Uncertainty analysis of impacts of climate change on snow processes: Case study of interactions of GCM uncertainty and an impact model
| Autor: | Takeo Yoshida, Takao Masumoto, Ryoji Kudo |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Coupled model intercomparison project
010504 meteorology & atmospheric sciences 0208 environmental biotechnology Elevation Climate change 02 engineering and technology Snow 01 natural sciences Subarctic climate 020801 environmental engineering Climatology Temperate climate Environmental science Mean radiant temperature Uncertainty analysis 0105 earth and related environmental sciences Water Science and Technology |
| Zdroj: | SC10201811010022 NARO成果DBa Green open Access This journal has an embargo period of 24 months. 著者版依頼中／Applying for the author's permission. |
| ISSN: | 0022-1694 |
| DOI: | 10.1016/j.jhydrol.2017.03.007 |
| Popis: | The impact of climate change on snow water equivalent (SWE) and its uncertainty were investigated in snowy areas of subarctic and temperate climate zones in Japan by using a snow process model and climate projections derived from general circulation models (GCMs). In particular, we examined how the uncertainty due to GCMs propagated through the snow model, which contained nonlinear processes defined by thresholds, as an example of the uncertainty caused by interactions among multiple sources of uncertainty. An assessment based on the climate projections in Coupled Model Intercomparison Project Phase 5 indicated that heavy-snowfall areas in the temperate zone (especially in low-elevation areas) were markedly vulnerable to temperature change, showing a large SWE reduction even under slight changes in winter temperature. The uncertainty analysis demonstrated that the uncertainty associated with snow processes (1) can be accounted for mainly by the interactions between GCM uncertainty (in particular, the differences of projected temperature changes between GCMs) and the nonlinear responses of the snow model and (2) depends on the balance between the magnitude of projected temperature changes and present climates dominated largely by climate zones and elevation. Specifically, when the peaks of the distributions of daily mean temperature projected by GCMs cross the key thresholds set in the model, the GCM uncertainty, even if tiny, can be amplified by the nonlinear propagation through the snow process model. This amplification results in large uncertainty in projections of CC impact on snow processes. |
| Databáze: | OpenAIRE |
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