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Datasets:
wuff-mann
/
ATLAS-WDS-v2

Tasks:
Image-to-Image
Modalities:
Tabular
Text
Time-series
Formats:
parquet
Size:
1M - 10M
Tags:
oceanography
wave-spectrum
wind-sea-swell
wave-age
directional-spectrum
Libraries:
Datasets
Dask
Polars
License:
Dataset card Data Studio Files
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1
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Auto-converted to Parquet Duplicate
sample_id
string
energy_mem
list
energy_fourier
list
freqs_real
list
n_freqs
int32
n_dirs
int32
source
string
station
string
timestamp_utc
string
lat
float32
lon
float32
has_wind
bool
u10
float32
wdir
float32
wave_age_map
list
windsea_mask
list
Hs
float32
Tp
float32
Dp
float32
total_energy
float32
Hs_obs
float32
Tp_obs
float32
Dp_obs
float32
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dods_41001_20230101T0300
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ATLAS-WDS-v2: Wave Directional Spectrum + Wind Field Dataset

海浪方向谱 + 风场融合数据集 (v4.1 管线: 2010–2026, 同站 stdmet 风场, 跨源去重). 每条样本同时含 MEM / Fourier 两种重建方向谱、真实 UTC 时间、 **同站(浮标自带 stdmet)风场 (u10, wdir)、逐点波龄判据 W(f,θ)**。 样本按 station + UTC 去重 (文本/DODS 同一物理观测只一条, source 记来源)。

字段

  • energy_mem, energy_fourier: 展平的 47×72 方向谱 (固定均匀频率网格 0.02–0.5 Hz)
  • freqs_real: 该样本的真实非均匀频率轴 (47,), 用于波龄判据相速计算
  • timestamp_utc, station, lat, lon
  • has_wind: 是否成功匹配到风场
  • u10 (m/s), wdir (deg true, FROM): 风速/风向 (has_wind=False 时为 NaN)
  • wave_age_map: 展平的 W(f,θ)=1.2·(u10/c_p)·cos(θ−ψ), c_p=g/(2πf) (无风场为 NaN)
  • windsea_mask: W>1 风浪区掩码
  • Hs, Tp, Dp, total_energy: 由 MEM 谱积分得到
  • source: ndbc_text / dods / cdip

加载 

from datasets import load_dataset
import numpy as np
ds = load_dataset("wuff-mann/ATLAS-WDS-v2", split="train")
s = ds[0]
E = np.array(s["energy_mem"], np.float32).reshape(s["n_freqs"], s["n_dirs"])
W = np.array(s["wave_age_map"], np.float32).reshape(s["n_freqs"], s["n_dirs"])
# 纯谱版: 用全量; 风场版: ds.filter(lambda x: x["has_wind"])

对照实验设计

  • 纯谱基线: 全量, 忽略风场列
  • 风场版: has_wind=True 子集, 用 wave_age_map 做强监督正则
  • MEM vs Fourier: 同一批样本两种方向谱, 比较分割效果
Downloads last month
574
Number of rows:
1,310,565
Total file size:
26.9 GB