A Data-driven Upscale Product of Global Gross Primary Production, Net Ecosystem Exchange and Ecosystem Respiration
Click Here to Download
The product includes 10-day means of global gross primary production (GPP), net ecosystem exchange (NEE), and ecosystem respiration (RECO) of 1999 to 2019 in 0.1x0.1 degree spatial resolution. Random Forest (RF) was used to upscale observations of FLUXNET 2015 to the globe from 60°S to 80°N. The daily GPP was extracted from GPP_NT_VUT_REF, NEE from NEE_VUT_REF and RECO from RECO_NT_VUT_REF in the FULLSET of FLUXNET 2015. Predictor variables include leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), air temperature (T), relative humidity (RH), downward solar radiation (DSR) on the surface, the minimum and maximum of LAI, and the number of LAI larger than the means of the minimum and maximum. The later three were derived to indicate the plant functional type (PFT) in each year and grid. They were expected to represent the temporal and spatial variations of PFT better than such product as BIOME4. So far as we were aware, all data-driven upscaling products used MODIS. We extracted LAI and FAPAR from the Copernicus Global Land Service; and T, RH and DSR from ERA5 of the European Centre for Medium-Range Weather Forecasts. This product using a different approach is expected to provide new information for studying global GPP, NEE, and RECO.
Description
Creator
|
|
Release date
|
2020/02/22
|
Temporal coverage
|
1999 - 2019
|
Data provider
|
NIES
Email: cgerdb_admin(at)nies.go.jp |
DOI
|
|
File format
|
|
Data volume
|
42.6 GiB
|
Version
|
ver.2020.2 (Last updated: 2020/10/14)
|
Language
|
English
|
Data Set
Parameters
|
GPP, NEE and RECO
|
Domain |
Global
|
Time resolution |
10 day
|
Spatial resolution |
0.1 x 0.1 degree
|
Calculation method |
Upscaling of site observations using Random Forest
|
Keywords
|
[GCMD_Platform]
Earth Observation Satellites > SPOT > SPOT-4
[GCMD_Science]BIOSPHERE > TERRESTRIAL ECOSYSTEMS
[Free keywords]GPP, NEE, RECO, FLUXNET, Machine Learning, Random Forest, ECMWF ERA5
|
Update history
|
[2020/10/14]
Update the reference DOI of data files. ver.2020.2.
[2020/03/11]In ver.2020.1, latitude and longitude were renamed according to COARDS NetCDF Conventions.
[2020/02/22]Data from 1999 to 2019 are released. ver.2020.
|
Terms and Conditions of Use*
*By accessing or using the Service you agree to follow these Terms. If you disagree with any part of the Terms, you may not access the Service.
License | |
Citation format |
When this data set is referred to in publications, it should be cited in the following format.
Zeng, J (2020), A Data-driven Upscale Product of Global Gross Primary Production, Net Ecosystem Exchange and Ecosystem Respiration, ver.xxxx *1, Center for Global Environmental Research, NIES, DOI:10.17595/20200227.001, (Reference date*2: YYYY/MM/DD)
*1 The version number is indicated in the name of each data file. *2 As the reference date, please indicate the date you downloaded the files. |
Advisory Service
Advisory service
|
If you need scientific advice or expert opinion regarding the contents or scientific validity of this data set or Products derived from it, we can provide an advisory service based on an individual contract, different from the above one.
Depending on the extent of the help required, we can offer collaboration and/or supervision of the work based on the present data set. If you want to use our advisory service, contact the Data Provider. |