Assessing Measurements of Pollution in the Troposphere (MOPITT) carbon monoxide retrievals over urban versus non-urban regions

Abstract

Abstract. The Measurements of Pollution in the Troposphere (MOPITT) retrievals over urban regions have not been validated systematically, even though MOPITT observations are widely used to study CO over urban regions. Here we compare MOPITT products over urban and non-urban regions with aircraft measurements from the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ – 2011–2014), Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS – 2013), Air Chemistry Research In Asia (ARIAs – 2016), A-FORCE (2009, 2013), and Korea United States Air Quality (KORUS-AQ – 2016) campaigns. In general, MOPITT agrees reasonably well with the in situ profiles, over both urban and non-urban regions. Version 8 multispectral product (V8J) biases vary from −0.7 % to 0.0 % and version 8 thermal-infrared product (TIR) biases vary from 2.0 % to 3.5 %. The evaluation statistics of MOPITT V8J and V8T over non-urban regions are better than those over urban regions with smaller biases and higher correlation coefficients. We find that the agreement of MOPITT V8J and V8T with aircraft measurements at high CO concentrations is not as good as that at low CO concentrations, although CO variability may tend to exaggerate retrieval biases in heavily polluted scenes. We test the sensitivities of the agreements between MOPITT and in situ profiles to assumptions and data filters applied during the comparisons of MOPITT retrievals and in situ profiles. The results at the surface layer are insensitive to the model-based profile extension (required due to aircraft altitude limitations), whereas the results at levels with limited aircraft observations (e.g., the 600 hPa layer) are more sensitive to the model-based profile extension. The results are insensitive to the maximum allowed time difference criterion for co-location (12, 6, 3, and 1 h) and are generally insensitive to the radius for co-location, except for the case where the radius is small (25 km), and hence few MOPITT retrievals are included in the comparison. Daytime MOPITT products have smaller overall biases than nighttime MOPITT products when comparing both MOPITT daytime and nighttime retrievals to the daytime aircraft observations. However, it would be premature to draw conclusions on the performance of MOPITT nighttime retrievals without nighttime aircraft observations. Applying signal-to-noise ratio (SNR) filters does not necessarily improve the overall agreement between MOPITT retrievals and in situ profiles, likely due to the reduced number of MOPITT retrievals for comparison. Comparisons of MOPITT retrievals and in situ profiles over complex urban or polluted regimes are inherently challenging due to spatial and temporal variabilities of CO within MOPITT retrieval pixels (i.e., footprints). We demonstrate that some of the errors are due to CO representativeness with these sensitivity tests, but further quantification of representativeness errors due to CO variability within the MOPITT footprint will require future work.

Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ

“…While chemical data assimilation is effective for CO in a global model, because of its longer lifetime than most of the reactive species, there are some limitations if the parameters, such as emission inventory inputs or physical and chemical processes, are not updated consistently with the initial conditions (Tang et al, 2013). The KORUS-AQ campaign provides a large array of measurements and is an excellent case study for testing the model with challenges that need to be addressed for further improvements of CO and related species of interest such as OH, O 3 , CH 4 , and NMVOCs.…”

Assessing sub-grid variability within satellite pixels using airborne mapping spectrometer measurements

“…This study also has implications for satellite validation and evaluation, and satellite-in situ data comparisons of other trace gas species. Our initial motivation to study satellite SGV arose from our previous work on validation of MOPITT (Measurements of Pollution in the Troposphere) CO retrievals over urban regions (Tang et al, 2020). In that study, we compared the satellite retrievals with aircraft profiles, and realized that satellite SGV and representativeness error of aircraft profiles in the comparisons to MOPITT retrievals introduced uncertainties in the validation results.…”

“…We focus on the GeoTASO measurements made during the Korea United States Air Quality (KORUS-AQ) field experiment in 2016. The measurements from KORUS-AQ have been widely used by researchers for various air quality topics, including quantification of emissions and model and satellite evaluation (e.g., Deeter et al, 2019;Huang et al, 2018;Kim et al, 2018;Miyazaki et al, 2019;Spinei et al, 2018;Tang et al, 2018Tang et al, , 2019Souri et al, 2020, Gaubert et al, 2020. We further compare our findings from KORUS-AQ with flights conducted during the NASA Student Airborne Research Program (SARP) in 2017 over the Los Angeles (LA) Basin to test the general applicability of our findings.…”

Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ

“…The new Troposphere and Stratosphere (TS1) reduced gas phase chemical mechanism contains 221 species and 528 reactions (Emmons et al, 2020), and thus explicitly represents stratospheric and tropospheric ozone and OH chemistry. This chemical scheme contains many updates, including on the isoprene oxidation mechanism, splitting a single aromatic into BENZENE, 305 TOLUENE and XYLENES lumped species and a terpene speciation.…”