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The northern high latitudes (50–90° N, mostly including boreal-forest and tundra ecosystems) have been undergoing rapid climate and ecological changes over recent decades, leading to significant variations in volatile organic compounds (VOC) emissions from biogenic and biomass burning sources. Formaldehyde (HCHO) is an indicator of VOC emissions, but the interannual variability of HCHO and its main drivers over the region remains unclear. In this study, we use the GEOS-Chem chemical transport model and satellite retrievals from the Ozone Monitoring Instrument (OMI) and the Ozone Mapping and Profiler Suite (OMPS) to examine the interannual variability of HCHO vertical column density (VCD) during the summer seasons spanning from 2005 to 2019. Our results show that, in 2005–2019 summers, wildfires contributed 75 %–90 % of the interannual variability of HCHO VCD over Siberia, Alaska and northern Canada, while biogenic emissions and background methane oxidation account for ∼ 90 % of HCHO interannual variability over eastern Europe. We find that monthly solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2), an efficient proxy for plant photosynthesis, shows a good linear relationship (R= 0.6–0.7) with the modeled biogenic HCHO column (dVCDBio,GC) in eastern Europe, Siberia, Alaska and northern Canada, indicating the coupling between SIF and biogenic VOC emissions over the four domains on a monthly scale. In Alaska, Siberia and northern Canada, SIF and dVCDBio,GC both show relatively lower interannual variabilities (SIF: CV = 1 %–9 %, dVCDBio,GC: CV = 1 %–2 %; note that CV stands for coefficient of variation) in comparison to wildfire-induced HCHO (CV = 8 %–13 %), suggesting that the high interannual variabilities of OMI HCHO VCD (CV = 10 %–16 %) in these domains are likely driven by wildfires instead of biogenic emissions.

Quantifying the global bromine monoxide (BrO) budget is essential to understand ozone chemistry better. In particular, the tropospheric BrO budget has not been well characterized. Here, we retrieve nearly a decade (February 2012–July 2021) of stratospheric and tropospheric BrO vertical columns from the Ozone Mapping and Profiling Suite Nadir Mapper (OMPS-NM) on board the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite. In quantifying tropospheric BrO enhancements from total slant columns, the key aspects involve segregating them from stratospheric enhancements and applying appropriate air mass factors. To address this concern and improve upon the existing methods, our study proposes an approach that applies distinct BrO vertical profiles based on the presence or absence of tropospheric BrO enhancement at each pixel, identifying it dynamically using a satellite-derived stratospheric-ozone–BrO relationship. We demonstrate good agreement for both stratosphere (r = 0.81–0.83) and troposphere (r = 0.50–0.70) by comparing monthly mean BrO vertical columns from OMPS-NM with ground-based observations from three stations (Lauder, Utqiaġvik, and Harestua). Although algorithm performance is primarily assessed at high latitudes, the OMPS-NM BrO retrievals successfully capture tropospheric enhancements not only in polar regions but also in extrapolar areas, such as the Rann of Kutch and the Great Salt Lake. We also estimate random uncertainties in the retrievals pixel by pixel, which can assist in quantitative applications of the OMPS-NM BrO dataset. Our BrO retrieval algorithm is designed for cross-sensor applications and can be adapted to other space-borne ultraviolet spectrometers, contributing to the creation of continuous long-term satellite BrO observation records.

This study aims to generate a spatially complete planetary boundary layer height (PBLH) product over the contiguous United States (CONUS). An eXtreme Gradient Boosting (XGB) regression model was developed using selected meteorological and geographical data fields as explanatory variables to fit the PBLH values derived from Aircraft Meteorological DAta Relay (AMDAR) reports hourly profiles at 13:00–14:00 LST (local solar time) during 2005–2019. A preprocessing step was implemented to exclude AMDAR data points that were unexplainable by the predictors, mostly under stable conditions. The PBLH prediction by this work as well as PBLHs from three reanalysis datasets (the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate – ERA5; the Modern-Era Retrospective analysis for Research and Applications, Version 2 – MERRA-2; and the North American Regional Reanalysis – NARR) were compared to reference PBLH observations from spaceborne lidar (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations, CALIPSO), airborne lidar (High Spectral Resolution Lidar, HSRL), and in situ research aircraft profiles from the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaigns. Compared with PBLHs from reanalysis products, the PBLH prediction from this work shows closer agreement with the reference observations, with the caveat that different PBLH products and estimates have different ways of identifying the PBLH; thus, their comparisons should be interpreted with caution. The reanalysis products show significant high biases in the western CONUS relative to the reference observations. One direct application of the dataset generated by this work is that it enables sampling of the PBLH at the sounding locations and times of sensors aboard satellites with an overpass time in the early afternoon, e.g., the Afternoon Train (A-train), the Suomi National Polar-orbiting Partnership (Suomi NPP), the Joint Polar Satellite System (JPSS), and the Sentinel-5 Precursor (Sentinel-5P) satellite sensors. As both AMDAR and ERA5 are continuous at hourly resolution, the observational-data-driven PBLHs may be extended to other daytime hours.