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- Creator:
- Hong, Yi, Fry, Lauren M., Orendorf, Sophie, Ward, Jamie L., Mroczka, Bryan, Wright, David, and Gronewold, Andrew
- Description:
- Accurate estimation of hydro-meteorological variables is essential for adaptive water management in the North American Laurentian Great Lakes. However, only a limited number of monthly datasets are available nowadays that encompass all components of net basin supply (NBS), such as over-lake precipitation (P), evaporation (E), and total runoff (R). To address this gap, we developed a daily hydro-meteorological dataset covering an extended period from 1979 to 2022 for each of the Great Lakes. The daily P and E were derived from six global gridded reanalysis climate datasets (GGRCD) that include both P and E estimates, and R was calculated from National Water Model (NWM) simulations. Ensemble mean values of the difference between P and E (P – E) and NBS were obtained by analyzing daily P, E, and R. Monthly averaged values derived from our new daily dataset were validated against existing monthly datasets. This daily hydro-meteorological dataset has the potential to serve as a validation resource for current data and analysis of individual NBS components. Additionally, it could offer a comprehensive depiction of weather and hydrological processes in the Great Lakes region, including the ability to record extreme events, facilitate enhanced seasonal analysis, and support hydrologic model development and calibration. The source code and data representation/analysis figures are also made available in the data repository.
- Keyword:
- Great Lakes, Hydrometeorological, National Water Model, Daily, Overlake precipitation, Overlake evaporation, Total runoff, Net Basin Supply, and Water Balance
- Discipline:
- Science and Engineering
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- Creator:
- Sorensen, Troy R, Espey, Eamon, Kelley, John G. W. , Kessler, James, and Gronewold, Andrew D.
- Description:
- Inland lakes play a critical role in ecosystem stability, and robust validation of lake models is essential for understanding their dynamics. While remote sensing data can assist with lake surface temperature validation, in situ data typically provides more accurate, reliable data not limited to only the lake surface. However, in situ temperature data for many individual lakes, particularly in North America, is difficult for researchers to quickly access in a standardized format. This database offers a well-organized collection of in situ near-surface and subsurface temperatures from 134 sites divided among 29 large North American inland lakes collected from a variety of sources. The database includes multiple subsurface temperatures throughout the depth profile of 84 of these sites, providing comprehensive data for lake model evaluation. All lakes selected for this database are large enough (over approximately 30 km^2 to be represented by large-scale operational weather models, supporting robust lake model validation efforts on the lakes that have the greatest impact on climatology.
- Keyword:
- lake, temperature, in situ, and subsurface
- Citation to related publication:
- Sorensen, T., Espey, E., Kelley, J.G.W. et al. A database of in situ water temperatures for large inland lakes across the coterminous United States. Sci Data 11, 282 (2024). https://doi.org/10.1038/s41597-024-03103-8
- Discipline:
- Science
-
- Creator:
- Surdoval, Alison, Jain, Meha, Wang, Haoyu, and Blesh, Jennifer
- Description:
- We conducted a mixed-methods study to understand how financial incentive programs impact transitions to cover cropping in Michigan. Michigan farms span a wide range of soil types, climate conditions, and cropping systems that create opportunities for cover crop adoption in the state. We tested the relationship between Environmental Quality Incentives Program (EQIP) payments for cover crops and cover crop adoption between 2008-2019, as measured by remote sensing. Panel fixed effects regressions showed that EQIP increased winter cover crop presence. Every EQIP dollar for cover crops was associated with a 0.01 hectare increase in winter cover, while each hectare enrolled in an EQIP contract for cover crops was associated with a 0.86 – 0.93 hectare increase in winter cover.
- Keyword:
- adoption, cover crop, Environmental Quality Incentives Program, financial incentive program, Michigan, remote sensing
- Citation to related publication:
- Surdoval, A., Jain, M., Blair, E., Wang, H., and J. Blesh. In press. Financial incentive programs and farm diversification with cover crops: Assessing opportunities and challenges.
- Discipline:
- Science
-
- Creator:
- Do, Hong X., Smith, Joeseph P., Fry, Lauren M., and Gronewold, Andrew D.
- Description:
- This data set contains a new monthly estimate of the water balance of the Laurentian Great Lakes, the largest freshwater system on Earth, from 1950 to 2019. The source codes and inputs to derive the new estimates are also included in this dataset. and ***ADDED 2024-02-27: The component net basins supply data "*NBSC_GLWBData.csv" in "output_ts_posterior.zip" need to be revised for further applications***
- Keyword:
- Laurentian Great Lakes, Bayesian inference, water levels, data assimilation, and water balance
- Citation to related publication:
- Do, H. X., Smith, J. P., Fry, L. M., & Gronewold, A. D. (2020). Seventy-year long record of monthly water balance estimates for Earth’s largest lake system. Scientific Data, 7(1), 276. https://doi.org/10.1038/s41597-020-00613-z, Gronewold, A. D., Smith, J. P., Read, L., & Crooks, J. L. (2020). Reconciling the water balance of large lake systems. Advances in Water Resources, 103505. https://doi.org/10.1016/j.advwatres.2020.103505 , and This version replaces the following deprecated dataset: Do, H.X., Smith, J.P., Fry, L.M., Gronewold, A.D. (2020). Monthly water balance estimates for the Laurentian Great Lakes from 1950 to 2019 [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/0rsp-v195
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:fish:227765 (Argyropelecus aculeatus Valenciennes, 1850). Raw Dataset includes 2401 TIF images (each 1316 x 1285 x 1 voxel at 0.02652906 mm resolution, derived from 2401 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:fish:227765 (Argyropelecus aculeatus Valenciennes, 1850). Reconstructed Dataset includes 1471 TIF images (each 1316 x 1285 x 1 voxel at 0.026529 mm resolution, derived from 2401 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Stomiiformes, Sternoptychidae, Argyropelecus aculeatus Valenciennes, 1850, 1889127527, computed tomography, X-ray, 3D, and DiceCT
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1889127527 and DiceCT for Fishes: Recommendations for pairing iodine contrast agents with μCT to visualize soft tissues in fishes https://doi.org/10.1111/jfb.15320
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:fish:165173 (Noturus gyrinus (Mitchill, 1817)). Raw Dataset includes 1801 TIF images (each 503 x 663 x 1 voxel at 0.0382276 mm resolution, derived from 1801 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:fish:165173 (Noturus gyrinus (Mitchill, 1817)). Reconstructed Dataset includes 1775 TIF images (each 503 x 663 x 1 voxel at 0.038228 mm resolution, derived from 1801 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Siluriformes, Ictaluridae, Noturus gyrinus (Mitchill, 1817), 1889067832, computed tomography, X-ray, 3D, and DiceCT
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1889067832 and DiceCT for Fishes: Recommendations for pairing iodine contrast agents with μCT to visualize soft tissues in fishes https://doi.org/10.1111/jfb.15320
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:fish:206739 (Ancistrus cirrhosus (Valenciennes, 1836)) - Skull. Reconstructed Dataset includes 1827 TIF images (each 1439 x 1229 x 1 voxel at 0.016076 mm resolution, derived from 1801 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:fish:206739 (Ancistrus cirrhosus (Valenciennes, 1836)) - Skull. Raw Dataset includes 1801 TIF images (each 1439 x 1229 x 1 voxel at 0.01607582 mm resolution, derived from 1801 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Siluriformes, Loricariidae, Ancistrus cirrhosus (Valenciennes, 1836), 1889108051, computed tomography, X-ray, 3D, and DiceCT
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1889108051 and DiceCT for Fishes: Recommendations for pairing iodine contrast agents with μCT to visualize soft tissues in fishes https://doi.org/10.1111/jfb.15320
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:fish:165173 (Noturus gyrinus (Mitchill, 1817)) - Skull. Raw Dataset includes 1801 TIF images (each 1376 x 1066 x 1 voxel at 0.01759152 mm resolution, derived from 1801 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:fish:165173 (Noturus gyrinus (Mitchill, 1817)) - Skull. Reconstructed Dataset includes 1511 TIF images (each 1376 x 1066 x 1 voxel at 0.017592 mm resolution, derived from 1801 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Siluriformes, Ictaluridae, Noturus gyrinus (Mitchill, 1817), 1889067832, computed tomography, X-ray, 3D, and DiceCT
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1889067832 and DiceCT for Fishes: Recommendations for pairing iodine contrast agents with μCT to visualize soft tissues in fishes https://doi.org/10.1111/jfb.15320
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:fish:172750 (Achirus lineatus (Linnaeus, 1758)). Reconstructed Dataset includes 2000 TIF images (each 1423 x 622 x 1 voxel at 0.047137 mm resolution, derived from 1801 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:fish:172750 (Achirus lineatus (Linnaeus, 1758)). Raw Dataset includes 1801 TIF images (each 1423 x 622 x 1 voxel at 0.04713662 mm resolution, derived from 1801 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Pleuronectiformes, Achiridae, Achirus lineatus (Linnaeus, 1758), 1889075287, computed tomography, X-ray, 3D, and DiceCT
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1889075287 and DiceCT for Fishes: Recommendations for pairing iodine contrast agents with μCT to visualize soft tissues in fishes https://doi.org/10.1111/jfb.15320
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:fish:218102 (Anabas testudineus (Bloch, 1792)). Reconstructed Dataset includes 1987 TIF images (each 683 x 585 x 1 voxel at 0.067089 mm resolution, derived from 2401 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:fish:218102 (Anabas testudineus (Bloch, 1792)). Raw Dataset includes 2401 TIF images (each 683 x 585 x 1 voxel at 0.06708945 mm resolution, derived from 2401 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Perciformes, Anabantidae, Anabas testudineus (Bloch, 1792), 1889118619, computed tomography, X-ray, 3D, and DiceCT
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1889118619 and DiceCT for Fishes: Recommendations for pairing iodine contrast agents with μCT to visualize soft tissues in fishes https://doi.org/10.1111/jfb.15320
- Discipline:
- Science