Multi-decadal classification of synoptic weather types, observed trends and links to rainfall characteristics over Saudi Arabia

*Correspondence: Ahmed M. El Kenawy, Earth System Observations and Modeling Group, Water Desalination and Reuse Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia e-mail: [email protected] An automated version of the Lamb weather type classification scheme was employed to characterize daily circulation conditions in Saudi Arabia from 1960 to 2005. Daily gridded fields of sea level pressure (SLP) from both the NCEP/NCAR and the European Center for Medium-Range Weather Forecast (ECMWF) reanalysis data (ERA40) were used as input data for this classification. The output catalog included 10 basic types, which describe the direction and vorticity of airflow in the region (i.e., cyclonic, anti-cyclonic, and directional). In general, our findings indicate that cyclonic (C) days represent the most frequent type among all days, with 69.2% of the annual count of days from 1960 to 2005, followed by SE directional flows (21%). It was also determined that airflows originating from the Indian Ocean (i.e., S, SE, and E) are more frequent than those from the Mediterranean and Red Seas (i.e., W, NW, and SW). The defined weather types were assessed for the presence of inter-annual and intra-annual trends using the Mann–Kendall tau statistic. The trend analysis suggests statistically significant changes in the frequencies of a majority of the weather types from 1960 to 2005. The relationship between the daily occurrence of rainfall and the frequency of individual weather types was also described using daily rainfall data from a network of 87 weather observatories. Results demonstrate that increasing frequencies of weather types connected to easterly inflows support higher precipitation amounts over the study domain. Characterizing the association between atmospheric circulation patterns and rainfall in Saudi Arabia is important for understanding potential impacts related to climate variability and also for developing circulation-based downscaling methods.