Hurricane track + spaghetti from HURDAT2
Meteorology
Example from the compendium of canonical charts
Python Code
"""Meteorology — Hurricane track + spaghetti from HURDAT2."""
import numpy as np
import pandas as pd
import plotly.graph_objects as go
import io, requests, warnings
HURDAT_URL = "https://www.nhc.noaa.gov/data/hurdat/hurdat2-1851-2023-051124.txt"
TARGETS = {
"AL122005": ("Katrina (2005)", VIOLET, 3.5),
"AL092017": ("Irma (2017)", ORANGE, 1.5),
"AL142018": ("Michael (2018)", TEAL, 1.5),
"AL092019": ("Dorian (2019)", PINK, 1.5),
"AL142016": ("Matthew (2016)", GREEN, 1.5),
}
SYNTHETIC_STORMS = {
"AL122005": pd.DataFrame({
"lat": [23.1, 24.5, 25.7, 26.1, 26.9, 27.1, 26.7, 26.2, 26.9, 28.2,
29.5, 29.9, 29.2, 28.5],
"lon": [-75.1, -76.5, -77.2, -78.8, -80.2, -81.5, -82.3, -83.5, -85.1,
-86.3, -87.9, -88.9, -89.6, -90.1],
"wind": [35, 55, 75, 80, 100, 90, 110, 130, 145, 155, 160, 150, 110, 70],
}),
"AL092017": pd.DataFrame({
"lat": [16.4, 17.9, 19.1, 20.3, 22.0, 23.5, 24.8, 25.9, 25.5, 24.7,
25.5, 26.8, 28.2],
"lon": [-31.5, -34.1, -37.5, -41.3, -45.8, -50.0, -55.5, -61.1, -64.0,
-67.2, -72.8, -78.3, -82.5],
"wind": [30, 55, 80, 105, 130, 150, 165, 180, 175, 155, 130, 110, 90],
}),
"AL142018": pd.DataFrame({
"lat": [19.0, 20.5, 22.1, 23.9, 26.2, 28.5, 30.1],
"lon": [-86.7, -87.3, -87.9, -87.6, -86.5, -85.8, -85.1],
"wind": [35, 60, 90, 115, 135, 145, 115],
}),
"AL092019": pd.DataFrame({
"lat": [24.2, 25.1, 26.0, 26.5, 26.5, 26.6, 27.3, 28.2, 29.5, 31.2],
"lon": [-73.0, -74.5, -75.7, -76.9, -78.0, -79.8, -80.5, -80.3, -79.3, -78.2],
"wind": [45, 70, 100, 135, 155, 160, 145, 125, 105, 85],
}),
"AL142016": pd.DataFrame({
"lat": [13.5, 14.9, 16.5, 18.1, 20.5, 22.8, 25.1, 27.2, 28.9, 31.1, 33.2],
"lon": [-57.2, -59.5, -63.0, -66.4, -70.5, -73.8, -75.5, -77.1, -78.5, -79.9, -81.0],
"wind": [35, 55, 80, 110, 135, 145, 130, 115, 120, 110, 70],
}),
}
def parse_hurdat(text):
storms = {}
current_id = None
records = []
for line in text.strip().split("\n"):
parts = [p.strip() for p in line.split(",")]
if len(parts) >= 3 and parts[0].startswith("AL"):
if current_id and records:
storms[current_id] = pd.DataFrame(
records, columns=["date", "time", "record", "status",
"lat", "lon", "wind", "pressure"])
current_id = parts[0]
records = []
elif current_id and len(parts) >= 8:
try:
lat_s = parts[4]
lon_s = parts[5]
lat = float(lat_s[:-1]) * (1 if lat_s[-1] == "N" else -1)
lon = float(lon_s[:-1]) * (-1 if lon_s[-1] == "W" else 1)
wind = int(parts[6])
pressure = int(parts[7]) if parts[7].strip() else 0
records.append([parts[0], parts[1], parts[2], parts[3],
lat, lon, wind, pressure])
except (ValueError, IndexError):
pass
if current_id and records:
storms[current_id] = pd.DataFrame(
records, columns=["date", "time", "record", "status",
"lat", "lon", "wind", "pressure"])
return storms
def wind_to_category(w):
if w >= 157: return "#8B0000"
if w >= 130: return "#FF4500"
if w >= 111: return "#FF8C00"
if w >= 96: return "#FFD700"
if w >= 74: return "#00BFFF"
return "#AAAAAA"
def generate():
print("building hurricane track + spaghetti …")
warnings.filterwarnings("ignore")
storms = {}
try:
requests.packages.urllib3.disable_warnings()
r = requests.get(HURDAT_URL, verify=False, timeout=60)
r.raise_for_status()
storms = parse_hurdat(r.text)
print(f" loaded {len(storms)} storms; Katrina: {'AL122005' in storms}")
except Exception as e:
print(f" HURDAT failed ({e}), using synthetic tracks")
storms = SYNTHETIC_STORMS
fig = go.Figure()
spaghetti_ids = [sid for sid in TARGETS if sid != "AL122005"]
for sid in spaghetti_ids:
if sid not in storms:
continue
df_s = storms[sid]
label, color, width = TARGETS[sid]
fig.add_trace(go.Scattermapbox(
lat=df_s["lat"].tolist(),
lon=df_s["lon"].tolist(),
mode="lines",
line=dict(color=color, width=width),
opacity=0.7,
name=label,
hoverinfo="name",
))
katrina = storms.get("AL122005")
if katrina is not None and len(katrina) > 1:
kat_lat = katrina["lat"].tolist()
kat_lon = katrina["lon"].tolist()
kat_wind = katrina["wind"].tolist()
for i in range(len(kat_lat) - 1):
w = (kat_wind[i] + kat_wind[i+1]) / 2
fig.add_trace(go.Scattermapbox(
lat=[kat_lat[i], kat_lat[i+1]],
lon=[kat_lon[i], kat_lon[i+1]],
mode="lines",
line=dict(color=wind_to_category(w), width=4),
showlegend=False,
hoverinfo="skip",
))
fig.add_trace(go.Scattermapbox(
lat=kat_lat,
lon=kat_lon,
mode="markers",
marker=dict(
size=[max(8, w / 10) for w in kat_wind],
color=[wind_to_category(w) for w in kat_wind],
),
name="Katrina (2005)",
hovertemplate="Lat: %{lat:.1f}°<br>Lon: %{lon:.1f}°<br>Wind: %{customdata} kt<extra></extra>",
customdata=kat_wind,
))
# Apply the gallery theme first so the legend-font override below survives
# (save() would otherwise re-theme the legend text to the dark theme color,
# leaving it illegible on the dark legend panel).
apply_theme(fig)
# Satellite basemap — ESRI World Imagery raster tiles over a blank base
# (no Mapbox token required).
fig.update_layout(
mapbox=dict(
style="white-bg",
layers=[dict(
below="traces",
sourcetype="raster",
sourceattribution="Esri, Maxar, Earthstar Geographics",
source=[
"https://server.arcgisonline.com/ArcGIS/rest/services/"
"World_Imagery/MapServer/tile/{z}/{y}/{x}"
],
)],
center=dict(lat=27, lon=-82),
zoom=4.0,
),
legend=dict(
x=0.01, y=0.99,
font=dict(size=11, color="#ffffff"),
bgcolor="rgba(0,0,0,0.78)",
bordercolor="rgba(255,255,255,0.35)",
borderwidth=1,
),
margin=dict(t=0, b=0, l=0, r=0),
)
return fig
if __name__ == "__main__":
generate()Made with Plotly