Westward mountain-gap wind jets of the northern Red Sea as seen by QuikSCAT
KAUST Grant NumberKSA00011
Online Publication Date2018-03-19
Print Publication Date2018-05
Permanent link to this recordhttp://hdl.handle.net/10754/629756
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AbstractWe analyse ten years of QuikSCAT satellite surface winds to statistically characterize the spatio-temporal variability of the westward mountain-gap wind jets over the northern Red Sea. These wind jets bring relatively cold and dry air from the Arabian Desert, increasing heat loss and evaporation over the region similar to cold-air outbreaks from mid and subpolar latitudes. QuikSCAT captures the spatial structure of the wind jets and agrees well with in situ observations from a heavily instrumented mooring in the northern Red Sea. The local linear correlations between QuikSCAT and in situ winds are 0.96 (speed) and 0.85 (direction). QuikSCAT also reveals that cross-axis winds such as the mountain-gap wind jets are a major component of the regional wind variability. The cross-axis wind pattern appears as the second (or third) mode in the four vector Empirical Orthogonal Function analyses we performed, explaining between 6% to 11% of the wind variance. Westward wind jets are typical in winter, especially in December and January, but with strong interannual variability. Several jets can occur simultaneously and cover a large latitudinal range of the northern Red Sea, which we call large-scale westward events. QuikSCAT recorded 18 large-scale events over ten years, with duration between 3 to 8 days and strengths varying from 3–4 to 9–10 m/s. These events cause large changes in the wind stress curl pattern, imposing a remarkable sequence of positive and negative curl along the Red Sea main axis, which might be a wind forcing mechanism for the oceanic mesoscale circulation.
CitationMenezes VV, Farrar JT, Bower AS (2018) Westward mountain-gap wind jets of the northern Red Sea as seen by QuikSCAT. Remote Sensing of Environment 209: 677–699. Available: http://dx.doi.org/10.1016/j.rse.2018.02.075.
SponsorsWe wish to acknowledge the use of the Ferret program (NOAA/PMEL) and NCL for analysis and graphics in this paper. We thank Houshuo Jiang for sharing the WRF model outputs and Bryan Stiles for helping with the QuikSCAT coastal data. VVM also acknowledges Marcio Vianna for fruitful discussion about wind jets and their potential effects. QuikSCAT (or SeaWinds) data are produced by Remote Sensing Systems and sponsored by the NASA Ocean Vector Winds Science Team. Data are available at www.remss.com. WHOI/KAUST mooring data collected during the WHOI-KAUST collaboration was made possible by Award Nos. USA00001, USA00002, and KSA00011 to WHOI by KAUST in the Kingdom of Saudi Arabia. The data are available from the authors upon request. This work was supported by NSF grant OCE-1435665 and NASA grant NNX14AM71G.
JournalRemote Sensing of Environment