The ensemble forecast is not good at temperature forecast, but it is good at speed forecast.
集合预报对冬季低温和夏季高温等极端温度的预报能力较差，但对风速的预报体现一定优势。
The verification of the ensemble forecast results of a tropical Pacific air-sea coupled ensemble prediction system is discussed.
讨论了一个热带太平洋海气耦合集合预报系统集合预报的检验问题。
Using the ECMWF ensemble forecasting system as an example, a deterministic forecast case and a probability forecast case are discussed, respectively.
以欧洲中期天气预报中心的集合预报系统的控制预报和集合预报为例，对确定性预报和概率预报的情况分别进行了说明。
To solve the uncertainty of initial fields in the traditional numerical forecast, medium-range ensemble forecast experiments using the model T106L19 were made.
为解决传统的数值预报初值存在的不确定性，利用增长模繁殖法在T106L19全球谱模式上进行了中期集合预报试验。
The results show the results of ensemble forecast are better than that of each member's, the simple average of ensemble members' prediction results can improve forecast accuracy;
结果显示集合预报在总体预报效果上比各个集合成员的预报效果好，简单的集合平均就可以提高模式形势场和降水要素场的预报准确率。
The latest precipitation forecast from the GFS ensemble model predicts the possibility of rains of around 1/2 inch for Shandong Province early next week, but these rains would help only a little.
最新的全球天气预报系统（GFS）预测下周初山东将有1/2（12毫米）英寸降雨的可能，但这对缓解旱情帮助甚微。
The Ensemble Prediction System (EPS) in principle can be called the Probabilistic Prediction System (PPS) of which its ultimate goal is to provide the full probabilistic forecast for all variables.
集合预报系统从原理上讲也可称之为概率预报系统，其最终目的是要提供所有大气变量的完全概率预报。
Viewed by the computed spread, ensemble averaged forecast is more reliable than the control forecast.
从计算的离散度来看，集合平均预报的可信度要比控制预报的高。
As applied in weather prediction like probability forecast, ensemble prediction has been used for "targeted observation" and data assimilation.
集合预报的应用，在天气预报上主要是概率预报，另外在“目标观测”、资料同化等方面也有广泛应用。
The optimal number of ensemble samples can be obtained theoretically, and it is consistent with the result of model forecast.
理论研究表明，可以求出最佳集合样本数，而且由模式预报试验得到的最佳集合样本数与理论结果是一致的。
The "ensemble dynamic factors" approach to predict precipitation is able to generate the product of precipitation forecast, and thus can provide assistance to forecasters.
集合动力因子预报方法计算量小，容易移植，可以提供降水预报产品，为预报员做暴雨预报提供支持。
The results show that TC initial position perturbation make its track different, but ensemble mean is close to control forecast.
试验结果表明：热带气旋定位误差影响路径预报，但扰动初始位置的集合平均预报与控制试验的预报水平相接近。
Also, the method is based on abundant theoretic evidence, and it is very simple to calculate and easy to program so, it initiates a new way to the forecast ensemble.
该方法理论依据充分，计算简单，易于编程，为预报集成开辟了一条新的途径。
By selecting sub-ensemble with smaller error, the root mean square error of forecast is reduced by over 10%.
采用最优集合子集预报方式时的臭氧预报均方根误差比原确定性预报低了10%以上。
By selecting sub-ensemble with smaller error, the root mean square error of forecast is reduced by over 10%.
采用最优集合子集预报方式时的臭氧预报均方根误差比原确定性预报低了10%以上。
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