{ "cells": [ { "cell_type": "markdown", "id": "boxed-driving", "metadata": {}, "source": [ "# Using cartopy and projections for plotting" ] }, { "cell_type": "markdown", "id": "weekly-immunology", "metadata": {}, "source": [ "## Open ERA5 dataset" ] }, { "cell_type": "code", "execution_count": 1, "id": "e9442b99-7e6b-4d3b-b6fe-479e1cee6563", "metadata": {}, "outputs": [], "source": [ "# Importing the required packages\n", "import intake\n", "import cartopy.crs as ccrs\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "id": "0fc2dc8d-1bed-4a3a-a771-72a03c73b845", "metadata": {}, "source": [ "## Reading and browsing the catalog" ] }, { "cell_type": "code", "execution_count": 3, "id": "9f79cb30-d905-443a-8fdd-75e0f8c8c959", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
cmip6 catalog with 155 dataset(s) from 536945 asset(s):
\n", " | unique | \n", "
---|---|
variable_id | \n", "583 | \n", "
table_id | \n", "24 | \n", "
source_id | \n", "75 | \n", "
experiment_id | \n", "94 | \n", "
member_id | \n", "190 | \n", "
grid_label | \n", "11 | \n", "
time_range | \n", "9100 | \n", "
activity_id | \n", "18 | \n", "
institution_id | \n", "35 | \n", "
version | \n", "577 | \n", "
path | \n", "536945 | \n", "
dcpp_init_year | \n", "0 | \n", "
derived_variable_id | \n", "0 | \n", "
<xarray.Dataset> Size: 438MB\n", "Dimensions: (member_id: 1, time: 1980, lat: 192, lon: 288, nbnd: 2)\n", "Coordinates:\n", " * lat (lat) float64 2kB -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0\n", " * lon (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n", " * time (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00\n", " * member_id (member_id) object 8B 'r1i1p1f1'\n", "Dimensions without coordinates: nbnd\n", "Data variables:\n", " tas (member_id, time, lat, lon) float32 438MB dask.array<chunksize=(1, 48, 192, 288), meta=np.ndarray>\n", " time_bnds (time, nbnd) object 32kB dask.array<chunksize=(48, 2), meta=np.ndarray>\n", " lat_bnds (lat, nbnd) float32 2kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n", " lon_bnds (lon, nbnd) float32 2kB dask.array<chunksize=(288, 2), meta=np.ndarray>\n", "Attributes: (12/59)\n", " Conventions: CF-1.7 CMIP-6.2\n", " activity_id: CMIP\n", " case_id: 15\n", " cesm_casename: b.e21.BHIST.f09_g17.CMIP6-historical.001\n", " contact: cesm_cmip6@ucar.edu\n", " creation_date: 2019-01-16T23:34:05Z\n", " ... ...\n", " intake_esm_attrs:activity_id: CMIP\n", " intake_esm_attrs:institution_id: NCAR\n", " intake_esm_attrs:version: v20190308\n", " intake_esm_attrs:path: /mnt/craas1-ns9989k-ns9560k/ESGF/CMIP6/...\n", " intake_esm_attrs:_data_format_: netcdf\n", " intake_esm_dataset_key: CMIP.NCAR
<xarray.DataArray 'tas' (member_id: 1, time: 1980, lat: 192, lon: 288)> Size: 438MB\n", "dask.array<broadcast_to, shape=(1, 1980, 192, 288), dtype=float32, chunksize=(1, 48, 192, 288), chunktype=numpy.ndarray>\n", "Coordinates:\n", " * lat (lat) float64 2kB -90.0 -89.06 -88.12 -87.17 ... 88.12 89.06 90.0\n", " * lon (lon) float64 2kB 0.0 1.25 2.5 3.75 ... 355.0 356.2 357.5 358.8\n", " * time (time) object 16kB 1850-01-15 12:00:00 ... 2014-12-15 12:00:00\n", " * member_id (member_id) object 8B 'r1i1p1f1'\n", "Attributes: (12/19)\n", " cell_measures: area: areacella\n", " cell_methods: area: time: mean\n", " comment: near-surface (usually, 2 meter) air temperature\n", " description: near-surface (usually, 2 meter) air temperature\n", " frequency: mon\n", " id: tas\n", " ... ...\n", " time_label: time-mean\n", " time_title: Temporal mean\n", " title: Near-Surface Air Temperature\n", " type: real\n", " units: K\n", " variable_id: tas