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Classifying direct normal irradiance 1-minute temporal variability from spatial characteristics of geostationary satellite-based cloud observations

Schroedter-Homscheidt, Marion and Kosmale, Miriam and Saint-Drenan, Yves-Marie (2020) Classifying direct normal irradiance 1-minute temporal variability from spatial characteristics of geostationary satellite-based cloud observations. Meteorologische Zeitschrift, 29 (2), pp. 131-145. Borntraeger Science Publishers. ISSN 0941-2948

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Official URL: https://www.schweizerbart.de/papers/metz/detail/29/93579/Classifying_direct_normal_irradiance_1_minute_temporal_variability_from_spatial_characteristics_of_geostationary_satellite_based_cloud_observations

Abstract

t Variability of solar surface irradiances in the 1-minute range is of interest especially for solar energy applications. Eight variability classes were previously defined for the 1 min resolved direct normal irradiance (DNI) variability inside an hour. In this study spatial structural parameters derived fromsatellite-based cloud observations are used as classifiers in order to detect the associated direct normal irradiance (DNI) variability class in a supervised classification scheme. A neighbourhood of 3×3 to 29×29 satellite pixels is evaluated to derive classifiers describing the actual cloud field better than just using a single satellite pixel at the location of the irradiance observation. These classifiers include cloud fraction in a window around the location of interest, number of cloud/cloud free changes in a binary cloud mask in this window, number of clouds, and a fractal box dimension of the cloud mask within the window. Furthermore, cloud physical parameters as cloud phase, cloud optical depth, and cloud top temperature are used as pixel-wise classifiers. A classification scheme is set up to search for the DNI variability class with a best agreement between these classifiers and the pre-existing knowledge on the characteristics of the cloud field within each variability class from the reference data base. Up to 55 % of all DNI variability class members are identified in the same class as in the reference data base. And up to 92 % cases are identified correctly if the neighbouring class is counted as success as well – the latter is a common approach in classifying natural structures showing no clear distinction between classes as in our case of temporal variability. Such a DNI variability classification method allows comparisons of different project sites in a statistical and automatic manner e.g. to quantify short-term variability impacts on solar power production. This approach is based on satellite-based cloud observations only and does not require any ground observations of the location of interest.

Item URL in elib:https://elib.dlr.de/135936/
Document Type:Article
Additional Information:weiteres EU-Projekt: info:eu-repo/grantAgreement/EC/FP7/654984
Title:Classifying direct normal irradiance 1-minute temporal variability from spatial characteristics of geostationary satellite-based cloud observations
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Schroedter-Homscheidt, Marionmarion.schroedter-homscheidt (at) dlr.dehttps://orcid.org/0000-0002-1854-903X
Kosmale, Miriammiriam.kosmale (at) fmi.fiUNSPECIFIED
Saint-Drenan, Yves-Marieyves-marie.saint-drenan (at) mines-paristech.frUNSPECIFIED
Date:4 August 2020
Journal or Publication Title:Meteorologische Zeitschrift
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:29
Page Range:pp. 131-145
Publisher:Borntraeger Science Publishers
ISSN:0941-2948
Status:Published
Keywords:Variability, global horizontal irradiance, direct irradiance, automatic classification, satellitebased, clouds, textural parameters
HGF - Research field:Energy
HGF - Program:Technology, Innovation and Society
HGF - Program Themes:Renewable Energy and Material Resources for Sustainable Futures - Integrating at Different Scales
DLR - Research area:Energy
DLR - Program:E SY - Energy Systems Analysis
DLR - Research theme (Project):E - Systems Analysis and Technology Assessment
Location: Oberpfaffenhofen , Oldenburg
Institutes and Institutions:Institute of Networked Energy Systems > Energy Systems Analysis
German Remote Sensing Data Center > Atmosphere
Deposited By: Schroedter-Homscheidt, Marion
Deposited On:14 Sep 2020 10:17
Last Modified:14 Sep 2020 10:17

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