Evaluation of local measurement-driven adjustments of modelled cloud-free atmospheric photolysis rate coefficients

Photolysis rate constants (j-values) play a crucial role in atmospheric chemistry modelling, but capturing the variability in local conditions needed for their accurate simulation is computationally challenging. One approach is to adjust modelled clear-sky estimates using ratios of measured-to-modelled j-values of a reference photolysis, typically j(NO2) or j((OD)-D-1). However, application of such adjustments to other photolysis reactions introduces uncertainty. Using spectral radiometer data from the UK, this study examines how hourly measurement driven adjustment factors (MDAF) across a set of 12 photolysis reactions group together using cluster analysis, and evaluates the uncertainties in using j(NO2) and j((OD)-D-1)-derived MDAF values to adjust modelled j-values of other photolysis reactions. The NO2-MDAF reference is suitable for adjusting photolysis reactions that absorb at lambda > 360 nm (HONO, methylglyoxal, ClNO2, ClONO2 -> Cl), which are largely independent of solar zenith angle and total ozone column (<31% error). In particular, NO2-MDAF is a good reference for j(HONO) and j(ClNO2). The (OD)-D-1-MDAF performed better at adjusting modelled j-values for species that predominantly photodissociate at lambda < 350 nm, such as HNO3, H2O2, CH3CHO, HCHO -> H, HCHO -> H-2 and ClONO2 -> ClO (errors <= 30%). However, j((OD)-D-1) radiometers require more data processing to account for local conditions. The maximum error determined using NO2-MDAF was within a factor of two (91% for j(H2O2)), which may still be acceptable in some instances. It is important that MDAFs are used to improve accuracy and uncertainty in simulated j-values caused by variation in local conditions.

Automated summary

Photolysis rate constants play a crucial role in atmospheric chemistry modelling. Adjusting modelled values using ratios of measured-to-modelled values of a reference photolysis can improve accuracy, but also introduces uncertainty. This study examines the clustering patterns of adjustment factors for different photolysis reactions and evaluates the uncertainties in using different reference values to adjust modelled results.