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Anne M Thompson

Publications and source records attributed to Anne M Thompson.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2026

SCOAPE-II: A 2024 Multiplatform Measurement Campaign off the US Gulf Coast to Assess Oil and Gas Emissions on the Outer Continental Shelf

Nine years ago, the Department of Interior’s Bureau of Ocean Energy Management (BOEM), the Agency with Air Quality (AQ) jurisdiction over the Outer Continental Shelf (OCS) of the US Gulf Coast west of 87.5° W longitude, asked NASA to determine the feasibility of using satellite data to measure offshore emissions in a region of concentrated oil and natural gas (ONG) operations. To study this issue NASA and BOEM conducted the May 2019 Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE) cruise in the Gulf. SCOAPE addressed both technological and scientific issues related to measuring nitrogen dioxide (NO 2 , a common air pollutant), including contrasting near-shore and deepwater regimes. Given the April 2023 launch of the geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO) AQ satellite, a 2024 SCOAPE-II was conducted in the Gulf with both ship and aircraft measurements. We present an overview of the SCOAPE-II campaign, analysis and validation of satellite-observed NO 2 , and evaluate measurements of methane from ship, aircraft, and satellite near ONG platforms. Our SCOAPE-II results are as follows: 1) Satellite NO 2 measurements (∼13:30 local time) from the TROPOspheric Monitoring Instrument (TROPOMI) are more accurate than TEMPO’s hourly scans (8.6% vs. 23.6% mean absolute bias); a new version of TEMPO data is currently being processed; 2) ship and aircraft measurements captured dozens of NO 2 and methane plumes from ONG operations, showing that they are persistent emitters; 3) satellite measurements of methane failed to replicate ship and aircraft measurements, presenting ongoing challenges for operational emissions monitoring over the Gulf.

satellite validation↗
NASA NTRS2024

Satellite NO 2 Trends and Hotspots Over Offshore Oil and Gas Operations in the Gulf of Mexico

The Outer Continental Shelf of the Gulf of Mexico (GOM) is populated with numerous oil and natural gas (ONG) platforms which produce NO x (NO x = NO + NO 2 ), a major component of air pollution. The Bureau of Ocean Energy Management (BOEM) is mandated to ensure that the air quality of coastal states is not degraded by these emissions. As part of a NASA-BOEM collaboration, we conducted a satellite data-based analysis of nitrogen dioxide (NO 2 ) patterns and trends in the GOM. Data from the OMI and TROPOMI sensors were used to obtain 18+ year records of tropospheric column (TrC) NO 2 in three GOM regions: (a) Houston urban area, (b) near shore area off the Louisiana coast, and a (c) deepwater area off the Louisiana coast. The 2004–2022 time series show a decreasing trend for the urban (−0.027 DU/decade) and near shore (−0.0022 DU/decade) areas, and an increasing trend (0.0019 DU/decade) for the deepwater area. MERRA-2 wind and TROPOMI NO 2 data were used to reveal several NO2 hotspots (up to 25% above background values) under calm wind conditions near individual platforms. The NO 2 signals from these deepwater platforms and the high density of shallow water platforms closer to shore were confirmed by TrC NO 2 anomalies of up to 10%, taking into account the monthly TrC NO 2 climatology over the GOM. The results presented in this study establish a baseline for future estimates of emissions from the ONG hotspots and provide a methodology for analyzing NO 2 measurements from the new geostationary TEMPO instrument.

NO2↗
NASA NTRS2023

Interpretation of Probabilistic Surface Ozone Forecasts: A Case Study for Philadelphia

The use of probabilistic forecasting has been growing in a variety of disciplines because of its potential to emphasize the degree of uncertainty inherent in a prediction. Interpretation of probabilistic forecasts, however, is oftentimes difficult, deterring users who may benefit from such forecasts. To encourage broader use of probabilistic forecasts in the field of air quality, a process for interpreting forecasts from a statistical probabilistic air quality surface ozone model [the Regression in Self Organizing Map (REGiS)] is demonstrated. Four procedures to convert probabilistic to deterministic forecasts are explored for the Philadelphia, Pennsylvania, metropolitan area. These procedures calibrate the predicted probability of daily maximum 8-h-average ozone exceeding a standard value by 1) estimating climatological relative frequency, 2) establishing a probability of an exceedance threshold as 50%, 3) maximizing the threat score, and 4) determining the unit bias ratio. REGiS is trained using 2000–11 ozone-season (1 May–30 September) data, calibrated using 2012–14 data, and evaluated using 2015–18 data. Assessment of the calibration data with the Pierce skill score suggests an exceedance threshold based on climatological relative frequency for the conversion from probabilistic to deterministic forecasts. Calibrated REGiS generally compares well to predictions from the U.S. national air quality model and operational “expert” forecasts over the evaluation period. For other probabilistic models and situations, different procedures of converting probabilistic to deterministic forecasts may be more beneficial. The methods presented in this paper represent an approach for operational air quality forecasters seeking to use probabilistic model output to support forecasts designed to protect public health.

Nikolay Balashov↗
NASA NTRS2023

Two Air Quality Regimes in Total Column NO2 over the Gulf of Mexico in May 2019: Shipboard and Satellite Views

The Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE) cruise in the Gulf of Mexico was conducted in May 2019 by NASA and the Bureau of Ocean Energy Management to determine the feasibility of using satellite data to measure air quality in a region of concentrated oil and natural gas (ONG) operations. SCOAPE addressed both technological and scientific issues related to measuring NO2 columns over the Outer Continental Shelf. Featured were nitrogen dioxide (NO 2 ) instruments (Pandora, Teledyne API analyzer) at Cocodrie, LA (29.26°, -90.66°), and on the Research Vessel Point Sur operating off the Louisiana coast with measurements of ozone, carbon monoxide and volatile organic compounds (VOC). The findings: (1) All NO 2 observations revealed two atmospheric regimes over the Gulf, the first influenced by tropical air in 10-14 May, the second influenced by flow from urban areas on 15-17 May; (2) Comparisons of OMI v4 and TROPOMI v1.3 TC (total column) NO 2 data with shipboard Pandora NO 2 column observations averaged 13% agreement with the largest difference during 15-17 May (~20%). At Cocodrie, the satellite-Pandora agreement was ~5%. (3) Three new-model Pandora instruments displayed a TC NO 2 precision of 0.01 Dobson Units (~5%); (4) Regions of smaller, older natural gas operations showed high methane readings from leakage; elevated VOC were also detected. Neither satellite nor spectrometer captured the magnitude of ambient NO 2 variability near ONG platforms. Given an absence of regular air quality monitoring over the Gulf of Mexico, SCOAPE data constitute a baseline against which future observations can be compared.

Nitrogen dioxide↗
NASA NTRS2022

Comment on "Observation of Large and All-Season Ozone Losses Over the Tropics" [AIP Advances 12, 075066 (2022)]

As discussed above, and supported by extensive literature, there is no robust, credible observational evidence for substantial ozone depletion (i.e., an “ozone hole”) in the tropics. It is well known that climatological total ozone in the tropics is much lower than that in the mid-latitudes (e.g., Sahai et al., 2000; Weber et al., 2022). Satellite and ozonesonde measurements indicate a 3%–5% per decade decline of tropical lower stratosphere ozone prior to 2000, far smaller than that reported by L2022. The stronger decline reported by L2022 is caused by inappropriate use of the gap-filled version of the TOST ozone dataset, which is based on sparse tropical ozone sondes before the 1990s. This misuse of data (TOST and total column ozone) shows the importance of collaboratively engaging with groups who obtain the measurements and create climatological datasets before performing such analyses. Furthermore, the study by L2022 has multiple flaws in its discussion of atmospheric chemistry and dynamics, particularly in the proposed, and previously refuted (see Sec. III A), cosmicray- driven electron induced (CRE) mechanism. Evidence for the occurrence of tropical stratospheric clouds, as needed for the tropical CRE mechanism, is lacking, nor do CFC-12 observations show signatures of depletion in the tropical lower stratosphere, which could be associated with dissociative electron attachment-induced loss of CFC-12 on particulate matter (i.e., the CRE mechanism). Finally, it is worth reiterating that the CRE mechanism is also not responsible for polar LS ozone depletion. Polar ozone loss can be well explained by the gas phase and heterogeneous chemistry, based on extensive observations and modeling studies documented in many thousands of scientific papers on the topic [e.g., see WMO (2018) and references therein], which is not acknowledged by L2022. L2022’s research paper is a severely flawed one. There is no tropical ozone hole, and the CRE mechanism does not explain observed changes in stratospheric ozone either in the polar regions or in the tropics.

Quality assurance↗
NASA NTRS2020

A New Method to Correct the Electrochemical Concentration Cell (ECC) Ozonesonde Time Response and its Implications for "Background Current" and Pump Efficiency

The electrochemical concentration cell (ECC) ozonesonde has been the main instrument for in situ profiling of ozone worldwide; yet, some details of its operation, which contribute to the ozone uncertainty budget, are not well understood. Here, we investigate the time response of the chemical reactions inside the ECC and how corrections can be used to remove some systematic biases. The analysis is based on the understanding that two reaction pathways involving ozone occur inside the ECC that generate electrical currents on two very different timescales. The main fast-reaction pathway with a time constant of about 20 s is due the conversion of iodide to molecular iodine and the generation of two free electrons per ozone molecule. A secondary slow-reaction pathway involving the buffer generates an excess current of about 2 %–10 % with a time constant of about 25 min. This excess current can be interpreted as what has conventionally been considered the “background current”. This contribution can be calculated and removed from the measured current instead of the background current. Here we provide an algorithm to calculate and remove the contribution of the slow-reaction pathway and to correct for the time lag of the fast-reaction pathway. This processing algorithm has been applied to ozonesonde profiles at Costa Rica and during the Central Equatorial Pacific Experiment (CEPEX) as well as to laboratory experiments evaluating the performance of ECC ozonesondes. At Costa Rica, where a 1 % KI, 1/10th buffer solution is used, there is no change in the derived total ozone column; however, in the upper troposphere and lower stratosphere, average reported ozone concentrations increase by up to 7 % and above 30 km decrease by up to 7 %. During CEPEX, where a 1 % KI, full-buffer solution was used, ozone concentrations are increased mostly in the upper troposphere, with no change near the top of the profile. In the laboratory measurements, the processing algorithms have been applied to measurements using the majority of current sensing solutions and using only the stronger pump efficiency correction reported by Johnson et al. (2002). This improves the accuracy of the ECC sonde ozone profiles, especially for low ozone concentrations or large ozone gradients and removes systematic biases relative to the reference instruments. In the surface layer, operational procedures prior to launch, in particular the use of filters, influence how typical gradients above the surface are detected. The correction algorithm may report gradients that are steeper than originally reported, but their uncertainty is strongly influenced by the prelaunch procedures.

electrochemical concentration cell (ECC) ozonesond↗
NASA NTRS2020

Evaluation of NASA’s Remote-Sensing Capabilities in Coastal Environments

This work represents the second part of a two-part study set up by the National Aeronautics and Space Administration (NASA) and Bureau of Ocean Energy Management (BOEM) in 2017. The study summarizes a three-year investigation on the feasibility of using satellite remote sensing to monitor emissions of oil and gas operations over the outer continental shelf (OCS) to determine if they have negative impacts on coastal air quality (AQ). The target pollutant is nitrogen dioxide (NO2), for which BOEM conducts regular emissions surveys. The major data source for this report is a May 2019 oceanographic cruise (“SCOAPE” = Satellite Coastal and Oceanic Atmospheric Pollution Experiment) conducted in the Gulf of Mexico (GoM) off Louisiana with the Research Vessel Point Sur, loaded with a suite of trace-gas analyzers and a direct-sun remote sensor Pandora spectrometer that measures column NO2. The SCOAPE cruise, augmented by in situ NO2 and Pandora measurements at Cocodrie (Louisiana; 29.25° N, 90.66° W) showed that (1) under cloud-free conditions, satellites can detect elevated column NO2 amounts near isolated large platforms and from clusters of smaller operations; (2) satellite (the European Space Agency’s TROPOspheric Monitoring Instrument [TROPOMI]) total column (TC) NO2 agrees well with TC NO2 from ground-based Pandora spectrometers (to 11–18%), with the satellite biased low when pollution levels are higher; (3) in general, NO2 measured in situ and in column amounts by Pandora or TROPOMI is greater over coastal Louisiana than over the OCS; (4) the extent to which Pandora or satellite measurements correlate with surface NO2 is highly variable.

NO2↗
NASA NTRS2020

Statistical Analysis of Factors Riving Surface Ozone Variability over Continental South Africa

Statistical relationships between surface ozone (O3) concentration, precursor species and meteorological conditions in continental South Africa were examined from data obtained from measurement stations in north-eastern South Africa. Three multivariate statistical methods were applied in the investigation, i.e. multiple linear regression (MLR), principal component analysis (PCA) and –regression (PCR), and generalised additive model (GAM) analysis. The daily maximum 8-h moving average O3 concentrations were considered in these statistical models (dependent variable). MLR models indicated that meteorology and precursor species concentrations are able to explain ~50% of the variability in daily maximum O3 levels. MLR analysis revealed that atmospheric carbon monoxide (CO), temperature and relative humidity were the strongest factors affecting the daily O3 variability. In summer, daily O3 variances were mostly associated with relative humidity, while winter O3 levels were mostly linked to temperature and CO. PCA indicated that CO, temperature and relative humidity were not strongly collinear. GAM also identified CO, temperature and relative humidity as the strongest factors affecting the daily variation of O3. Partial residual plots found that temperature, radiation and nitrogen oxides most likely have a non-linear relationship with O3,while the relationship with relative humidity and CO is probably linear. An inter-comparison between O3 levels modelled with the three statistical models compared to measured O3 concentrations showed that the GAM model offered a slight improvement over the MLR model. These findings emphasise the critical role of regional-scale O3 precursors coupled with meteorological conditions in daily variances of O3 levels in continental South Africa.

multiple linear regression (MLR)↗
NASA NTRS2020

Validation of SAGE III/ISS Solar Ozone Data with Correlative Satellite and Ground Based Measurements

The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) was launched on February 19, 2017 and began routine operation in June 2017. The first two years of SAGE III/ISS (v5.1) solar ozone data were evaluated by using correlative satellite and ground-based measurements. Among the three (MES, AO3, and MLR) SAGE III/ISS solar ozone products, AO3 ozone shows the best accuracy and precision, with mean biases less than 5% for altitudes ~15–55 km in the mid-latitudes and ~20–55 km in the tropics. In the lower stratosphere and upper troposphere, AO3 ozone shows high biases that increase with decreasing altitudes and reach ~10% near the tropopause. Preliminary studies indicate that those high biases primarily result from the contributions of the oxygen dimer (O4) not being appropriately removed within the ozone channel. The precision of AO3 ozone is estimated to be ~3% for altitudes between 20 and 40 km. It degrades to ~10–15% in the lower mesosphere (~55 km), and ~20–30% near the tropopause. There could be an altitude registration error of ~100 meter in the SAGE III/ISS auxiliary temperature and pressure profiles. This, however, does not affect retrieved ozone profiles in native number density on geometric altitude coordinates. In the upper stratosphere and lower mesosphere (~40–55 km) the SAGE III/ISS (and SAGE II) sunset ozone values are systematically higher than sunrise data by ~5–8% which are almost twice larger than what observed by other satellites or model predictions. This feature needs further study.

H J Wang↗
NASA NTRS2020

A Post-2013 Dropoff in Total Ozone at a Third of Global Ozonesonde Stations: Electrochemical Concentration Cell Instrument Artifacts?

An international effort to improve ozonesonde data quality and to reevaluate historical recordshas made significant improvements in the accuracy of global network data. However, between 2014 and2016, ozonesonde total column ozone (TCO; O3) at 14 of 37 regularly reporting stations exhibited a suddendropoff relative to satellite measurements. The ozonesonde TCO drop is 3–7% compared to satellite andground‐based TCO, and 5–10% or more compared to satellite stratospheric O3profiles, compromising theuse of recent data for trends, although they remain reliable for other uses. Hardware changes in theozonesonde instrument are likely a major factor in the O3dropoff, but no single property of the ozonesondeexplains thefindings. The bias remains in recent data. Research to understand the dropoff is in progress; thisletter is intended as a caution to users of the data. Ourfindings underscore the importance of regularozonesonde data evaluation.

ozonesonde TCO drop↗
NASA NTRS2019

Tropospheric Ozone Assessment Report: Tropospheric Ozone From 1877 to 2016, Observed Levels, Trends and Uncertainties

From the earliest observations of ozone in the lower atmosphere in the 19th century, both measurement methods and the portion of the globe observed have evolved and changed. These methods have different uncertainties and biases, and the data records differ with respect to coverage (space and time), information content, and representativeness. In this study, various ozone measurement methods and ozone datasets are reviewed and selected for inclusion in the historical record of background ozone levels, based on relationship of the measurement technique to the modern UV absorption standard, absence of interfering pollutants, representativeness of the well-mixed boundary layer and expert judgement of their credibility. There are significant uncertainties with the 19th and early 20th-century measurements related to interference of other gases. Spectroscopic methods applied before 1960 have likely underestimated ozone by as much as 11% at the surface and by about 24% in the free troposphere, due to the use of differing ozone absorption coefficients. There is no unambiguous evidence in the measurement record back to 1896 that typical mid-latitude background surface ozone values were below about 20 nmol mol–1, but there is robust evidence for increases in the temperate and polar regions of the northern hemisphere of 30–70%, with large uncertainty, between the period of historic observations, 1896–1975, and the modern period (1990–2014). Independent historical observations from balloons and aircraft indicate similar changes in the free troposphere. Changes in the southern hemisphere are much less. Regional representativeness of the available observations remains a potential source of large errors, which are difficult to quantify. The great majority of validation and intercomparison studies of free tropospheric ozone measurement methods use ECC ozonesondes as reference. Compared to UV-absorption measurements they show a modest (~1–5% ±5%) high bias in the troposphere, but no evidence of a change with time. Umkehr, lidar, and FTIR methods all show modest low biases relative to ECCs, and so, using ECC sondes as a transfer standard, all appear to agree to within one standard deviation with the modern UV-absorption standard. Other sonde types show an increase of 5–20% in sensitivity to tropospheric ozone from 1970–1995. Biases and standard deviations of satellite retrieval comparisons are often 2–3 times larger than those of other free tropospheric measurements. The lack of information on temporal changes of bias for satellite measurements of tropospheric ozone is an area of concern for long-term trend studies.

UV absorption standard↗
NASA NTRS2019

The Effects of a 1998 Observing System Change on MERRA-2-Based Ozone Profile Simulations

Model simulations of ozone (O3) driven by meteorological reanalyses are useful for filling observational gaps and interpreting observed O3 variability and trends. However, the transport circulation of reanalysis products is impacted by changes to the observing system (the data assimilated into the reanalyses). We examine the impacts of these changes on simulated O3 from two models, Global Modeling Initiative (GMI) Chemistry Transport Model (GMI CTM) and Modern‐Era Retrospective Analysis for Research Applications version 2 (MERRA‐2) GMI Replay (M2 GMI Replay) simulation, using observations from global ozonesondes (>50,000 profiles) and satellites from 1980 to 2016. Both models are constrained by meteorology from the NASA MERRA‐2 reanalysis, and both use versions of NASA's GMI chemical mechanism. We focus on an observing system change affecting simulated O3 after 1998, associated with the assimilation of temperature and humidity data from new microwave profiling satellites. A large post‐1998 O3 increase, mainly confined to 15–20‐km altitude, of ~10 Dobson units (DU) in midlatitudes occurs in the GMI CTM, worsening the bias compared to observations. In contrast, an increase in M2 GMI Replay simulation O3 of ~10 DU is observed only near −60° latitude, reducing the bias compared to observations. The GMI CTM O3 high biases display a Quasi‐Biennial Oscillation (QBO)‐like periodicity that result from excessive transport from the tropical stratosphere to the midlatitude lower stratosphere during the QBO westerly phase. We quantify O3 discontinuities caused by MERRA‐2 observing system changes and demonstrate how the MERRA‐2 Global Modeling Initiative Replay simulation dampens the effects of these changes and QBO‐driven artifacts on simulated lower stratospheric and total O3. We caution against using simulations driven by a reanalysis to derive multidecadal O3 trends, especially prior to 1998.

Replay↗
NASA NTRSDate not supplied

Regional and Seasonal Trends in Tropical Ozone from SHADOZ Profiles: Reference for Models and Satellite Products

Understanding lowermost stratosphere (LMS) ozone variability is an important topic in the trends and climate assessment communities because of feedbacks among changing temperature, dynamics, water vapor and ozone. LMS evaluations are usually based on satellite observations. Free tropospheric (FT) ozone assessments typically rely on profiles from commercial aircraft. Ozonesonde measurements constitute an independent dataset encompassing both LMS and FT. We used Southern Hemisphere Additional Ozonesondes (SHADOZ) data from 1998-2019 in the GSFC Multiple Linear Regression (MLR) model to analyze monthly mean FT and LMS ozone across five well-distributed tropical sites, three based on combination of nearby individual stations (Figure 1). Our findings: (1) both FT (defined as 5-15 km) and LMS (15-20 km) ozone trends exhibit marked regional and seasonal variability. (2) Stations with the largest FT ozone increases, in the equatorial Americas and western Pacific/east Indian Ocean, show these trends most strongly in February-May when there is convectively-driven wave activity. (3) LMS ozone losses are greatest in the 2nd half of the year (solid lines in Figure 2) when the losses are correlated with an increase in tropopause height (TH) as derived from SHADOZ radiosonde data. ( 4) When the upper FT and LMS are defined by tropopause-relative coordinates, the LMS ozone trend calculated by MLR becomes insignificant, as shown in the dashed lines in Figure 2. Thus, the 20-year decline in tropical LMS ozone reported in recent satellite- and model-based studies does not point to a chemical loss but is rather a signature of a tropopause that has been perturbed by a changing climate. Output based on our regional and monthly averaged FT and LMS ozone trends will be available as a reference for satellite- and model-based analyses.

Free Tropospheric (FT) ozone assessments↗
NASA NTRSDate not supplied

Homogenized Ground-Based and Profile Ozone Datasets From the TOAR-II/HEGIFTOM Project: Methods and Station Trends

Within the framework of the second phase of the Tropospheric Ozone Assessment Report (TOAR-II), it was recognized that an essential first step for deriving accurate trends from the ground-based networks that monitor ozone in the free troposphere is putting the measurements on the same basis with respect to absolute references and processing methods. The relevant procedures are referred to as “harmonization” or “homogenization”. The TOAR II working group, “HEGIFTOM” (Harmonization and Evaluation of Ground-based Instruments for Free-Tropospheric Ozone Measurements), has carried out harmonization for five types of network (Figure below) instruments (mid-1990s to 2020): ozonesondes, commercial aircraft IAGOS landing/takeoff profiles, Fourier-Transform Infrared spectrometer (FTIR), tropospheric Lidar, and Brewer/Dobson Umkehr. First, we summarize the homogenization effort for each network that provides new quality-assessed ozone profile or segment (partial column) data sets, including uncertainty estimates and quality flags. Second, with the HEGIFTOM datasets forming the basis for a global assessment of tropospheric ozone column trends, results derived with various trend detection algorithms will be presented. The ultimate goal is evaluation of the consistency of the calculated trends among different techniques at selected stations and/or regions.

ozone↗