Published 2025 | Version v2
Dataset Open

A vegetation phenology dataset by integrating multiple sources using the Reliability Ensemble Averaging method

Authors/Creators

  • 1. ROR icon Beijing Normal University
  • 2. ROR icon University of Antwerp

Description

A vegetation phenology dataset for the Northern Hemisphere( the latitude ranging from 30°N to 90°N, the longitude ranging from -180°E to 180°E), including start of season (SOS_merge), SOS uncertainty range (SOS_merge_r), end of season (EOS_merge), and EOS uncertainty range (EOS_merge_r). This dataset is generated by merging four vegetation phenology datasets including MODIS MCD12Q2(https://lpdaac.usgs.gov/products/mcd12q2v061/), MEaSUREs VIPPHEN(https://lpdaac.usgs.gov/products/vipphen_ndviv004/), GIMMS NDVI3g(http://data.globalecology.unh.edu/data/GIMMS_NDVI3g_Phenology/), GIMMS NDVI4g(https://doi.org/10.5281/zenodo.7649107) using the reliability ensemble averaging method. The uncertainty range is calculated based on the weight of each dataset and the deviation between REA result and data sources, the upper and lower uncertainty limits are measured by REA result and the uncertainty range.

The spatial resolution of the new dataset is 0.05° and its temporal scale spans 1982–2022. The new dataset was validated using data from the ground-based PhenoCam dataset from 280 sites over the period 2000–2018, which provided 1410 site–year combinations.

The dataset is stored in TIFF format, the unit of “SOS_merge” and “EOS_merge” is day of year (DOY), and the unit of “SOS_merge_r” and “EOS_merge_r” is day.

Files

EOS_merge.tif

Files (5.4 GB)

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md5:86b3852cb938d72c2d2815c3077a7d55
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md5:4ded07ee6f059c318c0ddd871673791c
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md5:807c428a48f840ea101d58a0c42c069f
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md5:c27067548ac36e69e5e3ca81cf59e553
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md5:0be15fad7844dc8768ffaa25e4d7345b
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Additional details

References

  • Giorgi, F. and Mearns, L. O.: Calculation of Average, Uncertainty Range, and Reliability of Regional Climate Changes from AOGCM Simulations via the "Reliability Ensemble Averaging" (REA) Method, Journal of Climate, 15, 1141–1158, https://doi.org/10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2, 2002.
  • Gray, J., Sulla-Menashe, D., and Friedl, M. A.: User guide to collection 6 modis land cover dynamics (mcd12q2) product, NASA EOSDIS Land Processes DAAC: Missoula, MT, USA, 6, 1–8, 2019.
  • Didan, K., Barreto-Munoz, A., Miura, T., Tsend-Ayush, J., Zhang, X., Friedl, M., and Meyer, D.: Multi-Sensor Vegetation Index and Phenology Earth Science Data Records, 2018.
  • Wang, X., Xiao, J., Li, X., Cheng, G., Ma, M., Zhu, G., Altaf Arain, M., Andrew Black, T., and Jassal, R. S.: No trends in spring and autumn phenology during the global warming hiatus, Nat Commun, 10, 2389, https://doi.org/10.1038/s41467-019-10235-8, 2019.
  • Fu, Y. H., Geng, X., Chen, S., Wu, H., Hao, F., Zhang, X., Wu, Z., Zhang, J., Tang, J., and Vitasse, Y.: Global warming is increasing the discrepancy between green (actual) and thermal (potential) seasons of temperate trees, Global Change Biology, 29, 1377–1389, https://doi.org/10.1111/gcb.16545, 2023.