计及季度趋势变时间步长风速仿真模型及应用

为提高风电并网系统充裕度评估精度,提出计及季度趋势的变时间步长风速仿真模型。该模型应用奇异谱分析从风速样本中提取季度趋势和随机波动分量,应用线性插值和奥恩斯坦-乌伦贝克过程对两分量建模,产生任意时间步长的仿真风速样本。将该模型嵌入蒙特卡罗模拟法,提出风电并网系统的季度充裕度评估方法。应用该模型仿真某观测站风速样本,评估风电并网IEEE-RTS发电系统的季度充裕度,结果表明,该模型可产生与实测风速样本统计指标等特征接近的任意时间步长仿真风速样本,且季度充裕度评估精度较高。

关于主导产品销量的“趋势—季度”变动预测

通过对主导产品Φ108mm×4.5mm热轧管销量的预测,从理论上、实践上详尽阐述了“趋势—季度”变动预测模型在实际生产经营中的具体运用,同时对模型的正确性也进行了实际验证。这对当今企业生产经营工作中各种目标的定量预测,具有重要的现实意义。

Trends of Temperature Extremes in Summer and Winter during 1971–2013 in China

The diurnal temperature range(DTR) has decreased dramatically in recent decades, but it is not yet obvious whether the extreme values of DTR have also reduced. Based on the daily maximum and minimum temperature data of 653 stations in China, a set of monthly indices of warm extremes, cold extremes, and DTR extremes in summer(June, July, August) and winter(December, January, February) were studied for spatial and temporal features during the period 1971–2013. Results show that the incidence of warm extremes has been increasing in most parts of China, while the opposite trend was found in the cold extremes for summer and winter months. Both increasing and decreasing trends of monthly DTR extremes were identified in China for both seasons. For high DTR extremes, decreasing trends were identified in northern China for both seasons, but increasing trends were found only in southern China in summer, while in winter, they were found in central China. Monthly low DTR extreme indices demonstrated consistent positive trends in summer and winter, while significant increases(P < 0.05) were identified for only a few stations.

TREND OF PRECIPITATION VARIATION IN HUBEI PROVINCE SINCE THE 1960S

Through linear regression analysis to the trend of annual,seasonal and monthly precipitation of 72 meteorological stations in Hubei Province from 1961 to 1995,it is revealed that: 1) annual precipitation was increasing by 61.0mm/10a in the eastern part of Hubei (112°E as a dividing line) and decreasing by 34.9mm/10a in the western part; 2) precipitation in winter and summer (January,February,March,June and July) was increasing in almost whole province which usually with non-uniformity of precipitation distribution from the south to the north. The precipitation in spring,autumn and winter (April,September,November and December) was decreasing in most of the areas which usually with non-uniformity of precipitation distribution from the east to the west. March and December were transition periods between two spatial distribution patterns mentioned above; 3) the eastern part of Hubei has beome one of precipitation increasing centers in China. The results was consistent with the trend that more frequent flood and drought events happened in Hubei Province which are more different in spatial and temporal scales.

Interdecadal variability of the South China Sea monsoon and its relationship with latent heat flux in the Pacific Ocean

We analyzed interdecadal variability of the South China Sea monsoon and its relationship with latent heat flux in the Pacific Ocean, using NCEP wind field and OAFlux heat flux datasets. Results indicate that South China Sea monsoon intensity had an obvious interdecadal variation with a decreasing trend. Variability of the monsoon was significantly correlated with latent heat flux in the Kuroshio area and tropical Pacific Ocean. Variability of latent heat flux in the Kuroshio area had an interdecadal increasing trend, while that in the tropical Pacific Ocean had an interdecadal decreasing trend. Latent heat flux variability in these two sea areas was used to establish a latent heat flux index, which had positive correlation with variability of the South China Sea monsoon. When the latent heat flux was 18 months ahead of the South China Sea monsoon, the correlation coefficient maximized at 0.58 (N=612), with a 99.9% significance level of 0.15. Thus, it is suggested that latent heat flux variability in the two areas contributes greatly to interdecadal variability of the South China Sea monsoon.

加权季节性指数法及其应用

预测医院季度出院人数季度变动趋势;加权季节性指数法;用加权季节性指数法进行季度变动趋势的定量预测与分析,对历史数据样本数量要求不多,并且计算简便;计算结果更具客观性、真实性.

Inter-comparison of seasonal variability and nonlinear trend between AERONET aerosol optical depth and PM10 mass concentrations in Hong Kong

Here we used Empirical Mode Decomposition （EMD） method to study seasonal variability and nonlinear trend of corrected AERONET Aerosol Optical Depth （AOD/Hi） and corrected PM10 mass concentrations （PMmxf（RH）） in Hong Kong during 2005-2011. AODPrli is highly correlated with PMI0xf（RH） in semi-annual and annual time scales （with correlation coefficient 0.67 for semi-annual and 0.79 for annual components, 95% confidence interval）. On the semi-annual scale, both AOD/Hi and PM10xf（RH） can capture the two maxima in March and October, respectively, with much stronger amplitude in March proba- bly due to the long-range transport of dust storm. On the annual cycle, the AOD/Hi and PMI0xf（RH）, which are negatively correlated with the precipitation and solar radiation, vary coherently with the maxima in February. This annual peak occurs about one month earlier than the first peak of the semi-annual variability in March, but with only half amplitude. During 2005-2011, both AOD/Hi and PM10xf（RH） exhibit the pronounced decreasing trend with the mean rate of 14 gg m-3 per year for PM10xf（RH）, which reflects the significant effects of the air pollution control policy in Hong Kong during the past decade. The nonlinear trend analysis indicates that the decreasing of PM10xf（RH） is slower than that of AOD/Hi when the AOD/Hi is less than 0.44 but becomes faster when the AOD/Hi exceeds 0.44. These results illustrate that the AERONET AOD can be used quantitatively to estimate local air-quality variability on the semi-annual, annual, and long-term trend time scales.