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- Creator:
- Zhang, Yingxiao MI and Steiner, Allison MI
- Description:
- Atmospheric aerosols are emitted from both natural and anthropogenic sources, and they play an important role in climate, impacting solar radiation and cloud formation. Compared to other types of aerosol particles, primary biological aerosol particles (PBAP, e.g., fungal spores, bacteria, pollen, virus, etc.) are relatively understudied. However, they are linked to adverse health effects and have the potential to influence ice nucleation at higher temperatures. Anemophilous (or wind-driven) pollen is one of the important PBAP, impacts cloud properties under some conditions, and triggers allergic diseases such as allergic rhinitis (also known as hay fever) and asthma. Because pollen emission is closely associated with environmental drivers, the climatic change could influence pollen emission and consequently the incidence of allergic disease. Using CMIP6 model data, our research projects continental-scale changes in pollen emissions at the end of the century, considering the effects of temperature, precipitation, CO2, and future vegetation distribution change. While prior studies have evaluated single types of pollen, we use a mechanistic model to comprehensively simulate total pollen across the United States from all sources. Similar to previous single-source pollen studies, our simulations suggest that pollen season duration will lengthen, and pollen emission will increase in the future, but in addition, we identify new synergies between different pollen types that can influence the maximum daily pollen. Our work highlights that the changes of overlap between pollen seasons of different vegetation taxa can magnify or mitigate the impacts of climate change, which addresses the importance to study all pollen emissions comprehensively. Given pollen is one of the most common triggers of seasonal allergies, our findings also provide information to evaluate global health conditions in the future. In this study, all of the pollen emission data are written in NetCDF files.
- Keyword:
- Pollen emission change, Climate change, Public health, Vegetation land cover change, and CO2 effects
- Citation to related publication:
- Zhang, Y. and Steiner, A. “Projected climate-driven changes in pollen emission season length and magnitude over the continental United States”, under review in Nature Communication, 2022. and yingxz. (2022). steiner-lab/pecm: PECM2.0 (2.0). Zenodo. https://doi.org/10.5281/zenodo.5874177
- Discipline:
- Science
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- Creator:
- Bradshaw, Lisa, Vernon, Julianne, Schmidt, Thomas, James, Timothy, Zhang, Jianzhi, Archbold, Hilary, Cadigan, Ken, Wolfe, John P., and Goldberg, Deborah E.
- Description:
- This is the experimental data referenced in our manuscript entitled "Influence of CUREs on STEM retention depends on demographic identities." The dataset comprises csv files with results from student surveys given to students enrolled in Biology 173 from Fall 2015 through Fall 2019 as well as institutional data of their course grades and cumulative GPA at the time they enrolled in Biology 173, and graduation and major data for student who had graduated by 2021. The survey questions used in the analysis and the IRB consent form are also included as pdfs.
- Keyword:
- undergraduate research, STEM retention, CURE, introductory biology laboratory, and education research
- Citation to related publication:
- Bradshaw, L., Vernon J., Schmidt T., James T., Zhang J., Archbold H., Cadigan K., Wolfe J.P. & Goldberg D. 2023. Research article: Influence of CUREs on STEM retention depends on demographic identities. J Microbiol Biol Educ (accepted)
- Discipline:
- Science
-
- Creator:
- Salaree, Amir, Spica, Zack, and Huang, Yihe
- Description:
- The items in this bundle are supporting videos to a study of subsea seismo-acoustics carried out regarding an earthquake in the Persian Gulf. The main data used in the study is a diver's recording of the acoustic waves from the earthquake. The epicenter and topography data used in this study are publicly available as cited in the README.txt file.
- Keyword:
- Seismo-acoustics, Persian Gulf, Divers’ Microphones, Seismic Hazard, Early Warning
- Discipline:
- Science
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- Creator:
- Limon, Garrett C.
- Description:
- The work guides the processing of CAM6 data for use in machine learning applications. We also provide workflow scripts for training both random forests and neural networks to emulate physic s schemes from the data, as well as analysis scripts written in both Python and NCL in order to process our results.
- Keyword:
- Machine Learning, Climate Modeling, and Physics Emulation
- Citation to related publication:
- Limon, G. C., Jablonowski, C. (2022) Probing the Skill of Random Forest Emulators for Physical Parameterizations via a Hierarchy of Simple CAM6 Configurations [Pre Print]. ESSOAr. https://10.1002/essoar.10512353.1
- Discipline:
- Engineering and Science
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Resources for Training Machine Learning Algorithms Using CAM6 Simple Physics Packages
User Collection- Creator:
- Limon, Garrett
- Description:
- The collection contains the code and the data used to train machine learning algorithms to emulate simplified physical parameterizations within the Community Atmosphere Model (CAM6). CAM6 is the atmospheric general circulation model (GCM) within the Community Earth System Model (CESM) framework, developed by the National Center for Atmospheric Research (NCAR). GCMs are made up of a dynamical core, responsible for the geophysical fluid flow calculations, and physical parameterization schemes, which estimate various unresolved processes. Simple physics schemes were used to train both random forests and neural networks in the interest of exploring the feasibility of machine learning techniques being used in conjunction with the dynamical core for improved efficiency of future climate and weather models. The results of the research show that various physical forcing tendencies and precipitation rates can be effectively emulated by the machine learning models.
- Keyword:
- Machine Learning, Climate Modeling, and Physics Emulators
- Discipline:
- Science and Engineering
2Works -
- Creator:
- Limon, Garrett C.
- Description:
- The data represents weekly output from three 60-year CAM6 model runs. The output includes state (.h0. files) and tendency (.h1. files) fields for three difference model configurations of increasing complexity. State fields include temperature, surface pressure, specific humidity, among others; while tendencies include temperature tendencies, specific humidity tendencies, as well as precipitation rates. Using the state variables at a given time step, machine learning techniques can be trained to predict the following tendency field, which can then be applied to the state variables to provide the state at the next physics time step of the model.
- Keyword:
- Machine Learning, Climate Modeling, and Physics Emulation
- Citation to related publication:
- Limon, G. C., Jablonowski, C. (2022) Probing the Skill of Random Forest Emulators for Physical Parameterizations via a Hierarchy of Simple CAM6 Configurations [Preprint]. ESSOAr. https://10.1002/essoar.10512353.1
- Discipline:
- Engineering and Science
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- Creator:
- University of Michigan Museum of Paleontology and CTEES
- Description:
- Reconstructed CT slices for Right innominate (acetabulum region) of Remingtonocetus domandaensis (University of Michigan Museum of Paleontology catalog number GSP-UM 3408) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Paleontology, Fossil, CT, Remingtonocetidae, UMMP, University of Michigan Museum of Paleontology, Eocene, and Geological Survey of Pakistan (GSP)
- Discipline:
- Science
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- Creator:
- University of Michigan Museum of Paleontology and CTEES
- Description:
- Reconstructed CT slices for phalanx (pathological) of phytosaur (University of Michigan Museum of Paleontology catalog number UMMP VP 13838) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Paleontology, Fossil, CT, Phytosauria, UMMP, University of Michigan Museum of Paleontology, Triassic, and e06c6866-4cba-4532-2a68-d8e3357a674e
- Discipline:
- Science
-
- Creator:
- Bueno-Junior, Lezio S., Ruckstuhl, Maxwell S., Lim, Miranda M., and Watson, Brendon O.
- Description:
- Rapid eye movement sleep (REM) is believed to have a binary temporal structure with “phasic” and “tonic" microstates, characterized by motoric activity versus quiescence, respectively. However, we observed in mice that the frequency of theta activity (a marker of rodent REM) fluctuates in a non-binary fashion, with the extremes of that fluctuation correlating with phasic-type and tonic-type facial motricity. Thus, phasic and tonic REM may instead represent ends of a continuum. These cycles of brain physiology and facial movement occurred at 0.01-0.06 Hz, or infraslow frequencies, and affected cross-frequency coupling and neuronal activity in the neocortex, suggesting network functional impact. We then analyzed human data and observed that humans also demonstrate non-binary phasic/tonic microstates, with continuous 0.01-0.04 Hz respiratory rate cycles matching the incidence of eye movements. These fundamental properties of REM can yield new insights into our understanding of sleep health.
- Keyword:
- REM sleep, Infraslow fluctuations, Facial movements, Theta oscillations, and Respiration rate
- Citation to related publication:
- L. S. Bueno-Junior, M. S. Ruckstuhl, M. M. Lim, B. O. Watson, The temporal structure of REM sleep shows minute-scale fluctuations across brain and body in mice and humans. Proc. Natl. Acad. Sci. U. S. A. In press (2023).
- Discipline:
- Science
-
Survey Data
User Collection- Creator:
- Galaty, Michael
- Description:
- All databases, field notebooks, paper maps, GIS files, photographs, and photo descriptions related to the intensive survey, of tracts and tumuli, and the collection of sites have been made available in PASH Deep Blue Data Realm 1. The data are broadly organized by team (A-K). The surveyed land was divided up into “tracts”. Tracts are labeled with team letter and a consecutive number: e.g., A-001, A-002, B-003, C-122, D-035.
- Keyword:
- Archaeology
- Discipline:
- Science
6Works