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At least 595 records · Page 33

Simulating coupled surface–subsurface flows with ParFlow v3.5.0: capabilities, applications, and ongoing development of an open-source, massively parallel, integrated hydrologic model

Surface flow and subsurface flow constitute a naturally linked hydrologic continuum that has not traditionally been simulated in an integrated fashion. Recognizing the interactions between these systems has encouraged the development of integrated hydrologic models (IHMs) capable of treating surface and subsurface systems as a single integrated resource. IHMs are dynamically evolving with improvements in technology, and the extent of their current capabilities are often only known to the developers and not general users. This article provides an overview of the core functionality, capability, applications, and ongoing development of one open-source IHM, ParFlow. ParFlow is a parallel, integrated, hydrologic model that simulates surface and subsurface flows. ParFlow solves the Richards equation for three-dimensional variably saturated groundwater flow and the two-dimensional kinematic wave approximation of the shallow water equations for overland flow. The model employs a conservative centered finite-difference scheme and a conservative finite-volume method for subsurface flow and transport, respectively. ParFlow uses multigrid-preconditioned Krylov and Newton–Krylov methods to solve the linear and nonlinear systems within each time step of the flow simulations. The code has demonstrated very efficient parallel solution capabilities. ParFlow has been coupled to geochemical reaction, land surface (e.g., the Common Land Model), and atmospheric models to study the interactions among the subsurface, land surface, and atmosphere systems across different spatial scales. This overview focuses on the current capabilities of the code, the core simulation engine, and the primary couplings of the subsurface model to other codes, taking a high-level perspective.

58 GEOSCIENCES↗

Mars Atmosphere Resource Verification INsitu (MARVIN) - In Situ Resource Demonstration for the Mars 2020 Mission

The making of oxygen from resources in the Martian atmosphere, known as In Situ Resource Utilization (ISRU), has the potential to provide substantial benefits for future robotic and human exploration. In particular, the ability to produce oxygen on Mars for use in propulsion, life support, and power systems can provide significant mission benefits such as a reducing launch mass, lander size, and mission and crew risk. To advance ISRU for possible incorporation into future human missions to Mars, NASA proposed including an ISRU instrument on the Mars 2020 rover mission, through an announcement of opportunity (AO). The purpose of the the Mars Atmosphere Resource Verification INsitu or (MARVIN) instrument is to provide the first demonstration on Mars of oxygen production from acquired and stored Martian atmospheric carbon dioxide, as well as take measurements of atmospheric pressure and temperature, and of suspended dust particle sizes and amounts entrained in collected atmosphere gases at different times of the Mars day and year. The hardware performance and environmental data obtained will be critical for future ISRU systems that will reduce the mass of propellants and other consumables launched from Earth for robotic and human exploration, for better understanding of Mars dust and mitigation techniques to improve crew safety, and to help further define Mars global circulation models and better understand the regional atmospheric dynamics on Mars. The technologies selected for MARVIN are also scalable for future robotic sample return and human missions to Mars using ISRU.

Sanders, Gerald B.↗

Seasonal southern hemisphere multi-variable reflection of the southern annular mode in atmosphere and ocean reanalyses

Variations of southern hemisphere (SH) climate variables are often linked to the southern annular mode (SAM) variability. We examined such linkage by seasons using state-of-the-art atmosphere and ocean/sea-ice reanalyses. The associated SAM related anomaly (SRA) fields of the climate variables, denoting anomalies corresponding to the same variation in SAM, are overall consistent across the reanalyses. Among the atmospheric products, 20CRV2 differs from ERA-interim and CFSR in the sea-level pressure SRAs over the Amundsen Sea, resulting in less warming over the Antarctic Peninsula. Among the ocean reanalyses, ORAP5 and C-GLORS exhibit the largest consistency. The major difference between them and the lower-resolution CFSR and SODA reanalyses is deeper penetration of anomalous meridional currents. Compared to the other ocean reanalyses, CFSR exhibits stronger and spatially more coherent surface-current SRAs, resulting in greater SRAs of sea-ice motion and ice thickness along the ice edges. The SRAs of sensible and total surface heat fluxes are reduced in CFSR due to ocean–atmosphere coupling. Significant sea-ice concentration SRAs are present on the west side of peninsulas along the east Antarctica coast in spring and winter, most notably in ORAP5 and C-GLORS, implying changes in new-ice production and shelf-water formation. Most atmosphere and ocean variables manifest an annular SRA pattern in summer and a non-annular pattern in the other seasons, with a wavenumber-3 structure strongest in autumn and weakest in summer. The wavenumber-3 structure should be related to the zonal wave three pattern of the SH circulation, the relation of which to SAM needs further exploration.

Meteorology & Atmospheric Sciences↗

Theory and observations: Model simulations of the period 1955-1985

The main objective of the theoretical studies presented here is to apply models of stratospheric chemistry and transport in order to understand the processes that control stratospheric ozone and that are responsible for the observed variations. The model calculations are intended to simulate the observed behavior of atmospheric ozone over the past three decades (1955-1985), for which there exists a substantial record of both ground-based and, more recently, satellite measurements. Ozone concentrations in the atmosphere vary on different time scales and for several different causes. The models described here were designed to simulate the effect on ozone of changes in the concentration of such trace gases as CFC, CH4, N2O, and CO2. Changes from year to year in ultraviolet radiation associated with the solar cycle are also included in the models. A third source of variability explicitly considered is the sporadic introduction of large amounts of NO sub x into the stratosphere during atmospheric nuclear tests.

Isaksen, Ivar S. A.↗

Simulations of X-59 Sonic Thumps and Traditional Sonic Booms Propagated Around the World for Three Atmospheric Models

Propagation simulations of sonic booms from supersonic aircraft through atmospheric data over time at fixed locations provides the opportunity to assess noise exposure statistics for different climate regions. Knowledge of climate-based differences in sonic boom noise exposure statistics is important to ensure that future civil supersonic aircraft noise certification standards are globally applicable and effective. In this presentation, simulated sonic booms from the NASA X-59 Quesst quiet supersonic aircraft and conventional supersonic aircraft were propagated through atmospheric data at 100 locations across the world using PCBoom. Noise exposure statistics are compared for propagation results from three different atmospheric databases (NOAA Global Forecast System, NOAA Climate Forecast System Version 2, and the ECMWF Reanalysis Version 5). These atmospheric models were chosen due to their global coverage, popularity, and database availability. Preliminary statistical models are fit to assess the impact of several factors including flight direction, season, ground elevation, and climate on noise exposure size and loudness. Areas with prevalence of higher noise due to their climate are identified, which could help inform future supersonic aircraft noise standards.

X-59↗

Active Region Magnetic Structure Observed in the Photosphere and Chromosphere

The magnetic flux above sunspots and plage in NOAA (National Oceanic and Atmospheric Administration) Active Region 8299 has been measured in the photosphere and the chromosphere. We investigate the vertical magnetic structure above the umbrae, penumbrae and plage regions using quantitative statistical comparisons of the photospheric and chromospheric vector magnetic flux data. The results include: (1) a decrease in flux with height, (2) the direct detection of the superpenumbral canopy in the chromosphere, (3) values for dB/dz which are consistent with earlier investigations when derived from a straight difference between the two datasets but quite low when derived from the delta x B = 0 condition, (4) a monolithic structure in the umbra which extends well into the upper chromosphere with a very complex and varied structure in the penumbra and plage, as evidenced by (5) a uniform magnetic scale height in the umbrae with an abrupt jump to widely varying scale heights in the penumbral and plage regions. Further, we find (6) evidence for a very large (delta z approximately equals 3Mm) height difference between the atmospheric layers sampled in the two magnetograms, almost a factor of three larger than that implied by atmospheric models. We additionally test the apropriateness of using photospheric magnetic flux as a boundary for field-line extrapolations, and find a better agreement with observed coronal structure when the chromospheric flux is used as a boundary.

Leka, K. D.↗

The birth of a field through a marriage of scales: urban meteorological modeling meets regional climate modeling

Urban meteorological modeling and regional climate modeling developed largely independently, with each discipline addressing different aspects of atmospheric processes across space and time. In this review, I show that urban climate modeling did not arise as a simple scaling extension of urban meteorological modeling or an add-on to regional climate modeling, but instead emerged through the selective inheritance of complementary strengths from its parents after both disciplines reached sufficient methodological maturity. By tracing the parallel evolution of these disciplines, I demonstrate that urban climate modeling inherited the physically explicit treatment of the built environment developed within urban meteorological modeling, and the hierarchical scale translation and climatological framing that matured within regional climate modeling, allowing urban effects to influence climate-relevant outcomes. Building on this synthesis, I propose an objective, and methodologically-grounded definition of urban climate modeling that distinguishes it from urban meteorological modeling. This distinction is increasingly important as urban climate data informs decisions with long-lived societal consequences, and as ambiguity in terminology risks conflating fundamentally different modeling frameworks with distinct physical meaning and decision relevance. In addition to a clarifying definition, this review outlines a research framework for advancing urban climate modeling through scale-aware coupling strategies that preserve physically consistent urban-atmosphere interactions.

regional climate↗

Variability of Neptune

Earth based observers of Neptune found that the planet varies in brightness at various wavelengths in ways that suggest that changes occur in the planet's atmosphere on several different time-scales. Global inhomogeneities in high altitude haze distribution that are stable for several days permit measurements of the planet's rotation period (about 18 hours), but this stability sometimes breaks down, obscuring the diurnal lightcurve. In addition, there is an apparent long term variability of the brightness of Neptune in anticorrelation with the cycle of solar activity. This slow variability of low amplitude may be punctuated by outbursts of high altitude condensation of particles in the atmosphere, whose decay time is several months.

Dale P Cruikshank↗

Variability of Neptune

Earth based observers of Neptune found that the planet varies in brightness at various wavelengths in ways that suggest that changes occur in the planet's atmosphere on several different time-scales. Global inhomogeneities in high altitude haze distribution that are stable for several days permit measurements of the planet's rotation period (about 18 hours), but this stability sometimes breaks down, obscuring the diurnal lightcurve. In addition, there is an apparent long term variability of the brightness of Neptune in anticorrelation with the cycle of solar activity. This slow variability of low amplitude may be punctuated by outbursts of high altitude condensation of particles in the atmosphere, whose decay time is several months.

Cruikshank, D. P.↗

Study of atmospheric diffusion using LANDSAT

The parameters of diffusion patterns of atmospheric pollutants under different conditions were investigated for use in the Gaussian model for calculation of pollution concentration. Value for the divergence pattern of concentration distribution along the Y axis were determined using LANDSAT images. Multispectral scanner images of a point source plume having known characteristics, wind and temperature data, and cloud cover and solar elevation data provided by LANDSAT, were analyzed using the 1-100 system for image analysis. These measured values are compared with pollution transport as predicted by the Pasquill-Gifford, Juelich, and Hoegstroem atmospheric models.

Torsani, J. A.↗

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex process-based crop models is a rather new idea. We demonstrate herewith that statistical methods can play an important role in analyzing simulated yield data sets obtained from the ensembles of process-based crop models. Formal statistical analysis is helpful to estimate the effects of different climatic variables on yield, and to describe the between-model variability of these effects.

climate↗

Propagation of sound through the Earth's atmosphere

The data collected at a pressure of one atmosphere for the different temperatures and relative humidities of the air-water vapor mixtures is summarized. The dew point hygrometer used in these measurements did not give reliable results for dew points much above the ambient room temperature. For this reason measurements were not attempted at the higher temperatures and humidities. Viscous wall losses in the resonant tube at 0 C so dominate the molecular relaxation of nitrogen, in the air-water vapor mixture, that reliable data could not be obtained using the free decay method in a resonant tube at one atmosphere. In an effort to obtain viable data at these temperatures, measurements were performed at a pressure of 10 atmospheres. Since the molecular relaxation peak is proportional to the pressure and the viscous losses are proportional to the inverse square root of the pressure the peak height should be measurable at the higher pressure. The tradeoff here is that at 10 atmospheres; the highest relative humidity attainable is 10 percent. The data collected at 10 atmospheres is also summarized.

Meredith, R. W.↗

Tethered Balloon System Ozone Profiles during CoURAGE Summer Intensive Operational Period Field Campaign Report

During the summer IOP, the small ARM field campaign CRGTBSO3 collected measurements to gain an improved understanding of differences between the atmospheric composition in and just above the marine layer at the CoURAGE TBS site near the eastern shore of Chesapeake Bay. CRGTBSO3 included guest instrumentation with ozone (O 3 ) profile measurements on the TBS and surface O3 and meteorological measurements at the TBS site. An En-Sci 2Z electrochemical cell (ECC) ozonesonde (Komhyr 1969, 1986, Witte et al. 2018) was included on the TBS. The ozonesonde was connected to an InterMet iMet-4RSB radiosonde, and the overall data collected included vertical profiles of ozone, relative humidity, temperature, pressure, and altitude. The CRGTBSO3 iMet-4 radiosonde data is identical to that of the iMet in the Tethered Balloon System Merged Data Product (TBSMERGED; Gaustad and Dexheimer 2025). The TBSMERGED data product also includes meteorological data from a different sensor, the iMet XQ2. In some cases, the iMet XQ2 relative humidity (RH) data may be more accurate than the iMet-4, such as for some instances when the iMet-4 RH data stays at 100% for an extended period throughout a profile.

54 ENVIRONMENTAL SCIENCES↗

A Near-Infrared and Thermal Imager for Mapping Titan's Surface Features

Approximately 10% of the solar insolation reaches the surface of Titan through atmospheric spectral windows. We will discuss a filter based imaging system for a future Titan orbiter that will exploit these windows mapping surface features, cloud regions, polar storms. In the near-infrared (NIR), two filters (1.28 micrometer and 1.6 micrometer), strategically positioned between CH1 absorption bands, and InSb linear array pixels will explore the solar reflected radiation. We propose to map the mid, infrared (MIR) region with two filters: 9.76 micrometer and 5.88-to-6.06 micrometers with MCT linear arrays. The first will map MIR thermal emission variations due to surface albedo differences in the atmospheric window between gas phase CH3D and C2H4 opacity sources. The latter spans the crossover spectral region where observed radiation transitions from being dominated by thermal emission to solar reflected light component. The passively cooled linear arrays will be incorporated into the focal plane of a light-weight thin film stretched membrane 10 cm telescope. A rad-hard ASIC together with an FPGA will be used for detector pixel readout and detector linear array selection depending on if the field-of-view (FOV) is looking at the day- or night-side of Titan. The instantaneous FOV corresponds to 3.1, 15.6, and 31.2 mrad for the 1, 5, and 10 micrometer channels, respectively. For a 1500 km orbit, a 5 micrometer channel pixel represents a spatial resolution of 91 m, with a FOV that spans 23 kilometers, and Titan is mapped in a push-broom manner as determined by the orbital path. The system mass and power requirements are estimated to be 6 kg and 5 W, respectively. The package is proposed for a polar orbiter with a lifetime matching two Saturn seasons.

Aslam, S.↗

Biodeactivation of Lipopolysaccharide Correlates with Surface‐Bound NO 3 After Cold Atmospheric Plasma Treatment

Cold atmospheric plasma (CAP) treatment of biological surfaces results in important changes of biological functions, but little knowledge on specific surface‐chemical changes is available. We measured surface‐bound NO 3 on polymer and biomolecular films after CAP treatment. An O 2 /N 2 ‐based surface microdischarge was used to deactivate lipopolysaccharide (LPS), an immune‐stimulating biomolecule found in Gram negative bacteria. The observed LPS biodeactivation was highest for low N 2 concentrations in O 2 , increased roughly linearly with surface NO 3 , and then saturated. NO 3 was also observed after treatment by a very different source: an atmospheric pressure plasma jet operating with an Ar carrier gas. Thus, NO 3 formation is a generic surface chemical modification of these materials by CAP sources.

Bartis, Elliot A. J.↗

Evaluation of Intercomparisons of Four Different Types of Model Simulating TWP-ICE

Four model intercomparisons were run and evaluated using the TWP-ICE field campaign, each involving different types of atmospheric model. Here we highlight what can be learnt from having single-column model (SCM), cloud-resolving model (CRM), global atmosphere model (GAM) and limited-area model (LAM) intercomparisons all based around the same field campaign. We also make recommendations for anyone planning further large multi-model intercomparisons to ensure they are of maximum value to the model development community. CRMs tended to match observations better than other model types, although there were exceptions such as outgoing long-wave radiation. All SCMs grew large temperature and moisture biases and performed worse than other model types for many diagnostics. The GAMs produced a delayed and significantly reduced peak in domain-average rain rate when compared to the observations. While it was shown that this was in part due to the analysis used to drive these models, the LAMs were also driven by this analysis and did not have the problem to the same extent. Based on differences between the models with parametrized convection (SCMs and GAMs) and those without (CRMs and LAMs), we speculate that that having explicit convection helps to constrain liquid water whereas the ice contents are controlled more by the representation of the microphysics.

convection↗

Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets

This dataset contains turbine- and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in Steady State (FLORIS) model, version 2.3.0. The 252,500 cases include 500 unique wind plants generated randomly by a specialized Plant Layout Generator (PLayGen) that samples randomized realizations of wind plant layouts from one of four canonical configurations: (i) cluster, (ii) single string, (iii) multiple string, (iv) parallel string. Other wind plant layout parameters were also randomly sampled, including the number of turbines (25-200) and the mean turbine spacing (3D-10D, where D denotes the turbine rotor diameter). For each layout, 500 different sets of atmospheric conditions were randomly sampled. These include wind speed in 0-25 m/s, wind direction in 0 deg.-360 deg., and turbulence intensity chosen from low (6%), medium (8%), and high (10%). For each atmospheric inflow scenario, the individual turbine yaw angles were randomly sampled from a one-sided truncated Gaussian on the interval 0 deg.-30 deg. oriented relative to wind inflow direction. This random data is supplemented with a collection of yaw-optimized samples where FLORIS was used to determine turbine yaw angles that maximize power production for the entire plant. To generate this data, a subset of cases were selected (50 atmospheric conditions from 50 layouts each for a total of additional 2,500 cases) for which FLORIS was re-run with wake steering control optimization. The IEA onshore reference turbine, which has a 130 m rotor diameter, a 110 m hub height, and a rated power capacity of 3.4 MW was used as the turbine for all simulations. The simulations were performed using NREL's Eagle high performance computing system in February 2021 as part of the Spatial Analysis for Wind Technology Development project funded by the U.S. Department of Energy Wind Energy Technologies Office. The data was collected, reformatted, and preprocessed for this OEDI submission in May 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub repository under explore_wind_plant_data_h5.ipynb.

AI↗

Environment of Mars, 1988

A compilation of scientific knowledge about the planet Mars is provided. Information is divided into three categories: atmospheric data, surface data, and astrodynamic data. The discussion of atmospheric data includes the presentation of nine different models of the Mars atmosphere. Also discussed are Martian atmospheric constituents, winds, clouds, and solar irradiance. The great dust storms of Mars are presented. The section on Mars surface data provides an in-depth examination of the physical and chemical properties observed at the two Viking landing sites. Bulk densities, dielectric constants, and thermal inertias across the planet are then described and related back to those specific features found at the Viking landing sites. The astrodynamic materials provide the astronomical constants, time scales, and reference coordinate frames necessary to perform flightpath analysis, navigation design, and science observation design.

Kaplan, David I.↗