Identifying dynamic stability coefficients plays a pivotal role in missions that involve atmospheric entry. Although several methods exist to derive these coefficients from experimental and numerical data, there are deficiencies that need to be addressed. In this study, a modular nonlinear parameter estimation (NPE) framework is proposed, which employs a neural network and Markov chain Monte Carlo (MCMC) algorithm to infer the dynamic stability coefficients and identify the uncertainties in the predictions. Given the sensitivity of Markov chains to initial chain location, the neural network is used to generate an initial sample for the first chain that will be used in the MCMC method, where the static and dynamic stability coefficients are estimated along with the uncertainties. The time histories of the moment and angle of attack obtained from computational fluid dynamics simulations with US3D are fed into the NPE framework to estimate the static and dynamic stability coefficients. The results show that the trajectories generated from the estimated coefficients agree with those obtained from the US3D simulations.
Overshooting storms are convective systems with updrafts that penetrate through the tropopause into the overlying stratosphere. These storms can rapidly transport a wide variety of chemical species and aerosols from the boundary layer and free troposphere directly to the stratosphere. The central plains of the U.S. and the Sierra Madre Occidental of Mexico are two of the global hotspots for overshooting convection. While the existence of these storms has been known for several decades, the amount of tropospheric air, including water vapor, trace gases, and aerosols, transported across the tropopause is poorly understood, as is their impact on the dynamics, chemistry, and radiative balance of the stratosphere. Climate models suggest that as Earth’s climate continues to warm, overshooting convection over the U.S. may increase, potentially causing changes to stratospheric composition and transport. To address these scientific questions, the NASA ER-2 high-altitude research aircraft flew 31 missions during the summers of 2021 and 2022 to make observations of the outflow from overshooting storms in the stratosphere over North America and the eastern Pacific Ocean as part of the Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) project. The ER-2 carried a payload of 12 instruments to measure meteorological parameters, water and its isotopologues, trace gases, and aerosol properties. Ozone, water vapor, and aerosol sondes were also launched on balloons during the field deployments. This paper describes the science goals of the DCOTSS project, the aircraft measurement strategy, the data produced by the project, and highlights of science results to date.
The 68th and 69th flights of NASA's Ingenuity Mars Helicopter marked the first dedicated system identification flights of a powered-lift aircraft on another planet. Frequency-domain techniques, similar to those utilized in the Earth-based system identification campaign for Ingenuity, were employed for the first time under free-flight conditions on Mars. Chirp signals were injected into the swashplate cyclic controls for both legs of the two out-and-back flights. Frequency responses were computed from the flight data, using both the direct method and the joint-input-output approach, for the identification of stability and control derivatives in forward flight conditions. The resulting identified state-space models were compared against existing flight dynamics simulation models, showing excellent correlation in the higher-frequency range. External disturbances were seen to introduce a bias in the identified lower-frequency responses, which was partially mitigated using the joint-input-output method. These findings will inform future modeling and flight testing efforts of Mars rotorcraft.
The latest generation of geostationary satellites provide Earth observations similar to widely used polar-orbiting sensors but at intervals as frequently as every 5–10 min, making them ideal for studying the diurnal dynamics of land–atmosphere interactions. The NASA Earth Exchange (NEX) group created the GeoNEX datasets by collating data from several geostationary platforms, including GOES-16/17/18, Himawari-8/9, and GK-2A, and placing them on a common grid to facilitate use by the Earth science community. Here, we document the GeoNEX Coincident Ground Observations (GeCGO) dataset for terrestrial ecosystem studies and provide examples for its use. Currently, GeCGO provides GOES-16 Advanced Baseline Imager (ABI) data over a 10 km × 10 km area surrounding 1586 network sites across the Americas. GeCGO makes it easy to compare the time series of geostationary data with the diurnal ground observations, including carbon/water fluxes and aerosol optical depth, and is extensible to other regions. We also develop GeoNEXTools to facilitate analyses that require both GeoNEX data and other NASA satellite data. The objectives of this paper are to introduce GeCGO and GeoNEXTools and demonstrate their applications. First, we describe the details of GeCGO and GeoNEXTools. Second, we explain how GeCGO can be integrated with other satellite data. Finally, we showcase comparisons between GeCGO and observations from three ground-based networks. GeCGO is available at https://doi.org/10.25966/y5pe-xp41 (Hashimoto et al., 2025).
A perspective on the luminous efficiency approach for determining the pre-atmospheric mass of a meteoroid from a measured light-curve is presented for meteors in the continuum flow regime. This perspective interprets the mass-loss rate evaluated from the luminous efficiency approach as a solution to the meteoroid surface energy balance, with the measured light-curve serving as a proxy for the radiative heating to the meteoroid surface. This differs from the standard interpretation that equates the radiation from the light-curve to a change in the kinetic energy of the meteor. Mathematically, the developed perspective is identical to the standard luminous efficiency approach, except that the deceleration term is shown to be extraneous. This perspective provides a clear relationship between the measured light-curve and the mass loss of a meteor, which is based on the observation that the radiative heating that drives the mass loss (through the surface energy balance) also provides the radiation for the light-curve. Furthermore, this perspective provides a simple mathematical framework for interpreting the impact of fragmentation on the luminous efficiency. This framework shows that the luminous efficiency of a fragmented meteoroid is a weighted sum of the luminous efficiency from the various fragments, which may each be assessed based on single-body simulations. To generate these single-body simulations, state-of-the-art flowfield and radiation simulations are performed for meteoroid diameters ranging from 0.02 to 100 m, velocities ranging from 12 to 24 km/s, and altitudes ranging from 20 to 50 km. The luminous efficiency values resulting from these simulations are distilled into a correlation and applied to trajectories resulting from the fragment cloud method. This allows the integral luminous efficiency to be computed using the developed luminous efficiency model and defined fragmentation framework. Both the silicon and visible passbands are considered. For the silicon passband, the computed integral luminous efficiency values track closely with the experimentally derived integral luminous efficiency model developed by Brown et al. (2002). This represents the first theoretical derivation of the integral luminous efficiency approach based on fully coupled radiation and ablation simulations with viscous effects, which also captures the impact of individual meteoroids that are combined using the developed fragmentation framework.
