Spatial evaluation of CAMS Radiation service using dense pyranometric networks

As part of the EU-funded CAMS (Copernicus Atmospheric Monitoring Services) project, the CAMS Radiation Service (CRS) provides estimates of direct and global downwelling solar irradiance (SSI). The SSI estimate uses ozone, water vapor and aerosols from CAMS and cloud properties assessed with the APOLLO_NG algorithm. In parallel to the continuous improvement of the SSI estimation method, the regular evaluation of solar radiation estimates is an important component of the CRS activities.

CRS evaluation is generally carried out using high-quality three-component (GHI, DHI, DNI) measurements as a reference, such as the ones provided by the stations of the Baseline Surface Radiation Network (BSRN). The advantage of such stations is that the maintenance, the availability and the strict quality control (QC) procedures of the three redundant components allow reaching a high level of confidence in the data. However, such stations are sparsely spread, which limits our understanding of the spatiotemporal error structure of CRS.

In this work, we tested the use of a dense meteorological network of pyranometers as a complement to above-mentioned pyranometric stations. The potential of 1-minute GHI measurements from 250 meteorological stations operated by Météo-France and 40 stations from the German PV-Live network for assessing CRS was tested based on an overall 8-year timespan of GHI measurements.

Because of the large number of stations, pyranometer maintenance is not as systematic as recommended by e.g. the BSRN. This means that QC must be carefully and specifically carried out to check the plausibility of the measurements before they are used in the spatio-temporal evaluation. Unfortunately, only GHI is measured, so it is not possible to apply quality control tests involving several redundant components, with consistency checks. To overcome this limitation, we propose several tests to verify, for example, radiometric calibration, time reference and instrument leveling.

Due to the limited QC based on GHI, the possibility of faulty measurements must be considered in the evaluation. Here, the uncertainty over data quality can be partially compensated by the high density of stations, with statistical consistency check in the domain of the spatio-temporal variability. If we consider that the measurements are independent, we consider that information on CRS is plausible if there is a consensus between the different stations located in a close vicinity. On the other hand, erroneous measurements appear as outliers in relation to the other nearby stations, if applicable, depending on the local distribution of the stations and the local orography. Using this strategy, we were able to provide, to some extent, an initial indication of a spatial structure in the CRS error. These results are presented, along with their potential sources (clear-sky modeling, cloud modification factors, cloud coverage, solar zenith angle, parallax, etc.) and the potential CRS improvements identified to address them.