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• SOS NDVI dates occurred much earlier than SOS dates from EVI, LSWI, GPP, and SIF. • SOS LSWI dates were more linearly consistent with SOS GPP and SOS SIF than EVI and NDVI. • Temperature analysis showed that early SOS NDVI dates were more likely affected by snowmelt. Accurate phenology characterization is of great importance for measuring ecosystem dynamics, especially for carbon and water exchange between land and the atmosphere. Vegetation indices (VIs), calculated from land surface reflectance, are widely used to estimate phenology from the leaf and canopy structure perspective. Gross Primary Production (GPP) and solar-induced chlorophyll fluorescence (SIF) are used to estimate phenology from the canopy functional (physiological) perspective. To what degree are the spring phenology estimated from these different perspectives consistent with each other? In this study, we evaluated the consistency of the start of the growing season (SOS) in spring for snow-covered evergreen needleleaf forests (ENF) and deciduous broadleaf forests (DBF) using three vegetation indices, in-situ GPP data from the eddy covariance flux towers (GPP EC), GPP data from the Vegetation Photosynthesis Model (GPP VPM), and SIF data from the GOME-2. Results showed that SOS NDVI dates were much earlier than SOS dates from EVI (SOS EVI), land surface water index (LSWI) (SOS LSWI), GPP (SOS GPP ; SOS GPP-EC , SOS GPP_VPM) and SIF (SOS SIF) for both snow-covered evergreen needleleaf forest (ENF) and deciduous broadleaf forest (DBF). SOS LSWI dates were more linearly correlated with SOS GPP and SOS SIF than SOS dates from NDVI and EVI. At ENF sites, SOS LSWI dates were 17 (± 27) days later and SOS EVI were 25 (± 34) days later than SOS GPP_EC dates. At DBF sites, SOS LSWI and SOS EVI dates were 1-week (± 13 days) later than SOS GPP_EC dates. In the snow-covered regions at mid- to high-latitude in the Northern Hemisphere, SOS LSWI dates were 2˜3 weeks (± 5 days) later than those of SOS GPP_VPM and SOS SIF for both ENF and DBF. Our results clearly highlight the need for further investigation of NDVI-based SOS dates, which were likely affected by snowmelt in snow-covered forests, and the potential of LSWI for tracking the effects of snow on SOS dates. Estimations of SOS dates in snow-covered forests should consider the effects of both snow cover and temperature on leaf emergence (green-up) and gross primary production. [ABSTRACT FROM AUTHOR]

• Optimum air temperature of photosynthesis from GPP EC agree well with those from MODIS EVI. • Optimum air temperature of photosynthesis from GPP EC and MODIS EVI differed substantially from those that are currently used in satellite-based models. • Use of optimum air temperature of photosynthesis from site-year specific or biome-specific approaches can affects global GPP estimates substantially. Gross primary productivity (GPP) of vegetation is affected by air temperature. Biogeochemical models use the optimum air temperature (T opt) parameter, which comes from biome-specific look-up tables (T opt − b − LT). Many studies have shown that plants have the capacity to adapt to changes in environmental conditions over time, which suggests that the static T opt − b − LT parameters in the biogeochemical models may poorly represent actual T opt and induce uncertainty in GPP estimates. Here, we estimated biome-specific, site-year-specific, and site-specific optimum air temperature using GPP data from eddy covariance (EC) flux tower sites (GPP EC) (T opt − b − EC , T opt − sy − EC , T opt − s − EC), the Enhanced Vegetation Index (EVI) from MODIS images (T opt − b − EVI , T opt − sy − EVI , T opt − s − EVI), and mean daytime air temperature (T DT). We evaluated the consistency among the four T opt parameters (T opt − b , T opt − sy , T opt − s and T opt − b − LT), and assessed how they affect satellite-based GPP estimates. We find that T opt parameters from MODIS EVI agree well with those from GPP EC , which indicates that EVI can be used as a variable to estimate T opt at individual pixels over large spatial domains. T opt − b , T opt − sy , and T opt − s differed significantly from T opt − b − LT. GPP estimates using T opt − b and T opt − sy were more consistent with GPP EC than when using T opt − b − LT for all the land cover types. Our use of T opt − sy substantially improved 8-day and annual GPP estimates across biomess (from 1% to 34%), especially for cropland, grassland, and open shrubland. Our simple calculation shows that global GPP estimates differ by up to 10 Pg C/yr when using our suggested T opt − sy − EVI instead of using the static T opt − b − LT. Our new approach on estimating T opt has the potential to improve estimates of GPP from satellite-based models, which could lead to better understanding of carbon-climate interactions. [ABSTRACT FROM AUTHOR]