Global Mean Sea Level rise dataset¶

The following dataset is the Global Mean Sea Level (GMSL) rise from the late 19th to the Early 21st Century 1. The original dataset was downloaded as a CSV file and subsequently converted to the CSD model format.

Let’s import this file.

import csdmpy as cp

filename = "https://www.ssnmr.org/sites/default/files/CSDM/gmsl/GMSL.csdf"
sea_level = cp.load(filename)

The variable filename is a string with the address to the .csdf file. The load() method of the csdmpy module reads the file and returns an instance of the CSDM class, in this case, as a variable sea_level. For a quick preview of the data structure, use the data_structure attribute of this instance.

print(sea_level.data_structure)

{
  "csdm": {
    "version": "1.0",
    "read_only": true,
    "timestamp": "2019-05-21T13:43:00Z",
    "tags": [
      "Jason-2",
      "satellite altimetry",
      "mean sea level",
      "climate"
    ],
    "description": "Global Mean Sea Level (GMSL) rise from the late 19th to the Early 21st Century.",
    "dimensions": [
      {
        "type": "linear",
        "count": 1608,
        "increment": "0.08333333333 yr",
        "coordinates_offset": "1880.0416666667 yr",
        "quantity_name": "time",
        "reciprocal": {
          "quantity_name": "frequency"
        }
      }
    ],
    "dependent_variables": [
      {
        "type": "internal",
        "name": "Global Mean Sea Level",
        "unit": "mm",
        "quantity_name": "length",
        "numeric_type": "float32",
        "quantity_type": "scalar",
        "component_labels": [
          "GMSL"
        ],
        "components": [
          [
            "-183.0, -171.125, ..., 59.6875, 58.5"
          ]
        ]
      }
    ]
  }
}

Warning

The serialized string from the data_structure attribute is not the same as the JSON serialization on the file. This attribute is only intended for a quick preview of the data structure and avoids displaying large datasets. Do not use the value of this attribute to save the data to the file. Instead, use the save() method of the CSDM class.

The tuple of the dimensions and dependent variables, from this example, are

x = sea_level.dimensions
y = sea_level.dependent_variables

respectively. The coordinates along the dimension and the component of the dependent variable are

print(x[0].coordinates)

[1880.04166667 1880.125      1880.20833333 ... 2013.79166666 2013.87499999
 2013.95833333] yr

and

print(y[0].components[0])

[-183.     -171.125  -164.25   ...   66.375    59.6875   58.5   ]

respectively.

Plotting the data

Note

The following code is only for illustrative purposes. The users may use any plotting library to visualize their datasets.

import matplotlib.pyplot as plt

plt.figure(figsize=(5, 3.5))
ax = plt.subplot(projection="csdm")

# csdmpy is compatible with matplotlib function. Use the csdm object as the argument
# of the matplotlib function.
ax.plot(sea_level)
plt.tight_layout()
plt.show()

The following is a quick description of the above code. Within the code, we make use of the csdm instance’s attributes in addition to the matplotlib functions. The first line is an import call for the matplotlib functions. The following line generates a plot of the coordinates along the dimension verse the component of the dependent variable. The next line sets the x-range. For labeling the axes, use the axis_label attribute of both dimension and dependent variable instances. For the figure title, use the name attribute of the dependent variable instance. The next statement adds the grid lines. For additional information, refer to Matplotlib documentation.