A Trade-Off Relation between Temporal and Spatial Averaging Scales on Future Precipitation Assessment

[摘要]  The detectability of climate change signals such as a precipitation change depends on temporal and spatial averaging scales. The present study aims to clarify the dependence of the detectability on the two averaging scales by analyzing the difference in daily precipitation between present (1979-2003) and future (2075-2099) climates. The dataset for the analysis is obtained from an atmospheric general circulation model. The robustness of the precipitation change signal is evaluated with the signal-to-noise ratio (SNR), which is often used in statistical tests to detect climate change signals. The SNR is increased and the detectability of the precipitation change signal is enhanced with increases in the two averaging scales. When either averaging scale is increased (decreased) with a constant SNR, the other averaging scale needs to be decreased (increased); this is the trade-off relation between the two averaging scales. The trade-off relation is obtained quantitatively and provides useful information for climate change impact assessments using various temporal and spatial scales or resolutions. The characteristics of the trade-off relation are found to differ qualitatively among the tropics, mid-latitudes, and subpolar regions and to derive from the precipitation power spectrum representing spatio-temporal scales of precipitation-related meteorological phenomena, e.g., baroclinic waves.

[学科分类] 大气科学

[关键词] climate change assessment;atmospheric general circulation model;averaging scale;robustness of climate change signal