“Forecast information is often distributed as a two-dimensional (2D) product. We present a novel application of the analog ensemble (AnEn) to generate gridded, short-term probabilistic forecasts of 10-m wind speed and 2-m temperature. The AnEn technique has been widely used in both meteorology and renewable energy applications. It is an effective method to generate skillful and reliable probabilistic predictions of meteorological variables, the wind and solar power for short-term forecasts up to 72 hours. It is based on a historical dataset including measurements paired with corresponding deterministic predictions. For each forecast lead time and location, AnEn is created using the measurements corresponding to the past deterministic predictions that are more similar to the current forecast. Until recently the AnEn technique has been used to generate predictions at specific locations, where observations are available. By using an analysis field as the ground-truth AnEn is extended here over a 2D grid, where each grid point is considered as a different location and treated independently. An in-depth analysis of AnEn skill and a comparison between AnEn and ECMWF-EPS forecasts will be presented.”

　　“预报信息经常作为二维（2D）产品被发布。我们最新应用类比集合(AnEn)方法制作格点化的10m风速和2m温度短期概率预报。AnEn技术已经广泛应用于气象和可再生能源领域，它是生成气象变量有技巧和可靠概率预报的有效方法，包括风和太阳能直到72小时的短期预报。这种方法基于历史数据库，包括观测及对应的确定预报。针对每个预报提前时间和地点，AnEn利用观测值和对应的过去中与当前最相似的确定预报得到。直到最近AnEn技术被用于制造有观测的特殊地点预报。通过利用地面真实分析场，AnEn向2D格点推广，其中的每个点都被认为是不同地点，从而被独立处理。我们对AnEn技巧进行了深度分析，并与CMWF-EPS预报进行了对比。”

　　 ——近日，NCAR科学家Stefano Allessandrini博士在ECMWF学术讲座上介绍了2011年提出的类比集合技术在2D概率预报上的应用方法他报告的题目是：Gridded Probabilistic Forecasts of Weather Parameters with an Analog Ensemble。