Observing atmospheric formaldehyde (HCHO) from space: validation andintercomparison of six retrievals from four satellites (OMI, GOME2A, GOME2B,OMPS) with SEAC4RS aircraft observations over the southeast US

摘要

Formaldehyde (HCHO) column data from satellites are widely used as a proxyfor emissions of volatile organic compounds (VOCs), but validation of thedata has been extremely limited. Here we use highly accurate HCHO aircraftobservations from the NASA SEACRS (Studies of Emissions, AtmosphericComposition, Clouds and Climate Coupling by Regional Surveys) campaign overthe southeast US in August–September 2013 to validate and intercompare sixretrievals of HCHO columns from four different satellite instruments (OMI,GOME2A, GOME2B and OMPS; for clarification of these and other abbreviationsused in the paper, please refer to Appendix A) and three different researchgroups. The GEOS-Chem chemical transport model is used as a commonintercomparison platform. All retrievals feature a HCHO maximum over Arkansasand Louisiana, consistent with the aircraft observations and reflecting highemissions of biogenic isoprene. The retrievals are also interconsistent intheir spatial variability over the southeast US (  =  0.4–0.8 on a0.5°  ×  0.5°  grid) and in their day-to-dayvariability (  =  0.5–0.8). However, all retrievals are biased low inthe mean by 20–51 %, which would lead to corresponding bias in estimatesof isoprene emissions from the satellite data. The smallest bias is forOMI-BIRA, which has high corrected slant columns relative to the otherretrievals and low scattering weights in its air mass factor (AMF)calculation. OMI-BIRA has systematic error in its assumed vertical HCHO shapeprofiles for the AMF calculation, and correcting this would eliminate itsbias relative to the SEACRS data. Our results support the use ofsatellite HCHO data as a quantitative proxy for isoprene emission aftercorrection of the low mean bias. There is no evident pattern in the bias,suggesting that a uniform correction factor may be applied to the data untilbetter understanding is achieved.