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The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is employed as an intercomparison tool for validating TROPOspheric Monitoring Instrument (TROPOMI) satellite NO 2 retrievals against high-resolution Airborne Prism EXperiment (APEX) remote sensing observations performed in June 2019 in the region of Antwerp, a major hotspot of NO 2 pollution in Europe. The model is first evaluated using meteorological and chemical observations in this area. Sensitivity simulations varying the model planetary layer boundary (PBL) parameterization were conducted for a 3 d period in June 2019, indicating a generally good performance of most parameterizations against meteorological data (namely ceilometer, surface meteorology, and balloon measurements), except for a moderate overestimation (∼ 1 m s -1) of near-surface wind speed. On average, all but one of the PBL schemes reproduce the surface NO 2 measurements at stations of the Belgian Interregional Environmental Agency fairly well, although surface NO 2 is generally underestimated during the day (between -4.3 % and -25.1 % on average) and overestimated at night (8.2 %–77.3 %). This discrepancy in the diurnal evolution arises despite (1) implementing a detailed representation of the diurnal cycle of emissions (Crippa et al., 2020) and (2) correcting the modeled concentrations to account for measurement interferences due to NO y reservoir species, which increases NO 2 concentrations by about 20 % during the day. The model is further evaluated by comparing a 15 d simulation with surface NO 2 , NO, CO, and O 3 data in the Antwerp region. The modeled daytime NO 2 concentrations are more negatively biased during weekdays than during weekends, indicating a misrepresentation of the weekly temporal profile applied to the emissions obtained from Crippa et al. (2020). Using a mass balance approach, we determined a new weekly profile of NO x emissions, leading to a homogenization of the relative bias among the different weekdays. The ratio of weekend to weekday emissions is significantly lower in this updated profile (0.6) than in the profile based on Crippa et al. (2020; 0.84). Comparisons with remote sensing observations generally show a good reproduction of the spatial patterns of NO 2 columns by the model. The model underestimated both APEX (by ca. -37 %) and TROPOMI columns (ca. -25 %) on 27 June, whereas no significant bias is found on 29 June. The two datasets are intercompared by using the model as an intermediate platform to account for differences in vertical sensitivity through the application of averaging kernels. The derived bias of TROPOMI v1.3.1 NO 2 with respect to APEX is about -10 % for columns between (6–12) × 10 15 molec. cm -2. The obtained bias for TROPOMI v1.3.1 increases with the NO 2 column, following CAPEX=1.217Cv1.3-0.783 × 10 15 molec. cm -2 , in line with previous validation campaigns. The bias is slightly lower for the reprocessed TROPOMI v2.3.1, with CAPEX=1.055CPAL-0.437 × 10 15 molec. cm -2 (PAL). Finally, a mass balance approach was used to perform a crude inversion of NO x emissions based on 15 d averaged TROPOMI columns. The emission correction is conducted only in regions with high columns and high sensitivity to emission changes in order to minimize the errors due to wind transport. The results suggest that emissions increase over Brussels–Antwerp (+20 %), the Ruhr Valley (13 %), and especially Paris (+39 %), and emissions decrease above a cluster of power plants in western Germany. [ABSTRACT FROM AUTHOR]

Single-column models (SCMs) have been used as tools to help develop numerical weather prediction and global climate models for several decades. SCMs decouple small-scale processes from large-scale forcing, which allows the testing of physical parameterisations in a controlled environment with reduced computational cost. Typically, either the ocean, sea ice or atmosphere is fully modelled and assumptions have to be made regarding the boundary conditions from other subsystems, adding a potential source of error. Here, we present a fully coupled atmosphere-ocean SCM (AOSCM), which is based on the global climate model EC-Earth3. The initial configuration of the AOSCM consists of the Nucleus for European Modelling of the Ocean (NEMO3.6) (ocean), the Louvain-la-Neuve Sea Ice Model (LIM3) (sea ice), the Open Integrated Forecasting System (OpenIFS) cycle 40r1 (atmosphere), and OASIS3-MCT (coupler). Results from the AOSCM are presented at three locations: the tropical Atlantic, the midlatitude Pacific and the Arctic. At all three locations, in situ observations are available for comparison. We find that the coupled AOSCM can capture the observed atmospheric and oceanic evolution based on comparisons with buoy data, soundings and ship-based observations. The model evolution is sensitive to the initial conditions and forcing data imposed on the column. Comparing coupled and uncoupled configurations of the model can help disentangle model feedbacks. We demonstrate that the AOSCM in the current set-up is a valuable tool to advance our understanding in marine and polar boundary layer processes and the interactions between the individual components of the system (atmosphere, sea ice and ocean). [ABSTRACT FROM AUTHOR]