Title: On the internal variability of simulated daily precipitation
Authors: SCHINDLER AnneTORETI ANDREAZAMPIERI MatteoSCOCCIMARRO EnricoGUALDI S.FUKUTOME SophieXOPLAKI ElenaLUTERBACHER Juerg
Citation: JOURNAL OF CLIMATE vol. 28 no. 9 p. 3624-3630
Publisher: AMER METEOROLOGICAL SOC
Publication Year: 2015
JRC N°: JRC93244
ISSN: 0894-8755
URI: http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-14-00745.1
http://publications.jrc.ec.europa.eu/repository/handle/JRC93244
DOI: 10.1175/JCLI-D-14-00745.1
Type: Articles in periodicals and books
Abstract: Climate model simulations are the main tool to provide information about possible future climates. Apart from scenario uncertainties and model error, internal variability is a major source of uncertainty, obfuscating predictions of future changes. Here, we propose a series of statistical tests to determine the shortest time window necessary to capture the internal variability of precipitation in a stationary climate. The length of this shortest time window thus expresses internal variability in terms of years. The method is applied globally to daily precipitation in a 200-year pre-industrial climate simulation with the CMCC CM coupled general circulation model. We assess differences in precipitation distribution with the Cramer-von Mises two sample test, account for multiple testing at grid cell level with the Walker test and determine field significance by calculating the Bejamini-Hochberg false-discovery-rate. We show that internal variability of daily precipitation is regionally and seasonally dependent, and that regions requiring long time windows do not necessarily coincide with areas with large standard deviation. The estimated timescales are longer over sea than land, longer in the tropics compared to the mid latitudes, and they are longer for the intermediate seasons than for winter and summer. For many land grid cells 30 seasons suffice to capture the internal variability of daily precipitation. There exist regions, however, where not even 50 years sample the internal variability. Our results show that diagnosing daily precipitation change based on fixed global snapshots of one climate simulation at different times might not be a robust detection method.
JRC Directorate:Sustainable Resources

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