Classify climate regions with Python - ESRI Tutorial

Tool Used: ArcGIS Pro (Python Notebook)
Skills Applied: Multidimensional Raster Analysis, Winkler Index Calculation, Climate Zoning
Dataset: NASA Daymet Daily Max/Min Temperature (2000–2020)
Course: Self-paced Project from Learn ArcGIS
Authors: Lain Graham, Josh Grail, Cole Walts, and Hong Xu (Esri)

Project Overview:
I tried the ESRI tutorial on Python Notebook in this project which mapped viticultural climate zoning in Napa County, California, using multidimensional climate data from NASA’s Daymet dataset. A 21-year subset (2000–2020) was defined for two key variables: daily maximum and minimum air temperature. The data was downloaded as .crf (Cloud Raster Format) files and processed in ArcGIS Pro using Python notebooks. Growing Degree Days (GDD) were calculated per pixel for each year to assess cumulative heat units. The resulting values were used to classify the region into six Winkler Index climate zones, a widely accepted framework in viticulture. A temporal chart was then generated to visualize how these zones shifted over time, providing insights into the ongoing impacts of climate change on Napa's wine industry.