Search Constraints
Filtering by:
Resource type
Dataset
Remove constraint Resource type: Dataset
Discipline
Science
Remove constraint Discipline: Science
Number of results to display per page
View results as:
Search Results
-
- Creator:
- Kim, YoungJae, Marcano, Maria C., Kim, Sooyeon, and Becker, Udo
- Description:
- The main objective of this research is to integrate electrochemical and microscopic approaches to understand reaction mechanisms and pathways of the uranyl reduction and nucleation mediated by magnetite and ilmenite. and This experimental data reveal how natural iron minerals mediate redox reactions of redox sensitive elements. We measure electrochemical responses of dissolved uranyl ions (UO22+) to potentials in the presence of organic molecules. The atomic force microscopic (AFM) images show nucleation of reduced uranyl on ilmenite (FeTiO3) as a function of potential.
- Keyword:
- electrochemical AFM and uranium reduction
- Citation to related publication:
- Kim, Y., Marcano, M. C., Kim, S., & Becker, U. (2021). Reduction of uranyl and uranyl-organic complexes mediated by magnetite and ilmenite: A combined electrochemical AFM and DFT study. Geochimica et Cosmochimica Acta, 293, 127–141. https://doi.org/10.1016/j.gca.2020.10.016 and Walker S. M., Marcano M. C., Bender W. M. and Becker U. (2016) Imaging the reduction of chromium (VI) on magnetite surfaces using in situ electrochemical AFM. Chemical Geology 429, 60-74.
- Discipline:
- Science
-
- Creator:
- Jiao, Zhenbang, Chen, Yang, and Manchester, Ward
- Description:
- GOES_flare_list: contains a list of more than 12,013 flare events. The list has 6 columns, flare classification, active region number, date, start time end time, emission peak time. SHARP_data.hdf5 files contain time series of 20 physical variables derived from the SDO/HMI SHARP data files. These data are saved at a 12 minute cadence and are used to train the LSTM model.
- Keyword:
- Solar Flare Prediction and Machine Learning
- Citation to related publication:
- Jiao, Z., Sun, H., Wang, X., Manchester, W., Gombosi, T., Hero, A., & Chen, Y. (2020). Solar Flare Intensity Prediction With Machine Learning Models. Space Weather, 18(7), e2020SW002440. https://doi.org/10.1029/2020SW002440 and Chen, Y., & Manchester, W. (2019). Data and Data products for machine learning applied to solar flares [Data set], University of Michigan - Deep Blue. https://doi.org/10.7302/qnsq-cs38
- Discipline:
- Engineering and Science
-
- Creator:
- Holmes, Iris A, Monagan Jr., Ivan V, Westphal, Michael F, and Davis Rabosky, Alison R
- Description:
- We generated these data from desert night lizards, Xantusia vigilis, from populations in central California. We performed phylogeographic analyses based on these data.
- Keyword:
- ddRADseq, phylogeography, Xantusia vigilis, lizard, and genome-scale sequencing
- Discipline:
- Science
-
- Creator:
- Zalmout, Iyad S, Sanders, William J, MacLatchy, Laura M, Gunnell, Gregg F, Al-Mufarreh, Yahya A, Ali, Mohammad A, Nasser, Abdul-Azziz H, Al-Masari, Abdu M, Al-Sobhi, Salih A, Nadhra, Ayman O, Matari, Adel H, Wilson, Jeffrey A, and Gingerich, Philip D
- Description:
- Reconstructed CT slices for the partial cranium of the holotype specimen of Saadanius hijazensis in DICOM format. Data supporting the publication: New Oligocene primate from Saudi Arabia and the divergence of apes and Old World monkeys, https://doi.org/10.1038/nature09094 Raw projections are not included in this dataset.
- Keyword:
- Paleontology, Fossil, Saudi Arabia, CT, Primate, Oligocene, Hominoidea, Cercopithecoidea, University of Michigan Museum of Paleontology, and UMMP
- Citation to related publication:
- Zalmout, I., Sanders, W., MacLatchy, L. et al. New Oligocene primate from Saudi Arabia and the divergence of apes and Old World monkeys. Nature 466, 360–364 (2010). https://doi.org/10.1038/nature09094, A cast of this specimen is held by the University of Michigan Museum of Paleontology (UMMP) under catalog number 14200., and 3D surface model viewable on UMORF site : https://umorf.ummp.lsa.umich.edu/wp/specimen-data/?Model_ID=1408
- Discipline:
- Science
-
- Creator:
- Lin, Xin, Keppel-Aleks, Gretchen, Rogers, Brendan M., and Birch, Leah
- Description:
- The data contain the daily-averaged atmospheric concentrations of CO2 tracers in the Northern Hemisphere simulated from a tagged tracer transport model GEOS-Chem v12.0.0. Thirteen land flux regions are defined and tagged in the model to separate their imprints on the long-term atmospheric CO2 seasonal amplification in Northern Hemisphere. A file describing the delineation of these land flux regions is also provided. See the README file for more details on the dataset and model configurations.
- Keyword:
- carbon dioxide, seasonal cycle, amplification, Arctic-boreal, global change, and GEOS-Chem
- Citation to related publication:
- Lin, X., Rogers, B. M., Sweeney, C., Chevallier, F., Arshinov, M., Dlugokencky, E., Machida, T., Sasakawa, M., Tans, P., & Keppel-Aleks, G. (2020). Siberian and temperate ecosystems shape Northern Hemisphere atmospheric CO2 seasonal amplification. Proceedings of the National Academy of Sciences, 117(35), 21079–21087.
- Discipline:
- Science
-
- Creator:
- Abid, Chaima, Kessentini, Marouane, Alizadeh, Vahid, Dhaouadi, Mouna, and Kazman, Rick
- Description:
- Data about the evaluation of the refactorings impact on security.
- Discipline:
- Science
-
- Creator:
- Gorchov Negron, Alan M., Kort, Eric A., Conley, Stephen A., and Smith, Mackenzie L.
- Description:
- This data-set contains data used in the publication "Airborne Assessment of Methane Emissions from Offshore Platforms in the U.S. Gulf of Mexico" by Gorchov Negron et al. (2020). There are 46,032 rows and 45 columns in the data. and The aircraft sampled offshore facilities with two unique sampling strategies: facility-level samples and regional box samples. Gorchov Negron et al. used facility-level samples to calculate facility-level fluxes and regional box samples, in conjunction with vertical profiles, to calculate regional-level fluxes. Meteorological parameters in the data were evaluated to discern when assumptions for each method were met. The facility-level fluxes were used to generate a facility-level aerial measurement-based inventory that was scaled up for comparison with regional-level fluxes.
- Keyword:
- Methane Emissions, Offshore Oil and Gas Platforms, Airborne Measurements, Greenhouse Gas Mitigation, and Gulf of Mexico
- Citation to related publication:
- Alan M. Gorchov Negron, Eric A. Kort, Stephen A. Conley, Mackenzie L. Smith. "Airborne Assessment of Methane Emissions from Offshore Platforms in the U.S. Gulf of Mexico". Environ. Sci. Technol. 2020. http://dx.doi.org/10.1021/acs.est.0c00179
- Discipline:
- Science
-
- Creator:
- Arbic, Brian K. and Luecke, Conrad A.
- Description:
- The locations ("locs") files in this directory contain indices pointing to the locations in the CMA superset datafiles that were used in the Luecke et al. 2020 comparison of HYCOM and MITgcm model output to CMA observations.
- Keyword:
- Physical oceanography, Numerical modeling, Ocean modeling, Model/data comparisons, and Internal gravity waves
- Citation to related publication:
- Luecke, C. A., Arbic, B. K., Richman, J. G., Shriver, J. F., Alford, M. H., Ansong, J. K., Bassette, S. L., Buijsman, M. C., Menemenlis, D., Scott, R. B., Timko, P. G., Voet, G., Wallcraft, A. J., & Zamudio, L. (2020). Statistical Comparisons of Temperature Variance and Kinetic Energy in Global Ocean Models and Observations: Results From Mesoscale to Internal Wave Frequencies. Journal of Geophysical Research: Oceans, 125(5), e2019JC015306. https://doi.org/10.1029/2019JC015306
- Discipline:
- Science
-
- Creator:
- Yang, Emily G, Kort, Eric A, Wu, Dien, Lin, John C, Oda, Tomohiro, Ye, Xinxin, and Lauvaux, Thomas
- Description:
- This data set supports a study that seeks to evaluate global fossil fuel CO2 emissions inventory representations of CO2 emissions of five cities in the Middle East, and assess the ability of satellite observations to inform this evaluation. Improved observational understanding of urban CO2 emissions, a large and dynamic global source of fossil CO2, can provide essential insights for both carbon cycle science and mitigation decision making. In this study we compare three distinct global CO2 emissions inventory representations of urban CO2 emissions for five Middle Eastern cities (Riyadh, Mecca, Tabuk, Jeddah, and Baghdad) and use independent satellite observations from the Orbiting Carbon Observatory-2 (OCO-2) satellite to evaluate the inventory representations of afternoon emissions. We use the column version of the Stochastic Time-Inverted Lagrangian Transport (X-STILT) model to account for atmospheric transport and link emissions to observations. We compare XCO2 simulations with observations to determine optimum inventory scaling factors. Applying these factors, we find that the average summed emissions for all five cities are 100 MtC/y (50-151, 90% CI), which is 2.0 (1.0, 3.0) times the average prior inventory magnitudes. The total adjustment of the emissions of these cities comes out to ~7% (0%, 14%) of total Middle Eastern emissions (~700 MtC/y). We find our results to be insensitive to the prior spatial distributions in inventories of the cities’ emissions, facilitating robust quantitative assessments of urban emission magnitudes without accurate high-resolution gridded inventories. and There are three files included in this data set, and all data are in tab-delimited form. The first file, xco2_lat.zip, contains 26 separate text files, each named by the city and date of the corresponding OCO-2 overpass. Each of these 26 files includes overpass-specific data, with modeled and observed XCO2 values binned by 0.1 degree of latitude. The file overpass_scaling_factors.txt provides the scaling factors for each overpass used in this study. The file city_estimates.txt provides the scaled emissions estimates for each city (or sum of cities) as well as the lower and upper bounds of the 90% confidence intervals, for each inventory.
- Keyword:
- greenhouse gases, carbon dioxide, urban, cities, satellite, remote sensing, Lagrangian modeling, emissions inventories, carbon cycle, and climate
- Citation to related publication:
- Yang, E. G., Kort, E. A., Wu, D., Lin, J. C., Oda, T., Ye, X., & Lauvaux, T. (2020). Using space‐based observations and Lagrangian modeling to evaluate urban carbon dioxide emissions in the Middle East. Journal of Geophysical Research: Atmospheres, 125, e2019JD031922. https://doi.org/10.1029/2019JD031922
- Discipline:
- Science
-
- Creator:
- Yue, Min, Kim, Jae Hyun, Evans, Charles R. , Kachman, Maureen, Erb-Downward, John R., D’Souza, Jennifer , Foxman, Betsy, Adar, Sara D. , Curtis, Jeffrey L. , and Stringer, Kathleen A.
- Description:
- This was a small descriptive study to determine whether short chain fatty acids (SCFAs) are detectable in water. It is part of a larger study that assessed the utility of exhaled breath condensate (EBC) as a biofluid for microbiome assays.
- Keyword:
- microbiome, short chain fatty acids, pulmonary, bronchoalveolar lavage fluid, exhaled breath condensate, and water
- Citation to related publication:
- Yue, M., Kim, J. H., Evans, C. R., Kachman, M., Erb-Downward, J. R., D’Souza, J., Foxman, B., Adar, S. D., Curtis, J. L., & Stringer, K. A. (2020). Measurement of Short-Chain Fatty Acids in Respiratory Samples: Keep Your Assay above the Water Line. American Journal of Respiratory and Critical Care Medicine, 202(4), 610–612. https://doi.org/10.1164/rccm.201909-1840LE
- Discipline:
- Science
-
- Creator:
- Lee, Dahee, Panicker, Veena, and Landis-Lewis, Zach
- Description:
- We use the term “performance summary display” (PSD) to mean a kind of visualization that relates performance levels to other types of information. In the context of healthcare organizations, PSDs are intended to be communicated to a healthcare professional, team, or organization. and Displays were identified, classified, and elements counted and coded. The performance summary display ontology provides a set of descriptions of components of displays that have been used to annotate performance feedback visualizations.
- Keyword:
- Performance
- Citation to related publication:
- Lee, D., Panicker, V., Gross, C., Zhang, J., & Landis-Lewis, Z. (2020). What was visualized? A method for describing content of performance summary displays in feedback interventions. BMC medical research methodology, 20(1), 90. https://doi.org/10.1186/s12874-020-00951-x
- Discipline:
- Health Sciences and Science
-
Monthly water balance estimates for the Laurentian Great Lakes from 1950 to 2019 (v1.0) [Deprecated]
- Creator:
- Do, Hong X., Smith, Joeseph P., Fry, Lauren M., and Gronewold, Andrew D.
- Description:
- This data set contains a new estimate of monthly water balance components from 1950 to 2019 for the Laurentian Great Lakes, the largest freshwater system on Earth. The source code and inputs to derive the new estimates are also included in this dataset.
- Keyword:
- Great Lakes water levels, statistical inference, water balance, and data assimilation
- Citation to related publication:
- Do, H.X., Smith, J., Fry, L.M., and Gronewold, A.D., Seventy-year long record of monthly water balance estimates for Earth’s largest lake system (pending for submission) and Version Note: This dataset is deprecated and has been replaced by version 1.1, found at https://deepblue.lib.umich.edu/data/concern/data_sets/sb3978457
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:mammals:123037 (Tscherskia TRITON) - WholeBody. Raw Dataset includes 1601 TIF images (each 715 x 1288 x 1 voxel at 0.0493711582967448 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:123037 (Tscherskia TRITON) - WholeBody. Reconstructed Dataset includes 2000 TIF images (each 715 x 1288 x 1 voxel at 0.049371 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Mammalia, Rodentia, Cricetidae, Tscherskia TRITON, 1987305166, computed tomography, X-ray, and 3D
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1987305166
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:mammals:111984 (Handleyomys ALFAROI ALFAROI) - WholeBody. Raw Dataset includes 1601 TIF images (each 815 x 1310 x 1 voxel at 0.0421497172804555 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:111984 (Handleyomys ALFAROI ALFAROI) - WholeBody. Reconstructed Dataset includes 2000 TIF images (each 815 x 1310 x 1 voxel at 0.042150 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Mammalia, Rodentia, Cricetidae, Handleyomys ALFAROI ALFAROI, 1987286466, computed tomography, X-ray, and 3D
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1987286466
- Discipline:
- Science
-
- Creator:
- Liemohn, Michael W, Azari, Abigail R, Ganushkina, Natalia Yu, and Rastätter, Lutz
- Description:
- Scientists often try to reproduce observations with a model, helping them explain the observations by adjusting known and controllable features within the model. They then use a large variety of metrics for assessing the ability of a model to reproduce the observations. One such metric is called the relative operating characteristic (ROC) curve, a tool that assesses a model’s ability to predict events within the data. The ROC curve is made by sliding the event-definition threshold in the model output, calculating certain metrics and making a graph of the results. Here, a new model assessment tool is introduced, called the sliding threshold of observation for numeric evaluation (STONE) curve. The STONE curve is created by sliding the event definition threshold not only for the model output but also simultaneously for the data values. This is applicable when the model output is trying to reproduce the exact values of a particular data set. While the ROC curve is still a highly valuable tool for optimizing the prediction of known and pre-classified events, it is argued here that the STONE curve is better for assessing model prediction of a continuous-valued data set. and Data and code were created using IDL, but can also be accessed with the open-source Gnu Data Language (GDL; see https://github.com/gnudatalanguage/gdl)
- Keyword:
- ROC curve, STONE curve, data-model comparison, model validation, forecasting, and statistical methods
- Citation to related publication:
- Liemohn, M. W., Azari, A. R., Ganushkina, N. Yu., & Rastätter, L. (2020). The STONE curve: A ROC-derived model performance assessment tool. Earth and Space Science, 7, e2020EA001106. https://doi.org/10.2019/2020EA001106
- Discipline:
- Science
-
- Creator:
- Liemohn, Michael W
- Description:
- The editorial decision process for the Journal of Geophysics Research Space Physics is assisted by over 1,000 scientists every year, providing over 3,000 reviews per year. These statistics are presented for the years 2013 through 2018, showing some fluctuations but, overall, consistency in the response of the space physics research community to requests to serve as manuscript reviewers. Over half of these reviews are submitted on time, and the average time to review actually dropped as the load increased. This is greatly appreciated and the community is to be commended and thanked for their willingness to help make this journal thrive and remain a premiere publication in the field.
- Keyword:
- Editorial and reviewer statistics
- Citation to related publication:
- Liemohn, M. W. (2020). Editorial: Multiyear analysis of JGR Space Physics reviewing statistics. Journal of Geophysical Research Space Physics, 125, e2019JA027719. https://doi.org/10.1029/2019JA027719
- Discipline:
- Science
-
- Creator:
- Hegedus, Alexander M
- Description:
- This is the README for the LunarSynchrotronArray package, maintained by Dr. Alex Hegedus alexhege@umich.edu This code repository corresponds to the Hegedus et al. 2020 (accepted) Radio Science paper, "Measuring the Earth's Synchrotron Emission from Radiation Belts with a Lunar Near Side Radio Array". The arxiv link for the paper is https://arxiv.org/abs/1912.04482. The DOI link is https://doi.org/10.1029/2019RS006891 , The Earth's Ionosphere is home to a large population of energetic electrons that live in the balance of many factors including input from the Solar wind, and the influence of the Earth's magnetic field. These energetic electrons emit radio waves as they traverse Earth's magnetosphere, leading to short‐lived, strong radio emissions from local regions, as well as persistent weaker emissions that act as a global signature of the population breakdown of all the energetic electrons. Characterizing this weaker emission (Synchrotron Emission) would lead to a greater understanding of the energetic electron populations on a day to day level. A radio array on the near side of the Moon would always be facing the Earth, and would well suited for measuring its low frequency radio emissions. In this work we simulate such a radio array on the lunar near side, to image this weaker synchrotron emission. The specific geometry and location of the test array were made using the most recent lunar maps made by the Lunar Reconnaissance Orbiter. This array would give us unprecedented day to day knowledge of the electron environment around our planet, providing reports of Earth's strong and weak radio emissions, giving both local and global information. , This set of codes should guide you through making the figures in the paper, as well as hopefully being accessible enough for changing the code for your own array. I would encourage you to please reach out to collaborate if that is the case! Requirements: , and CASA 4.7.1 (or greater?) built on python 2.7 Example link for Red Hat 7 https://casa.nrao.edu/download/distro/casa/release/el7/casa-release-4.7.1-el7.tar.gz Users may follow this guide to download and install the correct version of CASA for their system https://casa.nrao.edu/casadocs/casa-5.5.0/introduction/obtaining-and-installing CASA executables should be fairly straightforward to extract from the untarred files. gcc 4.8.5 or above (or below?) GCC installation instructions can be found here: https://gcc.gnu.org/install/ SPICE (I use cspice here) https://naif.jpl.nasa.gov/naif/toolkit_C.html As seen in lunar_furnsh.txt which loads the SPICE kernels, you also must download KERNELS_TO_LOAD = ( '/home/alexhege/SPICE/LunarEph/moon_pa_de421_1900-2050.bpc' '/home/alexhege/SPICE/LunarEph/moon_080317.tf' '/home/alexhege/SPICE/LunarEph/moon_assoc_me.tf' '/home/alexhege/SPICE/LunarEph/pck00010.tpc' '/home/alexhege/SPICE/LunarEph/naif0008.tls' '/home/alexhege/SPICE/LunarEph/de430.bsp' ) All of which can be found at https://naif.jpl.nasa.gov/pub/naif/generic_kernels/ SLDEM2015_128_60S_60N_000_360_FLOAT.IMG for the lunar surface data by LRO LOLA found at http://imbrium.mit.edu/DATA/SLDEM2015/GLOBAL/FLOAT_IMG/
- Citation to related publication:
- Hegedus, A., Nenon, Q., Brunet, A., Kasper, J., Sicard, A., Cecconi, B., MacDowall, R., & Baker, D. (2019). Measuring the Earth's Synchrotron Emission from Radiation Belts with a Lunar Near Side Radio Array. https://arxiv.org/abs/1912.04482 and Hegedus, A., Nenon, Q., Brunet, A., Kasper, J., Sicard, A., Cecconi, B., MacDowall, R., & Baker, D. (2020). Radio Science. https://doi.org/10.1029/2019RS006891
- Discipline:
- Engineering and Science
-
- Creator:
- Nelson, Arin D.
- Description:
- These MATLAB data files contain all the observations and model output used in the article Improved Internal Gravity Wave Spectral Continuum in a Regional Ocean Model by Nelson et al., recently submitted to Journal of Geophysical Research: Oceans.
- Keyword:
- Ocean, Ocean Mooring, Ocean Modeling, and Internal Waves
- Citation to related publication:
- Nelson, A. D., Arbic, B. K., Menemenlis, D., Peltier, W. R., Alford, M. H., Grisouard, N., & Klymak, J. M. (2020). Improved Internal Wave Spectral Continuum in a Regional Ocean Model. Journal of Geophysical Research: Oceans, 125(5), e2019JC015974. https://doi.org/10.1029/2019JC015974
- Discipline:
- Science
-
- Creator:
- Smith, Joeseph P., Gronewold, Andrew D., Read, Laura, Crooks, James L., School for Environment and Sustainability, University of Michigan, Department of Civil and Environmental Engineering, University of Michigan, and Cooperative Institute for Great Lakes Research
- Description:
- Using the statistical programming package R ( https://cran.r-project.org/), and JAGS (Just Another Gibbs Sampler, http://mcmc-jags.sourceforge.net/), we processed multiple estimates of the Laurentian Great Lakes water balance components -- over-lake precipitation, evaporation, lateral tributary runoff, connecting channel flows, and diversions -- feeding them into prior distributions (using data from 1950 through 1979), and likelihood functions. The Bayesian Network is coded in the BUGS language. Water balance computations assume that monthly change in storage for a given lake is the difference between beginning of month water levels surrounding each month. For example, the change in storage for June 2015 is the difference between the beginning of month water level for July 2015 and that for June 2015., More details on the model can be found in the following summary report for the International Watersheds Initiative of the International Joint Commission, where the model was used to generate a new water balance historical record from 1950 through 2015: https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf. Large Lake Statistical Water Balance Model (L2SWBM): https://www.glerl.noaa.gov/data/WaterBalanceModel/, and This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
- Keyword:
- Water, Balance, Great Lakes, Laurentian, Machine, Learning, Lakes, Bayesian, and Network
- Citation to related publication:
- Smith, J., Gronewald, A. et al. Summary Report: Development of the Large Lake Statistical Water Balance Model for Constructing a New Historical Record of the Great Lakes Water Balance. Submitted to: The International Watersheds Initiative of the International Joint Commission. Accessible at https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf, Large Lake Statistical Water Balance Model (L2SWBM). https://www.glerl.noaa.gov/data/WaterBalanceModel/, and Gronewold, A.D., Smith, J.P., Read, L. and Crooks, J.L., 2020. Reconciling the water balance of large lake systems. Advances in Water Resources, p.103505.
- Discipline:
- Science and Engineering
-
- Creator:
- Smith, Joeseph P., Gronewold, Andrew D., Read, Laura, Crooks, James L., School for Environment and Sustainability, University of Michigan, Department of Civil and Environmental Engineering, University of Michigan, and Cooperative Institute for Great Lakes Research
- Description:
- Using the statistical programming package R ( https://cran.r-project.org/), and JAGS (Just Another Gibbs Sampler, http://mcmc-jags.sourceforge.net/), we processed multiple estimates of the Laurentian Great Lakes water balance components -- over-lake precipitation, evaporation, lateral tributary runoff, connecting channel flows, and diversions -- feeding them into prior distributions (using data from 1950 through 1979), and likelihood functions. The Bayesian Network is coded in the BUGS language. Water balance computations assume that monthly change in storage for a given lake is the difference between beginning of month water levels surrounding each month. For example, the change in storage for June 2015 is the difference between the beginning of month water level for July 2015 and that for June 2015., More details on the model can be found in the following summary report for the International Watersheds Initiative of the International Joint Commission, where the model was used to generate a new water balance historical record from 1950 through 2015: https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf. Large Lake Statistical Water Balance Model (L2SWBM): https://www.glerl.noaa.gov/data/WaterBalanceModel/ , and This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
- Keyword:
- Water, Balance, Great Lakes, Laurentian, Machine, Learning, Lakes, Bayesian, and Network
- Citation to related publication:
- Smith, J., Gronewald, A. et al. Summary Report: Development of the Large Lake Statistical Water Balance Model for Constructing a New Historical Record of the Great Lakes Water Balance. Submitted to: The International Watersheds Initiative of the International Joint Commission. Accessible at https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf, Large Lake Statistical Water Balance Model (L2SWBM). https://www.glerl.noaa.gov/data/WaterBalanceModel/, and Gronewold, A.D., Smith, J.P., Read, L. and Crooks, J.L., 2020. Reconciling the water balance of large lake systems. Advances in Water Resources, p.103505.
- Discipline:
- Science and Engineering