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Extreme precipitation events in the otherwise arid Middle East can cause flooding with dramatic socioeconomic impacts. Most of these events are associated with tropical-extratropical interactions, whereby a stratospheric potential vorticity (PV) intrusion reaches deep into the subtropics and forces an incursion of high poleward vertically integrated water vapor transport (IVT) into the Middle East. This study presents an object-based identification method for extreme precipitation events based on the combination of these two larger-scale meteorological features. The general motivation for this approach is that precipitation is often poorly simulated in relatively coarse weather and climate models, whereas the synoptic-scale circulation is much better represented. The algorithm is applied to ERA-Interim reanalysis data (1979-2015) and detects 90% (83%) of the 99th (97.5th) percentile of extreme precipitation days in the region of interest. Our results show that stratospheric PV intrusions and IVT structures are intimately connected to extreme precipitation intensity and seasonality. The farther south a stratospheric PV intrusion reaches, the larger the IVT magnitude, and the longer the duration of their combined occurrence, the more extreme the precipitation. Our algorithm detects a large fraction of the climatological rainfall amounts (40-70%), heavy precipitation days (50-80%), and the top 10 extreme precipitation days (60-90%) at many sites in southern Israel and the northern and western parts of Saudi Arabia. This identification method provides a new tool for future work to disentangle teleconnections, assess medium-range predictability, and improve understanding of climatic changes of extreme precipitation in the Middle East and elsewhere.

Plain Language Summary Torrential rains lead almost every year to flooding and fatalities in the arid Middle East. At the same time, such heavy rainfall events can recharge scarce freshwater resources in the subtropical desert region. These events often occur when the atmospheric circulations of the midlatitudes and the tropics interact with another. More specifically, a disturbance from the midlatitudes intrudes into the subtropics and initiates an incursion of tropical moisture across the Middle East. In our study we developed an identification method for heavy rainfall events based on the combination of these two meteorological processes. This unique approach avoids dependency on rainfall data which is often poorly simulated in numerical weather and climate models, whereas the atmospheric circulation is much better represented. Our method successfully detects events that contribute to a large fraction of annual rainfall amounts (40-70%) and heavy rainfall days (50-90%) in the arid parts of the Levant and the Arabian Peninsula. Moreover, the characteristics and duration of the midlatitude disturbances and tropical moisture incursions strongly influence the rainfall severity. This knowledge and identification method can support weather prediction and early warnings for heavy rainfall events as well as future studies on their climatic changes due to global warming.