Computing Agroclimate Metrics in R

Agroclimate metrics are the backbone of all manner of mathematical models of crop development, crop management, site suitability, and pest pressure. Common metrics include:

• degree days
• frost days
• first freeze
• winter chill accumulation
• extreme heat days
• diurnal temperature range
• maximum July temperature
• total precipitation
• and many others!

This workshop will demonstrate how to compute common agroclimate metrics in R. We will also learn how to import into R weather data for past, present, and future modeled weather data using R packages like caladaptR and cimir., and compute metrics using tidyverse methods and specialized packages like degday.

Audience:

• UC Cooperative Extension
• UC students & faculty
• AIFS affiliates (including Davis, Berkeley, Cornell, U. Illinois, & USDA)

When & Where:

Friday December 2, 2022. 11:00a - 12:30p

This is a virtual workshop. You will receive a Zoom link via email prior to the training day.

Cost: This is a free workshop.

Requirements:

To complete the hands-on exercises (optional), participants should have a RStudio Cloud account (free). The instructor will provide a RStudio Cloud project that will have all the scripts and data needed. RStudio Desktop users can download the files from GitHub.

Some experience with R and RStudio is expected. Most of the code samples in the hands-on exercises will be "ready to go", so even if you're not sure what you're doing you should still be able to run the code. If you have never used R before, you are welcome to watch but we will not have time to review or troubleshoot the basics.

The R scripts presented will make extensive use of data wrangling functions from dplyr, tidyr, and other tidyverse packages. If you are not familiar with these packages, consider taking Part 3 of the Intro to R workshop series on October 14 (or watch the recording).

Having an external monitor is strongly recommended, so you can view the instructor's slides and demo on one monitor, while working in RStudio on the other.

Registration:

Click here to register.

Note - This event may reach capacity, after which a waiting list will be created.

This course content is the result of a collaborative effort between UC ANR IGIS Statewide Program, the USDA-NIFA/NSF AI Institute for Next Generation Food Systems (AIFS), and the UC Berkeley Geospatial Innovation Facility (GIF).

For information regarding other upcoming IGIS workshops, please see IGIS training or contact Sean Hogan at sdhogan@ucanr.edu