# Multi-LEO Satellite Stereo Winds
## 1 Introduction  
Tracking of cloud features from space to derive Atmospheric Motion Vectors (AMVs), or winds, is a long-established and important measurement technique. Operational meteorological agencies around the globe routinely produce satellite wind products using multi-temporal sequences of imagery from a single Geostationary (GEO) satellite [1, 2, 3, 4] or imagery from multiple passes over the poles by Low-Earth Orbiting (LEO) satellites [5, 6]. One of the largest sources of errors in satellite wind measurements is the height assignment for a wind vector [7]. [PERSON] and [PERSON] [8] estimated that height assignment is the dominant factor in satellite wind uncertainty and contributes up to 70% of the total error. Thus, several studies focused on interpreting satellite AMVs as a layer-average variable [9, 10, 11]. The height of atmospheric clouds and aerosol features is also a key parameter to understand and characterize their impacts on atmospheric dynamical, chemical, and radiative processes. Accurate cloud top height is critical for determining cloud radiation effects and cloud interactions with precipitation and dynamics [12, 13, 14]. Aerosol plume heights, such as those from wildfires, dust, and volcano eruptions, play a pivotal role in aerosol transport, air quality prediction, and aviation safety [15, 16, 17]. Light Detection and Ranging (LiDAR) instruments provide accurate measurements of height, but over a narrow swath, or curtain, without full horizontal sampling of the surrounding thermodynamics and cloud/aerosol processes [18, 19]. While such samplingby the Aedus Doppler-wind LiDAR has been shown to have positive impacts on Numerical Weather Prediction (NWP) [20; 21; 22], its horizontal coverage and 80 km sampling would be less than ideal for many mesoscale process, Planetary Boundary Layer (PBL), and precipitation studies. The standard practice of assigning height using Infra-Red (IR) brightness temperature requires prior information or assumptions about the atmospheric thermal structure, which can become problematic in the cases where the atmospheric temperature has a weak or inverted vertical gradient [23; 24]. Recent work has focused on improving height assignments using stereo methods, which are not new [25] but are now capable of making accurate height measurements thanks to the improved Image Navigation and Registration (INR) of modern observing systems such as the Geostationary Operational Environmental Satellite R series (GOES-R) Advanced Baseline Imager (ABI) with geo-registration accuracy of a few tenths of a pixel [26; 27]. Stereo methods unlock information about the vertical dimension by interpreting apparent shifts in feature locations observed from multiple vantage points as a combination of motion and parallax. Our previous work has developed and validated the stereo method using a pair of Geostationary (GEO) satellites [28; 29] or a GEO and a Low-Earth Orbiting (LEO) satellite [30; 31]. Using a GEO satellite practically limits the application of stereo methods to \(\pm 60^{\circ}\) latitude and where there is overlapping coverage. This work seeks to develop the stereo method using multiple LEO satellites to allow for polar coverage. The Multi-angle Imaging SpectroRadiometer (MISR) is a pathfinder instrument on the NASA Terra satellite that is expressly designed for stereoscopy, including stereo cloud-motion wind applications [32; 33]. Although MISR has nine angular looks to determine the cloud height and the cross-track wind component, the along-track winds and height parallaxes are coupled and difficult to separate cleanly [34]. By pairing MISR with GEO imagery, as shown by [PERSON] et al., 2018 [30], a joint LEO-GEO wind retrieval can resolve the along-track wind and height ambiguity, achieving a much better accuracy in both AMV and height.