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.
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.
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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