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The analysis of observed atmospheric trace-gas mole fractions to infer surface sources and sinks of chemical species relies heavily on simulated atmospheric transport. The chemical transport models (CTMs) used in flux-inversion models are commonly configured to reproduce the atmospheric transport of a general circulation model (GCM) as closely as possible. CTMs generally have the dual advantages of computational efficiency and improved tracer conservation compared to their parent GCMs, but they usually simplify the representations of important processes. This is especially the case for high-frequency vertical motions associated with diffusion and convection. Using common-flux experiments, we quantify the importance of parameterized vertical processes for explaining systematic differences in tracer transport between two commonly used CTMs. We find that differences in modeled column-average CO2 are strongly correlated with the differences in the models' convection. The parameterization of diffusion is more important near the surface due to its role in representing planetary-boundary-layer (PBL) mixing. Accordingly, simulated near-surface in situ measurements are more strongly impacted by this process than are simulated total-column averages. Both diffusive and convective vertical mixing tend to ventilate the lower atmosphere, so near-surface measurements may only constrain the net vertical mixing and not the balance between these two processes. Remote-sensing-based retrievals of total-column CO2, with their increased sensitivity to convection, may provide important new constraints on parameterized vertical motions.

Accurate accounting of emissions and removals of CO2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries' carbon budgets. These estimates are based on “top-down” NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-averaged dry-air mole fraction (XCO2) retrievals (ACOS v10), in situ CO2 measurements or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with “bottom-up” estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015–2020) as both a global 1∘ × 1∘ gridded dataset and a country-level dataset and are available for download from the Committee on Earth Observation Satellites' (CEOS) website: https://doi.org/10.48588/npf6-sw92 (Byrne et al., 2022). Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29–4.58 Pg CO2 yr−1 (0.90–1.25 Pg C yr−1). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems.

We evaluate terrestrial net ecosystem-atmosphere exchange (NEE) of CO2 from nine global inversion systems that inferred fluxes from four CO2 observational sources. We use 98 flights in the central ...

The Orbiting Carbon Observatory 2 (OCO-2) satellite has been provided information to estimate carbon dioxide (CO2) fluxes at global and regional scales since 2014 through the combination of CO2 retrievals with top-down atmospheric inversion methods. Column average CO2 dry air mole fraction retrievals has been constantly improved. A bias correction has been applied in the OCO-2 version 9 retrievals compared to the previous OCO-2 version 7r improving data accuracy and coverage. We study an ensemble of ten atmospheric inversions all characterized by different transport models, data assimilation algorithm and prior fluxes using first OCO-2 v7 in 2015-2016 and then OCO-2 version 9 land observations for the longer period 2015- 2018. Inversions assimilating in situ (IS) measurements have been also used to provide a baseline against which to compare the satellite-driven results. The times series at different scales (going from global to regional scales) of the models emissions are analyzed and compared to each experiments using either OCO-2 or IS data. We then evaluate the inversion ensemble based on dataset from TCCON, aircraft, and in-situ observations, all independent from assimilated data. While we find a similar constraint of global total carbon emissions between the ensemble spread using IS and both OCO-2 retrievals, differences between the two retrieval versions appear over regional scales and particularly in tropical Africa. A difference in the carbon budget between v7 and v9 is found over this region which seems to show the impact of corrections applied in retrievals. However, the lack of data in the tropics limits our conclusions and the estimation of carbon emissions over tropical Africa require further analysis.

The ability of current global models to simulate the transport of CO2 by mid-latitude, synoptic-scale weather systems (i.e. CO2 weather) is important for inverse estimates of ...

International audience; We use 148 airborne vertical profiles of CO2 for frontal cases from the summer 2016 Atmospheric Carbon and Transport—America (ACT America) campaign to evaluate the skill of 10 global CO2 in situ inversion models from the version 7 Orbiting Carbon Observatory-2 (OCO 2) Model Intercomparison Project (MIP). Model errors (model posterior—observed CO2 dry air mole fractions) were categorized by region (Mid Atlantic, Midwest, and South), frontal sector (warm or cold), and transport model (predominantly Tracer Model 5 (TM5) and Goddard Earth Observing System—Chemistry [GEOS Chem]). All inversions assimilated the same CO2 observations. Overall, the median inversion profiles reproduce the general structures of the observations (enhanced/depleted low level CO2 in warm/cold sectors), but 1) they underestimate the magnitude of the warm/cold sector mole fraction difference, and 2) the spread among individual inversions can be quite large (>5 ppm). Uniquely in the Mid Atlantic, inversion biases segregated according to atmospheric transport model, where TM5 inversions biases were -3 to -4 ppm in warm sectors, while those of GEOS Chem were +2 to +3 ppm in cold sectors. The large spread among the mean posterior CO2 profiles is not explained by the different atmospheric transport models. These results show that the inversion systems themselves are the dominant cause of this spread, and that the aircraft campaign data are clearly able to identify these large biases. Future controlled experiments should identify which inversions best reproduce mid latitude CO2 mole fractions, and how inversion system components are linked to system performance.

Attention to emotional stimuli has been associated with psychological health among adults and youth. In this study, we examined 2 putative functional psychophysiological correlates of attention to emotional information in a community sample of 135 youth (Mage^12 years, 7 months; SDage^1 year, 1 month; 50% girls). After measuring resting respiratory sinus arrhythmia (RSA), participants completed a 1,500 ms emotional faces dot probe task with eye tracking. We examined pupil dilation during angry, sad, and happy trials and predicted that lower resting RSA and greater pupil dilation would be associated with relatively greater attention to negative stimuli. Results partially confirmed our hypothesis. Lower resting RSA was associated with relatively greater attention to sad faces. Lower resting RSA was also associated with relatively greater attention to angry faces when pupil dilation was lower. RSA may be an important functional correlate of attention that should be explored further in future research.Keywords: adolescents; attention bias; vagal tone; pupil dilation; respiratory sinus arrhythmia; heart rate variabilityAttention to emotional information has been associated with psychological health in both youth and adults. For example, biased attention toward sad stimuli has been associated with depression, whereas biased attention toward angry stimuli has been associated with anxiety (Mathews & MacLeod, 2005; Mogg & Bradley, 2005). Biased attentional patterns may be an important marker of future psychopathology (e.g., Joormann, Talbot, & Gotlib, 2007); thus, understanding them has important implications for the assessment, prevention, and treatment of psychopathology. One way to better understand these attentional patterns is to examine whether they are associated with functional physiological processes involved in emotion. Surprisingly, little research has been devoted to this topic, especially among youth. This study examines two possible psychophysiological correlates of attention to emotional information among youth: pupil dilation and respiratory sinus arrhythmia (RSA).RESEARCH ON ATTENTION TO EMOTIONAL STIMULI IN ADULTS AND YOUTHDifferent tasks have been used to evaluate possible attention biases, with the two most common being an emotional Stroop task and an attentional probe method (Mathews & MacLeod, 2005). Emotional Stroop tasks compare the response latency of naming the colors of emotionally valenced words compared to neutral ones. Biases are inferred when color naming takes longer on emotional words compared to neutral words. Attentional probe methods briefly present stimuli (typically emotional and neutral words) on a computer screen and then assess how rapidly participants can find a probe that replaces one of the stimuli. Individuals respond faster to a probe that is presented in an attended rather than unattended area of a display; thus, attention is inferred based on reaction time (RT; Mathews & MacLeod, 2005; Mogg & Bradley, 2005).ADULTSResearch examining clinically depressed or anxious adults has generated considerable evidence, suggesting that both of these disorders are associated with biased attention related to emotional information (Mathews & MacLeod, 2005; Mogg & Bradley, 2005). Specifically, depressive disorders have generally been associated with attention to sad stimuli, whereas anxiety disorders have been associated with a bias toward or away from threat or angry stimuli, depending on the amount of time the stimulus is presented (Mathews & MacLeod, 2005).Interestingly, the bias toward sad stimuli often seen with depressive disorders is only present when the stimulus is presented for a fairly long time (1,000 ms or longer; Mathews & MacLeod, 2005). In their review, Gotlib and Joormann (2010) concluded that although depressed individuals may not automatically orient their attention toward negative information, once this negative information has become the focus of their attention, they may have greater difficulty disengaging from it. …

This study analyzes seasonal and spatial patterns of column carbon dioxide (CO2) over North America, calculated from aircraft and tall tower measurements from the NOAA Global Greenhouse Gas Reference Network from 2004 to 2014. Consistent with expectations, gradients between the eight regions studied are larger below 2 km than above 5 km. The 11-year mean CO2 dry mole fraction (XCO2) in the column below ∼ 330 hPa ( ∼ 8 km above sea level) from NOAA's CO2 data assimilation model, CarbonTracker (CT2015), demonstrates good agreement with those calculated from calibrated measurements on aircraft and towers. Total column XCO2 was attained by combining modeled CO2 above 330 hPa from CT2015 with the measurements. We find large spatial gradients of total column XCO2 from June to August, with north and northeast regions having ∼ 3 ppm stronger summer drawdown (peak-to-valley amplitude in seasonal cycle) than the south and southwest regions. The long-term averaged spatial gradients of total column XCO2 across North America show a smooth pattern that mainly reflects the large-scale circulation. We have conducted a CarbonTracker experiment to investigate the impact of Eurasian long-range transport. The result suggests that the large summertime Eurasian boreal flux contributes about half of the north–south column XCO2 gradient across North America. Our results confirm that continental-scale total column XCO2 gradients simulated by CarbonTracker are realistic and can be used to evaluate the credibility of some spatial patterns from satellite retrievals, such as the long-term average of growing-season spatial patterns from satellite retrievals reported for Europe which show a larger spatial difference ( ∼ 6 ppm) and scattered hot spots.

The Orbiting Carbon Observatory-2 has been on orbit since 2014, and its global coverage holds the potential to reveal new information about the carbon cycle through the use of top-down atmospheric inversion methods combined with column average CO2 retrievals. We employ a large ensemble of atmospheric inversions utilizing different transport models, data assimilation techniques and prior flux distributions in order to quantify the satellite-informed fluxes from OCO-2 Version 7r land observations and their uncertainties at continental scales. Additionally, we use in situ measurements to provide a baseline against which to compare the satellite-constrained results. We find that within ensemble spread, in situ observations and satellite retrievals constrain a similar global total carbon sink of 3.7 ± 0.5 PgC, and 1.5 ± 0.6 PgC per year for global land, for the 2015–2016 annual mean. This agreement breaks down on smaller regions, and we discuss the differences between the experiments. Of particular interest is the difference between the different assimilation constraints in the tropics, with the largest differences occurring in tropical Africa, which could be an indication of the global perturbation from the 2015–2016 El Niño. Evaluation of posterior concentrations using TCCON and aircraft observations gives some limited insight into the quality of the different assimilation constraints, but the lack of such data in the tropics inhibits our ability to make strong conclusions there.

Despite its importance to the climate system, the ocean meridional heat transport is still poorly quantified. We identify a strong link between the northern hemisphere deficit in atmospheric potential oxygen (APO = O $$_2$$ + 1.1 $$\times$$ CO $$_2$$ ) and the asymmetry in meridional heat transport between northern and southern hemispheres. The recent aircraft observations from the HIPPO campaign reveal a northern APO deficit in the tropospheric column of $$-$$ 10.4 $$\pm$$ 1.0 per meg, double the value at the surface and more representative of large-scale air–sea fluxes. The global northward ocean heat transport asymmetry necessary to explain the observed APO deficit is about 0.7–1.1 PW, which corresponds to the upper range of estimates from hydrographic sections and atmospheric reanalyses.

We show that transport differences between two commonly used global chemical transport models, GEOS‐Chem and TM5, lead to systematic space‐time differences in modeled distributions of carbon dioxide and sulfur hexafluoride. The distribution of differences suggests inconsistencies between the transport simulated by the models, most likely due to the representation of vertical motion. We further demonstrate that these transport differences result in systematic differences in surface CO2 flux estimated by a collection of global atmospheric inverse models using TM5 and GEOS‐Chem and constrained by in situ and satellite observations. While the impact on inferred surface fluxes is most easily illustrated in the magnitude of the seasonal cycle of surface CO2 exchange, it is the annual carbon budgets that are particularly relevant for carbon cycle science and policy. We show that inverse model flux estimates for large zonal bands can have systematic biases of up to 1.7 PgC/year due to large‐scale transport uncertainty. These uncertainties will propagate directly into analysis of the annual meridional CO2 flux gradient between the tropics and northern midlatitudes, a key metric for understanding the location, and more importantly the processes, responsible for the annual global carbon sink. The research suggests that variability among transport models remains the largest source of uncertainty across global flux inversion systems and highlights the importance both of using model ensembles and of using independent constraints to evaluate simulated transport., Key Points There are systematic differences in transport between two commonly used chemical transport models, TM5 and GEOS‐ChemThese systematic differences lead to significant and meaningful posterior flux uncertainties in atmospheric CO2 flux inversions

To investigate the effect of additional CO2 observations in the Siberia region on the Asian and global surface CO2 flux analyses, two experiments using different observation dataset were performed. One experiment was conducted using a data set that includes additional observations of Siberian tower measurements (Japan-Russia Siberian Tall Tower Inland Observation Network: JR-STATION), and the other experiment was conducted using a data set without the above additional observations. The results show that the global balance of the sources and sinks of surface CO2 fluxes was maintained for both experiments with and without the additional observations. While the magnitude of the optimized surface CO2 flux uptake in Siberia decreased, the magnitude of the optimized surface CO2 flux uptake in the other regions (e.g., Europe) of the Northern Hemisphere (NH) increased for the experiment with the additional observations. This change was mostly caused by changes in the magnitudes of surface CO2 flux in June and July. The observation impact measured by uncertainty reduction and self-sensitivity tests shows that additional observations provide useful information on the estimated surface CO2 flux. It is expected that the Siberian observations play an important role in estimating surface CO2 flux in the NH in the future.

International audience; Terrestrial biosphere models (TBMs) play a key role in the detection and attribution of carbon cycle processes at local to global scales and in projections of the coupled carbon-climate system. TBM evaluation commonly involves direct comparison to eddy-covariance flux measurements. We use atmospheric CO2 mole fraction ([CO2]) measured in situ from aircraft and tower, in addition to flux-measurements from summer 2016 to evaluate the Carnegie-Ames-Stanford-Approach (CASA) TBM. WRF-Chem is used to simulate [CO2] using biogenic CO2 fluxes from a CASA parameter-based ensemble and CarbonTracker version 2017 (CT2017) in addition to transport and CO2 boundary condition ensembles. The resulting “super ensemble” of modeled [CO2] demonstrates that the biosphere introduces the majority of uncertainty to the simulations. Both aircraft and tower [CO2] data show that the CASA ensemble net ecosystem exchange (NEE) of CO2 is biased high (NEE too positive) and identify the maximum light use efficiency Emax a key parameter that drives the spread of the CASA ensemble in summer 2016. These findings are verified with flux-measurements. The direct comparison of the CASA flux ensemble with flux-measurements confirms missing sink processes in CASA. Separating the daytime and nighttime flux, we discover that the underestimated net uptake results from missing sink processes that result in overestimation of respiration. NEE biases are smaller in the CT2017 posterior biogenic fluxes, which assimilate observed [CO2]. Flux tower analyses reveal an unrealistic overestimation of nighttime respiration in CT2017 which we attribute to limited flexibility in the inversion strategy.