Simple Practices in Climatological Analyses: A Review

Abstract Many studies in Meteorology and Climatology use methodologies that overestimate or even underestimate the statistical significance of the results. Analyses that underestimate the role of trends and temporal or spatial dependency in the data sets can lead to incorrect conclusions. On the other hand, unnecessarily rigorous analyses can undermine the conclusions. The objective of this article is to discuss some simple practices, commonly neglected, that can produce results much more robust and statistically significant. This paper discusses some problems related to the calculation of the mean annual cycle and anomalies, trend analyzes, and temporal and spatial dependency, emphasizing statistical hypothesis testing.