Engineering Papers⌕ Search

Engineering topics

Jason M St Clair

Publications and source records attributed to Jason M St Clair.

5 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2025

Validation of Formaldehyde Products From Three Satellite Retrievals (OMI SAO, OMPS-NPP SAO, and OMI BIRA) in the Marine Atmosphere With Four Seasons of Atom Aircraft Observations

Formaldehyde (HCHO) in the atmosphere is an intermediate product from the oxidation of methane and non-methane volatile organic compounds. In remote marine regions, HCHO variability is closely related to atmospheric oxidation capacity and modeled HCHO in these regions is usually added as a global satellite HCHO background. Thus, it is important to understand and validate the levels of satellite HCHO over the remote oceans. Here we intercompare three satellite retrievals of total HCHO columns (OMI-SAO (v004), OMPS-NPP SAO, and OMI BIRA) and validate them against in situ observations from the NASA Atmospheric Tomography Mission (ATom) mission. All retrievals are correlated with ATom integrated columns over remote oceans, with OMI SAO (v004) showing the best agreement. This is also reflected in the mean bias (MB) for OMI SAO (-0.73±0.87) x 10 15 molec cm -2 , OMPS SAO (-0.76±0.88) x 10 15 molec cm -2 , and OMI BIRA (-1.40±1.11) x 10 15 molec cm -2 . We recommend the OMI-SAO (v004) retrieval for remote ocean atmosphere studies. Three satellite HCHO retrievals and in situ ATom columns all generally captured the spatial and seasonal distributions of HCHO in the remote ocean atmosphere. Retrieval bias varies by latitude and season, but a persistent low bias is found in all products at high latitudes and the general low bias is most severe for the OMI BIRA product. Examination of retrieval components reveals slant column corrections have a larger impact on the retrievals over remote marine regions while AMFs play a smaller role. This study informs that the potential latitude-dependent biases in the retrievals require further investigation for improvement and should be considered when using marine HCHO satellite data, and vertical profiles from in situ instruments are crucial for validating satellite retrievals.

Atom↗
NASA NTRS2022

Source and Variability of Formaldehyde (HCHO) at Northern High Latitude: an Integrated Satellite, Aircraft, and Model Study

Here we use satellite observations of formaldehyde (HCHO)vertical column densities (VCD) from the TROPOspheric Monitoring Instrument (TROPOMI), aircraft measurements, combined with a nested regional chemical transport model (GEOS-Chem at 0.5°×0.625° resolution), to understand the variability and sources of summertime HCHO better in Alaska. We first evaluate GEOS-Chem with in-situ airborne measurements during Atmospheric Tomography Mission 1 (ATom-1) aircraft campaign. We show reasonable agreement between observed and modeled HCHO, isoprene, monoterpenes and the sum of methyl vinyl ketone and methacrolein (MVK+MACR) in continental boundary layer. In particular, HCHO profiles show spatial homogeneity in Alaska, suggesting a minor contribution of biogenic emissions to HCHO VCD. We further examine the TROPOMI HCHO product in Alaska summer, reprocessed by GEOS-Chem model output for a priori profiles and shape factors. For the year with low wildfire activity (e.g.,2018), we find that HCHO VCDs are largely dominated by background HCHO (58-71%), with minor contributions from wildfires (20-32%) and biogenic VOC emissions (8-10%). For the year with intense wildfires (e.g.,2019), summertime HCHO VCD is dominated by wildfire emissions (50-72%), with minor contributions from background (22-41%) and biogenic VOCs (6-10%). In particular, the model indicates a major contribution of wildfires from direct emissions of HCHO, instead of secondary production of HCHO from oxidation of larger VOCs. We find that the column contributed by biogenic VOC is often small and below the TROPOMI detection limit, in part due to the slow HCHO production from isoprene oxidation under low NOx conditions. This work highlights challenges for quantifying HCHO and its precursors in remote pristine regions.

HCHO↗
NASA NTRS2022

Photochemical Evolution of the 2013 California Rim Fire: Synergistic Impacts of Reactive Hydrocarbons and Enhanced Oxidants

Large wildfires markedly alter regional atmospheric composition, but chemical complexity challenges model predictions of downwind impacts. Here, we elucidate key facets of gas-phase photochemistry and assess novel chemical processes via a case study of the 2013 California Rim Fire plume. Airborne in situ observations, acquired during the NASA Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) mission, illustrate the evolution of volatile organic compounds (VOC), oxidants, and reactive nitrogen over 12 hours of atmospheric aging. Measurements show rapid formation of ozone and peroxyacyl nitrates (PNs), sustained peroxide production, and prolonged enhancements in oxygenated VOC and nitrogen oxides (NOX). Measurements and Lagrangian trajectories constrain a 0-D puff model that approximates plume photochemical history and provides a framework for evaluating key processes. Simulations examine the effects of 1) previously-unmeasured reactive VOC identified in recent laboratory studies, and 2) emissions and secondary production of nitrous acid (HONO). Inclusion of estimated unmeasured VOC leads to a 250% increase in OH reactivity and a 70% increase in radical production via oxygenated VOC photolysis. HONO amplifies radical cycling and serves as a downwind NOX source, although two different HONO production mechanisms (particulate nitrate photolysis and heterogeneous NO2 conversion) exhibit markedly different effects on ozone, NOX, and PNs. Analysis of radical initiation rates suggests that oxygenated VOC photolysis is a major radical source, exceeding HONO photolysis when averaged over the first 2 hours of aging. Ozone production chemistry transitions from VOC-sensitive to NOX-sensitive within the first hour of plume aging, with both peroxide and organic nitrate formation contributing significantly to radical termination. To simulate smoke plume chemistry accurately, models should simultaneously account for the full reactive VOC pool and all relevant oxidant sources.

SEAC4RS↗
NASA NTRSDate not supplied

Atmospheric Variability and Measurement Uncertainty: Pitfalls in Averaging in situ Data

Satellite measurements and atmospheric models, two essential components of the integrated global observing system, provide crucial tools for monitoring and predicting regional and global foci, spanning numerous Earth Science fields. Unfortunately, models can lack the spatial and temporal resolution needed to resolve finer scale structure. Satellite measurements also have similar tempo-spatial restriction issues, but additionally can only measure certain species and can have biases that must be evaluated. Ground measurement networks are critical components of this system, by providing both independent inputs of species needed by models (including those that satellites do not provide) and assisting with investigation of biases in satellite products. Similarly, aircraft measurements play a vital role in closing the gaps between satellite measurements, model products, and ground monitoring networks by providing high accuracy, high-resolution data on local to regional spatial scales. Therefore, both ground-based and airborne observations are widely used to assess model predictions and satellite observations. One of the great challenges in using both ground and aircraft data in this fashion is matching the data temporally and spatially to the model/satellite data. A meaningful comparison with model or satellite requires a solid assessment of the variability of the in-situ measurements, which include both the instrument uncertainty and the statistical uncertainty due to atmospheric variability. While instrument uncertainty is generally more straightforwardly characterized, it can be challenging to accurately capture this variability uncertainty as it often presents in a non-Gaussian manner (e.g. emission plumes, frontal passages). We will present results examining spatial and temporal variability over a selection of scales relevant to satellite measurements and models of several in situ measurement species spanning both airborne and ground measurements. The extent of non-Gaussian variability will be quantified, and we will discuss additional statistical parameters that help assess the fitness of gaussian variability assumption when temporally or spatially averaging.

satellite validation↗