Testing for Trends on a Regional Scale: Beyond Local Significance

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378289%3A_____%2F21%3A00556716" target="_blank" >RIV/68378289:_____/21:00556716 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11310/21:10433548 RIV/86652079:_____/21:00603924

Result on the web

<a href="https://journals.ametsoc.org/view/journals/clim/aop/JCLI-D-19-0960.1/JCLI-D-19-0960.1.xml" target="_blank" >https://journals.ametsoc.org/view/journals/clim/aop/JCLI-D-19-0960.1/JCLI-D-19-0960.1.xml</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1175/JCLI-D-19-0960.1" target="_blank" >10.1175/JCLI-D-19-0960.1</a>

Result language

angličtina

Original language name

Testing for Trends on a Regional Scale: Beyond Local Significance

Original language description

Studies detecting trends in climate elements typically concentrate on their local significance, ignoring the question of whether the significant local trends may or may not have occurred as a result of chance. This paper fills this gap by examining several approaches to detecting statistical significance of trends defined on a grid (i.e., on a regional scale). To this end, we introduce a novel simple procedure of significance testing that is based on counting signs of local trends (sign test), and we compare it with five other approaches to testing collective significance of trends: counting, extended Mann-Kendall, Walker, false detection rate (FDR), and regression tests. Synthetic data are used to construct null distributions of trend statistics, to determine critical values of the tests, and to assess the performance of tests in terms of type-II error. For lower values of spatial and temporal autocorrelations, the sign test and extended Mann-Kendall test perform slightly better than the counting test: these three tests outperform the Walker, FDR, and regression tests by a wide margin. For high autocorrelations, which is a more realistic case, all tests become similar in their performance, with the exception of the regression test, which performs somewhat worse. Some tests cannot be used under specific conditions because of their construction: the Walker and FDR tests for high temporal autocorrelations, and the sign test under high spatial autocorrelations.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10509 - Meteorology and atmospheric sciences

Project

<a href="/en/project/GA16-04676S" target="_blank" >GA16-04676S: Novel approaches to assessing climatic trends and their statistical significance</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Climate

ISSN

0894-8755

e-ISSN

1520-0442

Volume of the periodical

34

Issue of the periodical within the volume

13

Country of publishing house

US - UNITED STATES

Number of pages

17

Pages from-to

5349-5365

UT code for WoS article

000775651000012

EID of the result in the Scopus database

2-s2.0-85106949119