diff --git a/notebooks/wp4/extreme_indices.ipynb b/notebooks/wp4/extreme_indices.ipynb index 627c4eb..a2f0e93 100644 --- a/notebooks/wp4/extreme_indices.ipynb +++ b/notebooks/wp4/extreme_indices.ipynb @@ -41,7 +41,7 @@ "import icclim\n", "import matplotlib.pyplot as plt\n", "import xarray as xr\n", - "from c3s_eqc_automatic_quality_control import diagnostics, download, plot\n", + "from c3s_eqc_automatic_quality_control import diagnostics, download, plot, utils\n", "from xarrayMannKendall import Mann_Kendall_test\n", "\n", "plt.style.use(\"seaborn-v0_8-notebook\")\n", @@ -96,6 +96,9 @@ "# Interpolation method\n", "interpolation_method = \"bilinear\"\n", "\n", + "# Area to show\n", + "area = [72, -22, 27, 45]\n", + "\n", "# Chunks for download\n", "chunks = {\"year\": 1}" ] @@ -187,7 +190,6 @@ }, "outputs": [], "source": [ - "area = [72, -22, 27, 45]\n", "request_era = (\n", " \"reanalysis-era5-single-levels\",\n", " {\n", @@ -556,8 +558,21 @@ "metadata": {}, "outputs": [], "source": [ - "# Mask\n", "lsm = download.download_and_transform(*request_lsm)[\"lsm\"].squeeze(drop=True)\n", + "\n", + "# Cutout\n", + "regionalise_kwargs = {\n", + " \"lon_slice\": slice(area[1], area[3]),\n", + " \"lat_slice\": slice(area[0], area[2]),\n", + "}\n", + "lsm = utils.regionalise(lsm, **regionalise_kwargs)\n", + "ds_interpolated = utils.regionalise(ds_interpolated, **regionalise_kwargs)\n", + "model_datasets = {\n", + " model: utils.regionalise(ds, **regionalise_kwargs)\n", + " for model, ds in model_datasets.items()\n", + "}\n", + "\n", + "# Mask\n", "ds_era5 = ds_era5.where(lsm)\n", "ds_interpolated = ds_interpolated.where(lsm)\n", "model_datasets = {\n", diff --git a/notebooks/wp4/extreme_indices_future.ipynb b/notebooks/wp4/extreme_indices_future.ipynb index 1bc921c..13a90b9 100644 --- a/notebooks/wp4/extreme_indices_future.ipynb +++ b/notebooks/wp4/extreme_indices_future.ipynb @@ -41,7 +41,7 @@ "import icclim\n", "import matplotlib.pyplot as plt\n", "import xarray as xr\n", - "from c3s_eqc_automatic_quality_control import diagnostics, download, plot\n", + "from c3s_eqc_automatic_quality_control import diagnostics, download, plot, utils\n", "from xarrayMannKendall import Mann_Kendall_test\n", "\n", "plt.style.use(\"seaborn-v0_8-notebook\")\n", @@ -96,6 +96,9 @@ "# Interpolation method\n", "interpolation_method = \"bilinear\"\n", "\n", + "# Area to show\n", + "area = [72, -22, 27, 45]\n", + "\n", "# Chunks for download\n", "chunks = {\"year\": 1}" ] @@ -182,7 +185,6 @@ "metadata": {}, "outputs": [], "source": [ - "area = [72, -22, 27, 45]\n", "request_lsm = (\n", " \"reanalysis-era5-single-levels\",\n", " {\n", @@ -602,8 +604,21 @@ "metadata": {}, "outputs": [], "source": [ - "# Mask\n", "lsm = download.download_and_transform(*request_lsm)[\"lsm\"].squeeze(drop=True)\n", + "\n", + "# Cutout\n", + "regionalise_kwargs = {\n", + " \"lon_slice\": slice(area[1], area[3]),\n", + " \"lat_slice\": slice(area[0], area[2]),\n", + "}\n", + "lsm = utils.regionalise(lsm, **regionalise_kwargs)\n", + "ds_interpolated = utils.regionalise(ds_interpolated, **regionalise_kwargs)\n", + "model_datasets = {\n", + " model: utils.regionalise(ds, **regionalise_kwargs)\n", + " for model, ds in model_datasets.items()\n", + "}\n", + "\n", + "# Mask\n", "ds_interpolated = ds_interpolated.where(\n", " diagnostics.regrid(lsm, ds_interpolated, method=\"bilinear\")\n", ")\n",