Jérôme Patoux

Sensitivity of Midlatitude Storm Intensification to Perturbations in the Sea Surface Temperature near the Gulf Stream

AbstractThe Gulf Stream region is a primary location for midlatitude storm cyclogenesis and growth. However, the influence of sea surface temperature (SST) on storms in the region is still under question, particularly after a storm has developed. Using the Weather Research and Forecasting (WRF) model, a storm that intensified as it transited northward across the Gulf Stream is simulated multiple times using different SST boundary conditions. These experiments test the storm response to changes in both the absolute value of the SST and the meridional SST gradient. Across the different simulations, the storm strength increases monotonically with the magnitude of the SST perturbations, even when the perturbations weaken the SST gradient. The storm response to the SST perturbations is driven by the latent heat release in the storm warm conveyor belt (WCB). During the late stages of development, the surface fluxes under the storm warm sector regulate the supply of heat and moisture to the WCB. This allows the ...

The Signature of the Midlatitude Tropospheric Storm Tracks in the Surface Winds

Abstract Storm-track analysis is applied to the meridional winds at 10 m and 850 hPa for the winters of 1999–2006. The analysis is focused on the North Atlantic and North Pacific Ocean basins and the Southern Ocean spanning the region south of the Indian Ocean. The spatial patterns that emerge from the analysis of the 850-hPa winds are the typical free-tropospheric storm tracks. The spatial patterns that emerge from the analysis of the surface winds differ from the free-tropospheric storm tracks. The spatial differences between the surface and free-tropospheric storm tracks can be explained by the influence of the spatial variability in the instability of the atmospheric boundary layer. Strongly unstable boundary layers allow greater downward mixing of free-tropospheric momentum (momentum mixing), and this may be the cause of the stronger surface storm tracks in regions with greater instability in the time mean. Principal component analysis suggests that the basin-scale variability that is reflected in th...

Spectral analysis of QuikSCAT surface winds and two‐dimensional turbulence

A spectral decomposition of QuikSCAT surface wind vectors reveals different levels of variance and different values of the spectral slope in various regions of the world ocean for the 12 months investigated. The traditional considerations on the factors affecting the shape of the spectra are reviewed and compared to the results. In particular, the influence of large-scale synoptic systems is shown by comparing the steeper and more energetic spectra of the midlatitudes to the shallower spectra of the tropics. Similarly, the signature of convection is investigated by comparing spectra in the tropical convectively active and dry zones of the Pacific Ocean. Spectra of vorticity and divergence are calculated, along with spectral vorticity-to-divergence ratios. Their spatial and temporal variations are discussed. It is hypothesized that when convection is enhanced in the tropics, the spectral analysis captures the mesoscale/synoptic structures in which convection is embedded and that the spectra exhibit some of the characteristics of their midlatitude counterparts (i.e., steeper and more energetic).

Global pressure fields from scatterometer winds

A method is presented for computing global surface pressure fields from satellite scatterometer winds. Pressure gradients are estimated using a two-layer similarity planetary boundary layer model in the midlatitudes and a mixed-layer model in the Tropics. A global pressure field is then fit to the pressure gradients by least squares optimization. A series of surface pressure fields calculated from SeaWinds-on-QuikSCAT (Quick Scatterometer) measurements are compared with numerical weather analyses and buoy measurements. Surface pressure observations in the tropical oceans are scarce and come largely from ships of opportunity. At present no buoy in the Atlantic Ocean and only 10 buoys in the Pacific Ocean have pressure sensors. The method presented here suggests that 0.58-resolution maps of sea surface pressure can be readily retrieved from available satellite remote sensing data every 12 h in near‐real time. It is shown that these fields are at least of comparable quality to the ECMWF analyses.

A Gradient Wind Correction for Surface Pressure Fields Retrieved from Scatterometer Winds

Given a field of geostrophic winds and at least one pressure observation, a pressure field can be computed. If the winds are in reality gradient winds, then a correction must be applied to calculate the actual geostrophic winds. Here a method is proposed for including a gradient wind correction in the retrieval of geostrophic winds from Quick Scatterometer (QuikSCAT) surface measurements with a planetary boundary layer model. This correction translates into a better estimate of the corresponding surface pressure fields. The scheme is assessed by comparing these pressure fields to buoy measurements in the Gulf of Alaska and to radiosonde measurements in Hurricane Floyd. The gradient wind correction has a curvature component and a time-dependent component. Their relative magnitude is evaluated.

An Evaluation of Scatterometer-Derived Oceanic Surface Pressure Fields

Abstract Oceanic surface pressure fields are derived from the NASA Quick Scatterometer (QuikSCAT) surface wind vector measurements using a two-layer similarity planetary boundary layer model in the midlatitudes and a mixed layer planetary boundary layer model in the tropics. These swath-based surface pressure fields are evaluated using the following three methods: 1) a comparison of bulk pressure gradients with buoy pressure measurements in the North Pacific and North Atlantic Oceans, 2) a least squares difference comparison with the European Centre for Medium-Range Weather Forecasts (ECMWF) surface pressure analyses, and 3) a parallel spectral analysis of the QuikSCAT and ECMWF surface pressure fields. The correlation coefficient squared between scatterometer-derived pressure fields and buoys is found to be R2 = 0.936. The average root-mean-square difference between the scatterometer-derived and the ECMWF pressure fields ranges from 1 to 3 hPa, depending on the latitude and season, and decreases after th...

A scheme for improving scatterometer surface wind fields

A method is presented for improving QuikSCAT surface wind fields. The University of Washington Planetary Boundary Layer model is used to retrieve a surface pressure field from any swath of QuikSCAT surface wind vectors. An alternate set of surface wind vectors is computed from the newly calculated pressure field. The latter can be smoothed and the process can be iterated. New surface wind vectors can be calculated where ambiguity removal fails and where measurements are missing. The present methodology preserves boundary layer dynamics and is an improvement over a statistical filter.

Diagnosis of Frontal Instabilities over the Southern Ocean

The development of three fronts over the Southern Ocean is described using SeaWinds-on-QuikSCAT scatterometer surface winds and an attribution technique to partition the wind field in three components: nondivergent and irrotational components at the scale of the front, and the remaining harmonic component (or environmental flow) induced by the synoptic-scale flow. The front and the environment in which the front is embedded are analyzed separately. A frontal wave is shown to develop out of the first front when the large-scale alongfront stretching decreases, the environmental flow becomes frontolytic, and a connection with the upper levels is established. In the second case, the stretching remains relatively strong and no frontal wave develops. The third front exhibits a developing wave but is not in a favorable configuration with the upper levels; the frontal wave does not deepen significantly.

A method for including mesoscale and synoptic-scale information in scatterometer wind retrievals

[1] A method for improving scatterometer wind retrievals based on the mesoscale and synoptic‐scale structure of the flow field is presented and evaluated. The large‐scale structure of the flow is inferred from the sea‐level pressure (SLP) field derived from the scatterometer winds using a planetary boundary layer model. The wind vectors derived from this SLP field can be used to either (1) inform the ambiguity selection, (2) correct the direction of the scatterometer wind vectors, in all cases or above a certain threshold, or (3) replace the scatterometer winds. The methodology is demonstrated with QuikSCAT (QS) scatterometer wind vectors. The new wind vector set is evaluated statistically by comparison with buoy measurements, with numerical weather prediction model analyses, and by spectral analysis. It is found that the new wind vectors are particularly valuable at nadir and in rain‐contaminated areas, and that their spectral behavior is closer to a power law than are the uncorrected QS winds.

The Contribution of Extratropical Waves to the MJO Wind Field

AbstractA method for capturing the different dynamical components of the Madden–Julian oscillation (MJO) is presented. The tropical wind field is partitioned into three components using free-space Green’s functions: 1) a nondivergent component, 2) an irrotational component, and 3) a background or environmental flow that is interpreted as the influence on the tropical flow due to vorticity and divergence elements outside of the tropical region. The analyses performed in this study show that this background flow is partly determined by a train of extratropical waves. Space–time power spectra for each flow component are calculated. The strongest signal in the nondivergent wind spectrum corresponds to equatorial Rossby, mixed Rossby–gravity, and easterly waves. The strongest signal in the irrotational winds corresponds to Kelvin and inertia–gravity modes. The strongest signal in the power spectrum of the background flow corresponds to the wave band of extratropical Rossby waves. Furthermore, a coherence analy...