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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models

Results from the fully and biogeochemically coupled simulations in which CO 2 increases at a rate of 1 % yr –1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO 2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm –1 ) and ocean (0.79 ± 0.07 PgC ppm –1 ), while the carbon–climate feedback over land (–45.1 ± 50.6 PgC °C –1 ) is about 3 times larger than over ocean (–17.2 ± 5.0 PgC °C –1 ). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 °C EgC –1 and is similar to that found in CMIP5 models (1.63 ± 0.48 °C EgC –1 ) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model

Abstract. Lakes in the Arctic are important reservoirs of heat with much lower albedo in summer and greater absorption of solar radiation than surrounding tundra vegetation. In the winter, lakes that do not freeze to their bed have a mean annual bed temperature >0 ∘C in an otherwise frozen landscape. Under climate warming scenarios, we expect Arctic lakes to accelerate thawing of underlying permafrost due to warming water temperatures in the summer and winter. Previous studies of Arctic lakes have focused on ice cover and thickness, the ice decay process, catchment hydrology, lake water balance, and eddy covariance measurements, but little work has been done in the Arctic to model lake heat balance. We applied the LAKE 2.0 model to simulate water temperatures in three Arctic lakes in northern Alaska over several years and tested the sensitivity of the model to several perturbations of input meteorological variables (precipitation, shortwave radiation, and air temperature) and several model parameters (water vertical resolution, sediment vertical resolution, depth of soil column, and temporal resolution). The LAKE 2.0 model is a one-dimensional model that explicitly solves vertical profiles of water state variables on a grid. We used a combination of meteorological data from local and remote weather stations, as well as data derived from remote sensing, to drive the model. We validated modeled water temperatures with data of observed lake water temperatures at several depths over several years for each lake. Our validation of the LAKE 2.0 model is a necessary step toward modeling changes in Arctic lake ice regimes, lake heat balance, and thermal interactions with permafrost. The sensitivity analysis shows us that lake water temperature is not highly sensitive to small changes in air temperature or precipitation, while changes in shortwave radiation and large changes in precipitation produced larger effects. Snow depth and lake ice strongly affect water temperatures during the frozen season, which dominates the annual thermal regime of Arctic lakes. These findings suggest that reductions in lake ice thickness and duration could lead to more heat storage by lakes and enhanced permafrost degradation.

Clark, Jason A. (ORCID:0000000248105261)↗
DOE OSTI2022

Modeling the topographic influence on aboveground biomass using a coupled model of hillslope hydrology and ecosystem dynamics

Abstract. Topographic heterogeneity and lateral subsurface flow at the hillslope scale of ≤1 km may have outsized impacts on tropical forest through their impacts on water available to plants under water-stressed conditions. However, vegetation dynamics and finer-scale hydrologic processes are not concurrently represented in Earth system models. In this study, we integrate the Energy Exascale Earth System Model (E3SM) land model (ELM) that includes the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), with a three-dimensional hydrology model (ParFlow) to explicitly resolve hillslope topography and subsurface flow and perform numerical experiments to understand how hillslope-scale hydrologic processes modulate vegetation along water availability gradients at Barro Colorado Island (BCI), Panama. Our simulations show that groundwater table depth (WTD) can play a large role in governing aboveground biomass (AGB) when drought-induced tree mortality is triggered by hydraulic failure. Analyzing the simulations using random forest (RF) models, we find that the domain-wide simulated AGB and WTD can be well predicted by static topographic attributes, including surface elevation, slope, and convexity, and adding soil moisture or groundwater table depth as predictors further improves the RF models. Different model representations of mortality due to hydraulic failure can change the dominant topographic driver for the simulated AGB. Contrary to the simulations, the observed AGB in the well-drained 50 ha forest census plot within BCI cannot be well predicted by the RF models using topographic attributes and observed soil moisture as predictors, suggesting other factors such as nutrient status may have a larger influence on the observed AGB. The new coupled model may be useful for understanding the diverse impact of local heterogeneity by isolating the water availability and nutrient availability from the other external and internal factors in ecosystem modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1)

Abstract. The Community Atmosphere Model (CAM6.1), the atmospheric component of the Community Earth System Model (CESM; version 2.1), simulates the life cycle (emission, transport, and deposition) of mineral dust and its interactions with physio-chemical components to quantify the impacts of dust on climate and the Earth system. The accuracy of such quantifications relies on how well dust-related processes are represented in the model. Here we update the parameterizations for the dust module, including those on the dust emission scheme, the aerosol dry deposition scheme, the size distribution of transported dust, and the treatment of dust particle shape. Multiple simulations were undertaken to evaluate the model performance against diverse observations, and to understand how each update alters the modeled dust cycle and the simulated dust direct radiative effect. The model–observation comparisons suggest that substantially improved model representations of the dust cycle are achieved primarily through the new more physically-based dust emission scheme. In comparison, the other modifications induced small changes to the modeled dust cycle and model–observation comparisons, except the size distribution of dust in the coarse mode, which can be even more influential than that of replacing the dust emission scheme. We highlight which changes introduced here are important for which regions, shedding light on further dust model developments required for more accurately estimating interactions between dust and climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model

Wildfires have shown increasing trends in both frequency and severity across the contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth system models (ESMs). Alternatively, fire models based on machine learning (ML), which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ELM2.1-XGBFire1.0) that integrates an eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran–C–Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001–2019, the ELM2.1-XGBFire1.0 outperforms process-based fire models in terms of spatial distribution and seasonal variations. The ELM2.1-XGBFire1.0 has proven to be a new tool for studying vegetation–fire interactions and, more importantly, enables seamless exploration of climate–fire feedback, working as an active component of E3SM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗
NASA NTRS1991

Model reduction by trimming for a class of semi-Markov reliability models and the corresponding error bound

Semi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. A model reduction technique called trimming is presented that can be applied to a popular class of systems. Automatic model generation programs were written to help the reliability analyst produce models of complex systems. This method, trimming, is easy to implement and the error bound easy to compute. Hence, the method lends itself to inclusion in an automatic model generator.

White, Allan L.↗
NASA NTRS1991

An analytically linearized helicopter model with improved modeling accuracy

An analytically linearized model for helicopter flight response including rotor blade dynamics and dynamic inflow, that was recently developed, was studied with the objective of increasing the understanding, the ease of use, and the accuracy of the model. The mathematical model is described along with a description of the UH-60A Black Hawk helicopter and flight test used to validate the model. To aid in utilization of the model for sensitivity analysis, a new, faster, and more efficient implementation of the model was developed. It is shown that several errors in the mathematical modeling of the system caused a reduction in accuracy. These errors in rotor force resolution, trim force and moment calculation, and rotor inertia terms were corrected along with improvements to the programming style and documentation. Use of a trim input file to drive the model is examined. Trim file errors in blade twist, control input phase angle, coning and lag angles, main and tail rotor pitch, and uniform induced velocity, were corrected. Finally, through direct comparison of the original and corrected model responses to flight test data, the effect of the corrections on overall model output is shown.

Jensen, Patrick T.↗
NASA NTRS1992

Comparison of the USU ionospheric model with the UCL-Sheffield coupled thermospheric-ionospheric model

Several physical models of the high-latitude ionosphere have been developed that describe the time-dependent evolution of the E- and F-region plasma density. The models require a variety of inputs, including solar EUV fluxes, magnetospheric convection, auroral precipitation, and neutral atmosphere. Of specific relevance to this study is how the neutral atmosphere is incorporated into the ionospheric models. For the USU ionospheric model, the neutral atmosphere is the MSIS 1986 empirical model, while for the UCL-Sheffield coupled thermospheric-ionospheric model the neutral atmosphere is computed simultaneously with the ionosphere. Both models were run for similar solar and magnetospheric conditions (solar maximum, moderate geomagnetic activity, and winter solstice). Solar maximum conditions ensured a strong coupling between the ionosphere and thermosphere, which provided the possibility of a large ionospheric difference between the two physical models. This was further enhanced by choosing winter conditions so that the densities were not dominated by sunlight. The comparison of the two models indicated that both models predict the same morphological features with similar ionospheric densities, generally within about 30 percent.

Sojka, J. J.↗
NASA NTRS1997

Global Analysis, Interpretation and Modelling: An Earth Systems Modelling Program

The Goal of the GAIM is: To advance the study of the coupled dynamics of the Earth system using as tools both data and models; to develop a strategy for the rapid development, evaluation, and application of comprehensive prognostic models of the Global Biogeochemical Subsystem which could eventually be linked with models of the Physical-Climate Subsystem; to propose, promote, and facilitate experiments with existing models or by linking subcomponent models, especially those associated with IGBP Core Projects and with WCRP efforts. Such experiments would be focused upon resolving interface issues and questions associated with developing an understanding of the prognostic behavior of key processes; to clarify key scientific issues facing the development of Global Biogeochemical Models and the coupling of these models to General Circulation Models; to assist the Intergovernmental Panel on Climate Change (IPCC) process by conducting timely studies that focus upon elucidating important unresolved scientific issues associated with the changing biogeochemical cycles of the planet and upon the role of the biosphere in the physical-climate subsystem, particularly its role in the global hydrological cycle; and to advise the SC-IGBP on progress in developing comprehensive Global Biogeochemical Models and to maintain scientific liaison with the WCRP Steering Group on Global Climate Modelling.

Moore, Berrien, III↗
NASA NTRS2003

Cox Proportional Hazards Models for Modeling the Time to Onset of Decompression Sickness in Hypobaric Environments

In this paper we fit Cox proportional hazards models to a subset of data from the Hypobaric Decompression Sickness Databank. The data bank contains records on the time to decompression sickness (DCS) and venous gas emboli (VGE) for over 130,000 person-exposures to high altitude in chamber tests. The subset we use contains 1,321 records, with 87% censoring, and has the most recent experimental tests on DCS made available from Johnson Space Center. We build on previous analyses of this data set by considering more expanded models and more detailed model assessments specific to the Cox model. Our model - which is stratified on the quartiles of the final ambient pressure at altitude - includes the final ambient pressure at altitude as a nonlinear continuous predictor, the computed tissue partial pressure of nitrogen at altitude, and whether exercise was done at altitude. We conduct various assessments of our model, many of which are recently developed in the statistical literature, and conclude where the model needs improvement. We consider the addition of frailties to the stratified Cox model, but found that no significant gain was attained above a model that does not include frailties. Finally, we validate some of the models that we fit.

Thompson, Laura A.↗
NASA NTRS2006

Real-time Models at the Community Coordinated Modeling Center and their Capabilities

Real-time models at the Community Coordinated Modeling Center and their capabilities The Community Coordinated Modeling Center serves both scientific research and space weather operations communities through access to and evaluation of modern space environment models. Critical to both objectives is an unbiased assessment of model capabilities, which includes scientific validity, performance verification, and model robustness. While all of these assessments are relevant to operational customers, the latter plays a particularly important role. For this reason, as well as for testing model validity, CCMC established a set of fully automated real-time execution systems, which are based on models provided by the research community. This presentation will provide a summary of these activities, and a report on experiences and model validity. Finally, this presentation will invite feedback from CCMC customers regarding future directions of real time modeling at CCMC.

Hesse, Michael↗
NASA NTRS2006

The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

Kim, E.↗
NASA NTRS2010

Sorbent, Sublimation, and Icing Modeling Methods: Experimental Validation and Application to an Integrated MTSA Subassembly Thermal Model

This paper details the validation of modeling methods for the three core components of a Metabolic heat regenerated Temperature Swing Adsorption (MTSA) subassembly, developed for use in a Portable Life Support System (PLSS). The first core component in the subassembly is a sorbent bed, used to capture and reject metabolically produced carbon dioxide (CO2). The sorbent bed performance can be augmented with a temperature swing driven by a liquid CO2 (LCO2) sublimation heat exchanger (SHX) for cooling the sorbent bed, and a condensing, icing heat exchanger (CIHX) for warming the sorbent bed. As part of the overall MTSA effort, scaled design validation test articles for each of these three components have been independently tested in laboratory conditions. Previously described modeling methodologies developed for implementation in Thermal Desktop and SINDA/FLUINT are reviewed and updated, their application in test article models outlined, and the results of those model correlations relayed. Assessment of the applicability of each modeling methodology to the challenge of simulating the response of the test articles and their extensibility to a full scale integrated subassembly model is given. The independent verified and validated modeling methods are applied to the development of a MTSA subassembly prototype model and predictions of the subassembly performance are given. These models and modeling methodologies capture simulation of several challenging and novel physical phenomena in the Thermal Desktop and SINDA/FLUINT software suite. Novel methodologies include CO2 adsorption front tracking and associated thermal response in the sorbent bed, heat transfer associated with sublimation of entrained solid CO2 in the SHX, and water mass transfer in the form of ice as low as 210 K in the CIHX.

Bower, Chad↗
NASA NTRS2009

Validation of Community Models: 2. Development of a Baseline, Using the Wang-Sheeley-Arge Model

This paper is the second in a series providing independent validation of community models of the outer corona and inner heliosphere. Here I present a comprehensive validation of the Wang-Sheeley-Arge (WSA) model. These results will serve as a baseline against which to compare the next generation of comparable forecasting models. The WSA model is used by a number of agencies to predict Solar wind conditions at Earth up to 4 days into the future. Given its importance to both the research and forecasting communities, it is essential that its performance be measured systematically and independently. I offer just such an independent and systematic validation. I report skill scores for the model's predictions of wind speed and interplanetary magnetic field (IMF) polarity for a large set of Carrington rotations. The model was run in all its routinely used configurations. It ingests synoptic line of sight magnetograms. For this study I generated model results for monthly magnetograms from multiple observatories, spanning the Carrington rotation range from 1650 to 2074. I compare the influence of the different magnetogram sources and performance at quiet and active times. I also consider the ability of the WSA model to forecast both sharp transitions in wind speed from slow to fast wind and reversals in the polarity of the radial component of the IMF. These results will serve as a baseline against which to compare future versions of the model as well as the current and future generation of magnetohydrodynamic models under development for forecasting use.

MacNeice, Peter↗
NASA NTRS2010

Modeling Flight: The Role of Dynamically Scaled Free-Flight Models in Support of NASA's Aerospace Programs

The state of the art in aeronautical engineering has been continually accelerated by the development of advanced analysis and design tools. Used in the early design stages for aircraft and spacecraft, these methods have provided a fundamental understanding of physical phenomena and enabled designers to predict and analyze critical characteristics of new vehicles, including the capability to control or modify unsatisfactory behavior. For example, the relatively recent emergence and routine use of extremely powerful digital computer hardware and software has had a major impact on design capabilities and procedures. Sophisticated new airflow measurement and visualization systems permit the analyst to conduct micro- and macro-studies of properties within flow fields on and off the surfaces of models in advanced wind tunnels. Trade studies of the most efficient geometrical shapes for aircraft can be conducted with blazing speed within a broad scope of integrated technical disciplines, and the use of sophisticated piloted simulators in the vehicle development process permits the most important segment of operations the human pilot to make early assessments of the acceptability of the vehicle for its intended mission. Knowledgeable applications of these tools of the trade dramatically reduce risk and redesign, and increase the marketability and safety of new aerospace vehicles. Arguably, one of the more viable and valuable design tools since the advent of flight has been testing of subscale models. As used herein, the term "model" refers to a physical article used in experimental analyses of a larger full-scale vehicle. The reader is probably aware that many other forms of mathematical and computer-based models are also used in aerospace design; however, such topics are beyond the intended scope of this document. Model aircraft have always been a source of fascination, inspiration, and recreation for humans since the earliest days of flight. Within the scientific community, Leonardo da Vinci, George Cayley, and the Wright brothers are examples of early aviation pioneers who frequently used models during their scientific efforts to understand and develop flying machines. Progress in the technology associated with model testing in worldwide applications has firmly established model aircraft as a key element in new aerospace research and development programs. Models are now routinely used in many applications and roles, including aerodynamic data gathering in wind tunnel investigations for the analysis of full-scale aircraft designs, proof-of-concept demonstrators for radical aeronautical concepts, and problem-solving exercises for vehicles already in production. The most critical contributions of aerospace models are to provide confidence and risk reduction for new designs and to enhance the safety and efficiency of existing configurations.

Chambers, Joseph↗
NASA NTRS2011

Modeling of Coronal Mass Ejections that Caused Particularly Large Geomagnetic Storms Using ENLIL Heliosphere Cone Model

In our previous paper we reported the results of modeling of 14 selected well -observed strong halo coronal mass ejection (CME) events using the WSA -ENLIL cone model combination. Cone model input parameters were obtained from white light coronagraph images of the CME events using the analytical method developed by Xie et al. This work verified that coronagraph input gives reasonably good results for the CME arrival time prediction. In contrast to Taktakishvili et al., where we started the analysis by looking for clear CME signatures in the data and then proceeded to model the interplanetary consequences at 1 AU, in the present paper we start by generating a list of observed geomagnetic storm events and then work our way back to remote solar observations and carry out the corresponding CME modeling. The approach used in this study is addressing space weather forecasting and operational needs. We analyzed 36 particularly strong geomagnetic storms, then tried to associate them with particular CMEs using SOHO/LASCO catalogue, and finally modeled these CMEs using WSA-ENLIL cone model. Recently, Pulkkinen et al. developed a novel method for automatic determination of cone model parameters. We employed both analytical and automatic methods to determine cone model input parameters. We examined the CME arrival times and magnitude of impact at 1 AU for both techniques. The results of the simulations are compared with the ACE satellite observations. This comparison demonstrated that WSA -ENLIL model combination with coronagraph input gives reasonably good results for the CME arrival times for this set of 'geoeffective" CME events as well.

Taktakishvili, A.↗