ALBERT

Description: Measurements from actinic flux spectroradiometers on board the NASA DC-8 during the Atmospheric Tomography (ATom) mission provide an extensive set of statistics on how clouds alter photolysis rates (J values) throughout the remote Pacific and Atlantic Ocean basins. J values control tropospheric ozone and methane abundances, and thus clouds have been included for more than three decades in tropospheric chemistry modeling. ATom made four profiling circumnavigations of the troposphere capturing each of the seasons during 2016–2018. This work examines J values from the Pacific Ocean flights of the first deployment, but publishes the complete Atom-1 data set (29 July to 23 August 2016). We compare the observed J values (every 3 s along flight track) with those calculated by nine global chemistry–climate/transport models (globally gridded, hourly, for a mid-August day). To compare these disparate data sets, we build a commensurate statistical picture of the impact of clouds on J values using the ratio of J-cloudy (standard, sometimes cloudy conditions) to J-clear (artificially cleared of clouds). The range of modeled cloud effects is inconsistently large but they fall into two distinct classes: (1) models with large cloud effects showing mostly enhanced J values aloft and or diminished at the surface and (2) models with small effects having nearly clear-sky J values much of the time. The ATom-1 measurements generally favor large cloud effects but are not precise or robust enough to point out the best cloud-modeling approach. The models here have resolutions of 50–200 km and thus reduce the occurrence of clear sky when averaging over grid cells. In situ measurements also average scattered sunlight over a mixed cloud field, but only out to scales of tens of kilometers. A primary uncertainty remains in the role of clouds in chemistry, in particular, how models average over cloud fields, and how such averages can simulate measurements.

Description: An approach for analysis and modeling of global atmospheric chemistry is developed for application to measurements that provide a tropospheric climatology of those heterogeneously distributed, reactive species that control the loss of methane and the production and loss of ozone. We identify key species (e.g., O3, NOx, HNO3, HNO4, C2H3NO5, H2O, HOOH, CH3OOH, HCHO, CO, CH4, C2H6, acetaldehyde, acetone) and presume that they can be measured simultaneously in air parcels on the scale of a few km horizontally and a few tenths of a km vertically. As a first step, six global models have prepared such climatologies sampled at the modeled resolution for August with emphasis on the vast central Pacific Ocean basin. Objectives of this paper are to identify and characterize differences in model-generated reactivities as well as species covariances that could readily be discriminated with an unbiased climatology. A primary tool is comparison of multidimensional probability densities of key species weighted by the mass of such parcels or frequency of occurrence as well as by the reactivity of the parcels with respect to methane and ozone. The reactivity-weighted probabilities tell us which parcels matter in this case, and this method shows skill in differentiating among the models' chemistry. Testing 100 km scale models with 2 km measurements using these tools also addresses a core question about model resolution and whether fine-scale atmospheric structures matter to the overall ozone and methane budget. A new method enabling these six global chemistry–climate models to ingest an externally sourced climatology and then compute air parcel reactivity is demonstrated. Such an objective climatology containing these key species is anticipated from the NASA Atmospheric Tomography (ATom) aircraft mission (2015–2020), executing profiles over the Pacific and Atlantic Ocean basins. This modeling study addresses a core part of the design of ATom.

Description: The impacts of climate change on tropospheric transport, diagnosed from a carbon monoxide (CO)-like tracer species emitted from global CO sources, are evaluated from an ensemble of four chemistry–climate models (CCMs) contributing to the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Model time-slice simulations for present-day and end-of-the-21st-century conditions were performed under the Representative Concentrations Pathway (RCP) climate scenario RCP 8.5. All simulations reveal a strong seasonality in transport, especially over the tropics. The highest CO-tracer mixing ratios aloft occur during boreal winter when strong vertical transport is co-located with biomass burning emission source regions. A consistent and robust decrease in future CO-tracer mixing ratios throughout most of the troposphere, especially in the tropics, and an increase around the tropopause is found across the four CCMs in both winter and summer. Decreases in CO-tracer mixing ratios in the tropical troposphere are associated with reduced convective mass fluxes in this region, which in turn may reflect a weaker Hadley cell circulation in the future climate. Increases in CO-tracer mixing ratios near the tropopause are largely attributable to a rise in tropopause height enabling lofting to higher altitudes, although a poleward shift in the mid-latitude jets may also play a minor role in the extratropical upper troposphere. An increase in CO-tracer mixing ratios also occurs near the Equator, centred over equatorial and Central Africa, extending from the surface to the mid-troposphere. This is most likely related to localised decreases in convection in the vicinity of the Intertropical Convergence Zone (ITCZ), resulting in larger CO-tracer mixing ratios over biomass burning regions and smaller mixing ratios downwind.

Description: We develop a new protocol for merging in situ measurements with 3-D model simulations of atmospheric chemistry with the goal of integrating these data to identify the most reactive air parcels in terms of tropospheric production and loss of the greenhouse gases ozone and methane. Presupposing that we can accurately measure atmospheric composition, we examine whether models constrained by such measurements agree on the chemical budgets for ozone and methane. In applying our technique to a synthetic data stream of 14 880 parcels along 180∘ W, we are able to isolate the performance of the photochemical modules operating within their global chemistry-climate and chemistry-transport models, removing the effects of modules controlling tracer transport, emissions, and scavenging. Differences in reactivity across models are driven only by the chemical mechanism and the diurnal cycle of photolysis rates, which are driven in turn by temperature, water vapor, solar zenith angle, clouds, and possibly aerosols and overhead ozone, which are calculated in each model. We evaluate six global models and identify their differences and similarities in simulating the chemistry through a range of innovative diagnostics. All models agree that the more highly reactive parcels dominate the chemistry (e.g., the hottest 10 % of parcels control 25–30 % of the total reactivities), but do not fully agree on which parcels comprise the top 10 %. Distinct differences in specific features occur, including the spatial regions of maximum ozone production and methane loss, as well as in the relationship between photolysis and these reactivities. Unique, possibly aberrant, features are identified for each model, providing a benchmark for photochemical module development. Among the six models tested here, three are almost indistinguishable based on the inherent variability caused by clouds, and thus we identify four, effectively distinct, chemical models. Based on this work, we suggest that water vapor differences in model simulations of past and future atmospheres may be a cause of the different evolution of tropospheric O3 and CH4, and lead to different chemistry-climate feedbacks across the models.

Description: Solar-J is a comprehensive radiative transfer model for the solar spectrum that addresses the needs of both solar heating and photochemistry in Earth system models. Solar-J is a spectral extension of Cloud-J, a standard in many chemical models that calculates photolysis rates in the 0.18–0.8 µm region. The Cloud-J core consists of an eight-stream scattering, plane-parallel radiative transfer solver with corrections for sphericity. Cloud-J uses cloud quadrature to accurately average over correlated cloud layers. It uses the scattering phase function of aerosols and clouds expanded to eighth order and thus avoids isotropic-equivalent approximations prevalent in most solar heating codes. The spectral extension from 0.8 to 12 µm enables calculation of both scattered and absorbed sunlight and thus aerosol direct radiative effects and heating rates throughout the Earth's atmosphere.The Solar-J extension adopts the correlated-k gas absorption bins, primarily water vapor, from the shortwave Rapid Radiative Transfer Model for general circulation model (GCM) applications (RRTMG-SW). Solar-J successfully matches RRTMG-SW's tropospheric heating profile in a clear-sky, aerosol-free, tropical atmosphere. We compare both codes in cloudy atmospheres with a liquid-water stratus cloud and an ice-crystal cirrus cloud. For the stratus cloud, both models use the same physical properties, and we find a systematic low bias of about 3 % in planetary albedo across all solar zenith angles caused by RRTMG-SW's two-stream scattering. Discrepancies with the cirrus cloud using any of RRTMG-SW's three different parameterizations are as large as about 20–40 % depending on the solar zenith angles and occur throughout the atmosphere.Effectively, Solar-J has combined the best components of RRTMG-SW and Cloud-J to build a high-fidelity module for the scattering and absorption of sunlight in the Earth's atmosphere, for which the three major components – wavelength integration, scattering, and averaging over cloud fields – all have comparably small errors. More accurate solutions with Solar-J come with increased computational costs, about 5 times that of RRTMG-SW for a single atmosphere. There are options for reduced costs or computational acceleration that would bring costs down while maintaining improved fidelity and balanced errors.

Description: Global temperature is a fundamental climate metric highly correlated with sea level, which implies that keeping shorelines near their present location requires keeping global temperature within or close to its preindustrial Holocene range. However, global temperature excluding short-term variability now exceeds +1 °C relative to the 1880–1920 mean and annual 2016 global temperature was almost +1.3 °C. We show that global temperature has risen well out of the Holocene range and Earth is now as warm as it was during the prior (Eemian) interglacial period, when sea level reached 6–9 m higher than today. Further, Earth is out of energy balance with present atmospheric composition, implying that more warming is in the pipeline, and we show that the growth rate of greenhouse gas climate forcing has accelerated markedly in the past decade. The rapidity of ice sheet and sea level response to global temperature is difficult to predict, but is dependent on the magnitude of warming. Targets for limiting global warming thus, at minimum, should aim to avoid leaving global temperature at Eemian or higher levels for centuries. Such targets now require negative emissions, i.e., extraction of CO2 from the air. If phasedown of fossil fuel emissions begins soon, improved agricultural and forestry practices, including reforestation and steps to improve soil fertility and increase its carbon content, may provide much of the necessary CO2 extraction. In that case, the magnitude and duration of global temperature excursion above the natural range of the current interglacial (Holocene) could be limited and irreversible climate impacts could be minimized. In contrast, continued high fossil fuel emissions today place a burden on young people to undertake massive technological CO2 extraction if they are to limit climate change and its consequences. Proposed methods of extraction such as bioenergy with carbon capture and storage (BECCS) or air capture of CO2 have minimal estimated costs of USD 89–535 trillion this century and also have large risks and uncertain feasibility. Continued high fossil fuel emissions unarguably sentences young people to either a massive, implausible cleanup or growing deleterious climate impacts or both.

Description: The rapid rise of global temperature that began about 1975 continues at a mean rate of about 0.18 °C/decade, with the current annual temperature exceeding +1.25 °C relative to 1880–1920. Global temperature has just reached a level similar to the mean level in the prior interglacial (Eemian) period, when sea level was several meters higher than today, and, if it long remains at this level, slow amplifying feedbacks will lead to greater climate change and consequences. The growth rate of climate forcing due to human-caused greenhouse gases (GHGs) increased over 20 % in the past decade mainly due to resurging growth of atmospheric CH4, thus making it increasingly difficult to achieve targets such as limiting global warming to 1.5 °C or reducing atmospheric CO2 below 350 ppm. Such targets now require "negative emissions", i.e., extraction of CO2 from the atmosphere. If rapid phasedown of fossil fuel emissions begins soon, most of the necessary CO2 extraction can take place via improved agricultural and forestry practices, including reforestation and steps to improve soil fertility and increase its carbon content. In this case, the magnitude and duration of global temperature excursion above the natural range of the current interglacial (Holocene) could be limited and irreversible climate impacts could be minimized. In contrast, continued high fossil fuel emissions by the current generation would place a burden on young people to undertake massive technological CO2 extraction, if they are to limit climate change. Proposed methods of extraction such as bioenergy with carbon capture and storage (BECCS) or air capture of CO2 imply minimal estimated costs of 104–570 trillion dollars this century, with large risks and uncertain feasibility. Continued high fossil fuel emissions unarguably sentences young people to either a massive, possibly implausible cleanup or growing deleterious climate impacts or both, scenarios that should provide both incentive and obligation for governments to alter energy policies without further delay.

Description: An approach for analysis and modeling of global atmospheric chemistry is developed for application to measurements that provide a tropospheric climatology of those heterogeneously distributed, reactive species that control the loss of methane and the production and loss of ozone. We identify key species (e.g., O3, NOx, HNO3, HNO4, C2H3NO5, H2O, HOOH, CH3OOH, HCHO, CO, CH4, C2H6, acetaldehyde, acetone), and presume that they can be measured simultaneously in air parcels on the scale of a few km horizontally and a few tenths vertically. Six global models have prepared such climatologies (at model resolution) for August with emphasis on the vast central Pacific and Atlantic Ocean basins. We show clear differences in model generated reactivities as well as species covariances that could readily be discriminated with an unbiased climatology. A primary tool is comparison of multi-dimensional probability densities of key species weighted by frequency of occurrence as well as by the reactivity of the parcels with respect to methane and ozone. The reactivity-weighted probabilities tell us which parcels matter in this case. Testing 100-km scale models with 2-km measurements using these tools also addresses a core question about model resolution and whether fine-scale atmospheric structures matter to the overall ozone and methane budget. A new method enabling these six global chemistry-climate models to ingest an externally-sourced climatology and then compute air parcel reactivity is demonstrated. Such an observed climatology is anticipated from the NASA Atmospheric Tomography (ATom) aircraft mission (2015–2020), measuring the key species, executing profiles over the Pacific and Atlantic Ocean basins. This work is a core part of the design of ATom.

Description: We develop a new protocol for merging in situ measurements with 3-D model simulations of atmospheric chemistry with the goal of integrating over the data to identify the most reactive air parcels in terms of tropospheric production and loss of the greenhouse gases ozone and methane. Presupposing that we can accurately measure atmospheric composition, we examine whether models constrained by such measurements agree on the chemical budgets for ozone and methane. In applying our technique to a synthetic data stream of 14,880 parcels along 180 W, we are able to isolate the performance of the photochemical modules operating within their global chemistry-climate and chemistry-transport models, removing the effects of modules controlling tracer transport, emissions, and scavenging. Differences in reactivity across models are driven only by the chemical mechanism and the diurnal cycle of photolysis rates, which are driven in turn by temperature, water vapor, solar zenith angle, clouds, and possibly aerosols and overhead ozone, which are calculated in each model. We evaluate six global models and identify their differences and similarities in simulating the chemistry through a range of innovative diagnostics. All models agree that the more highly reactive parcels dominate the chemistry (e.g., the hottest 10 % of parcels control 25–30 % of the total reactivities), but do not fully agree on which parcels comprise the top 10 %. Distinct differences in specific features occur, including the regions of maximum ozone production and methane loss, as well as in the relationship between photolysis and these reactivities. Unique, possibly aberrant, features are identified for each model, providing a benchmark for photochemical module development. Among the 6 models tested here, 3 are almost indistinguishable based on the inherent variability caused by clouds, and thus we identify 4, effectively distinct, chemical models. Based on this work, we suggest that water vapor differences in model simulations of past and future atmospheres may be a cause of the different evolution of tropospheric O3 and CH4, and lead to different chemistry-climate feedbacks across the models.

Description: Measurements from actinic flux spectroradiometers on board the NASA DC-8 during the Atmospheric Tomography (ATom) mission provide an extensive set of statistics on how clouds alter photolysis rates (J-values) throughout the remote Pacific and Atlantic Ocean basins. ATom made profiling circumnavigations of the troposphere over four seasons during 2016–2018. J-values are a primary chemical control over tropospheric ozone and methane abundances and their greenhouse effects. Clouds have been recognized for more than three decades as being an important factor in tropospheric chemistry. The ATom climatology of J-values is a unique test of how the chemistry models treat clouds. This work focuses on measurements over the Pacific during the first deployment (ATom-1) in August 2016. Nine global chemistry–climate or –transport models provide J-values for the domains measured in ATom-1. We compare mean profiles over a range of cloudy and clear conditions; but, more importantly, we build a statistical picture of the impact of clouds on J-values through the distribution of the ratio of J-cloudy to J-clear. In detail, the models show largely disparate patterns. When compared with measurements, there is some limited, broad agreement. Models here have resolutions of 50–200km and thus reduce the occurrence of clear sky when averaging over grid cells. In situ measurements also average the scattered sunlight, but only out to scales of 10s of km. A primary uncertainty remains in the role of clouds in chemistry, in particular, how models average over cloud fields, and how such averages can simulate measurements.