Search

Abstract: In the Southern Hemisphere and tropics, the main contribution to carbon monoxide (CO) variability is from fire emissions, which are connected to climate through the availability, type, and dryness of fuel. Here we assess the data‐driven relationships between CO and climate, aiming to predict atmospheric loading during fire seasons. Observations of total column CO from the Measurements Of Pollution In The Troposphere satellite instrument are used to build a record of monthly anomalies between 2001 and 2016, focusing on seven biomass burning regions of the Southern Hemisphere and tropics. With the exception of 2015, the range of absolute variability in CO is similar between regions. We model CO anomalies in each of the regions using climate indices for the climate modes: El Niño–Southern Oscillation, Indian Ocean Dipole, Tropical South Atlantic, and Antarctic Oscillation. Stepwise forward and backward variable selection is used to choose from statistical regression models that use combinations of climate indices, at lag times between 1 and 8 months relative to CO anomalies. The Bayesian information criterion selects models with the best predictive power. We find that all climate mode indices are required to model CO in each region, generally explaining over 50% of the variability and over 70% for tropical regions. First‐order interaction terms of the climate modes are necessary, producing greatly improved explanation of CO variability over single terms. Predictive capability is assessed for the Maritime Southeast Asia and the predicted peak CO anomaly in 2015 is within 20% of the measurements. [ABSTRACT FROM AUTHOR]

We investigate the impact of biogenic emissions on carbon monoxide (CO) and formaldehyde (HCHO) in the Southern Hemisphere (SH), with simulations using two different biogenic emission inventories for isoprene and monoterpenes. Results from four atmospheric chemistry models are compared to continuous long-term groundbased CO and HCHO column measurements at the SH Network for the Detection of Atmospheric Composition Change (NDACC) sites, the satellite measurement of tropospheric CO columns from the Measurement of Pollution in the Troposphere (MOPITT), and in situ surface CO measurements from across the SH, representing a subset of the National Oceanic and Atmospheric Administration's Global Monitoring Division (NOAA GMD) network. Simulated mean model CO using the Model of Emissions of Gases and Aerosols from Nature (v2.1) computed in the frame work of the Land Community Model (CLM-MEGANv2.1) inventory is in better agreement with both column and surface observations than simulations adopting the emission inventory generated from the LPJ-GUESS dynamical vegetation model framework, which markedly underestimate measured column and surface CO at most sites. Differences in biogenic emissions cause large differences in CO in the source regions which propagate to the remote SH. Significant inter-model differences exist in modelled column and surface CO, and secondary production of CO dominates these inter-model differences due mainly to differences in the models' oxidation schemes for volatile organic compounds, predominantly isoprene oxidation. While biogenic emissions are a significant factor in modelling SH CO, inter-model differences pose an additional challenge to constrain these emissions. Corresponding comparisons of HCHO columns at two SH mid-latitude sites reveal that all models significantly underestimate the observed values by approximately a factor of 2. There is a much smaller impact on HCHO of the significantly different biogenic emissions in remote regions, compared to the source regions. Decreased biogenic emissions cause decreased CO export to remote regions, which leads to increased OH; this in turn results in increased HCHO production through methane oxidation. In agreement with earlier studies, we corroborate that significant HCHO sources are likely missing in the models in the remote SH. [ABSTRACT FROM AUTHOR]

The combination of low anthropogenic emissions and large biogenic sources that characterizes the Southern Hemisphere (SH) leads to significant differences in atmospheric composition relative to the better studied Northern Hemisphere. This unique balance of sources poses significant challenges for global models. Carbon monoxide (CO) in particular is difficult to simulate in the SH due to the increased importance of secondary chemical production associated with the much more limited primary emissions. Here, we use aircraft observations from the 1991-2000 Cape Grim Overflight Program (CGOP) and the 2009-2011 HIAPER (High-performance Instrumented Airborne Platform for Environmental Research) Pole-to-Pole Observations (HIPPO), together with model output from the SH Model Intercomparison Project, to elucidate the drivers of CO vertical structure in the remote SH. Observed CO vertical profiles from Cape Grim are remarkably consistent with those observed over the southern mid-latitudes Pacific 10-20 years later, despite major differences in time periods, flight locations, and sampling strategies between the two data sets. These similarities suggest the processes driving observed vertical gradients are coherent across much of the remote SH and have not changed significantly over the past 2 decades. Model ability to simulate CO profiles reflects the interplay between biogenic emission sources, the chemical mechanisms that drive CO production from these sources, and the transport that redistributes this CO throughout the SH. The four chemistryclimate and chemical transport models included in the intercomparison show large variability in their abilities to reproduce the observed CO profiles. In particular, two of the four models significantly underestimate vertical gradients in austral summer and autumn, which we find are driven by long-range transport of CO produced from oxidation of biogenic compounds. Comparisons between the models show that more complex chemical mechanisms do not necessarily provide more accurate simulation of CO vertical gradients due to the convolved impacts of emissions, chemistry, and transport. Our results imply a large sensitivity of the remote SH troposphere to biogenic emissions and chemistry, both of which remain key uncertainties in global modeling. We suggest that the CO vertical gradient can be used as a metric for future model evaluation as it provides a sensitive test of the processes that define the chemical state of the background atmosphere. [ABSTRACT FROM AUTHOR]