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Urban regions emit a large fraction of anthropogenic emissions of greenhouse gases (GHG) such as carbon dioxide (CO2) and methane (CH4) that contribute to modern-day climate change. As such, a growing number of urban policymakers and stakeholders are adopting emission reduction targets and implementing policies to reach those targets. Over the past two decades research teams have established urban GHG monitoring networks to determine how much, where, and why a particular city emits GHGs, and to track changes in emissions over time. Coordination among these efforts has been limited, restricting the scope of analyses and insights. Here we present a harmonized data set synthesizing urban GHG observations from cities with monitoring networks across North America that will facilitate cross-city analyses and address scientific questions that are difficult to address in isolation.

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 5 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. Accurate simulation of atmospheric circulation,particularly in the lower stratosphere, is challenging due to unresolvedwave–mean flow interactions and limited high-resolution observations for validation. Gravity-induced pressure gradients lead to a small butmeasurable separation of heavy and light gases by molecular diffusion in thestratosphere. Because the relative abundance of Ar to N2 is exclusivelycontrolled by physical transport, the argon-to-nitrogen ratio (Ar∕N2)provides an additional constraint on circulation and the age of air (AoA),i.e., the time elapsed since entry of an air parcel into the stratosphere. Here we use airborne measurements of N2O and Ar∕N2 from ninecampaigns with global coverage spanning 2008–2018 to calculate AoA and toquantify gravitational separation in the lowermost stratosphere. To thisend, we develop a new N2O–AoA relationship using a Markov chain Monte Carlo algorithm. We observe that gravitational separation increases systematically with increasing AoA for samples with AoA between 0 and 3 years. These observations are compared to a simulation of the TOMCAT/SLIMCAT 3-D chemical transport model, which has been updated to includegravitational fractionation of gases. We demonstrate that although AoA atold ages is slightly underestimated in the model, the relationship betweenAr∕N2 and AoA is robust and agrees with the observations. Thishighlights the potential of Ar∕N2 to become a new AoA tracer that is subject only to physical transport phenomena and can supplement the suite of available AoA indicators.

Abstract. Accurate simulation of atmospheric circulation, particularly in the lower stratosphere, is challenging due to unresolved wave-mean flow interactions and limited high-resolution observations for validation. Gravity-induced pressure gradients lead to a small but measurable separation of heavy and light gases by molecular diffusion in the stratosphere. Because the relative abundance of Ar to N2 is exclusively controlled by physical transport, the argon-to-nitrogen ratio (Ar/N2) provides an additional constraint on circulation and the age of air (AoA), i.e. the time elapsed since entry of an air parcel into the stratosphere. Here we use airborne measurements of N2O and Ar/N2 from nine campaigns with global coverage spanning 2008–2018 to calculate AoA and to quantify gravitational separation in the lowermost stratosphere. To this end, we develop a new N2O-AoA relationship using a Markov Chain Monte Carlo algorithm. We observe that gravitational separation increases systematically with increasing AoA for samples with AoA between 0 to 3 years. These observations are compared to a simulation of the TOMCAT/SLIMCAT 3-D chemical transport model, which has been updated to include gravitational fractionation of gases. We demonstrate that although AoA at old ages is slightly underestimated in the model, the relationship between Ar/N2 and AoA is robust and agrees with the observations. This highlights the potential of Ar/N2 to become a new AoA tracer that is subject only to physical transport phenomena and can supplement the suite of available AoA indicators.

The literature presents different views on how the stratosphere influences variability in surface nitrous oxide (N 2 O) and on whether that influence is outweighed by surface emission changes driven by the El Niño–Southern Oscillation (ENSO). These questions are investigated using a chemistry–climate model with a stratospheric N 2 O tracer; surface and aircraft-based N 2 O measurements; and indices for ENSO, polar lower stratospheric temperature (PLST), and the stratospheric quasi-biennial oscillation (QBO). The model simulates well-defined seasonal cycles in tropospheric N 2 O that are caused mainly by the seasonal descent of N 2 O-poor stratospheric air in polar regions with subsequent cross-tropopause transport and mixing. Similar seasonal cycles are identified in recently available N 2 O data from aircraft. A correlation analysis between the N 2 O atmospheric growth rate (AGR) anomaly in long-term surface monitoring data and the ENSO, PLST, and QBO indices reveals hemispheric differences. In the Northern Hemisphere, the surface N 2 O AGR is negatively correlated with winter (January–March) PLST. This correlation is consistent with an influence from the Brewer–Dobson circulation, which brings N 2 O-poor air from the middle and upper stratosphere into the lower stratosphere with associated warming due to diabatic descent. In the Southern Hemisphere, the N 2 O AGR is better correlated to QBO and ENSO indices. These different hemispheric influences on the N 2 O AGR are consistent with known atmospheric dynamics and the complex interaction of the QBO with the Brewer-Dobson circulation. More airborne surveys extending to the tropopause would help elucidate the stratospheric influence on tropospheric N 2 O, allowing for better understanding of surface sources. [ABSTRACT FROM AUTHOR]

The Total Carbon Column Observing Network (TCCON) measures column-average mole fractions of several greenhouse gases (GHGs), beginning in 2004, from over 30 current or past measurement sites around the world using solar absorption spectroscopy in the near-infrared (near-IR) region. TCCON GHG data have been used extensively for multiple purposes, including in studies of the carbon cycle and anthropogenic emissions, as well as to validate and improve observations from space-based sensors. Here, we describe an update to the retrieval algorithm used to process the TCCON near-IR solar spectra and to generate the associated data products. This version, called GGG2020, was initially released in April 2022. It includes updates and improvements to all steps of the retrieval, including but not limited to the conversion of the original interferograms into spectra, the spectroscopic information used in the column retrieval, post hoc air mass dependence correction, and scaling to align with the calibration scales of in situ GHG measurements. All TCCON data are available through https://tccondata.org/ (last access: 22 April 2024) and are hosted on CaltechDATA (https://data.caltech.edu/ , last access: 22 April 2024). Each TCCON site has a unique DOI for its data record. An archive of all the sites' data is also available with the DOI 10.14291/TCCON.GGG2020. The hosted files are updated approximately monthly, and TCCON sites are required to deliver data to the archive no later than 1 year after acquisition. Full details of data locations are provided in the "Code and data availability" section. [ABSTRACT FROM AUTHOR]

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.

We present improved estimates of air–sea CO2 exchange over three latitude bands of the Southern Ocean using atmospheric CO2 measurements from global airborne campaigns and an atmospheric 4-box inverse model based on a mass-indexed isentropic coordinate (Mθe). These flux estimates show two features not clearly resolved in previous estimates based on inverting surface CO2 measurements: a weak winter-time outgassing in the polar region and a sharp phase transition of the seasonal flux cycles between polar/subpolar and subtropical regions. The estimates suggest much stronger summer-time uptake in the polar/subpolar regions than estimates derived through neural-network interpolation of pCO2 data obtained with profiling floats but somewhat weaker uptake than a recent study by Long et al. [Science 374, 1275–1280 (2021)], who used the same airborne data and multiple atmospheric transport models (ATMs) to constrain surface fluxes. Our study also uses moist static energy (MSE) budgets from reanalyses to show that most ATMs tend to have excessive diabatic mixing (transport across moist isentrope, θe, or Mθe surfaces) at high southern latitudes in the austral summer, which leads to biases in estimates of air–sea CO2 exchange. Furthermore, we show that the MSE-based constraint is consistent with an independent constraint on atmospheric mixing based on combining airborne and surface CO2 observations. [ABSTRACT FROM AUTHOR]

We present a chemistry-climate model with a tagged stratospheric nitrous oxide (N2O) tracer that predicts distinct seasonal cycles in tropospheric N2O caused by descent of N2O-depleted stratospheric air in polar regions. We identify similar phenomena in recently available aircraft profiles from global campaigns and routine monitoring. Long-term atmospheric measurements from the National Oceanic Atmospheric Administration (NOAA) global surface monitoring network provide additional support for a significant impact on surface N2O originating from the stratosphere. In the northern hemisphere, the NOAA surface N2O atmospheric growth rate anomaly is negatively correlated with the previous winter's polar lower stratospheric temperature. This negative correlation is consistent with increased (decreased) transport in years with a strong weak) Brewer Dobson circulation of warm, N2O-depleted air from the middle and upper stratosphere into the lower stratosphere, with subsequent cross-tropopause transport of the N2O-depleted air into the troposphere. In the southern hemisphere, polar lower stratospheric temperature is correlated to monthly summertime anomalies in tropospheric N2O as it descends into its seasonal minimum, a result that is supported by aircraft data as well as the chemistry-climate model. However, the N2O atmospheric growth rate anomaly in the southern hemisphere is better correlated to the stratospheric quasibiennial oscillation (QBO) index, as well as the El Niño Southern Oscillation index, than to polar lower stratospheric temperature. These hemispheric differences in the factors influencing the N2O atmospheric growth rate are consistent with known atmospheric dynamics and the complex interaction of the QBO with the Brewer Dobson circulation. [ABSTRACT FROM AUTHOR]

Tropical lands play an important role in the global carbon cycle yet their contribution remains uncertain owing to sparse observations. Satellite observations of atmospheric carbon dioxide (CO2) have greatly increased spatial coverage over tropical regions, providing the potential for improved estimates of terrestrial fluxes. Despite this advancement, the spread among satellite‐based and in‐situ atmospheric CO2 flux inversions over northern tropical Africa (NTA), spanning 0–24°N, remains large. Satellite‐based estimates of an annual source of 0.8–1.45 PgC yr−1 challenge our understanding of tropical and global carbon cycling. Here, we compare posterior mole fractions from the suite of inversions participating in the Orbiting Carbon Observatory 2 (OCO‐2) Version 10 Model Intercomparison Project (v10 MIP) with independent in‐situ airborne observations made over the tropical Atlantic Ocean by the National Aeronautics and Space Administration (NASA) Atmospheric Tomography (ATom) mission during four seasons. We develop emergent constraints on tropical African CO2 fluxes using flux‐concentration relationships defined by the model suite. We find an annual flux of 0.14 ± 0.39 PgC yr−1 (mean and standard deviation) for NTA, 2016–2018. The satellite‐based flux bias suggests a potential positive concentration bias in OCO‐2 B10 and earlier version retrievals over land in NTA during the dry season. Nevertheless, the OCO‐2 observations provide improved flux estimates relative to the in situ observing network at other times of year, indicating stronger uptake in NTA during the wet season than the in‐situ inversion estimates. Plain Language Summary: Satellite carbon dioxide (CO2) observations over land imply a major revision to our understanding of the global carbon cycle linked to large emissions from northern tropical Africa (NTA) during the dry season, from October to May. We use aircraft observations made over the Atlantic Ocean in four seasons to evaluate flux models driven by a range of ground and satellite observations. Our results show that models using satellite observations over land overestimate annual emissions from NTA by approximately 1 PgC yr−1, concentrated in the dry season. At other times of year, satellite CO2 observations provide improved estimates of NTA exchange, with a stronger CO2 uptake during the wet season. Key Points: Emergent constraints derived from aircraft carbon dioxide (CO2) measurements and inversions estimate a near neutral northern tropical African CO2 budgetInversions using satellite observations overestimate annual emissions from northern tropical Africa (NTA) by approximately 1 PgC yr−1Satellite CO2 observations imply a strong sink during the wet season over NTA [ABSTRACT FROM AUTHOR]

The Total Carbon Column Observing Network (TCCON) measures column-average mole fractions of several greenhouse gases (GHGs) beginning in 2004 from over 30 current or past measurement sites around the world, using solar absorption spectroscopy in the near infrared region. TCCON GHG data have been used extensively for multiple purposes, including in studies of the carbon cycle and anthropogenic emissions as well as to validate and improve observations made from space based sensors. Here, we describe an update to the retrieval algorithm used to process the TCCON near IR solar spectra and the associated data product. This version, called GGG2020, was initially released in April 2022. It includes updates and improvements to all steps of the retrieval, including but not limited to: converting the original interferograms into spectra, the spectroscopic information used in the column retrieval, post hoc airmass dependence correction, and scaling to align with the calibration scales of in situ GHG measurements. All TCCON data are available through tccondata.org and hosted on CaltechDATA (data.caltech.edu). Each TCCON site has a unique DOI for its data record. An archive of all sites’ data is also available with the DOI 10.14291/TCCON.GGG2020 (Total Carbon Column Observing Network (TCCON) Team, 2022). The hosted files are updated approximately monthly, and TCCON sites are required to deliver data to the archive no later than one year after acquisition. Full details of data locations are provided in the data availability section. [ABSTRACT FROM AUTHOR]

Optimal estimation retrievals of trace gas total columns require prior vertical profiles of the gases retrieved to drive the forward model and ensure the retrieval problem is mathematically well-posed. For well-mixed gases, it is possible to derive accurate prior profiles using an algorithm that accounts for general patterns of atmospheric transport coupled with measured time series of the gases in questions. Here we describe the algorithm used to generate the prior profiles for GGG2020, a new version of the GGG retrieval that is used to analyze spectra from solar-viewing Fourier transform spectrometers, including the Total Carbon Column Observing Network (TCCON). A particular focus of this work is improving the description of CO2, CH4, N2O, HF, and CO in the stratosphere. We show that the revised priors agree well with independent in situ and space-based measurements and improve the total column retrievals. [ABSTRACT FROM AUTHOR]