A Unified Framework for Trend Uncertainty Assessment in Climate Data Records: Demonstration on Global Mean Sea Level

Abstract

Trends of essential climate variables are often estimated from climate data records to quantify changes in the Earth system. An understanding of the uncertainty in a trend is essential for accurately determining the significance of a trend and attributing its causes. Despite this importance, trend-uncertainty estimates rarely account for all known sources of uncertainty. Common approaches neglect measurement-system instability or neglect the impact of natural variability on trend uncertainty. Such neglect can result in over-confidence in trend estimates. This study addresses trend-uncertainty assessment, particularly the need to account for the combined effects of measurement instability and natural variability on the trend uncertainty. The study presents a novel, unified framework for trend estimation that combines available measurement uncertainty information with empirical modelling of natural climate variability to achieve a more accurate uncertainty estimate. The framework is demonstrated for a time series of global mean sea level observations, obtaining more realistic trend-uncertainty values. The framework is applicable to most other climate data records. Adopting this approach will enhance confidence in climate change analysis through more accurate trend-uncertainty assessment in climate studies.