Multi-source climate data synthesis for RMBL

Knowledge graph centered on Multi-source climate data synthesis for RMBL with 10 nodes and 20 connections. Top connected: Rocky Mountain Biological Laboratory, Crested Butte, Snodgrass Mountain, Climate data from the Rocky Mountain Biological La, Rebecca M. Dalton.

Method synopsis

Synthesis of climate records from five different sources (resident observer, NOAA, USGS, USDA, and PRISM) with standardized protocols for handling missing data and format inconsistencies. Includes calculation of derived ecological variables and multi-temporal summary statistics.

Synthesized from method descriptions across 1 paper using this protocol.

Procedure as described in the canonical source

Steps below were extracted from the paper that introduces this protocol — Climate data from the Rocky Mountain Biological Laboratory (1975–2022) (2023), Ecology. Implementations in other papers (listed below) may differ.

1. Collect existing climate data from five sources
   Gathered climate records from: (1) RMBL resident billy barr's observations, (2) National Oceanic and Atmospheric Administration (NOAA) automated meteorological station in Crested Butte CO, (3) United States Geological Survey (USGS) automated meteorological station in Crested Butte CO, (4) United States Department of Agriculture (USDA) automated meteorological station on Snodgrass Mountain, and (5) Oregon State University's PRISM Climate Group data.
   Quantities: Five distinct data sources covering the Rocky Mountain Biological Laboratory vicinityDuration: Data spanning 1975-2022 (47 years)Conditions: NOAA and USGS stations located approximately 10 km from RMBL in Crested Butte, CO; USDA station located approximately 2.5 km from RMBL on Snodgrass Mountain
   Equipment: Automated meteorological stations
2. Standardize data formatting and handle missing values
   Applied consistent formatting across all five data sources and implemented standardized protocols for handling missing data, with all decisions documented in annotated scripts.
   Quantities: Daily observations from all five sourcesDuration: Applied to entire 47-year datasetConditions: Each data source had unique spatial and temporal coverage and formats requiring standardization
   Equipment: R statistical software
3. Calculate derived ecological variables
   Computed new variables commonly used in ecological analyses from the daily weather records, including growing degree days, growing season length, cold severity index, hard frost days, El Niño-Southern Oscillation index, and aridity (standardized precipitation evapotranspiration index).
   Quantities: Multiple derived variables calculated from daily records

Typical Equipment

• Automated meteorological stations
• R statistical software

Output Measurements

• daily climate observations
• growing degree days
• growing season length
• cold severity index
• hard frost days
• El Niño-Southern Oscillation index
• standardized precipitation evapotranspiration index

Papers Using This Protocol (1)

Places Where Used