CFD | Rhie-Chow interpolation
Rhie-Chow Interpolation Instead of storing and updating vector velocity \(\mathbf{U}\) directly at the cell faces (a layout known as a staggered grid), modern unstructured CFD solvers like OpenFOAM pr
TimesFM | time-series foundation model | Google
TimesFM https://github.com/google-research/timesfm https://research.google/blog/a-decoder-only-foundation-model-for-time-series-forecasting/ TimesFM (Time Series Foundation Model) is a pretrained
AI-DOP | Artificial Intelligence-Direct Observation Prediction | ECMWF
AIFS-DOP We introduce the Artificial Intelligence Forecasting System for Direct Observation Prediction (AIFS-DOP). AIFS-DOP is trained on a 40-year harmonized dataset of gridded observations, without
Anemoi applications | ECMWF
AICON 德国国家气象局用自己的数据体系，训练AICON并真正部署进业务 | 那么预报员怎么说？ https://arxiv.org/pdf/2608.24651 德国国家气象局用自己的数据体系，训练AICON并真正部署进业务 (预报员, 国家气象业务) Anemoi 框架 接使用 ICON 的 terrain-following 模式层 宁愿牺牲部分长时效 RMSE，也尽量保住高分辨率
China Weather Radar | 中国天气雷达基数据
pycwr PyCWR简介 PyCWR 解决的是中国天气雷达基数据“格式多、年代跨度大、业务链路不一致”的现实问题。 它把 reader、体扫对象、绘图、QC、HID、风场反演、插值和标准格式导出连成一条 连贯的 Python 工作流，让你不必为每一种输入格式单独重写处理逻辑。 https://pycwr.readthedocs.io/en/latest/PyCWR_intro.html htt
MPAS | MPAS UCM | Urban Canopy Model | HKUST
MPAS | Convert LCZs into static.nc WRF | MPAS | UCM Urban canopy parameters (UCPs) WRF | MPAS | UCM and LCZs Map of Local Climate Zones (LCZs) MPAS workshop 2025 Developing and Evaluating the MPAS
NWP | Microphysics | Convert moisture variables q's into rainfall
Atmospheric models convert moisture variables (\(q_v, q_c, q_r, q_i, q_s, q_g\)) into rainfall and precipitation through microphysics parameterizations that simulate microphysical phase changes and dr
MPAS | CRITICAL ERROR NaN detected in 'w' field" crash after MPASv8.0.0 | config_len_disp
config_len_disp Regarding the 'config_len_disp' option, with MPAS v8.0 it's no longer necessary to specify this length scale if you're using new meshes from the mesh download page, since these new mes
