Earth aeolian wind streaks: Comparison to wind data from model and stations

Abstract

Wind streak is a collective term for a variety of aeolian features that display distinctive albedo surface patterns. Wind streaks have been used to map near‐surface winds and to estimate atmospheric circulation patterns on Mars and Venus. However, because wind streaks have been studied mostly on Mars and Venus, much of the knowledge regarding the mechanism and time frame of their formation and their relationship to the atmospheric circulation cannot be verified. This study aims to validate previous studies' results by a comparison of real and modeled wind data with wind streak orientations as measured from remote‐sensing images. Orientations of Earth wind streaks were statistically correlated to resultant drift direction (RDD) values calculated from reanalysis and wind data from 621 weather stations. The results showed good agreement between wind streak orientations and reanalysis RDD (r = 0.78). A moderate correlation was found between the wind streak orientations and the weather station data (r = 0.47); a similar trend was revealed on a regional scale when the analysis was performed by continent, with r ranging from 0.641 in North America to 0.922 in Antarctica. At sites where wind streak orientations did not correspond to the RDDs (i.e., a difference of 45°), seasonal and diurnal variations in the wind flow were found to be responsible for deviation from the global pattern. The study thus confirms that Earth wind streaks were formed by the present wind regime and they are indeed indicative of the long‐term prevailing wind direction on global and regional scales.

Identification of Dust Sources in a Saharan Dust Hot-Spot and Their Implementation in a Dust-Emission Model

“…The surface of Zones S and N shows stripes oriented in (north)eastern to western direction, so-called wind streaks. These are indicators that the surface is regularly affected by winds from a prevailing direction [68]. It is likely that these landforms are a result of the strong Harmattan winds that occur in the area during winter.…”

Spatiotemporal analysis of dune stabilization in the Kyzylkum and Karakum sandy deserts

“…Based on the studied aeolian profiles and active dune orientation, it can be assumed that the local sand transport patterns in the KKCAD deviate considerably from those predicted using weather-station data. Such performance is generally attributed to one of the three dominantly recognized factors: low spatial and/or temporal resolution of measurements, topographical dependencies, or secondary atmospheric circulations (Pye and Tsoar, 2009;Cohen-Zada et al, 2017). Therefore, the ERA5 reanalysis-assimilated dataset was identified as a more relevant wind data source for correlating dune morphologies and climatic drivers in the KKCAD.…”

“…Previous studies demonstrated that sand seas and aeolian formations can provide records of current and previous climatic shifts and conditions (Lancaster, 1995;Muhs and Holliday, 1995;Roskin et al, 2011b;Leighton et al, 2013) and may be a regional indication of prior and current wind directions and strength (Lancaster, 1995;Muhs and Holliday, 1995;Leighton et al, 2013;Lindhorst and Reimann, 2021;Robins et al, 2021). The regional sand flow results could be approximated using three methodologies (Pye and Tsoar, 2009): by considering the a) wind velocity data, with a sand transport rate equation, such as that proposed by Bagnold (1941); ; b) sandstorm duration and direction records (Dubief, 1952); and c) size and orientation of aeolian bedforms and sand streaks (Cohen-Zada et al, 2017). The drift potential is assumed to be an essential factor determining the formation and growth of dunes provided sufficient wind records are available (Zamani et al, 2020;Hu et al, 2021), and the first approach (use of wind chronicles) can yield the results for any period and particle size (Pye and Tsoar, 2009).…”

“…As the coastal region had a complex dune setting, some incompatibilities existed between the dune orientation and RDDs, referring to a better correlation between the superimposed formations and the obtained RDDs, or the underlying mega-dunes. Thus, the wind data acquired for the active Caspian coastal region were split into the Northern Hemisphere seasons, namely, winter (November-February) and summer (May-August), as well as the geomagnetic time hours of sampling of the reanalysis data (06:00 h and 18:00 h) (Cohen-Zada et al, 2017), for the same statistical period. As the segment of different dune types varied significantly, we used Google Earth Pro, whose DEM model is based on the Shuttle Radar Topography Mission (SRTM) data (30 MP resolution), along with other sources (Table 1).…”