Comparative characteristics of gap filling methods in high-frequency data of micrometeorological measurements

This article is devoted to one of the most complex technical aspects of the primary processing of micrometeorological data. The article contains a description of basic algorithms for restoring missing values in time series of data. The gap filling methods implemented by the authors on the basis of t...

Full description

Saved in:
Bibliographic Details
Published in:IOP conference series. Earth and environmental science 2022-05, Vol.1023 (1), p.12009
Main Authors: Drozd, I D, Gavrikov, A V, Stepanenko, V M
Format: Article
Language:English
Subjects:
Algorithms
Frequency measurement
Wind speed
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This article is devoted to one of the most complex technical aspects of the primary processing of micrometeorological data. The article contains a description of basic algorithms for restoring missing values in time series of data. The gap filling methods implemented by the authors on the basis of the thus described algorithms are tested using an example of filling-in generated gaps in series of temperature and vertical wind speed. The series of high-frequency measurements of an acoustic anemometer installed on the micrometeorological tower of the meteorological observatory (MO) of Moscow State University (MSU) are used as test data. As a result of this review of gap-filling methods, the effectiveness of various methods for filling-in missing values is assessed.
ISSN:1755-1307
1755-1315
DOI:10.1088/1755-1315/1023/1/012009