README for Physical and biogeochemical observations from Bear Lake, New York, USA: 2024-2026

This resource contains observations from Bear Lake, an open-basin, dimictic lake in western New York State, USA. These data were collected to gain a comprehensive understanding of the modern lake system to support numerical model calibration and interpretation of paleoclimate data from lake sediments.

Resource map

📦 Bear Lake resource
│   ⭐ readme.md
│   📄 BearLake-limnology-observations-MASTERFILE.csv
|   📄 BearLake-area-depth-slices.csv
│
└─── 📂 raw_data
│   │   ⭐ readme-METHODS.md
|   |
│   └───📂 bathymetry
|   |
│   └───📂 logger_raw_files
|   |
│   └───📂 sonde_raw_files
|
│─── 📂 scripts
|   |   📄 clean-logger-data-BearLake.R
|   |   📄 get-AreaDepthslices-BearLake.R
|   |   📄 process-sonde-data.R
|   |   📄 select-variables-and-make-plots-WNY-database.ipynb
|
│─── 📂 figures

File descriptions

(1) BearLake-limnology-observations-MASTERFILE.csv

This file contains all post-processed daily average biogeochemical and physical observations, excluding bathymetry. Measurements of water stable oxygen and hydrogen isotope values were made at the Organic and Stable Isotope Biogeochemistiry Laboratory (OSIBL) at the University at Buffalo. Water isotope measurements in this file include both lake water and groundwater from a nearby well.

Here are the column descriptions in the file:

(2) BearLake-area-depth-slices.csv

This file includes the lake area for every 1-meter depth slice. These values were generated from Google Earth contour lines (BearLake-contours.kml) using the R script in the scripts folder. These values were used as an input parameter for numerical modeling work. Columns are Depth in meters and Area in hectares.

(4) Files in the raw_data folder

These are raw data files that come directly from the instruments (data loggers, sonde, bathymetry contours).

(5) Files in the scripts folder

These are code scripts in Python and R that walk through how the raw datasets were processed to e.g. remove measurements made on shore, correct for slight changes in logger depths between deployments, aggregate from 30-minute to daily averages, etc. The readme-METHODS.md file has details on what the codes do and how the datasets were generated and processed in words.

Contact rgtopnes@buffalo.edu with any questions about the datasets.