Water Resources Research · 2007 · 315 citations · 52 references
Natural SciencesEarth SciencesHydrologyClimate ScienceClimatologyTime Series AnalysisClimate ChangeClimate Data AnalysisClimate ModelingClimate VariabilityHydrologic Time Series AnalysisPhysical ClimatologyClimate Time Series AnalysisHydroclimatic Variability AnalysisHydrologic StatisticsLong-term Climate VariabilityPersistenceStatistical Significance TestingStatistical TestingUncertainty Characterization
Hydrologic research depends on climatological inputs, yet debates over their statistical behavior—especially long‑term persistence (LTP)—highlight a gap in understanding its impact on uncertainty and physical interpretation. The study seeks to demonstrate that temperature series consistent with LTP markedly increase uncertainty in statistical estimation and reduce significance in testing compared to classical approaches. Analytical methods were applied to temperature time series to quantify how LTP affects statistical uncertainty and significance. The analysis shows that LTP inflates uncertainty and weakens statistical significance, indicating that hydroclimatic statistical analyses must be revisited and that statistical tests alone cannot confirm or refute LTP.
Today, hydrologic research and modeling depends largely on climatological inputs, whose physical and statistical behavior are the subject of many debates in the scientific community. A relevant ongoing discussion is focused on long‐term persistence (LTP), a natural behavior identified in several studies of instrumental and proxy hydroclimatic time series, which, nevertheless, is neglected in some climatological studies. LTP may reflect a long‐term variability of several factors and thus can support a more complete physical understanding and uncertainty characterization of climate. The implications of LTP in hydroclimatic research, especially in statistical questions and problems, may be substantial but appear to be not fully understood or recognized. To offer insights on these implications, we demonstrate by using analytical methods that the characteristics of temperature series, which appear to be compatible with the LTP hypothesis, imply a dramatic increase of uncertainty in statistical estimation and reduction of significance in statistical testing, in comparison with classical statistics. Therefore we maintain that statistical analysis in hydroclimatic research should be revisited in order not to derive misleading results and simultaneously that merely statistical arguments do not suffice to verify or falsify the LTP (or another) climatic hypothesis.
52