Comparative assessment of TROPOMI and OMI formaldehyde observations and validation against MAX-DOAS network column measurements

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI), launched in

October 2017 on board the Sentinel-5 Precursor (S5P) satellite, monitors the

composition of the Earth's atmosphere at an unprecedented horizontal

resolution as fine as 3.5 × 5.5 km2. This paper assesses the performances

of the TROPOMI formaldehyde (HCHO) operational product compared to its

predecessor, the OMI (Ozone Monitoring Instrument) HCHO QA4ECV product, at different spatial and temporal

scales. The parallel development of the two algorithms favoured the

consistency of the products, which facilitates the production of long-term

combined time series. The main difference between the two satellite products

is related to the use of different cloud algorithms, leading to a positive

bias of OMI compared to TROPOMI of up to 30 % in tropical regions. We show

that after switching off the explicit correction for cloud effects, the two

datasets come into an excellent agreement. For medium to large HCHO vertical

columns (larger than 5 × 1015 molec. cm−2) the median bias between

OMI and TROPOMI HCHO columns is not larger than 10 % (< 0.4 × 1015 molec. cm−2). For lower columns, OMI observations present

a remaining positive bias of about 20 % (< 0.8 × 1015 molec. cm−2) compared to TROPOMI in midlatitude regions. Here, we also

use a global network of 18 MAX-DOAS (multi-axis differential optical absorption spectroscopy) instruments to validate both satellite

sensors for a large range of HCHO columns. This work complements the study

by Vigouroux et al. (2020), where a global FTIR (Fourier transform infrared) network is used to validate

the TROPOMI HCHO operational product. Consistent with the FTIR validation

study, we find that for elevated HCHO columns, TROPOMI data are

systematically low (−25 % for HCHO columns larger than 8 × 1015 molec. cm−2), while no significant bias is found for medium-range column

values. We further show that OMI and TROPOMI data present equivalent biases

for large HCHO levels. However, TROPOMI significantly improves the precision

of the HCHO observations at short temporal scales and for low HCHO columns.

We show that compared to OMI, the precision of the TROPOMI HCHO columns is

improved by 25 % for individual pixels and by up to a factor of 3 when

considering daily averages in 20 km radius circles. The validation precision

obtained with daily TROPOMI observations is comparable to the one obtained

with monthly OMI observations. To illustrate the improved performances of

TROPOMI in capturing weak HCHO signals, we present clear detection of HCHO

column enhancements related to shipping emissions in the Indian Ocean. This

is achieved by averaging data over a much shorter period (3 months) than

required with previous sensors (5 years) and opens new perspectives to

study shipping emissions of VOCs (volatile organic compounds) and related atmospheric chemical

interactions.