Multi-LEO Satellite Stereo Winds

Abstract

The stereo-winds method follows trackable atmospheric cloud features from multiple viewing perspectives over multiple times, generally involving multiple satellite platforms. Multi-temporal observations provide information about the wind velocity and the observed parallax between viewing perspectives provides information about the height. The stereo-winds method requires no prior assumptions about the thermal profile of the atmosphere to assign a wind height, since the height of the tracked feature is directly determined from the viewing geometry. The method is well developed for pairs of Geostationary (GEO) satellites and a GEO paired with a Low Earth Orbiting (LEO) satellite. However, neither GEO-GEO nor GEO-LEO configurations provide coverage of the poles. In this paper, we develop the stereo-winds method for multi-LEO configurations, to extend coverage from pole to pole. The most promising multi-LEO constellation studied consists of Terra/MODIS and Sentinel-3/SLSTR. Stereo-wind products are validated using clear-sky terrain measurements, spaceborne LiDAR, and reanalysis winds for winter and summer over both poles. Applications of multi-LEO polar stereo winds range from polar atmospheric circulation to nighttime cloud identification. Low cloud detection during polar nighttime is extremely challenging for satellite remote sensing. The stereo-winds method can improve polar cloud observations in otherwise challenging conditions.

A GEO-GEO Stereo Observation of Diurnal Cloud Variations over the Eastern Pacific

“…Notably, the 3D-Wind algorithm has been developed for the pairings between H8/H9 and GOES-West (G17/G18) and GOES-West (G17/G18) and GOES-East (G16). More recently, the algorithm has been demonstrated for H8-GK2A pairing [22] and triple GEO (G16-G17-G18) stereo [23]. The future 3D-Wind developments include the pairing between GOES-East and the newly launched MTG-l1 (Meteosat Third Generation-Imaging 1).…”

“…Recent studies have demonstrated that stereo observations from satellite imagers on different geostationary (GEO) and low Earth orbit (LEO) platforms can produce 3D regional AMVs with an accurate height assignment [11][12][13][14][15]. Derived from tracking cloud and moisture features in motion, AMVs have proven to be very valuable for weather forecasts [16,17].…”

“…Using the pairing between Himawari-8 (H8) and GOES-17 (G17), Carr et al [14] applied the 3D-Wind algorithm to the historical eruption of Hunga Tonga-Hunga Ha'apai (HTHH) volcano and reported a record 55 km plume height and massive outflows in the stratosphere. Extending the 3D-Wind algorithm to multi-LEO pairing, Carr et al [15] demonstrated a science application of stereo observations for polar atmospheric circulation and nighttime cloud identification.…”

Contribution of Photogrammetry for Geometric Quality Assessment of Satellite Data for Global Climate Monitoring

“…On the other hand, a study by Carr et al [68] demonstrated discrepancies between the SLSTR nadir and oblique scenes when compared to the MODIS reference, suggesting a misalignment or lack of registration between the SLSTR images and MODIS while validating stereo-wind products. Moreover, nighttime ascending passes have presented challenges with increased geo-registration errors caused by the absence of GCPs in the reflective channel, although the study focused on the polar regions and further investigations may be needed on this topic in different geographic locations.…”