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The NASA Atmospheric Tomography (ATom) mission built a photochemical climatology of air parcels based on in situ measurements with the NASA DC-8 aircraft along objectively planned profiling transects through the middle of the Pacific and Atlantic oceans. In this paper we present and analyze a data set of 10s (2km) merged and gap-filled observations of the key reactive species driving the chemical budgets of O3 and CH4 (O3, CH4, CO, H2O, HCHO, H2O2, CH3OOH, C2H6, higher alkanes, alkenes, aromatics, NOx, HNO3, HNO4, peroxyacetyl nitrate, and other organic nitrates), consisting of 146494 distinct air parcels from ATom deployments 1 through 4. Six models calculated the O3 and CH4 photochemical tendencies from this modeling data stream for ATom 1. We find that 80%-90% of the total reactivity lies in the top 50% of the parcels and 25%-35% in the top 10%, supporting previous model-only studies that tropospheric chemistry is driven by a fraction of all the air. Surprisingly, the probability densities of species and reactivities averaged on a model scale (100 km) differ only slightly from the 2km ATom 10s data, indicating that much of the heterogeneity in tropospheric chemistry can be captured with current global chemistry models. Comparing the ATom reactivities over the tropical oceans with climatological statistics from six global chemistry models, we find generally good agreement with the reactivity rates for O3 and CH4. Models distinctly underestimate O3 production below 2km relative to the mid-troposphere, and this can be traced to lower NOx levels than observed. Attaching photochemical reactivities to measurements of chemical species allows for a richer, yet more constrained-to-what-matters, set of metrics for model evaluation. This paper presents a corrected version of the paper published under the same authors and title (sans "corrected") as 10.5194/acp-21-13729-2021.

Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic-boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic-boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19% of the monthly observations), snow diffusion (3%) and eddy covariance (78%) techniques. The largest number of observations were collected during the climatological summer (June-August; 32%), and fewer observations were available for autumn (September-October; 25%), winter (December-February; 18%), and spring (March-May; 25%). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, 10.3334/ORNLDAAC/1934). Copyright:

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season.

The NASA Atmospheric Tomography (ATom) mission built a photochemical climatology of air parcels based on in situ measurements with the NASA DC-8 aircraft along objectively planned profiling transects through the middle of the Pacific and Atlantic oceans. In this paper we present and analyze a data set of 10s (2km) merged and gap-filled observations of the key reactive species driving the chemical budgets of O3 and CH4 (O3, CH4, CO, H2O, HCHO, H2O2, CH3OOH, C2H6, higher alkanes, alkenes, aromatics, NOx, HNO3, HNO4, peroxyacetyl nitrate, other organic nitrates), consisting of 146494 distinct air parcels from ATom deployments 1 through 4. Six models calculated the O3 and CH4 photochemical tendencies from this modeling data stream for ATom 1. We find that 80%-90% of the total reactivity lies in the top 50% of the parcels and 25%-35% in the top 10%, supporting previous model-only studies that tropospheric chemistry is driven by a fraction of all the air. In other words, accurate simulation of the least reactive 50% of the troposphere is unimportant for global budgets. Surprisingly, the probability densities of species and reactivities averaged on a model scale (100km) differ only slightly from the 2km ATom data, indicating that much of the heterogeneity in tropospheric chemistry can be captured with current global chemistry models. Comparing the ATom reactivities over the tropical oceans with climatological statistics from six global chemistry models, we find excellent agreement with the loss of O3 and CH4 but sharp disagreement with production of O3. The models sharply underestimate O3 production below 4km in both Pacific and Atlantic basins, and this can be traced to lower NOx levels than observed. Attaching photochemical reactivities to measurements of chemical species allows for a richer, yet more constrained-to-what-matters, set of metrics for model evaluation.

Recent warming in the Arctic, which has been amplified during the winter1-3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is highly uncertain and has not been well represented by ecosystem models or by empirically-based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1662 Tg C yr-1 from the permafrost region during the winter season (October through April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (-1032 Tg C yr-1). Extending model predictions to warmer conditions in 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario-Representative Concentration Pathway (RCP) 4.5-and 41% under business-as-usual emissions scenario-RCP 8.5. Our results provide a new baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions.

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]

With rapid changes in climate and the seasonal amplitude of carbon dioxide (CO2) in the Arctic, it is critical that we detect and quantify the underlying processes controlling the changing amplitude of CO2 to better predict carbon cycle feedbacks in the Arctic climate system. We use satellite and airborne observations of atmospheric CO2 with climatically forced CO2 flux simulations to assess the detectability of Alaskan carbon cycle signals as future warming evolves. We find that current satellite remote sensing technologies can detect changing uptake accurately during the growing season but lack sufficient cold season coverage and near-surface sensitivity to constrain annual carbon balance changes at regional scale. Airborne strategies that target regular vertical profile measurements within continental interiors are more sensitive to regional flux deeper into the cold season but currently lack sufficient spatial coverage throughout the entire cold season. Thus, the current CO2 observing network is unlikely to detect potentially large CO2 sources associated with deep permafrost thaw and cold season respiration expected over the next 50 y. Although continuity of current observations is vital, strategies and technologies focused on cold season measurements (active remote sensing, aircraft, and tall towers) and systematic sampling of vertical profiles across continental interiors over the full annual cycle are required to detect the onset of carbon release from thawing permafrost.

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 quasi-biennial 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]

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]

Landscapes are often assumed to be homogeneous when interpreting eddy covariance fluxes, which can lead to biases when gap-filling and scaling-up observations to determine regional carbon budgets. Tundra ecosystems are heterogeneous at multiple scales, with variation in plant functional types, soil moisture, thaw depth, and microtopography, for example, influencing net ecosystem exchange (NEE) of carbon dioxide (CO2) and methane (CH4) fluxes. With warming temperatures, Arctic ecosystems could change from a net sink to a net source of carbon to the atmosphere in some locations, but the carbon balance remains highly uncertain. In this study we report results from growing season NEE and CH4 fluxes from an eddy covariance tower in the Yukon-Kuskokwim Delta in Alaska. We used footprint models and Bayesian Markov Chain Monte Carlo (MCMC) methods to un-mix tower observations into constituent landcover fluxes based on high resolution landcover maps of the tower region. We compared three types of footprint models and used two landcover maps with varying complexity to determine the effects of these choices on derived ecosystem fluxes. We used artificially created gaps of withheld observations to compare gap-filling performance using our derived landcover-specific fluxes and traditional gap-filling methods that assume homogeneous landscapes. We also compared resulting regional carbon budgets when scaling-up observations using heterogeneous and homogeneous approaches. Traditional gap-filling methods performed worse at predicting artificially withheld gaps in NEE than those that accounted for heterogeneous landscapes, while there were only slight differences between footprint models and landcover maps. We identified and quantified hot spots of carbon fluxes in the landscape (e.g., late growing season emissions from wetlands and small ponds). We resolved distinct seasonality in tundra growing season NEE fluxes. Scaling while assuming a homogeneous landscape overestimated the growing season CO2 sink by a factor of two and underestimated CH4 emissions by a factor of two when compared to scaling with any method that accounts for landscape heterogeneity. We show how Bayesian MCMC, analytical footprint models, and high resolution landcover maps can be leveraged to derive detailed landcover carbon fluxes from eddy covariance timeseries. These results demonstrate the importance of landscape heterogeneity when scaling carbon emissions across the Arctic. [ABSTRACT FROM AUTHOR]