Evaluating solar radiation forecast uncertainty
<p>The presence of clouds and their characteristics have a strong impact on the radiative balance of the Earth and on the amount of solar radiation reaching the Earth's surface. Many applications require accurate forecasts of surface radiation on weather timescales, for example solar ener...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-02-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://www.atmos-chem-phys.net/19/1985/2019/acp-19-1985-2019.pdf |
| Summary: | <p>The presence of clouds and their characteristics have a strong impact on the
radiative balance of the Earth and on the amount of solar radiation reaching
the Earth's surface. Many applications require accurate forecasts of surface
radiation on weather timescales, for example solar energy and UV radiation
forecasts. Here we investigate how operational forecasts of low and mid-level
clouds affect the accuracy of solar radiation forecasts. A total of 4 years
of cloud and solar radiation observations from one site in Helsinki, Finland,
are analysed. Cloud observations are obtained from a ceilometer and therefore
we first develop algorithms to reliably detect cloud base, precipitation, and
fog. These new algorithms are widely applicable for both operational use and
research, such as in-cloud icing detection for the wind energy industry and
for aviation. The cloud and radiation observations are compared to forecasts
from the Integrated Forecast System (IFS) run operationally and developed by
the European Centre for Medium-Range Weather Forecasts (ECMWF). We develop
methods to evaluate the skill of the cloud and radiation forecasts. These
methods can potentially be extended to hundreds of sites globally.</p>
<p>Over Helsinki, the measured global horizontal irradiance (GHI) is strongly
influenced by its northerly location and the annual variation in cloudiness.
Solar radiation forecast error is therefore larger in summer than in winter,
but the relative error in the solar radiation forecast is more or less
constant throughout the year. The mean overall bias in the GHI forecast is
positive (8 W m<span class="inline-formula"><sup>−2</sup></span>). The observed and forecast distributions in
cloud cover, at the spatial scales we are considering, are strongly skewed
towards clear-sky and overcast situations. Cloud cover forecasts show more
skill in winter when the cloud cover is predominantly overcast; in summer
there are more clear-sky and broken cloud situations. A negative bias was
found in forecast GHI for correctly forecast clear-sky cases and a positive
bias in correctly forecast overcast cases. Temporal averaging improved the
cloud cover forecast and hence decreased the solar radiation forecast error.
The positive bias seen in overcast situations occurs when the model cloud has
low values of liquid water path (LWP). We attribute this bias to the model
having LWP values that are too low or the model optical properties for
clouds with low LWP being incorrect.</p> |
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| ISSN: | 1680-7316 1680-7324 |