Work Description

Date: 15 March, 2024

Dataset Title: A Daily Hydro-Meteorological Dataset for The World’s Largest System of Lakes

Dataset Creators: Yi Hong, Lauren M. Fry, Sophie Orendorf, Jamie L. Ward, Bryan Mroczka, David Wright, Andrew Gronewold

Dataset Contact: Yi Hong, yhon@umich.edu

Funding: Bipartisan Infrastructure Law (BIL) (Award ID: NA22OAR4050675I).

Key Points:
- Developed a daily hydro-meteorological dataset that encompass all components of net basin supply (NBS) covering 1979 – 2022 for each of the Great Lakes.
- The daily overlake precipitation (P) and overlake evaporation (E) were derived from six global gridded reanalysis climate datasets.
- The total runoff (R) was calculated from National Water Model simulations.
- Ensemble mean values of NBS were obtained by analyzing daily P, E, and R

Research Overview:
We developed a daily hydro-meteorological dataset covering 1979 – 2022 for each of the Great Lakes. The daily P and E were derived from six global gridded reanalysis climate datasets, and R was calculated from National Water Model simulations.
Ensemble mean values of 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 hydro-meteorological processes in the Great Lakes region.

Methodology:
The daily overlake precipitation (P) and overlake evaporation (E) were derived from six global gridded reanalysis climate datasets (GGRCD) that include both P and E estimates, and total runoff (R) was calculated from National Water Model (NWM) simulations.
Ensemble mean values of the difference between P and E (P – E) and net basin supply (NBS) were obtained by analyzing daily P, E, and R.
Date Coverage: 1979 - 2022.

Instrument and/or Software specifications:
Python 3.9 was used for plotting daily and monthly data variables.
Required packages include: os, datetime, numpy, pandas, itertools, matplotlib, and seaborn.
In the "Configuration settings" section, file paths could be changed as needed:
"fig_path" refer to the path for saving figures;
"Dir_day" and "Dir_mon" refer to directories containing daily and monthly .CSV data files, respectively.

Files contained here:
- Daily CSV files containing multiple daily hydro-meteorological variables for each of the Great Lakes.
- Monthly CSV files containing multiple monthly hydro-meteorological variables for each of the Great Lakes.
- Compressed mask.zip contains Netcdf files representing masks for gridded datasets for each of the Great Lakes.
- Compressed python_code.zip includes Python scripts to calculate averaged variable values for each of the Great Lakes and perform analysis to represent datasets.
- Compressed Daily_Figures.zip contains figures representing daily datasets
- Compressed Monthly_Figures.zip contains figures representing monthly datasets

Naming Conventions:
1, CSV files:
Description: CSV files containing multiple daily/monthly hydro-meteorological variables for each of the Great Lakes
File Naming Convention: Daily_CNBS_.csv, Monthly_CNBS_.csv
Filename Example: Daily_CNBS_ER.csv; Monthly_CNBS_MIHU.csv
Column Naming Convention: _
Column Name Example: ERA_P(mm); GLERL_NBS(cms)

2, Directory "Masks":
Description: Netcdf files representing masks for gridded datasets for each of the Great Lakes
File Naming Convention: mask_.nc
Filename Example: mask_cfsr.nc

3, Directory "Python_code":
Description: Python scripts for plotting datasets
File Naming Convention: _Analysis.py
Filename Example: Daily_Analysis.py

4, Directory "Daily_Figures":
Description: Figures representing daily datasets
File Naming Convention: sub____.jpg
Filename Example: Sub_maxmin_CFSR_E(mm)_MIHU.jpg

5, Directory "Monthly_Figures":
Description: Figures representing monthly datasets
File Naming Convention: __.jpg
Filename Example: Mon_NBS(cms)_MIHU.jpg

List of abbreviations:
P: Overlake Precipitation
E: Overlake Evaporation
R: Total Runoff
NBS: Net Basin Supply
CNBS: Component Net Basin Supply
RNBS: Residual Net Basin Supply
SU: Lake Superior
MIHU: Lake Michigan-Huron
ER: Lake Erie
ON: Lake Ontario
ERA5: Fifth Generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis
ERA-Interim: ECMWF Re-Analysis Interim
MERRA: Modern-Era Retrospective analysis for Research and Applications, version 2
CFSR: Climate Forecast System Reanalysis
NARR: North American Regional Reanalysis
JRA: Japanese Reanalysis
GLERL: NOAA Great Lakes Environmental Research Laboratory

Related publication(s):
Hong Y., et al. (2024). A Daily Hydro-Meteorological Dataset for The World’s Largest System of Lakes . Nature Scientific Data.

Use and Access:
This data set is made available under a Creative Commons Public Domain license (CC0 1.0).