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SUMMARY:Scaling land-atmosphere fluxes from sites to globe: Overview and s
 ynthesis of the FLUXCOM approach - Dr Martin Jung | Max Planck Institute o
 f Biogeochemistry
DTSTART:20211026T100000Z
DTEND:20211026T113000Z
UID:TALK165055@talks.cam.ac.uk
CONTACT:Tudor Suciu
DESCRIPTION:FLUXNET comprises globally distributed eddy-covariance-based e
 stimates of carbon fluxes between the biosphere and the atmosphere. Since 
 eddy covariance flux towers have a relatively small footprint and are dist
 ributed unevenly across the world\, upscaling the observations is necessar
 y to obtain global-scale estimates of biosphere-atmosphere exchange. Based
  on cross-consistency checks with atmospheric inversions\, sun-induced flu
 orescence (SIF) and dynamic global vegetation models (DGVMs)\, here we pro
 vide a systematic assessment of the latest upscaling efforts for gross pri
 mary production (GPP) and net ecosystem exchange (NEE) of the FLUXCOM init
 iative\, where different machine learning methods\, forcing data sets and 
 sets of predictor variables were employed.\n\nSpatial patterns of mean GPP
  are consistent across FLUXCOM and DGVM ensembles (R^2^>0.94 at 1^∘^ spa
 tial resolution) while the majority of DGVMs show\, for 70 % of the land
  surface\, values outside the FLUXCOM range. Global mean GPP magnitudes fo
 r 2008–2010 from FLUXCOM members vary within 106 and 130 PgC yr^−1
 ^ with the largest uncertainty in the tropics. Seasonal variations in inde
 pendent SIF estimates agree better with FLUXCOM GPP (mean global pixel-wis
 e R^2^∼0.75) than with GPP from DGVMs (mean global pixel-wise R^2^∼0.6
 ). Seasonal variations in FLUXCOM NEE show good consistency with atmospher
 ic inversion-based net land carbon fluxes\, particularly for temperate and
  boreal regions (R^2^>0.92). Interannual variability of global NEE in FLUX
 COM is underestimated compared to inversions and DGVMs. The FLUXCOM versio
 n which also uses meteorological inputs shows a strong co-variation in int
 erannual patterns with inversions (R^2^=0.87 for 2001–2010). Mean region
 al NEE from FLUXCOM shows larger uptake than inversion and DGVM-based esti
 mates\, particularly in the tropics with discrepancies of up to several hu
 ndred grammes of carbon per square metre per year. These discrepancies can
  only partly be reconciled by carbon loss pathways that are implicit in in
 versions but not captured by the flux tower measurements such as carbon em
 issions from fires and water bodies. We hypothesize that a combination of 
 systematic biases in the underlying eddy covariance data\, in particular i
 n tall tropical forests\, and a lack of site history effects on NEE in FLU
 XCOM are likely responsible for the too strong tropical carbon sink estima
 ted by FLUXCOM. Furthermore\, as FLUXCOM does not account for CO2 fertiliz
 ation effects\, carbon flux trends are not realistic. Overall\, current FL
 UXCOM estimates of mean annual and seasonal cycles of GPP as well as seaso
 nal NEE variations provide useful constraints of global carbon cycling\, w
 hile interannual variability patterns from FLUXCOM are valuable but requir
 e cautious interpretation. Exploring the diversity of Earth observation da
 ta and of machine learning concepts along with improved quality and quanti
 ty of flux tower measurements will facilitate further improvements of the 
 FLUXCOM approach overall.
LOCATION:https://zoom.us/j/6708259482?pwd=Qk03U3hxZWNJZUZpT2pVZnFtU2RRUT09
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