54 research outputs found
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Heterogeneity and chemical reactivity of the remote troposphere defined by aircraft measurements
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 10 s (2 km) 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 146 494 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 (100 km) differ only slightly from the 2 km 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 4 km 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.
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Impact of stratospheric air and surface emissions on tropospheric nitrous oxide during ATom
We measured the global distribution of tropospheric N2O mixing ratios during the NASA airborne Atmospheric Tomography (ATom) mission. ATom measured concentrations of ∼ 300 gas species and aerosol properties in 647 vertical profiles spanning the Pacific, Atlantic, Arctic, and much of the Southern Ocean basins, nearly from pole to pole, over four seasons (2016–2018). We measured N2O concentrations at 1 Hz using a quantum cascade laser spectrometer (QCLS). We introduced a new spectral retrieval method to account for the pressure and temperature sensitivity of the instrument when deployed on aircraft. This retrieval strategy improved the precision of our ATom QCLS N2O measurements by a factor of three (based on the standard deviation of calibration measurements). Our measurements show that most of the variance of N2O mixing ratios in the troposphere is driven by the influence of N2O-depleted stratospheric air, especially at mid- and high latitudes. We observe the downward propagation of lower N2O mixing ratios (compared to surface stations) that tracks the influence of stratosphere–troposphere exchange through the tropospheric column down to the surface. The highest N2O mixing ratios occur close to the Equator, extending through the boundary layer and free troposphere. We observed influences from a complex and diverse mixture of N2O sources, with emission source types identified using the rich suite of chemical species measured on ATom and the geographical origin calculated using an atmospheric transport model. Although ATom flights were mostly over the oceans, the most prominent N2O enhancements were associated with anthropogenic emissions, including from industry (e.g., oil and gas), urban sources, and biomass burning, especially in the tropical Atlantic outflow from Africa. Enhanced N2O mixing ratios are mostly associated with pollution-related tracers arriving from the coastal area of Nigeria. Peaks of N2O are often associated with indicators of photochemical processing, suggesting possible unexpected source processes. In most cases, the results show how difficult it is to separate the mixture of different sources in the atmosphere, which may contribute to uncertainties in the N2O global budget. The extensive data set from ATom will help improve the understanding of N2O emission processes and their representation in global models.
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Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020)
Here we present a global and regionally resolved terrestrial net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010-2018: Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020). It is estimated using the NASA Carbon Monitoring System Flux (CMS-Flux) top-down flux inversion system that assimilates column CO2 observations from the Greenhouse Gases Observing Satellite (GOSAT) and NASA\u27s Observing Carbon Observatory 2 (OCO-2). The regional monthly fluxes are readily accessible as tabular files, and the gridded fluxes are available in NetCDF format. The fluxes and their uncertainties are evaluated by extensively comparing the posterior CO2 mole fractions with CO2 observations from aircraft and the NOAA marine boundary layer reference sites. We describe the characteristics of the dataset as the global total, regional climatological mean, and regional annual fluxes and seasonal cycles. We find that the global total fluxes of the dataset agree with atmospheric CO2 growth observed by the surface-observation network within uncertainty. Averaged between 2010 and 2018, the tropical regions range from close to neutral in tropical South America to a net source in Africa; these contrast with the extra-tropics, which are a net sink of 2.5±0.3 Gt C/year. The regional satellite-constrained NBE estimates provide a unique perspective for understanding the terrestrial biosphere carbon dynamics and monitoring changes in regional contributions to the changes of atmospheric CO2 growth rate. The gridded and regional aggregated dataset can be accessed at http://doi.org/10.25966/4v02-c391 (Liu et al., 2020).
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Evaluating consistency between total column CO2 retrievals from OCO-2 and the in situ network over North America: implications for carbon flux estimation
The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.
Feedbacks between the climate system and the carbon cycle represent a key source of uncertainty in model projections of Earth's climate, in part due to our inability to directly measure large-scale biosphere–atmosphere carbon fluxes. In situ measurements of the CO2 mole fraction from surface flasks, towers, and aircraft are used in inverse models to infer fluxes, but measurement networks remain sparse, with limited or no coverage over large parts of the planet. Satellite retrievals of total column CO2 (XCO2), such as those from NASA's Orbiting Carbon Observatory-2 (OCO-2), can potentially provide unprecedented global information about CO2 spatiotemporal variability. However, for use in inverse modeling, data need to be extremely stable, highly precise, and unbiased to distinguish abundance changes emanating from surface fluxes from those associated with variability in weather. Systematic errors in XCO2 have been identified and, while bias correction algorithms are applied globally, inconsistencies persist at regional and smaller scales that may complicate or confound flux estimation. To evaluate XCO2 retrievals and assess potential biases, we compare OCO-2 v10 retrievals with in situ data-constrained XCO2 simulations over North America estimated using surface fluxes and boundary conditions optimized with observations that are rigorously calibrated relative to the World Meteorological Organization X2007 CO2 scale. Systematic errors in simulated atmospheric transport are independently evaluated using unassimilated aircraft and AirCore profiles. We find that the global OCO-2 v10 bias correction shifts the distribution of retrievals closer to the simulated XCO2, as intended. Comparisons between bias-corrected and simulated XCO2 reveal differences that vary seasonally. Importantly, the difference between simulations and retrievals is of the same magnitude as the imprint of recent surface flux in the total column. This work demonstrates that systematic errors in OCO-2 v10 retrievals of XCO2 over land can be large enough to confound reliable surface flux estimation and that further improvements in retrieval and bias correction techniques are essential. Finally, we show that independent observations, especially vertical profile data, such as those from the National Oceanic and Atmospheric Administration aircraft and AirCore programs are critical for evaluating errors in both satellite retrievals and carbon cycle models.</p
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1.5 years of TROPOMI CO measurements: comparisons to MOPITT and ATom
We have analyzed TROPOspheric Monitoring Instrument (TROPOMI) carbon monoxide (CO) data acquired between November 2017 and March 2019 with respect to other satellite (MOPITT, Measurement Of Pollution In The Troposphere) and airborne (ATom, Atmospheric Tomography mission) datasets to better understand TROPOMI's contribution to the global tropospheric CO record (2000 to present). MOPITT and TROPOMI are two of only a few satellite instruments to ever derive CO from solar-reflected radiances. Therefore, it is particularly important to understand how these two datasets compare. Our results indicate that TROPOMI CO retrievals over land show excellent agreement with respect to MOPITT: relative biases and their SD (i.e., accuracy and precision) are on average , , and compared to the MOPITT TIR (thermal infrared), NIR (near infrared), and TIR + NIR (multispectral) products, respectively. TROPOMI and MOPITT data also show good agreement in terms of temporal and spatial patterns.</p
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Using atmospheric trace gas vertical profiles to evaluate model fluxes: a case study of Arctic-CAP observations and GEOS simulations for the ABoVE domain
Accurate estimates of carbon–climate feedbacks require an independent means for evaluating surface flux models at regional scales. The altitude-integrated enhancement (AIE) derived from the Arctic Carbon Atmospheric Profiles (Arctic-CAP) project demonstrates the utility of this bulk quantity for surface flux model evaluation. This bulk quantity leverages background mole fraction values from the middle free troposphere, is agnostic to uncertainties in boundary layer height, and can be derived from model estimates of mole fractions and vertical gradients. To demonstrate the utility of the bulk quantity, six airborne profiling surveys of atmospheric carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) throughout Alaska and northwestern Canada between April and November 2017 were completed as part of NASA's Arctic–Boreal Vulnerability Experiment (ABoVE). The Arctic-CAP sampling strategy involved acquiring vertical profiles of CO2, CH4, and CO from the surface to 5 km altitude at 25 sites around the ABoVE domain on a 4- to 6-week time interval. All Arctic-CAP measurements were compared to a global simulation using the Goddard Earth Observing System (GEOS) modeling system. Comparisons of the AIE bulk quantity from aircraft observations and GEOS simulations of atmospheric CO2, CH4, and CO highlight the fidelity of the modeled surface fluxes. The model–data comparison over the ABoVE domain reveals that while current state-of-the-art models and flux estimates are able to capture broad-scale spatial and temporal patterns in near-surface CO2 and CH4 concentrations, more work is needed to resolve fine-scale flux features that are captured in CO observations.
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