Ralph C. Foster

Why Rolls are Prevalent in the Hurricane Boundary Layer

Recent remote sensing observations show that the hurricane boundary layer flow, although energetic, is not a region of homogeneous turbulence. In fact, the observations convincingly demonstrate that a large fraction of the turbulent flow in the regions away from the deep convective rainbands is highly organized into intense horizontal roll vortices that are approximately aligned with the mean wind and span the depth of the boundary layer. These observations show that rolls strongly increase the flux of momentum between the underlying surface and the main body of the storm compared to an equivalent hurricane boundary layer flow without rolls. The linear and nonlinear dynamics of hurricane boundary layer roll formation are outlined and it is shown why rolls are, in fact, the expected basic hurricane boundary layer state. The model presented here explains the hurricane roll features currently documented in field programs and makes predictions that can be tested in future experiments. The primary effects of rolls on the boundary layer fluxes are inherently nonlocal and nongradient and hence cannot be captured by standard downgradient turbulence parameterizations used in hurricane simulations. However, the nonlinear theory is the proper starting point for developing boundary layer parameterizations that include roll modification of the turbulent fluxes.

The Structure of the Near-Neutral Atmospheric Surface Layer

Abstract Recent observational data (turbulence variables by sonic anemometers and three-dimensional flow pattern by Doppler lidar), obtained during the Cooperative Atmosphere Surface Exchange Study field campaign in October 1999 (CASES-99), show evidence of a layered structure of the near-neutral surface layer: (i) the eddy surface layer (ESL), which is the lower sublayer where blocking of impinging eddies is the dominating mechanism; and (ii) the shear surface layer (SSL), which is an intermediate sublayer, where shear affects the isotropy of turbulence. The origin of the eddies impinging from aloft (probably from the SSL) down to the ESL is preliminarily addressed in this study, since the Doppler lidar data show evidence of linearly organized eddies embedded in the surface layer (i.e., about 100-m vertical extent) and horizontally spaced by about 300 m. This is consistent with theories predicting that the primary mechanism of eddy motion in high Reynolds number wall layers is “top-down.” The layered str...

Structure and energetics of optimal Ekman layer perturbations

The optimal non-modal perturbations for the neutrally stratified boundary layer in a rotating frame of reference (Ekman layer) are found for a Reynolds number characteristic of the planetary boundary layer (PBL). Two classes of non-modal instabilities are found: evanescent perturbations, with lifetimes up to about one hour, and growing instabilities. The important difference between these types of perturbations is whether or not the optimal non-modal perturbation projects onto an unstable normal mode. The evanescent instabilities are of smaller scale and are oriented at larger angles to the surface isobars compared to either the growing perturbations or normal-mode instabilities. The optimal perturbations take the form of vortices at an acute angle to the geostrophic flow that rapidly transform into streaks with associated overturning motion. The energetics of the optimal perturbations are investigated in detail to clarify the instability mechanism throughout its evolution. Nonlinear stability analyses of the neutrally stratified Ekman layer have shown that the normal-mode instability will equilibrate with the mean flow to form boundary-layer-scale equilibrium roll eddies aligned closely with the geostrophic flow. However, numerical simulations do not generate these rolls in neutral stratification although they often realize small-scale near-surface streaks oriented at large angles to the geostrophic wind. The evanescent optimal perturbations bear a close resemblance to the simulated streaks. It is proposed that the non-model perturbation mechanism is associated with the streaks.

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.

Baroclinic modification of midlatitude marine surface wind vectors observed by the NASA scatterometer

Baroclinic modification of surface wind vectors determined from satellite microwave radar data over the Northern Hemisphere midlatitude (30°-60°N) oceans is presented. The analysis uses data from the NASA scatterometer (NSCAT) collocated with operational surface analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) at synoptic times. A total of 71,769 NSCAT wind vector observations from the Northwest Pacific and Northeast Atlantic Oceans were used in this study. A statistically significant baroclinic modification of the surface wind is detectable in the NSCAT winds that accounts for 5-35% of the variance in wind speed and 5-20% of the variance in wind direction depending primarily on the thermal wind strength. The amplitude of the baroclinic wind speed modification can be much larger than the effects of stratification in the surface layer. For the maximum thermal wind strength considered here (7 × 10 -3 s -1 ), the explained variances due to baroclinic effects were 59% for speed and 35% in direction. Because of data uncertainties these results probably underestimate the actual contribution of baroclinity to the surface wind variance. The NSCAT results are compared to ECMWF and to a theoretical model. The baroclinic modification of the NSCAT and ECMWF surface wind speed agree quite closely, but larger differences are seen in the cross-isobar angles. Reasons for these differences are discussed. These observations show that in addition to the primary surface wind data product, the scatterometer radar backscatter contains potentially useful information about the boundary layer temperature field.

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...

The Contribution of Organized Roll Vortices to the Surface Wind Vector in Baroclinic Conditions

Abstract Observations show that, for a given geostrophic forcing, baroclinity acting on the planetary boundary layer produces a nearly sinusoidal modification of the near-surface wind. Compared to barotropic conditions the speed is enhanced in the direction of the thermal wind and the cross-isobar angle increases (decreases) in cold (warm) advection. These modifications are asymmetric with respect to the thermal wind orientation. Two-layer similarity models that match a stratification-dependent surface layer to a stratification and baroclinity dependent Ekman layer simulate aspects of this asymmetric baroclinic modification if the cold advection conditions are more unstably stratified than the warm advection conditions. The authors demonstrate that roll vortices in a baroclinic planetary boundary layer produce an asymmetric surface wind modification in neutral stratification that can work in concert with the coupling between stratification and baroclinity to enhance the net effect of baroclinity on the su...

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...

Cross-Validation of Scatterometer Measurements via Sea-Level Pressure Retrieval

A combined analysis of ocean surface wind vector measurements by the European Advanced Scatterometer (ASCAT) and the National Aeronautics and Space Administration QuikSCAT (QS) scatterometer using buoy measurements, numerical weather prediction model analyses, and spectral decomposition reveals significant statistical differences between the two data sets. While QS wind speeds agree better with buoy wind speeds than ASCAT above 15 m s-1, ASCAT wind directions agree better with buoy directions overall than QS. In contrast, it is shown that sea-level pressure (SLP) fields derived from ASCAT and QS measurements compare better with each other than the winds in a statistical sense, even though ASCAT bulk pressure gradients (BPGs) are slightly weaker than buoy pressure gradients and have slightly lower spectral energy than QS. Weaker BPGs in ASCAT are consistent with the low bias in ASCAT wind speeds. Thus, it is proposed that scatterometer-derived SLP fields can be used as a filter to improve the wind directions. This improves the QS wind directions but has less effect on the more accurate ASCAT wind directions. The unfiltered ASCAT wind vector statistics compare well with the statistics of the direction-filtered QS winds. It is suggested that this methodology might provide a basis for minimizing the discrepancies between various satellite wind measurement data sets in view of producing a long-term record of satellite-derived SLP fields and ocean surface wind vectors.