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Full catalog/CMIP245-winter-median-ta
CMIP245-winter-median-ta·dataset

Projected Winter Temperature Changes: Moderate-Emissions Scenario

Projected changes to winter (January, February, and March) average daily air temperature
land NASA VEDA COG
In plain English

What it measures. Shows how much average winter (January–March) air temperature is projected to change versus the 1995–2014 baseline, across future 20-year periods.

How it's made. Built from an ensemble of CMIP6 climate models under the moderate SSP2-4.5 scenario, downscaled to local detail by NASA's NEX-GDDP method.

How & where you'd use it. Helps communities prepare for warmer winters and shifting cold-season patterns under moderate emissions.

What's measured

CMIP245wintermedian

Coverage & cadence

  • Time span2025-01-01 → 2085-03-31
  • Spatial extent-126, 30, -104, 51
  • FormatsCOG

What you can do with it

  • Track deforestation, fire scars and land-cover change
  • Monitor crop and vegetation health (NDVI/EVI)
  • Map how built-up vs. green an area is over time
Official description

Differences in winter (January, February, and March) average daily air temperature between a historical period (1995 - 2014) and multiple 20-year periods from an ensemble of CMIP6 climate projections (SSP2-4.5) downscaled by NASA Earth Exchange (NEX-GDDP-CMIP6)

Get the data

veda_access.py
# NASA VEDA — open STAC API, anonymous (cloud-optimized GeoTIFFs)
from pystac_client import Client

cat = Client.open("https://openveda.cloud/api/stac")
col = cat.get_collection("CMIP245-winter-median-ta")
items = list(col.get_items())          # browse the analysis-ready COGs
# open an asset with rioxarray:
# import rioxarray; da = rioxarray.open_rasterio(items[0].assets["cog_default"].href)
NASA VEDA is an open STAC catalog — browse and stream the cloud-optimized GeoTIFFs anonymously (no login).