiation on a plane inclined at the optimum angle (Wh m -2 )

Figure 2 :

 2 Figure 2: Seasonal variation of the monthly PV electricity generation from a 100 W p system with modules in horizontal position in Aswan (Egypt; kWh)

Figure 3 :

 3 Figure 3: Cumulative probability distribution of daily global horizontal irradiation (Wh m -2 ) in a year in Aswan (Egypt) in the period 1985-2004

  Šúri M., Huld T.A., Dunlop E.D., Albuisson M.,Wald L, 2006. Online data and tools for estimation of solar electricity in Africa: the PVGIS approach. Proceedings from 21 st European Photovoltaic Solar Energy Conference and Exhibition,4-8 October 2006, Dresden, Germany (preprint)

	1. Long-term monthly and yearly averages of daily
	global and diffuse horizontal irradiation. This
	segment was spatially enhanced by digital elevation
	model to 2-km grid resolution.
	2. Probability distribution statistics of daily values of
	global horizontal irradiation that is kept in the
	original data resolution (15 arc-minutes).

  Šúri M.,Huld T.A., Dunlop E.D., Albuisson M., Wald L, 2006. Online data and tools for estimation of solar electricity in Africa: the PVGIS approach. Proceedings from 21 st European Photovoltaic Solar Energy Conference and Exhibition,4-8 October 2006, Dresden, Germany (preprint)

  Šúri M.,Huld T.A., Dunlop E.D., Albuisson M., Wald L, 2006. Online data and tools for estimation of solar electricity in Africa: the PVGIS approach. Proceedings from 21 st European Photovoltaic Solar Energy Conference and Exhibition, 4-8 October 2006, Dresden, Germany (preprint) 4 Congo River Basin) it is much lower, especially near the Western coast.


M Lefèvre

S Cros

M Albuisson

L Wald

Developing a database using METEOSAT data for the delivery of solar radiation assessments at ground level

Keywords: Remote sensing, Meteosat, solar radiation, climatology, database, information system

An information system, called HelioClim, is offered for answering the needs for long-term time-series of solar radiation data. These data originate from the processing of spaceborne observations made in the visible range by geostationnary satellites to derive solar radiation available at ground level. The recent method Heliosat 2 is used. It offers several improvements in operation and accuracy with respect to previous methods. Typical bias for irradiance for a month is 3 W m -2 . A database is being produced, covering the Eastern Atlantic Ocean, Europe and Africa from 1985 onwards and for each day. This database is accessible through the SoDa service on a free basis (http://www.soda-is.com).

INTRODUCTION

Time series of solar radiation at ground level open the way to many applications for different users. Biomass production and crop forecast, oceanography and limnology applications, urban air quality studies, sizing of space borne sensors, solar energy engineering or even the optimization of daylight use in building applications, are among the various domains needing solar radiation information.

Researchers and engineers are facing the problem of solar radiation data retrieving on various parts of the world. Several studies assessed the user needs for solar radiation data [START_REF] Esra | European solar radiation atlas)[END_REF]. These needs consist generally in values of hourly or daily global irradiation and their derived quantities (diffuse component, spectral distribution, spatial structure of the radiation) for various part of the world. Accordingly, databases should be available that cover the whole earth surface for several years. These data should be available at high spatial resolution (about 10 km in size) with a relative accuracy less than 20 % in root mean square error (RMSE) for the daily irradiation. The data should present a convenient and low cost access. Even if several initiatives have been made to answer these requirements [START_REF] Fontoynont | Satel-Light: a WWW server which provides high quality daylight and solar radiation da-ta for Western and Central Europe[END_REF][START_REF] Heidt | Satellite-based solar radiation data go Internet[END_REF][START_REF] Cros | Survey of the main databases providing solar radiation data at ground level[END_REF], there is still a discrepancy between user needs requirements and availability of solar radiation data [START_REF] Mayer | The availability of irradiation data, presented at Energy International Agency, Task II -Operational Performances of PV systems[END_REF].

We propose an answer by building an integrated information system called HelioClim. It contains a database of global irradiation routinely estimated from a times-series of Meteosat images from 1985 onwards and a software to exploit it.

This paper presents briefly the Heliosat-2 method, which converts satellite images into global irradiation maps. It then presents the climatological database building. Finally, we describe the exploitation software of that database.

SOLAR RADIATION MAPPING FROM SATELLITE IMAGES: THE HELIOSAT-METHOD

Once properly processed, such Meteosat images can produce maps of solar radiation which are more accurate than those obtained from interpolation of measurements of radiation made at ground level [START_REF] Perez | Comparing satellite remote sensing and ground network measurements for the production of site/time specific irradiance data[END_REF][START_REF] Zelenka | Effective accuracy of satellite-derived hourly irradiances[END_REF]. Several methods are available for this processing. When operated on a routine basis, many of them exhibit several drawbacks, one of them being the poor accuracy in irradiance (Rigollier and Wald, 1999a).

A new method, called Heliosat-2, has been designed that is capable of processing long time-series of images acquired by the series of sensors aboard the Meteosat satellites. The method is using the same principle than several methods of proven quality [START_REF] Pastre | D•veloppement d'une m•thode de d•termination du rayonnement solaire global OE partir des donn•es Meteosat[END_REF]M€ser andRaschke, 1983, 1984;[START_REF] Cano | A method for the determination of the global solar radiation from meteorological satellite data[END_REF][START_REF] Diabat | Estimating incident solar radiation at the surface from images of the Earth transmitted by geostationary satellites: the Heliosat Project[END_REF][START_REF] Beyer | Modifications of the Heliosat procedure for irradiance estimates from satellite images[END_REF][START_REF] Stuhlmann | An improvement of the IGMK model to derive total and diffuse solar radiation at the surface from satellite data[END_REF][START_REF] Delorme | Quick use of Wefax images from Meteosat to determine daily solar radiation in France[END_REF]. With respect to these methods, Heliosat-2 offers several improvements in operation and accuracy. These improvements are due to several causes. Main improvement is due to an accurate calibration of the Meteosat data to convert them into radiances and reflectances. More physical description of the optical processes was made possible by the calibration step; known proven models are implemented in the method. The will-proven ESRA model describing the irradiation under clear-skies is used (Rigollier et al. 1999;[START_REF] Geiger | A web service for controlling the quality of measurements of global solar irradiation[END_REF]. The optical effects of the atmosphere are modeled by the Linke turbidity factor. We use a new database of monthly values of the atmospheric optical turbidity for clear skies available on cells of 5' of arc angle in size at SoDa web site: http://www.soda-is.com (Lefƒvre et al. 2003;[START_REF] Remund | Worldwide Linke turbidity information[END_REF]. We use terrain elevation TerrainBase (NGDC-NOAA). The model for the irradiation under heavily covered skies calls upon climatological knowledge (Rigollier and Wald, 1999b). Observations of [START_REF] Taylor | Reflectance characteristics of uniform Earth and cloud surfaces derived from Nimbus 7 ERB[END_REF] were used to model the spatial distribution of radiances of the very thick clouds. Changes in ocean albedo due to sun glitter are taken into account.

We made comparisons between satellite-derived assessments and measurements performed in the world radiation network in Europe and Africa. The results depend upon several parameters; the type of data (high-resolution or B2 format) and the number of pixels whose values are averaged for the comparison with the irradiation measurements.

As for the high-resolution data, assessments were compared to observations made by 60 stations in Europe for one year. The bias and root mean square error (RMSE) for the assessment of the irradiance for a month are equal to respectively 2 and 11 W m -2 on cells of 5' of arc angle in size (approx. 10 km at midlatitude). The RMSE may decrease down to 4 W m -2 if assessments are averaged over cells of 0.5" of arc angle.

DESIGN AND BUILDING OF HELIOCLIM

The B2 format

The processing of satellite data may prove to be very time and memory consuming; depending upon the provider, the costs for purchasing data may also be important. Eumetsat agreed to provide us Meteosat images in the reduced resolution ISCCP-B2 (Schiffer andRossow, 1983, 1985) format from 1985 up to now. Spatial support information of these B2 images is a pixel of 10 km in size available every 60 km in each direction (figure 1). Such images are available every 3 hours. These images cover one third of the earth, including Europe, Africa and Atlantic Ocean (figure 2). Satellite-derived assessments performed from B2 images give worse results. Comparisons were performed using 60 stations in Europe and 30 stations in Africa for the same year. The bias and RMSE are better than respectively 3 and 17 W m -2 for one month and a cell of 5'. The RMSE decreases to 9 W m -2 for cells of 0.5" in size.

Design of the database

From 1985 up to now, the time-series of images represents about 6 billions of values to be processed by Heliosat-2 and they must be stored in an appropriate database. Pixels outside of the earth images and unusable for the processing are rejected; there remains approximately 118 500 pixels per image. This number may be compared to the 70 sites offering daily values for a period of similar duration that are available for Europe [START_REF] Esra | European solar radiation atlas)[END_REF] and the 30 stations in Africa with daily values for more than four years available through the WMO World Radiation Data Center (WRDC).

An important aspect of the requirements is that the large majority of customers requested time-series for a specific location and not time-series of gridded (maps) values. We decided to discard the image structure and to shape the database to facilitate the search for time-series for a given location. The requested location is usually not a B2-pixel. It follows that answering a request needs the extraction of time-series of the nine neighbourhood B2-pixels and the interpolation of each daily value.

The cloud index [START_REF] Cano | A method for the determination of the global solar radiation from meteorological satellite data[END_REF]) has been selected to be stored into the database. This value ranges from -0.2 to 1.1. It is a convenient value to compute global irradiation. It can be included in a byte. This value is stored with the number of the slot associated, which needs one more byte. Finally, one year of solar data is stored in a file of one gigabyte. These files are in a binary format. Each record is identified by a number comprised between 1 and 118500 called "pixel identifier" and each field corresponds to the julian day of the year (figure 3).

Pixel identifiers

Julian days 1 2 3 … 366 1

For each slot (cloud index, slot number value)

2 3 … 118500
Figure 3: Scheme of a yearly file of data, each couple of values (slot, cloud index) is stored in a cell identifiable by the pixel identifier and the julian day

Building of data files

B2 images were quality-controlled by visual inspection for geometrical superimposition, for radiometric defects (the so-called "fishes") and any other aspects. Then an automatic process performs the first steps of the Heliosat-2 method and converts the Meteosat images into cloud index images. These temporary images feed the cloud index database. It performs on a series of images contained in a given directory. The image files were named in such a way that the name contains all information that is necessary for the processing, namely instant of acquisition by the sensor. For each image, there is a request to the database of the calibration coefficients through a call to the server www.helioclim.net. Heliosat-2 algorithm needs values of the Linke turbidity factor and the orography. The software calls also these databases through the SoDa server. Figure 2 recapitulates the process of the cloud indices storage.

EXPLOITATION OF THE DATABASE

To exploit this database and answer user request, an exploitation software was devised that executes itself quickly. It is triggered by a request send by the SoDa intelligent system (SoDa-IS, Wald et al. 2002). The customer connects to the web server So-Da and the SoDa-IS builds automatically the interface appearing in the standard browser. The SoDa-IS transmits geographical coordinates and time period selected to the exploitation software via the HelioClim server. This software extracts the cloud index value from the 9 nearest pixels around the desired location, computes the irradiation for these 9 pixels by calling resources necessary for Heliosat-2: the ground elevation and the turbidity of Linke. These data are available through the SoDa server [START_REF] Wald | SoDa: a project for the integration and exploitation of networked solar radiation databases[END_REF]. Then, the software proceeds to a spatial interpolation [START_REF] Lefƒvre | Study of effective distances for interpolation schemes in meteorology[END_REF] for each instant and constructs the resulting time-series. Figure 5 presents the exploitation scheme.

Outputs are various values of the irradiation (daily sum, monthly mean, 5-day sum of daily irradiation, 10-day sum of daily irradiation, monthly sum...). These values are then XML encoded and sent to the SoDa-IS for delivery to the customers.

CONCLUSION

We built a database and its software exploitation. This database gives solar data covering Europe, Africa and Atlantic Ocean from 1985 onwards with a resolution of 5 minutes of arc angle (about 10 km at mid-latitude). These data are available on a free basis via the SoDa server. Validation was performed by comparing the outputs of the SoDa server to ground measurements for one year. The bias and the relative RMSE are respectively 3 and 17 W.m -2 for the irradiance over one month. Efforts are underway for a validation over a period of 12 years for sites in Europe and Africa.

Figure 1 .

 1 Figure 1. Scheme showing the sub-sampling in the B2 format.

Figure 2 :

 2 Figure 2: B2 format image

Figure 4 :

 4 Figure 4: Operational scheme of the cloud indices database building

Figure 5 :

 5 Figure 5: Scheme of the database exploitation

Table of

 of

pixel identifiers


S Cros

L Wald

Survey of the main databases providing solar radiation data at the ground level

Keywords: solar radiation, database, information system, climatology

Solar radiation at ground level is a necessary input for several applications such as primary production and agronomic related studies or potential solar energy assessments. The user needs consist generally in values of global daily or hourly irradiation with a spatial resolution of approximately 10 km. Relative errors (RMSE) of daily irradiation should be less than 20 %. Spatial coverage (continent) and temporal coverage are of importance. The data must be available conveniently at low cost. Several regional solar atlases have been made by interpolation of ground measurements, taking into account the local variation of climate. Satellite data produce irradiation maps offering a regular sampling in space and a wide geographical coverage. Time-series are also obtained by weather forecast models. Digital atlases have been created as integrated information system. They comprise a database and software to exploit it. The co-operative systems are connected with other servers that provide necessary weather data to compute solar radiation quantities. This survey of solar databases showed that in a general case, there is a discrepancy between users needs and available databases. This conclusion supports the efforts made in integrating information systems and co-operative systems to overcome the technical limits of measurements by using the information and communication technologies.

INTRODUCTION

Incident downwelling solar radiation at ground level is a key input for several applications. Solar energy engineering, optimization of daylight use in building applications, biomass production and crop forecast, oceanography and limnology applications and urban air quality studies or even the sizing of space borne sensors are among the various domains needing solar radiation information.

Researchers and engineers are facing the problem of solar radiation data retrieving on land or on oceanic surfaces. Their needs consists generally in values of hourly or daily global irradiation and its derived quantities (diffuse component, spectral distribution, spatial structure of the radiation) for various part of the world. Accordingly, databases should be available that cover the whole Earth surface for several years. These data should be available in a high spatial resolution (about 10 km in size) with a relative accuracy of 20 % in root mean square error (RMSE) for the daily irradiation. The data should present a convenient and low cost access.

The access to the relevant information is poor for many reasons. The number of stations measuring irradiation is too small to achieve an accurate worldwide coverage. Access is generally complicated by the various type of data, various storage standards, various units, various way of expressing time … Space and time characteristics of presently available data are often unsatisfactory. Most often, raw measurements stored and supplied by the present databases are not matching to actual users needs.

Nevertheless, efforts have been made to collect, store and disseminate such information with respect to the user needs.

This paper presents a survey on the main possibilities offered for retrieving solar irradiation values at ground level. This study has been performed by analyzing different information sources of focused data and their characteristics having major interest to users. One can see that regions are better covered than others. The network is very dense in Western and Central Europe and Japan. The coasts of Australia are well covered but not the inland. There are large parts of the world that are mostly unknown.

Estimation of the solar irradiation at each point of a zone needs consequently to proceed with interpolations or extrapolations of measurements. This method induces some errors due to the distance between two stations. Climatic zones difference between measurement sites is also a source of errors.

Several studies have been performed to retrieve solar radiation by this way [START_REF] Hay | The mesoscale distribution of solar radiation at the Earth's surface and the ability of satellites to resolve it[END_REF][START_REF] Hay | An assessment of the mesoscale variability of solar radiation at the Earth's surface[END_REF][START_REF] Hay | Evaluating the solar resource: a review of problems resulting from temporal, spatial and angular variations[END_REF]Perez et al. 1997;Supit 1994Supit , 1998;;Zelenka et al. 1992). It was shown that daily values measured at a station may be considered valid in an area of 30 km of radius. The validity area of a daily measurement is taken as a square of 0.5 degrees (approx. 60 km) in size. If we limit ourselves to the land masses (30 % of the Earth surface), and assuming that the 751 stations were equally distributed (which is wrong as shown in the map on figure 1), the probability of being in the vicinity of a station is equal to 1 %. In other terms, in 99 % of cases, the stations are too far to deliver an accurate information to users. Considering only Western and Central Europe, outside Scandinavia, the number of stations is large: 2030 stations, of which 214 are measuring the global irradiation and 890 the sunshine duration. In that case, the probability of being in the vicinity of a station amounts to 7 %. That is 93 % of sites are too far from stations.

These numbers should be considered with care. In many countries, more radiometric stations are available than those reported to the WMO. For example, Germany and United Kingdom total more stations than the 214 reported above for Europe. In addition, parallel networks exist, e.g. for agriculture or hydrology purposes, that are unknown to the WMO and not managed by the weather bureaus. Their data are usually available to other users. However, it remains that the density of the networks is too small for the delivering of accurate data according to users needs.

Access to the data

Getting the data physically is not always simple. They are usually provided by the weather bureaus in each country. Sometimes, centralized access is possible. For example, the World Radiation Data Center (WRDC) offers an on-line access to archived data for many countries.

Measurements are most often made on a daily basis and not hourly basis, except for a limited number of countries. Users should find models that synthesize hourly irradiation from a daily irradiation. These models call upon statistical knowledge on the hourly profile that is not available at most stations and should be inferred from other stations performing hourly measurements. A good point is that long series of records are most often available in stations.

Another good point is that data are in digital form, even for the past years which have been digitized. The accuracy is excellent if the instrument is well maintained.

Access is further complicated by the various types of data (hourly or daily measurements, global and diffuse irradiation, sunshine duration) that are available for the countries of interest. If collected in several countries, these data have various storage standards and various units (e.g., J/cm 2 , J/m 2 , Wh/m 2 , cal/cm 2 ). Various ways of expressing time (coordinated universal time, mean solar time, true solar time, local time) are used. A standard exists within the WMO for defining hourly measurement: the hour allotted to the data is the end of the measuring period (e.g., data at 12h is the measurement made between 11 and 12h). It is not always the case in other networks, where the hour may be the beginning of the measuring period or the middle of the period.

A particular case : the Baseline Surface Radiation Network

The Baseline Surface Radiation Network (BSRN) is a project of the World Climate Research Programme (WCRP). It aims at detecting important changes in the Earth's radiation fields which may cause climate changes. At a small number (less than 40, see figure 2) of stations in contrasting climatic zones, covering a latitude range from 80°N to 90°S, solar and atmospheric radiation is measured with instruments of the best accuracy available and at a very high (minutes) frequency. The radiation data are stored together with collocated surface and upper-air observations in an integrated database. The bias is usually very small. Compared to the models based on cloud cover or sunshine duration, the accuracy seems to be similar in regions with very dense radiometric networks (Perez et al. 1997;Zelenka et al. 1992). In other parts, while the accuracy of the models degrades with usually an increase in bias, that of satellite-derived assessments remains the same.

Probably the most known of these initiatives is the ISCCP program (International Satellite Cloud Climatology Project) and its brother, the SRB (Surface Radiation Budget) program which freely provide maps of the monthly-averaged daily irradiation for the entire world on cells of 280 km in size. These satellite-derived maps offer a knowledge of the radiation at any site in the world. The SRB data are of easy access and are delivered by the NASA (Figure 3). They are monthly means of daily irradiation, available for several years and covering the whole world.

Figure 3. Example of information that is available for the whole world derived from the NASA Surface Radiation Budget project. This is the annual irradiance (energy flux). Units are kLangley. Values are to be multiplied by 1.33 to obtain W/m 2 . Copyright CIBA.

The NASA Surface Solar Energy Data Set is derived from the SRB data set and intends to serve solar energy purposes. Figure 4 is an example of the maps that can be obtained through this server for Brazil. The spatial description is coarse due to the large size of the cell. Apart from these international programmes and the NASA programme, several weather bureaus are performing routine processing of satellite images to derive hourly or more frequently maps of irradiation over large areas. These data are used for weather forecasts and can be delivered to users. Australia, France, Germany, Hungary or United States are known weather bureaus offering products of high quality. Australia delivers such information free of charge on Internet (figure 5). The spatial resolution of the maps is better than those provided by the international programmes. The spatial distribution of the radiation is much more detailed. Such maps are more than nice pictures. They show the spatial distribution of the solar radiation at ground level. They demonstrate the relationships between the radiation and latitude, geographical features and orography.

Apart from the weather bureaus, several initiatives established databases that can be accessed to by customers, on a free basis or at moderate costs. The Satel-Light server delivers information of statistical type (i.e., cumulative frequencies) for Europe. The server of the University of Siegen [START_REF] Heidt | Satellite-based solar radiation data go Internet[END_REF] provides global hourly irradiation over Europe. The SoDa server offers time-series of daily irradiation over Europe, Africa and the Atlantic Ocean.

Several servers deliver maps of irradiation. However, these maps cannot be integrated in the softwares used for modelling the solar systems, except integrated information systems. It follows that most servers propose an access to their satellite-derived databases under the form of time-series for a given location.

RE-ANALYSES OF WEATHER FORECAST

Models for weather forecasts are used in a reanalysis mode to reproduce what was effectively observed. The global radiation, called downward shortwave radiation in such models, is one the modelled parameters. It is usually expressed as irradiance (energy flux, W/m 2 ) instead of irradiation (energy, J/m 2 ). Models may deal with the whole world or be of regional impact. The grid cell is ap-proximately 1 -2 '. Daily values are usually offered. Time-series originate from 1960 approximately.

The SoDa server offers an access to the global daily irradiation derived from the outputs of the NCEP/NCAR re-analyses together with other meteorological parameters.

INTEGRATED INFORMATION SYSTEM

An integrated information system is a database completed by a software. Digital atlases have been recently created which are more relevant to the field of renewable energies. Presented on CD-ROMs or online through the web, they comprise a database (maps, time-series of ground measurements, synthetic reference years, geographical information...) and software to exploit it (user interface, data management, result presentation, import-export capabilities...). The software also includes models for the computation of parameters of higher level such as direct and diffuse components or spectral distribution of irradiation or photosynthetically active radiation (PAR).

Meteonorm

Meteonorm ( 2000) is a digital solar atlas presented on CD-ROM. It contains a database of ground stations measurements made by a combination of several databases from different parts of the world (Swiss meteorological institute, GEBA, WMO …). The main period of the measurement is from 1961 to 1990. Other climatological data useful for renewable energy engineering are also available (temperature, humidity, wind speed, precipitation).

The software included in this atlas permits to retrieve radiation data by a model of interpolation. It contains also algorithms to calculate radiation on inclined surface. Radiation data provided by this tool are available in various units according the user need.

Satel-light

The European Union funded Satel-Light project offers a database of solar radiation data derived from satellite images, which can be accessed through the world wide web and produces value-added information mostly for daylighting purposes [START_REF] Fontoynont | Satel-Light: a WWW server which provides high quality daylight and solar radiation data for Western and Central Europe[END_REF]Reise et al. 1999). The database covers the European continent for a period comprised between 1996 and 2000.

Though limited to the solar energy domain, these atlases and servers are excellent examples of what can be done to bring to users the information they require starting from basic meteorological measurements.

The European Solar Radiation Atlas (ESRA)

This atlas is an instrument dedicated to providing knowledge and aiding exploitation of the solar resources across a wide sweep of Europe, from the Urals to the Azores and from Northern Africa to Polar Circle. The input data are based on the period 1981-1990. This atlas provides a broad overview with supporting maps. It starts by describing the course of the Sun across the sky as it varies across the year with geographical location. Then the interactions of the solar radiation with the atmosphere and its components (haze, turbidity, clouds, etc.) and the separation of the solar radiation into the direct and diffuse parts are discussed. Sixteen colored maps provide data on the monthly mean global, beam, diffuse irradiation on horizontal surface and the clearness index for March, June, September and December. The mapped values are averages over the 10-year period 1981-1990. Additionally there are the corresponding four annual maps, also a country-based relief map and a map of ground observing stations used. There are two special maps giving zones of similar irradiation and zones of similar biomass productivity.

The CD-ROM contains a database, which offers spatial (every 10 km approximately) and temporal climatic information for different time scales (from climatological means -more than 700 stations -to hourly values -7 stations). It includes the solar resources: irradiation (global and its components), sunshine duration, as well as air temperatures, precipitation, water vapour pressure, air pressure for a number of stations. The CD-ROM also contains the software to exploit the database.

The software uses either a "map" or a "station" mode at user choice. In the first case, any geographical site can be designated. In the second mode, only the available measuring stations can be selected. The software includes algorithms covering the following fields: solar geometry, optical properties of the atmosphere, estimation of hourly irradiation on slope under cloudless skies, estimation of solar irradiation values (going from daily to hourly values, conversion from horizontal to tilted surfaces), spectral irradiance, illuminance, daily mean profiles of temperature and other statistical quantities (central moments, extremes, probability, cumulative probability and utilisability curves). Graphics can be displayed in two or three dimensions. Applications in solar engineering can be handled. A few new algorithms were developed. Among them is a model for the assessment of the irradiance and irradiation under clearsky conditions developed by Page (1995), which was proved to perform in checks by independent authors (Rigollier et al. 2000).

Maps are one attractive aspect of the ESRA. Spatial interpolation techniques do not lead to satisfactory results for meteorological parameters. For a start, terrain height is so impactive. Hence, maps were constructed only for solar radiation, its components and the clearness index. An innovative method was developed, following the path shown by Zelenka (1994), and based on the fusion of ground-measured data and satellite-derived maps of radiation [START_REF] Beyer | Assessment of the method used to construct clearness index maps for the new European Solar Radiation Atlas (ESRA)[END_REF].

The ESRA continues, at enlarged scale, the previous work of the European Commission on solar radiation mapping (Commission of the European Communities, 1984aCommunities, , b, 1997) ) and complements similar works in other European programmes, e.g., the European Wind Atlas (Troen, Petersen 1989), the Solar Radiation Atlas of Africa (Raschke et al. 1991). These atlases are on paper only. Compared to them, the ESRA benefits from the advances in information technologies. Databases are available, digital values can be exported, interactivity is everywhere, complex computations can be performed. The elevation of any geographical location is embedded in the database. In addition, the ESRA offers map capabilities, which are presently unique in solar radiation atlases

The CD-ROM-based atlases have their advantages and limitations. Further progresses in the dissemination of information on solar radiation and resources are expected due to the world wide web capabilities. This approach is already demonstrated by the co-operative information systems.

CO-OPERATIVE INFORMATION SYSTEM

Such an information system is essentially based on the benefit of an interactivity between different web servers. Information-delivery system is co-operating with other servers that provide the necessary weather data. The two following examples presents clearly the advantages of such co-operation.

The RETScreen system

The RETScreen system calls upon data from the NASA Surface Solar Energy Data Set. The user is invited to copy outputs of the NASA server and paste them into the input table of the RETScreen software. The RETScreen International Photovoltaic Project Model (version 2000) can be used worldwide to easily evaluate the energy production, life-cycle costs and greenhouse gas emissions reduction for three basic PV applications: on-grid, off-grid, and water pumping. For on-grid applications the model can be used to evaluate both central-grid and isolated-grid PV systems. For off-grid applications the model can be used to evaluate both stand-alone (PV-battery) and hybrid (PV-battery-genset) systems. For water pumping applications the model can be used to evaluate PV-pump systems.

The RETScreen International Online Weather Database provides users access to weather data from more than 1,000 ground monitoring stations around the world. These data can be "pasted" to the pertinent cells within the RETScreen software. The database is provided free-of-charge and it is accessed directly through each of the 8 software models available for free download from this Website. As an alternative the user can use satellite data, particularly for the case when the project location is not close to a ground monitoring station. The NASA Surface Meteorology and Solar Energy Data Set provides RETScreen users access to satellite derived weather data for the entire surface of the planet. Via a direct Internet link to the NASA website, the user may simply "copy" this data from the NASA Website and then "paste" it into the RETScreen spreadsheets.

The SoDa web server

The project SoDa is based on the previous experience gained in the realisation of the ESRA product and the servers Satel-Light, Avalanche and SWITCH, and uses it as a springboard to answer customer needs by an efficient use of advanced information and communication technologies. An integration of information sources of different natures within a smart network is realized (see online at http://www.soda-is.com). These sources include databases containing solar radiation parameters and other relevant information. Several of these databases originate from an advanced processing of remote sensing images. Several were available separately and the SoDa Intelligent System builds smart Internet co-operation between sources. The information sources also include application-specific useroriented numerical models and advanced algorithms. The system is being validated through users trials. The project SoDa focuses on several applications: energy-conscious building design, daylighting, vegetation, environment, climate change, oceanography, health and industrial use of renewable energies.

CONCLUSION

In the most of cases, accuracy of solar radiation information available is not that expected by users. Nevertheless, solar radiation data at the ground level are retrievable by a diversity of tools. Ground station measurements are far from being the only answer to the user needs. Real efforts have been performed to provide irradiation values in various part of the world in a satisfactory way. Satellite-derived assessments represent an accurate solution for the mapping of the solar radiation on a wide geographical area. Moreover, combining measured or assessed data and physical models permits a convenient access to the information. Co-operation between several sources of information provides fruitful results. Efforts made in integrated information system and co-operative system have to be supported to overcome the technical limits of measurements by using the information and communication technologies.

  The world radiometric network Solar radiation is measured by ground networks of measuring stations. Well controlled measurements have only been available in a limited number of sites, and since the middle of the 20 th century or so. Various types of data are measured: sunshine duration, cloudiness, global irradiation and more rarely its diffuse and direct components, spectral distribution etc. Ground based measuring networks have been established but investments and maintenance costs for each site are of importance. Consequently, national networks often comprise only few stations, even in Western Europe and Northern America. In other parts of the world, measures are more rare. Oceanic surfaces are almost totally deprived of measures sites.The exact number of stations measuring irradiation throughout the world depends on sources of information. Stations belonging to a national network are not necessary part of the World Radiation Network supervised by the World Meteorological Organization (WMO). According to the list of stations available from the WMO in May 2002, there are 10930 measuring stations, of which 2900 measure the sunshine duration and 751 the global irradiation. Between 1966 and 1993, 1195 stations were measuring the sunshine duration and the global irradiation (WRDC/WMO). As shown in figure1, the spatial distribution of stations is strongly heterogeneous through the world.

Figure 1 .

 1 Figure 1. The World Radiometric Network for the period 1966-1993 (source WRDC)

Figure 2 :

 2 Figure 2: The Baseline Surface Radiation Network (May 2002)

Figure 4 .

 4 Figure 4. Example of output of the NASA Surface Solar Energy Data Set server. Map of the ten-years average of the monthly mean of daily irradiation for January for Brazil, expressed in kWh/m 2 . Note that the displayed units (kWh/m 2 /day) are incorrect.

Figure 5

 5 Figure 5 Example of output of the Australian Global Solar Radiation Archive server. This is a map of daily irradiation for the 20 th November 1998, derived from satellite images. Units are MJ/m 2 .


Jan Remund
email: remund@meteotest.ch

Lucien Wald

Jan Remund Meteotest

Fabrikstrasse

CHAIN OF ALGORITHMS TO CALCULATE ADVANCED RADIATION PARAMETERS

INTRODUCTION

This paper depicts the chain of algorithms for generating, hour by hour, day by day, shortwave radiation. It shows their integration in a compound service like SoDa (Wald et al., 2002).

Existing models were used as far as possible. The main scientific contributions emerged through the systematic inter-comparison of the ESRA (2000) and METEONORM (2000) (Remund et al., 1998) chains leading onto the definition of a new standard in the modelling of solar radiation parameters, by using the best of both existing chains and filling gaps by focused research.

The basic inputs to the full chain are monthly mean values of the Linke turbidity factor and global radiation. The outputs of the chain are hourly values of global radiation on inclined planes. This is achieved via stochastic generation of daily and hourly values of global radiation by splitting global radiation into beam and diffuse radiation and finally calculating the radiation on inclined planes. The stochastic process leads to an hourly dataset of a statistically average year with average mean, minimum and maximum values.

DEFINITION OF CHAINS

Algorithms linked to form focused chains of algorithms are needed to fill gaps between generally available data resources and the parameters requested by solar applications. This report first describes the parameters needed to address applications. Then the algorithms are established and linked into defined chains to provide the requested information from the available inputs.

Based on measurements and/or interpolation worldwide monthly mean values of global radiation and other meteorological parameters are available. Unfortunately, most applications need hourly time series of at least global radiation. This information gap can be filled with an algorithmic chains resource. The missing parameters are mainly values that are not stored (too many values), not available (not public) or not measured (needing too complicated equipment).

The main missing parameter is the global radiation on inclined planes. The diffuse radiation part is needed to calculate this value. The following description is concentrated on new or corrected models, the changes in clear sky models are described in the paper "Worldwide Linke turbidity information". Additional parameters like temperature and dewpoint temperature also available in SoDa are not described in this paper.

THE ESTIMATION OF HOURLY VALUES OF SHORT WAVE RADIATION

The basic inputs into the short wave chain of algorithms used to estimate the hourly values of the irradiance in the new system are monthly values of global radiation Gm and the air mass 2 Linke turbidity factor TL.

The target of this chain of algorithms is to provide hourly values of global, diffuse and beam radiation on horizontal and inclined planes. The whole chain does not have to be used for all applications. It is possible to run only parts of the chain. This choice is dependent on input data availability and the precise output data requirements.

This process is complemented by the use of state-ofthe-art models for splitting the global radiation into its beam and diffuse components. A state of art model for predicting hour by hour radiation on inclined planes provides the last link in the chain.

DAILY VALUES OF GLOBAL RADIATION

The model of Aguiar et al. (1988) The original model gives one single distribution of daily clearness index KT d values for any one monthly mean value KT m (see definition in Annex). The model does not take into account any local factors like site altitude above sea level (higher maximum irradiation values at higher altitude) or different turbidity situations. There are also problems with the coupling to the clear sky model of ESRA when this original model is used in the new chain of algorithms. The estimated clear sky values can be much higher or much lower than the maximum values predicted by the unmodified Aguiar. The whole system of the matrices was therefore changed from a clearness index basis to clear sky clearness index basis. Formulated like this, the maximum value of KT d,c (=1) must correspond automatically to the clear sky model predictions used. KT d , c is calculated as the ratio G d /G c,d .

The mapped resource of monthly mean Linke turbidity factors is used to drive the clear sky model to obtain the required monthly mean daily values of G c,d needed to calculate KT d,c in any selected month for any point. This change required the daily Markov transition matrices tables to be completely revised to match the new formulation. The new Tables giving the revised distributions are given in the Annex. The description of the methodology can be found at Aguiar et al. (1998).

Validation

The validation was done at 10 stations. 3 stations are in Switzerland, 3 in Germany, 1 in Puerto Rico and 3 in the USA. The stations cover a wide range of climates. As a measure of quality, the root mean square error (RMSE) between measured and generated kt values was calculated. The mean bias errors (MBE) are small. Remund J., Wald L., Page, J., 2003 Fig. 1 shows typical forms of the profiles. At noon all lines are very close. At low solar altitude the measured values are lower than the modeled ones; the new model is in between the measurements and the values of the model used in ESRA. Further, significantly higher KT h values are measured and calculated for very low solar altitudes. The new model quite often yields -as do the measured values -higher KT h values for the first and the last hour of the day. This is due to the one dimensional concept of the clearness index, where, as in nature, the radiation -particularly at low solar elevation -is influenced by the three dimensional form of the atmosphere. To avoid unreasonable values, the KT h values are limited to values of 0.8 for solar elevation below 10".

The new model has the advantage of allowing good interaction with the SoDa/ESRA clear sky model.

HOURLY VALUES OF SHORTWAVE RADIATION

Generating mean daily profiles of irradiance.

Knowledge of the mean daily profiles is essential for many simulation applications. It is also the first step in the generation of hourly values of global radiation from daily values of clearness index.

The model of Aguiar and Collares-Pereira (1992) was used in METEONORM Version 3.0 (Remund and Kunz, 1997). This model is very badly suited for high latitudes. The hourly integration model of Gueymard (2000) was introduced in version 4 of METEONORM (Remund and Kunz, 1999). Gueymard validated different models for 135 stations. One of them was the model of Collares-Pereira and Rabl (1979), which is used in ESRA (2000). Gueymard also presented a corrected version of Collares-Rabl model, that was better adapted for high latitudes. Gueymard's new model and the corrected model of Collares-Rabl showed approximately the same quality.

Method. For the new chain of algorithms we included another model based on the hypothesis that the average day global irradiance mean profile should exactly mirror the clear day global profile in form. The proposed method for mean daily irradiance profile generation is therefore based on the use of the global radiation clear sky profile to calculate the global irradiance profile for all days in the time series. The advantage of this model is that daily values of beam or diffuse radiation do not have to be known in advance. The model, called Remund-Page (RP) here, fits perfectly to the upper edge of the distribution, i.e. the clear sky profile, which is needed as a first step in the chain of algorithms. A short validation can be found in the next section.

Validation. The model was validated at 12 sites (Tab. 3 and 4). The distributions (Fig. 2), the first autocorrelation and the maximum KT d value were investigated. The maximum values are dependent on the T L values used and the quality therefore on the accuracy of the T L .

Stochastic generation of hourly variations in global irradiance from the daily mean profile

The

Splitting the global radiation to diffuse and beam

The models of Perez (METEONORM) and Skartveit (Satel-light project) for the splitting of global radiation have been examined briefly. The models are very similar after the correction of Skartveit (1998). The disadvantage of using a model like Perez or Skartveit is that the hourly diffuse values can not be known without (stochastic) generation of hourly global values. Therefore the beam and diffuse values depend to a small extent on random numbers. The use of mean daily profiles to calculate the beam and diffuse profile is not reliable. Both the Skartveit and Perez models depend on the hourly variations from one hour to the next. Mean profiles and hourly values with variations do not give the same result.

One advantage of the Skartveit model is that a correction for high albedoes is available for this model. There is also a formula to calculate the hourly variation, if this value is not known. The model was adapted to data of Bergen, Norway. The Perez model, which is more widely used, is still the standard model. J., Wald L., Page, J., 2003 Validation. A short validation of the models was made at 3 sites (Tab. 5). The quality of the different models is about the same with some advantages for Perez. Our decision to use the Perez model has been influenced by the possibility of using it with high horizons (Remund et al., 1998). The introduction of the modeling of the hourly variations lowers the accuracy of both models.

Remund

Radiation on the inclined plane

The Perez model (Perez et al. 1986) enables global and diffuse radiation to be calculated on an inclined surface using two input values, hourly global horizontal and diffuse horizontal irradiance.

The diffuse radiation on an inclined surface is calculated as the sum of two diffuse components, diffuse celestial irradiance (D i c ) and diffuse reflected irradiance (D i r ) by means of Eqn. 7:

r i c i i i D D B G     
The beam component is simply given by

   cos   n i B B  
The diffuse reflected irradiance (D i r ) is calculated with the following model:

    h r r i G D g           2 cos 1  
where  is the surface inclination, r g the isotropic reflected view factor and  the surface albedo. As no changes have been made, we refer to Remund et al. (1998).

New albedo model. The albedo is calculated with a model that gives albedo as a function of temperature. A new model is introduced. Verification with 8 stations showed that the model of Br…hwiler (1990) is not sufficient -especially in Swiss mountains, the place it has been made for. Data of GEBA (Goose, Fredericton, Jokmok, Toronto, Hamburg, Payerne) and WRC Davos (ASRB network Davos and Weissfluhjoch) were used for adapting and testing the new model.

            (10)
The r 2 values for both models are 0.92 and 0.93, respectively. A distinct separation for areas with a great amount of snow and areas with less snow was found. A great amount of snow enhances the possibility of fresh snow and therefore higher albedoes and prolongates the time of snow cover in spring. For temperatures below -10"C and above 10"C there is no difference between the models. The separation into the 2 groups is not easy. As a first approximation the following rule is used to determine areas with a great amount of snow:

 Sum of precipitation for 3 winter months > 150 mm  Mean temperature for 3 winter months < -3"C

The new model gives very similar results to the model used in versions 3 and 4 in the range of 0.2-0.5 (Fig. 3). The big difference is for values greater than 0.5, which did not exist with the old model -but was found in the data. In various tests the following temperatures were evaluated to use for albedo calculation: With hourly generated data the mean of the last 2 weeks is used. If only monthly temperature values are available, the interpolated daily value of the day 5 days before is used.

Validation of the slope irradiance model. The generated diffuse radiation on inclined planes is calculated in two steps. The two Perez models were first tested alone with measured hourly values of global radiation as inputs. Secondly they were tested within the combined model, using generated hourly radiation values.

Validation was carried out for 2 sites in Switzerland for inclinations of 33-45" with a more or less South orientation (typical for solar energy applications) and also for a West facing facade in Bavaria (typical exposure for overheating studies using building simulation).

Tests of inclined surface data for solar energy applications

Using measured hourly global radiation values:

The tests were carried out for 2 sites in Switzerland with data of 1993 46.95"N,7.45"E,520 m,inclination 35",azimuth: 37"E;8.85"E,197 m,inclination: 35"S,azimuth: 15"W). The average MBE error in the hourly values was 5 W/m 2 (over all hours) (generated values slightly too high) and the RMSE standard deviation 33 W/m 2 (G h > 0). For monthly average values, the MBE was 3 W/m 2 (5 %) and the RMSE 5 W/m 2 . The distributions of both MBE and RMSE errors display a distinct seasonal variation.

Using generated hourly values:

The tests were carried out for 2 sites in Switzerland. The average MBE error in the average monthly values was 0 W/m 2 (1 %) (generated values too high) and the RMSE standard deviation 5 W/m 2 (6 %). For yearly average values, the MBE was 2 W/m 2 (1 %) and the RMSE 5 W/m 2 (3 %). The average discrepancy with generated radiation is (surprisingly) somewhat smaller than achieved with measured radiation as input. This indicates that the errors partly compensate one-another. The distributions of both MBE and RMSE again display a distinct yearly pattern, having a maximum in winter.

Test for building simulation Using measured hourly global radiation values:

The test was carried out at Holzkirchen (Bavaria; 11.71"E, 47.87"N, 680m) for a West facade. The average MBE error in the hourly values was 3 W/m 2 (over all hours) (generated values slightly too high) and the RMSE standard deviation 51 W/m 2 (G h > 0). For monthly average values, the MBE was 3 W/m 2 (0 %) and the RMSE 8 W/m 2 (13 %).

Using generated hourly values: The test was carried out at Holzkirchen on a West facade. The average MBE error in the average monthly valuesm 2 (7 %) (generated values too high) and the RMSE standard deviation 7 W/m 2 (9 %). The average discrepancy with generated radiation is somewhat bigger than with measured radiation as input. The distributions of both MBE and RMSE errors display a distinct yearly pattern, having a maximum in winter (as for tests in Switzerland).

Modification of irradiance due to horizon

The aim of the modification method described here is to calculate the radiation at sites with raised (distant) horizons. A number of assumptions which were used in the raised (local) skyline model are not valid in this case. The modification procedure for the different radiation components is described in this section.

For the modifications due to skyline profiles we also refer to Remund et al. (1998), as no changes were made.

CONCLUSIONS

New chains drawing on the design of the existing METEONORM chains with algorithms mainly selected from those used in ESRA were developed. Testing against observed data shows that the stochastic generation of the hourly short wave parameters is possible and that the quality is acceptable. The models constructed are based as much as possible on published work. Nevertheless some important new validated chain links were introduced. ISES Solar World Congress, 16-19 June, G€teborg, Sweden, CD-ROM published by International Solar Energy Society

The main scientific contributions sprang from the detailed inter-comparison of the ESRA and METEONORM chains. This process drove the achievement of a new standard in the modelling of solar radiation parameters for practical applications on a global basis, using the best of both existing chains.

The establishment of a well-defined functional relationship between clear day and all day short wave radiation models was especially important for systematic model building . This relationship could not have been made into an effective working tool without the extensive efforts made within the SoDa program to establish a world wide digitally mapped data resource of values of the Linke turbidity factors.

The understanding of the relationship between solar radiation estimation and screen air temperature estimation was advanced into effective working program that deliver data needed for effective simulation for any site in the world. Globalisation of the algorithmic structures was indeed achieved.

One drawback springing from lack of time in the face of many challenges within the framework of SoDa, is that not all parts of the chains could be reviewed with the same thoroughness. Therefore some parts, mainly at the end of the longer chains -like the radiation on inclined planes with high horizons -are used without validation.

The advanced chain of algorithms was included in the new version of METEONORM.

Fig. 1 :

 1 Fig. 1: Mean daily profiles of KT h for daily KT d values of 0.6 at San Juan PR.

  where G d is the daily global horizontal irradiance, G c the clear sky hourly global irradiance, G c,d the daily Remund J., Wald L., Page, J., 2003. Chain of algorithms to calculate advanced radiation parameters. Proceedings of ISES Solar World Congress, 16-19 June, Göteborg, Sweden, CD-ROM published by International Solar Energy Society clear sky global irradiance. Other authors like Grüter et al. (1986) have used this approach as well.

Fig. 2 :

 2 Fig. 2: Histogram of the daily KT d values for Dodge City (USA).The validation does not show a clear result. Generally the new model is slightly better (Tab. 3 and 4). The distributions do not differ much from the original ones. Generally the new model shows better results for North American sites than for European sites. This could be explained by the choice of sites used for making the original and the new model.

  stochastic generation of hourly irradiance values from the daily mean profile is based on the model of Aguiar and Collares-Pereira (1992) (TAG-model: Time dependent, Auto-regressive, Gaussian model). This model, also used in METEONORM, consists of two parts: the first part calculates an average daily profile. No change has been made to this model compared to Remund et al. (1998), so we refer to this paper.

  Fig. 3: Albedo vs. temperature (TT). Model used in version 3 and 4 (with max. at 0.5) and new model (max. at 0.8).

  Frequently only monthly values of climatic data are available only for certain parts of the world, so techniques to generate hourly values world wide are required. ISES Solar World Congress, 16-19 June, G€teborg, Sweden, CD-ROM published by International Solar Energy Society Tab. 1: Proposed models for chain of algorithms. Models not used in ESRA or METEONORM are highlighted (bold).

	Model	Algorithms ESRA	METEONORM	SoDa
	Solar geom.	div.	Bourges (1985)	Ineichen (1983)	Bourges (1985)
	Clear sky	Beam	Rigollier et al. (2000)	Rigollier et al. (2000)	Rigollier corr.
		Diffuse	Rigollier et al. (2000)	Global-Beam	Rigollier corr.
		Global	Global + Diffuse	Kasten 1983	Global + Diffuse
	Daily profile	Global	Collares-P. and Rabl,	Gueymard (2000)	New
			(1979)
	Stochastic gener. Global day -	Aguiar et al. (1988)	Aguiar et al. (1988) corr.
		Global hour -	Aguiar & Collares-Pereira	Aguiar & Collares-
				(1992)	Pereira (1992) corr.*
	Rad. Separation Diffuse	ESRA (2000)	Perez et al. (1991)	Perez et al. (1991)
	Tilted planes	Global	Muneer (1990)	Perez et al. (1986/87)	Perez et al. (1986/87)
	High horizons	Global	-	Remund et al. (1998)	Remund et al. (1998)
	* Aguiar and Collares-Pereira: only stochastic part (profile by other model)

  . Chain of algorithms to calculate advanced radiation parameters. Proceedings of ISES Solar World Congress, 16-19 June, G€teborg, Sweden, CD-ROM published by International Solar Energy Society In order to calculate the mean daily profiles of the measured values, the daily values were binned in KT d groups using a 0.05 band width. The new RP model shows the smallest deviation from the measured values at most stations and the best overall result for all sites. The model ACP has the highest deviations. CPRG-model is second best. This model is very similar to CPR, showing slightly better results at higher latitudes (Tab. 2).

	Tab. 2: RMSE of hourly KT h values (generated -measured). The best model is highlighted. ACP: Aguiar & Collares-
	Pereira (1992); GM: Gueymard (2000); CPR: Collares-Pereira & Rabl (1979); CPRG: Collares-Pereira & Rabl (1979),
	Gueymard (2000).
	Site	Latitude	Period	ACP	GM	RP	CPR	CPRG
	Magadino	46"10'N	95 -99 0.094	0.071	0.067	0.070	0.070
	Haerkingen	47"19'N	95 -99 0.102	0.087	0.093	0.088	0.088
	Hamburg	53"39'N	81 -90 0.055	0.046	0.047	0.044	0.044
	W…rzburg	49"46'N	81 -90 0.062	0.040	0.038	0.039	0.038
	Weihenstephan 48"24'N	81 -90 0.064	0.039	0.036	0.041	0.040
	Albuquerque	35"03'N	61 -90 0.091	0.076	0.048	0.063	0.062
	Dodge City	37"46'N	61 -90 0.098	0.081	0.088	0.074	0.073
	San Juan	18"26'N	61 -90 0.082	0.077	0.055	0.066	0.066
	Anchorage	61"10'N	61 -90 0.105	0.077	0.068	0.083	0.082
	All sites			0.095	0.078	0.072	0.075	0.0074

  Tab. 3: Correlation coefficients of the grouped frequencies (width of groups: 0.05) as a measure of the quality of the distribution (better model is highlighted).

			Whatever the relative results look like, only the new
			version allows a good interaction with the clear sky
			model. Additionally the new model is easier to use (no
			minimum and maximum classes) and generally runs
			faster (less loops).
			Tab. 4: First autocorrelation of daily KT d values.
			Site	Meas-	Original New
				ured
			Raleigh	0.406	0.321	0.306
			Dodge City	0.335	0.153	0.301
			Int. Falls	0.332	0.261	0.387
			Salt Lake City	0.456	0.358	0.524
			Haerkingen	0.542	0.344	0.403
			Hamburg		0.383	0.381
			Würzburg	0.471	0.275	0.351
			Weihenstephan	0.512	0.313	0.325
			Nice	0.346	0.292	0.339
			Kobenhavn	0.422	0.402	0.387
			Arkangelsk	0.459	0.358	0.479
			mean difference	-	-0.125 -0.060
			Standard error	-	0.071	0.085
	Site	Original	New
	Raleigh	0.897	0.910
	Dodge City	0.766	0.773
	Int. Falls	0.715	0.854
	Salt Lake City	0.910	0.939
	Haerkingen	0.693	0.645
	Hamburg	0.854	0.884
	Würzburg	0.796	0.814
	Weihenstephan	0.881	0.763
	Nice	0.973	0.933
	Kobenhavn	0.895	0.886
	Arhangelsk	0.781	0.715
	Mean	0.769	0.754

  . Chain of algorithms to calculate advanced radiation parameters. Proceedings of ISES Solar World Congress, 16-19 June, G€teborg, Sweden, CD-ROM published by International Solar Energy Society It can be adapted to both US and EU climates. A model has been included in the SoDa chains to estimate the hourly variation parameter dk for use with the Perez model for cases in which no hourly variation data are available:

					h KT	,	c		. 0	98
					dk		1 . 0		. 0	03	*	sin	  KT	h	,	c		05 . 0			527 . 8	
						. 0	02		KT	h	,	c		
					h KT	,	c		98 . 0
					dk		. 1 	634		. 1	72		h KT	,	c
	Tab. 5: Results of the comparison of Perez and Skartveit model. "mod." means modelled variance from hour to hour
	(according to Eqn. 6).
	Site	Perez	Perez	Skartv. Skartv.					Perez	Perez	Skartv. Skartv.
			mod.		mod.												mod.	mod.
		MBE	MBE	MBE	MBE						RMSE RMSE RMSE RMSE
	Payerne BSRN 1998	-0.7	3.7	5.5	6.5									34.5	44.5	33.9	43.0
	Vaulx-en-Velin IDMP 1994	10.2	12.5	12.1	13.9									38.1	41.8	36.0	40.3
	Melbourne (Australia) 1998	3.2	10.5	11.0	11.3									43.1	49.4	43.2	46.3

Acknowledgements -Many thanks goes to H. Gilgen and A. Ohmura of Institute for Atmosphere and Climate ETH (IACETH) for BSRN data and data of Payerne and Reckenholz. The Swiss Agency for Environment, Forest and Landscape (SAEFL) provided data of 3 NABEL stations and the Australian Regional Instrument Center, Bureau of Meteorology a CD-ROM with global and beam irradiance data of several years. Further we like to thank the Fraunhofer Institute for Building Physics IBP Holzkirchen for the example climate dataset as well as TNC (Erlenbach ZH) for global radiation data on inclined surfaces. Swiss Meteorological Institute provided data of 5 ANETZ-stations. This work is supported partly by the programme IST of the European Commission, by the Swiss Federal Office of Energy, Bern (conctract No. 79564) and the Swiss Federal Office for Education and Science (contract No. 99.0513).

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Reinhardt, P.Schwarzmann, L. Wald, 1986. Solar Radiation Data from Satellite Images. Determination of Solar Radiation at Ground Level from Images of the Earth Meteorological Satellites -An Assessment Study. D. Reidel Publishing Company. Gueymard C.A., 1998. Turbidity determination from Broadband Irradiance measurements: a detailed multicoefficient approach, Journal of Applied Meteorology, Vol. 37, pp 414-435. Gueymard, C., 2000. Prediction and performance assessment of mean hourly global radiation. Solar Energy, Vol.68, No.3, pp. 285-303, 2000. Ineichen, P., 1983. Quatre ann †es de mesures d'ensoleillement ˆ Gen‰ve. Th‰se No. 2089, Facult † des sciences de l'Universit † de Gen‰ve. Kasten F., 1983) Parametrisierung der Globalstrahlung durch Bedeckungsgrad und Tr…bungsfaktor. Ann. Met, 20, 49-50. Muneer T., 1990. Solar radiation model for Europe. Building Serv. Eng. Res. Technol. 11, 153-163 Molineaux, B, P. Ineichen and Delauney, J.J., 1995. Direct luminous efficacy and atmospheric turbidityimproving model performance. Solar Energy, Vol. 55, No. 2, pp. 125-137, 1995. Page, J., 1996. ESRA Task II Technical Report Number 11. Project Internal. Perez, R., R. Stewart, C. Arbogast, R. Seals and J. Scott, 1986. An anisotropic hourly diffuse radiation model for sloping surfaces: Description, performance validation, site dependency evaluation. Solar Energy, Vol. 36, No. 6, pp. 481-497. Perez, R., R. Seals, P. Ineichen, R. Stewart and D. Menicucci, 1987. A new simplified version of the Perez Diffuse Irradiance Model for tilted surfaces. Solar Energy, Vol. 39, No.3,pp. 221-231. Perez, R., P. Ineichen, R. Seals, J. Michalsky and R. Stewart, 1990. Modeling daylight availability and irradiance components from direct and global irradiance. Solar Energy, Vol. 44, No.5, pp. 271-289. Perez, R., P. Ineichen, E. Maxwell, R. Seals and A. Zelenka, 1991. Dynamic Models for hourly global-to-Remund J., Wald L., Page, J., 2003. Chain of algorithms to calculate advanced radiation parameters. Proceedings of ISES Solar World Congress, 16-19 June, G€teborg, Sweden, CD-ROM published by International Solar Energy Society direct irradiance conversion. Edited in: Solar World Congress 1991. Volume 1, Part II. Proceedings of the Biennial Congress of the International Solar Energy Society, Denver, Colorado, USA, 19-23 August 1991. Remund, J. and S. Kunz, 1995. METEONORM -a comprehensive meteorological database and planning tool for system design. In Proceedings of 13th Solar Energy Photovoltaic Conference and Exhibition, Nice. Commission of the European Communities, CEC). Volume I. Remund, J. and S. Kunz, 1997. METEONORM Version 3.0. Meteotest, Fabrikstrasse 14, 3012 Bern, Switzerland. Remund, J. and S. Kunz, 1999. METEONORM Version 4.0. Meteotest, Fabrikstrasse 14, 3012 Bern, Switzerland. Remund, J., E. Salvisberg and S. Kunz, 1998. 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ANNEX

For many chain links the clearness index is used. This index is defined by Tab. A1: Markov transition matrix for 0.10 <= KT m,c <= 0.20 0.0-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.6 0.6-0.7 0.7-0.8 0.8-0.9 0.9-1.0 0.0-0.1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.1-0.2 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.2-0.3 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.3-0.4 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.4-0.5 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.5-0.6 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.6-0.7 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 0.7-0.8 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.8-0.9 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.9-1.0 0.000 0.000 0.000 0.000 0.000 0.000 0.250 0.000 0.000 0.750

Tab. A2: Markov transition matrix for 0.20 <= KT m,c <= 0.30 0.0-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.6 0.6-0.7 0.7-0.8 0.8-0.9 0.9-1.0 0.0-0.1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.1-0.2 0.000 0.500 0.167 0.167 0.167 0.000 0.000 0.000 0.000 0.000 0.2-0.3 0.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.3-0.4 0.000 0.333 0.000 0.000 0.333 0.000 0.000 0.000 0.000 0.333 0.4-0.5 0.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.5-0.6 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.6-0.7 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.7-0.8 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.8-0.9 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.9-1.0 0.000 0.000 0.000 0.000 0.000 1.000 0.000 0.000 0.000 0.000

Tab. A3:Markov transition matrix for 0.30 <= KT m,c <= 0.40 0.0-0.1 0.1-0.2 0.2-0.3 0.3-0.4 0.4-0.5 0.5-0.6 0.6-0.7 0.7-0.8 0.8-0.9 0.9-1.0 0.0-0.