2009
DOI: 10.1029/2008jd010873
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Satellite‐based midlatitude cyclone statistics over the Southern Ocean: 1. Scatterometer‐derived pressure fields and storm tracking

Abstract: [1] A wavelet-based method is described for incorporating swaths of surface pressure derived from scatterometer measurements into surface pressure analyses obtained from the European Centre for Medium-range Weather Forecasts (ECMWF). The resulting modified pressure fields are used to identify low-pressure centers over the Southern Ocean and to build statistics of midlatitude cyclones during 7 years of the SeaWinds-on-QuikSCAT operational period (July 1999 to June 2006. The impact of the scatterometer-derived p… Show more

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Cited by 35 publications
(32 citation statements)
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“…τ max is modulated by a sinusoidal seasonal cycle so it varies from τ max0 /2 during austral summer and τ max0 during austral winter, with τ max0 = 1.5 N m −2 . Each vortex forms and vanishes at the same latitude (no meridional displacement) but the latitude of formation varies following a Gamma distribution similar to the meridional distribution inferred from cyclones tracks in Patoux et al (2009), with most of the cyclones located between 50 and 70 • S. The distribution follows a cycle that repeats each 10 years. The lifetime of the storms is computed such that one cyclone travels the 2000 km zonal extension of the domain with full strength (∼ 2 days).…”
Section: Appendix A: Wind Forcing Strategymentioning
confidence: 99%
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“…τ max is modulated by a sinusoidal seasonal cycle so it varies from τ max0 /2 during austral summer and τ max0 during austral winter, with τ max0 = 1.5 N m −2 . Each vortex forms and vanishes at the same latitude (no meridional displacement) but the latitude of formation varies following a Gamma distribution similar to the meridional distribution inferred from cyclones tracks in Patoux et al (2009), with most of the cyclones located between 50 and 70 • S. The distribution follows a cycle that repeats each 10 years. The lifetime of the storms is computed such that one cyclone travels the 2000 km zonal extension of the domain with full strength (∼ 2 days).…”
Section: Appendix A: Wind Forcing Strategymentioning
confidence: 99%
“…These high-frequency winds induce intense near-inertial energy and mixing into the ocean interior. From the analysis of scatterometer measurements, Patoux et al (2009) provided general statistics of the spatial and temporal variability of the Southern Ocean midlatitude cyclones for the period 1999-2006: most of the cyclones occurred between 50 and 70 • S, have a radius between 400 and 800 km and last between 12 h and 5 days. Mesoscale cyclones lasting less than 4 days represent about 75 % of all cyclone tracks ).…”
Section: Modelmentioning
confidence: 99%
“…These studies have focused on particular localized scenarios, and their relevance has not yet been contextualized within the broader seasonal mean state. The SO, in particular the SAZ, is a region of strong eddy (Frenger et al, ) and small‐scale frontal activity (du Plessis et al, , ) and strong winds from passing storms (Patoux et al, ; Yuan, ; Yuan et al, ). We hypothesize that storms increase mixing and advection during summer that are enhanced by wind‐mesoscale interactions and may result in nonnegligible physical iron supplies from the subsurface to the surface ocean to support phytoplankton production beyond what is possible by the once‐off winter supply.…”
Section: Introductionmentioning
confidence: 99%
“… Patoux et al [2009] (hereafter PYL) described how to use SLP fields derived from QuikSCAT (QS) scatterometer winds using the University of Washington planetary boundary layer (UWPBL) model [ Brown and Levy , 1986; Brown and Liu , 1982; Brown and Zeng , 1994; Patoux , 2004] to incorporate mesoscale to synoptic‐scale satellite information into NWP model surface analyses. The high‐wavenumber wavelet coefficients of the scatterometer‐derived pressure fields were injected into ECMWF SLP analyses over the Southern Ocean with the following method: (1) Swaths of surface pressure were retrieved from QS winds using the UWPBL model.…”
Section: Introductionmentioning
confidence: 99%