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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

ARES Education and Public Outreach

The ARES Directorate education team is charged with translating the work of ARES scientists into content that can be used in formal and informal K-12 education settings and assisting with public outreach. This is accomplished through local efforts and national partnerships. Local efforts include partnerships with universities, school districts, museums, and the Lunar and Planetary Institute (LPI) to share the content and excitement of space science research. Sharing astromaterials and exploration science with the public is an essential part of the Directorate's work. As a small enclave of physical scientists at a NASA Center that otherwise emphasizes human space operations and engineering, the ARES staff is frequently called upon by the JSC Public Affairs and Education offices to provide presentations and interviews. Scientists and staff actively volunteer with the JSC Speaker's Bureau, Digital Learning Network, and National Engineers Week programs as well as at Space Center Houston activities and events. The education team also participates in many JSC educator and student workshops, including the Pre-Service Teacher Institute and the Texas Aerospace Scholars program, with workshop presentations, speakers, and printed materials.

Allen, Jaclyn↗
NASA NTRS2012

Plant Science in Reduced Gravity: Lessons Learned

The effect of gravity on the growth and development of plants has been the subject of scientific investigation for over a century. The results obtained in space to test specific hypotheses on gravitropism, gene expression, seed formation, or growth rate are affected by both the primary effect of the microgravity and secondary effects of the spaceflight environment. The secondary effects of the spaceflight environment include physical effects arising from physical changes, such as the absence of buoyancy driven convective mixing, altered behavior of liquids and gases, and the environmental conditions in the spacecraft atmosphere. Thus, the design of biological experiments (e.g. cells, plants, animals, etc.) conducted in microgravity must account for changes in the physical forces, as well as the environmental conditions, imposed by the specific spaceflight vehicle and experimental hardware. In addition, researchers must become familiar with other aspects of spaceflight experiments: payload integration with hardware developers, safety documentation and crew procedures, and the logistics of conducting flight and ground controls. This report reviews the physical and environmental factors that directly and indirectly affect the results of plant science experiments in microgravity and is intended to serve as a guide in the design and implementation plant experiments in space.

Stutte, Gary W.↗
NASA NTRS2016

Unique Results and Lessons Learned from the TSS Missions

In 1924, Irvin Langmuir and H. M. Mott-Smith published a theoretical model for the complex plasma sheath phenomenon in which they identified some very special cases which greatly simplified the sheath and allowed a closed solution to the problem. The most widely used application is for an electrostatic, or "Langmuir," probe in laboratory plasma. Although the Langmuir probe is physically simple (a biased wire) the theory describing its functional behavior and its current-voltage characteristic is extremely complex and, accordingly, a number of assumptions and approximations are used in the LMS model. These simplifications, correspondingly, place limits on the model's range of application. Adapting the LMS model to real-life conditions is the subject of numerous papers and dissertations. The Orbit-Motion Limited (OML) model that is widely used today is one of these adaptions that is a convenient means of calculating sheath effects. The OML equation for electron current collection by a positively biased body is simply: I is approximately equal to A x j(sub eo) x 2/√𝜋(phi)(exp ½) where A is the area of the body and phi is the electric potential on the body with respect to the plasma. Since the Langmuir probe is a simple biased wire immersed in plasma, it is particularly tempting to use the OML equation in calculating the characteristics of the long, highly biased wires of an Electric Sail in the solar wind plasma. However, in order to arrive at the OML equation, a number of additional simplifying assumptions and approximations (beyond those made by Langmuir-Mott-Smith) are necessary. The OML equation is a good approximation when all conditions are met, but it would appear that the Electric Sail problem lies outside of the limits of applicability.

Stone, Nobie H.↗
NASA NTRS2004

Flywheel Technology

Throughout the summer of 2004, I am working on a number of different projects. While located in the Space Power and Propulsion Test Engineering branch, my main area of study is flywheel technology. I have been exposed to flywheels, their components, and their uses in today's society. I have been able to experience numerous flywheels here in the flywheel lab at NASA Glenn. My first main project was to explore the attributes and physical characteristics of a flywheel. Our branch was constructing a flywheel demonstration to be presented at the public open house taking place in June. Our Flywheel Interactive Demo, or FIDO, represents a real life multi-flywheel system here at NASA. I was given the opportunity to learn about how these flywheels store energy and are able to position a satellite. With all of this new knowledge, I was able to create the posters that explained how our demonstration worked. I also composed a step-by-step process made up of four experiments that any visitor could follow and perform on FIDO. By stepping through these experiments, the individual learns how a flywheel works. They not only read the explanation of what is happening, but they are also able to see it happen. Creating these two posters not only taught me, but also helped teach the general public during the open house, how flywheel technology is a very important part of our future. Through my research, I have learned that flywheels are able to store massive amounts of energy. They can be described as an electro-mechanical battery that stores kinetic energy while rotating. The faster it rotates, the more energy it stores. Their lifetime is about triple that of an ordinary battery. Flywheels also have the ability to combine energy storage with attitude control all in a single system. Attitude control is the ability to position a satellite as required. FIDO helps us to understand the rotational force (torque) that is applied upon a turn-table or satellite during wheel acceleration/deceleration. My other main project that I have just begun is to create a flywheel presentation, brochure, and video all explaining the history, applications, early attempts, and working processes of modem flywheels. These items are all usefull tools for educating school children and even adults about flywheels. This task will require a large amount of research and skills in the use of multiple applications. My goal this summer is to learn the dynamics and uses of a flywheel in today s society, and then inform and encourage the public about flywheels. I am able to express my knowledge by creating some effective as well as attractive posters, presentations, brochures, videos, etc. that are able to explain how a flywheel works along with how our FIDO demonstration simulates a real flywheel. My goal is underway, and should be successfully reached with the help of my mentor, other coworkers, and fellow interns.

Ritchie, Lisa M.↗
NASA NTRS2007

NASA Langley's Approach to the Sandia's Structural Dynamics Challenge Problem

The objective of this challenge is to develop a data-based probabilistic model of uncertainty to predict the behavior of subsystems (payloads) by themselves and while coupled to a primary (target) system. Although this type of analysis is routinely performed and representative of issues faced in real-world system design and integration, there are still several key technical challenges that must be addressed when analyzing uncertain interconnected systems. For example, one key technical challenge is related to the fact that there is limited data on target configurations. Moreover, it is typical to have multiple data sets from experiments conducted at the subsystem level, but often samples sizes are not sufficient to compute high confidence statistics. In this challenge problem additional constraints are placed as ground rules for the participants. One such rule is that mathematical models of the subsystem are limited to linear approximations of the nonlinear physics of the problem at hand. Also, participants are constrained to use these models and the multiple data sets to make predictions about the target system response under completely different input conditions. Our approach involved initially the screening of several different methods. Three of the ones considered are presented herein. The first one is based on the transformation of the modal data to an orthogonal space where the mean and covariance of the data are matched by the model. The other two approaches worked solutions in physical space where the uncertain parameter set is made of masses, stiffnesses and damping coefficients; one matches confidence intervals of low order moments of the statistics via optimization while the second one uses a Kernel density estimation approach. The paper will touch on all the approaches, lessons learned, validation 1 metrics and their comparison, data quantity restriction, and assumptions/limitations of each approach. Keywords: Probabilistic modeling, model validation, uncertainty quantification, kernel density

Horta, Lucas G.↗
NASA NTRS2010

GOATS - Orbitology Component

The GOATS Orbitology Component software was developed to specifically address the concerns presented by orbit analysis tools that are often written as stand-alone applications. These applications do not easily interface with standard JPL first-principles analysis tools, and have a steep learning curve due to their complicated nature. This toolset is written as a series of MATLAB functions, allowing seamless integration into existing JPL optical systems engineering modeling and analysis modules. The functions are completely open, and allow for advanced users to delve into and modify the underlying physics being modeled. Additionally, this software module fills an analysis gap, allowing for quick, high-level mission analysis trades without the need for detailed and complicated orbit analysis using commercial stand-alone tools. This software consists of a series of MATLAB functions to provide for geometric orbit-related analysis. This includes propagation of orbits to varying levels of generalization. In the simplest case, geosynchronous orbits can be modeled by specifying a subset of three orbit elements. The next case is a circular orbit, which can be specified by a subset of four orbit elements. The most general case is an arbitrary elliptical orbit specified by all six orbit elements. These orbits are all solved geometrically, under the basic problem of an object in circular (or elliptical) orbit around a rotating spheroid. The orbit functions output time series ground tracks, which serve as the basis for more detailed orbit analysis. This software module also includes functions to track the positions of the Sun, Moon, and arbitrary celestial bodies specified by right ascension and declination. Also included are functions to calculate line-of-sight geometries to ground-based targets, angular rotations and decompositions, and other line-of-site calculations. The toolset allows for the rapid execution of orbit trade studies at the level of detail required for the early stage of mission concept development.

Haber, Benjamin M.↗
NASA NTRS1999

Countermeasures to Neurobehavioral Deficits from Cumulative Partial Sleep Deprivation During Space Flight

This project is concerned with identifying ways to prevent neurobehavioral and physical deterioration due to inadequate sleep in astronauts during long-duration manned space flight. The performance capability of astronauts during extended-duration space flight depends heavily on achieving recovery through adequate sleep. Even with appropriate circadian alignment, sleep loss can erode fundamental elements of human performance capability including vigilance, cognitive speed and accuracy, working memory, reaction time, and physiological alertness. Adequate sleep is essential during manned space flight not only to ensure high levels of safe and effective human performance, but also as a basic regulatory biology critical to healthy human functioning. There is now extensive objective evidence that astronaut sleep is frequently restricted in space flight to averages between 4 hr and 6.5 hr/day. Chronic sleep restriction during manned space flight can occur in response to endogenous disturbances of sleep (motion sickness, stress, circadian rhythms), environmental disruptions of sleep (noise, temperature, light), and curtailment of sleep due to the work demands and other activities that accompany extended space flight operations. The mechanism through which this risk emerges is the development of cumulative homeostatic pressure for sleep across consecutive days of inadequate sleep. Research has shown that the physiological sleepiness and performance deficits engendered by sleep debt can progressively worsen (i.e., accumulate) over consecutive days of sleep restriction, and that sleep limited to levels commonly experienced by astronauts (i.e., 4 - 6 hr per night) for as little as 1 week, can result in increased lapses of attention, degradation of response times, deficits in complex problem solving, reduced learning, mood disturbance, disruption of essential neuroendocrine, metabolic, and neuroimmune responses, and in some vulnerable persons, the emergence of uncontrolled sleep attacks. The prevention of cumulative performance deficits and neuroendocrine disruption from sleep restriction during extended duration space flight involves finding the most effective ways to obtain sleep in order to maintain the high-level cognitive and physical performance functions required for manned space flight. There is currently a critical deficiency in knowledge of the effects of how variations in sleep duration and timing relate to the most efficient return of performance per unit time invested in sleep during long-duration missions, and how the nature of sleep physiology (i.e., sleep stages, sleep electroencephalographic [EEG] power spectral analyses) change as a function of sleep restriction and performance degradation. The primary aim of this project is to meet these critical deficiencies through utilization of a response surface experimental paradigm, testing in a dose-response manner, varying combinations of sleep duration and timing, for the purpose of establishing how to most effectively limit the cumulative adverse effects on human performance and physiology of chronic sleep restriction in space operations.

Dinges, David F.↗
NASA NTRS2019

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗
NASA NTRS2000

Air, Ocean and Climate Monitoring Enhancing Undergraduate Training in the Physical, Environmental and Computer Sciences

Faculty in the Department of Physical, Environmental and Computer Sciences strongly believe in the concept that undergraduate research and research-related activities must be integrated into the fabric of our undergraduate Science and Technology curricula. High level skills, such as problem solving, reasoning, collaboration and the ability to engage in research, are learned for advanced study in graduate school or for competing for well paying positions in the scientific community. One goal of our academic programs is to have a pipeline of research activities from high school to four year college, to graduate school, based on the GISS Institute on Climate and Planets model.

Hope, W. W.↗
NASA NTRSDate not supplied

ISS Payload Operations Training During the COVID-19 Pandemic: Impacts and Solutions

Introduction: The onset and the protracted duration of the COVID-19 pandemic brought a dramatic and rapid transformation to almost every aspect of humanity in 2020. The world’s space agencies and their missions were not immune to the unpredictable and wide-sweeping changes. One discipline principally affected was mission operations and the various groups supporting that critical function. Mission support teams, especially for complex and crewed missions like the International Space Station (ISS) were forced to rapidly rethink how and where control center staff performed their vital work. Operations training – an essential element to mission ops, had unique hurdles to overcome. Operations training is responsible for preparing astronaut crews for their scientific missions, providing recurring proficiency and currency material to flight controllers, as well as ensuring new team members are ready to join their colleagues on console. Every element of training was impacted by COVID restrictions. From orientation and introductory classes for new controllers, training for scientists and payload developers, to simulations and advanced lessons, critical On the Job Training (OJT) and final evaluations; all aspects faced new challenges. Operations trainers at NASA’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama, were forced to rethink, retool, and become more efficient with trainees and training resources in order to continue supporting payload operations on the ISS. Impacts and Barriers to Operations Training: The pandemic started in the United States in early March 2020. Immediately, NASA mandated that the support for ISS real-time operations was critical. As a result, physical access to the ISS Payload Operations Center was restricted to only those people supporting console operations. Thus, use of on-site NASA facilities and any trainer to trainee face-to-face interaction was not authorized. Trainers and trainees had to quickly shift to 100% remote learning. In the short term, this was not a problem since NASA had already prepared Information Technology (IT) resources that facilitated remote access to mission resources like classes, documents and teleconferences. However, instructors quickly discovered the classes that they were accustomed to delivering in a large classroom environment did not translate well to remote teaching. The lack of non-verbal communication with the class became a major barrier to instruction. Another significant hurdle to operations training was the mandate that all simulations could only be held remotely. The logistics of planning and executing even small simulations proved to be challenging, almost impossible, due to IT technology and public internet limitations. With simulations essentially stopped, as well as the restrictions on most OJT training, trainees were essentially stopped in their advancement towards certification. An additional barrier that had to be overcome was the formal documentation of the curriculum objectives. Even though NASA had been deliberately transitioning to electronic documents for years, some organizations were still relying on “pen and ink” documents to formalize training completion. The logistics of implementing secure and controlled e-signature documents in a standardized, NASA approved format had to be addressed. Lesson Learned and Efficiencies: Once the various limitations were identified, ISS trainers at MSFC discussed, proposed, and prioritized new options and techniques. Transitioning to all electronic learning materials and certifications was a relevantly easy fix. Teaching courses to large and diverse groups took additional shifts in the NASA training paradigm. Likewise, methods and procedures for preparing astronauts for their missions were forced to be revised. Simulation supervisors and their teams were also forced to find more efficient techniques to provide realistic training experience. Communication and approvals from management was essential. In every case, the ISS payload operations instructors found novel and efficient solutions to all functions listed above. This paper will discuss the factors and solutions payloads operations trainers found to keep scientific research on the ISS flying forward to mission success.

ISS Operations↗
NASA NTRSDate not supplied

LON 94101 Provides a Unique Record of C-Class Asteroid Regolith Diversity

LON 94101 and its pairing mate LON 94102 are two of the largest CM finds, with a collective mass of 3.8kg.Over the years we noticed that every section of these meteorites appeared significantly different. These stones are highly brecciated and display an unprecedented range of CM lithologies [1-3, and numerous other papers]. They thus record direct information regarding the physical and petrologic characteristics of the CM parent asteroid(s) at the greatest scale observable from meteorites. Still unanswered questions are what the typical clast size was for each lithology, and what the full range of CM textures in LON 94101 could be. We were also interested in learning whether there were xenoliths in these breccias, these being apparently unknown for CM chondrites. Detailed characterization of an especially large sample is required to address these issues. This abstract reports results of the initial characterization of one large sample of LON 94101.

Michael Zolensky↗
NASA NTRS2022

Design of Materials with Alchemite

Machine learning models that establish the relationships between materials processing and properties can enable inverse design of materials through active learning. Alchemite is a commercial software that can perform inverse materials design on sparse data. Here we evaluate Alchemite’s performance on a dataset of shape memory alloys and a dataset of heat exchangers compared to baseline random forest models. Alchemite had higher accuracy when making predictions on sparse data and was more accurate or nearly as accurate as random forests on complete datasets while also quantifying uncertainty. The software was also used to suggest processing steps and design parameters to optimize properties and performance; however, physical validation of the suggested design parameters was beyond the scope of this work. Several useful design insights were gained about the impact of the design parameters on properties and performance including the importance of dopant choice and amount for shape memory alloys and the importance of height and weight on the thermal resistance of heat exchangers.

Machine learning↗
NASA NTRS2000

ISS Fiber Optic Failure Investigation Root Cause Report

In August of 1999, Boeing Corporation (Boeing) engineers began investigating failures of optical fiber being used on International Space Station flight hardware. Catastrophic failures of the fiber were linked to a defect in the glass fiber. Following several meetings of Boeing and NASA engineers and managers, Boeing created and led an investigation team, which examined the reliability of the cable installed in the U.S. Lab. NASA Goddard Space Flight Center's Components Technologies and Radiation Effects Branch (GSFC) led a team investigating the root cause of the failures. Information was gathered from: regular telecons and other communications with the investigation team, investigative trips to the cable distributor's plant, the cable manufacturing plant and the fiber manufacturing plant (including a review of build records), destructive and non-destructive testing, and expertise supplied by scientists from Dupont, and Lucent-Bell Laboratories. Several theories were established early on which were not able to completely address the destructive physical analysis and experiential evidence. Lucent suggested hydrofluoric acid (HF) etching of the glass and successfully duplicated the "rocket engine" defect. Strength testing coupled with examination of the low strength break sites linked features in the polyimide coating with latent defect sites. The information provided below explains what was learned about the susceptibility of the pre-cabled fiber to failure when cabled as it was for Space Station and the nature of the latent defects.

Leidecker, Henning↗
NASA NTRS2009

What was Learned from Numerical Simulations of F-16XL (CAWAPI) at Flight Conditions

Nine groups participating in the CAWAPI project have contributed steady and unsteady viscous simulations of a full-scale, semi-span model of the F-16XL aircraft. Three different categories of flight Reynolds/Mach number combinations were computed and compared with flight-test measurements for the purpose of code validation and improved understanding of the flight physics. Steady-state simulations are done with several turbulence models of different complexity with no topology information required and which overcome Boussinesq-assumption problems in vortical flows. Detached-eddy simulation (DES) and its successor delayed detached-eddy simulation (DDES) have been used to compute the time accurate flow development. Common structured and unstructured grids as well as individually-adapted unstructured grids were used. Although discrepancies are observed in the comparisons, overall reasonable agreement is demonstrated for surface pressure distribution, local skin friction and boundary velocity profiles at subsonic speeds. The physical modeling, be it steady or unsteady flow, and the grid resolution both contribute to the discrepancies observed in the comparisons with flight data, but at this time it cannot be determined how much each part contributes to the whole. Overall it can be said that the technology readiness of CFD-simulation technology for the study of vehicle performance has matured since 2001 such that it can be used today with a reasonable level of confidence for complex configurations.

Rizzi, Arthur↗
NASA NTRS2010

SSME Electrical Harness and Cable Development and Evolution

The Space Shuttle Main Engine (SSME) electrical harness and cable system consists of the various interconnecting devices necessary for operation of complex rocket engine functions. Thirty seven harnesses incorporate unique connectors, backshell adapters, conductors, insulation, shielding, and physical barriers for a long maintenance-free life while providing the means to satisfy performance requirements and to mitigate adverse environmental influences. The objective of this paper is to provide a description of the SSME electrical harness and cable designs as well as the development history and lessons learned.

Abrams, Russ↗
NASA NTRS2013

Numerical Prediction of Dust

Covers the whole breadth of mineral dust research, from a scientific perspective Presents interdisciplinary work including results from field campaigns, satellite observations, laboratory studies, computer modelling and theoretical studies Explores the role of dust as a player and recorder of environmental change This volume presents state-of-the-art research about mineral dust, including results from field campaigns, satellite observations, laboratory studies, computer modelling and theoretical studies. Dust research is a new, dynamic and fast-growing area of science and due to its multiple roles in the Earth system, dust has become a fascinating topic for many scientific disciplines. Aspects of dust research covered in this book reach from timescales of minutes (as with dust devils, cloud processes, and radiation) to millennia (as with loess formation and oceanic sediments), making dust both a player and recorder of environmental change. The book is structured in four main parts that explore characteristics of dust, the global dust cycle, impacts of dust on the Earth system, and dust as a climate indicator. The chapters in these parts provide a comprehensive, detailed overview of this highly interdisciplinary subject. The contributions presented here cover dust from source to sink and describe all the processes dust particles undergo while travelling through the atmosphere. Chapters explore how dust is lifted and transported, how it affects radiation, clouds, regional circulations, precipitation and chemical processes in the atmosphere, and how it deteriorates air quality. The book explores how dust is removed from the atmosphere by gravitational settling, turbulence or precipitation, how iron contained in dust fertilizes terrestrial and marine ecosystems, and about the role that dust plays in human health. We learn how dust is observed, simulated using computer models and forecast. The book also details the role of dust deposits for climate reconstructions. Scientific observations and results are presented, along with numerous illustrations. This work has an interdisciplinary appeal and will engage scholars in geology, geography, chemistry, meteorology and physics, amongst others with an interest in the Earth system and environmental change.

dust↗
NASA NTRS2016

Brief History of Agricultural Systems Modeling

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the next generation models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.

agricultural systems↗
NASA NTRS2018

Southeast Atmosphere Studies: Learning from Model-Observation Syntheses

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

atmospheric chemistry↗