Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
Comparison of homogeneity tests for temperature using a simulation study
Date
2016-01-01
Author
Yozgatlıgil, Ceylan
YAZICI, Ceyda
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
14
views
0
downloads
Homogeneity testing is one of the most important analyses in climate-related studies as it underpins the reliability of any inferences. The effects not directly related with climate are identified and removed from the meteorological variables, and then the obtained homogeneous variables are used to present an enhanced picture of the current situation and produce realistic forecasts based upon the variables. In this study, we investigate the performances of well-known homogeneity tests and introduce some tests that are not usually used for testing homogeneity via Monte Carlo simulation. We generate data using a normally distributed temperature variable. We consider both absolute and relative homogeneity tests (RHTest). Although relative tests are the best performing homogeneity tests, their results highly depend on the quality of the reference series. Consequently, they have to be used with at least one of the absolute tests in order to detect possible inhomogeneities in the reference series. Our results show that the relative tests which are standard normal homogeneity test, F-test for structural breaks with reference series, multiple change point detection method, namely and the RHTest have the best detection rates whereas the absolute tests, namely, Kruskal-Wallis, Pettitt and Friedman tests have the worst performances. The best performing absolute test is F-test for structural breaks.
Subject Keywords
Atmospheric Science
URI
https://hdl.handle.net/11511/36860
Journal
INTERNATIONAL JOURNAL OF CLIMATOLOGY
DOI
https://doi.org/10.1002/joc.4329
Collections
Department of Statistics, Article