摘要 :
This paper analyzed the anomalous low-temperature events and the anomalous rain-abundant events in January since 1951 and winter since 1880 for southern China. The anomalous events are defined using ±1σ thresholds. Twelve cold J...
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This paper analyzed the anomalous low-temperature events and the anomalous rain-abundant events in January since 1951 and winter since 1880 for southern China. The anomalous events are defined using ±1σ thresholds. Twelve cold Januaries are identified where temperature anomaly below -1σ, and ten wet Januaries are identified where precipita-tion anomaly above +1σ. Among these events there are three patterns of cold-wet Januaries, namely 1969, 1993 and 2008. The NCEP/NCAR reanalysis data are used to check the at-mospheric circulation changes in association with the anomalous temperature and precipita-tion events. The results show that the strong Siberian High (SBH), East Asian trough (EAT) and East Asian jet stream (EAJS) are favorable conditions for low-temperature in southern China. While the anomalous southerly flow at 850 hPa, the weak EAT at 500 hPa, the strong Middle East jet stream (MEJS) and the weaker EAJS are found to accompany a wetter southern China. The cold-wet winters in southern China, such as January of 2008, are mainly related to a stronger SBH, and the circulation in the middle to upper troposphere is precipita-tion-favorable. In wet winters, the water vapor below 500 hPa is mainly transported by the anomalous southwesterly flow and the anomalous southern flow over the Indo-China Penin-sula and the South China Sea area. The correlation coefficients of MEJS, EAMW (East Asian meridional wind) and EU (Eurasian pattern) to southern China precipitation in January are +0.65, -0.59 and -0.48 respectively, and the correlations for high-pass filtered data are +0.63, -0.55 and -0.44 respectively, the significant level is all at 99%. MEJS, EAMW and EU to-gether can explain 49.4% variance in January precipitation. Explained variance for January and winter temperature by SBH, EU, WP (west Pacific pattern) and AO (Arctic Oscillation) are 47.2% and 51.5%, respectively. There is more precipitation in southern China during El Nitro winters, and less precipitation during La Nina winters. And there is no clear evidence that the occurrence of anomalous temperature events in winter over southern China is closely linked to ENSO events.
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摘要 :
森林生态系统能够有效地吸收大气中的CO2,在一定程度上缓解全球变暖的压力.生态系统固碳能力取决于两个关键因素:NPP的增长强度与碳周转时间.论文通过对遥感监测到的森林生态系统NPP增长趋势进行校正,结合森林样地实测数据得到的碳分配系数与周转时间...
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森林生态系统能够有效地吸收大气中的CO2,在一定程度上缓解全球变暖的压力.生态系统固碳能力取决于两个关键因素:NPP的增长强度与碳周转时间.论文通过对遥感监测到的森林生态系统NPP增长趋势进行校正,结合森林样地实测数据得到的碳分配系数与周转时间,建立了中国森林生态系统碳周转模型,并模拟了1982～1999年森林生态系统的碳汇量及其年际变化.结果表明:1982～1999年,我国森林生态系统的平均碳汇量为0.051 PgC a-1,其中植被的碳汇量为0.034 PgC a-1,凋落物的碳汇量为0.013 PgC a-1,土壤的碳汇量为0.004 PgC a-1;不同森林类型中,常绿针叶林和常绿阔叶林的碳汇贡献最大,落叶针叶林和针阔叶混交林贡献最小;进一步分析表明森林植被的固碳效率显著地受到碳周转时间的控制.
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