High-Resolution Polar Low Winds Obtained from Unsupervised SAR Wind Retrieval

Abstract

High-resolution sea surface observations by spaceborne synthetic aperture radar (SAR) instruments are sorely neglected resources for meteorological applications in polar regions. Such radar observations provide information about wind speed and direction based on wind-induced roughness of the sea surface. The increasing coverage of SAR observations in polar regions calls for the development of SAR-specific applications that make use of the full information content of this valuable resource. Here we provide examples of the potential of SAR observations to provide details of the complex, mesoscale wind structure during polar low events, and examine the performance of two current wind retrieval methods. Furthermore, we suggest a new approach towards accurate wind vector retrieval of complex wind fields from SAR observations that does not require a priori wind direction input that the most common retrieval methods are dependent on. This approach has the potential to be particularly beneficial for numerical forecasting of weather systems with strong wind gradients, such as polar lows.

Polar low research: recent developments and promising courses of research

“…This year, the Cold Air Outbreak Experiment in the Sub-Arctic Region (CAESAR) 2 will provide observations of clouds that form during MCAOs, and has therefore the potential to capture PLs. Regarding satellite observations, Synthetic Aperture Radar (SAR) observations provide details of the structure of PLs thanks to their high resolution (Tollinger et al, 2021). Atmospheric fronts and cyclonic centers are key features in SAR images that allow the identification of polar mesoscale cyclones using a deep learning algorithm (Grahn and Bianchi, 2022).…”

“…Atmospheric fronts and cyclonic centers are key features in SAR images that allow the identification of polar mesoscale cyclones using a deep learning algorithm (Grahn and Bianchi, 2022). However, SAR observations have rarely been used to study PLs (e.g., Hallerstig et al, 2021), probably because the current wind retrieval techniques perform poorly with highly variable wind (Tollinger et al, 2021).…”

Exploring the Potential of Sentinel-1 Ocean Wind Field Product for Near-Surface Offshore Wind Assessment in the Norwegian Arctic

“…Furthermore, different polarization signals inhibit different limitations in the accurate representation of either low or high wind speeds: while co-polarized signals saturate with increasing wind speeds, cross-polarized signals cannot be distinguished from instrument noise at low wind speeds. Even a combined signal wind retrieval approach requires a priori information about the wind direction most commonly provided by NWP models [10]. Lastly, as no information about atmospheric stratification is available, wind retrieval at 10 m above the surface from SAR utilizes a geophysical model function assuming neutral stability.…”

Spatiotemporal Patterns of Polar Low Activity Over the Southern Ocean

“…For example, PLs are also described as meso‐scale cyclones with winds above 14 ms −1 , convective precipitation, and a lifetime of 18–36 hr (Farjami & Esmaeili, 2023; Fulton et al., 2017; Turner & Bracegirdle, 2007). Identifying and forecasting PLs is crucial for assessing regional natural hazards (Bresson et al., 2022), marine operations (Pakkan et al., 2013), coastal management practices (Tollinger et al., 2021), and climate change (Bresson et al., 2022). However, due to their small size and transient nature, it is challenging to model and forecast the spatiotemporal features of PLs (Ganeshan et al., 2022).…”