The sources of extreme precipitation predictability; the case of the ‘Wet’ Red Sea Trough

Hochman, Assaf; Plotnik, Tair; Marra, Francesco; Shehter, Elizabeth-Ruth; Raveh‐Rubin, Shira; Magaritz-Ronen, Leehi

doi:10.1016/j.wace.2023.100564

Cited by 3 publications

(2 citation statements)

References 49 publications

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“…This transitional period, from the dry and intense summer heat to more moderate temperatures, marks the onset of the region's rainy season 18 . The Mediterranean Sea serves as the principal moisture source, as humid air masses from the sea converge with the prevailing arid continental air 19 . This juxtaposition gives rise to diverse precipitation patterns, ranging from isolated convective thunderstorms to more extensive stratiform rainfall events 20 .…”

Section: Introductionmentioning

confidence: 99%

Unraveling sub-seasonal precipitation variability in the Middle East via Indian Ocean sea surface temperature

Hochman,

Shachar,

Gildor

2024

Sci Rep

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This study examines sub-seasonal precipitation anomalies, challenging to predict yet vital for society and the environment. Focusing on October, we investigate correlations between the Indian Ocean Dipole Mode Index (DMI), West Tropical Indian Ocean Index (WTIO), and Middle Eastern precipitation. We find robust correlations (~ 0.7), up to a two-month lag, demonstrating strong links between these climate indices and rainfall patterns, potentially suggesting sub-seasonal precipitation predictability. Over the past four decades, DMI and WTIO have shown a significant upward trend of ~ 0.4 °C, intensifying their impact on precipitation dynamics. This trend signifies evolving Indian Ocean climate patterns with potential regional consequences and is projected to continue in the twenty-first century. Significant correlations also emerge between DMI, WTIO, and maximum daily precipitation, highlighting their role in extreme rainfall events. Finally, our study attributes most of October’s precipitation variability to Indian Ocean sea surface temperature variations. These temperature anomalies influence the Indian Ocean’s Walker circulation, affecting water vapor flux to the Middle East and shaping regional precipitation. Our findings underscore the importance of these indices in understanding and predicting Middle East climate variability, revealing intricate ocean–atmosphere interactions.

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Section: Introductionmentioning

confidence: 99%

Unraveling sub-seasonal precipitation variability in the Middle East via Indian Ocean sea surface temperature

Hochman,

Shachar,

Gildor

2024

Sci Rep

Self Cite

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“…The resulting rainfall pattern is highly dependent on the cyclone's path, orographic forcing and mesoscale airstreams (Catto & Raveh‐Rubin, 2019; Ziv et al, 2010). Over Israel, rain distribution is dominated by convection (Goldreich, 2003; Hochman et al, 2023; Ziv et al, 2009), which further reduces its predictability. Several larger scale modes (subseasonal Rossby waves, the North Atlantic storm track, decadal oscillations) also affect rain in the region over longer periods (Black, 2012; Feldstein & Dayan, 2008; Gaetani et al, 2011; Krichak & Alpert, 2005; Seager et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

A multiscale approach to statistical downscaling of daily precipitation: Israel as a test case

Sandler,

Saaroni,

Ziv

et al. 2023

Intl Journal of Climatology

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Rainfall in the Eastern Mediterranean is strongly modulated by complex topography and localized mesoscale processes. General circulation models (GCMs) struggle to capture daily precipitation variability in the region, both in time and in space. Rain in the Eastern Mediterranean occurs within a hierarchy of scales, as synoptic scale structures often drive local rainfall patterns. Daily rain prediction in the region can therefore benefit from analog downscaling—a nonlinear regression of a high‐resolution predictand from past synoptic‐scale predictors. We present a multiscaled downscaling algorithm of daily rain over Israel. The underlying goal is to create a mechanism‐based tool that will improve the analysis and prediction of precipitation on short time scales in models that cannot produce the field explicitly. We train the algorithm using coarse grid ERA5 reanalysis data and measurements from 21 rain gauges. The routine uses a k‐nearest neighbours algorithm to find the most similar past instances (i.e., analogs) for every predicted day. Analog selection is performed in two steps, based on scale (synoptic and local), as to not overshadow correlative but local predictors. The algorithm also includes several unique aspects tailored to Mediterranean climate: subdaily predictors of cyclone life cycles; representation of upper level cyclonic drivers; and the inclusion of rainfall potential using the Modified K‐Index (MKI). The proposed algorithm has better accuracy (66% correct predictions) compared to non‐downscaled reanalysis and climatological predictions. It better captures the spatial rainfall variance, mitigates the “drizzle bias,” and improves skill in extreme event prediction. However, it underestimates very rainy events and has trouble fully representing the spatial variance in the region. Nonetheless, our algorithm represents the potential for computationally inexpensive downscaling of daily precipitation in the Mediterranean with various possible applications, for example, characterization of droughts and storms, linking hydrological and synoptic scale processes and introducing uncertainty estimates using large ensembles.

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Seasonal Characteristics of Forecasting Uncertainties in Surface PM2.5 Concentration Associated with Forecast Lead Time over the Beijing-Tianjin-Hebei Region

Du,

Zhao,

Feng

et al. 2024

Adv. Atmos. Sci.

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The sources of extreme precipitation predictability; the case of the ‘Wet’ Red Sea Trough

Cited by 3 publications

References 49 publications

Unraveling sub-seasonal precipitation variability in the Middle East via Indian Ocean sea surface temperature

Unraveling sub-seasonal precipitation variability in the Middle East via Indian Ocean sea surface temperature

A multiscale approach to statistical downscaling of daily precipitation: Israel as a test case

Seasonal Characteristics of Forecasting Uncertainties in Surface PM2.5 Concentration Associated with Forecast Lead Time over the Beijing-Tianjin-Hebei Region

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