The spatial distribution of the seasonal and annual precipitation was analyzed in western Iran using data from 140 stations covering the period 1965–2000. Applying the Precipitation Concentration Index (PCI), the intra-annual precipitation variability was also studied. Furthermore, nine precipitation-derived parameters were used to regionalize climate in western Iran using principal component analysis and clustering techniques. Results suggest that five spatially homogenous sub-regions can be identified characterized by different precipitation regimes. The spatial pattern of seasonal precipitation seems to be highly controlled by the wide latitudinal extent of the region and by the pronounced orographic relieves, and the time of occurrence of the maximum precipitation varies from spring in the north to winter in the south. The time variability of dry and wet periods in the identified sub-regions was analyzed using the Precipitation Index (PI) and the existence of any long-term trend was tested. Results show that the northern and southern regions of western Iran are characterized by different climatic variability. Furthermore, a negative long-term linear trend in the north and a weak positive trend in the south of the study area have been detected though they are not statistically significant.

The relationships between large‐scale atmospheric circulation types and seasonal regimes of daily precipitation over Iran are assessed using daily precipitation from a high‐resolution gridded dataset provided by the Asian Precipitation‐Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE) Project. Regional spatial modes of daily precipitation variability were identified by S‐mode Principal Component Analysis (PCA) with Varimax rotation, applied to the subset of days when at least 10% of all grid‐points over Iran received precipitation ≥ 5 mm. The study refers to the period 1961–2004 and is carried out for each season (excluding summer) separately. To characterize the dynamical features associated with each regional precipitation regime (PR), composites of daily atmospheric fields are computed by only averaging days with rotated PCA scores ≥ 1.5 (strong positive phase). In autumn and winter, Iran is divided into five PRs, while four PRs are identified in spring. Results suggest that the spatial distribution of precipitation over Iran is largely governed by the geographical position of both the mid‐tropospheric trough over the Middle East and the Arabian anticyclone. In fact, in almost all PRs, the trough, as a pre‐conditioning factor, leads to regional‐scale ascending motions, whereas the Arabian anticyclone induces low‐tropospheric moisture transports from southern water bodies into the cyclonic systems near Iran, triggering rain‐generating conditions. Copyright © 2011 Royal Meteorological Society

The spatial variability of precipitation and drought are investigated for Portugal using monthly precipitation from 74 stations and minimum and maximum temperature from 27 stations, covering the common period of 1941–2006. Seasonal precipitation and the corresponding percentages in the year, as well as the precipitation concentration index (PCI), was computed for all 74 stations and then used as an input matrix for an R-mode principal component analysis to identify the precipitation patterns. The standardized precipitation index at 3 and 12 month time scales were computed for all stations, whereas the Palmer Drought Severity Index (PDSI) and the modified PDSI for Mediterranean conditions (MedPDSI) were computed for the stations with temperature data. The spatial patterns of drought over Portugal were identified by applying the S-mode principal component analysis coupled with varimax rotation to the drought indices matrices. The result revealed two distinct sub-regions in the country relative to both precipitation regimes and drought variability. The analysis of time variability of the PC scores of all drought indices allowed verifying that there is no linear trend indicating drought aggravation or decrease. In addition, the analysis shows that results for SPI-3, SPI-12, PDSI and MedPDSI are coherent among them.