Air pollution trends measured from Terra: CO and AOD over industrial, fire-prone, and background regions

Buchholz, Rebecca R.; Worden, Helen; Park, Mi-Jeong; Francis, Gene; Deeter, Merritt N.; Edwards, David; Emmons, L. K.; Gaubert, Benjamin; Gille, J. C.; Martínez-Alonso, S.; Tang, Wenfu; Kumar, Rajesh; Drummond, J. R.; Clerbaux, Cathy; George, Martin Andreas Robert M.; Coheur, Pierre‐François; Hurtmans, Daniel; Bowman, K. W.; Luo, Ming; Payne, Vivienne; Worden, J.; Chin, Mian; Levy, Robert R.C.; Warner, J. X.; Wei, Zigang; Kulawik, S. S.

doi:10.1016/j.rse.2020.112275

Cited by 67 publications

(55 citation statements)

References 104 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The units of column-averaged volume mixing ratios are parts per billion by volume (ppb). Using column-averaged volume mixing ratios instead of total column CO removes dependence on surface topography and pressure changes (Buchholz et al, 2021).…”

Section: Response Variablementioning

confidence: 99%

“…We aggregate CO observations into a single biomass burning region in the Southern Hemisphere: Maritime Southeast Asia (MSEA). We focus on MSEA because it is a biomass burning region that experiences significant CO anomalies (i.e., concentrations well above average) (Buchholz et al, 2021). Note that this methodology has been applied to other regions as well (including Southeast Australia -the region that experienced severe bushfires in 2019 and 2020), but for brevity, we discuss only results from MSEA in this paper.…”

Section: Response Variablementioning

confidence: 99%

“…CO is produced by incomplete combustion from biomass burning, fossil fuel use, and indirectly by photochemistry (Holloway et al, 2000;Buchholz et al, 2018), and its link to fires is well established (Edwards, Emmons, et al, 2006). In fact, biomass burning is the primary source of atmospheric CO variability in the Southern Hemisphere, making CO anomalies a useful proxy for fire intensity (Voulgarakis et al, 2015;Bloom et al, 2015;Buchholz et al, 2021). As discussed earlier, biomass burning responds to variability in the climate.…”

Section: Introductionmentioning

confidence: 99%

“…Buchholz et al (2018) expanded on Edwards, Pétron, et al (2006), finding that atmospheric CO anomalies in a number of Southern Hemisphere regions are related to four di↵erent climate modes (including ENSO) and that the interactions between these climate modes are important for explaining atmospheric CO anomalies. In this study, we also examine the relationship between atmospheric CO and climate variability, further focusing on the Maritime Southeast Asia (MSEA) region because of its extremely large CO anomalies (Buchholz et al, 2021). While we focus on a single region in this paper, the modeling framework we have developed can easily be applied to other parts of the globe.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Interpretable Models Capture the Complex Relationship Between Climate Indices and Fire Season Intensity in Maritime Southeast Asia

Daniels¹,

Hammerling²,

Buchholz³

et al. 2022

Preprint

View full text Add to dashboard Cite

There have been many extreme fire seasons in Maritime Southeast Asia (MSEA) over the last two decades, a trend which will likely continue, if not accelerate, due to climate change. Fires, in turn, are a major driver of atmospheric carbon monoxide (CO) variability, especially in the Southern Hemisphere. Previous studies have explored the relationship between climate variability and fire counts, burned area, and atmospheric CO through regression models that use climate mode indices as predictor variables. Here we model the connections between climate variability and atmospheric CO at a level of complexity not yet studied and make accurate predictions of atmospheric CO (a proxy for fire intensity) at useful lead times. To do this, we develop a regularization-based statistical modeling framework that can accommodate multiple lags of a single climate index, which we show to be an important feature in explaining CO. We use this framework to present advancements over previous modeling efforts, such as the inclusion of outgoing longwave radiation (OLR) anomalies, the use of high resolution weekly data, and a stability analysis that adds weight to the scientific interpretation of selected model terms. We find that the El Nino Southern Oscillation (ENSO), the Dipole Mode Index (DMI), and OLR (as a proxy for the Madden-Julian Oscillation) at various lead times are the most significant predictors of atmospheric CO in MSEA. We further show that the model gives accurate predictions of atmospheric CO at leads times of up to 6 months, making it a useful tool for fire season preparedness.

show abstract

Section: Response Variablementioning

confidence: 99%

Section: Response Variablementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Interpretable Models Capture the Complex Relationship Between Climate Indices and Fire Season Intensity in Maritime Southeast Asia

Daniels¹,

Hammerling²,

Buchholz³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…CC BY 4.0 License. transport, and tropospheric chemistry that are associated with human activity and climate change (Worden et al, 2013;Strode et al, 2013, Buchholz et al, 2021. During MOPITT's long mission, data processing algorithms have been updated considerably to improve the quality of the CO retrievals and their sensitivity to the lower troposphere.…”

Section: Introductionmentioning

confidence: 99%

Enhanced MOPITT data coverage through cloud detection improvement

Marey

Drummond

Jones

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. The Measurements of Pollution in the Troposphere (MOPITT) satellite instrument has been measuring global tropospheric carbon monoxide (CO) since March 2000, providing the longest nearly continuous record of CO from space. During its long mission the data processing algorithms have been updated to improve the quality of CO retrievals and the sensitivity to the lower troposphere. Currently, MOPITT retrievals are only performed for clear-sky observations or over low clouds for ocean scenes. Compared to all observed radiances, successful retrieval rates are about 30 % and 40 % between 90° S–90° N and 60° S–60° N, respectively. Spatial seasonal variations show that while MOPITT data coverage in some places reaches 30 % in summer, this number can drop to less than 10 % in winter due to significantly increased cloud cover. Therefore, we investigate the current MOPITT cloud detection algorithm and consider approaches to increase the data coverage. The MOPITT CO total column (TC) data were modified by turning off the cloud detection scheme to allow a CO retrieval result regardless of their cloud status. Analyses of the standard CO TC product (cloud filtered) and non-standard product (non-cloud masked) were conducted for selected days. Results showed some coherent structures that were observed frequently in the non-masked CO product that were not present in the standard product and could potentially be actual CO features. A corresponding analysis of Moderate Resolution Imaging Spectroradiometer(MODIS) cloud height and cloud mask products along with MOPITT cloud flag descriptors was conducted in order to understand the cloud conditions present for these apparently physical CO features. Results show that a significant number of low cloud CO retrievals were rejected in the standard product. Those missing areas match the coherent patterns that were detected in the non-masked CO product. Many times, these structures were also seen in the Infrared Atmospheric Sounding Interferometer (IASI) CO TC product indicating actual CO plumes. Multi-angle Imaging SpectroRadiometer (MISR) data on the Terra satellite were also employed for cloud height comparison with MODIS. Comparisons of MODIS and MISR cloud height data indicate remarkable agreement which is encouraging for the possibility of incorporating MODIS cloud height in the MOPITT cloud detection scheme. Statistics of the global assessment of the potential use of MODIS cloud height shows that MOPITT data increases significantly when cloud heights less than 2 km in height are incorporated in the retrievals. However quality indices should be defined and produced to ensure sufficient retrieval quality.

show abstract

Recent decrease in inner‐core rain rate of tropical cyclones over the western North Pacific

Wei

Song

Dai

et al. 2022

Atmospheric Science Letters

View full text Add to dashboard Cite

The tendency in tropical cyclone (TC) rainfall is of great concern due to its remarkable contribution to global precipitation and extreme rainfall events. This study finds a decreasing trend in TC inner‐core rain rate over the western North Pacific (WNP) from 1998 to 2019. This basinwide trend is mainly induced by the decreasing TC inner‐core rain rates over the region west of 150°E, while it is seldom linked to the changes in the distribution of TC occurrence. The maximum decreases in TC inner‐core rain rate are observed over the offshore areas along the coastlines of East Asia. Further analysis reveals that the change in atmospheric stability, referred to as a dominant environmental contributor to basinwide TC inner‐core rain rate decreases shown in previous studies, only has a primary impact over the northern South China Sea. By comparison, there is a positive correlation between the variations of the aerosol optical depth and TC inner‐core rain rate over the mid‐latitude regions extending from the East China Sea to Japan. Our result highlights the linkage of the recent decreasing trends in aerosol optical depth and TC inner‐core rain rate over the WNP.

show abstract

Air pollution trends measured from Terra: CO and AOD over industrial, fire-prone, and background regions

Cited by 67 publications

References 104 publications

Interpretable Models Capture the Complex Relationship Between Climate Indices and Fire Season Intensity in Maritime Southeast Asia

Interpretable Models Capture the Complex Relationship Between Climate Indices and Fire Season Intensity in Maritime Southeast Asia

Enhanced MOPITT data coverage through cloud detection improvement

Recent decrease in inner‐core rain rate of tropical cyclones over the western North Pacific

Contact Info

Product

Resources

About