The MJO phase diagram illustrates its progression through phases, coinciding with locations along the equator around the globe. This can also illustrate its intensity.

Future posts will elaborate on parts of this recipe.

#python #atmosci

import pandas as pd
import hvplot.pandas
import holoviews as hv
from bokeh.models import FixedTicker

hv.extension("bokeh")

# load data
url = "https://ds.data.jma.go.jp/tcc/tcc/products/clisys/mjo/figs/olr0-sst1_1980-2010/rmm8.csv"
df = pd.read_csv(url)

# clean up columns
df.columns = df.columns.str.strip()

# add datetime to subset
df.index = pd.to_datetime({"year": df["#year"], "month": df["month"], "day": df["day"]})
df["date"] = df.index
df = df.loc[df.index > "2023"]

# format plots
ini = df.iloc[0]["date"].strftime("%b %d, %Y")
end = df.iloc[0]["date"].strftime("%b %d, %Y")
plot_opts = dict(
    xlim=(-4, 4),
    ylim=(-4, 4),
    frame_width=800,
    frame_height=800,
    line_width=1.8,
    colorbar=True,
    clabel="Month",
    cmap="RdYlBu_r",
    color_levels=len(df["month"].unique()) - 1,
    title=f"MJO RMM phase space from {ini} to {end}\nData: {url}",
    colorbar_opts={
        "ticker": FixedTicker(ticks=sorted(df["month"].unique())),
        "major_label_overrides": {
            1: "Jan",
            2: "Feb",
            3: "Mar",
            4: "Apr",
            5: "May",
            6: "Jun",
            7: "Jul",
            8: "Aug",
            9: "Sep",
            10: "Oct",
            11: "Nov",
            12: "Dec",
        },
    },
)

# actually plot
rmm_line = df.hvplot.paths(
  	x="RMM1", y="RMM2", color="month"
).opts(**plot_opts)
rmm_scatter = df.hvplot.scatter(
  	"RMM1", "RMM2", color="black", groupby="date", size=50
)
rmm_plot = rmm_line * rmm_scatter

# add start and end date
rmm_plot *= hv.Text(*df.iloc[0][["RMM1", "RMM2"]], text="START", valign="bottom")
rmm_plot *= hv.Text(*df.iloc[-1][["RMM1", "RMM2"]], text="END", valign="bottom")

# add phase labels
rmm_plot *= hv.Text(-3.5, -1.5, text="1")
rmm_plot *= hv.Text(-1.5, -3.5, text="2")
rmm_plot *= hv.Text(1.5, -3.5, text="3")
rmm_plot *= hv.Text(3.5, -1.5, text="4")
rmm_plot *= hv.Text(3.5, 1.5, text="5")
rmm_plot *= hv.Text(1.5, 3.5, text="6")
rmm_plot *= hv.Text(-1.5, 3.5, text="7")
rmm_plot *= hv.Text(-3.5, 1.5, text="8")

# add region labels
rmm_plot *= hv.Text(0, 4, text="Western\nPacific", valign="top")
rmm_plot *= hv.Text(
  	4, 0, text="Maritime\nContinent", valign="top", rotation=270)
rmm_plot *= hv.Text(0, -4, text="Indian\nOcean", valign="bottom")
rmm_plot *= hv.Text(
  	-4, 0, text="West Hem.\nand Africa", valign="top", rotation=90)

# add reference lines
ref_opts = dict(color="black", line_width=0.5, alpha=0.5, line_dash="dashed")
rmm_plot *= hv.Slope(1, 0).opts(**ref_opts)
rmm_plot *= hv.Slope(-1, 0).opts(**ref_opts)
rmm_plot *= hv.VLine(0).opts(**ref_opts)
rmm_plot *= hv.HLine(0).opts(**ref_opts)
rmm_plot *= hv.Ellipse(0, 0, (1, 1)).opts(**ref_opts)

hv.save(rmm_plot, "output.html")