Received: 20 May 2015 – Accepted for review: 26 May 2015 – Discussion started: 22 Jun 2015
Abstract. A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen–Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8 % for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity.
How to cite. Los, S. O.: Modelling spatial and temporal vegetation variability with the Climate Constrained Vegetation Index: evidence of CO2 fertilisation and of water stress in continental interiors, Geosci. Model Dev. Discuss., 8, 4781–4821, https://doi.org/10.5194/gmdd-8-4781-2015, 2015.
A model was developed to simulate spatio-temporal variations in vegetation in response to temperature, precipitation and atmospheric CO2 levels. The model reproduced variations in vegetation well; it showed a greater response to drought stress in N Hemisphere continents than previous implementations and showed a decline in vegetation during the US dust bowl (1930s and 1950s) and the drought of the century in the Sahel (1984). Vegetation greenness increased in response to atmospheric CO2 levels.
A model was developed to simulate spatio-temporal variations in vegetation in response to...