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Julia
Python

using CairoMakie

xs = LinRange(0, 10, 100);
ys = LinRange(0, 10, 100);
zs = [cos(x) * sin(y) for x in xs, y in ys];
us=[-cos(x) * cos(y) for x in xs, y in ys];
vs=[-sin(x) * sin(y) for x in xs, y in ys];
fig = Figure(backgroundcolor = RGBf0(0.98, 0.98, 0.98),
    resolution = (1000, 600))

ax1 = fig[1, 1] = Axis(fig, title = "Test")
#scene, layout = layoutscene(resolution = (1000, 600))
#scene, layout = layoutscene()
#display(scene)
#ax1 = layout[1,1] = LAxis(scene)
heatmap!(ax1, xs, ys, zs, colormap=cgrad(:jet, 10, categorical=true), interpolate=true)
ax1.aspect = AxisAspect(1)
ax1.xticks = 1:10
ax1.yticks = 0:10
contour!(ax1,xs, ys, zs, levels = 10, linewidth = 1, fillrange = true)
contour!(ax1,xs, ys, zs, levels = 10, linewidth = 0.2, fillrange = false, color = "black")
arrows!(ax1,xs,ys,us,vs, arrowsize = 0.25, lengthscale = 0.25)
#heatmap!(ax2, xs, ys, zs, colormap=:starrynight)
#ax1.aspect = AxisAspect(1)
fig

import plotly.graph_objects as go

import pandas as pd

# Read data from a csv
z_data = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/api_docs/mt_bruno_elevation.csv')

fig = go.Figure(data=[go.Surface(z=z_data.values)])

fig.update_layout(title='Mt Bruno Elevation', autosize=False,
                  width=500, height=500,
                  margin=dict(l=65, r=50, b=65, t=90))

fig.show()

1 Modelos de Capas

\dfrac {\partial \overrightarrow {u}_{i}}{\partial t}+\overrightarrow {u}_{i}\cdot {\nabla \overrightarrow u}_{i}+f \overrightarrow {k}\times \overrightarrow {u}_{i}=-\dfrac {1}{\rho _{0}}\nabla P_{i}

\dfrac {\partial h_{i}}{\partial t}+\nabla \cdot \left( h\overrightarrow {u}_{i}\right) =0

\dfrac {\partial P}{\partial z}=-\rho g