In this paper we try to extract stable components in the extended-range forecast for the coming 10–30 days by using empirical orthogonal function(EOF) analysis, similarity coefficient, and some other methods based on the National Center for Environmental Prediction(NCEP)/National Center for Atmospheric Research(NCAR) reanalysis daily data. The comparisons of the coefficient of variance of climatological background field and truth data in winter between 2010 and 2011 are made. The method of extracting stable components and climatological background field can be helpful to increase forecasting skill. The forecasting skill improvement of air temperature is better than geopotential height at 500 hPa. Moreover, this method improves the predictability better in the Pacific Ocean. In China, the forecast in winter in Northeast China is more uncertain than in the other parts.
In this paper, the northward jump time of the western Pacific subtropical high(WPSH) is defined and analyzed on the interdecadal timescale. The results show that under global warming, significant interdecadal changes have occurred in the time of the WPSH northward jumps. From 1951 to 2012, the time of the first northward jump of WPSH has changed from "continuously early" to "continuously late", with the transition occurring in 1980. The time of the second northward jump of WPSH shows a similar change, with the transition occurring in 1978. In this study, we offer a new perspective by using the time of the northward jump of WPSH to explain the eastern China summer rainfall pattern change from "north-abundant-southbelow-average" to "south-abundant-north-below-average" at the end of the 1970 s. The interdecadal change in the time of the northward jump of WPSH corresponds not only with the summer rainfall pattern, but also with the Pacific decadal oscillation(PDO). The WPSH northward jump time corresponding to the cold(warm) phase of the PDO is early(late). Although the PDO and the El Nino–Southern Oscillation(ENSO)both greatly influence the time of the two northward jumps of WPSH, the PDO's effect is noticed before the ENSO's by approximately 1–2 months. After excluding the ENSO influence, we derive composite vertical atmospheric circulation for different phases of the PDO. The results show that during the cold(warm)phase of the PDO, the atmospheric circulations at 200, 500, and 850 h Pa all contribute to an earlier(later)northward jump of the WPSH.
Based on nonlinear prediction and information theory,vertical heterogeneity of predictability and information loss rate in geopotential height field are obtained over the Northern Hemisphere.On a seasonal-to-interannual time scale,the predictability is low in the lower troposphere and high in the mid-upper troposphere.However,within mid-upper troposphere over the subtropics ocean area,there is a relatively poor predictability.These conclusions also fit the seasonal time scale.Moving to the interannual time scale,the predictability becomes high in the lower troposphere and low in the mid-upper troposphere,contrary to the former case.On the whole the interannual trend is more predictable than the seasonal trend.The average information loss rate is low over the mid-east Pacific,west of North America,Atlantic and Eurasia,and the atmosphere over other places has a relatively high information loss rate on all-time scales.Two channels are found steadily over the Pacific Ocean and Atlantic Ocean in subtropics.There are also unstable channels.The fourseason influence on predictability and information communication are studied.The predictability is low,no matter which season data are removed and each season plays an important role in the existence of the channels,except for the winter.The predictability and teleconnections are paramount issues in atmospheric science,and the teleconnections may be established by communication channels.So,this work is interesting since it reveals the vertical structure of predictability distribution,channel locations,and the contributions of different time scales to them and their variations under different seasons.
The initial value error and the imperfect numerical model are usually considered as error sources of numerical weather prediction (NWP). By using past multi-time observations and model output, this study proposes a method to estimate imperfect numerical model error. This method can be inversely estimated through expressing the model error as a Lagrange interpolation polynomial, while the coefficients of polynomial are determined by past model performance. However, for practical application in the full NWP model, it is necessary to determine the following criteria: (1) the length of past data sufficient for estimation of the model errors, (2) a proper method of estimating the term "model integration with the exact solution" when solving the inverse problem, and (3) the extent to which this scheme is sensitive to the observational errors. In this study, such issues are resolved using a simple linear model, and an advection-diffusion model is applied to discuss the sensitivity of the method to an artificial error source. The results indicate that the forecast errors can be largely reduced using the proposed method if the proper length of past data is chosen. To address the three problems, it is determined that (1) a few data limited by the order of the corrector can be used, (2) trapezoidal approximation can be employed to estimate the "term" in this study; however, a more accurate method should be explored for an operational NWP model, and (3) the correction is sensitive to observational error.
