# Parameters
variable = "hfsifrazil"
long_name = "Heat Flux into Sea Water due to Frazil Ice Formation"

hfsifrazil

from IPython.display import display, Markdown

The history saving thread hit an unexpected error (OperationalError('database is locked')).History will not be written to the database.

# Dynamically generate markdown content
markdown_text = f" This notebook compares area-weighted mean and, in some cases, integral time series for {variable} in different basins."

# Display the updated markdown content
display(Markdown(markdown_text))

This notebook compares area-weighted mean and, in some cases, integral time series for hfsifrazil in different basins.

%load_ext autoreload
%autoreload 2

%%capture 
# comment above line to see details about the run(s) displayed
import sys, os
sys.path.append(os.path.abspath(".."))
from misc import *
import glob
print("Last update:", date.today())
%matplotlib inline

# figure size
fs = (10,4)

# load data
ds = []
for c, p in zip(casename, ocn_path):
  file = glob.glob(p+'{}.native.{}.??????-??????.nc'.format(c, variable))[0]
  ds.append(xr.open_dataset(file))

def ts_plot(variable, ds, fs, label, reg='Global'):
    """
    Plot time series of regional means and integrals for a given variable from a list of datasets.

    Parameters
    ----------
    variable : str
        Name of the variable to plot (prefix for "_mean" and "_int" variables in dataset).
    ds : list of xarray.Dataset
        List of datasets, each containing time series data for the specified variable with
        variables named as `<variable>_mean` and optionally `<variable>_int`, and with
        attributes 'long_name', 'units_mean', and optionally 'units_int'.
    fs : tuple
        Figure size (width, height) in inches for the plots.
    label : list of str
        List of labels corresponding to each dataset, used for the legend.
    reg : str, optional
        Name of the region to select for plotting (default is 'Global').

    Returns
    -------
    None
        Displays the plots but does not return any value.

    Notes
    -----
    - This function creates one or two plots:
        1. A time series of the variable's regional mean (`<variable>_mean`).
        2. If available, a time series of the variable's regional integral (`<variable>_int`).
    - The function expects each dataset to have attributes 'long_name', 'units_mean', and optionally 'units_int'.
    - The same region name is applied across all datasets.
    """
    
    fig, ax = plt.subplots(nrows=1, ncols=1, figsize=fs)
    for l, i in zip(label, range(len(label))):
        ds[i][variable+"_mean"].sel(region=reg).plot(ax=ax, label=l, lw=3, linestyle=linestyle[i], color=color[i])
    
    long_name = ds[0].attrs['long_name']
    ax.set_title("{}, {}".format(reg, long_name))
    ax.set_ylabel(variable+"_mean, " + ds[i].attrs['units_mean'])
    ax.set_xlabel('Year')
    ax.grid()
    ax.legend(ncol=3, loc=1)
    
    if variable+"_int" in ds[0]:
        fig, ax = plt.subplots(nrows=1, ncols=1, figsize=fs)
        for l, i in zip(label, range(len(label))):
            ds[i][variable+"_int"].sel(region=reg).plot(ax=ax, label=l, lw=3, linestyle=linestyle[i], color=color[i])

        ax.set_title("{}, {}".format(reg, long_name))
        ax.set_ylabel(variable+"_int, " + ds[i].attrs['units_int'])
        ax.set_xlabel('Year')
        ax.grid()
        ax.legend(ncol=3, loc=1)

    return

Global

reg = 'Global'
ts_plot(variable, ds, fs, label, reg = reg)

PersianGulf

reg = 'PersianGulf'
ts_plot(variable, ds, fs, label, reg = reg)

RedSea

reg = 'RedSea'
ts_plot(variable, ds, fs, label, reg = reg)

BlackSea

reg = 'BlackSea'
ts_plot(variable, ds, fs, label, reg = reg)

MedSea

reg = 'MedSea'
ts_plot(variable, ds, fs, label, reg = reg)

BalticSea

reg = 'BalticSea'
ts_plot(variable, ds, fs, label, reg = reg)

HudsonBay

reg = 'HudsonBay'
ts_plot(variable, ds, fs, label, reg = reg)

Arctic

reg = 'Arctic'
ts_plot(variable, ds, fs, label, reg = reg)

PacificOcean

reg = 'PacificOcean'
ts_plot(variable, ds, fs, label, reg = reg)

AtlanticOcean

reg = 'AtlanticOcean'
ts_plot(variable, ds, fs, label, reg = reg)

IndianOcean

reg = 'IndianOcean'
ts_plot(variable, ds, fs, label, reg = reg)

SouthernOcean

reg = 'SouthernOcean'
ts_plot(variable, ds, fs, label, reg = reg)

LabSea

reg = 'LabSea'
ts_plot(variable, ds, fs, label, reg = reg)

BaffinBay

reg = 'BaffinBay'
ts_plot(variable, ds, fs, label, reg = reg)

Maritime

reg = 'Maritime'
ts_plot(variable, ds, fs, label, reg = reg)

SouthernOcean60S

reg = 'SouthernOcean60S'
ts_plot(variable, ds, fs, label, reg = reg)

EGreenlandIceland

reg = 'EGreenlandIceland'
ts_plot(variable, ds, fs, label, reg = reg)

GulfOfMexico

reg = 'GulfOfMexico'
ts_plot(variable, ds, fs, label, reg = reg)