The impact of observed vegetation changes on land-atmosphere feedbacks during drought.

Meng., X., J.P. Evans and M.F. McCabe
Journal of Hydrometeorology, 15(2), 759-776, doi: 10.1175/JHM-D-13-0130.1, 2013.

Abstract

MODIS derived vegetation fraction data were used to update the boundary conditions of the advanced research Weather Research and Forecasting (WRF) model to assess the influence of realistic vegetation cover on climate simulations in southeast Australia for the period 2000 to 2008. Results show that modeled air temperature was improved when MODIS data were incorporated, while precipitation changes little with only a small decrease in the bias. Air temperature changes in different seasons reflect the variability of vegetation cover well, while precipitation changes have a more complicated relationship to changes in vegetation fraction. Both the MODIS and climatology-based simulation experiments capture the overall precipitation changes, indicating that precipitation is dominated by the large-scale circulation, with local vegetation changes contributing variations around these.

Simulated feedbacks between vegetation fraction, soil moisture and drought over southeast Australia were also investigated. Results indicate that vegetation fraction changes lag precipitation reductions by 6 to 8 months in non-arid regions. With the onset of the 2002 drought, a potential fast physical mechanism was found to play a positive role in the soil moisture-precipitation feedback, while a slow biological mechanism provides a negative feedback in the soil moisture-precipitation interaction on a longer time scale. That is, in the short term, a reduction in soil moisture leads to a reduction in the convective potential and hence precipitation, further reducing the soil moisture. If low levels of soil moisture persist for long enough, reductions in vegetation cover and vigor occur, reducing the evapotranspiration and hence reducing the soil moisture decreases and dampening the fast physical feedback. Importantly, it was observed that these feedbacks are both space and time dependent.

Key Figure

Distribution of the potential fast and slow mechanisms

Figure 12: Distribution of the potential fast and slow mechanisms that exist in monthly and annual variations in the WRF_MODIS simulations in 2002 and 2003.


UNSW    This page is maintaind by Jason Evans | Last updated 31st January 2013