Kallenborn, 2021). The CEO of the system's manufacturer STM maintains that the use of autonomy in the Kargu-2 is primarily restricted to navigation, and that "[u]nless an operator pushes the button, it is not possible for the drone to select a target and attack" (Tavsan, 2021). Despite this ambiguity, the incident has been widely portrayed as the first battlefield use of autonomous weapon systems (AWS), often colloquially called "killer robots" (see Mizokami, 2021;Stanley, 2021;Vincent, 2021).AWS are defined as "any weapons that select and apply force to targets without human intervention" (ICRC, 2022). 1 Militaries throughout the world have demonstrated 1 In this article we generally refer to autonomous weapon systems (AWS). AWS are not a specific category of weapon. Rather, we understand AWS as being any type of weapon system which utilizes machine autonomy to select and apply force without immediate human control or intervention. While some autonomous weapons integrate AI elements into their critical functions, they may not all necessarily be based on AI technologies. We will only employ the term lethal autonomous weapon systems (LAWS) when specifically citing the discussion at the UN CCW, as this is the official term which states parties have used as part of this debate. The term "killer robots" is also commonly
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Abstract. Spatial variability in snowpack properties negatively impacts our capacity to make direct measurements of snow water equivalent (SWE) using satellites. A comprehensive data set of snow microstructure (94 profiles at 36 sites) and snow layer thickness (9000 vertical profiles across 9 trenches) collected over two winters at Trail Valley Creek, NWT, Canada, were applied in synthetic radiative transfer experiments. This allowed robust assessment of the impact of first guess information of snow microstructural characteristics on the viability of SWE retrievals. Depth hoar layer thickness varied over the shortest horizontal distances, controlled by subnivean vegetation and topography, while variability of total snowpack thickness approximated that of wind slab layers. Mean horizontal correlation lengths were sub-metre for all layers. Depth hoar was consistently ~ 30 % of total depth, and with increasing total depth the proportion of wind slab increased at the expense of the decreasing surface snow layer. Distinct differences were evident between distributions of layer properties; a single median value represented density and SSA of each layer well. Spatial variability in microstructure of depth hoar layers dominated SWE retrieval errors. A depth hoar SSA estimate of around 7 % under the median value was needed to accurately retrieve SWE. In shallow snowpacks
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