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Process-guided deep learning water temperature predictions: 6a Lake Mendota detailed evaluation data

Dates

Publication Date
Start Date
1980-04-01
End Date
2018-12-31

Citation

Read, J.S., Jia, X., Willard, J., Appling, A.P., Zwart, J.A., Oliver, S.K., Karpatne, A., Hansen, G.J.A., Hanson, P.C., Watkins, W., Steinbach, M., and Kumar, V., 2019, Data release: Process-guided deep learning predictions of lake water temperature: U.S. Geological Survey data release, https://doi.org/10.5066/P9AQPIVD.

Summary

This dataset includes "test data" compiled water temperature data from an instrumented buoy on Lake Mendota, WI and discrete (manually sampled) water temperature records from North Temperate Lakes Long-TERM Ecological Research Program (NTL-LTER; https://lter.limnology.wisc.edu/). The buoy is supported by both the Global Lake Ecological Observatory Network (gleon.org) and the NTL-LTER. The dataset also includes Lake Mendota model erformance as measured as root-mean squared errors relative to temperature observations during the test period. This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).

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Attached Files

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me_test.csv 5.94 MB text/csv
me_RMSE_limited_training.csv 1.16 KB text/csv
me_RMSE.csv 4.02 KB text/csv

Purpose

Fisheries biology, limnological research, and climate science.

Map

Communities

  • National and Regional Climate Adaptation Science Centers
  • Northeast CASC

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