Climate conditions and drought assessment with the Palmer Drought Severity Index in Iran: evaluation of CORDEX South Asia climate projections (2070–2099)

Autor: Parviz Irannejad, Giuseppe Mendicino, Javad Bazrafshan, Alfonso Senatore, Somayeh Hejabi
Rok vydání: 2018
Předmět:
Zdroj: Climate Dynamics. 52:865-891
ISSN: 1432-0894
0930-7575
DOI: 10.1007/s00382-018-4171-x
Popis: Climate change projections were evaluated over both the whole Iran and six zones having different precipitation regimes considering the CORDEX South Asia dataset, for assessing space–time distribution of drought occurrences in the future period 2070–2099 under RCP4.5 scenario. Initially, the performances of eight available CORDEX South Asia Regional Climate Models (RCMs) were assessed for the baseline period 1970–2005 through the GPCC v.7 precipitation dataset and the CFSR temperature dataset, which were previously selected as the most reliable within a set of five global datasets compared to 41 available synoptic stations. Though the CCLM RCM driven by the MPI-ESM-LR General Circulation Model is in general the most suitable for temperature and, together with the REMO 2009 RCM also driven by MPI-ESM-LR, for precipitation, their performances do not overwhelm other models for every season and zone in which Iranian territory was divided according to a principal component analysis approach. Hence, a weighting approach was tested and adopted to take into account useful information from every RCM in each of the six zones. The models resulting more reliable compared to current climate show a strong precipitation decrease. Weighted average predicts an overall yearly precipitation decrease of about 20%. Temperature projections provide a mean annual increase of 2.4 °C. Future drought scenarios were depicted by means of the self-calibrating version of the Palmer drought severity index (SC-PDSI) model. Weighted average predicts a sharp drying that can be configured as a real shift in mean climate conditions, drastically affecting water resources of the country.
Databáze: OpenAIRE
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