From 4118b46d82f054f0c4ac920168b91076e0272ed9 Mon Sep 17 00:00:00 2001
From: beinggod <beinggod@foxmail.com>
Date: Sat, 1 Mar 2025 08:37:32 +0000
Subject: [PATCH 1/9] Add FengWu predictor

---
 examples/fengwu/conf/fengwu.yaml |  46 ++++++++
 examples/fengwu/predict.py       | 173 +++++++++++++++++++++++++++++++
 2 files changed, 219 insertions(+)
 create mode 100644 examples/fengwu/conf/fengwu.yaml
 create mode 100644 examples/fengwu/predict.py

diff --git a/examples/fengwu/conf/fengwu.yaml b/examples/fengwu/conf/fengwu.yaml
new file mode 100644
index 0000000000..d6fb79cce2
--- /dev/null
+++ b/examples/fengwu/conf/fengwu.yaml
@@ -0,0 +1,46 @@
+defaults:
+  - ppsci_default
+  - INFER: infer_default
+  - hydra/job/config/override_dirname/exclude_keys: exclude_keys_default
+  - _self_
+
+hydra:
+  run:
+    # dynamic output directory according to running time and override name
+    dir: ./outputs_fengwu
+  job:
+    name: ${mode} # name of logfile
+    chdir: false # keep current working directory unchanged
+  callbacks:
+    init_callback:
+      _target_: ppsci.utils.callbacks.InitCallback
+  sweep:
+    # output directory for multirun
+    dir: ${hydra.run.dir}
+    subdir: ./
+
+# general settings
+mode: infer # running mode: infer
+seed: 2023
+output_dir: ${hydra:run.dir}
+log_freq: 20
+
+# inference settings
+INFER:
+  pretrained_model_path: null
+  export_path: inference/fengwu_v2
+  onnx_path: ${INFER.export_path}.onnx
+  device: gpu
+  engine: onnx
+  precision: fp32
+  ir_optim: false
+  min_subgraph_size: 30
+  gpu_mem: 100
+  gpu_id: 3
+  max_batch_size: 1
+  num_cpu_threads: 10
+  batch_size: 1
+  mean_path: ./data_mean.npy
+  std_path: ./data_std.npy
+  input_prev_file: './data/input1.npy'
+  input_next_file: './data/input2.npy'
diff --git a/examples/fengwu/predict.py b/examples/fengwu/predict.py
new file mode 100644
index 0000000000..436a861543
--- /dev/null
+++ b/examples/fengwu/predict.py
@@ -0,0 +1,173 @@
+# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+#     http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from os import path as osp
+from typing import List
+
+import hydra
+import numpy as np
+import paddle
+from omegaconf import DictConfig
+from packaging import version
+
+from deploy.python_infer import base
+from ppsci.utils import logger
+
+
+class FengWuPredictor(base.Predictor):
+    """General predictor for FengWu model.
+
+    Args:
+        cfg (DictConfig): Running configuration.
+    """
+
+    # 14 day with time-interval of siz hours
+    PREDICT_TIMESTAMP = 14 * 24 / 6
+
+    def __init__(
+        self,
+        cfg: DictConfig,
+    ):
+        assert cfg.INFER.engine == "onnx", "FengWu engine only supports 'onnx'."
+
+        super().__init__(
+            pdmodel_path=None,
+            pdiparams_path=None,
+            device=cfg.INFER.device,
+            engine=cfg.INFER.engine,
+            precision=cfg.INFER.precision,
+            onnx_path=cfg.INFER.onnx_path,
+            ir_optim=cfg.INFER.ir_optim,
+            min_subgraph_size=cfg.INFER.min_subgraph_size,
+            gpu_mem=cfg.INFER.gpu_mem,
+            gpu_id=cfg.INFER.gpu_id,
+            max_batch_size=cfg.INFER.max_batch_size,
+            num_cpu_threads=cfg.INFER.num_cpu_threads,
+        )
+        self.log_freq = cfg.log_freq
+
+        # get input names
+        self.input_names = [
+            input_node.name for input_node in self.predictor.get_inputs()
+        ]
+
+        # get output names
+        self.output_names = [
+            output_node.name for output_node in self.predictor.get_outputs()
+        ]
+
+        # load mean and std data
+        self.data_mean = np.load(cfg.INFER.mean_path)[:, np.newaxis, np.newaxis]
+        self.data_std = np.load(cfg.INFER.std_path)[:, np.newaxis, np.newaxis]
+
+    def _preprocess_data(
+        self, input_data_prev: np.ndarray, input_data_next: np.ndarray
+    ) -> np.ndarray:
+        input_data_prev_after_norm = (
+            input_data_prev.astype("float32") - self.data_mean
+        ) / self.data_std
+        input_data_next_after_norm = (
+            input_data_next.astype("float32") - self.data_mean
+        ) / self.data_std
+        input_data = np.concatenate(
+            (input_data_prev_after_norm, input_data_next_after_norm), axis=0
+        )[np.newaxis, :, :, :]
+        input_data = input_data.astype(np.float32)
+
+        return input_data
+
+    def predict(
+        self,
+        input_data_prev: np.ndarray,
+        input_data_next: np.ndarray,
+        batch_size: int = 1,
+    ) -> List[np.ndarray]:
+        """Predicts the output of the yinglong model for the given input.
+
+        Args:
+            input_data_prev(np.ndarray): Atomospheric data at the first time moment.
+            input_data_next(np.ndarray): Atmospheric data six later.
+            batch_size (int, optional): Batch size, now only support 1. Defaults to 1.
+
+        Returns:
+            List[np.ndarray]: Prediction for next 56 hours.
+        """
+        if batch_size != 1:
+            raise ValueError(
+                f"FengWuPredictor only support batch_size=1, but got {batch_size}"
+            )
+
+        # process data
+        input_data = self._preprocess_data(input_data_prev, input_data_next)
+
+        output_data_list = []
+        # prepare input dict
+        for _ in range(self.__class__.PREDICT_TIMESTAMP):
+            input_dict = {
+                self.input_names[0]: input_data,
+            }
+
+            # run predictor
+            output_data = self.predictor.run(None, input_dict)[0]
+            input_data = np.concatenate(
+                (input_data[:, 69:], output_data[:, :69]), axis=1
+            )
+            output_data = (output_data[0, :69] * self.data_std) + self.data_mean
+
+            output_data_list.append(output_data)
+
+        return output_data_list
+
+
+def inference(cfg: DictConfig):
+    # log paddlepaddle's version
+    if version.Version(paddle.__version__) != version.Version("0.0.0"):
+        paddle_version = paddle.__version__
+        if version.Version(paddle.__version__) < version.Version("2.6.0"):
+            logger.warning(
+                f"Detected paddlepaddle version is '{paddle_version}', "
+                "currently it is recommended to use release 2.6 or develop version."
+            )
+    else:
+        paddle_version = f"develop({paddle.version.commit[:7]})"
+
+    logger.info(f"Using paddlepaddle {paddle_version}")
+
+    # create predictor
+    predictor = FengWuPredictor(cfg)
+
+    # load data
+    input_data_prev = np.load(cfg.INFER.input_prev_file).astype(np.float32)
+    input_data_next = np.load(cfg.INFER.input_next_file).astype(np.float32)
+
+    # run predictor
+    output_data_list = predictor.predict(input_data_prev, input_data_next)
+
+    # save predict data
+    for i in range(FengWuPredictor.PREDICT_TIMESTAMP):
+        output_save_path = osp.join(cfg.output_dir, f"output_{i}.npy")
+        np.save(output_save_path, output_data_list[i])
+        logger.info(f"Save output with timestamp:{i} to {output_save_path}.")
+
+
+@hydra.main(version_base=None, config_path="./conf", config_name="fengwu.yaml")
+def main(cfg: DictConfig):
+    if cfg.mode == "infer":
+        inference(cfg)
+    else:
+        raise ValueError(f"cfg.mode should in ['infer'], but got '{cfg.mode}'")
+
+
+if __name__ == "__main__":
+    main()

From 1a490dc986f4655dc50e3bdd53dd182f253bec8a Mon Sep 17 00:00:00 2001
From: beinggod <beinggod@foxmail.com>
Date: Tue, 4 Mar 2025 05:36:27 +0000
Subject: [PATCH 2/9] fix reviewer issue

---
 examples/fengwu/predict.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/fengwu/predict.py b/examples/fengwu/predict.py
index 436a861543..8e071f76c6 100644
--- a/examples/fengwu/predict.py
+++ b/examples/fengwu/predict.py
@@ -33,7 +33,7 @@ class FengWuPredictor(base.Predictor):
     """
 
     # 14 day with time-interval of siz hours
-    PREDICT_TIMESTAMP = 14 * 24 / 6
+    PREDICT_TIMESTAMP = int(14 * 24 / 6)
 
     def __init__(
         self,

From 0837a2a01f90c2635ee6e5ce0d374882195015aa Mon Sep 17 00:00:00 2001
From: beinggod <beinggod@foxmail.com>
Date: Tue, 4 Mar 2025 05:47:29 +0000
Subject: [PATCH 3/9] gpu_id default set to 0

---
 examples/fengwu/conf/fengwu.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/fengwu/conf/fengwu.yaml b/examples/fengwu/conf/fengwu.yaml
index d6fb79cce2..6a0c52ede8 100644
--- a/examples/fengwu/conf/fengwu.yaml
+++ b/examples/fengwu/conf/fengwu.yaml
@@ -36,7 +36,7 @@ INFER:
   ir_optim: false
   min_subgraph_size: 30
   gpu_mem: 100
-  gpu_id: 3
+  gpu_id: 0
   max_batch_size: 1
   num_cpu_threads: 10
   batch_size: 1

From b1d7b8a17e64cce1befcd2ddd326414813bd511c Mon Sep 17 00:00:00 2001
From: beinggod <beinggod@foxmail.com>
Date: Mon, 10 Mar 2025 00:12:26 +0800
Subject: [PATCH 4/9] Add convert script

---
 examples/fengwu/convert_data.py | 172 ++++++++++++++++++++++++++++++++
 1 file changed, 172 insertions(+)
 create mode 100644 examples/fengwu/convert_data.py

diff --git a/examples/fengwu/convert_data.py b/examples/fengwu/convert_data.py
new file mode 100644
index 0000000000..90c98c40ff
--- /dev/null
+++ b/examples/fengwu/convert_data.py
@@ -0,0 +1,172 @@
+# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+#     http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# ref: https://github.com/HaxyMoly/Pangu-Weather-ReadyToGo/blob/main/forecast_decode_functions.py
+
+import os
+from os import path as osp
+from typing import Dict
+
+import hydra
+import netCDF4 as nc
+import numpy as np
+
+from ppsci.utils import logger
+
+
+def convert_surface_data_to_nc(
+    surface_file: str, file_name: str, output_dir: str
+) -> None:
+    surface_data = np.load(surface_file)
+    u_component_of_wind_10m = surface_data[0]
+    v_component_of_wind_10m = surface_data[1]
+    temperature_2m = surface_data[2]
+    mean_sea_level_pressure = surface_data[3]
+
+    with nc.Dataset(
+        os.path.join(output_dir, file_name), "w", format="NETCDF4_CLASSIC"
+    ) as nc_file:
+        # Create dimensions
+        nc_file.createDimension("longitude", 1440)
+        nc_file.createDimension("latitude", 721)
+
+        # Create variables
+        nc_lon = nc_file.createVariable("longitude", np.float32, ("longitude",))
+        nc_lat = nc_file.createVariable("latitude", np.float32, ("latitude",))
+        nc_msl = nc_file.createVariable(
+            "mean_sea_level_pressure", np.float32, ("latitude", "longitude")
+        )
+        nc_u10 = nc_file.createVariable(
+            "u_component_of_wind_10m", np.float32, ("latitude", "longitude")
+        )
+        nc_v10 = nc_file.createVariable(
+            "v_component_of_wind_10m", np.float32, ("latitude", "longitude")
+        )
+        nc_t2m = nc_file.createVariable(
+            "temperature_2m", np.float32, ("latitude", "longitude")
+        )
+
+        # Set variable attributes
+        nc_lon.units = "degrees_east"
+        nc_lat.units = "degrees_north"
+        nc_msl.units = "Pa"
+        nc_u10.units = "m/s"
+        nc_v10.units = "m/s"
+        nc_t2m.units = "K"
+
+        # Write data to variables
+        nc_lon[:] = np.linspace(0.125, 359.875, 1440)
+        nc_lat[:] = np.linspace(90, -90, 721)
+        nc_msl[:] = mean_sea_level_pressure
+        nc_u10[:] = u_component_of_wind_10m
+        nc_v10[:] = v_component_of_wind_10m
+        nc_t2m[:] = temperature_2m
+
+    logger.info(
+        f"Convert output surface data file {surface_file} as nc format and save to {output_dir}/{file_name}."
+    )
+
+
+def convert_upper_data_to_nc(upper_file: str, file_name: str, output_dir: str) -> None:
+    # Load the saved numpy arrays
+    upper_data = np.load(upper_file)
+
+    # surface data offset
+    st = 4
+    level = 13
+
+    geopotential = upper_data[st : st + level]
+    specific_humidity = upper_data[st + level : st + 2 * level]
+    u_component_of_wind = upper_data[st + 2 * level : st + 3 * level]
+    v_component_of_wind = upper_data[st + 3 * level : st + 4 * level]
+    temperature = upper_data[st + 4 * level :]
+
+    with nc.Dataset(
+        os.path.join(output_dir, file_name), "w", format="NETCDF4_CLASSIC"
+    ) as nc_file:
+        # Create dimensions
+        nc_file.createDimension("longitude", 1440)
+        nc_file.createDimension("latitude", 721)
+        nc_file.createDimension("level", level)
+
+        # Create variables
+        nc_lon = nc_file.createVariable("longitude", np.float32, ("longitude",))
+        nc_lat = nc_file.createVariable("latitude", np.float32, ("latitude",))
+        nc_geopotential = nc_file.createVariable(
+            "geopotential", np.float32, ("level", "latitude", "longitude")
+        )
+        nc_specific_humidity = nc_file.createVariable(
+            "specific_humidity", np.float32, ("level", "latitude", "longitude")
+        )
+        nc_temperature = nc_file.createVariable(
+            "temperature", np.float32, ("level", "latitude", "longitude")
+        )
+        nc_u_component_of_wind = nc_file.createVariable(
+            "u_component_of_wind", np.float32, ("level", "latitude", "longitude")
+        )
+        nc_v_component_of_wind = nc_file.createVariable(
+            "v_component_of_wind", np.float32, ("level", "latitude", "longitude")
+        )
+
+        # Set variable attributes
+        nc_lon.units = "degrees_east"
+        nc_lat.units = "degrees_north"
+        nc_geopotential.units = "m"
+        nc_specific_humidity.units = "kg/kg"
+        nc_temperature.units = "K"
+        nc_u_component_of_wind.units = "m/s"
+        nc_v_component_of_wind.units = "m/s"
+        # Write data to variables
+        nc_lon[:] = np.linspace(0.125, 359.875, 1440)
+        nc_lat[:] = np.linspace(90, -90, 721)
+        nc_geopotential[:] = geopotential
+        nc_specific_humidity[:] = specific_humidity
+        nc_temperature[:] = temperature
+        nc_u_component_of_wind[:] = u_component_of_wind
+        nc_v_component_of_wind[:] = v_component_of_wind
+
+    logger.info(
+        f"Convert output upper data file {upper_file} as nc format and save to {output_dir}/{file_name}."
+    )
+
+
+def convert(cfg: Dict):
+    output_dir = cfg.output_dir
+
+    for _, file_name in os.listdir(output_dir):
+        if not file_name.endwiths("npy"):
+            continue
+
+        convert_surface_data_to_nc(
+            osp.join(output_dir, file_name),
+            osp.basename(file_name) + "_surface.nc",
+            output_dir,
+        )
+        convert_upper_data_to_nc(
+            osp.join(output_dir, file_name),
+            osp.basename(file_name) + "_upper.nc",
+            output_dir,
+        )
+
+
+@hydra.main(version_base=None, config_path="./conf", config_name="fengwu.yaml")
+def main(cfg: Dict):
+    if cfg.mode == "infer":
+        convert(cfg)
+    else:
+        raise ValueError(f"cfg.mode should in ['infer'], but got '{cfg.mode}'")
+
+
+if __name__ == "__main__":
+    main()

From 149a2ce19e8429cf370685c45c5b6acfcd34b418 Mon Sep 17 00:00:00 2001
From: beinggod <beinggod@foxmail.com>
Date: Mon, 10 Mar 2025 13:03:58 +0800
Subject: [PATCH 5/9] Add docs and fix some bugs

---
 docs/zh/examples/fengwu.md       |  95 +++++++++++++++++++++++++++++++
 examples/fengwu/conf/fengwu.yaml |   2 +-
 examples/fengwu/data_mean.npy    | Bin 0 -> 680 bytes
 examples/fengwu/data_std.npy     | Bin 0 -> 680 bytes
 examples/fengwu/predict.py       |   2 +-
 mkdocs.yml                       |   1 +
 6 files changed, 98 insertions(+), 2 deletions(-)
 create mode 100644 docs/zh/examples/fengwu.md
 create mode 100644 examples/fengwu/data_mean.npy
 create mode 100644 examples/fengwu/data_std.npy

diff --git a/docs/zh/examples/fengwu.md b/docs/zh/examples/fengwu.md
new file mode 100644
index 0000000000..63b1e91629
--- /dev/null
+++ b/docs/zh/examples/fengwu.md
@@ -0,0 +1,95 @@
+# FengWu
+
+=== "模型训练命令"
+
+    暂无
+
+=== "模型评估命令"
+
+    暂无
+
+=== "模型导出命令"
+
+    暂无
+
+=== "模型推理命令"
+
+    ``` sh
+    # Download sample input data
+    mkdir -p ./data
+    wget -nc https://paddle-org.bj.bcebos.com/paddlescience/models/Fengwu/input1.npy -P ./data
+    wget -nc https://paddle-org.bj.bcebos.com/paddlescience/models/Fengwu/input2.npy -P ./data
+
+    # Download pretrain model weight
+    mkdir -p ./inference
+    wget -nc https://paddle-org.bj.bcebos.com/paddlescience/models/Fengwu/fengwu_v2.onnx -P ./inference
+
+    # inference
+    python predict.py
+    ```
+
+## 1. 背景简介
+
+随着近年来全球气候变化加剧，极端天气频发，各界对天气预报的时效和精度的期待更是与日俱增。如何提高天气预报的时效和准确度，一直是业内的重点课题。AI大模型“风乌”基于多模态和多任务深度学习方法构建，实现在高分辨率上对核心大气变量进行超过10天的有效预报，并在80%的评估指标上超越DeepMind发布的模型GraphCast。同时，“风乌”仅需30秒即可生成未来10天全球高精度预报结果，在效率上大幅优于传统模型。
+
+## 2. 模型原理
+
+本章节仅对风乌气象大模型的原理进行简单地介绍，详细的理论推导请阅读 [FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead](https://arxiv.org/pdf/2304.02948)。
+
+模型的总体结构如图所示：
+
+待补充
+
+模型使用预训练权重推理，接下来将介绍模型的推理过程。
+
+## 3. 模型构建
+
+在该案例中，实现了 FengWuPredictor用于ONNX模型的推理：
+
+``` py linenums="102" title="examples/fengwu/predict.py"
+--8<--
+examples/fengwu/predict.py:28:130
+--8<--
+```
+
+``` yaml linenums="18" title="examples/fengwu/conf/fengwu.yaml"
+--8<--
+examples/fengwu/conf/fengwu.yaml:28:46
+--8<--
+```
+
+其中，`input_file` 和 `input_next_file` 分别代表网络模型输入的开始时刻气象数据和6小时后的气象数据。
+
+## 4. 结果可视化
+
+模型推理结果包含 56 个 npy 文件，表示从预测时间点开始，未来 14 天内每隔6小时的气象数据。结果可视化需要先将数据从 npy 转换为 NetCDF 格式，然后采用 ncvue 进行查看。
+
+1. 安装相关依赖
+```python
+pip install cdsapi netCDF4 ncvue
+```
+
+2. 使用脚本进行数据转换
+```python
+python convert_data.py
+```
+
+3. 使用 ncvue 打开转换后的 NetCDF 文件, ncvue 具体说明见[ncvue官方文档](https://github.com/mcuntz/ncvue)
+
+## 5. 完整代码
+
+``` py linenums="1" title="examples/fengwu/predict.py"
+--8<--
+examples/fengwu/predict.py
+--8<--
+```
+
+## 6. 结果展示
+
+下图展示了模型的平均海平面气压预测结果，更多指标可以使用 ncvue 查看。
+
+待补充
+
+## 7. 参考资料
+
+- [FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead](https://arxiv.org/pdf/2304.02948)
diff --git a/examples/fengwu/conf/fengwu.yaml b/examples/fengwu/conf/fengwu.yaml
index 6a0c52ede8..2af18f3a7e 100644
--- a/examples/fengwu/conf/fengwu.yaml
+++ b/examples/fengwu/conf/fengwu.yaml
@@ -42,5 +42,5 @@ INFER:
   batch_size: 1
   mean_path: ./data_mean.npy
   std_path: ./data_std.npy
-  input_prev_file: './data/input1.npy'
+  input_file: './data/input1.npy'
   input_next_file: './data/input2.npy'
diff --git a/examples/fengwu/data_mean.npy b/examples/fengwu/data_mean.npy
new file mode 100644
index 0000000000000000000000000000000000000000..b79998952c03d26106ecc23a9cdfc436d0ffde10
GIT binary patch
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diff --git a/examples/fengwu/data_std.npy b/examples/fengwu/data_std.npy
new file mode 100644
index 0000000000000000000000000000000000000000..805d54884a3a6dc0cda635ec467e46353e2cdbb7
GIT binary patch
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diff --git a/examples/fengwu/predict.py b/examples/fengwu/predict.py
index 8e071f76c6..73641dbb1e 100644
--- a/examples/fengwu/predict.py
+++ b/examples/fengwu/predict.py
@@ -148,7 +148,7 @@ def inference(cfg: DictConfig):
     predictor = FengWuPredictor(cfg)
 
     # load data
-    input_data_prev = np.load(cfg.INFER.input_prev_file).astype(np.float32)
+    input_data_prev = np.load(cfg.INFER.input_file).astype(np.float32)
     input_data_next = np.load(cfg.INFER.input_next_file).astype(np.float32)
 
     # run predictor
diff --git a/mkdocs.yml b/mkdocs.yml
index a9515dece9..780ffc2835 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -105,6 +105,7 @@ nav:
         - VelocityGAN: zh/examples/velocity_gan.md
         - TGCN: zh/examples/tgcn.md
         - IOPS: zh/examples/iops.md
+        - FengWu: zh/examples/fengwu.md
       - 化学科学(AI for Chemistry):
         - Moflow: zh/examples/moflow.md
         - IFM: zh/examples/ifm.md

From 9bd18f123dbce5845544a5705bc6375560970a30 Mon Sep 17 00:00:00 2001
From: beinggod <beinggod@foxmail.com>
Date: Mon, 10 Mar 2025 15:16:58 +0800
Subject: [PATCH 6/9] update docs

---
 docs/zh/examples/fengwu.md | 14 ++++++++++----
 1 file changed, 10 insertions(+), 4 deletions(-)

diff --git a/docs/zh/examples/fengwu.md b/docs/zh/examples/fengwu.md
index 63b1e91629..7b2e6744b0 100644
--- a/docs/zh/examples/fengwu.md
+++ b/docs/zh/examples/fengwu.md
@@ -16,12 +16,10 @@
 
     ``` sh
     # Download sample input data
-    mkdir -p ./data
     wget -nc https://paddle-org.bj.bcebos.com/paddlescience/models/Fengwu/input1.npy -P ./data
     wget -nc https://paddle-org.bj.bcebos.com/paddlescience/models/Fengwu/input2.npy -P ./data
 
     # Download pretrain model weight
-    mkdir -p ./inference
     wget -nc https://paddle-org.bj.bcebos.com/paddlescience/models/Fengwu/fengwu_v2.onnx -P ./inference
 
     # inference
@@ -38,7 +36,12 @@
 
 模型的总体结构如图所示：
 
-待补充
+<figure markdown>
+  ![result](https://paddle-org.bj.bcebos.com/paddlescience/docs/fengwu/model_architecture.png){ loading=lazy style="margin:0 auto;"}
+  <figcaption>模型结构</figcaption>
+</figure>
+
+模型将气候变量作为不同模态的输入。在 `Modal-Customized Encoder` 中将多个模态的特征进行编码，并使用基于 Transformer 的 `Cross-modal Fuser` 对编码后的特征进行融合，得到联合表示，最后在 `Modal-Customized Decoder` 中从联合表示中分别预测气候变量。
 
 模型使用预训练权重推理，接下来将介绍模型的推理过程。
 
@@ -88,7 +91,10 @@ examples/fengwu/predict.py
 
 下图展示了模型的平均海平面气压预测结果，更多指标可以使用 ncvue 查看。
 
-待补充
+<figure markdown>
+  ![result](https://paddle-org.bj.bcebos.com/paddlescience/docs/fengwu/image.png){ loading=lazy style="margin:0 auto;"}
+  <figcaption>平均海平面气压</figcaption>
+</figure>
 
 ## 7. 参考资料
 

From 9998d981f25ca5503ba57291dcbe08dc6f112e43 Mon Sep 17 00:00:00 2001
From: beinggod <beinggod@foxmail.com>
Date: Mon, 10 Mar 2025 16:10:31 +0800
Subject: [PATCH 7/9] fix docs

---
 docs/zh/examples/fengwu.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/zh/examples/fengwu.md b/docs/zh/examples/fengwu.md
index 7b2e6744b0..04e716dfe0 100644
--- a/docs/zh/examples/fengwu.md
+++ b/docs/zh/examples/fengwu.md
@@ -49,13 +49,13 @@
 
 在该案例中，实现了 FengWuPredictor用于ONNX模型的推理：
 
-``` py linenums="102" title="examples/fengwu/predict.py"
+``` py linenums="74" title="examples/fengwu/predict.py"
 --8<--
-examples/fengwu/predict.py:28:130
+examples/fengwu/predict.py:74:130
 --8<--
 ```
 
-``` yaml linenums="18" title="examples/fengwu/conf/fengwu.yaml"
+``` yaml linenums="28" title="examples/fengwu/conf/fengwu.yaml"
 --8<--
 examples/fengwu/conf/fengwu.yaml:28:46
 --8<--

From ff68413a74c9d14c7c653e5830fa12449a32ca62 Mon Sep 17 00:00:00 2001
From: beinggod <beinggod@foxmail.com>
Date: Mon, 10 Mar 2025 22:50:15 +0800
Subject: [PATCH 8/9] fix docs

---
 docs/zh/examples/fengwu.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/zh/examples/fengwu.md b/docs/zh/examples/fengwu.md
index 04e716dfe0..2466b62924 100644
--- a/docs/zh/examples/fengwu.md
+++ b/docs/zh/examples/fengwu.md
@@ -89,11 +89,11 @@ examples/fengwu/predict.py
 
 ## 6. 结果展示
 
-下图展示了模型的平均海平面气压预测结果，更多指标可以使用 ncvue 查看。
+下图展示了模型的未来6小时平均海平面气压预测结果，更多指标可以使用 ncvue 查看。
 
 <figure markdown>
   ![result](https://paddle-org.bj.bcebos.com/paddlescience/docs/fengwu/image.png){ loading=lazy style="margin:0 auto;"}
-  <figcaption>平均海平面气压</figcaption>
+  <figcaption>未来6小时平均海平面气压</figcaption>
 </figure>
 
 ## 7. 参考资料

From 664904ebd11d5192e073a410f90851c37fce1a5a Mon Sep 17 00:00:00 2001
From: beinggod <beinggod@foxmail.com>
Date: Tue, 11 Mar 2025 09:42:53 +0000
Subject: [PATCH 9/9] resolve reviewer issues

---
 README.md                  |  2 ++
 docs/index.md              |  2 ++
 examples/fengwu/predict.py | 17 ++++++++++++++---
 3 files changed, 18 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 65ee734668..71d0cc5557 100644
--- a/README.md
+++ b/README.md
@@ -112,6 +112,8 @@ PaddleScience 是一个基于深度学习框架 PaddlePaddle 开发的科学计
 | 天气预报 | [FourCastNet 气象预报](https://paddlescience-docs.readthedocs.io/zh-cn/latest/zh/examples/fourcastnet) | 数据驱动 | FourCastNet | 监督学习 | [ERA5](https://app.globus.org/file-manager?origin_id=945b3c9e-0f8c-11ed-8daf-9f359c660fbd&origin_path=%2F~%2Fdata%2F) | [Paper](https://arxiv.org/pdf/2202.11214.pdf) |
 | 天气预报 | [NowCastNet 气象预报](https://paddlescience-docs.readthedocs.io/zh-cn/latest/zh/examples/nowcastnet) | 数据驱动 | NowCastNet | 监督学习 | [MRMS](https://app.globus.org/file-manager?origin_id=945b3c9e-0f8c-11ed-8daf-9f359c660fbd&origin_path=%2F~%2Fdata%2F) | [Paper](https://www.nature.com/articles/s41586-023-06184-4) |
 | 天气预报 | [GraphCast 气象预报](https://paddlescience-docs.readthedocs.io/zh-cn/latest/zh/examples/graphcast) | 数据驱动 | GraphCastNet | 监督学习 | - | [Paper](https://arxiv.org/abs/2212.12794) |
+| 天气预报 | [FengWu 气象预报](https://paddlescience-docs.readthedocs.io/zh-cn/latest/zh/examples/fengwu) | 数据驱动 | Transformer | 监督学习 | - | [Paper](https://arxiv.org/pdf/2304.02948) |
+| 天气预报 | [Pangu-Weather 气象预报](https://paddlescience-docs.readthedocs.io/zh-cn/latest/zh/examples/pangu_weather) | 数据驱动 | Transformer | 监督学习 | - | [Paper](https://arxiv.org/pdf/2211.02556) |
 | 大气污染物 | [UNet 污染物扩散](https://aistudio.baidu.com/projectdetail/5663515?channel=0&channelType=0&sUid=438690&shared=1&ts=1698221963752) | 数据驱动 | UNet | 监督学习 | [Data](https://aistudio.baidu.com/datasetdetail/198102) | - |
 | 天气预报 | [DGMR 气象预报](https://paddlescience-docs.readthedocs.io/zh-cn/latest/zh/examples/dgmr.md) | 数据驱动 | DGMR | 监督学习 | [UK dataset](https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km) | [Paper](https://arxiv.org/pdf/2104.00954.pdf) |
 | 地震波形反演 | [VelocityGAN 地震波形反演](https://paddlescience-docs.readthedocs.io/zh-cn/latest/zh/examples/velocity_gan.md) | 数据驱动 | VelocityGAN | 监督学习 | [OpenFWI](https://openfwi-lanl.github.io/docs/data.html#vel) | [Paper](https://arxiv.org/abs/1809.10262v6) |
diff --git a/docs/index.md b/docs/index.md
index 602c238c2c..732aeca6f0 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -148,6 +148,8 @@
 | 天气预报 | [FourCastNet 气象预报](./zh/examples/fourcastnet.md) | 数据驱动 | FourCastNet | 监督学习 | [ERA5](https://app.globus.org/file-manager?origin_id=945b3c9e-0f8c-11ed-8daf-9f359c660fbd&origin_path=%2F~%2Fdata%2F) | [Paper](https://arxiv.org/pdf/2202.11214.pdf) |
 | 天气预报 | [NowCastNet 气象预报](./zh/examples/nowcastnet.md) | 数据驱动 | NowCastNet | 监督学习 | [MRMS](https://app.globus.org/file-manager?origin_id=945b3c9e-0f8c-11ed-8daf-9f359c660fbd&origin_path=%2F~%2Fdata%2F) | [Paper](https://www.nature.com/articles/s41586-023-06184-4) |
 | 天气预报 | [GraphCast 气象预报](./zh/examples/graphcast.md) | 数据驱动 | GraphCastNet | 监督学习 | - | [Paper](https://arxiv.org/abs/2212.12794) |
+| 天气预报 | [FengWu 气象预报](./zh/examples/fengwu.md) | 数据驱动 | Transformer | 监督学习 | - | [Paper](https://arxiv.org/pdf/2304.02948) |
+| 天气预报 | [Pangu-Weather 气象预报](./zh/examples/pangu_weather.md) | 数据驱动 | Transformer | 监督学习 | - | [Paper](https://arxiv.org/pdf/2211.02556) |
 | 大气污染物 | [UNet 污染物扩散](https://aistudio.baidu.com/projectdetail/5663515?channel=0&channelType=0&sUid=438690&shared=1&ts=1698221963752) | 数据驱动 | UNet | 监督学习 | [Data](https://aistudio.baidu.com/datasetdetail/198102) | - |
 | 天气预报 | [DGMR 气象预报](./zh/examples/dgmr.md) | 数据驱动 | DGMR | 监督学习 | [UK dataset](https://huggingface.co/datasets/openclimatefix/nimrod-uk-1km) | [Paper](https://arxiv.org/pdf/2104.00954.pdf) |
 | 地震波形反演 | [VelocityGAN 地震波形反演](./zh/examples/velocity_gan.md) | 数据驱动 | VelocityGAN | 监督学习 | [OpenFWI](https://openfwi-lanl.github.io/docs/data.html#vel) | [Paper](https://arxiv.org/abs/1809.10262v6) |
diff --git a/examples/fengwu/predict.py b/examples/fengwu/predict.py
index 73641dbb1e..d5b756edbe 100644
--- a/examples/fengwu/predict.py
+++ b/examples/fengwu/predict.py
@@ -34,6 +34,11 @@ class FengWuPredictor(base.Predictor):
 
     # 14 day with time-interval of siz hours
     PREDICT_TIMESTAMP = int(14 * 24 / 6)
+    # Where 69 represents 69 atmospheric features, The first four variables are surface variables in the order of ['u10', 'v10', 't2m', 'msl'],
+    # followed by non-surface variables in the order of ['z', 'q', 'u', 'v', 't']. Each data has 13 levels, which are ordered as
+    # [50, 100, 150, 200, 250, 300, 400, 500, 600, 700, 850, 925, 1000].
+    # Therefore, the order of the 69 variables is [u10, v10, t2m, msl, z50, z100, ..., z1000, q50, q100, ..., q1000, t50, t100, ..., t1000].
+    NUM_ATMOSPHERIC_FEATURES = 69
 
     def __init__(
         self,
@@ -113,7 +118,7 @@ def predict(
 
         output_data_list = []
         # prepare input dict
-        for _ in range(self.__class__.PREDICT_TIMESTAMP):
+        for _ in range(self.PREDICT_TIMESTAMP):
             input_dict = {
                 self.input_names[0]: input_data,
             }
@@ -121,9 +126,15 @@ def predict(
             # run predictor
             output_data = self.predictor.run(None, input_dict)[0]
             input_data = np.concatenate(
-                (input_data[:, 69:], output_data[:, :69]), axis=1
+                (
+                    input_data[:, self.NUM_ATMOSPHERIC_FEATURES :],
+                    output_data[:, : self.NUM_ATMOSPHERIC_FEATURES],
+                ),
+                axis=1,
             )
-            output_data = (output_data[0, :69] * self.data_std) + self.data_mean
+            output_data = (
+                output_data[0, : self.NUM_ATMOSPHERIC_FEATURES] * self.data_std
+            ) + self.data_mean
 
             output_data_list.append(output_data)