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diff --git a/README.md b/README.md
index b187bb7e7d837a367ccd0862441947ad412c77f7..afe530f7c5146923e92e9401809e95a0dc3b128f 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,59 @@
---
license: cc-by-4.0
+#User-Defined Tags
+tags:
+ - ERA5
+ - climate
+ - weather forecast
+language:
+ - en
+ - zh
---
+
+
+ ERA5
+
+
+
+## Dataset Description
+ERA5 is the fifth-generation global atmospheric reanalysis dataset produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). By combining global observations with physical models, it provides consistent and comprehensive global estimates of hourly, high-resolution (approximately 31 km) climate variables covering the atmosphere, land, and ocean from 1940 to the present.
+
+## Supported Tasks
+This standardized data repository provides annual HDF5 files for 1979-2025. Each file contains multivariable atmospheric gridded fields, along with global means and standard deviations aligned with the variable order, and can be used by multiple weather models for training, inference data loading, evaluation, and visualization.
+
+
+## Dataset Format and Structure
+
+Each annual file is in HDF5 format and follows the path pattern `data/.h5`. Each file contains:
+
+| HDF5 Path | shape | dtype | Description |
+|---|---|---|---|
+| `fields` | `[T, 243, 721, 1440]` | `float32` | Multivariable gridded fields; variable names are stored in `fields.attrs["variables"]` |
+| `global_means` | `[1, 243, 1, 1]` | `float32` | Global means aligned with the variable order |
+| `global_stds` | `[1, 243, 1, 1]` | `float32` | Global standard deviations aligned with the variable order |
+
+`fields.attrs["time_step"]` is 6, indicating 6-hour intervals. The detailed schema is provided in `metadata/schema.yaml`.
+
+`./static/` contains common static variables such as terrain and land-sea masks.
+
+
+## How to Use the Dataset
+This dataset is suitable for multiple weather models in the `OneScience-Sugon` repository, including but not limited to GraphCast, FengWu, Fuxi, and Pangu_Weather.
+
+Download the dataset:
+
+```bash
+hf download --dataset OneScience-Sugon/ERA5 --local-dir ./data
+```
+
+
+## Official OneScience Information
+
+| Platform | OneScience Main Repository | Skills Repository |
+|---|---|---|
+| Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |
+| GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |
+
+## Limitations and License
+
+This dataset was converted from the original ECMWF ERA5 data and uses the same ECMWF CC-BY-4.0 license.
diff --git a/README_zh.md b/README_zh.md
new file mode 100644
index 0000000000000000000000000000000000000000..3a3de810f7d666fc377e558d5a2f8f39a657336f
--- /dev/null
+++ b/README_zh.md
@@ -0,0 +1,59 @@
+---
+license: CC-BY-4.0
+#用户自定义标签
+tags:
+ - ERA5
+ - climate
+ - weather forecast
+language:
+ - en
+ - zh
+---
+
+
+ ERA5
+
+
+
+## 数据集描述
+ERA5是欧洲中期天气预报中心（ECMWF）推出的第五代全球大气再分析数据集，它通过将全球观测数据与物理模型相结合，提供了从1940年至今、覆盖大气、陆地和海洋的每小时、高分辨率（约31公里）气候变量的一致且完整的全球估算数据
+
+## 数据集支持的任务
+本标准化数据仓库整理了 1979-2025 年年度 HDF5 文件，每个文件包含多变量大气格点场以及与变量顺序对齐的全局均值和标准差，可被多个气象模型用于训练、推理数据读取、评测和可视化。
+
+
+## 数据集的格式和结构
+
+每个年度文件为 HDF5，路径模式为 `data/.h5`。文件内包含：
+
+| HDF5 路径 | shape | dtype | 说明 |
+|---|---|---|---|
+| `fields` | `[T, 243, 721, 1440]` | `float32` | 多变量格点场，变量名在 `fields.attrs["variables"]` |
+| `global_means` | `[1, 243, 1, 1]` | `float32` | 与变量顺序对齐的全局均值 |
+| `global_stds` | `[1, 243, 1, 1]` | `float32` | 与变量顺序对齐的全局标准差 |
+
+`fields.attrs["time_step"]` 为 6，表示 6 小时间隔。详细 schema 在 `metadata/schema.yaml`。
+
+`./static/`内包含常见的静态变量，如地势、海陆掩码等。
+
+
+## 数据集使用方式
+本数据集适用于`OneScience-Sugon`仓库内多个气象模型，包括但不局限于GraphCast、FengWu、Fuxi、Pangu_Weather等。
+
+下载数据集：
+
+```bash
+hf download --dataset OneScience-Sugon/ERA5 --local-dir ./data
+```
+
+
+## OneScience 官方信息
+
+| 平台 | OneScience 主仓库 | Skills 仓库 |
+|---|---|---|
+| Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |
+| GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |
+
+## 限制与许可证
+
+本数据集基于ECMEF原始ERA5数据转换，许可证同ECMWF CC-BY-4.0。
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diff --git a/manifest.yaml b/manifest.yaml
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+onescience_manifest_version: "0.1"
+resource_type: dataset
+resource:
+ id: OneScience/ERA5
+ name: ERA5
+ domain: earth
+ domain_tags: [earth, atmosphere, reanalysis]
+ task: weather_forecast
+ task_tags: [weather_forecast, dataset, benchmark]
+ modalities: [gridded_field]
+ input_formats: [hdf5]
+ output_formats: []
+ summary: 1979-2025 年 ERA5 年度 HDF5 数据集，包含多变量格点场和全局归一化统计量。
+
+platform_resource:
+ primary:
+ platform: modelscope
+ repo_id: OneScience/ERA5
+ repo_type: dataset
+ url: https://modelscope.cn/datasets/OneScience/ERA5
+ revision: main
+ readme_path: README.md
+ manifest_path: onescience_run_manifest.yaml
+ mirrors: []
+ access:
+ visibility: public
+ license: null
+
+website_integration:
+ enabled: true
+ click_target:
+ platform: modelscope
+ resource_url: https://modelscope.cn/datasets/OneScience/ERA5
+ llm_handoff:
+ readme_required: true
+ manifest_required: true
+ download_readme_first: true
+ resolve_related_models: true
+ default_run_goal: minimal_validation
+
+runtime:
+ enabled: true
+ onescience_domain: earth
+ min_onescience_version: null
+ supported_execution: [local, local_slurm, remote_slurm, scnet_mcp]
+
+onescience:
+ repo: https://gitee.com/onescience-ai/onescience
+ official_links:
+ gitee:
+ doc: https://gitee.com/onescience-ai/onescience-doc
+ onescience: https://gitee.com/onescience-ai/onescience
+ skills: https://gitee.com/onescience-ai/oneskills
+ github:
+ doc: https://github.com/onescience-ai/OneScience-doc
+ onescience: https://github.com/onescience-ai/OneScience
+ skills: https://github.com/onescience-ai/oneskills
+ install:
+ required_by_default: false
+ command: bash install.sh earth
+ source_paths: []
+ compatibility:
+ examples_path: null
+ status: standard_first
+
+runtime_package:
+ kind: standard_runtime_package
+ package_root: .
+ standard_layout:
+ workdir: .
+ config_dir: metadata
+ checkpoint_dir: null
+ data_dir: data
+ output_dir: null
+ apply_policy:
+ mode: direct_use
+ target: session_workdir
+ overwrite: true
+ protect_installed_onescience: true
+ entry_files:
+ - metadata/schema.yaml
+ - scripts/validate_era5_dataset.py
+ entrypoints:
+ preflight: scripts/validate_era5_dataset.py
+ inference: null
+ train: null
+ finetune: null
+ evaluate: null
+ visualize: null
+ deploy: null
+
+files:
+ model_files: []
+ dataset_files:
+ - id: era5_yearly_hdf5
+ path: data/*.h5
+ role: train_data
+ description_zh: 1979-2025 年 ERA5 年度 HDF5 文件，包含 fields、global_means 和 global_stds。
+ required: true
+ required_for: [preflight, train, inference, evaluate, visualize]
+ format: hdf5
+ source:
+ platform: modelscope
+ repo_id: OneScience/ERA5
+ repo_type: dataset
+ path: data/*.h5
+ revision: main
+ download_method: command_ref
+ command_ref: commands.download.download_full_dataset
+ mirrors: []
+ local_path: data/*.h5
+ size: "约 221G，47 个年度文件"
+ checksum: null
+ large_file: true
+ - id: era5_schema
+ path: metadata/schema.yaml
+ role: schema
+ description_zh: HDF5 数据结构、shape、dtype、attrs 和样本定义。
+ required: true
+ required_for: [preflight]
+ format: yaml
+ source:
+ platform: modelscope
+ repo_id: OneScience/ERA5
+ repo_type: dataset
+ path: metadata/schema.yaml
+ revision: main
+ download_method: command_ref
+ command_ref: commands.download.download_full_dataset
+ mirrors: []
+ local_path: metadata/schema.yaml
+ size: null
+ checksum: null
+ large_file: false
+ config_files:
+ - id: dataset_schema
+ path: metadata/schema.yaml
+ role: dataset_schema
+ description_zh: 数据 schema 文件。
+ required: true
+ required_for: [preflight]
+ format: yaml
+ source:
+ platform: modelscope
+ repo_id: OneScience/ERA5
+ repo_type: dataset
+ path: metadata/schema.yaml
+ revision: main
+ download_method: command_ref
+ command_ref: commands.download.download_full_dataset
+ local_path: metadata/schema.yaml
+ size: null
+ checksum: null
+ large_file: false
+ sample_files: []
+
+dataset:
+ format: [hdf5]
+ sample_unit: 一个由 ERA5Datapipe 从年度 HDF5 相邻时间步构造的输入/目标格点场样本。
+ schema:
+ path: metadata/schema.yaml
+ splits:
+ train:
+ years: [1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023]
+ validation:
+ years: [2024]
+ test:
+ years: [2025]
+ hdf5:
+ file_pattern: data/.h5
+ file_count: 47
+ fields_shape: [5, 243, 721, 1440]
+ dtype: float32
+ variable_count: 243
+ time_step_hours: 6
+ statistics:
+ - global_means
+ - global_stds
+
+relations:
+ required_datasets: []
+ optional_datasets: []
+ compatible_models:
+ - id: OneScience/FengWu/
+ role: train_data
+ required_for: [preflight, train, inference, evaluate, visualize]
+ resource_ref:
+ platform: modelscope
+ repo_id: OneScience/FengWu/
+ repo_type: model
+ url: https://modelscope.cn/models/OneScience/FengWu/
+ revision: main
+ readme_path: README.md
+ manifest_path: onescience_run_manifest.yaml
+ expected_local_path: data/ERA5
+ adapter: null
+
+run_matrix:
+ scenarios:
+ - name: minimal_validation
+ default: true
+ capability: preflight
+ required_datasets:
+ - id: OneScience/ERA5
+ role: train_data
+ local_path: data
+ required_model_files: []
+ command_refs:
+ - commands.preflight.validate_dataset
+ expected_outputs:
+ - ERA5 dataset validation passed
+ preconditions:
+ - data/1979.h5 和 data/2025.h5 存在且可读。
+ - name: full_structure_validation
+ default: false
+ capability: preflight
+ required_datasets:
+ - id: OneScience/ERA5
+ role: train_data
+ local_path: data
+ required_model_files: []
+ command_refs:
+ - commands.preflight.validate_dataset_all_files
+ expected_outputs:
+ - ERA5 dataset validation passed
+ preconditions:
+ - 全量数据已下载或链接到 data/。
+
+capabilities:
+ preflight: true
+ inference: false
+ train: false
+ finetune: false
+ evaluate: false
+ visualize: false
+ deploy: false
+
+commands:
+ download:
+ - name: download_full_dataset
+ description: 下载 ERA5 标准数据集。
+ target: dataset
+ repo_id: OneScience/ERA5
+ source: .
+ local_path: .
+ required: true
+ required_for: [preflight, train, inference, evaluate, visualize]
+ command: modelscope download --dataset OneScience/ERA5 --local_dir .
+ - name: download_for_fengwu
+ description: 在 FengWu 模型包根目录下载 ERA5 到模型期望路径。
+ target: dataset
+ repo_id: OneScience/ERA5
+ source: .
+ local_path: data/ERA5
+ required: true
+ required_for: [preflight, train, inference, evaluate, visualize]
+ command: modelscope download --dataset OneScience/ERA5 --local_dir data/ERA5
+ preflight:
+ - name: validate_dataset
+ description: 快速验证首尾年度 HDF5 文件结构和可读性。
+ cwd: .
+ command: python scripts/validate_era5_dataset.py --data-dir data
+ required_files:
+ - data/1979.h5
+ - data/2025.h5
+ - metadata/schema.yaml
+ required_env: [python, h5py]
+ expected_outputs:
+ - ERA5 dataset validation passed
+ success_criteria: [exit_code == 0]
+ - name: validate_dataset_all_files
+ description: 逐文件验证 1979-2025 全部 HDF5 文件结构和可读性。
+ cwd: .
+ command: python scripts/validate_era5_dataset.py --data-dir data --check-all
+ required_files:
+ - data/*.h5
+ - metadata/schema.yaml
+ required_env: [python, h5py]
+ expected_outputs:
+ - ERA5 dataset validation passed
+ success_criteria: [exit_code == 0]
+ prepare: []
+ inference: []
+ train: []
+ finetune: []
+ evaluate: []
+ visualize: []
+ deploy: []
+
+expected_outputs:
+ - path: stdout
+ type: text
+ produced_by: commands.preflight.validate_dataset
+ contains: ERA5 dataset validation passed
+
+diagnostics:
+ - id: missing_hdf5
+ match: no HDF5 files found
+ severity: error
+ message_zh: data 目录下没有年度 HDF5 文件。
+ fix_zh: 运行 modelscope download --dataset OneScience/ERA5 --local_dir .，或检查标准化链接是否存在。
+ - id: missing_year
+ match: missing expected yearly files
+ severity: error
+ message_zh: 1979-2025 年度文件不完整。
+ fix_zh: 对照 checksums 文件重新整理或下载缺失年份。
+ - id: schema_mismatch
+ match: expected [T, 243, 721, 1440]
+ severity: error
+ message_zh: HDF5 fields 数据结构不符合当前 FengWu 适配 schema。
+ fix_zh: 使用 OneScience/ERA5 标准数据，或为新 schema 更新模型配置、README 和 Manifest。
+
+domain_extension:
+ earth:
+ dataset_family: ERA5
+ year_range: [1979, 2025]
+ file_count: 47
+ grid: 0.25_degree
+ time_step_hours: 6
+ variable_count: 243
+ fengwu_selected_channels: 189
diff --git a/metadata/schema.yaml b/metadata/schema.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f7dc6f7a19f5128fe77b876dca2da56cf6f08afb
--- /dev/null
+++ b/metadata/schema.yaml
@@ -0,0 +1,32 @@
+schema_version: "0.1"
+dataset: ERA5
+format: hdf5
+file_pattern: data/.h5
+year_range:
+ start: 1979
+ end: 2025
+file_count: 47
+datasets:
+ fields:
+ shape: [T, 243, 721, 1440]
+ dtype: float32
+ dimension_order: [time, variable, latitude, longitude]
+ attrs:
+ variables: "243 个变量名，顺序与 fields 第二维、global_means、global_stds 对齐"
+ time_step: 6
+ global_means:
+ shape: [1, 243, 1, 1]
+ dtype: float32
+ description: "按变量顺序排列的全局均值"
+ global_stds:
+ shape: [1, 243, 1, 1]
+ dtype: float32
+ description: "按变量顺序排列的全局标准差"
+spatial_grid:
+ latitude_points: 721
+ longitude_points: 1440
+ nominal_resolution: [0.25, 0.25]
+sample_unit: "一个年度 HDF5 文件包含该年的 6 小时间隔多变量格点场；一个训练样本由 datapipe 从相邻时间步构造输入和目标。"
+notes:
+ - "变量列表以每个 HDF5 文件中 fields.attrs['variables'] 为准。"
+ - "FengWu 标准化模型包使用其中 189 个通道。"
diff --git a/onescience_relations.yaml b/onescience_relations.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..14019b543b848ffc3eac8d6177849593adf33229
--- /dev/null
+++ b/onescience_relations.yaml
@@ -0,0 +1,16 @@
+required_datasets: []
+optional_datasets: []
+compatible_models:
+ - id: OneScience/FengWu/
+ role: train_data
+ required_for: [preflight, train, inference, evaluate, visualize]
+ resource_ref:
+ platform: modelscope
+ repo_id: OneScience/FengWu/
+ repo_type: model
+ url: https://modelscope.cn/models/OneScience/FengWu/
+ revision: main
+ readme_path: README.md
+ manifest_path: onescience_run_manifest.yaml
+ expected_local_path: data/ERA5
+ adapter: null
diff --git a/onescience_run_manifest.yaml b/onescience_run_manifest.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..b776b8fbff48063a9e86fd6fe3b09f191e1d74a6
--- /dev/null
+++ b/onescience_run_manifest.yaml
@@ -0,0 +1,321 @@
+onescience_manifest_version: "0.1"
+resource_type: dataset
+resource:
+ id: OneScience/ERA5
+ name: ERA5
+ domain: earth
+ domain_tags: [earth, atmosphere, reanalysis]
+ task: weather_forecast
+ task_tags: [weather_forecast, dataset, benchmark]
+ modalities: [gridded_field]
+ input_formats: [hdf5]
+ output_formats: []
+ summary: 1979-2025 年 ERA5 年度 HDF5 数据集，包含多变量格点场和全局归一化统计量。
+
+platform_resource:
+ primary:
+ platform: modelscope
+ repo_id: OneScience/ERA5
+ repo_type: dataset
+ url: https://modelscope.cn/datasets/OneScience/ERA5
+ revision: main
+ readme_path: README.md
+ manifest_path: onescience_run_manifest.yaml
+ mirrors: []
+ access:
+ visibility: public
+ license: null
+
+website_integration:
+ enabled: true
+ click_target:
+ platform: modelscope
+ resource_url: https://modelscope.cn/datasets/OneScience/ERA5
+ llm_handoff:
+ readme_required: true
+ manifest_required: true
+ download_readme_first: true
+ resolve_related_models: true
+ default_run_goal: minimal_validation
+
+runtime:
+ enabled: true
+ onescience_domain: earth
+ min_onescience_version: null
+ supported_execution: [local, local_slurm, remote_slurm, scnet_mcp]
+
+onescience:
+ repo: https://gitee.com/onescience-ai/onescience
+ official_links:
+ gitee:
+ doc: https://gitee.com/onescience-ai/onescience-doc
+ onescience: https://gitee.com/onescience-ai/onescience
+ skills: https://gitee.com/onescience-ai/oneskills
+ github:
+ doc: https://github.com/onescience-ai/OneScience-doc
+ onescience: https://github.com/onescience-ai/OneScience
+ skills: https://github.com/onescience-ai/oneskills
+ install:
+ required_by_default: false
+ command: bash install.sh earth
+ source_paths: []
+ compatibility:
+ examples_path: null
+ status: standard_first
+
+runtime_package:
+ kind: standard_runtime_package
+ package_root: .
+ standard_layout:
+ workdir: .
+ config_dir: metadata
+ checkpoint_dir: null
+ data_dir: data
+ output_dir: null
+ apply_policy:
+ mode: direct_use
+ target: session_workdir
+ overwrite: true
+ protect_installed_onescience: true
+ entry_files:
+ - metadata/schema.yaml
+ - scripts/validate_era5_dataset.py
+ entrypoints:
+ preflight: scripts/validate_era5_dataset.py
+ inference: null
+ train: null
+ finetune: null
+ evaluate: null
+ visualize: null
+ deploy: null
+
+files:
+ model_files: []
+ dataset_files:
+ - id: era5_yearly_hdf5
+ path: data/*.h5
+ role: train_data
+ description_zh: 1979-2025 年 ERA5 年度 HDF5 文件，包含 fields、global_means 和 global_stds。
+ required: true
+ required_for: [preflight, train, inference, evaluate, visualize]
+ format: hdf5
+ source:
+ platform: modelscope
+ repo_id: OneScience/ERA5
+ repo_type: dataset
+ path: data/*.h5
+ revision: main
+ download_method: command_ref
+ command_ref: commands.download.download_full_dataset
+ mirrors: []
+ local_path: data/*.h5
+ size: "约 221G，47 个年度文件"
+ checksum: null
+ large_file: true
+ - id: era5_schema
+ path: metadata/schema.yaml
+ role: schema
+ description_zh: HDF5 数据结构、shape、dtype、attrs 和样本定义。
+ required: true
+ required_for: [preflight]
+ format: yaml
+ source:
+ platform: modelscope
+ repo_id: OneScience/ERA5
+ repo_type: dataset
+ path: metadata/schema.yaml
+ revision: main
+ download_method: command_ref
+ command_ref: commands.download.download_full_dataset
+ mirrors: []
+ local_path: metadata/schema.yaml
+ size: null
+ checksum: null
+ large_file: false
+ config_files:
+ - id: dataset_schema
+ path: metadata/schema.yaml
+ role: dataset_schema
+ description_zh: 数据 schema 文件。
+ required: true
+ required_for: [preflight]
+ format: yaml
+ source:
+ platform: modelscope
+ repo_id: OneScience/ERA5
+ repo_type: dataset
+ path: metadata/schema.yaml
+ revision: main
+ download_method: command_ref
+ command_ref: commands.download.download_full_dataset
+ local_path: metadata/schema.yaml
+ size: null
+ checksum: null
+ large_file: false
+ sample_files: []
+
+dataset:
+ format: [hdf5]
+ sample_unit: 一个由 ERA5Datapipe 从年度 HDF5 相邻时间步构造的输入/目标格点场样本。
+ schema:
+ path: metadata/schema.yaml
+ splits:
+ train:
+ years: [1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023]
+ validation:
+ years: [2024]
+ test:
+ years: [2025]
+ hdf5:
+ file_pattern: data/.h5
+ file_count: 47
+ fields_shape: [5, 243, 721, 1440]
+ dtype: float32
+ variable_count: 243
+ time_step_hours: 6
+ statistics:
+ - global_means
+ - global_stds
+
+relations:
+ required_datasets: []
+ optional_datasets: []
+ compatible_models:
+ - id: OneScience/FengWu/
+ role: train_data
+ required_for: [preflight, train, inference, evaluate, visualize]
+ resource_ref:
+ platform: modelscope
+ repo_id: OneScience/FengWu/
+ repo_type: model
+ url: https://modelscope.cn/models/OneScience/FengWu/
+ revision: main
+ readme_path: README.md
+ manifest_path: onescience_run_manifest.yaml
+ expected_local_path: data/ERA5
+ adapter: null
+
+run_matrix:
+ scenarios:
+ - name: minimal_validation
+ default: true
+ capability: preflight
+ required_datasets:
+ - id: OneScience/ERA5
+ role: train_data
+ local_path: data
+ required_model_files: []
+ command_refs:
+ - commands.preflight.validate_dataset
+ expected_outputs:
+ - ERA5 dataset validation passed
+ preconditions:
+ - data/1979.h5 和 data/2025.h5 存在且可读。
+ - name: full_structure_validation
+ default: false
+ capability: preflight
+ required_datasets:
+ - id: OneScience/ERA5
+ role: train_data
+ local_path: data
+ required_model_files: []
+ command_refs:
+ - commands.preflight.validate_dataset_all_files
+ expected_outputs:
+ - ERA5 dataset validation passed
+ preconditions:
+ - 全量数据已下载或链接到 data/。
+
+capabilities:
+ preflight: true
+ inference: false
+ train: false
+ finetune: false
+ evaluate: false
+ visualize: false
+ deploy: false
+
+commands:
+ download:
+ - name: download_full_dataset
+ description: 下载 ERA5 标准数据集。
+ target: dataset
+ repo_id: OneScience/ERA5
+ source: .
+ local_path: .
+ required: true
+ required_for: [preflight, train, inference, evaluate, visualize]
+ command: modelscope download --dataset OneScience/ERA5 --local_dir .
+ - name: download_for_fengwu
+ description: 在 FengWu 模型包根目录下载 ERA5 到模型期望路径。
+ target: dataset
+ repo_id: OneScience/ERA5
+ source: .
+ local_path: data/ERA5
+ required: true
+ required_for: [preflight, train, inference, evaluate, visualize]
+ command: modelscope download --dataset OneScience/ERA5 --local_dir data/ERA5
+ preflight:
+ - name: validate_dataset
+ description: 快速验证首尾年度 HDF5 文件结构和可读性。
+ cwd: .
+ command: python scripts/validate_era5_dataset.py --data-dir data
+ required_files:
+ - data/1979.h5
+ - data/2025.h5
+ - metadata/schema.yaml
+ required_env: [python, h5py]
+ expected_outputs:
+ - ERA5 dataset validation passed
+ success_criteria: [exit_code == 0]
+ - name: validate_dataset_all_files
+ description: 逐文件验证 1979-2025 全部 HDF5 文件结构和可读性。
+ cwd: .
+ command: python scripts/validate_era5_dataset.py --data-dir data --check-all
+ required_files:
+ - data/*.h5
+ - metadata/schema.yaml
+ required_env: [python, h5py]
+ expected_outputs:
+ - ERA5 dataset validation passed
+ success_criteria: [exit_code == 0]
+ prepare: []
+ inference: []
+ train: []
+ finetune: []
+ evaluate: []
+ visualize: []
+ deploy: []
+
+expected_outputs:
+ - path: stdout
+ type: text
+ produced_by: commands.preflight.validate_dataset
+ contains: ERA5 dataset validation passed
+
+diagnostics:
+ - id: missing_hdf5
+ match: no HDF5 files found
+ severity: error
+ message_zh: data 目录下没有年度 HDF5 文件。
+ fix_zh: 运行 modelscope download --dataset OneScience/ERA5 --local_dir .，或检查标准化链接是否存在。
+ - id: missing_year
+ match: missing expected yearly files
+ severity: error
+ message_zh: 1979-2025 年度文件不完整。
+ fix_zh: 对照 checksums 文件重新整理或下载缺失年份。
+ - id: schema_mismatch
+ match: expected [T, 243, 721, 1440]
+ severity: error
+ message_zh: HDF5 fields 数据结构不符合当前 FengWu 适配 schema。
+ fix_zh: 使用 OneScience/ERA5 标准数据，或为新 schema 更新模型配置、README 和 Manifest。
+
+domain_extension:
+ earth:
+ dataset_family: ERA5
+ year_range: [1979, 2025]
+ file_count: 47
+ grid: 0.25_degree
+ time_step_hours: 6
+ variable_count: 243
+ fengwu_selected_channels: 189
diff --git a/scripts/validate_era5_dataset.py b/scripts/validate_era5_dataset.py
new file mode 100644
index 0000000000000000000000000000000000000000..8682dcc8631b7cde69ae5d19a7b26ecdb7534774
--- /dev/null
+++ b/scripts/validate_era5_dataset.py
@@ -0,0 +1,81 @@
+#!/usr/bin/env python3
+"""Validate the standardized ERA5 HDF5 dataset package."""
+
+from __future__ import annotations
+
+import argparse
+from pathlib import Path
+
+import h5py
+
+
+def read_variables(fields) -> list[str]:
+ return [
+ v.decode() if isinstance(v, bytes) else str(v)
+ for v in fields.attrs.get("variables", [])
+ ]
+
+
+def check_file(path: Path, expected_variables: list[str] | None) -> list[str]:
+ with h5py.File(path, "r") as f:
+ for name in ("fields", "global_means", "global_stds"):
+ if name not in f:
+ raise RuntimeError(f"{path}: missing dataset {name}")
+ fields = f["fields"]
+ if fields.dtype.name != "float32":
+ raise RuntimeError(f"{path}: fields dtype is {fields.dtype}, expected float32")
+ if len(fields.shape) != 4:
+ raise RuntimeError(f"{path}: fields shape is {fields.shape}, expected [T, C, H, W]")
+ if fields.shape[1:] != (243, 721, 1440):
+ raise RuntimeError(f"{path}: fields shape {fields.shape}, expected [T, 243, 721, 1440]")
+ if f["global_means"].shape != (1, 243, 1, 1):
+ raise RuntimeError(f"{path}: global_means shape is {f['global_means'].shape}")
+ if f["global_stds"].shape != (1, 243, 1, 1):
+ raise RuntimeError(f"{path}: global_stds shape is {f['global_stds'].shape}")
+ variables = read_variables(fields)
+ if len(variables) != 243:
+ raise RuntimeError(f"{path}: variables length is {len(variables)}, expected 243")
+ if expected_variables is not None and variables != expected_variables:
+ raise RuntimeError(f"{path}: variables attr differs from first checked file")
+ if int(fields.attrs.get("time_step", -1)) != 6:
+ raise RuntimeError(f"{path}: time_step is {fields.attrs.get('time_step')}, expected 6")
+ _ = fields[0, 0, 0, 0]
+ _ = f["global_means"][0, 0, 0, 0]
+ _ = f["global_stds"][0, 0, 0, 0]
+ return variables
+
+
+def main() -> int:
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--data-dir", default="data", help="directory containing yearly *.h5 files")
+ parser.add_argument("--expected-start-year", type=int, default=1979)
+ parser.add_argument("--expected-end-year", type=int, default=2025)
+ parser.add_argument("--check-all", action="store_true", help="inspect every yearly file")
+ args = parser.parse_args()
+
+ data_dir = Path(args.data_dir).resolve()
+ files = sorted(data_dir.glob("*.h5"))
+ if not files:
+ raise FileNotFoundError(f"no HDF5 files found under {data_dir}")
+
+ expected_names = [f"{year}.h5" for year in range(args.expected_start_year, args.expected_end_year + 1)]
+ actual_names = [p.name for p in files]
+ missing = [name for name in expected_names if name not in actual_names]
+ if missing:
+ raise FileNotFoundError(f"missing expected yearly files: {missing[:10]}")
+
+ to_check = files if args.check_all else [data_dir / expected_names[0], data_dir / expected_names[-1]]
+ variables = None
+ for path in to_check:
+ variables = check_file(path, variables)
+
+ print("ERA5 dataset validation passed")
+ print(f"data_dir: {data_dir}")
+ print(f"files: {len(files)}")
+ print(f"checked_files: {len(to_check)}")
+ print(f"variables: {len(variables or [])}")
+ return 0
+
+
+if __name__ == "__main__":
+ raise SystemExit(main())
diff --git a/static/.gitkeep b/static/.gitkeep
new file mode 100644
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diff --git a/static/geopotential.nc b/static/geopotential.nc
new file mode 100644
index 0000000000000000000000000000000000000000..05b70b4ec3a474b23d1dc338a03e2058246ccb1a
--- /dev/null
+++ b/static/geopotential.nc
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+version https://git-lfs.github.com/spec/v1
+oid sha256:ae99ac619fdb60d88d7b980065c56d5448497ac147b5863c16a92a6a88a27ad1
+size 4180485
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index 0000000000000000000000000000000000000000..34d2f1a0eb3f4dafe5dc0b6948a8040bff19f5cd
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+version https://git-lfs.github.com/spec/v1
+oid sha256:6542ae38406341a69ff7bccf86ae82503829ed0339b43fb0f67d07aa03ce1985
+size 8306048
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new file mode 100644
index 0000000000000000000000000000000000000000..8fc69db06dd00b9528975e16bf82129a67f03b31
--- /dev/null
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+version https://git-lfs.github.com/spec/v1
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+size 4180489
diff --git a/static/soil_type.npy b/static/soil_type.npy
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+version https://git-lfs.github.com/spec/v1
+oid sha256:3aa3dc0aee7a3a53ff305f91aad0f8e43abdcf552da0568954b6889b5f344bc9
+size 8306048
diff --git a/static/topography.npy b/static/topography.npy
new file mode 100644
index 0000000000000000000000000000000000000000..7b10c7f12c5e87fcee0f4e98c5941e6279786f80
--- /dev/null
+++ b/static/topography.npy
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+version https://git-lfs.github.com/spec/v1
+oid sha256:9732d89e52d654c748072f28f13cea8911f83f74509cc0530be22ccf83caea0f
+size 4153088