Applications of DLR-ISIS data


Climate Change Studies

The global radiation budget of the Earth is a fundamental part of the global energy and water cycle and therefore plays a crucial role in the Earth's climate system. Determining fluxes at the surface as an element of climate variability can extend the understanding of the response of the climate system to natural and anthropogenic climate forcings. One example is the so-called "global dimming", a gradual reduction of the GHI, which is probably caused by an increased amount of aerosol in the atmosphere due to anthropogenic carbon burning.

The
World Climate Research Programme (WCRP) started the Global Energy and Water Cycle Experiment (GEWEX) to gain a greater understanding of the Earth's water cycle including the radiation budget. Part of the GEWEX is the Radiative Flux Assessment (RFA) project, which will provide a platform for the analysis of long-term radiative flux products. DLR-ISIS irradiances will also be added to the data base of surface fluxes and therefore contribute to the study of climate change.

Solar Energy Applications

The most important application of the DLR-ISIS data set is the use of the DNI data during the planning stage of concentrating solar power plants. These use large parabolic mirrors to concentrate the incoming solar irradiance on an absorber tube and heat the fluid running through it to up to 400°C. The heat is then channelled through a conventional generator to produce power. 

Solar thermal power plantparabolic mirror

The DLR-ISIS data set is used to determine the average annual irradiance at sites for new concentrating solar power plants, evaluate the variability of irradiance from year to year and study the effect of extreme atmospheric conditions on the irradiance at the surface e.g. after a volcano eruption. The analysis of the long-term variability of DNI in the DLR-ISIS data set contributed to the approval of several new concentrating solar power plants in southern Spain.


Sensitivity of DNI to change in cloud amount and aerosol load is very high. Therefore, variability of these atmospheric constituents results in strong variability of irradiance at the surface of the Earth. Due to this high variability, measurements of only a few years are not representative for the long-term averages. In the images below averages over one year, two years etc. of irradiance are compared to the long-term average over 21 years (grid box no. 4834, Israel/Jordan). DNI averages taken over only a single year of data differ from the 21-year mean by as much as 17%. Only after 13 years of measurements is the average within 5% of the 21-year mean. Considering all 6596 grid boxes of the DLR-ISIS data set, averages for a single year differ from the 21-year value by an average 20%. For all DLR-ISIS grid boxes, the derived average DNI is within 5% of the long-term mean only after a minimum of 12 years.

For GHI, variability from year to year is low. For grid box 4834, differences between short term averages and the 21-year average  never exceed 4%. On average over all grid boxes, after 3 years of measurements, derived GHI values are within 5% of the 21-year average.

DLR-ISIS DNI deviation from long term averageDLR-ISIS GHI deviation from long term average
These plots indicate how important long time series of irradiance data are to rate solar irradiance at a specific site. DLR-ISIS grid boxes are 280 km x 280 km in size, therefore, the plots above can give an indication of the variability at a specific site. For a station, minimum measuring intervals for the derivation of a representative average irradiance can be much longer, as the spatial variability within a grid box is high, particularly for DNI (Lohmann et al. 2007).
Although surface measurements with pyrheliometers are routine during the planning stage of a concentrating solar power plant, only satellite data can provide reliable long term averages that cover more than 10 years of irradiance data.



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