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This paper presents a validation study of a specific integrated modeling methodology which is a candidate tool for modeling complex opto-mechanical systems such as spaceborne interferometers.
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A small thruster, that will herein be called the Hydrazine milliNewton Thruster (HmNT), has been designed and vacuum hot-fire tested, demonstrating a range of thrust and impulse far below the current state-of-the-art (SOA) hydrazine thruster. Steady-state thrust levels of 35–135 mN, and minimum impulse-bits of 25–120 μN-s were demonstrated over a typical operating range of inlet pressures. These capabilities provide new spacecraft and mission design options, including the following: Functional backup for Reaction Wheel Assemblies (RWAs), which can be used to prolong the useful life of RWAs; RWA replacement for certain missions to save mass, power, and cost; Precision delta-V that can be used for: proximity operations and docking maneuvers, formation flying, primary attitude control for SmallSats and CubeSats, and primary delta-V for CubeSats.
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Precipitation modifies atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially for low-intensity precipitation) within global scale models is crucial. In addition to improving our modeling of the hydrological cycle, this will reduce the associated uncertainty of global climate models in correctly forecasting future scenarios, and will enable the application of mitigation strategies. In this manuscript we present a proof of concept algorithm to automatically detect precipitation from lidar measurements obtained from the National Aeronautics and Space Administration Micropulse lidar network (MPLNET). The algorithm, once tested and validated against other remote sensing instruments, will be operationally implemented into the network to deliver a near real time (latency <1.5 h) rain masking variable that will be publicly available on MPLNET website as part of the new Version 3 data products. The methodology, based on an image processing technique, detects only light precipitation events (defined by intensity and duration) such as light rain, drizzle, and virga. During heavy rain events, the lidar signal is completely extinguished after a few meters in the precipitation or it is unusable because of water accumulated on the receiver optics. Results from the algorithm, in addition to filling a gap in light rain, drizzle, and virga detection by radars, are of particular interest for the scientific community as they help to fully characterize the aerosol cycle, from emission to deposition, as precipitation is a crucial meteorological phenomenon accelerating atmospheric aerosol removal through the scavenging effect. Algorithm results will also help the understanding of long term aerosol–cloud interactions, exploiting the multi-year database from several MPLNET permanent observational sites across the globe. The algorithm is also applicable to other lidar and/or ceilometer network infrastructures in the framework of the Global Aerosol Watch (GAW) aerosol lidar observation network (GALION).
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