Mean global and regional distributions of MOPITT carbon monoxide during 2000–2009 and during ENSO

The MOPITT (Measurements Of Pollution In The Troposphere) CO measurements over a 10-year period (2000–2009) reveal consistently positive trends on the order of 0.13–0.19 × 1016 mol cm−2 per month in CO total column concentrations over the entire globe and the hemispheres. Two maxima in globally averaged CO concentrations are identified: one in April and one in October, with two minima in July and December. These maxima and minima are attributable to the respective maxima and minima in CO concentrations over the Northern and Southern Hemispheres. Over the Tropics, maximum and minimum CO concentrations are noted in October and June, respectively, due primarily to biomass burning.During El Niño DJF (December–January–February) and JJA (June–July–August), predominantly positive anomalies in CO total column are noted over the entire globe except for the high latitudes of both hemispheres and the central part of the South America where negative anomalies are identified. La Niña DJF and JJA are largely opposite to El Niño DJF and JJA in CO total column anomalies. Negative (positive) anomalies in CO total column tend to be associated with wet (dry) anomalies in precipitation over the major polluted areas during ENSO. It is suggested that changes in the atmospheric circulations during ENSO either enhance or weaken precipitation systems with the associated precipitation modulating CO total column. The correspondence between anomalies in CO total column and anomalies in Terra MODIS fire pixels during ENSO is rather poor over many parts of the world.

Research highlights
► The MOPITT CO total column over a ten-year period is examined.
► Anomalies in CO total column during ENSO are constructed and examined.
► Wind, precipitation and fire anomalies during ENSO are employed to explain the anomalies in CO.
► There is a close relationship between precipitation anomalies and CO anomalies.
► Correspondence between fire anomalies and CO anomalies is poor.