I am pleased to announce my CTS.csv file which includes 18 climate monthly time series in one easy to access csv file. This is part of my goal of having a user friendly way for do-it-yourself citizen climate scientists to get up-to-date agency climate time series in a painless way.
Update 1: Reader Scott asked if I could provide meta data for the columns in my CTS.csv. This page lists the source agency and data links for the climate data series.
Here’s a snap shot of the first 6 rows of my CTS.csv file. The data extends from 1880 until the most recent month. Click image to enlarge
My hope is to make the CTS.csv the go-to file for citizen climate scientists who may want to:
- Check temperature anomalies trends by series (GISS, HAD, NOAA, RSS, UAH)
- Assess climate oscillations(AMO, AO, MEI, Nino34, PDO) trends
- Evaluate CO2 versus temperature anomaly relationships
- Evaluate relationship between Sunspot numbers and anomaly temperature anomaly trends
- Compare atmospheric transmission, SATO index and volcanic activity
- Assess impact of volcanoes on temperature anomaly trends
- Compare MEI versus Nino ENSO 34 indicators
- Assess lower stratospheric trends using RSS’s TLS series
By having these climate time series in a single csv file, R and Excel users can work with up to date data in a convenient form. The file will be automatically updated monthly as the climate agencies release their latest data.
How can CTS.csv Help Do-It-Yourself Citizen Climate Scientists?
Interested climate observers who want to compare global SSTA versus Nino34 trends, for example, have to follow a multiphase process:
- Find data file – even with Google this can take time
- Download files
- Merge 2 or more files to get data into a usable format – source files all have different formats
- Perform analysis
Steps 1-3 can be very time consuming, so many users don’t bother checking out their ideas. Rather, they may rely on climate blog comments. With CTS.csv and some R or Excel analysis, they can find the facts themselves rather than just having opinions. They can submit their analysis and charts to blog posts, hopefully increasing the rigor of blog discussions.
Climate bloggers can request that their readers submit charts to back up their climate trend claims.
Data & RClimate Scripts Are All Open Book
Filed under: Citizen Climate Science, Do-it-yourself Climate Science, Global Warming, RClimate Script, Time Series Charts Tagged: R scripts