Climate and Vegetation: An ERA-Interim and GIMMS NDVI Analysis

Author:

Cai Danlu1,Fraedrich Klaus2,Sielmann Frank3,Guan Yanning2,Guo Shan2,Zhang Ling4,Zhu Xiuhua3

Affiliation:

1. * Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China, and Max Planck Institute for Meteorology, Hamburg, Germany, and University of the Chinese Academy of Sciences, Beijing, China

2. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China

3. KlimaCampus, University of Hamburg, Hamburg, Germany

4. Max Planck Institute for Meteorology, Hamburg, Germany

Abstract

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.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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