Center for Ocean-Atmospheric Prediction Studies

Abstract: A more versatile and robust technique is developed for determining area averaged surface vorticity based on vector winds from the SeaWinds scatterometer on the QuikSCAT satellite. This improved technique is discussed in detail and compared to two previous studies by Sharp et al. (2002) and Gierach et al. (2007) that focused on early development of tropical systems. The error characteristics of the technique are examined in detail. Specifically, three independent sources of error are explored: random observational error, truncation error and representation error. Observational errors are due to random errors in the wind observations, and determined as a worst-case estimate as a function of averaging spatial scale. The observational uncertainty in vorticity averaged for a roughly circular shape with a 100 km diameter, expressed as one standard deviation, is approximately 0.5 x 10 -5 s-1 for the methodology described herein. Truncation error is associated with the assumption of linear changes between wind vectors. For accurate results, it must be estimated on a case-by-case basis. An attempt is made to determine a lower bound of truncation errors through the use of composites of tropical disturbances. This lower bound is calculated as 10-7 s-1 for the composites, which is relatively small compared to the tropical disturbance detection threshold set at 5 x 10-5 s-1, used in an earlier study. However, in more realistic conditions, uncertainty related to truncation errors is much larger than observational uncertainty. The third type of error discussed is due to the size of the area being averaged. If the wind vectors associated with a vorticity maximum are inside the perimeter of this area (away from the edges), it will be missed. This type of error is analogous to over-smoothing. Tropical and sub-tropical low pressure systems from three months of QuikSCAT observations are used to examine this error. This error results in a bias of approximately 1.5 x 10-5 s-1 for area averaged vorticity calculated on a 100 km scale compared to vorticity calculated on a 25 km scale. The discussion of these errors will benefit future projects of this nature as well as future satellite missions.

Abstract: Twenty turbulent flux parameterizations are compared globally and regionally with a focus on the differences associated with episodic events. The regional focus is primarily upon the Gulf Stream and Drake Passage, as these two regions contain vastly different physical characteristics related to storm and frontal passages, varieties of sea-states, and atmospheric stability conditions. These turbulent flux parameterizations are comprised of six stress-related parameterizations [i.e., Large and Pond (1981), Large et al. (1994), Smith (1988), HEXOS (Smith et al. 1992, 1996), Taylor and Yelland (2001), and Bourassa (2006)] which are paired with a choice of three atmospheric stability parameterizations ['Neutral' assumption, Businger-Dyer (Businger 1966, Dyer 1967, Businger et al. 1971, and Dyer 1974) relations, and Beljaars-Holtslag (1991) with Benoit (1977)]. Two remaining turbulent flux algorithms are COARE version 3 (Fairall et al. 2003) and Kara et al. (2005), where Kara et al. is a polynomial curve fit approximation to COARE; these have their own separate stability considerations. The following data sets were used as a common input for parameterization: Coordinated Ocean Reference Experiment version 1.0, Reynolds daily SST, and NOAA WaveWatch III. The overlapping time period for these data sets is an eight year period (1997 through 2004). Four turbulent flux diagnostics (latent heat flux, sensible heat flux, stress, curl of the stress) are computed using the above parameterizations and analyzed by way of probability distribution functions (PDFs) and RMS analyses. The differences in modeled flux consistency are shown to vary by region and season. Modeled flux consistency is determined both qualitatively (using PDF diagrams) and quantitatively (using RMS differences), where the best consistencies are found during near-neutral atmospheric stratification. Drake Passage shows the least sensitivity (in terms of the change in the tails of PDFs) to seasonal change. Specific flux diagnostics show varying degrees of consistency between stability parameterizations. For example, the Gulf Stream's latent heat flux estimates are the most inconsistent (compared to any other flux diagnostic) during episodic and non-neutral conditions. In all stability conditions, stress and the curl of stress are the most consistent modeled flux diagnostics. Sea-state is also a very important source of modeled flux inconsistencies during episodic events for both regions.