
Monitoring soil carbon / increase soil carbon sequestration is of exteme importance for climate change mitigation. The OEMC project will produce 1km daily climate element (max., min., mean temperature, sea level pressure, total precipitation) maps to support the creation and monitoring of carbon credit projects under VERRA methodology for the estimation of baseline scenario carbon emissions. This will help to fill a need in financial analysis and design of Regenerative Agriculture projects, specifically in the estimation of future soil carbon sequestration.
What is the challenge?
There is a lack of detailed daily climate data for accurate modeling of carbon sequestration, and existing datasets lack the necessary spatial and temporal detail. This data is essential to the creation and monitoring of Regenerative Agriculture projects, specifically in the estimation of future soil carbon sequestration using the models such as RothC, CENTURY, etc.
Our solution
Providing high resolution (1 km) daily maps of maximum, minimum, and mean temperature, sea level pressure, and total precipitation.
Who will benefit?
Regenerative agriculture project proponents, academic community, One Carbon World, regenerative agriculture project developers, organizations using RothC and CENTURY, and carbon cycle researchers will all benefit from this use case.
Scope
Target Partner Organizations
OEMC Leading Partner
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Type of output
High resolution (1 km) daily maps of maximum, minimum, and mean temperature, sea level pressure, and total precipitation.
Technology readiness level
TRL3: Experimental proof of concept
Location
Worldwide
Links of interest
- MeteoEurope1km: a high-resolution daily gridded meteorological dataset for Europe for the 1991–2020 period
- Spatio-temporal interpolation of daily temperatures for global land areas at 1 km resolution
- Random Forest Spatial Interpolation
- A high-resolution daily gridded meteorological dataset for Serbia made by Random Forest Spatial Interpolation
- Aleksandar Sekulić: MeteoEurope1km - a high-resolution daily gridded meteorological dataset