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- Author or Editor: Britton B. Stephens x
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Abstract
A commercially available differential fuel-cell analyzer has been adapted to make field-based ppm-level measurements of atmospheric O2 variations. With the implementation of rapid calibrations and active pressure and flow control, the analysis system described here has a 1σ precision of ±2.5 per meg (≈0.5 ppm) for a 2-min measurement. Allowing for system stabilization after switching inlet lines, a 6-min measurement with a precision of ±1.4 per meg (≈0.3 ppm) every 20 min is obtained. The elimination of biases in any atmospheric O2 measurement depends critically on careful gas-handling procedures, and after screening for known sources of bias a comparability of ±10 per meg (≈2 ppm) with the present setup is estimated. In comparison to existing techniques, the relatively small size, low cost, fast response, motion insensitivity, and ease of implementation of the fuel-cell analyzer make it particularly useful for a wide range of unattended field applications. This system has been used to measure atmospheric O2 concentrations at the WLEF tall-tower research site in northern Wisconsin semicontinuously from June 2000 to December 2003. These measurements represent the first extended O2 record in and above a forest ecosystem, and are being used to investigate global carbon budgeting, plant physiology, continental boundary layer mixing and synoptic transport, and potential means of industrial emission verification. In this paper, the measurement technique is described in detail and several weeks of data are presented to illustrate its performance.
Abstract
A commercially available differential fuel-cell analyzer has been adapted to make field-based ppm-level measurements of atmospheric O2 variations. With the implementation of rapid calibrations and active pressure and flow control, the analysis system described here has a 1σ precision of ±2.5 per meg (≈0.5 ppm) for a 2-min measurement. Allowing for system stabilization after switching inlet lines, a 6-min measurement with a precision of ±1.4 per meg (≈0.3 ppm) every 20 min is obtained. The elimination of biases in any atmospheric O2 measurement depends critically on careful gas-handling procedures, and after screening for known sources of bias a comparability of ±10 per meg (≈2 ppm) with the present setup is estimated. In comparison to existing techniques, the relatively small size, low cost, fast response, motion insensitivity, and ease of implementation of the fuel-cell analyzer make it particularly useful for a wide range of unattended field applications. This system has been used to measure atmospheric O2 concentrations at the WLEF tall-tower research site in northern Wisconsin semicontinuously from June 2000 to December 2003. These measurements represent the first extended O2 record in and above a forest ecosystem, and are being used to investigate global carbon budgeting, plant physiology, continental boundary layer mixing and synoptic transport, and potential means of industrial emission verification. In this paper, the measurement technique is described in detail and several weeks of data are presented to illustrate its performance.
Abstract
Cloud phase and relative humidity (RH) distributions at −67° to 0°C over the Southern Ocean during austral summer are compared between in situ airborne observations and global climate simulations. A scale-aware comparison is conducted using horizontally averaged observations from 0.1 to 50 km. Cloud phase frequencies, RH distributions, and liquid mass fraction are found to be less affected by horizontal resolutions than liquid and ice water content (LWC and IWC, respectively), liquid and ice number concentrations (Ncliq and Ncice, respectively), and ice supersaturation (ISS) frequency. At −10° to 0°C, observations show 27%–34% and 17%–37% of liquid and mixed phases, while simulations show 60%–70% and 3%–4%, respectively. Simulations overestimate (underestimate) LWC and Ncliq in liquid (mixed) phase, overestimate Ncice in mixed phase, underestimate IWC in ice and mixed phases, and underestimate (overestimate) liquid mass fraction below (above) −5°C, indicating that observational constraints are needed for different cloud phases. RH frequently occurs at liquid saturation in liquid and mixed phases for all datasets, yet the observed RH in ice phase can deviate from liquid saturation by up to 20%–40% at −20° to 0°C, indicating that the model assumption of liquid saturation for coexisting ice and liquid is inaccurate for low liquid mass fractions (<0.1). Simulations lack RH variability for partial cloud fractions (0.1–0.9) and underestimate (overestimate) ISS frequency for cloud fraction <0.1 (≥0.6), implying that improving RH subgrid-scale parameterizations may be a viable path to account for small-scale processes that affect RH and cloud phase heterogeneities. Two sets of simulations (nudged and free-running) show very similar results (except for ISS frequency) regardless of sample sizes, corroborating the statistical robustness of the model–observation comparisons.
Abstract
Cloud phase and relative humidity (RH) distributions at −67° to 0°C over the Southern Ocean during austral summer are compared between in situ airborne observations and global climate simulations. A scale-aware comparison is conducted using horizontally averaged observations from 0.1 to 50 km. Cloud phase frequencies, RH distributions, and liquid mass fraction are found to be less affected by horizontal resolutions than liquid and ice water content (LWC and IWC, respectively), liquid and ice number concentrations (Ncliq and Ncice, respectively), and ice supersaturation (ISS) frequency. At −10° to 0°C, observations show 27%–34% and 17%–37% of liquid and mixed phases, while simulations show 60%–70% and 3%–4%, respectively. Simulations overestimate (underestimate) LWC and Ncliq in liquid (mixed) phase, overestimate Ncice in mixed phase, underestimate IWC in ice and mixed phases, and underestimate (overestimate) liquid mass fraction below (above) −5°C, indicating that observational constraints are needed for different cloud phases. RH frequently occurs at liquid saturation in liquid and mixed phases for all datasets, yet the observed RH in ice phase can deviate from liquid saturation by up to 20%–40% at −20° to 0°C, indicating that the model assumption of liquid saturation for coexisting ice and liquid is inaccurate for low liquid mass fractions (<0.1). Simulations lack RH variability for partial cloud fractions (0.1–0.9) and underestimate (overestimate) ISS frequency for cloud fraction <0.1 (≥0.6), implying that improving RH subgrid-scale parameterizations may be a viable path to account for small-scale processes that affect RH and cloud phase heterogeneities. Two sets of simulations (nudged and free-running) show very similar results (except for ISS frequency) regardless of sample sizes, corroborating the statistical robustness of the model–observation comparisons.
Abstract
The construction and deployment of a portable trace-gas measurement system (TGaMS) is described. The air-collection system (dubbed HYDRA) collects air samples from 18 different locations and was connected to either one or two LI-COR LI-7000 gas analyzers to measure CO2. An in situ “field calibration” method, that uses four calibration gases with an uncertainty on the order of ±0.1 μmol mol−1 relative to the WMO CO2 mole fraction scale, revealed CO2 output from the LI-7000 had a slightly nonlinear relationship relative to the CO2 concentration of the calibration gases. The sensitivity of the field-calibrated CO2 to different forms of the field-calibration equation is investigated. To evaluate TGaMS performance, CO2 from collocated inlets, portable gas cylinders, and nearby independent CO2 instruments are compared. Results are as follows: 1) CO2 measurements from HYDRA multiple inlets are feasible with a reproducibility of ±0.4 μmol mol−1 (based on the standard deviation of the CO2 difference between collocated inlets when HYDRA was operating with two LI-7000s); 2) CO2 differences among the various field-calibration equations were on the order of ±0.3 μmol mol−1; and 3) comparison of midday hourly CO2 measurements at 30 m AGL between TGaMS and an independent high-accuracy CO2 measurement system (within 300 m of TGaMS) had a median difference and standard deviation of 0.04 ± 0.81 μmol mol−1 over two months.
Abstract
The construction and deployment of a portable trace-gas measurement system (TGaMS) is described. The air-collection system (dubbed HYDRA) collects air samples from 18 different locations and was connected to either one or two LI-COR LI-7000 gas analyzers to measure CO2. An in situ “field calibration” method, that uses four calibration gases with an uncertainty on the order of ±0.1 μmol mol−1 relative to the WMO CO2 mole fraction scale, revealed CO2 output from the LI-7000 had a slightly nonlinear relationship relative to the CO2 concentration of the calibration gases. The sensitivity of the field-calibrated CO2 to different forms of the field-calibration equation is investigated. To evaluate TGaMS performance, CO2 from collocated inlets, portable gas cylinders, and nearby independent CO2 instruments are compared. Results are as follows: 1) CO2 measurements from HYDRA multiple inlets are feasible with a reproducibility of ±0.4 μmol mol−1 (based on the standard deviation of the CO2 difference between collocated inlets when HYDRA was operating with two LI-7000s); 2) CO2 differences among the various field-calibration equations were on the order of ±0.3 μmol mol−1; and 3) comparison of midday hourly CO2 measurements at 30 m AGL between TGaMS and an independent high-accuracy CO2 measurement system (within 300 m of TGaMS) had a median difference and standard deviation of 0.04 ± 0.81 μmol mol−1 over two months.
Abstract
Changes in atmospheric CO2 variability during the twenty-first century may provide insight about ecosystem responses to climate change and have implications for the design of carbon monitoring programs. This paper describes changes in the three-dimensional structure of atmospheric CO2 for several representative concentration pathways (RCPs 4.5 and 8.5) using the Community Earth System Model–Biogeochemistry (CESM1-BGC). CO2 simulated for the historical period was first compared to surface, aircraft, and column observations. In a second step, the evolution of spatial and temporal gradients during the twenty-first century was examined. The mean annual cycle in atmospheric CO2 was underestimated for the historical period throughout the Northern Hemisphere, suggesting that the growing season net flux in the Community Land Model (the land component of CESM) was too weak. Consistent with weak summer drawdown in Northern Hemisphere high latitudes, simulated CO2 showed correspondingly weak north–south and vertical gradients during the summer. In the simulations of the twenty-first century, CESM predicted increases in the mean annual cycle of atmospheric CO2 and larger horizontal gradients. Not only did the mean north–south gradient increase due to fossil fuel emissions, but east–west contrasts in CO2 also strengthened because of changing patterns in fossil fuel emissions and terrestrial carbon exchange. In the RCP8.5 simulation, where CO2 increased to 1150 ppm by 2100, the CESM predicted increases in interannual variability in the Northern Hemisphere midlatitudes of up to 60% relative to present variability for time series filtered with a 2–10-yr bandpass. Such an increase in variability may impact detection of changing surface fluxes from atmospheric observations.
Abstract
Changes in atmospheric CO2 variability during the twenty-first century may provide insight about ecosystem responses to climate change and have implications for the design of carbon monitoring programs. This paper describes changes in the three-dimensional structure of atmospheric CO2 for several representative concentration pathways (RCPs 4.5 and 8.5) using the Community Earth System Model–Biogeochemistry (CESM1-BGC). CO2 simulated for the historical period was first compared to surface, aircraft, and column observations. In a second step, the evolution of spatial and temporal gradients during the twenty-first century was examined. The mean annual cycle in atmospheric CO2 was underestimated for the historical period throughout the Northern Hemisphere, suggesting that the growing season net flux in the Community Land Model (the land component of CESM) was too weak. Consistent with weak summer drawdown in Northern Hemisphere high latitudes, simulated CO2 showed correspondingly weak north–south and vertical gradients during the summer. In the simulations of the twenty-first century, CESM predicted increases in the mean annual cycle of atmospheric CO2 and larger horizontal gradients. Not only did the mean north–south gradient increase due to fossil fuel emissions, but east–west contrasts in CO2 also strengthened because of changing patterns in fossil fuel emissions and terrestrial carbon exchange. In the RCP8.5 simulation, where CO2 increased to 1150 ppm by 2100, the CESM predicted increases in interannual variability in the Northern Hemisphere midlatitudes of up to 60% relative to present variability for time series filtered with a 2–10-yr bandpass. Such an increase in variability may impact detection of changing surface fluxes from atmospheric observations.
A significant fraction of Earth consists of mountainous terrain. However, the question of how to monitor the surface–atmosphere carbon exchange over complex terrain has not been fully explored. This article reports on studies by a team of investigators from U.S. universities and research institutes who carried out a multiscale and multidisciplinary field and modeling investigation of the CO2 exchange between ecosystems and the atmosphere and of CO2 transport over complex mountainous terrain in the Rocky Mountain region of Colorado. The goals of the field campaign, which included ground and airborne in situ and remote-sensing measurements, were to characterize unique features of the local CO2 exchange and to find effective methods to measure regional ecosystem–atmosphere CO2 exchange over complex terrain. The modeling effort included atmospheric and ecological numerical modeling and data assimilation to investigate regional CO2 transport and biological processes involved in ecosystem–atmosphere carbon exchange. In this report, we document our approaches, demonstrate some preliminary results, and discuss principal patterns and conclusions concerning ecosystem–atmosphere carbon exchange over complex terrain and its relation to past studies that have considered these processes over much simpler terrain.
A significant fraction of Earth consists of mountainous terrain. However, the question of how to monitor the surface–atmosphere carbon exchange over complex terrain has not been fully explored. This article reports on studies by a team of investigators from U.S. universities and research institutes who carried out a multiscale and multidisciplinary field and modeling investigation of the CO2 exchange between ecosystems and the atmosphere and of CO2 transport over complex mountainous terrain in the Rocky Mountain region of Colorado. The goals of the field campaign, which included ground and airborne in situ and remote-sensing measurements, were to characterize unique features of the local CO2 exchange and to find effective methods to measure regional ecosystem–atmosphere CO2 exchange over complex terrain. The modeling effort included atmospheric and ecological numerical modeling and data assimilation to investigate regional CO2 transport and biological processes involved in ecosystem–atmosphere carbon exchange. In this report, we document our approaches, demonstrate some preliminary results, and discuss principal patterns and conclusions concerning ecosystem–atmosphere carbon exchange over complex terrain and its relation to past studies that have considered these processes over much simpler terrain.
Abstract
The Southern Ocean plays a critical role in the global climate system by mediating atmosphere–ocean partitioning of heat and carbon dioxide. However, Earth system models are demonstrably deficient in the Southern Ocean, leading to large uncertainties in future air–sea CO2 flux projections under climate warming and incomplete interpretations of natural variability on interannual to geologic time scales. Here, we describe a recent aircraft observational campaign, the O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) study, which collected measurements over the Southern Ocean during January and February 2016. The primary research objective of the ORCAS campaign was to improve observational constraints on the seasonal exchange of atmospheric carbon dioxide and oxygen with the Southern Ocean. The campaign also included measurements of anthropogenic and marine biogenic reactive gases; high-resolution, hyperspectral ocean color imaging of the ocean surface; and microphysical data relevant for understanding and modeling cloud processes. In each of these components of the ORCAS project, the campaign has significantly expanded the amount of observational data available for this remote region. Ongoing research based on these observations will contribute to advancing our understanding of this climatically important system across a range of topics including carbon cycling, atmospheric chemistry and transport, and cloud physics. This article presents an overview of the scientific and methodological aspects of the ORCAS project and highlights early findings.
Abstract
The Southern Ocean plays a critical role in the global climate system by mediating atmosphere–ocean partitioning of heat and carbon dioxide. However, Earth system models are demonstrably deficient in the Southern Ocean, leading to large uncertainties in future air–sea CO2 flux projections under climate warming and incomplete interpretations of natural variability on interannual to geologic time scales. Here, we describe a recent aircraft observational campaign, the O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) study, which collected measurements over the Southern Ocean during January and February 2016. The primary research objective of the ORCAS campaign was to improve observational constraints on the seasonal exchange of atmospheric carbon dioxide and oxygen with the Southern Ocean. The campaign also included measurements of anthropogenic and marine biogenic reactive gases; high-resolution, hyperspectral ocean color imaging of the ocean surface; and microphysical data relevant for understanding and modeling cloud processes. In each of these components of the ORCAS project, the campaign has significantly expanded the amount of observational data available for this remote region. Ongoing research based on these observations will contribute to advancing our understanding of this climatically important system across a range of topics including carbon cycling, atmospheric chemistry and transport, and cloud physics. This article presents an overview of the scientific and methodological aspects of the ORCAS project and highlights early findings.
Abstract
Wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical–meteorological interactions that drive high-pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in western U.S. basins. Approximately 120 people participated, representing 50 institutions and five countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological–chemical linkages outlined here, nor to validate complex processes within coupled atmosphere–chemistry models.
Abstract
Wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical–meteorological interactions that drive high-pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in western U.S. basins. Approximately 120 people participated, representing 50 institutions and five countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological–chemical linkages outlined here, nor to validate complex processes within coupled atmosphere–chemistry models.
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.
