广州地Ⅸ的高温天气主要是受副热带高压和台风外围下沉气流的影响所致.文中采用BDA(Bogus Data Assimila-tion)方法,探讨BDA方案对广州地区台风背景条件下高温预报的改进能力.选取2005年7月中旬广州地区出现的高温天气进行研究.这是比较典型的受副热带高压和台风(海棠)共同影响造成高温的天气过程.分析有无采用BDA方案的模式初始场.结果表明:采用BDA方案同化Bogus模型可以调整台风中心位置和强度,使所得到的初始场中心位置与观测更为接近,台风强度(气压梯度力、风速)比末用Bogus的情况强,与观测值更为接近.数值模拟的结果表明,采用了BDA方案的敏感试验可以更好地预撤台风路径和台风中心强度变化,从而更好地预报高温天气,对高温区分布、日平均温度大小等的预报都有改进.文中对引起这种预报差异的原因进行了讨论,并探讨高温预报改进的可能机制.大气下沉运动的增强是高温预报改进的主要原因.敏感试验由于广州中低层大气的水汽减少,大气的下沉增强,致使天空的云量减少,对太阳短波辐射的阻挡减小,从而地面吸收热量增多,温度升高,输送给大气的感热增加,大气气温升高.采用BDA方案可以改进模式在台风"海棠"过程对广州高温的预报. 相似文献
Future climate projections of extreme events can help forewarn society of high-impact events and allow the development of better adaptation strategies. In this study a non-stationary model for Generalized Extreme Value (GEV) distributions is used to analyze the trend in extreme temperatures in the context of a changing climate and compare it with the trend in average temperatures.
The analysis is performed using the climate projections of the Canadian Regional Climate Model (CRCM), under an IPCC SRES A2 greenhouse gas emissions scenario, over North America. Annual extremes in daily minimum and maximum temperatures are analyzed. Significant positive trends for the location parameter of the GEV distribution are found, indicating an expected increase in extreme temperature values. The scale parameter of the GEV distribution, on the other hand, reveals a decrease in the variability of temperature extremes in some continental regions. Trends in the annual minimum and maximum temperatures are compared with trends in average winter and summer temperatures, respectively. In some regions, extreme temperatures exhibit a significantly larger increase than the seasonal average temperatures.
The CRCM projections are compared with those of its driving model and framed in the context of the Coupled Model Intercomparison Project, phase 3 (CMIP3) Global Climate Model projections. This enables us to establish the CRCM position within the CMIP3 climate projection uncertainty range. The CRCM is validated against the HadEX2 dataset in order to assess the CRCM representation of temperature extremes in the present climate. The validation is also framed in the context of CMIP3 validation results. The CRCM cold extremes validate better and are closer to the driving model and CMIP3 projections than the hot extremes. 相似文献