This study analyzed the changes in precipita- tion over summer and autumn across the Yunnan region of China, and undertook a composite analysis of the atmo- spheric circulations in the troposphere, which included an analysis of the interannual and interdecadal variations. This paper examines in detail the circulation backgrounds of the wet and dry periods in summer and autumn and their correlations with the sea surface temperature. The results indicated that the summer and autumn precipitation across Yunnan has significantly decreased over the past 50 years. Furthermore, since the beginning of the century, the summer and autumn precipitation cycle has been in a low precipitation phase. The overlap of two extremely low rain phases has caused frequent droughts in the region. In addition, the atmospheric circulation fields during these wet and dry periods are very different. These are mainly shown as a meridional wind anomaly in eastern China in the low atmosphere, as a cross-equatorial airflow anomaly, a tropical zonal wind anomaly over the Indian Ocean, and as a related South Asia High and Western Pacific Subtropical High. Further analysis suggested that the SST over the Indian Ocean and the Pacific warm pool critically affect the anomalous summer and autumn precipitation over Yunnan by impacting the monsoon circulations. Future projections for greenhouse gas wann- ing suggest a potential anomalous circulation background between 2010 and 2020 which may result in less precipitation during the wet season or even drought events across the Yunnan region.
Climatological patterns in wind fluctuations on time scales of 1–10 h are analyzed at a meteorological mast at the Yangmeishan wind farm, Yunnan Province,China, using a 2-yr time series of 10-min wind speed observations. For analyzing the spectral properties of nonstationary wind fluctuations in mountain terrain, the Hilbert-Huang transform(HHT) is applied to investigate climatological patterns between wind variability and several variables including time of year, time of day, wind direction, and pressure tendency. Compared with that for offshore sites, the wind variability at Yangmeishan wind farm has a more distinct diurnal cycle, but the seasonal discrepancies and the differences according to directions are not distinct, and the synoptic influences on wind variability are weaker. There is enhanced variability in spring and winter compared with summer and autumn. For flow from the main direction sector, the maximum wind variability is observed in spring. And the severe wind fluctuations are more common when the pressure tendency is rising.
One of the major high-latitude circulation systems in the Southern Hemisphere is the Southern Annular Mode(SAM). Its effect on the Somali Jet(SMJ), which connects the Southern and Northern hemispheres, cannot be ignored. The present reported results show that time series of both the Southern Annular Mode Index(SAMI) during the preceding winter and the summertime Somali Jet intensity Index(SMJI) display a significant increasing trend and have similar interdecadal variation. The latter was rather strong around 1960, then became weaker up to the mid-1980 s, before starting to strengthen again. The lead-lag correlations of monthly mean SAMI with the following summertime SMJI showed significant positive correlations in November, December, and January. There are thus connections across two seasons between the SAM and the SMJ. The influence of the winter SAM on the summer SMJ was explored via analyses of SST anomalies in the Southern Indian Ocean. During strong(weak) SAM/SMJ years, the SST east of Madagascar is colder(warmer) while the SST west of Australia is warmer(colder), corresponding to the positive(negative) Southern Indian Ocean Dipole-like(SIODL) event. Subsequently, the SIODL excites an anticyclone located over the Arabian Sea in summer through air-sea coupling from winter to summer, which causes an increase in the summer SMJ intensity. The anticyclone/high branch of the SAM over the Southern Hemisphere subtropics and the cyclone/low over the east coast of Madagascar play an important role in the formation of Southern Indian Ocean "bridge" from winter to summer.
Wind direction forecasting plays an important role in wind power prediction and air pollution management. Weather quantities such as temperature, precipitation, and wind speed are linear variables in which traditional model output statistics and bias correction methods are applied. However, wind direction is an angular variable; therefore, such traditional methods are ineffective for its evaluation. This paper proposes an effective bias correction technique for wind direction forecasting of turbine height from numerical weather prediction models, which is based on a circular-circular regression approach. The technique is applied to a 24-h forecast of 65-m wind directions observed at Yangmeishan wind farm, Yunnan Province, China, which consistently yields improvements in forecast performance parameters such as smaller absolute mean error and stronger similarity in wind rose diagram pattern.
