ECMWF IFS High-Resolution Operational Forecasts

ECMWF has implemented a significant resolution upgrade and methodology for high-resolution forecasts (HRES) and ensemble forecasts (ENS) beginning January of 2016. HRES is now performed via a transform grid with a nominal grid point spacing of 9 kilometers (0.08 degrees), and is carried out with IFS (Integrated Forecast System). Improvements in computational efficiency and effective resolution have been brought about by implementing a triangular cubic octahedral reduced Gaussian grid in which the shortest spatial wavelength is represented by at least four grid points anywhere on the globe, as opposed to the former linear arrangement whereby the shortest wavelength was represented by two grid points, while at the same time retaining the same number of spherical harmonics and triangular truncation. (The term "cubic" is due to the ability of the grid to represent cubic products in the dynamical equations.) In addition, the reduction of grid points along latitude circles as one approaches the poles is achieved using a triangular to octahedral mapping which corresponds to a poleward reduction of four points per latitude circle and an optimization of the total number of grid points and their local mesh resolution. ECMWF has documented superior filtering properties at higher resolution, an improved representation of orography, improved global mass conservation properties, substantial efficiency gains, and more scalable locally compact computations of derivatives and other properties that depend on nearest-neighbor information only. More details may be found in the publications cited below. NCAR's DECS is performing and supplying a grid transformed version of HRES IFS, in which variables originally represented as spectral coefficients or archived on a reduced Gaussian grid are transformed to a regular 5120 longitude by 2560 latitude N1280 Gaussian grid. In addition, DECS is also computing horizontal winds (u-component, v-component) from spectral vorticity and divergence where these are available.

欧洲中期天气预报中心（European Centre for Medium-Range Weather Forecasts, ECMWF）已于2016年1月起，针对高分辨率预报（High-resolution Forecasts, HRES）与集合预报（Ensemble Forecasts, ENS）实施了重大分辨率升级与方法革新。目前，高分辨率预报（HRES）已采用标称网格点间距为9公里（0.08°）的变换网格，并通过综合预报系统（Integrated Forecast System, IFS）运行。此次升级通过采用三角立方八面体缩减高斯网格（triangular cubic octahedral reduced Gaussian grid）实现了计算效率与有效分辨率的提升：该网格可在全球任意区域以至少4个网格点表征最短空间波长，而此前的线性布局仅能以2个网格点表征最短波长；同时，升级保留了相同数量的球谐函数（spherical harmonics）与三角截断（triangular truncation）设置。（术语“立方”源于该网格可在动力学方程中表征立方项的特性。）此外，随着向极地靠近，纬度圈上的网格点数量可通过三角至八面体映射实现缩减，该映射方式可使每个纬度圈的网格点向极地方向每圈减少4个，并优化了总网格点数量与局地网格分辨率。ECMWF已证实，高分辨率配置下具备更优异的滤波特性、更精准的地形表征能力、更完善的全球质量守恒属性，同时实现了显著的计算效率增益，以及仅依赖最近邻信息的导数与其他属性的局地紧凑可扩展计算。更多细节可参阅下文引用的相关文献。美国国家大气研究中心（National Center for Atmospheric Research, NCAR）的DECS系统正在处理并提供HRES IFS的网格变换版本：该版本将原本以谱系数形式表征或存储于缩减高斯网格的变量，转换为规则的5120经度×2560纬度的N1280高斯网格。此外，当谱涡度与散度数据可用时，DECS系统还将基于这些数据计算水平风场（u分量、v分量）。

搜集汇总

背景与挑战

背景概述

该数据集是ECMWF提供的高分辨率全球气象预报数据，时间跨度为2016-2026年，包含多种气象要素，空间分辨率达0.07度，数据量超过273TB。数据集采用先进的三角立方八面体缩减高斯网格技术，显著提高了计算效率和分辨率。