A new method for estimating cloud optical depth from  photovoltaic power measurements

Wandji Nyamsi, William; Lindfors, Anders V.; Meyer, Angela; Lipponen, Antti; Arola, Antti

doi:10.5194/amt-19-899-2026

Articles | Volume 19, issue 3

https://doi.org/10.5194/amt-19-899-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-19-899-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 3

Research article

|

09 Feb 2026

Research article |

| 09 Feb 2026

A new method for estimating cloud optical depth from photovoltaic power measurements

William Wandji Nyamsi, Anders V. Lindfors, Angela Meyer, Antti Lipponen, and Antti Arola

Data sets

PV production data with ancillary PV and meteorological data including solar radiation measurements from FMI's outdoor solar laboratories in Helsinki, Kuopio and Sodankylä (Finland) starting from August 2015 and ending Dec 2021 Juha A. Karhu and Anders Lindfors https://doi.org/10.57707/fmi-b2share.c7b3ec9f19324a6497639d6d8c0cde84

Open-source quality control routine and multi-year power generation data of 175 PV systems Lennard Visser et al. https://doi.org/10.5281/zenodo.10953360

ERA5 hourly data on single levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.adbb2d47

Short summary

This paper proposes a new, fast and accurate method for estimating the cloud optical depth (τ_c) from photovoltaic (PV) power measurements under overcast sky conditions. The method performs very well with the European Centre for Medium-Range Weather Forecasts (ECMWF) products as inputs describing the state of the atmosphere. The method exhibits a better performance than published state-of-the-art methods when compared to ground and satellite-based τ_c retrievals serving as reference.