Identification and extraction length of dry spells in arid and semi-arid regions is very important. Thus, the use of climate change prediction models for study the behavior of the climatic parameters in the future tim...Identification and extraction length of dry spells in arid and semi-arid regions is very important. Thus, the use of climate change prediction models for study the behavior of the climatic parameters in the future time is inevitable. With recognition of the spatial and temporal behavior variables such as precipitation, we can prevent from destructive effects. In this research, the performance of Atmosphere-Ocean General Circulation Models (AOGCMs) was evaluated for simulation length of dry spells in the south-western area of Iran. The results show that the length of dry spell is relatively decreased in cold seasons (autumn and winter) and increased in the warm season (spring and summer) in both A2 and B2 Scenarios. The length of the dry spell on monthly scale for scenario A2 is 6% (equivalent to 2 days) and for scenario B2 is 9 percent (approximately 2.4 day) increased compared to the baseline period. For assess the uncertainty, AOGCMs were weighting. The results show that the best model for simulation of dry spells is HADCM3 and GFCM2.1, because the results have a less error. On the other hand, NCCCSM have the lowest weight for simulation dry spells in both scenarios.展开更多
文摘Identification and extraction length of dry spells in arid and semi-arid regions is very important. Thus, the use of climate change prediction models for study the behavior of the climatic parameters in the future time is inevitable. With recognition of the spatial and temporal behavior variables such as precipitation, we can prevent from destructive effects. In this research, the performance of Atmosphere-Ocean General Circulation Models (AOGCMs) was evaluated for simulation length of dry spells in the south-western area of Iran. The results show that the length of dry spell is relatively decreased in cold seasons (autumn and winter) and increased in the warm season (spring and summer) in both A2 and B2 Scenarios. The length of the dry spell on monthly scale for scenario A2 is 6% (equivalent to 2 days) and for scenario B2 is 9 percent (approximately 2.4 day) increased compared to the baseline period. For assess the uncertainty, AOGCMs were weighting. The results show that the best model for simulation of dry spells is HADCM3 and GFCM2.1, because the results have a less error. On the other hand, NCCCSM have the lowest weight for simulation dry spells in both scenarios.
