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AI-DOP | Artificial Intelligence-Direct Observation Prediction | ECMWF

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

2026-09-01

NWP

#NWP #ECMWF #AI #ML #Anemoi #AIFS #AI–DOP

Anemoi applications | ECMWF

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

2026-09-01

NWP

#NWP #ECMWF #AI #ML #Anemoi #AIFS #AICON

China Weather Radar | 中国天气雷达基数据

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

2026-08-28

NWP

#NWP #WRF #MPAS #DA #Radar

MPAS | MPAS UCM | Urban Canopy Model | HKUST

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

2026-08-18

MPAS

#NWP #WRF #MPAS

NWP | Microphysics | Convert moisture variables q's into rainfall

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

2026-07-02

NWP

#NWP #WRF #MPAS #Microphysics

MPAS | CRITICAL ERROR NaN detected in 'w' field" crash after MPASv8.0.0 | config_len_disp

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

2026-06-30

MPAS

#NWP #WRF #MPAS #NaN #config_len_disp

MPAS | Joint MPAS/WRF Users Workshop 2026 | MPASv8.4.1

MPAS | Joint MPAS/WRF Users Workshop 2026 | MPASv8.4.1

Joint MPAS/WRF Users Workshop 2026 MPAS-Atmosphere: Update Data Assimilation with MPAS-JEDI: 2026 Annual update The Weather Research and Forecasting Model: 2026 Annual Update WRF development has sl

2026-06-25

MPAS

#NWP #WRF #MPAS

CFD | Urban CFD | Atmospheric Boundary Layer (ABL) simulation

CFD | Urban CFD | Atmospheric Boundary Layer (ABL) simulation

Wall function Wall functions act as a boundary condition on this first cell. Instead of resolving the complicated flow within the viscous sublayer directly, the software bridges the gap by using semi-

2026-06-24

CFD

#HPC #Urban #OpenFOAM #CFD #ABL

MPAS | MPAS-JEDI | ioda | observation | .h5

MPAS | MPAS-JEDI | ioda | observation | .h5

NWP | BUFR data | GFS - Binary Universal Form for the Representation of meteorological data MPAS | MPAS-JEDI MPAS | MPAS-JEDI V3.0.2 MPAS | MPAS-JEDI | spack-stack 1.9.3 MPAS | Joint MPAS/WRF Users W

2026-06-18

MPAS-JEDI

#MPAS #DA #MPAS-JEDI #Spack #Spack-Stack #ioda #observation #h5

NWP | Derivation of Turbulent Kinetic Energy (TKE) from YSU/SH

NWP | Derivation of Turbulent Kinetic Energy (TKE) from YSU/SH

NWP | Eddy Dissipation Rate (EDR) MPAS | Eddy dissipation rate (EDR) We developed a method to estimate the eddy dissipation rate (EDR) using the resolved wind field of the MPAS simulations. (3D fiel

2026-06-11

NWP

#NWP #WRF #MPAS #TKE #EDR #aviation #PBL #YSU #SH