Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products
(2018) In International Journal of Applied Earth Observation and Geoinformation 65. p.124-136- Abstract
The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperature at 2 m (Ta) from ERA-Interim data.... (More)
The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperature at 2 m (Ta) from ERA-Interim data. The GPP product (MSG GPP) was produced for 2012 and assessed by direct site-level comparison with GPP from eddy covariance data (EC GPP). MSG GPP presents relative bias errors lower than 40% for the most forest vegetation types with a high agreement (r > 0.7) when compared with EC GPP. For drylands, MSG GPP reproduces the seasonal variations related to water limitation in a good agreement with site level GPP estimates (RMSE = 2.11 g m−2 day−1; MBE = −0.63 g m−2 day−1), especially for the dry season. A consistency analysis against other GPP satellite products (MOD17A2 and FLUXCOM) reveals a high consistency among products (RMSD < 1.5 g m−2 day−1) over Europe, North and South Africa. The major GPP disagreement arises over moist biomes in central Africa (RMSD > 3.0 g m−2 day−1) and over dry biomes with MSG GPP estimates lower than FLUXCOM (MBD up to −3.0 g m−2 day−1). This newly derived product has the potential for analysing spatial patterns and temporal dynamics of GPP at the MSG spatial resolutions on a daily basis allowing to better capture the GPP dynamics and magnitude.
(Less)
- author
- organization
- publishing date
- 2018
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Daily, GPP, Light-use efficiency, LSA SAF, MSG, Water stress
- in
- International Journal of Applied Earth Observation and Geoinformation
- volume
- 65
- pages
- 13 pages
- publisher
- Elsevier
- external identifiers
-
- scopus:85036533746
- ISSN
- 1569-8432
- DOI
- 10.1016/j.jag.2017.10.011
- language
- English
- LU publication?
- yes
- id
- 037319a7-6479-4271-9940-9b58701d3f55
- date added to LUP
- 2017-12-21 08:56:00
- date last changed
- 2022-04-09 20:59:32
@article{037319a7-6479-4271-9940-9b58701d3f55, abstract = {{<p>The main goal of this paper is to derive a method for a daily gross primary production (GPP) product over Europe and Africa taking the full advantage of the SEVIRI/MSG satellite products from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) sensors delivered from the Satellite Application Facility for Land Surface Analysis (LSA SAF) system. Special attention is paid to model the daily GPP response from an optimized Montheith's light use efficiency model under dry conditions by controlling water shortage limitations from the actual evapotranspiration and the potential evapotranspiration (PET). The PET was parameterized using the mean daily air temperature at 2 m (T<sub>a</sub>) from ERA-Interim data. The GPP product (MSG GPP) was produced for 2012 and assessed by direct site-level comparison with GPP from eddy covariance data (EC GPP). MSG GPP presents relative bias errors lower than 40% for the most forest vegetation types with a high agreement (r > 0.7) when compared with EC GPP. For drylands, MSG GPP reproduces the seasonal variations related to water limitation in a good agreement with site level GPP estimates (RMSE = 2.11 g m<sup>−2</sup> day<sup>−1</sup>; MBE = −0.63 g m<sup>−2</sup> day<sup>−1</sup>), especially for the dry season. A consistency analysis against other GPP satellite products (MOD17A2 and FLUXCOM) reveals a high consistency among products (RMSD < 1.5 g m<sup>−2</sup> day<sup>−1</sup>) over Europe, North and South Africa. The major GPP disagreement arises over moist biomes in central Africa (RMSD > 3.0 g m<sup>−2</sup> day<sup>−1</sup>) and over dry biomes with MSG GPP estimates lower than FLUXCOM (MBD up to −3.0 g m<sup>−2</sup> day<sup>−1</sup>). This newly derived product has the potential for analysing spatial patterns and temporal dynamics of GPP at the MSG spatial resolutions on a daily basis allowing to better capture the GPP dynamics and magnitude.</p>}}, author = {{Martínez, B. and Sanchez-Ruiz, S. and Gilabert, M. A. and Moreno, A. and Campos-Taberner, M. and García-Haro, F. J. and Trigo, I. F. and Aurela, M. and Brümmer, C. and Carrara, A. and De Ligne, A. and Gianelle, D. and Grünwald, T. and Limousin, J. M. and Lohila, A. and Mammarella, I. and Sottocornola, M. and Steinbrecher, R. and Tagesson, T.}}, issn = {{1569-8432}}, keywords = {{Daily; GPP; Light-use efficiency; LSA SAF; MSG; Water stress}}, language = {{eng}}, pages = {{124--136}}, publisher = {{Elsevier}}, series = {{International Journal of Applied Earth Observation and Geoinformation}}, title = {{Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products}}, url = {{https://lup.lub.lu.se/search/files/86152499/JAG_D_17_00309R2_final_version.pdf}}, doi = {{10.1016/j.jag.2017.10.011}}, volume = {{65}}, year = {{2018}}, }