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NASA NTRSDate not supplied

Swarm Mentality: Toward Automatic Swarm State Awareness with Runtime Verification

Cyber-Physical Systems (CPSs) already exhibit impressive performance in all areas of human life, and swarms of CPSs promise to increase their capabilities even further. However, to effectively utilize CPS swarms their complexity of operation has to scale sub-linearly with the number of swarm members. Presenting the swarm to an operator as a single entity almost eliminates the additional per-member overhead entirely. To operate a swarm as one entity, and/or to increase the swarm’s autonomy, the operator and the swarm members need to reason and communicate at the same level of abstraction, i.e. the swarm needs a sense of “self.” Therefore, we require the ability to specify whole swarm properties yet monitor them at the member level. We examine one architecture for achieving this awareness by: 1) Defining a taxonomy for comparing techniques that synthesize this belief-state 2) Propose use of the Runtime Verification formal method to fill this role 3) Present preliminary designs for extending and embedding such a system in the Distributed Spacecraft Autonomy architecture to generate per-member monitors from swarm level specification.

Runtime Verification↗

NASA NTRSDate not supplied

Porous Microstructure Analysis (PuMA) software

The Porous Microstructure Analysis (PuMA) software was developed to provide a robust and efficient framework for computing material properties based on their microstructures. The development was motivated by advancements in X-ray microtomography, an imaging technology that can resolve the structure of a material at a sub-micron scale, in 3D and even in 4D (over time). PuMA provides the capability of computing a comprehensive spectrum of properties, from the most fundamental geometric features of a microstructure, to advanced anisotropic thermo-elastic properties. In addition, the software can generate artificial microstructures, ranging from simple analytical shapes to complex fibrous woven and non- woven geometries, which can be used in performance optimization studies. This presentation will highlight many of the capabilities of the recent open-source release.

microtomography↗

NASA NTRSDate not supplied

TROPOMI Geometry-dependent Lambertian-Equivalent surface Reflectivity (GLER) Product for Improved Trace-Gas Retrieval

Accurate information about the reflectivity of the Earth's surface is required for most satellite retrievals of atmospheric composition, and this information is generally taken from monthly surface reflectivity climatology that neglects angular dependence. Previously we introduced Geometry-dependent Lambertian-equivalent surface reflectivity (GLER) which captures solar and satellite viewing angle dependence as well as daily and seasonal changes. GLER is calculated from simulations of Rayleigh-only top-of-atmosphere (TOA) radiances over non-Lambertian surfaces. We use NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) product over land and the wind-dependent Cox–Munk wave-facet slope distribution including water-leaving radiance over water to accounts for surface BRDF. We have developed global GLER product, previously for the Ozone Monitoring Instrument (OMI) and recently for Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) with several new improvements and updates. We have implemented the near real time daily V006 MODIS MCD43C1 BRDF data and gap-filled with a daily BRDF coefficient climatology created from 2002-2017 V006 MCD43GF data. The NASA’s Global Modelling Initiative hourly 0.25 x 0.25 deg Replay simulations are used for more accurate determination of pixel specific terrain pressure. To improve detection of seasonal snow/ice scenes, we use the 4-km snow cover product from the Interactive Multi-sensor Snow and Ice Mapping System (IMS). Finally, we use an improved version of the vector linearized discrete ordinate radiative transfer (VLIDORT) for update of the top-of-atmosphere (TOA) radiance look-up-tables (LUTs). We demonstrate how the use of GLER is beneficial to TROPOMI’s high spatial resolution (up to 3.5 km x 3.5 km) measurements to monitor atmospheric trace gas pollutants down to the sub-city scale.

TROPOMI↗

NASA NTRS2021

Error Propagation in Microwave Soil Moisture and Vegetation Optical Depth Retrievals

Satellite soil moisture and vegetation optical depth (VOD; related to the total vegetation water mass per unit area) are increasingly being used to study water relations in the soil-plant continuum across the globe. However, soil moisture and VOD are typically jointly estimated, where errors in the optimization approach can cause compensation between both variables and confound such studies. It is thus critical to quantify how satellite microwave measurement errors propagate into soil moisture and VOD. Such a study is especially important for VOD given limited investigations of whether VOD reflects in-situ plant physiology. Furthermore, despite new approaches that constrain (or regularize) VOD dynamics to reduce soil moisture errors, there is limited study of whether regularization reduces VOD errors without obscuring true vegetation temporal dynamics. Here, we find that, across the globe, VOD is less robust to measurement error (more difficult for optimization methods to find the true solution) than soil moisture in their joint estimation. However, a moderate degree of regularization (via time-constrained VOD) reduces errors in VOD to a greater degree than soil moisture and reduces spurious soil moisture-VOD coupling. Furthermore, despite constraining VOD time dynamics, regularized VOD variations on sub-weekly scales are both closer to simulated true VOD time series and have global VOD post-rainfall responses with reduced error signatures compared to VOD retrievals without regularization. Ultimately, we recommend moderately regularized VOD for use in large scale studies of soil-plant water relations because it suppresses noise and spurious soil moisture-VOD coupling without removing the physical signal.

Vegetation optical depth↗

NASA NTRS2023

Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs

The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers, and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.

Carl Malings↗

NASA NTRSDate not supplied

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

High spatial and temporal resolution air quality estimation and forecasting can be enhanced by combining global data sources, like chemical transport models and satellite remote sensing, with local information from regulatory and low-cost air quality monitors. Successful integration of data from these diverse sources is complicated by many factors, however, including differences in spatial and temporal resolution, data availability and latency issues, varying data quality, and large computational and data storage requirements. This presentation will provide an overview of a NASA-funded effort to develop the foundation for future operationalization of air quality forecasting for world-wide end-users and integration into their air quality management decision processes, which will be achieved in future phases of this multi-year project. We will summarize our progress in developing a data fusion system using the Google Earth Engine platform which can integrate model, satellite, and surface-level monitoring datasets to enhance estimation and forecasting of air-quality-relevant pollutants at sub-daily and sub-city scales. The tool is being developed in close cooperation with several city- and regional-level air quality managers in the USA and around the world. Our end-goal is to provide these air quality managers with the information they need to assess and anticipate the impacts of poor air quality, track changes in air quality due to ongoing mitigation efforts and land use changes, and identify ways to improve their air quality monitoring strategies. This presentation will focus on recent advances achieved through the project, including integration of multiple air quality datasets in a prototype data fusion system in Google Earth Engine, the quantification of uncertainties associated with our data fusion approach, and the development of user interfaces and visualization tools to convey air quality information in a way which best meets end-user needs.

Carl Malings↗

NASA NTRSDate not supplied

Air Quality Data Fusion with Sensors, Satellites, and Models

Global forecasting models, satellite remote sensing, and ground-based regulatory and low-cost monitors all have strengths and weaknesses with respect to providing locally relevant information about air quality. This presentation will give a brief overview of these data sources and then discuss a method for combining them via data fusion to support near-real-time air quality estimation and forecasting at sub-city scales. The basic idea behind the approach will be summarized, followed by an update on recent developments towards creating an operational system using Google Earth Engine and on quantifying uncertainties related to data fusion outputs.

Carl Malings↗

NASA NTRSDate not supplied

Flexible Data Fusion for Air Quality Estimation and Forecasting in Google Earth Engine to support Global Health Management Needs

The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.

Nathan R. Pavlovic↗

NASA NTRS2023

Simulations of 7 Be and 10 Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates

The cosmogenic radionuclides 7 Be and 10 Be are useful aerosol tracers for atmospheric transport studies. Combining 7 Be and 10 Be measurements with an atmospheric transport model can not only improve our understanding of the radionuclide transport and deposition processes but also provide an evaluation of the transport process in the model. To simulate these aerosol tracers, it is critical to evaluate the influence of radionuclides production uncertainties on simulations. Here we use the GEOS-Chem chemical transport model driven by the MERRA-2 reanalysis to simulate 7 Be and 10 Be with different production scenarios: the default production rate in GEOS-Chem based on an empirical approach (Lal and Peters, 1967; denoted as LP67), and two production rates from the CRAC:Be (Cosmic Ray Atmospheric Cascade: Beryllium; Poluianov et al., 2016) model considering only geomagnetic cut-off rigidities for a geocentric axial dipole (denoted as P16) or realistic spatial geomagnetic cut-off rigidity variations due to non-dipole moments of the geomagnetic field (denoted as P16spa). The model results are comprehensively evaluated with a large number of measurements including surface air concentrations and deposition fluxes. The model with the P16spa production can reproduce the absolute values and temporal variability of 7 Be and 10 Be surface concentrations and deposition fluxes on annual and sub-annual scales, as well as the vertical profiles of air concentrations. Simulations with the LP67 production tend to overestimate the absolute values of 7 Be and 10 Be concentrations. The P16 simulations suggest less than 10% differences compared to P16spa but tend to produce a significant positive bias (>20%) in the 7 Be deposition fluxes over East Asia. We find that the deposition fluxes are more sensitive to the production in the troposphere and downward transport from the stratosphere. Independent of the production models, surface air concentrations and deposition fluxes from all simulations show similar seasonal variations, suggesting a dominant meteorological influence. The model can also simulate reasonably the stratosphere-troposphere exchange process of 7 Be and 10 Be by producing stratospheric contribution and 10 Be/ 7 Be ratio values that agree with measurements. Finally, we illustrate the importance of including the time-varying solar modulation in the production calculation, which can significantly improve the agreement between model results and measurements, especially at mid- and high- latitudes. Reduced uncertainties in the production rates, as demonstrated in this study, improve the utility of 7 Be and 10 Be as aerosol tracers for evaluating and testing transport and scavenging processes in global models.

Minjie Zheng↗

NASA NTRSDate not supplied

Supporting Global Air Quality Management Needs With A Flexible Data Fusion Tool for Estimation and Forecasting in Google Earth Engine

Carl Malings↗

NASA NTRS2015

Correlating Mineralogy and Amino Acid Contents of Milligram-Scale Murchison Carbonaceous Chondrite Samples

Amino acids, the building blocks of proteins, have been found to be indigenous in most of the carbonaceous chondrite groups. The abundances of amino acids, as well as their structural, enantiomeric and isotopic compositions differ significantly among meteorites of different groups and petrologic types. This suggests that there is a link between parent-body conditions, mineralogy and the synthesis and preservation of amino acids (and likely other organic molecules). However, elucidating specific causes for the observed differences in amino acid composition has proven extremely challenging because samples analyzed for amino acids are typically much larger ((is) approximately 100 mg powders) than the scale at which meteorite heterogeneity is observed (sub mm-scale differences, (is) approximately 1-mg or smaller samples). Thus, the effects of differences in mineralogy on amino acid abundances could not be easily discerned. Recent advances in the sensitivity of instrumentation have made possible the analysis of smaller samples for amino acids, enabling a new approach to investigate the link between mineralogical con-text and amino acid compositions/abundances in meteorites. Through coordinated mineral separation, mineral characterization and highly sensitive amino acid analyses, we have performed preliminary investigations into the relationship between meteorite mineralogy and amino acid composition. By linking amino acid data to mineralogy, we have started to identify amino acid-bearing mineral phases in different carbonaceous meteorites. The methodology and results of analyses performed on the Murchison meteorite are presented here.

Burton, Aaron, S.↗

NASA NTRSDate not supplied

Mission Design & Operations Approach for the HelioSwarm Mission

HelioSwarm: The Nature of Turbulence in Space Plasmas is a transformational mission to explore the dynamic three-dimensional mechanisms controlling the physics of plasma turbulence, a ubiquitous process occurring in the heliosphere and plasmas throughout the universe. Turbulence is the process by which energy contained in fluctuating magnetic fields and plasma motion cascades from large to smaller spatial scales. HelioSwarm achieves its science goals by making simultaneous measurements across a wide range of measurement baselines, spanning magnetohydrodynamic scales (1000’s of km) to sub-ion heating scales (10’s of km), using a novel nine-spacecraft swarm. The swarm operates in a high-altitude lunar resonant Earth orbit (two-week period, ~63 RE apogee, ~13 RE perigee), giving it access to both the pristine solar wind and regions of strongly driven turbulence (specifically the magnetosphere and foreshock), and utilizes customized relative orbital motion of the swarm members to produce the range of measurement baselines and configurations. The swarm comprises eight “node” spacecraft, manufactured by Blue Canyon Technologies, and a “hub” spacecraft produced by Northrop Grumman Corp. The hub serves as a communications relay, with all communications between the ground and the nodes flowing through it. Mission operations are conducted within the Multi-Mission Operations Center at the NASA Ames Research Center and science operations at the University of New Hampshire, Durham. HelioSwarm was selected in 2022 as one of NASA’s newest Heliophysics Explorer missions to proceed from mission concept into mission implementation, with a target launch in 2029. This paper provides an overview of the mission’s science goals and objectives, the mission design, and the concept of operations, with an emphasis on how the swarm aspects of the mission both enable the science measurements and present unique operational challenges. The paper then describes the proposed development approach for the mission operations system and ground data system which relies on a selective combination of scaling strategies to meet the challenges.

HelioSwarm↗

NASA NTRS1997

Damage Initiation and Ultimate Tensile Strength of Scaled [0 deg n/90 deg n/0 deg n]sub T Graphite-Epoxy Coupons

Previous research on scaling effects in composite materials has demonstrated that the stress levels at first ply failure and ultimate failure of composite laminates are dependent on the size of the laminate. In particular, the thickness dimension has been shown to be the most influential parameter in strength scaling of composite coupons loaded in tension. Geometrically and constitutively scaled laminates exhibit decreasing strength with increasing specimen size, and the magnitude of the strength-size effect is a function of both material properties and laminate stacking sequence. Some of the commonly used failure criteria for composite materials such as maximum stress, maximum strain, and tensor polynomial (e.g., Tsai-Wu) cannot account for the strength-size effect. In this paper, three concepts are developed and evaluated for incorporating size dependency into failure criteria for composite materials. An experimental program of limited scope was performed to determine the first ply failure stress in scaled cross-ply laminates loaded in tension. Test specimens were fabricated of AS-4/3502 graphite-epoxy composite material with laminate stacking sequences of [0 deg n/90 deg n/o deg n]subT where n=1-6. Two experimental techniques were used to determine first ply failure, defined as a transverse matrix crack in the 90 deg ply: (1) step loading with dye penetrant x-ray of the specimen at each load interval, and (2) acoustic emission. The best correlation between first ply failure analysis and experimental data was obtained using a modified Weibull approach which incorporated the residual thermal stress and the outer ply constraint, as well as the ply thickness effect. Finally, a second set of experiments was performed to determine the tensile response and ultimate failure of the scaled cross-ply laminates. The results of these experiments indicated no influence of specimen size on tensile response or ultimate strength.

Jackson, Karen E.↗

NASA NTRS1992

Aerodynamic roughness measured in the field and simulated in a wind tunnel

This study evaluates how well values of aerodynamic surface roughness, z sub 0, measured over scale models in wind tunnels correlate with values of z sub 0 measured at full scale in the field. A field experiment was conducted in which values of z sub 0 and u* (wind friction speed) were measured over three arrays of non-erodible roughness elements on a dry lake bed. Wind profiles were measured by ten anemometers on a 15 m mast under thermally neutral atmospheric conditions. Values of z sub 0 increased from .00014 m (dry lake bed only) to .026 m with increasing roughness element density. The three roughness element arrays were simulated at 1/10 and 1/20 scale in an open-circuit atmospheric boundary-layer wind tunnel. Velocities were measured with a boundary-layer pitot-tube rake from the same relative position within the scale model arrays as the anemometers were relative to the field arrays. Each array at each scale was sampled three times at five freestream velocities. Average values of z sub 0 for each model array at each scale were compared with full-scale values of z sub 0 obtained in the field. The field vs. wind tunnel correspondence of z sub 0 is found to be z sub 0 field = 0.2661 x (z sub(0 model) x scale(exp -1))exp .8159.

Sullivan, Robert↗

NASA NTRS1998

Boreal Winter Predictions with the GEOS-2 GCM: The Role of Boundary Forcing and Initial Conditions

Ensembles of atmospheric General Circulation Model (GCM) seasonal forecasts and long-term simulations (1980-94) are analyzed to assess the controlling influences of boundary forcing and memory of the initial conditions. Both the forecasts and simulations are carried out with version 2 of the Goddard Earth Observing System (GEOS-2) GCM forced with observed sea surface temperatures (SSTs). While much of the focus is on the seasonal time scale (January- March) and the Pacific North American (PNA) region, we also present results for other regions, shorter time scales, and other known modes of variability in the northern hemisphere extratropics. Forecasts of indices of some of the key large-scale modes of variability show that there is considerable variability in skill between different regions of the Northern Hemisphere. The eastern North Atlantic region has the poorest long lead forecast skill showing no skill beyond about 10 days. Skillful seasonal forecasts are primarily confined to the wave-like ENSO response emanating from the tropical Pacific. In the Northern Hemisphere, this is associated with the well-known Pacific/North American (PNA) pattern. Memory of the initial conditions is the major factor leading to skillful extratropical forecasts of lead time less than one month, while SST forcing is the only factor at the seasonal time scale. SST forcing contributes to skillful forecasts at sub- seasonal time scales only over the PNA region. The GEOS-2 GCM produces average (1980-94) signal to noise ratios which are less than one everywhere in the extratropics, except for the subtropical Pacific where they approach 1.5. When confined to the ENSO years, the maximum signal to noise ratios occur in the PNA region where they exceed three. An assessment of the sampling distribution of the forecasts suggests the model's ENSO response is very likely too weak. These results show some sensitivity to the uncertainties in the estimates of the SST forcing fields. In the North Pacific region, the sensitivity to SST forcing manifests itself primarily as changes in the variability of the PNA response, underscoring the need for an ensemble approach to the seasonal prediction problem.

Chang, Yehui↗

NASA NTRS2022

CLEAR: Boosted Lyα Transmission of the Intergalactic Medium in UV-bright Galaxies

Reionization is an inhomogeneous process, thought to begin in small ionized bubbles of the intergalactic medium (IGM) around overdense regions of galaxies. Recent Lyα studies during the epoch of reionization show evidence that ionized bubbles formed earlier around brighter galaxies, suggesting higher IGM transmission of Lyα from these galaxies. We investigate this problem using IR slitless spectroscopy from the Hubble Space Telescope (HST) Wide-Field Camera 3 (WFC3) G102 grism observations of 148 galaxies selected via photometric redshifts at 6.0 < z < 8.2. These galaxies have spectra extracted from the CANDELS Lyα Emission at Reionization (CLEAR) survey. We combine the CLEAR data for 275 galaxies with the Keck Deep Imaging Multi-Object Spectrograph and MOSFIRE data set from the Texas Spectroscopic Search for Lyα Emission at the End of Reionization Survey. We constrain the Lyα equivalent width (EW) distribution at 6.0 < z < 8.2, which is described by an exponential form, dN / dEW ∝ exp(-EW) W(sub 0), with the characteristic e-folding scale width (W(sub 0)). We confirm a significant drop in the Lyα strength (i.e., W(sub 0)) at z > 6. Furthermore, we compare the redshift evolution of W(sub 0) between galaxies at different UV luminosities. UV-bright (M(sub UV) < −21 [i.e., L(sub UV) > L*]) galaxies show weaker evolution with a decrease of 0.4 ( ± 0.2) dex in W(sub 0) at z > 6, while UV-faint (M(sub UV) > −21 [LUV < L*]) galaxies exhibit a significant drop of 0.7–0.8 (±0.2) dex in W(sub 0) from z < 6 to z > 6. If the change in W(sub 0) is proportional to the change in the IGM transmission for Lyα photons, then this is evidence that the transmission is “boosted” around UV-brighter galaxies, suggesting that reionization proceeds faster in regions around such galaxies.

Reionization↗

NASA NTRS1994

Experimental Study of Vane Heat Transfer and Aerodynamics at Elevated Levels of Turbulence

A four vane subsonic cascade was used to investigate how free stream turbulence influences pressure surface heat transfer. A simulated combustor turbulence generator was built to generate high level (13 percent) large scale (Lu approximately 44 percent inlet span) turbulence. The mock combustor was also moved upstream to generate a moderate level (8.3 percent) of turbulence for comparison to smaller scale grid generated turbulence (7.8 percent). The high level combustor turbulence caused an average pressure surface heat transfer augmentation of 56 percent above the low turbulence baseline. The smaller scale grid turbulence produced the next greatest effect on heat transfer and demonstrated the importance of scale on heat transfer augmentation. In general, the heat transfer scaling parameter U(sub infinity) TU(sub infinity) LU(sub infinity)(exp -1/3) was found to hold for the turbulence. Heat transfer augmentation was also found to scale approximately on Re(sub ex)(exp 1/3) at constant turbulence conditions. Some evidence of turbulence intensification in terms of elevated dissipation rates was found along the pressure surface outside the boundary layer. However, based on the level of dissipation and the resulting heat transfer augmentation, the amplification of turbulence has only a moderate effect on pressure surface heat transfer. The flow field turbulence does drive turbulent production within the boundary layer which in turn causes the high levels of heat transfer augmentation. Unlike heat transfer, the flow field straining was found to have a significant effect on turbulence isotropy. On examination of the one dimensional spectra for u' and v', the effect to isotropy was largely limited to lower wavenumber spectra. The higher wavenumber spectra showed little or no change. The high level large scale turbulence was found to have a strong influence on wake development. The free stream turbulence significantly enhanced mixing resulting in broader and shallower wakes than the baseline case. High levels of flow field turbulence were found to correlate with a significant increase in total pressure loss in the core of the flow. Documenting the wake growth and characteristics provides boundary conditions for the downstream rotor.

Ames, Forrest E.↗

NASA NTRS2013

A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

For the first time, a formal comparison is made between gravity wave momentum fluxes in models and those derived from observations. Although gravity waves occur over a wide range of spatial and temporal scales, the focus of this paper is on scales that are being parameterized in present climate models, sub-1000-km scales. Only observational methods that permit derivation of gravity wave momentum fluxes over large geographical areas are discussed, and these are from satellite temperature measurements, constant-density long-duration balloons, and high-vertical-resolution radiosonde data. The models discussed include two high-resolution models in which gravity waves are explicitly modeled, Kanto and the Community Atmosphere Model, version 5 (CAM5), and three climate models containing gravity wave parameterizations,MAECHAM5, Hadley Centre Global Environmental Model 3 (HadGEM3), and the Goddard Institute for Space Studies (GISS) model. Measurements generally show similar flux magnitudes as in models, except that the fluxes derived from satellite measurements fall off more rapidly with height. This is likely due to limitations on the observable range of wavelengths, although other factors may contribute. When one accounts for this more rapid fall off, the geographical distribution of the fluxes from observations and models compare reasonably well, except for certain features that depend on the specification of the nonorographic gravity wave source functions in the climate models. For instance, both the observed fluxes and those in the high-resolution models are very small at summer high latitudes, but this is not the case for some of the climate models. This comparison between gravity wave fluxes from climate models, high-resolution models, and fluxes derived from observations indicates that such efforts offer a promising path toward improving specifications of gravity wave sources in climate models.

mathematical models↗