Fendrock
Michaela
Fendrock
Michaela
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ArticleA geostatistical framework for quantifying the imprint of mesoscale atmospheric transport on satellite trace gas retrievals(American Geophysical Union, 2019-07-29) Torres, Anthony D. ; Keppel-Aleks, Gretchen ; Doney, Scott C. ; Fendrock, Michaela ; Luis, Kelly M. A. ; De Mazière, Martine ; Hase, Frank ; Petri, Christof ; Pollard, David ; Roehl, Coleen M. ; Sussmann, Ralf ; Velazco, Voltaire A. ; Warneke, Thorsten ; Wunch, DebraNational Aeronautics and Space Administration's Orbiting Carbon Observatory‐2 (OCO‐2) satellite provides observations of total column‐averaged CO2 mole fractions (XCO2 ) at high spatial resolution that may enable novel constraints on surface‐atmosphere carbon fluxes. Atmospheric inverse modeling provides an approach to optimize surface fluxes at regional scales, but the accuracy of the fluxes from inversion frameworks depends on key inputs, including spatially and temporally dense CO2 observations and reliable representations of atmospheric transport. Since XCO2 observations are sensitive to both synoptic and mesoscale variations within the free troposphere, horizontal atmospheric transport imparts substantial variations in these data and must be either resolved explicitly by the atmospheric transport model or accounted for within the error covariance budget provided to inverse frameworks. Here, we used geostatistical techniques to quantify the imprint of atmospheric transport in along‐track OCO‐2 soundings. We compare high‐pass‐filtered (<250 km, spatial scales that primarily isolate mesoscale or finer‐scale variations) along‐track spatial variability in XCO2 and XH2O from OCO‐2 tracks to temporal synoptic and mesoscale variability from ground‐based XCO2 and XH2O observed by nearby Total Carbon Column Observing Network sites. Mesoscale atmospheric transport is found to be the primary driver of along‐track, high‐frequency variability for OCO‐2 XH2O. For XCO2 , both mesoscale transport variability and spatially coherent bias associated with other elements of the OCO‐2 retrieval state vector are important drivers of the along‐track variance budget.
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ArticleA comprehensive global oceanic dataset of helium isotope and tritium measurements.(Copernicus Publications, 2019-04-05) Jenkins, William J. ; Doney, Scott C. ; Fendrock, Michaela ; Fine, Rana A. ; Gamo, Toshitaka ; Jean-Baptiste, Philippe ; Key, Robert M. ; Klein, Birgit ; Lupton, John E. ; Newton, Robert ; Rhein, Monika ; Roether, Wolfgang ; Sano, Yuji ; Schlitzer, Reiner ; Schlosser, Peter ; Swift, James H.Tritium and helium isotope data provide key information on ocean circulation, ventilation, and mixing, as well as the rates of biogeochemical processes and deep-ocean hydrothermal processes. We present here global oceanic datasets of tritium and helium isotope measurements made by numerous researchers and laboratories over a period exceeding 60 years. The dataset's DOI is https://doi.org/10.25921/c1sn-9631, and the data are available at https://www.nodc.noaa.gov/ocads/data/0176626.xml (last access: 15 March 2019) or alternately http://odv.awi.de/data/ocean/jenkins-tritium-helium-data-compilation/ (last access: 13 March 2019) and includes approximately 60 000 valid tritium measurements, 63 000 valid helium isotope determinations, 57 000 dissolved helium concentrations, and 34 000 dissolved neon concentrations. Some quality control has been applied in that questionable data have been flagged and clearly compromised data excluded entirely. Appropriate metadata have been included, including geographic location, date, and sample depth. When available, we include water temperature, salinity, and dissolved oxygen. Data quality flags and data originator information (including methodology) are also included. This paper provides an introduction to the dataset along with some discussion of its broader qualities and graphics.
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ThesisQuestions and clarity: insights from applying computational methods to paleoclimate archives(Massachusetts Institute of Technology and Woods Hole Oceanographic Institution, 2022-05) Fendrock, Michaela ; McGee, David ; Condron, AlanIt is a scientifically accepted fact that the Earth’s climate is presently undergoing significant changes with the potential for immense negative impacts on human society. As evidence of these impacts become clear and common, it becomes ever more important to constrain the nature, magnitude, and speed of changes to Earth systems. A fundamentally important tool to this understanding is the Earth’s past, recorded in the geologic record. There, lie examples of climate change under various forcings: important data for understanding the fundamental dynamics of climate change on our planet. However, when a climate signal is written in the geologic record, it is coded into the language of proxies and distorted by time. This thesis endeavors to decode that record using a variety of computational methods on a number of challenging proxies, to draw more information from the climate past than has previously been possible. First, machine learning and computer vision are used to decipher the primary, centimeter-scale textures of carbonate deposits in Searles Valley and Mono Lake, California. This work is able to connect facies in the tufa at Searles, grown during the Last Glacial Period, and those forming presently at Mono Lake. Next, the tracks of icebergs purged during Heinrich Events are simulated using the MIT General Circulation Model. This work, running multiple experiments exploring different aspects internal and external to the icebergs, reveals wind and sediment partitioning as centrally important to the spatial extent of Heinrich Layers. Each of these works considers a traditional geologic archive – a carbonate facies, a marine sediment layer – and uses computational methods to approach that archive from a different perspective. By applying these new methods, more information can be gleaned from the geologic record, building a richer narrative of the Earth’s climate history. The final chapter of this thesis discusses effective teaching and strategies for building communities to support teaching practice in Earth Science departments.
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ArticleModeling iceberg longevity and distribution during Heinrich Events(American Geophysical Union, 2022-05-17) Fendrock, Michaela ; Condron, Alan ; McGee, DavidDuring the last glacial period (120–12 ka), the Laurentide ice sheet discharged large numbers of icebergs into the North Atlantic. These icebergs carried sediments that were dropped as the icebergs melted, leaving a record of past iceberg activity on the floor of the subpolar North Atlantic. Periods of significant iceberg discharge and increased ice-rafted debris (IRD) deposition, are known as Heinrich Events. These events coincide with global climate change, and the melt from the icebergs involved is frequently hypothesized to have contributed to these changes in climate by adding a significant volume of cold, fresh water to the North Atlantic. Using an iceberg model coupled with the Massachusetts Institute of Technology Global Circulation Model numerical circulation model, we explore the various factors controlling iceberg drift and rates of melt that influence the spatial patterns of IRD deposition during Heinrich Events. In addition to clarifying the influence of sea surface temperature and wind on the path of an armada of icebergs, we demonstrate that the same volume of ice can produce very different patterns of iceberg drift simply by altering the size of icebergs involved. We note also a significant difference in the seasonal locations of icebergs, influenced primarily by the changing winds, and show that the spatial patterns of IRD for Heinrich Event 1 most closely corresponds to where icebergs are located during the summer months. Consistent with proxy evidence, the ocean must be several degrees colder than temperatures estimated for the Last Glacial Maximum in order for icebergs to travel the distance implied by Heinrich Layers.