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At least 811 records · Page 45

The Venus Atmospheric Sample Return (VATMOS-SR) Mission Concept

VATMOS-SR (Venus ATMOSpheric - Sample Return) is a small space- craft mission concept that would return several gas samples from the upper atmosphere of Venus (< 110 km) to Earth for scientific analysis. This could be the first sample return mission for an extraterrestrial atmosphere and potentially the first sample return from an Earth-sized planet. The VATMOS-SR mission concept consists of a SmallSat atmospheric sampling probe (45 deg. sphere/cone geometry, <1 m diameter) that is designed to skim through the Venus upper atmosphere and ac- quire gas samples below the homopause altitude (around ~110 km altitude), where the different atmospheric gases are mixed. The velocity of the spacecraft where sampling would occur is expected to be between ~10.5 km/s and ~13.1 km/s, depending on the trajectory chosen (e.g. trajectory shown in Fig. 1).

direct simulation Monte Carlo↗

The Venus Atmospheric Sample Return (VATMOS-SR) Mission Concept

VATMOS-SR (Venus ATMOSpheric - Sample Return) is a small space- craft mission concept that would return several gas samples from the upper atmosphere of Venus (< 110 km) to Earth for scientific analysis. This could be the first sample return mission for an extraterrestrial atmosphere and potentially the first sample return from an Earth-sized planet. The VATMOS-SR mission concept consists of a SmallSat atmospheric sampling probe (45 deg. sphere/cone geometry, <1 m diameter) that is designed to skim through the Venus upper atmosphere and ac- quire gas samples below the homopause altitude (around ~110 km altitude), where the different atmospheric gases are mixed. The velocity of the spacecraft where sampling would occur is expected to be between ~10.5 km/s and ~13.1 km/s, depending on the trajectory chosen.

direct simulation Monte Carlo↗

Cloud Condensation Nuclei in the Early Martian Atmosphere

Explanations for how early Mars supported warmer and wetter conditions 3.5 to 4 billion years ago have long been debated. A water cloud greenhouse has been proposed as a mechanism of warming early Mars, but modeling studies of these environments produce mixed results. Studies show that both H 2 O and CO 2 clouds are capable of influencing atmospheric and surface temperatures, but the amount of warming induced is very sensitive to the cloud physics assumptions made. Producing a strong water cloud greenhouse effect is dependent on forming clouds as high in the atmosphere as possible to maximize warming. However, the majority of studies of H 2 O and CO 2 clouds on early Mars assume that a constant number of seed nuclei are available at all altitudes for clouds to condense onto. Here we test the validity of this assumption in massive CO 2 atmospheres. Explaining how dust is lofted into the middle atmosphere to serve as seed nuclei for cloud formation is a challenge even for present day Mars. This problem may change in an early Mars environment where having a more massive atmosphere could result in differences in the general circulation, vertical transport, and settling time scales of dust. Here, we begin a first-ever study of the early Mars dust cycle and how it might couple to the water cycle. We present early Mars simulations in which dust is injected at the surface and can be transported throughout the atmosphere. We explore the resulting vertical and horizontal distributions of dust particles and their sizes with an emphasis on the maximum height of the dust. We aim to investigate what the distribution of cloud condensation nuclei may have been on early Mars and how this might impact cloud formation.

Kathryn Steakley↗

Neural Network Atmospheric Correction of Remote Sensing Imagery Over Water Using a Synthetic Dataset

Remote sensing atmospheric correction methods have primarily focused on imagery over land. However, accurate correction over water is important for monitoring and research of aquatic environments. More research in this area is ongoing, though one of the biggest challenges is enough quality data to develop and validate correction methods. This is especially true for neural network (NN) -based models which have shown promise in this area given enough quality data. To address this deficiency of data, we are leveraging a synthetic dataset produced by a model called SWIPE that uses radiative transfer modeling to simulate the atmospheric effects on water-leaving (WL) reflectance to estimate top-of-atmosphere (TOA) reflectance. This allows us to produce almost unlimited pairs of WL reflectance and corresponding TOA reflectance for model training across a variety of atmospheric conditions. We use two approaches for our atmospheric correction model. One uses a conditional variational autoencoder (VAE) to estimate a single WL reflectance value from a single TOA reflectance value. The second is based on a UNET architecture and estimates an array of WL reflectance values from an array of TOA reflectance values. The goal of the second method is to capture atmospheric effects that occur spatially between values within the array as compared to the first method.

deep learning↗

Accurate Assessment of Land-Atmosphere Coupling in Climate Models Requires High Frequency Data Output

Land-atmosphere (L-A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centred climate anomalies. Local L-A coupling (LoCo) metrics capture relevant L-A processes, highlighting the impact of soil and vegetation states on surface flux partitioning, and the impact of surface fluxes on boundary layer (BL) growth, development, and entrainment of air above the BL. A primary goal of the Climate Process Team on Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L-A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land-atmosphere interactions span time scales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability of behavioural regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics. Here we outline a reasonable data request that would allow for adequate characterization of sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyse, and better understand L-A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behaviour. Higher-frequency model output will (i) allow for more direct comparison with observational field campaigns on process-relevant time scales, (ii) enable demonstration of inter-model spread in L-A coupling processes, and (iii) aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.

Kirsten L. Findell↗

Use of Forecast Atmosphere for Earth Entry, Descent, and Landing Modeling

Flight mechanics simulations are used to characterize the performance of Earth entry, descent, and landing vehicles. Atmospheric prediction models are often a key component of these simulations. Global atmospheric models are used for both engineering design due to their ability to define atmospheric properties over a large swath of locations and times as well as used for the availability of atmospheric uncertainties in the models that can be used in statistical performance analysis. However for day-of-flight operations, the use of forecast atmospheres based on more current measurements are beneficial to the accuracy of the performance prediction, including landing locations. Reanalysis of these forecasts can also be used for post-flight analysis, including trajectory reconstruction. This paper describes how forecast atmospheres can be beneficial for Earth entry, descent, and landing analysis and ways these models can be implemented in simulations.

Soumyo Dutta↗

Atmospheric Transformation of Refrigerants: Current Research Developments and Knowledge Gaps

Refrigerants have evolved through the years to reduce their global warming potential while providing sufficient cooling in refrigeration systems. Replacements for hydrofluorocarbons (HFCs) and chlorofluorocarbons (CFCs) are the hydrofluoroolefins (HFOs), which contain reactive double bonds that decrease the atmospheric lifetime of fluorinated compounds. However, the transformation of unsaturated fluorinated compounds in the atmosphere could generate persistent pollutants, particularly trifluoroacetic acid (TFA) which is the simplest Perfluoroalkyl carboxylic acids (PFCAs). Understanding the transformation of refrigerants is critical in assessing their contribution to atmospheric levels of TFA and their impact on watersheds and human health. This article will present the reactivity of the refrigerants, atmospheric oxidation source, and sink processes of fluorinated refrigerants under daytime conditions, particularly the variability of TFA from refrigerants. Moreover, the discussion will suggest experimental procedures that can quantify the low concentration (~parts per trillion) of TFA generated from the transformation of HFOs. New state-of-the-art techniques such as chemical ionization mass spectrometers (HR-CIMS) will be assessed in providing high temporal resolution (minutes to hourly) to fully capture the atmospheric sources and variability of TFA. Likewise, local, regional, and global concentrations of TFA accounted from the oxidation of refrigerants will be examined. This will include data from both experimental procedures and simulation models. Participation of TFA in critical atmospheric processes such as new particle formation will also be included in this study. Lastly, overall knowledge gaps related to the oxidation products and their dispersion in the environment will be summarized to guide future research needs.

Salvador, Christian↗

End-of-Century Changes in Orographic Precipitation with the Intermediate Complexity Atmospheric Research Model over the Western United States

Abstract Downscaled precipitation projections were created using the Intermediate Complexity Atmospheric Research (ICAR) model over the western United States to increase the physical realism in orographic precipitation changes. End-of-century simulations from eight models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) were downscaled with ICAR and compared to the widely utilized statistically downscaled dataset, localized constructed analogs (LOCAs), to understand where and why projections of cool-season (September–May) precipitation differed. ICAR and LOCA precipitation projections were similar, but their sign differed in hydrologically relevant regions likely due to ICAR’s simulation of microphysics and mesoscale dynamics with high-resolution topography (6 km). In the Pacific Northwest, cool-season precipitation projections from ICAR showed an increase on the windward side of the Cascades and no significant change within the lee. This difference between the windward and leeward side was attributed to reduced zonal wind speeds, allowing more time for microphysical processes within ICAR. This contrast is enhanced by rain’s faster fall speed compared to snow, limiting transport into the lee. Meanwhile, LOCA projected an increase in precipitation across the Cascades. In the Upper Colorado River basin, LOCA projected an increase in precipitation in high elevation regions (>3000 m), but ICAR projected no significant change or a decrease in precipitation. High elevation differences were most evident in the spring and fall and were also attributed to a snow-to-rain transition and dynamical processes that impacted orographic enhancement within ICAR. Idealized, controlled studies are needed to better isolate individual processes, but these results underscore the importance of including microphysics and mesoscale dynamics within regional-scale precipitation projections. Significance Statement A set of global climate model simulations was downscaled using an atmospheric model that contains key physical equations, referred to as Intermediate Complexity Atmospheric Research (ICAR). ICAR was used to examine projected changes in end-of-century cool-season precipitation over mountains in the western United States. Precipitation projections from ICAR were similar to projections that used statistical relationships to downscale climate projections. However, projections differed between ICAR and statistically downscaled datasets in whether they increased, decreased, or stayed the same in specific, hydrologically relevant regions such as the eastern Cascades and high elevation areas of the Upper Colorado River basin. These differences were attributed to the simulation of physical processes in ICAR. The results highlight the importance of kilometer-scale atmospheric processes in regional climate projections.

Currier, William Ryan [NOAA/Physical Sciences Labo↗

2025 Atmospheric Radiation Measurement (ARM) Annual Report

ARM is a multi-laboratory, U.S. Department of Energy (DOE) Office of Science user facility and a key contributor to atmospheric research efforts. For more than 30 years, ARM has supported the DOE and Office of Science missions by providing atmospheric observations to enable scientific discovery, transform our understanding of the atmosphere, and evaluate and improve the accuracy of atmospheric models. ARM’s cutting-edge capabilities for scientists include continuously operating ground-based observatories, aerial observation platforms, and high performance computing.

54 ENVIRONMENTAL SCIENCES↗

Venus Global Reference Atmospheric Model (Venus-GRAM): User Guide

This Technical Memorandum (TM) presents the Venus Global Reference Atmospheric Model (Venus-GRAM) and the updated features of the GRAMs. Venus-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Venus. This TM summarizes the atmospheric data model in Venus-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Venus-GRAM input and output files and how to interpret Venus-GRAM results are also provided.

atmospheric models↗

Mars Global Reference Atmospheric Model (Mars-GRAM): User Guide

This Technical Memorandum (TM) presents the Mars Global Reference Atmospheric Model (Mars-GRAM) and the updated features of the GRAMs. Mars-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Mars. This TM summarizes the atmospheric data model in Mars-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Mars-GRAM input and output files and how to interpret Mars-GRAM results are also provided.

atmospheric models↗

The TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI). Part II: Moist Cases - The Two Waterworlds

To identify promising exoplanets for atmospheric characterization and to make the best use of observational data, a thorough understanding of their atmospheres is needed. 3D general circulation models (GCMs) are one of the most comprehensive tools available for this task and will be used to interpret observations of temperate rocky exoplanets. Due to parameterization choices made in GCMs, they can produce different results, even for the same planet. Employing four widely-used exoplanetary GCMs - ExoCAM, LMD-G, ROCKE-3D and the UM - we continue the TRAPPIST-1 Habitable Atmosphere Intercomparison by modeling aquaplanet climates of TRAPPIST-le with a moist atmosphere dominated by either nitrogen or carbon dioxide. Although the GCMs disagree on the details of the simulated regimes, they all predict a temperate climate with neither of the two cases pushed out of the habitable state. Nevertheless, the inter-model spread in the global mean surface temperature is non-negligible: 14 K and 24 K in the nitrogen and carbon dioxide dominated case, respectively. We find substantial inter-model differences in moist variables, with the smallest amount of clouds in LMDGeneric and the largest in ROCKE-3D. ExoCAM predicts the warmest climate for both cases and thus has the highest water vapor content and the largest amount and variability of cloud condensate. The UM tends to produce colder conditions, especially in the nitrogen-dominated case due to a strong negative cloud radiative effect on the day side of TRAPPIST-le. Our study highlights various biases of GCMs and emphasizes the importance of not relying solely on one model to understand exoplanet climates.

TRAPPIST↗

Mars Global Reference Atmospheric Model (Mars-GRAM) 2024: User Guide

This Technical Memorandum (TM) presents the Mars Global Reference Atmospheric Model (Mars-GRAM) 2024 and its updated features. Mars-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Mars. This TM summarizes the atmospheric data model in Mars-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Mars-GRAM input and output files and how to interpret Mars-GRAM results are also provided.

atmospheric density↗

Atmospheric and oceanic energy transport during North Atlantic freshening events: influences of moisture transport and hydrologic cycle feedbacks

Analogs of present-day rapid ice melt can be found in episodic discharges of icebergs that occurred during glacial periods called Heinrich events. This introduces excess meltwater into the North Atlantic and weakens the Atlantic thermohaline circulation (AMOC), triggering a hydrologic cycle–AMOC collapse feedback as the atmospheric energy transport compensates for reduced northward heat transport. Here we employ a novel series of 100-year North Atlantic “hosing” simulations to investigate atmospheric and oceanic energy transport response from freshwater forcing, focusing in particular on the role of atmospheric rivers (ARs) within atmospheric energy transport. Importantly, we use an “overwriting” methodology that allow us to attribute AMOC weakening to added North Atlantic meltwater and subsequent hydrologic cycle responses, respectively. In contrast to far-reaching response of transient eddies, our results show a substantial increase in moisture convergence from ARs that is geographically constrained to the North Atlantic midlatitudes. Such AR changes nevertheless comprise an important component of net precipitation changes over the Euro-Atlantic sector, with the amount being comparable to that from transient eddies over the subpolar Atlantic. Over the course of the century-long simulations, we demonstrate that hydrologic cycle responses to North Atlantic freshening and subsequent feedbacks, including those from ARs, account for approximately half of the simulated AMOC collapse. Furthermore, our work highlights the dynamics of atmospheric moisture transport response to North Atlantic freshening events and elucidates how intensifying moisture transport may accelerate AMOC collapse in the future.

Atmospheric Science↗

Investigating the relationship between simulation parameters and flow variables in simulating atmospheric gravity waves for wind energy applications

Wind farms, particularly offshore clusters, are becoming larger than ever before. Besides influencing the surface wind flow and the inflow for downstream wind farms, large wind farms can trigger atmospheric gravity waves in the inversion layer and the free atmosphere aloft. Wind-farm-induced gravity waves can cause adverse pressure gradients upstream of the wind farm, which contribute to the global blockage effect, and can induce favorable pressure gradients above and downstream of the wind farm that enhance wake recovery. Numerical modeling is a powerful means of studying these wind-farm-induced atmospheric gravity waves, but it comes with the challenge of handling spurious reflections of these waves from domain boundaries. Typically, approaches which employ radiation boundary conditions and forcing zones are used to avoid these reflections. However, the simulation setup of these approaches relies heavily on ad hoc processes. For instance, the widely used Rayleigh damping method requires ad hoc tuning to produce a setup that may only produce satisfactory results for a particular case. To provide more systematic guidance on setting up realistic simulations of atmospheric gravity waves, we conduct a large-eddy simulation (LES) study of flow over a 2D hill and through a wind farm canopy that explores the optimum domain size and damping layer setup depending on the fundamental parameters which determine the flow characteristics. In this work, we only consider linearly stratified conditions (i.e., no inversion layer), thereby focusing on internal gravity waves in the free atmosphere and their reflections from the domain boundaries. This type of flow is governed by a single Froude number, which dictates most of the internal wave properties, such as wavelength, amplitude, and direction. This, in turn, will dictate the optimum domain size and Rayleigh damping layer setup. We find the effective horizontal and vertical wavelengths (the representative wavelengths of the entire wave spectrum) to be the appropriate length scales to size the domain and damping layer thickness, and the optimal Rayleigh damping coefficient scales with the Brunt–Väisälä frequency. Considering Froude numbers seen in wind farm applications, we propose recommendations to limit the reflections to less than 10 % of the total upward-propagating wave energy. Typically, damping is done at the top boundary, but given the non-periodic lateral boundary conditions of practical wind farm simulation domains, we find that damping the inflow–outflow boundaries is of equal importance to damping the top boundary. The Brunt–Väisälä frequency-normalized damping coefficient should be between 1 and 10. The damping layer thickness should be at least one effective vertical wavelength; damping layers exceeding 1.5 times the vertical wavelength are found to be unnecessary. The domain length and height should accommodate at least one effective horizontal and vertical wavelength, respectively. Moreover, Rayleigh damping does not damp the waves completely, and the non-damped energy might accumulate over the simulation time.

17 WIND ENERGY↗

Science Highlights and Lessons Learned from the Atmospheric Infrared Sounder (AIRS)

The Atmospheric Infrared Sounder (AIRS) and companion instrument, the Advanced Microwave Sounding Unit (AMSU) on the NASA Earth Observing System Aqua spacecraft are facility instruments designed to support measurements of atmospheric temperature, water vapor and a wide range of atmospheric constituents in support of weather forecasting and scientific research in climate and atmospheric chemistry. This paper is an update to the science highlights from a paper by the authors released last year and also looks back at the lessons learned and future needs of the scientific community. These lessons not only include requirements on the measurements, but scientific shortfalls as well. Results from the NASA Science Community Workshop in IR and MW Sounders relating to AIRS and AMSU requirements and concerns are covered and reflect much of what has been learned and what is needed for future atmospheric sounding from Low Earth Orbit.

Atmospheric Composition↗

Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits

Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

Atmospheric Turbulence Modeling↗

Isolated Rotor Forward Flight Testing at Martian Atmospheric Density Data Report

With the recent interest in Martian exploration using Unmanned Aerial Vehicles (UAVs), an experimental study was conducted to investigate rotor performance at Martian atmospheric conditions. Both simulation and testing of rotors is vital for evaluating rotor performance and behavior, especially for operations at Martian atmospheric densities and pressures. One critical test that has not been performed to date is helicopter forward flight testing at Martian atmospheric densities. To achieve this, a test was conducted in a tunnel facility that could be evacuated to the atmospheric pressure and density of Mars. A 40-inch-diameter rotor, roughly approximating the scale of the proposed Mars Helicopter (MH) design by the NASA Jet Propulsion Laboratory (JPL), was tested in forward flight at Mars’ atmospheric pressure at the NASA Ames Planetary Aeolian Laboratory (PAL). In this forward flight testing, the drive system of the Martian Surface Wind Tunnel (MARSWIT) was never turned on; all wind speeds read were generated either through the rotor spinning or from facility effects. The goal of this experiment was to collect rotor thrust, rotational speed, power, torque, and acoustics measurements. Subsequently, these results can be used for correlation with simulated cases using a mid-fidelity Computational Fluid Dynamics (CFD) simulation. As expected, rotor thrust and power are drastically reduced at air densities 100 times lower than at sea level on Earth. In addition, Reynolds number effects seem to play a vital role at reduced pressure that cannot be neglected in the simulation.

One Atmosphere↗