The atmospheric effects of stratospheric aircraft: A topical review

In the late 1960s the aircraft industry became interested in developing a fleet of supersonic transports (SSTs). Between 1972 and 1975, the Climatic Impact Assessment Program (CIAP) studied the possible environmental impact of SSTs. For environmental and economic reasons, the fleet of SSTs was not developed. The Upper Atmosphere Research Program (UARP) has recently undertaken the responsibility of directing scientific research needed to assess the atmospheric impact of supersonic transports. The UARP and the High-Speed Research Program asked Harold Johnston to review the current understanding of aircraft emissions and their effect on the stratosphere. Johnston and his colleagues have recently re-examined the SST problem using current models for stratospheric ozone chemistry. A unique view is given here of the current scientific issues and the lessons learned since the beginning of CIAP, and it links the current research program with the assessment process that began two years ago

Direct observations of the atmospheric processing of Asian mineral dust

The accumulation of secondary acids and ammonium on individual mineral dust particles during ACE-Asia has been measured with an online single-particle mass spectrometer, the ATOFMS. Changes in the amounts of sulphate, nitrate, and chloride mixed with dust particles correlate with air masses from different source regions. The uptake of secondary acids depended on the individual dust particle mineralogy; high amounts of nitrate accumulated on calcium-rich dust while high amounts of sulphate accumulated on aluminosilicate-rich dust. Oxidation of S(IV) to S(VI) by iron in the aluminosilicate dust is a possible explanation for this enrichment of sulphate, which has important consequences for the fertilization of remote oceans by soluble iron. This study shows the segregation of sulphate from nitrate and chloride in individual aged dust particles for the first time. A transport and aging timeline provides an explanation for the observed segregation. Our data suggests that sulphate became mixed with the dust first. This implies that the transport pathway is more important than the reaction kinetics in determining which species accumulate on mineral dust. Early in the study, dust particles in volcanically influenced air masses were mixed predominately with sulphate. Dust mixed with chloride then dominated over sulphate and nitrate when a major dust front reached the R. V. Ronald Brown. We hypothesize that the rapid increase in chloride on dust was due to mixing with HCl(g) released from acidified sea salt particles induced by heterogeneous reaction with volcanic SO₂(g), prior to the arrival of the dust front. The amount of ammonium mixed with dust correlated strongly with the total amount of secondary acid reaction products in the dust. Submicron dust and ammonium sulphate were internally mixed, contrary to frequent reports that they exist as external mixtures. The size distribution of the mixing state of dust with these secondary species validates previous mechanisms of the atmospheric processing of dust and generally agrees with simulated aerosol chemistry from the STEM-2K3 model. This series of novel results has important implications for improving the treatment of dust in global chemistry models and highlights a number of key processes that merit further investigation through laboratory and field studies

Using graphical and pictorial representations to teach introductory astronomy students about the detection of extrasolar planets via gravitational microlensing

The detection and study of extrasolar planets is an exciting and thriving field in modern astrophysics, and an increasingly popular topic in introductory astronomy courses. One detection method relies on searching for stars whose light has been gravitationally microlensed by an extrasolar planet. In order to facilitate instructors' abilities to bring this interesting mix of general relativity and extrasolar planet detection into the introductory astronomy classroom, we have developed a new Lecture-Tutorial, "Detecting Exoplanets with Gravitational Microlensing." In this paper, we describe how this new Lecture-Tutorial's representations of astrophysical phenomena, which we selected and created based on theoretically motivated considerations of their pedagogical affordances, are used to help introductory astronomy students develop more expert-like reasoning abilities.Comment: 10 pages, 10 figures, accepted for publication in the American Journal of Physic

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

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

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date

Direct observations of the atmospheric processing of Asian mineral dust

International audienceThe accumulation of secondary acids and ammonium on individual mineral dust particles during ACE-Asia has been measured with an online single-particle mass spectrometer, the ATOFMS. Changes in the amounts of sulphate, nitrate, and chloride mixed with dust particles correlate with air masses from different source regions. The uptake of secondary acids depended on the individual dust particle mineralogy; high amounts of nitrate accumulated on calcium-rich dust while high amounts of sulphate accumulated on aluminosilicate-rich dust. Oxidation of S(IV) to S(VI) by iron in the aluminosilicate dust is a possible explanation for this enrichment of sulphate, which has important consequences for the fertilization of remote oceans by soluble iron. This study shows the segregation of sulphate from nitrate and chloride in individual aged dust particles for the first time. A transport and aging timeline provides an explanation for the observed segregation. Our data suggests that sulphate became mixed with the dust first. This implies that the transport pathway is more important than the reaction kinetics in determining which species accumulate on mineral dust. Early in the study, dust particles in volcanically influenced air masses were mixed predominately with sulphate. Dust mixed with chloride then dominated over sulphate and nitrate when a major dust front reached the R. V. Ronald Brown. We hypothesize that the rapid increase in chloride on dust was due to mixing with HCl(g) released from acidified sea salt particles induced by heterogeneous reaction with volcanic SO2(g), prior to the arrival of the dust front. The amount of ammonium mixed with dust correlated strongly with the total amount of secondary acid reaction products in the dust. Submicron dust and ammonium sulphate were internally mixed, contrary to frequent reports that they exist as external mixtures. The size distribution of the mixing state of dust with these secondary species validates previous mechanisms of the atmospheric processing of dust and generally agrees with simulated aerosol chemistry from the STEM-2K3 model. This series of novel results has important implications for improving the treatment of dust in global chemistry models and highlights a number of key processes that merit further investigation through laboratory and field studies

Closure between aerosol particles and cloud condensation nuclei at Kaashidhoo Climate Observatory

Predicting the cloud condensation nuclei (CCN) supersaturation spectrum from aerosol properties is a fairly straightforward matter, as long as those properties are simple. During the Indian Ocean Experiment we measured CCN spectra, size-resolved aerosol chemical composition, and aerosol number distributions and attempted to reconcile them using a modified form of Köhler theory. We obtained general agreement between our measured and modeled CCN spectra. However, the agreement was not as good during a time period when organic carbon comprised a quarter of the total mass of the aerosol in the submicron size range. The modeled concentrations overpredict those actually measured during that time period. This suggests that some component, presumably organic material, can inhibit the uptake of water by the electrolytic fraction of the mass