【作者】 邓伟涛；

【导师】 孙照渤；

【作者基本信息】 南京信息工程大学 ， 气象学， 2008， 博士

【摘要】 随着社会和经济发展的需要,短期气候预测的研究越来越受到大家的重视和关注。最近气候动力学方法的预测结果在业务预测中越来越多的被参考和应用。由于区域气候模式具有在时间和空间上能够提供更为细致模拟结果的优势,本工作利用最新一代的全球大气环流模式CAM3与区域气候模式RegCM3进行单向嵌套(CAM-RegCM),对我国夏季(6-8月)降水距平百分率进行预测,为汛期的降水预测提供一种新的参考。本文实现了全球大气环流模式CAM3的预报结果作为背景场,单向驱动区域气候模式RegCM3,利用CAM-RegCM嵌套模式对1984～2000年我国夏季降水异常进行了后报试验以及2003～2006年我国夏季降水异常进行了独立实时预报试验,得到以下主要结论:(1)通过后报试验可知,CAM-RegCM嵌套模式对我国夏季降水距平百分率的预报具有一定的预测能力,在未订正前的预测水平与我国汛期业务预测的平均水平相当,其中预测评分P还要好于我国汛期业务预测的平均水平(距平相关系数ACC为0.03,预测评分P为72)。CAM-RegCM嵌套模式对我国东部地区的预测水平要好于西部地区,西北地区的模拟结果可信度较低。(2)从单个预报与集合预报的比较来看,集合预报的作用是平均化了单个预报效果,使得集合预报中出现异常级站点的数量减少,所以预报结果集合后使得异常级的预测水平被弱化了;同时集合预报的平均化也使得单个预报结果起了取长补短的作用,使得降水的预测结果在空间分布形势上与实际观测结果更加的相似。(3)通过距平订正(CM-AN)方法和距平百分率(CM-AP)方法订正后,使得我国夏季降水距平百分率的分布形势与观测结果更加的相似,而异常降水的预报效果略有下降。在我国东部地区,这两种订正方法预报效果的差异很小,而在西部地区,这两种订正方法在预报效果上存在一定差异。从全国范围来看,在经过CM-AP方法订正后预测技巧评分都要略好于CM-AN订正方法。(4)基于ENSO分类的订正(CM-ENSO)方法,主要在降水距平百分率(CM-AP)订正方案上,对于不同ENSO类(E1 Nino年、Normal年、La Nina年)而进行的。经过CM-ENSO订正后预报效果有一个整体的提高,所有的预报技巧评分指数总体都有明显的提高(距平相关系数ACC为0.29,预测评分P为81),不仅降水距平百分率的分布形式与观测结果更接近,同时对强度和异常级的预报都有很大的提高。可以认为CAM-RegCM嵌套模式在经过CM-ENSO订正后对我国夏季降水距平百分率的预测能力有很好的订正作用。(5)将CAM-RegCM嵌套模式的后报试验与中国科学院大气物理研究所研制的跨季度动力气候预测系统(IAP DCP-Ⅱ)和国家气候中心已经建立了第一代动力气候模式预测预测业务系统的预测效果进行比较,可以发现,CAM-RegCM嵌套模式能够达到我国其他气候动力学方法对我国夏季降水异常预测的平均水平。(6)通过独立实时预测试验,发现CAM-RegCM嵌套模式对2003、2004、2006年我国夏季降水距平百分率的形势和强度预测效果较好,但对2005年我国夏季降水距平百分率的预测效果不佳。更多还原

【Abstract】 With the requirement of social and economic development, short-term climate forecast more and more engages our attention. Recently, the dynamical climate methods in operational forecast are more and more applied and consulted. Owing to advance of spacial and temporal higher resolution modeled result with regional climate model, we use the most new generation of Atmospheric Circulation Model CAM3 one-side nested Regional Climate Model RegCM3 to forecast summer (JJA) precipitation anomaly percent over China, which can provide helpful reference to precipitation operational forecast.We realize that Atmospheric Circulation Model CAM3 results as background field one-side nest Regional Climate Model RegCM3. and we perform 1984～2000 hidecast experiment and 2003～2006 real-time forecast experiment of summer precipitation anomaly over China. The main conclusion can be drawn by following:(1) Through the hidecast experiment, we know that CAM-RegCM nested model has some skill to forecast summer precipitation anomaly percent over China. Before the correction, anomaly correlation coefficient(ACC) between the observed data and CAM-RegCM result is about 0.03 and prediction grade(P) is 72, which shows that CAM-RegCM nested model’s forecasting ability can arrive to the average of Chinese summer precipitation anomaly operational forecast, and prediction grade is higher than the average. Furthermore, the prediction result in the East of China is better than that in the West of China, and the prediction confidence in the northwest of China is very low.(2) Compared ensemble forecast with the single forecast, we can conclude that the ensemble forecast with average of every single forecast result makes the stations getting the anomaly category less, leading to the anomaly forecast ability lower in ensemble forecast. At the same time, we also can consider that the ensemble forecast makes the spacial pattern in the summer precipitation anomaly percent over China similar to the observed pattern, which improve the CAM-RegCM results’ special forecast ability.(3) After the correction method of anomaly (CM-AN) and anomaly percent (CM-AP), the spacial pattern in the summer precipitation anomaly percent over China is more similar to observed than the result without correction, but summer precipitation anomaly category forecast’s ability becomes a lot lower. In the east of China, the difference between the two correction methods is negligible, while in the west of China, there is obvious difference between them. As far as the whole country be concerned, the prediction indexes evaluating model result after CM-AP correction is better than these after CM-AN correction.(4) The correction method with ENSO category (CM-ENSO) is base on the CM-AP at difference ENSO category (El Nino year, normal year, and La Nina year). The predict result after CM-ENSO has more improve as a whole, with the obvious increase of prediction indexes (ACC is 0.29, and P is 81). Not only the spacial pattern in the summer precipitation anomaly percent over China is close to the observed pattern, but also the intensity forecast and anomaly category predict approach to observe. We can conclude that CM-ENSO can improve the CAM-RegCM nested model’s prediction ability to forecast summer precipitation anomaly percent over China.(5) Compared with the second generation of the IAP (Institute of Atmospheric Physics, Chinese Academy of sciences) dynamical climate prediction system (IAP DCP- II) and the first generation of dynamical climate model prediction operation system in National Climate Center (NCC), we can find that CAM-RegCM nested model prediction ability can arrive to their average prediction ability to forecast summer precipitation anomaly percent over China.(6) Through real-time forecast experiment, we find that CAM-RegCM nested model can well predict 2003, 2004, and 2006 summer precipitation anomaly percent pattern and intensity over China, but 2005 summer precipitation anomaly percent prediction is not perfect.更多还原