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NASA NTRS2021

Secondary Science Teachers’ Implementation of a Curricular Intervention When Teaching With Global Climate Models

In the past decade, emphasis on promoting “climate literacy” in K-16 science classrooms has increased. Teachers play a critical role in cultivating these opportunities, especially in secondary science classrooms. However, most prior climate education research has focused on students and student learning; little is known about how teachers implement climate-focused curricular interventions. Here, we report findings from a concurrent mixed methods, multiple-case study of four secondary science teachers’ implementation of a new, NGSS-aligned, model-centric climate curriculum module grounded in the use of a data-driven, computer-based climate modeling tool—Easy Global Climate Model (EzGCM). We employ multiple data sources, including video-recorded classroom observations, interviews, and instructional artifacts, and both qualitative and quantitative analyses, to investigate how teachers implemented the curriculum. Findings show that, overall, teachers implemented the curriculum in ways that were less model-centric than designed, placing greater emphasis on EzGCM itself rather than using the model to investigate Earth’s changing climate. Additionally, we present detailed single-case studies of each participant teacher that highlight differences in teachers’ implementation of the curriculum module and their reasoning for making observed instructional decisions. This research sheds light on the design of secondary science learning environments by illustrating the varied ways teachers implement a climate-focused curriculum to support students’ developing climate literacy. This has important implications for the design of climate-focused curriculum and supports for teachers.

Secondary science teaching↗
NASA NTRS1977

A global thermospheric model based on mass spectrometer and incoherent scatter data MSIS. I - N2 density and temperature

Measurements of neutral nitrogen density from mass spectrometers on five satellites (AE-B, Ogo 6, San Marco 3, Aeros A, and AE-C) and neutral temperatures inferred from incoherent scatter measurements at four ground stations are combined to produce a model of thermospheric neutral temperatures and nitrogen densities similar to the Ogo 6 empirical model (Hedin et al., 1974). This global model is designated MSIS (mass spectrometer and incoherent scatter). The global average temperature, the annual temperature variation, lower bound density, and lower bound temperature are discussed. The data set covers the time period from the end of 1965 to mid-1975 and also a wide range of solar activities. Diurnal and semidiurnal variations in lower bound density and temperature are considered, as is magnetic activity.

Hedin, A. E.↗
NASA NTRS2019

Parameterization-Induced Uncertainties and Impacts of Crop Management Harmonization in a Global Gridded Crop Model Ensemble

Global gridded crop models (GGCMs) combine agronomic or plant growth models with gridded spatial input data to estimate spatially explicit crop yields and agricultural externalities at the global scale. Differences in GGCM outputs arise from the use of different biophysical models, setups, and input data. GGCM ensembles are frequently employed to bracket uncertainties in impact studies without investigating the causes of divergence in outputs. This study explores differences in maize yield estimates from five GGCMs based on the public domain field-scale model Environmental Policy Integrated Climate (EPIC) that participate in the AgMIP Global Gridded Crop Model Intercomparison initiative. Albeit using the same crop model, the GGCMs differ in model version, input data, management assumptions, parameterization, and selection of subroutines affecting crop yield estimates via cultivar distributions, soil attributes, and hydrology among others. The analyses reveal inter-annual yield variability and absolute yield levels in the EPIC-based GGCMs to be highly sensitive to soil parameterization and crop management. All GGCMs show an intermediate performance in reproducing reported yields with a higher skill if a static soil profile is assumed or sufficient plant nutrients are supplied. An in-depth comparison of setup domains for two EPIC-based GGCMs shows that GGCM performance and plant stress responses depend substantially on soil parameters and soil process parameterization, i.e. hydrology and nutrient turnover, indicating that these often neglected domains deserve more scrutiny. For agricultural impact assessments, employing a GGCM ensemble with its widely varying assumptions in setups appears the best solution for coping with uncertainties from lack of comprehensive global data on crop management, cultivar distributions and coefficients for agro-environmental processes. However, the underlying assumptions require systematic specifications to cover representative agricultural systems and environmental conditions. Furthermore, the interlinkage of parameter sensitivity from various domains such as soil parameters, nutrient turnover coefficients, and cultivar specifications highlights that global sensitivity analyses and calibration need to be performed in an integrated manner to avoid bias resulting from disregarded core model domains. Finally, relating evaluations of the EPIC-based GGCMs to a wider ensemble based on individual core models shows that structural differences outweigh in general differences in configurations of GGCMs based on the same model, and that the ensemble mean gains higher skill from the inclusion of structurally different GGCMs. Although the members of the wider ensemble herein do not consider crop-soil-management interactions, their sensitivity to nutrient supply indicates that findings for the EPIC-based sub-ensemble will likely become relevant for other GGCMs with the progressing inclusion of such processes.

Folberth, Christian↗
NASA NTRS2004

Development of Global Magnetosphere Models of Jupiter

The objective of the proposal was to construct global magnetospheric models of Jupiter for the use of Jovian magnetospheric community. In the four years of the grant period we were able to achieve all of the stated science objectives. The work has resulted in: 1) A new structural model of Jovian current sheet; 2) Global thickness map of the current sheet; 3) Magnetic field models of the current sheet; 4) The global model of Jupiter's magnetospheric field including hinging and delay of the current sheet, sweepback of the magnetic field and the shielding field of the magnetopause. To accomplish our work, we assembled an exhaustive magnetic field data base from all of the spacecraft that have visited Jupiter (Pioneers 10 and 11, Voyagers 1 and 2, Ulysses and Galileo). The data were rotated into system III and JSM coordinates. We used the data at resolutions of 1 minute (for studies of the structure of the current sheet) and 10 minutes (for building the global model).

Khurana, Krishan K.↗
NASA NTRS1989

Flight motor set 360L001 (STS-26R). (Reconstructed dynamic loads analysis)

A transient analysis was performed to correlate the predicted versus measured behavior of the Redesigned Solid Rocket Booster (RSRB) during Flight 360L001 (STS-26R) liftoff. Approximately 9 accelerometers, 152 strain gages, and 104 girth gages were bonded to the motors during this event. Prior to Flight 360L001, a finite element model of the RSRB was analyzed to predict the accelerations, strains, and displacements measured by this developmental flight instrumentation (DFI) within an order of magnitude. Subsequently, an analysis has been performed which uses actual Flight 360L001 liftoff loading conditions, and makes more precise predictions for the RSRB structural behavior. Essential information describing the analytical model, analytical techniques used, correlation of the predicted versus measured RSRB behavior, and conclusions, are presented. A detailed model of the RSRB was developed and correlated for use in analyzing the motor behavior during liftoff loading conditions. This finite element model, referred to as the RSRB global model, uses super-element techniques to model all components of the RSRB. The objective of the RSRB global model is to accurately predict deflections and gap openings in the field joints to an accuracy of approximately 0.001 inch. The model of the field joint component was correlated to Referee and Joint Environment Simulation (JES) tests. The accuracy of the assembled RSRB global model was validated by correlation to static-fire tests such DM-8, DM-9, QM-7, and QM-8. This validated RSRB global model was used to predict RSRB structural behavior and joint gap opening during Flight 360L001 liftoff. The results of a transient analysis of the RSRB global model with imposed liftoff loading conditions are presented. Rockwell used many gage measurements to reconstruct the load parameters which were imposed on the RSRB during the Flight 360L001 liftoff. Each load parameter, and its application, is described. Also presented are conclusions and recommendations based on the analysis of this load case and the resulting correlation between predicted and measured RSRB structural behavior.

Call, V. B.↗
NASA NTRS2022

Constraining Global Coronal Models with Multiple Independent Observables

Global coronal models seek to produce an accurate physical representation of the Sun's atmosphere that can be used, for example, to drive space-weather models. Assessing their accuracy is a complex task, and there are multiple observational pathways to provide constraints and tune model parameters. Here, we combine several such independent constraints, defining a model-agnostic framework for standardized comparison. We require models to predict the distribution of coronal holes at the photosphere, and neutral line topology at the model's outer boundary. We compare these predictions to extreme-ultraviolet (EUV) observations of coronal hole locations, white-light Carrington maps of the streamer belt, and the magnetic sector structure measured in situ by Parker Solar Probe and 1 au spacecraft. We study these metrics for potential field source surface (PFSS) models as a function of source surface height and magnetogram choice, as well as comparing to the more physical Wang–Sheeley–Arge (WSA) and the Magnetohydrodynamic Algorithm outside a Sphere (MAS) models. We find that simultaneous optimization of PFSS models to all three metrics is not currently possible, implying a trade-off between the quality of representation of coronal holes and streamer belt topology. WSA and MAS results show the additional physics that they include address this by flattening the streamer belt while maintaining coronal hole sizes, with MAS also improving coronal hole representation relative to WSA. We conclude that this framework is highly useful for inter- and intra-model comparisons. Integral to the framework is the standardization of observables required of each model, evaluating different model aspects.

S. T. Badman↗
NASA NTRS2014

The QBO in Two GISS Global Climate Models: 1. Generation of the QBO

The adjustment of parameterized gravity waves associated with model convection and finer vertical resolution has made possible the generation of the quasi-biennial oscillation (QBO) in two Goddard Institute for Space Studies (GISS) models, GISS Middle Atmosphere Global Climate Model III and a climate/middle atmosphere version of Model E2. Both extend from the surface to 0.002 hPa, with 2deg × 2.5deg resolution and 102 layers. Many realistic features of the QBO are simulated, including magnitude and variability of its period and amplitude. The period itself is affected by the magnitude of parameterized convective gravity wave momentum fluxes and interactive ozone (which also affects the QBO amplitude and variability), among other forcings. Although varying sea surface temperatures affect the parameterized momentum fluxes, neither aspect is responsible for the modeled variation in QBO period. Both the parameterized and resolved waves act to produce the respective easterly and westerly wind descent, although their effect is offset in altitude at each level. The modeled and observed QBO influences on tracers in the stratosphere, such as ozone, methane, and water vapor are also discussed. Due to the link between the gravity wave parameterization and the models' convection, and the dependence on the ozone field, the models may also be used to investigate how the QBO may vary with climate change.

middle atmosphere dynamics↗
DOE OSTI2022

A survey of pedestal magnetic fluctuations using gyrokinetics and a global reduced model for microtearing stability

This article presents a global reduced model for slab-like microtearing modes (MTMs) in the H-mode pedestal, which reproduces distinctive features of experimentally observed magnetic fluctuations, such as chirping and discrete frequency bands at noncontiguous mode numbers. Our model, importantly, includes the global variation of the diamagnetic frequencies, which is necessary to reproduce the experimental observations. The key insight underlying this model is that MTM instability is enabled by the alignment of a rational surface with the peak in the profile of the diamagnetic frequency. Conversely, MTMs are strongly stabilized for toroidal mode numbers for which these quantities are misaligned. This property explains the discrete fluctuation bands in several DIII-D and JET discharges, which we survey using our reduced model in conjunction with global gyrokinetic simulations. A fast yet accurate reduced model for MTMs enables rapid interpretation of magnetic fluctuation data from a wide range of experimental conditions to help assess the role of MTM in the pedestal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1993

A satellite-borne radar wind sensor (RAWS)

Modeling global atmospheric circulations and forecasting the weather would improve if worldwide information on winds aloft were available. Accurate prediction of weather is important to agriculture, shipping, air traffic, and many other fields. Global system models of climate are of great importance. Current global atmospheric models use pressure measurements and thermodynamic properties to calculate the effects of wind for use in Numerical Weather Prediction (NWP) models. Inputs to the NWP models are temperature, pressure and wind velocities at different heights. Clearly direct wind measurements could significantly improve the NWP model performance. The RAdar Wind Sounder (RAWS) program at the University of Kansas is a study of the feasibility and the trade-offs in the design of a space-based radar system to measure wind vectors. This can be done by measuring the Doppler shift of cloud and rain returns from three or more points and calculating the components of the wind vector. The RAWS study to date uses the candidate system selected after preliminary study of frequencies and sensitivities. Two frequencies chosen, 10 and 35 GHz, allow higher sensitivity for clouds and more penetration for rain. The past year was devoted to modeling the signal-to-noise ratio (SNR) achievable for the two frequencies. The determination of SNR versus cloud penetration depth used a cloud backscattering and attenuation model in the appropriate radar equation. Calculations assumed reasonable losses in reception and transmission, in addition to the atmospheric attenuation. We discovered that ice clouds provide a higher SNR than previously calculated, but some water clouds give lower SNRs than we calculated before. One of the primary issues in the SNR calculation was the choice of the drop size distribution. Although Xin used several distributions (e.g., log normal, Khrigian and Mazin), this year we used the Deirmendjian cloud model. SNR versus cloud penetration plots were generated to validate the candidate system. Rain, which appears in the cloud models at the lower altitudes, provides ample SNR, as do the higher clouds composed of ice particles. However, in some cloud situations we found the sensitivity for the clouds was marginal or inadequate. At 35 GHz, two of the cloud models characterized by 1 to 2 g/cu m of water content at altitudes extending from 150 to 1500 meters, produced a sufficient SNR. Other models, however, with water contents ranging from 0.5 to 4 g/cu m and altitudes up to 4000 meters, exhibit SNR of -3 to -23 dB, largely because of attenuation in the upper cloud layers. These results coupled with the lower SNR at 10 GHz, led to an investigation of alternate frequencies. The rain present beneath these clouds provides adequate SNR at 10 GHz, and in most cases, at GHz.

Moore, Richard K.↗
NASA NTRS1999

Global Magnetospheric Modeling of 3D Reconnection

A review of approaches to the global modeling of the terrestrial magnetosphere, how these approaches are utilized to interpret satellite data, and how these approaches have been successful at predicting magnetospheric phenomena will be presented. In addition, the importance of the ionospheric boundary and its effect on the globally topology of the magnetospheric magnetic field will be reviewed. In particular, numerical results that are rapidly changing our view of magnetospheric reconnection within the magnetospheric magnetic field will be discussed.

Spicer, Daniel S.↗
DOE OSTI2020

Characterization of organic aerosol across the global remote troposphere: a comparison of ATom measurements and global chemistry models

The spatial distribution and properties of submicron organic aerosol (OA) are among the key sources of uncertainty in our understanding of aerosol effects on climate. Uncertainties are particularly large over remote regions of the free troposphere and Southern Ocean, where very few data have been available and where OA predictions from AeroCom Phase II global models span 2 to 3 orders of magnitude, greatly exceeding the model spread over source regions. The (nearly) pole-to-pole vertical distribution of non-refractory aerosols was measured with an aerosol mass spectrometer onboard the NASA DC-8 aircraft as part of the Atmospheric Tomography (ATom) mission during the Northern Hemisphere summer (August 2016) and winter (February 2017). This study presents the first extensive characterization of OA mass concentrations and their level of oxidation in the remote atmosphere. OA and sulfate are the major contributors by mass to submicron aerosols in the remote troposphere, together with sea salt in the marine boundary layer. Sulfate was dominant in the lower stratosphere. OA concentrations have a strong seasonal and zonal variability, with the highest levels measured in the lower troposphere in the summer and over the regions influenced by biomass burning from Africa (up to 10 µg sm -3 ). Lower concentrations (~0.1–0.3 µg sm -3 ) are observed in the northern middle and high latitudes and very low concentrations (<0.1 µg sm -3 ) in the southern middle and high latitudes. The ATom dataset is used to evaluate predictions of eight current global chemistry models that implement a variety of commonly used representations of OA sources and chemistry, as well as of the AeroCom-II ensemble. The current model ensemble captures the average vertical and spatial distribution of measured OA concentrations, and the spread of the individual models remains within a factor of 5. These results are significantly improved over the AeroCom-II model ensemble, which shows large overestimations over these regions. However, some of the improved agreement with observations occurs for the wrong reasons, as models have the tendency to greatly overestimate the primary OA fraction and underestimate the secondary fraction. Measured OA in the remote free troposphere is highly oxygenated, with organic aerosol to organic carbon (OA/OC) ratios of ~2.2–2.8, and is 30 %–60 % more oxygenated than in current models, which can lead to significant errors in OA concentrations. The model–measurement comparisons presented here support the concept of a more dynamic OA system as proposed by Hodzic et al. (2016), with enhanced removal of primary OA and a stronger production of secondary OA in global models needed to provide better agreement with observations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

biogeochemistry↗
NASA NTRS1976

The global reference atmospheric model, mod 2 (with two scale perturbation model)

The Global Reference Atmospheric Model was improved to produce more realistic simulations of vertical profiles of atmospheric parameters. A revised two scale random perturbation model using perturbation magnitudes which are adjusted to conform to constraints imposed by the perfect gas law and the hydrostatic condition is described. The two scale perturbation model produces appropriately correlated (horizontally and vertically) small scale and large scale perturbations. These stochastically simulated perturbations are representative of the magnitudes and wavelengths of perturbations produced by tides and planetary scale waves (large scale) and turbulence and gravity waves (small scale). Other new features of the model are: (1) a second order geostrophic wind relation for use at low latitudes which does not "blow up" at low latitudes as the ordinary geostrophic relation does; and (2) revised quasi-biennial amplitudes and phases and revised stationary perturbations, based on data through 1972.

Justus, C. G.↗
NASA NTRS1987

Improvements in the perturbation simulations of the global reference atmospheric model

The Global Reference Atmospheric Model (GRAM) program includes the capability for simulating pseudo-random perturbations in density, temperature, pressure, or wind components along a simulated reentry trajectory or other path through the atmosphere. Some concerns were expressed by GRAM users, however, that the mean-square perturbation gradients may be too large for small values of the vertical separation Delta z. The present GRAM perturbation simulations, based on a one-step autoregressive model, yield a power spectrum versus wavenumber k which is proportional to k sup -2 at high wavenumbers. This feature also produces mean-square perturbation differences which are directly proportional to Delta z, and mean-square perturbation gradients which are inversely proportional to Delta z. Thus, root-mean-square gradients, (Delta f/Delta z) sub rms, increase with decreasing Delta a as Delta z sup -1/2. A simple modification to GRAM is suggested which overcomes this problem, i.e., which produce root-mean-square gradient that remain bound as Delta z approaches zero. Possible applications of more sophisticated simulation approaches, e.g., second order autoregressive models, or fractal model techniques, were also explored briefly but found to yield improvements which appear too small to justify their considerable added complexity for use in the GRAM programs.

Justus, C. G.↗
NASA NTRS2017

Venus Global Reference Atmospheric Model

Venus Global Reference Atmospheric Model (Venus-GRAM) is an engineering-level atmospheric model developed by MSFC that is widely used for diverse mission applications including: Systems design; Performance analysis; Operations planning for aerobraking, Entry, Descent and Landing, and aerocapture; Is not a forecast model; Outputs include density, temperature, pressure, wind components, and chemical composition; Provides dispersions of thermodynamic parameters, winds, and density; Optional trajectory and auxiliary profile input files Has been used in multiple studies and proposals including NASA Engineering and Safety Center (NESC) Autonomous Aerobraking and various Discovery proposals; Released in 2005; Available at: https://software.nasa.gov/software/MFS-32314-1.

Justh, Hilary L.↗
NASA NTRS2013

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

interference↗
NASA NTRS2017

The Substorm Cycle as Reproduced by Global MHD Models

Recently, Gordeev et al. (2015) suggested a method to test global MHD models against statistical empirical data. They showed that four community-available global MHD models supported by the Community Coordinated Modeling Center (CCMC) produce a reasonable agreement with reality for those key parameters (the magnetospheric size, magnetic field, and pressure) that are directly related to the large-scale equilibria in the outer magnetosphere. Based on the same set of simulation runs, here we investigate how the models reproduce the global loading-unloading cycle. We found that in terms of global magnetic flux transport, three examined CCMC models display systematically different response to idealized2 h north then 2 h south interplanetary magnetic field (IMF) Bz variation. The LFM model shows a depressed return convection and high loading rate during the growth phase as well as enhanced return convection and high unloading rate during the expansion phase, with the amount of loaded unloaded magnetotail flux and the growth phase duration being the closest to their observed empirical values during isolated substorms. Two other models exhibit drastically different behavior. In the BATS-R-US model the plasma sheet convection shows a smooth transition to the steady convection regime after the IMF southward turning. In the Open GGCM a weak plasma sheet convection has comparable intensities during both the growth phase and the following slow unloading phase. We also demonstrate potential technical problem in the publicly available simulations which is related to post processing interpolation and could affect the accuracy of magnetic field tracing and of other related procedures.

Gordeev, E.↗