| 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.
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