EGU24-9396, updated on 08 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Reduction of systematic differences of LSASAF shortwave solar radiation fluxes using neural networks

Matic Savli1 and Peter Mlakar1,2
Matic Savli and Peter Mlakar
  • 1Slovenian Environmental Agency, Section for Meteorological, Hydrological and Oceanographic products, Slovenia (
  • 2Faculty for Computer Science and Informatics, University of Ljubljana, Slovenia (
To improve the process of solar energy production, we can utilize the downward
shortwave flux (DSSF) measurement, which constitutes a part of the satellite
derived total and diffuse downward surface shortwave flux (MDSSFTD) product.
MDSSFTD is issued by the Satellite Application Facility on Land Surface Analysis (LSA SAF).
However, its direct application in this area is inhibited by potential systematic
errors in the DSSF product. Therefore, this has to be addressed before the DSSF can be used downstream.

To this end, we implemented a neural network-based post-processing procedure
that uses previous temporal DSSF observations and additional predictors, such
as cloudiness and time of day, to generate a corrected DSSF value. The ground
truth for this regression task are the in-situ measurements across a variety of
locations in Slovenia. Additionally, the neural network produces DSSF estimates
in terms of quantiles, providing an uncertainty estimate of the corrected prediction itself.

We verified our new method on the aforementioned region over a period of
four years. We found that our neural network approach successfully reduces
the presence of systematic differences present in the DSSF. Additionally, the
neural network method outperforms a baseline look-up-table approach in terms
of multiple criteria, such as mean absolute error, bias, and error variability.

How to cite: Savli, M. and Mlakar, P.: Reduction of systematic differences of LSASAF shortwave solar radiation fluxes using neural networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9396,, 2024.