The ENSO signal in atmospheric composition fields: emission-driven versus dynamically induced changes

Inness, Antje; Benedetti, Angela; Flemming, Johannes; Huijnen, Vincent; Kaiser, J. W.; Parrington, Mark; Rémy, Samuel

doi:10.5194/acp-15-9083-2015

Cited by 37 publications

(53 citation statements)

References 48 publications

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“…ENSO) and the number of fire occurrences (e.g. Alencar et al, 2006;Inness et al, 2015). We find a negative relationship between MISR plume heights and drought conditions in tropical forest fires, as wet years show smoke plume altitudes 300 m higher than dry years.…”

Section: Discussionmentioning

confidence: 65%

“…We note that our dataset was fully acquired at Terra overpass time, which occurs between about 10:00-11:00 LT. This might produce a bias toward the more stable atmospheric conditions that occur preferentially during the morning; later in the afternoon convection tends to become more important (Itterly et al, 2016). Figure 5 shows the seasonal cycle of maximum plume height with FRP, AOD and atmospheric conditions over the major Amazon biomes.…”

Section: Effect Of Atmospheric and Fire Conditions On Smoke Plumesmentioning

confidence: 99%

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Biomass-burning smoke heights over the Amazon observed from space

2019

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We characterise the vertical distribution of biomass-burning emissions across the Amazon during the biomass-burning season (July-November) with an extensive climatology of smoke plumes derived from MISR and MODIS (2005-2012) and CALIOP (2006CALIOP ( -2012 observations. Smoke plume heights exhibit substantial variability, spanning a few hundred metres up to 6 km above the terrain. However, the majority of the smoke is located at altitudes below 2.5 km. About 60 % of smoke plumes are observed in drought years, 40 %-50 % at the peak month of the burning season (September) and 94 % over tropical forest and savanna regions, with respect to the total number of smoke plume observations. At the time of the MISR observations (10:00-11:00 LT), the highest plumes are detected over grassland fires (with an averaged maximum plume height of ∼ 1100 m) and the lowest plumes occur over tropical forest fires (∼ 800 m). A similar pattern is found later in the day (14:00-15:00 LT) with CALIOP, although at higher altitudes (2300 m grassland vs. 2000 m tropical forest), as CALIOP typically detects smoke at higher altitudes due to its later overpass time, associated with a deeper planetary boundary layer, possibly more energetic fires, and greater sensitivity to thin aerosol layers. On average, 3 %-20 % of the fires inject smoke into the free troposphere; this percentage tends to increase toward the end of the burning season (November: 15 %-40 %). We find a well-defined seasonal cycle between MISR plume heights, MODIS fire radiative power and atmospheric stability across the main biomes of the Amazon, with higher smoke plumes, more intense fires and reduced atmospheric stability conditions toward the end of the burning season. Lower smoke plume heights are detected during drought (800 m) compared to non-drought (1100 m) conditions, in particular over tropical forest and savanna fires. Drought conditions favour understory fires over tropical forest, which tend to produce smouldering combustion and low smoke injection heights. Droughts also seem to favour deeper boundary layers and the percentage of smoke plumes that reach the free troposphere is lower during these dry conditions. Consistent with previous studies, the MISR mid-visible aerosol optical depth demonstrates that smoke makes a significant contribution to the total aerosol loading over the Amazon, which in combination with lower injection heights in drought periods has important implications for air quality. This work highlights the importance of biome type, fire properties and atmospheric and drought conditions for plume dynamics and smoke loading. In addition, our study demonstrates the value of combining observations of MISR and CALIOP constraints on the vertical distribution of smoke from biomass burning over the Amazon.

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Section: Discussionmentioning

confidence: 65%

Section: Effect Of Atmospheric and Fire Conditions On Smoke Plumesmentioning

confidence: 99%

Biomass-burning smoke heights over the Amazon observed from space

2019

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“…Biomass burning emissions are commonly calculated as the product of burned area, fuel loads, combustion completeness and emission factors (e.g., van der Werf et al, 2006van der Werf et al, , 2010van Leeuwen and van der Werf, 2011). Because of the large uncertainties in the emission inventories, space-based remotely sensed measurements and surface/aircraft in situ observations have been assimilated to provide "top-down" constraints on CO emissions (e.g., Arellano et al, 2006;Chevallier et al, 2009;Jones et al, 2009;Kopacz et al, 2010;Jiang et al, 2011;Fortems-Cheiney et al, 2011;Hooghiemstra et al, 2012;Miyazaki et al, 2015). In a recent study, Yin et al (2015) constrained global CO emissions for the period 2002-2011 to investigate the possible reasons for the decreasing CO abundance in the Northern Hemisphere.…”

Section: Introductionmentioning

confidence: 99%

A 15-year record of CO emissions constrained by MOPITT CO observations

et al. 2017

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Long-term measurements from satellites and surface stations have demonstrated a decreasing trend of tropospheric carbon monoxide (CO) in the Northern Hemisphere over the past decade. Likely explanations for this decrease include changes in anthropogenic, fires, and/or biogenic emissions or changes in the primary chemical sink hydroxyl radical (OH). Using remotely sensed CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) satellite instrument, in situ methyl chloroform (MCF) measurements from the World Data Centre for Greenhouse Gases (WDCGG) and the adjoint of the GEOS-Chem model, we estimate the change in global CO emissions from 2001 to 2015. We show that the loss rate of MCF varied by 0.2 % in the past 15 years, indicating that changes in global OH distributions do not explain the recent decrease in CO. Our two-step inversion approach for estimating CO emissions is intended to mitigate the effect of bias errors in the MOPITT data as well as model errors in transport and chemistry, which are the primary factors contributing to the uncertainties when quantifying CO emissions using these remotely sensed data. Our results confirm that the decreasing trend of tropospheric CO in the Northern Hemisphere is due to decreasing CO emissions from anthropogenic and biomass burning sources. In particular, we find decreasing CO emissions from the United States and China in the past 15 years, and unchanged anthropogenic CO emissions from Europe since 2008. We find decreasing trends of biomass burning CO emissions from boreal North America, boreal Asia and South America, but little change over Africa. In contrast to prior results, we find that a positive trend in CO emissions is likely for India and southeast Asia. 2011. Using observations from Mt. Bachelor Observatory, Gratz et al. (2015) also show a negative trend of CO concentration by 1.9 % yr −1 in the period of 2004-2013. However, the reason for the large variation of tropospheric CO abundance is still unclear; for example, Strode et al. (2016) found decreases in modeled CO abundance over North America and Published by Copernicus Publications on behalf of the European Geosciences Union.

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“…The changing precipitation patterns lead to draughts in Indonesia and many other regions of the world (El Niño events) which foster large-scale biomass burning not only in Indonesia [Fuller and Murphy, 2006] but also in Siberian and North American boreal forests [Monks et al, 2012]. Because biomass burning is one of the major sources of atmospheric CO, CH 4 , CH 3 Cl, and many other trace gases and aerosols [Andreae and Merlet, 2001], the observed interannual variations of many of these gases could be shown to be driven by ENSO [e.g., Wang et al, 2004;Simmonds et al, 2005;Logan et al, 2008;Chandra et al, 2009;Voulgarakis et al, 2010;Inness et al, 2015]. Brunke et al [2016] noticed that the annual average mercury concentrations in the atmosphere and in rainwater at Cape Point, South Africa, correlate with annual precipitation depth which in turn is also influenced by ENSO in southern Africa.…”

Section: Introductionmentioning

confidence: 99%

El Niño–Southern Oscillation influence on tropospheric mercury concentrations

Šlemr

Brenninkmeijer

Rauthe-Schöch

et al. 2016

Geophysical Research Letters

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The El Niño–Southern Oscillation (ENSO) affects the tropospheric concentrations of many trace gases. Here we investigate the ENSO influence on mercury concentrations measured in the upper troposphere during Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrumented Container flights and at ground at Cape Point, South Africa, and Mace Head, Ireland. Mercury concentrations cross‐correlate with Southern Oscillation Index (SOI) with a lag of 8 ± 2 months. Highest mercury concentrations are always found at the most negative SOI values, i.e., 8 months after El Niño, and the amplitude of the interannual variations fluctuates between ~5 and 18%. The time lag is similar to that of CO whose interannual variations are driven largely by emissions from biomass burning (BB). The amplitude of the interannual variability of tropospheric mercury concentrations is consistent with the estimated variations in mercury emissions from BB. We thus conclude that BB is a major factor driving the interannual variation of tropospheric mercury concentrations.

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The ENSO signal in atmospheric composition fields: emission-driven versus dynamically induced changes

Cited by 37 publications

References 48 publications

Biomass-burning smoke heights over the Amazon observed from space

Biomass-burning smoke heights over the Amazon observed from space

A 15-year record of CO emissions constrained by MOPITT CO observations

El Niño–Southern Oscillation influence on tropospheric mercury concentrations

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