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51<br />

Regional modelling of climate and extremes in southeast China<br />

Laurent Li(1), Weilin Chen(2) and Zhihong Jiang(2)<br />

(1) Laboratoire de Météorologie Dynamique, CNRS/IPSL, Université Paris VI, France, li@lmd.jussieu.fr<br />

(2) Nanjing University of Information Science and Technology, Jiangsu Key Laboratory of Meteorological Disaster, China<br />

A variable-grid atmospheric general circulation model,<br />

LMDZ, with a local zoom over southeast China is used as a<br />

traditional regional model to investigate climate changes in<br />

terms of both mean and extremes. This regional version of<br />

LMDZ can also be interactively coupled to the global<br />

version of LMDZ in a two-way nesting manner.<br />

Two time slices of 30 years are chosen to represent<br />

respectively the end of the 20th century and the middle of<br />

the 21st century. The boundary conditions were taken from<br />

the outputs of three global coupled climate models. An<br />

evaluation of the simulated temperature and precipitation for<br />

the current climate shows that in general LMDZ reproduces<br />

well the spatial distribution of mean climate and extremes in<br />

southeast China, but the model has systematic cold bias in<br />

temperature and tends to overestimate the extreme<br />

precipitation.<br />

Scenario results show that in all seasons there is a<br />

significant increase for mean, maximum and minimum<br />

temperature in the entire region, associated with a<br />

decrease in the number of frost days and with an increase<br />

in the heat wave duration. The magnitudes and main<br />

spatial patterns of the changes in temperature extremes<br />

show a quite good consistency among the three global<br />

scenarios. A warming environment also gives rise to<br />

changes in extreme precipitation events. Precipitation<br />

extremes increase over most of southeast China, in a quite<br />

consistent manner among the three global scenarios<br />

Fig. 1: Annual-mean precipitation rate (mm/day) in the global model (left), in the regional model driven by the global model<br />

(middle), and in the regional model operated interactively with the global model (right).<br />

Fig.2: As in Fig.1, but for changes of precipitation (2050-2000).

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