Ozone-CO Correlations Determined by the TES Satellite Instrument in Continental Outflow Regions

Collocated measurements of tropospheric ozone (O3) and carbon monoxide (CO) from the Tropospheric Emission Spectrometer (TES) aboard the EOS Aura satellite provide information on O3-CO correlations to test our understanding of global anthropogenic influence on O3. We examine the global distribution of TES O3-CO correlations in the middle troposphere (618 hPa) for July 2005 and compare to correlations generated with the GEOS-Chem chemical transport model and with ICARTT aircraft observations over the eastern United States (July 2004). The TES data show significant O3-CO correlations downwind of polluted continents, with dO3/dCO enhancement ratios in the range 0.4–1.0 mol mol−1 and consistent with ICARTT data. The GEOS-Chem model reproduces the O3-CO enhancement ratios observed in continental outflow, but model correlations are stronger and more extensive. We show that the discrepancy can be explained by spectral measurement errors in the TES data. These errors will decrease in future data releases, which should enable TES to provide better information on O3-CO correlations.Earth and Planetary SciencesEngineering and Applied Science

Comparison of Upper Tropospheric Carbon Monoxide from MOPITT, ACE-FTS, and HIPPO-QCLS

Products from the Measurements Of Pollution In The Troposphere (MOPITT) instrument are regularly validated using in situ airborne measurements. However, few of these measurements reach into the upper troposphere, thus hindering MOPITT validation in that region. Here we evaluate upper tropospheric (~500 hPa to the tropopause) MOPITT CO profiles by comparing them to satellite Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) retrievals and to measurements from the High-performance Instrumented Airborne Platform for Environmental Research Pole to Pole Observations (HIPPO) Quantum Cascade Laser Spectrometer (QCLS). Direct comparison of colocated v5 MOPITT thermal infrared-only retrievals, v3.0 ACE-FTS retrievals, and HIPPO-QCLS measurements shows a slight positive MOPITT CO bias within its 10% accuracy requirement with respect to the other two data sets. Direct comparison of colocated ACE-FTS and HIPPO-QCLS measurements results in a small number of samples due to the large disparity in sampling pattern and density of these data sets. Thus, two additional indirect techniques for comparison of noncoincident data sets have been applied: tracer-tracer (CO-O3) correlation analysis and analysis of profiles in tropopause coordinates. These techniques suggest a negative bias of ACE-FTS with respect to HIPPO-QCLS; this could be caused by differences in resolution (horizontal, vertical) or by deficiencies in the ACE-FTS CO retrievals below ~20 km of altitude, among others. We also investigate the temporal stability of MOPITT and ACE-FTS data, which provide unique global CO records and are thus important in climate analysis. Our results indicate that the relative bias between the two data sets has remained generally stable during the 2004–2010 period. © 2014. American Geophysical Union

Indonesian Fire Activity and Smoke Pollution in 2015 Show Persistent Nonlinear Sensitivity to El Nio-induced Drought

The 2015 fire season and related smoke pollution in Indonesia was more severe than the major 2006 episode, making it the most severe season observed by the NASA Earth Observing System satellites that go back to the early 2000s, namely active fire detections from the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS), MODIS aerosol optical depth, Terra Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO), Aqua Atmospheric Infrared Sounder (AIRS) CO, Aura Ozone Monitoring Instrument (OMI) aerosol index, and Aura Microwave Limb Sounder (MLS) CO. The MLS CO in the upper troposphere showed a plume of pollution stretching from East Africa to the western Pacific Ocean that persisted for two months. Longer-term records of airport visibility in Sumatra and Kalimantan show that 2015 ranked after 1997 and alongside 1991 and 1994 as among the worst episodes on record. Analysis of yearly dry season rainfall from the Tropical Rainfall Measurement Mission (TRMM) and rain gauges shows that, due to the continued use of fire to clear and prepare land on degraded peat, the Indonesian fire environment continues to have non-linear sensitivity to dry conditions during prolonged periods with less than 4mmday of precipitation, and this sensitivity appears to have increased over Kalimantan. Without significant reforms in land use and the adoption of early warning triggers tied to precipitation forecasts, these intense fire episodes will re-occur during future droughts, usually associated with El Nio events

Ozone-CO Correlations Determined by the TES Satellite Instrument in Continental Outflow Regions

Collocated measurements of tropospheric ozone (O3) and carbon monoxide (CO) from the Tropospheric Emission Spectrometer (TES) aboard the EOS Aura satellite provide information on O3-CO correlations to test our understanding of global anthropogenic influence on O3. We examine the global distribution of TES O3-CO correlations in the middle troposphere (618 hPa) for July 2005 and compare to correlations generated with the GEOS-Chem chemical transport model and with ICARTT aircraft observations over the eastern United States (July 2004). The TES data show significant O3-CO correlations downwind of polluted continents, with dO3/dCO enhancement ratios in the range 0.4–1.0 mol mol−1 and consistent with ICARTT data. The GEOS-Chem model reproduces the O3-CO enhancement ratios observed in continental outflow, but model correlations are stronger and more extensive. We show that the discrepancy can be explained by spectral measurement errors in the TES data. These errors will decrease in future data releases, which should enable TES to provide better information on O3-CO correlations.Earth and Planetary SciencesEngineering and Applied Science

Anomalies of O3_3, CO, C2_2H2_2, H2_2CO, and C2_2H6_6 detected with multiple ground-based Fourier-transform infrared spectrometers and assessed with model simulation in 2020: COVID-19 lockdowns versus natural variability

Anomalies of tropospheric columns of ozone (O$_3$), carbon monoxide (CO), acetylene (C$_2$H$_2$), formaldehyde (H$_2$CO), and ethane (C$_2$H$_6$) are quantified during the 2020 stringent COVID-19 world-wide lockdown using multiple ground-based Fourier-transform infrared spectrometers covering urban and remote conditions. We applied an exponential smoothing forecasting approach to the data sets to estimate business-as-usual values for 2020, which are then contrasted with actual observations. The Community Atmosphere Model with chemistry (CAM-chem) is used to simulate the same gases using lockdown-adjusted and business-as-usual emissions. The role of meteorology, or natural variability, is assessed with additional CAM-chem simulations. The tropospheric column of O$_3$ declined between March and May 2020 for most sites with a mean decrease of 9.2% ± 4.7%. Simulations reproduce these anomalies, especially under background conditions where natural variability explains up to 80% of the decline for sites in the Northern Hemisphere. While urban sites show a reduction between 1% and 12% in tropospheric CO, the remote sites do not show a significant change. Overall, CAM-chem simulations capture the magnitude of the anomalies and in many cases natural variability and lockdowns have opposite effects. We further used the long-term record of the Measurements of Pollution in the Troposphere (MOPITT) satellite instrument to capture global anomalies of CO. Reductions of CO vary highly across regions but North America and Europe registered lower values in March 2020. The absence of CO reduction in April and May, concomitant with reductions of anthropogenic emissions, is explained by a negative anomaly in the hydroxyl radical (OH) found with CAM-chem. The implications of these findings are discussed for methane (CH$_4$), which shows a positive lifetime anomaly during the COVID-19 lockdown period. The fossil fuel combustion by-product tracer C2H2 shows a mean drop of 13.6% ± 8.3% in urban Northern Hemisphere sites due to the reduction in emissions and in some sites exacerbated by natural variability. For some sites with anthropogenic influence there is a decrease in C$_2$H$_6$. The simulations capture the anomalies but the main cause may be related to natural variability. H$_2$CO declined during the stringent 2020 lockdown in all urban sites explained by reductions in emissions of precursors

Sixteen years of MOPITT satellite data strongly constrain Amazon CO fire emissions

Despite consensus on the overall downward trend in Amazon forest loss in the previous decade, estimates of yearly carbon emissions from deforestation still vary widely. Estimated carbon emissions are currently often based on data from local logging activity reports, changes in remotely sensed biomass as well as remote detection of fire hotspots, and burned area. Here, we use sixteen years of satellite-derived carbon monoxide (CO) columns to constrain fire CO emissions from the Amazon basin between 2003 and 2018. Through data assimilation, we produce 3-daily maps of fire CO emissions over the Amazon that we verified to be consistent with a long-term monitoring program of aircraft CO profiles over five sites in the Amazon. Our new product independently confirms a long-term decrease of 54 % in deforestation-related CO emissions over the study period. Interannual variability is large, with known anomalously dry years showing a more than fourfold increase in basin-wide fire emissions. At the level of individual Brazilian states, we find that both soil moisture anomalies and human ignitions determine fire activity, suggesting that future carbon release from fires depends on drought intensity as much as on continued forest protection. Our study shows that the atmospheric composition perspective on deforestation is a valuable additional monitoring instrument that complements existing bottom-up and remote sensing methods for land-use change. Extension of such a perspective to an operational framework is timely considering the observed increased fire intensity in the Amazon basin in 2019&ndash;2021.</p

Sixteen years of MOPITT satellite data strongly constrain Amazon CO fire emissions

Despite the consensus on the overall downward trend in Amazon forest loss in the previous decade, estimates of yearly carbon emissions from deforestation still vary widely. Estimated carbon emissions are currently often based on data from local logging activity reports, changes in remotely sensed biomass, and remote detection of fire hotspots and burned area. Here, we use 16 years of satellite-derived carbon monoxide (CO) columns to constrain fire CO emissions from the Amazon Basin between 2003 and 2018. Through data assimilation, we produce 3 d average maps of fire CO emissions over the Amazon, which we verified to be consistent with a long-term monitoring programme of aircraft CO profiles over five sites in the Amazon. Our new product independently confirms a long-term decrease of 54 % in deforestation-related CO emissions over the study period. Interannual variability is large, with known anomalously dry years showing a more than 4-fold increase in basin-wide fire emissions relative to wet years. At the level of individual Brazilian states, we find that both soil moisture anomalies and human ignitions determine fire activity, suggesting that future carbon release from fires depends on drought intensity as much as on continued forest protection. Our study shows that the atmospheric composition perspective on deforestation is a valuable additional monitoring instrument that complements existing bottom-up and remote sensing methods for land-use change. Extension of such a perspective to an operational framework is timely considering the observed increased fire intensity in the Amazon Basin between 2019 and 2021

The impact of internal climate variability on OH trends between 2005 and 2014

The hydroxyl radical (OH) lies at the nexus of climate and air quality as the primary oxidant for both reactive greenhouse gases and many hazardous air pollutants. To better understand the role of climate variability on spatiotemporal patterns of OH, we utilize a 13-member ensemble of the Community Earth System Model version 2-Whole Atmosphere Community Climate Model version 6 (CESM2-WACCM6), a fully coupled chemistry-climate model, spanning the years 1950–2014. Ensemble members vary only in their initial conditions of the climate state in 1950. We focus on the final decade of the simulation, 2005–2014, when prior studies disagree on the signs of the global OH trends. The ensemble mean global airmass-weighted mean tropospheric column OH ( $\Omega_{\mathrm{TOH}}$ ), which is an estimate of the forced signal, increases by 0.06%/year between 2005 and 2014 while regional $\Omega_{\mathrm{TOH}}$ trends range from −0.56%/year over Southern Europe to +0.64%/year over South America. We show that ten-year $\Omega_{\mathrm{TOH}}$ trends are strongly affected by internal climate variability, as the spread of $\Omega_{\mathrm{TOH}}$ trends across the ensemble varies between 0.23%/year in Asia and 1.53%/year in South America. We train a fully connected neural network to emulate the $\Omega_{\mathrm{TOH}}$ simulated by the CESM2-WACCM6 model and combine it with satellite observations to interpret the role of OH chemical proxies. While the OH chemical proxies are subject to internal variability, the impact of internal variability on $\Omega_{\mathrm{TOH}}$ trends is primarily due to the meteorological parameters except for South America. Forced trends in global mean $\Omega_{\mathrm{TOH}}$ do not unambiguously emerge from trends driven by internal variability over the 2005–2014 period. The observation-constrained $\Omega_{\mathrm{TOH}}$ presents opposite trends due to climate variability, resulting in varying conclusions on the attribution of OH to CH _4 trends