Atmospheric & Oceanic Science
Permanent URI for this communityhttp://hdl.handle.net/1903/2264
Formerly known as the Department of Meteorology.
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Item REMOTE SENSING OF ATMOSPHERIC TRACE GASES FROM SPACEBORNE UV MEASUREMENTS(2022) Huang, Xinzhou; Yang, Kai; Dickerson, Russell R.; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Satellite measurements of atmospheric trace gases provide continuous long-term information for monitoring the atmospheric chemical environment and air quality at local, regional, and global scales. Trace gas retrievals play a critical role in chemical data assimilation, air quality modeling and forecast, and regulatory decision-making. In this dissertation, I present retrievals of three trace gases species (O3, SO2, and NO2) from measurements of Ultraviolet (UV) radiation made from the imaging spectrometers onboard operational satellites, including the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR), the Ozone Mapping and Profiler Suite - Nadir Mapper (OMPS-NM) onboard Suomi-NPP (SNPP), and the OMPS-NM onboard NOAA-20 satellite. The retrievals of the trace gas vertical columns are achieved through the Direct Vertical Column Fitting (DVCF) algorithm, which is designed to maximize the absorption signature from the Earth’s atmosphere in the UV spectral range. This dissertation first demonstrates the theoretical basis and mathematical procedures of the DVCF algorithm used for retrieving total vertical columns of ozone (O3) and sulfur dioxide (SO2) from DSCOVR EPIC. We describe algorithm advances, including an improved O3 profile representation that enables profile adjustments from multiple spectral measurements and the spatial optimal estimation (SOE) scheme that reduces O3 artifacts resulted from EPIC’s band-to-band misregistrations. Furthermore, we present detailed error analyses to quantify retrieval uncertainties from various sources, assess EPIC-observed volcanic plumes, and validate O3 and SO2 retrievals with correlative data. The second part of this dissertation presents a suite of efforts to retrieve the tropospheric and stratospheric NO2 vertical columns from the new NOAA-20 OMPS hyperspectral Ultraviolet-Visible (UV-Vis) instrument, covering retrieval algorithm, Stratosphere-Troposphere Separation (STS) scheme, measurement sensitivity assessment, inter-comparison with the Ozone Monitoring Instrument (OMI), evaluation with ground-based Pandora spectrometers, as well as a case study of drastic NO2 changes during COVID-19 pandemic. The third part of my dissertation focuses on validation and algorithm improvements for the tropospheric NO2 retrievals from SNPP OMPS UV measurements. OMPS column NO2 was validated against coincidence measurements from two ground-based MAX-DOAS spectrometers deployed in eastern China. To achieve higher retrieval accuracy, we developed and implemented a series of algorithm improvements, including an explicit aerosol correction scheme to account for changes in measurement sensitivity caused by aerosol scattering and absorption, the replacement of climatological a priori NO2 profile with more accurate NO2 vertical distribution from high-resolution CMAQ model simulations, and the application of model-derived spatial weighting kernel to account for the effect of heterogeneous subpixel distribution. These improvements yield more accurate OMPS NO2 retrievals in better agreement with MAX-DOAS NO2 measurements. The analysis concluded that explicit aerosol correction and a priori profile adjustment are critical for improving satellite NO2 observations in highly polluted regions and spatial downscaling is helpful in resolving NO2 subpixel variations.Item High Resolution Remote Sensing Observations of Summer Sea Ice(2022) Buckley, Ellen Margaret; Farrell, Sinéad L; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)During the Arctic summer melt season, the sea ice transitions from a consolidated ice pack with a highly reflective snow-covered surface to a disintegrating unconsolidated pack with melt ponds spotting the ice surface. The albedo of the Arctic decreases by up to 50%, resulting in increased absorption of solar radiation, triggering the positive sea ice albedo feedback that further enhances melting. Summer melt processes occur at a small scale and are required for melt pond parameterization in models and quantifying albedo change. Arctic-wide observations of melt features were however not available until recently. In this work we develop original techniques for the analysis of high-resolution remote sensing observations of summer sea ice. By applying novel algorithms to data acquired from airborne and satellite sensors onboard IceBridge, Sentinel-2, WorldView and ICESat-2, we derive a set of parameters that describe melt conditions on Arctic sea ice in summer. We present a new, pixel-based classification scheme to identify melt features in high-resolution summer imagery. We apply the classification algorithm to IceBridge Digital Mapping System data and find a greater melt pond fraction (25%) on sea ice in the Beaufort and Chukchi Seas, a region consisting of predominantly first year ice, compared to the Central Arctic, where the melt pond fraction is 14% on predominantly multiyear ice. Expanding the study to observations acquired by the Sentinel-2 Multispectral Instrument, we track the variability in melt pond fraction and sea ice concentration with time, focusing on the anomalously warm summer of 2020. So as to obtain a three-dimensional view of the evolution of summer melt we also exploit ICESat-2 surface elevation measurements. We develop and apply the Melt Pond Algorithm to track ponds in ICESat-2 photon cloud data and derive their depth. Pond depth measurements in conjunction with melt pond fraction and sea ice concentration provide insights into the regional patterns and temporal evolution of melt on summer sea ice. We found mean melt pond fraction increased rapidly in the beginning of the melt season, peaking at 16% on 24 June 2020, while median pond depths increased steadily from 0.4 m at the beginning of the melt season, to peaking at 0.97 m on 16 July, even as melt pond fraction had begun to decrease. Our findings may be used to improve parameterization of melt processes in models, quantify freshwater storage, and study the partitioning of under ice light.Item A 20-YEAR CLIMATOLOGY OF GLOBAL ATMOSPHERIC METHANE FROM HYPERSPECTRAL THERMAL INFRARED SOUNDERS WITH SOME APPLICATIONS(2022) Zhou, Lihang; Warner, Juying; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Atmospheric Methane (CH4) is the second most important greenhouse gas after carbon dioxide (CO2), and accounts for approximately 20% of the global warming produced by all well-mixed greenhouse gases. Thus, its spatiotemporal distributions and relevant long-term trends are critical to understanding the sources, sinks, and global budget of atmospheric composition, as well as the associated climate impacts. The current suite of hyperspectral thermal infrared sounders has provided continuous global methane data records since 2002, starting with the Atmospheric Infrared Sounder (AIRS) onboard the NASA EOS/Aqua satellite launched on 2 May 2002. The Cross-track Infrared Sounder (CrIS) was launched onboard the Suomi National Polar Orbiting Partnership (SNPP) on 28 October 2011 and then on NOAA-20 on 18 November 2017. The Infrared Atmospheric Sounding Interferometer (IASI) was launched onboard the EUMETSAT MetOp-A on 19 October 2006, followed by MetOp-B on 17 September 2012, then Metop-C on 7 November 2018. In this study, nearly two decades of global CH4 concentrations retrieved from the AIRS and CrIS sensors were analyzed. Results indicate that the global mid-upper tropospheric CH4 concentrations (centered around 400 hPa) increased significantly from 2003 to 2020, i.e., with an annual average of ~1754 ppbv in 2003 and ~1839 ppbv in 2020. The total increase is approximately 85 ppbv representing a +4.8% change in 18 years. More importantly, the rate of increase was derived using satellite measurements and shown to be consistent with the rate of increase previously reported only from in-situ observational measurements. It further confirmed that there was a steady increase starting in 2007 that became stronger since 2014, as also reported from the in-situ observations. In addition, comparisons of the methane retrieved from the AIRS and CrIS against in situ measurements from NOAA Global Monitoring Laboratory (GML) were conducted. One of the key findings of this comparative study is that there are phase shifts in the seasonal cycles between satellite thermal infrared measurements and ground measurements, especially in the middle to high latitudes in the northern hemisphere. Through this, an issue common in the hyperspectral thermal sensor retrievals were discovered that was unknown previously and offered potential solutions. We also conducted research on some applications of the retrieval products in monitoring the changes of CH4 over the selected regions (the Arctic and South America). Detailed analyses based on local geographic changes related to CH4 concentration increases were discussed. The results of this study concluded that while the atmospheric CH4 concentration over the Arctic region has been increasing since the early 2000s, there were no catastrophic sudden jumps during the period of 2008-2012, as indicated by the earlier studies using pre-validated retrieval products. From our study of CH4 climatology using hyperspectral infrared sounders, it has been proved that the CH4 from hyperspectral sounders provide valuable information on CH4 for the mid-upper troposphere and lower stratosphere. Future approaches are suggested that include: 1) Utilizing extended data records for CH4 monitoring using AIRS, CrIS, and other potential new generation hyperspectral infrared sensors; 2). Improving the algorithms for trace gas retrievals; and 3). Enhancing the capacity to detect CH4 changes and anomalies with radiance signals from hyperspectral infrared sounders.Item APPLICATIONS OF THE OZONE MONITORING INSTRUMENT IN OBSERVING VOLCANIC SULFUR DIOXIDE PLUMES AND SULFATE DEPOSITION(2021) Fedkin, Niko Markovich; Dickerson, Russell R; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Sulfur dioxide (SO2), a gas emitted by both volcanoes and anthropogenic activity, is a major pollutant and a precursor to sulfate aerosols. Sulfates can be deposited back to the ground where they have adverse impact on the environment or reside in the stratosphere as aerosols and affect radiative forcing. I investigated two components that stem from SO2: the deposition of sulfate, and the remote sensing of the SO2 layer height, important for aviation safety and chemical modeling. In the first study, I used column SO2 data from the Ozone Monitoring Instrument (OMI), and sulfate wet deposition data from the National Atmospheric Deposition Program to investigate the temporal and spatial relationship between trends in SO2 emissions and the downward sulfate wet deposition over the northeastern U.S. from 2005 to 2015. The results showed that emission reductions are reflected in deposition reductions within this same region. Emission reductions along the Ohio River Valley led to decreases in sulfate deposition not only in eastern OH and western PA, but also further downwind at sites in Delaware and Maryland. The findings suggested that emissions and wet deposition are linked through not only the location of sources relative to the observing sites, but also photochemistry and weather patterns characteristic to the region in winter and summer. The second part of this dissertation focuses on SO2 layer height retrievals and their applications. To this end I applied the Full Physics Inverse Learning Machine (FP-ILM) algorithm to OMI radiances in the spectral range of 310-330 nm. This approach utilized radiative transfer calculations to generate a large dataset of synthetic radiance spectra for a wide range of geophysical parameters. The spectral information was then used to train a neural network to predict the SO2 height. The main advantage of the algorithm is its speed, retrieving plume height in less than 10 min for an entire OMI orbit. I also compared the SO2 height retrievals to other data sources and explored some potential applications, in particular their use in volcanic SO2 plume forecasts and estimating the total mass emitted from volcanic eruptions.Item RETRIEVALS OF ANTARCTIC SEA ICE PHYSICAL PROPERTIES FROM SATELLITE RADAR ALTIMETRY(2021) Fons, Steven William; Carton, James; Kurtz, Nathan; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Satellite observations have been used in sea ice research throughout the last 40+ years and have brought to light substantial changes in the global sea ice coverage. More recently, satellite altimetry has become a valuable tool to estimate the thickness of sea ice - a parameter that plays an important role in the Earth System by moderating heat and moisture fluxes between the polar ocean and atmosphere. While radar altimetry has been effective in providing estimates of Arctic sea ice thickness, the complex snow stratigraphy and uncertain snow depth on Antarctic sea ice have precluded sea ice thickness retrievals in the Southern Ocean, leading to a decade-long gap in the thickness record spanning the lifetime of ESA’s CryoSat-2 satellite. This dissertation will address the need for Antarctic sea ice thickness estimates from CryoSat-2 through the development and assessment of new retrievals of sea ice physical properties that enable the estimation of sea ice thickness.The first part of this dissertation is aimed at developing a CryoSat-2 retrieval algorithm that is less dependent on uncertain returns from the snow-ice interface of Antarctic sea ice. This method exploits observed scattering of Ku-band radar pulses from the snow surface and snow volume atop sea ice and uses a physical waveform model and optimization approach to retrieve the air-snow interface elevation and snow freeboard. Building off the initial development, the second part of this work offers improvements to – and assessments of – the retrieval process though comparisons with coincident snow freeboard measurements from NASA’s ICESat-2 laser altimeter. The final part of this dissertation uses the retrieval process to estimate snow depth and ice freeboard, enabling first estimates of Antarctic sea ice thickness that span the CryoSat-2 mission. Potential applications for use of this method over Arctic sea ice are also explored. The studies within this dissertation represent new possibilities for CryoSat-2 data and lay a foundation for the development of a combined laser-radar altimetric record of Antarctic sea ice thickness.Item Satellite Remote Sensing of Smoke Particle Optical Properties, Their Evolution and Controlling Factors(2021) Junghenn, Katherine Teresa; Li, Zhanqing; Kahn, Ralph A.; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood, nor are those driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem and ambient conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging Spectrometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD), and to provide constraints on plume vertical extent, smoke age, and particle size, shape, light-absorption, and absorption spectral dependence. These capabilities are evaluated using near-coincident in situ data from two aircraft field campaigns. Results indicate that the satellite retrievals successfully map particle-type distributions, and that the observed trends in retrieved particle size and light-absorption can be reliably attributed to aging processes such as gravitational settling, oxidation, secondary particle formation, and condensational growth. The remote-sensing methods are then applied to numerous wildfire plumes in Canada and Alaska that are not constrained by field observations. For these plumes, satellite measurements of fire radiative power and land cover characteristics are also collected, as well as short-term meteorological data and drought index. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the tallest and thickest plumes containing the largest, brightest particles, and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution, over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.