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X. H. Meng, J. P. Evans, and M. F. McCabe

Abstract

Moderate Resolution Imaging Spectroradiometer (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 2000–08. 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 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 6–8 months in nonarid 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 long enough, reductions in vegetation cover and vigor occur, reducing the evapotranspiration and thus reducing the soil moisture decreases and dampening the fast physical feedback. Importantly, it was observed that these feedbacks are both space and time dependent.

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E. J. Barton, C. M. Taylor, C. Klein, P. P. Harris, and X. Meng

Abstract

Convection over the Tibetan Plateau (TP) has been linked to heavy rain and flooding in downstream parts of China. Understanding processes which influence the development of convection on the TP could contribute to better forecasting of these extreme events. TP scale (~1000 km) soil moisture gradients have been shown to influence formation of convective systems over the eastern TP. The importance of smaller-scale (~10 km) variability has been identified in other regions (including the Sahel and Mongolia) but has yet to be investigated for the TP. In addition, compared to studies over flat terrain, much less is known about soil moisture–convection feedbacks above complex topography. In this study we use satellite observations of cold cloud, land surface temperature, and soil moisture to analyze the effect of mesoscale soil moisture heterogeneity on the initiation of strong convection in the complex TP environment. We find that strong convection is favored over negative (positive) land surface temperature (soil moisture) gradients. The signal is strongest for less vegetation and low topographic complexity, though still significant up to a local standard deviation of 300 m in elevation, accounting for 65% of cases. In addition, the signal is dependent on background wind. Strong convective initiation is only sensitive to local (tens of kilometers) soil moisture heterogeneity for light wind speeds, though large-scale (hundreds of kilometers) gradients may still be important for strong wind speeds. Our results demonstrate that, even in the presence of complex topography, local soil moisture variability plays an important role in storm development.

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