Comparison of homogeneity tests for temperature using a simulation study

Date

2016-01-01

Author

Yozgatlıgil, Ceylan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

129
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

Suggestions

OpenMETU
Core

Statistical downscaling of monthly reservoir inflows for Kemer watershed in Turkey: use of machine learning methods, multiple GCMs and emission scenarios OKKAN, UMUT; İnan, Gül (Wiley, 2015-09-01) In this study, statistical downscaling of general circulation model (GCM) simulations to monthly inflows of Kemer Dam in Turkey under A1B, A2, and B1 emission scenarios has been performed using machine learning methods, multi-model ensemble and bias correction approaches. Principal component analysis (PCA) has been used to reduce the dimension of potential predictors of National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis data. Then, the reasonabl...
Predictability of Seasonal Precipitation Using Joint Probabilities Yılmaz, Mustafa Tuğrul (2010-01-17) This paper tests whether seasonal mean precipitation is predictable using a new method that estimates and analyzes joint probabilities. The new estimation method is to partition the globe into boxes, pool all data within the box to estimate a single joint probability of precipitation for two consecutive seasons, and then apply the resulting joint probability to individual pixels in the box. Pooling data in this way allows joint probabilities to be estimated in relatively small sample sizes, but assumes that...
Evaluation of Assumptions in Soil Moisture Triple Collocation Analysis Yılmaz, Mustafa Tuğrul (American Meteorological Society, 2014-06-01) Triple collocation analysis (TCA) enables estimation of error variances for three or more products that retrieve or estimate the same geophysical variable using mutually independent methods. Several statistical assumptions regarding the statistical nature of errors (e.g., mutual independence and orthogonality with respect to the truth) are required for TCA estimates to be unbiased. Even though soil moisture studies commonly acknowledge that these assumptions are required for an unbiased TCA, no study has sp...
Comparison of different yield criteria in various deep drawn cups Cogun, Ferah; Darendeliler, Haluk (Springer Science and Business Media LLC, 2017-03-01) The aim of the study is to evaluate the performance of three recent yield criteria namely; BBC2008-8p, Yld2003-8p, Hu2003 through the simulation of the hemispherical, cylindrical and square cup drawing processes by comparing the results with the ones obtained by using the von Mises criterion for the isotropic, kinematic and combined hardening and the Hill'48 criterion. For this purpose, two different sheet materials, SS304 stainless steel and DKP6112 steel, and various punch travels were used in the simulat...
Evaluation of Multiple Satellite-Based Precipitation Products over Complex Topography DERIN, Yagmur; Yılmaz, Koray Kamil (American Meteorological Society, 2014-08-01) This study evaluates the performance of four satellite-based precipitation (SBP) products over the western Black Sea region of Turkey, a region characterized by complex topography that exerts strong controls on the precipitation regime. The four SBP products include the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis version 7 experimental near-real-time product (TMPA-7RT) and post-real-time research-quality product (TMPA-7A), the Climate Prediction Center morphing technique...

Citation Formats

C. Yozgatlıgil, “Comparison of homogeneity tests for temperature using a simulation study,” INTERNATIONAL JOURNAL OF CLIMATOLOGY, pp. 62–81, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36860.