Testing for collective statistical significance in climate change detection studies

Abstract

We examine several approaches to detecting statistical significance of trends defined on a grid, that is, on a regional scale. To this end, we introduce a novel simple procedure of significance testing, which is based on counting signs of local trends (sign test), and compare it with four other approaches to testing collective significance of trends (counting, extended Kendall, Walker, and fdr tests).

Keywords

• climate change
• significance testing
• collective statistical significance
• temperature
• trend detection