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Abstract
Detailed information on the four-channel Airborne Chromatograph for Atmospheric Trace Species (ACATS-IV), used to measure long-lived atmospheric trace gases, is presented. Since ACATS-IV was last described in the literature, the temporal resolution of some measurements was tripled during 1997–99, chromatography was significantly changed, and data processing improved. ACATS-IV presently measures CCl3F [chlorofluorocarbon (CFC)-11], CCl2FCClF2 (CFC-113), CH3CCl3 (methyl chloroform), CCl4 (carbon tetrachloride), CH4 (methane), H2 (hydrogen), and CHCl3 (chloroform) every 140 s, and N2O (nitrous oxide), CCl2F2 (CFC-12), CBrClF2 (halon-1211), and SF6 (sulfur hexafluoride) every 70 s. An in-depth description of the instrument operation, standardization, calibration, and data processing is provided, along with a discussion of precision and uncertainties of ambient air measurements for several airborne missions.
Abstract
Detailed information on the four-channel Airborne Chromatograph for Atmospheric Trace Species (ACATS-IV), used to measure long-lived atmospheric trace gases, is presented. Since ACATS-IV was last described in the literature, the temporal resolution of some measurements was tripled during 1997–99, chromatography was significantly changed, and data processing improved. ACATS-IV presently measures CCl3F [chlorofluorocarbon (CFC)-11], CCl2FCClF2 (CFC-113), CH3CCl3 (methyl chloroform), CCl4 (carbon tetrachloride), CH4 (methane), H2 (hydrogen), and CHCl3 (chloroform) every 140 s, and N2O (nitrous oxide), CCl2F2 (CFC-12), CBrClF2 (halon-1211), and SF6 (sulfur hexafluoride) every 70 s. An in-depth description of the instrument operation, standardization, calibration, and data processing is provided, along with a discussion of precision and uncertainties of ambient air measurements for several airborne missions.
Accurate and reliable predictions and an understanding of future changes in the stratosphere are major aspects of the subject of climate change. Simulating the interaction between chemistry and climate is of particular importance, because continued increases in greenhouse gases and a slow decrease in halogen loading are expected. These both influence the abundance of stratospheric ozone. In recent years a number of coupled chemistry–climate models (CCMs) with different levels of complexity have been developed. They produce a wide range of results concerning the timing and extent of ozone-layer recovery. Interest in reducing this range has created a need to address how the main dynamical, chemical, and physical processes that determine the long-term behavior of ozone are represented in the models and to validate these model processes through comparisons with observations and other models. A set of core validation processes structured around four major topics (transport, dynamics, radiation, and stratospheric chemistry and microphysics) has been developed. Each process is associated with one or more model diagnostics and with relevant datasets that can be used for validation. This approach provides a coherent framework for validating CCMs and can be used as a basis for future assessments. Similar efforts may benefit other modeling communities with a focus on earth science research as their models increase in complexity.
Accurate and reliable predictions and an understanding of future changes in the stratosphere are major aspects of the subject of climate change. Simulating the interaction between chemistry and climate is of particular importance, because continued increases in greenhouse gases and a slow decrease in halogen loading are expected. These both influence the abundance of stratospheric ozone. In recent years a number of coupled chemistry–climate models (CCMs) with different levels of complexity have been developed. They produce a wide range of results concerning the timing and extent of ozone-layer recovery. Interest in reducing this range has created a need to address how the main dynamical, chemical, and physical processes that determine the long-term behavior of ozone are represented in the models and to validate these model processes through comparisons with observations and other models. A set of core validation processes structured around four major topics (transport, dynamics, radiation, and stratospheric chemistry and microphysics) has been developed. Each process is associated with one or more model diagnostics and with relevant datasets that can be used for validation. This approach provides a coherent framework for validating CCMs and can be used as a basis for future assessments. Similar efforts may benefit other modeling communities with a focus on earth science research as their models increase in complexity.
Abstract
The February–March 2014 deployment of the National Aeronautics and Space Administration (NASA) Airborne Tropical Tropopause Experiment (ATTREX) provided unique in situ measurements in the western Pacific tropical tropopause layer (TTL). Six flights were conducted from Guam with the long-range, high-altitude, unmanned Global Hawk aircraft. The ATTREX Global Hawk payload provided measurements of water vapor, meteorological conditions, cloud properties, tracer and chemical radical concentrations, and radiative fluxes. The campaign was partially coincident with the Convective Transport of Active Species in the Tropics (CONTRAST) and the Coordinated Airborne Studies in the Tropics (CAST) airborne campaigns based in Guam using lower-altitude aircraft (see companion articles in this issue). The ATTREX dataset is being used for investigations of TTL cloud, transport, dynamical, and chemical processes, as well as for evaluation and improvement of global-model representations of TTL processes. The ATTREX data are publicly available online (at https://espoarchive.nasa.gov/).
Abstract
The February–March 2014 deployment of the National Aeronautics and Space Administration (NASA) Airborne Tropical Tropopause Experiment (ATTREX) provided unique in situ measurements in the western Pacific tropical tropopause layer (TTL). Six flights were conducted from Guam with the long-range, high-altitude, unmanned Global Hawk aircraft. The ATTREX Global Hawk payload provided measurements of water vapor, meteorological conditions, cloud properties, tracer and chemical radical concentrations, and radiative fluxes. The campaign was partially coincident with the Convective Transport of Active Species in the Tropics (CONTRAST) and the Coordinated Airborne Studies in the Tropics (CAST) airborne campaigns based in Guam using lower-altitude aircraft (see companion articles in this issue). The ATTREX dataset is being used for investigations of TTL cloud, transport, dynamical, and chemical processes, as well as for evaluation and improvement of global-model representations of TTL processes. The ATTREX data are publicly available online (at https://espoarchive.nasa.gov/).
Abstract
This article provides an overview of the NASA Atmospheric Tomography (ATom) mission and a summary of selected scientific findings to date. ATom was an airborne measurements and modeling campaign aimed at characterizing the composition and chemistry of the troposphere over the most remote regions of the Pacific, Southern, Atlantic, and Arctic Oceans, and examining the impact of anthropogenic and natural emissions on a global scale. These remote regions dominate global chemical reactivity and are exceptionally important for global air quality and climate. ATom data provide the in situ measurements needed to understand the range of chemical species and their reactions, and to test satellite remote sensing observations and global models over large regions of the remote atmosphere. Lack of data in these regions, particularly over the oceans, has limited our understanding of how atmospheric composition is changing in response to shifting anthropogenic emissions and physical climate change. ATom was designed as a global-scale tomographic sampling mission with extensive geographic and seasonal coverage, tropospheric vertical profiling, and detailed speciation of reactive compounds and pollution tracers. ATom flew the NASA DC-8 research aircraft over four seasons to collect a comprehensive suite of measurements of gases, aerosols, and radical species from the remote troposphere and lower stratosphere on four global circuits from 2016 to 2018. Flights maintained near-continuous vertical profiling of 0.15–13-km altitudes on long meridional transects of the Pacific and Atlantic Ocean basins. Analysis and modeling of ATom data have led to the significant early findings highlighted here.
Abstract
This article provides an overview of the NASA Atmospheric Tomography (ATom) mission and a summary of selected scientific findings to date. ATom was an airborne measurements and modeling campaign aimed at characterizing the composition and chemistry of the troposphere over the most remote regions of the Pacific, Southern, Atlantic, and Arctic Oceans, and examining the impact of anthropogenic and natural emissions on a global scale. These remote regions dominate global chemical reactivity and are exceptionally important for global air quality and climate. ATom data provide the in situ measurements needed to understand the range of chemical species and their reactions, and to test satellite remote sensing observations and global models over large regions of the remote atmosphere. Lack of data in these regions, particularly over the oceans, has limited our understanding of how atmospheric composition is changing in response to shifting anthropogenic emissions and physical climate change. ATom was designed as a global-scale tomographic sampling mission with extensive geographic and seasonal coverage, tropospheric vertical profiling, and detailed speciation of reactive compounds and pollution tracers. ATom flew the NASA DC-8 research aircraft over four seasons to collect a comprehensive suite of measurements of gases, aerosols, and radical species from the remote troposphere and lower stratosphere on four global circuits from 2016 to 2018. Flights maintained near-continuous vertical profiling of 0.15–13-km altitudes on long meridional transects of the Pacific and Atlantic Ocean basins. Analysis and modeling of ATom data have led to the significant early findings highlighted here.