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| Titel |
Hydrological extremes in hyper-arid regions: A diagnostic characterization of intense precipitation over the Arabian Peninsula |
| VerfasserIn |
NIranjan Kumar, Dara Entekhabi, Annalisa Molini |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250111806
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| Publikation (Nr.) |
 EGU/EGU2015-11950.pdf |
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| Zusammenfassung |
| Aridity is typically associated with deep and dry daytime boundary layers, stable nighttime
stratification, and divergent flows. All these factors are paramount in regulating the
hydro-climatology of hyper-arid regions, resulting in extremely intermittent – and often
intense – spatial and temporal precipitation patterns. If large-scale circulation has clearly a
crucial role in advecting the atmospheric moisture necessary to the onset of extreme
precipitation in arid regions, the understanding of how this synoptic-scale forcing
contributes to local extremes under aridity still remains exceedingly limited. We present
here a diagnostic study of intense precipitation in the Central Arabian Peninsula,
based on the analysis of local extreme signatures embedded in synoptic patterns.
Special emphasis is given to the genesis of winter extremes over the Peninsula, and to
possible effects of synchronization between the atmospheric circulation over the
Mediterranean and the Indian Ocean. Based on composites of tropospheric wind, precipitable
water, meridional wind, vertically integrated moisture flux convergence and potential
vorticity for a large ensemble of intense events, we show that moisture necessary
to trigger winter extremes over the Peninsula starts to build up in average 8 days
before heavy rainfall occurrence, mainly as a consequence of the interplay between
the Mediterranean and the Monsoonal circulation. Moisture advection is in turn
associated with an upper-troposphere cyclonic circulation and pronounced potential
vorticity intrusions. Overall, our results show how large-scale precursors can be
effectively used to improve the predictability of local rainfall extremes in hyper-arid
regions. |
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