A new estimator of heat periods for decadal climate predictions – a complex network approach
Regional decadal predictions have emerged in the past few years as a research field with high application potential, especially for extremes like heat and drought periods. However, up to now the prediction skill of decadal hindcasts, as evaluated with standard methods, is moderate and for extreme va...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-08-01
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| Series: | Nonlinear Processes in Geophysics |
| Online Access: | http://www.nonlin-processes-geophys.net/23/307/2016/npg-23-307-2016.pdf |
| Summary: | Regional decadal predictions have emerged in the past few years as a research
field with high application potential, especially for extremes like heat and
drought periods. However, up to now the prediction skill of decadal
hindcasts, as evaluated with standard methods, is moderate and for extreme
values even rarely investigated. In this study, we use hindcast data from
a regional climate model (CCLM) for eight regions in Europe and quantify the
skill of the model alternatively by constructing time-evolving climate
networks and use the network correlation threshold (link strength) as
a predictor for heat periods. We show that the skill of the network measure
to estimate the low-frequency dynamics of heat periods is superior for
decadal predictions with respect to the typical approach of using a fixed
temperature threshold for estimating the number of heat periods in Europe. |
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| ISSN: | 1023-5809 1607-7946 |