Testing for trends on a regional scale: Beyond local significance

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