The SNAP Climate Analytics Shiny app has been updated. Previously, the app included seasonally and annually aggregated data. With the recent inclusion of monthly data, the number of conditional spatio-temporal climate probability distributions has now increased from a base set of about 13 million unique distributions to over 46 million. The Season dropdown menu now offers annual average, 3-month seasonals, and individual months.
These conditional distributions for historical and projected temperature and precipitation over different geographic regions, time periods, climate models and greenhouse gas emissions scenarios represent the source data sets available in the app.
I have posted a new R data animation video. It’s an example animation of modeled historical and projected global temperature change from 1850 - 2100. The data prep, analysis, full processing and generation of all sets of still frames for each layer in the video are done using R.
Typically an ensemble of models would be used but this video is just to demonstrate a basic animation using one climate model, both with a monthly time series and a monthly 10-year moving average time series.