Global Gridded 1-km Annual Soil Respiration and Uncertainty Derived from SRDB V3

This dataset provides six global gridded products at 1-km resolution of predicted annual soil respiration (Rs) and associated uncertainty, maps of the lower and upper quartiles of the prediction distributions, and two derived annual heterotrophic respiration (Rh) maps. A machine learning approach was used to derive the predicted Rs and uncertainty data using a quantile regression forest (QRF) algorithm trained with observations from the global Soil Respiration Database (SRDB) version 3 spanning from 1961 to 2011. The two Rh maps were derived from the predicted Rs with two different empirical equations. These products were produced to support carbon cycle research at local- to global-scales, and highlight the immense spatial variability of soil respiration and our ability to predict it across the globe.

Data and Resources

Additional Info

Field Value
Maintainer Earthdata Forum
Last Updated August 11, 2025, 15:47 (UTC)
Created March 20, 2025, 16:09 (UTC)
accessLevel public
bureauCode {026:00}
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
harvest_object_id b0bf3820-b8f3-4d30-8783-f6464322b8cd
harvest_source_id 44069cc8-d515-495f-9ea4-b67f76a0a7cb
harvest_source_title Science Discovery Engine
identifier 10.3334/ORNLDAAC/1736
landingPage https://doi.org/10.3334/ORNLDAAC/1736
modified 2025-08-08
programCode {026:000}
publisher ORNL_DAAC
references {https://daac.ornl.gov/graphics/browse/project/square/cms_logo_square.png}
resource-type Dataset
source_datajson_identifier true
source_hash 204d078142e12f1f4c471f4aed6ee480b52ea5b4b330a9b696794442542bad0a
source_schema_version 1.1
spatial [[{"WestBoundingCoordinate":-180.0,"NorthBoundingCoordinate":90.0,"EastBoundingCoordinate":180.0,"SouthBoundingCoordinate":-90.0}],"CARTESIAN"]
temporal 1963-01-01/1963-01-01
theme {"Earth Science"}