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Journal Article

Climate and vegetation: An ERA-Interim and GIMMS NDVI analysis


Cai,  Danlu
Max Planck Fellows, MPI for Meteorology, Max Planck Society;


Fraedrich,  Klaus F.
Max Planck Fellows, MPI for Meteorology, Max Planck Society;

Zhang,  Ling
Max Planck Fellows, MPI for Meteorology, Max Planck Society;

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Cai, D., Fraedrich, K. F., Sielmann, F., Guan, Y., Guo, S., Zhang, L., et al. (2014). Climate and vegetation: An ERA-Interim and GIMMS NDVI analysis. Journal of Climate, 27, 5111-5118. doi:10.1175/JCLI-D-13-00674.1.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0019-E8BE-F
To complement geographical presentation of remote sensing vegetation information, the authors apply Budyko’s physical state space diagram to analyze functional climate relations. As an example, the authors use Interim ECMWF Re-Analysis (ERA-Interim) global weather data to provide the statistics (1982–2006) of climate states in a two-dimensional state space spanned by water demand (net radiation N) versus water/energy limitation (dryness ratio D of net radiation over precipitation). Embedding remote sensing–based Global Inventory Modeling and Mapping Studies (GIMMS) data [normalized difference vegetation index (NDVI) > 0.1] shows the following results: (i) A bimodal frequency distribution of unit areas (pixels) is aligned near D ~ 1 but separated meridionally, associated with higher and lower net radiation. (ii) Vegetation states are represented as (N, D, NDVI) triplets that reveal temperate and tropical forests crossing the border (D ~ 1) separating energy- and water-limited climates but unexpectedly show that they also exist in marginal regions (few pixels) of large dryness. (iii) Interannual variability of dryness is lowest where the largest climate mean NDVI values of greenness (forests) occur. The authors conclude that the combined (N, D, NDVI) analysis based on climate means has shown that tropical and temperate forests (NDVI > 0.6) are (i) not restricted to the energy-limited domain D < 1 (extending into the water-limited surface climate regime) and (ii) associated with low interannual variability of dryness. Thus, measures of interannual variability may be included in Budyko’s classical framework of geobotanic analysis of surface climates.