Spatial Verification of High-Resolution Ensemble Forecasts using Wavelet Transformation

VeriWave的目的是开发一种方法，利用具有不可忽略不计的不确定性的观测对高分辨率集合模型输出进行空间验证。所提出的技术是基于小波变换，并有可能产生复杂的诊断信息量身定制的物理过程中的利益和突出的功能为基础的方法相媲美，同时保留了对噪声的鲁棒性和计算效率的尺度分离方法。特别强调的是建议的验证分数分量的强度，位置，方向和纹理的正交性，这使得人们可以减少高维数据只有几个关键特性。我们提出以下研究目标：（1）定义一个适合于现有数据和感兴趣的物理过程的小波变换框架，（2）推导出一种基于小波的空间验证方法，该方法产生关于强度、位置和纹理的诊断信息，（3）确保该方法对于变化的参数和观测不确定性是稳健的，（4）将方法学扩展到集合预报;（5）通过提供软件和用户手册来传播所提出的方法。所提出的方法将在一个层次的数据上进行研究，从简单的几何测试案例和综合扰动预报到高分辨率案例研究和大集合数据集。

The aim of VeriWave is to develop a method for spatial verification of high-resolution ensemble model output with observations with non-negligible uncertainties. The proposed technique is based on wavelet transforms and bears the potential to yield sophisticated diagnostic information tailored to the physical process of interest and comparable to prominent feature based methods, while retaining the robustness to noise and the computational efficiency of scale separation methods. Particular emphasize lies on the orthogonality of the proposed verification score components intensity, location, orientation and texture, which allows one to reduce the high-dimensional data to only a few key characteristics. We propose the following research objectives: (1) Define an framework of wavelet transformations tailored to the data at hand and the physical process of interest, (2) derive a wavelet based methodology for spatial verification that yields diagnostic information on intensity, location and texture, (3) ensure that the methodology is robust with respect to varying parameters and observational uncertainties, (4) extend methodology to ensemble forecast, and (5) disseminate the proposed method by providing the software together with a user handbook.The proposed method will be studied on a hierarchy of data ranging from simple geometric test cases and synthetically disturbed forecaststo high-resolution case studies and large sets of ensemble data.