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Desai, A. R.*; Wohlfahrt, G.*; Zeeman, M. J.*; Katata, Genki; Eugster, W.*; Montagnani, L.*; Gianelle, D.*; Mauder, M.*; Schmid, H. P.*
Environmental Research Letters, 11(2), p.024013_1 - 024013_9, 2016/02
Times Cited Count：21 Percentile：58.47(Environmental Sciences)Regional ecosystem productivity is highly sensitive to inter-annual climate variability, both within and outside the primary carbon uptake period. However, Earth system models lack sufficient spatial scales and ecosystem processes to resolve how these processes may change in a warming climate. Here, we show, how for the European Alps, mid-latitude Atlantic ocean winter circulation anomalies drive high-altitude summer forest and grassland productivity, through feedbacks among orographic wind circulation patterns, snowfall, winter and spring temperatures, and vegetation activity. Therefore, to understand future global climate change influence to regional ecosystem productivity, Earth systems models need to focus on improvements towards topographic downscaling of changes in regional atmospheric circulation patterns and to lagged responses in vegetation dynamics to non-growing season climate anomalies.
Katata, Genki; Nagai, Haruyasu; Wrzesinsky, T.*; Klemm, O.*; Eugster, W.*; Burkard, R.*
Journal of Applied Meteorology and Climatology, 47(8), p.2129 - 2146, 2008/08
Times Cited Count：30 Percentile：58.06(Meteorology & Atmospheric Sciences)A land surface model including cloud water deposition to vegetation was developed to better predict water exchanges between biosphere and atmosphere. High performance of our new model was confirmed and it provided a better prediction of measured cloud water flux than the commonly used model. Simple linear relationships between wind speed and deposition velocity (
) were found. Numerical experiments were performed to study the influences of leaf shapes (needle and broad leaves) and canopy structure (Leaf area index (LAI) and canopy height) on . Broad leaves with small sized leaves can capture larger amounts of cloud water than needle leaves. From the analyses of conductances at given Leaf Area Density (LAD), we found that trees whose LAD 
0.1 m
m
are the most efficient structures for cloud water deposition. A simple expression for the slope of against LAD obtained from the experiments can be useful to predict cloud water deposition.
Katata, Genki; Nagai, Haruyasu; Wrzesinsky, T.*; Klemm, O.*; Eugster, W.*; Reto, B.*
no journal, ,
Several experiments focusing on cloud (fog) water deposition on the land surface suggest that cloud water plays an important role in water resource in arid and semi-arid areas. A one-dimensional vegetation model including the process of cloud water deposition on vegetation has been developed to better predict cloud water deposition on the vegetation. High performance of the model was confirmed by comparisons of calculated surface heat and cloud water fluxes over the forest with measurements acquired at the Norway spruce forest in the Waldstein, Germany. Numerical experiments to examine the dependence of cloud water deposition on the vegetation species and structures are performed using the presented model. The results showed that the differences of leaf shape and size have a large impact on cloud water deposition and cloud water deposition varies with the growth of vegetation and seasonal change of Leaf Area Index (LAI).
