Science Source
Seung-Ki Min, Xuebin Zhang, Francis W. Zwiers, Petra Friederichs, Andreas Hense
Climate Dynamics
Published date February 5, 2008
Climate Dynamics
Published date February 5, 2008
Signal detectability in extreme precipitation changes assessed from twentieth century climate simulations
- Assesses the detectability of external influences in changes of precipitation extremes in the twentieth century
- Defines three indices of precipitation extremes from the generalized extreme value (GEV) distribution: the 20-year return value (P 20), the median (P m), and the cumulative probability density as a probability-based index (PI)
- Analyzes time variations of area-averages of these three extreme indices over different spatial domains from the globe to continental regions
- Estimates the amplitudes of response patterns to anthropogenic (ANT), natural (NAT), greenhouse-gases (GHG), and sulfate aerosols (SUL) forcings, treating all forcing simulations (ALL; natural plus anthropogenic) of the twentieth century as observations and using a preindustrial control run (CTL) to estimate the internal variability
- Results show that there are decisively detectable ANT signals in extreme precipitation changes in global, hemispheric, and zonal band areas
- Finds that when only land is considered, the global and hemispheric detection results are unchanged, but detectable ANT signals in the zonal bands are limited to low latitudes
- Finds that the ANT signals are also detectable in the P m and PI but not in P 20 at continental scales over Asia, South America, Africa, and Australia
- Results indicate that indices located near the center of the GEV (generalized extreme value) distribution (P m and PI) may give better signal-to-noise ratio than indices representing the tail of the distribution (P 20)
- Finds that GHG and NAT signals are also detectable, but less robustly for more limited extreme indices and regions
- Finds that these results are largely insensitive when model data are masked to mimic the availability of the observed data
- An imperfect model analysis in which fingerprints are obtained from simulations with a different GCM suggests that ANT is robustly detectable only at global and hemispheric scales, with high uncertainty in the zonal and continental results
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