Evaluating the Detection of Mesoscale Outflow Boundaries Using Scatterometer Winds at Different Spatial Resolutions

Abstract

Outflow boundaries induced by cold-pools are a key characteristic of convective systems related to microphysical and kinematic processes during the mature stage of their lifecycle. Over the ocean, such kinematic processes are associated with low-level wind modulations that are captured by scatterometers. This study investigates the ability of the Advanced Scatterometer (ASCAT) wind retrievals to detect the outflow boundary associated with an oceanic mesoscale convective system (MCS). Leveraging a new technique to identify cold pools that is based on features that enclose elevated magnitude of the gradient of the wind, termed as `Gradient Feature’ (GF), wind retrievals at 50-, 25- and 7-km spatial resolution were utilized to explore how the characteristics of the outflow boundary vary with resolution. Ground-based radar retrievals were also implemented to assess and correct, when possible, the performance of the ASCAT retrievals. The magnitude of the gradient of the wind for the coarser resolution was an order of magnitude smaller (10−4 s−1) than the finer ones (10−3 s−1). An increase in the magnitude of the gradient wind field associated with the outflow boundary was captured by all resolutions and a respective feature was identified by the GF method. The location of the features relative to the distance from the front edge of the MCS decreased with resolution, indicating the importance of the high resolution ASCAT product to capture their extent, as well as additional smaller scale features. The effect of the background wind field on the selection of the final wind field during the ambiguity removal process for the high-resolution product is also discussed.

Correlating Extremes in Wind Divergence with Extremes in Rain over the Tropical Atlantic

“…The small-scale wind variability in and near MCSs can be resolved by C-band fixed fanbeam space-borne scatterometers, such as the advanced scatterometer (ASCAT) on-board the MetOp series of satellites [6][7][8][9][10][11][12]. The potential of ASCAT to detect the horizontal wind divergence associated with individual MCS downdrafts was investigated by Kilpatrick and Xie [9], who concluded that ASCAT could reliably detect mesoscale (100-300 km) downdrafts, but not convective-scale (5-20 km) gust fronts.…”

An Efficient Algorithm for Ocean-Front Evolution Trend Recognition

“…Several ocean-related variables have been identified for the ocean dynamic process, such as ocean currents, ocean tides, inner waves, ocean fronts, mesoscale vortices [1], etc. The oceanfront is an important branch of the ocean dynamic process [2][3][4]. Specifically, ocean fronts are located at the boundary between water masses with different properties [5,6], such as density, temperature, salinity, etc.…”

“…The method not only gets rid of the complex operations required for selecting the frames with ocean fronts from a video sequence but can also aggregate the information extracted from different classification methods. (2) We have created a new database for ocean-front trend recognition, to encourage other researchers to evaluate their methods for ocean-front trend classification and facilitate them in using data-driven methods, especially deep-learning-based methods, to deal with this challenging task.…”