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Claudia Bernier

Publications and source records attributed to Claudia Bernier.

10 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Synthesis Analysis of Mulit-Dimensional Ozone Lidar Measurements in Coastal Environments Toward Improving Ozone Simulation

Large surface ozone variations are frequently observed in coastal regions which makes the modeling of air quality in these regions challenging. The ability to properly model coastal regions relies heavily on the proper detailed observations. There have been three air quality studies (over Chesapeake Bay and the Long Island Sound) that focused on thorough measurements in these complex coastal regions; OWLETS 1 & 2 and LISTOS. Over the course of the campaigns, there were surface ozone observations taken from LIDAR (LIght Detection And Ranging) instruments for a total of 89 days at a high temporal rate. We developed a clustering method that characterizes the multiple timestamps of measurements into a range of ozone events that are specific to these coastal regions. We simulated coastal ozone for these cluster groups using WRF-GC and WRF-Chem to identify gaps within the model. Using the characterized ozone clusters, we were able to identify multiple coastal mechanisms that led to incorrect model simulations.

Claudia Bernier↗
NASA NTRSDate not supplied

Model Evaluation and Intercomparison Using Data Collected by the Langley Mobile Ozone Lidar in Hampton, Virginia

Throughout the year 2022, the Langley Mobile Ozone Lidar (LMOL) has been frequently collecting ozone and aerosol measurements in the lower troposphere. The lidar is located in the parking lot behind the Atmospheric Sciences building at NASA Langley in Hampton, Virginia, approximately 37.095 N, -76.389 W. The data was collected during a range of several distinct atmospheric conditions, including stratospheric intrusions, surface frontal passages, and long-range transported wildfire smoke plumes. We use this data to evaluate and intercompare the forecast accuracy of two atmospheric chemistry models: the GEOS Composition Forecasting model (GEOS-CF) and the Weather Research and Forecasting model with Chemistry (WRF-Chem). Both models make daily three-dimensional forecasts of many trace gases and species for the contiguous United States. Over a range of ten distinct collection events, each spanning 36 hours to nearly seven days, the forecast models predict tropospheric ozone at NASA Langley with reasonable accuracy. The models best predict the timing and shape of the observed stratospheric intrusions in the middle troposphere but often vary in the magnitude of the ozone mixing ratios. For other atmospheric conditions, there is more variability in the model accuracy. Here, we summarize the accuracy of the models for all events and investigate reasons for differences between the models and the lidar.

Daniel B. Phoenix↗
NASA NTRSDate not supplied

Analysis of Atmospheric Conditions Responsible for an Ozone Exceedance Event in Southeast Virginia on June 15, 2022

On June 15, 2022, the Virginia Department of Environmental Quality monitoring site at Suffolk/Holland, a rural site in southeast Virginia, recorded its first ozone exceedance since 2016. An ozone exceedance day occurs when the daily maximum 8-hour average surface ozone concentration is greater than 70 ppb. On this day, it was 75 ppb. This event is also noteworthy due to the rapid increase in surface ozone between 6 am and 9 am EDT as well as the hourly maximum ozone concentration of 82 ppb that was measured at 1 pm EDT. In this analysis, we utilize various observational and model data to determine the atmospheric conditions responsible for this ozone exceedance event. The analysis is conducted in two parts: (1) an evaluation of the accuracy of the GEOS-CF and WRF-Chem model forecasts and (2) an investigation of the mechanisms responsible for the high surface ozone at the Virginia DEQ Suffolk/Holland monitoring site. Comparisons of model forecasted ozone time-height cross sections with measured ozone by lidars from the Tropospheric Ozone Lidar Network (TOLNet) at NASA Langley and NASA Goddard reveal that both models forecasted ozone reasonably well near the surface. Model and observational data reveal that an upper-level ridge was present over much of the eastern United States, with a broad anticyclonic circulation near the surface, resulting in north-northeasterly flow over southeast Virginia. Back trajectory calculations using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) and model data suggest that a low-level plume rich in ozone and precursor species originating from the New York City and New Jersey region was transported along the east coast between June 14 and June 15, arriving in southeast Virginia around 6 am EDT on June 15. In the early morning hours, this plume mixed down to the surface, elevating the background ozone mixing ratio as well as the mixing ratios of several precursor species. Other potential contributions are also explored and discussed. Lastly, the authors note that this work represents the analysis of the authors and not the Virginia Department of Environmental Quality.

Daniel B Phoenix↗
NASA NTRSDate not supplied

Observation of Pollution Events at Low Altitude During TRACER-AQ – The Advantage of Adaptive Resolution Lidar

The TRACER-AQ campaign happened in August-September 2021 in Houston, Texas. Its objective was to better understand the pollution events in the coastal environment and to evaluate models and satellite observations. As a supporting instrument, NASA’s Langley Mobile Ozone Lidar (LMOL) was installed on the Houston campus, adjacent to University of Houston’s air-quality site, and performed observations of ozone and aerosols. Co-located instrumentation included a Pandora spectrophotometer, in-situ trace-gas measurements, and ozonesonde launches. Thanks to an adaptive resolution retrieval scheme, LMOL was able to detect thin-layer O3 structures at low (~200m) altitude that are not captured by the ozonesondes, and would ordinarily be missed with traditional coarse TOLNet lidar vertical averaging. We show that some of these features are not present in the models and are likely coming from local, industry-generated, emissions.

Guillaume Gronoff↗
NASA NTRSDate not supplied

Atmospheric Composition Forecast Model Evaluation Using Ozone Measurements Collected by the Langley Mobile Ozone Lidar

The Langley Mobile Ozone Lidar (LMOL) is a mobile ground based lidar system based at NASA Langley in Hampton, Virginia. Between 2022 and 2024, LMOL collected over 2500 hours of ozone measurements for a range of different atmospheric conditions, including calm days, stratospheric intrusions, surface frontal passages, and long-range transported wildfire smoke plumes. Here, the data is used to evaluate the forecast accuracy of NASA’s Global GEOS Composition Forecasting (GEOS-CF) model. GEOS-CF makes daily three-dimensional forecasts of trace gases and aerosol species. Overall, for calm periods, the forecast model predicts lower tropospheric ozone at NASA Langley with reasonable accuracy (within 20%). The model best predicts the timing and extent of stratospheric intrusions but often vary in the magnitude of the ozone mixing ratio. Among the other types of atmospheric conditions, there is more variability in the model forecasts. Based on this analysis, model forecasts are utilized to determine future data acquisition opportunities with the goal of providing feedback to the modeling teams, thereby enabling them to better understand the model biases and improve the model forecasts of ozone during these different atmospheric conditions.

Daniel B Phoenix↗