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Full catalog/lis-tws-nonstationarity-index
lis-tws-nonstationarity-index·dataset

Where the Global Water Cycle Is Shifting

Global TWS Non-Stationarity Index
land NASA VEDA COG
In plain English

What it measures. Maps a worldwide index showing where stored land water is breaking from its normal patterns of trend, seasonal timing, and variability, for 2003 to 2020. Lower values mark places where the water cycle is changing most.

How it's made. Modelled by NASA's Land Information System by jointly blending MODIS vegetation, ESA soil moisture, and GRACE satellite gravity data at 10-kilometre detail.

How & where you'd use it. Helps scientists pinpoint regions where the water cycle is destabilising under climate change.

What's measured

listwsnonstationarityindex

Coverage & cadence

  • Time span2003-01-01 → 2020-01-01
  • Spatial extent-179.95, -59.95, 179.95, 89.95
  • 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

The global Terrestrial Water Storage (TWS) non-stationarity index integrates the trend, seasonal shifts, and variability change of TWS for the period of 2003 - 2020. TWS is derived by jointly assimilating the MODIS Leaf Area Index, the ESA CCI surface soil moisture, and the GSFC GRACE mascon-based TWS anomalies into the Noah-MP land surface model within the NASA Land Information System (LIS) at 10 km spatial resolution forced by the combination of MERRA2 and IMERG meteorological fields. The smaller the non-stationarity index is, the more the water cycle is under a non-stationary process. Glaciers and Greenland are excluded from the analysis.

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("lis-tws-nonstationarity-index")
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).