diff --git a/catalog/Red_River_MPI-ESM-LR_future/collection.json b/catalog/Red_River_MPI-ESM-LR_future/collection.json
index f77bfeb2ec4c826c67e270bce40c32afa8bae405..9efdaea1335943be5167b10186ec4954615467b9 100644
--- a/catalog/Red_River_MPI-ESM-LR_future/collection.json
+++ b/catalog/Red_River_MPI-ESM-LR_future/collection.json
@@ -2,7 +2,7 @@
"type": "Collection",
"id": "Red_River_MPI-ESM-LR_future",
"stac_version": "1.0.0",
- "description": "Red_River_MPI-ESM-LR_future",
+ "description": "downscaled estimate of tasmin for fudge experiment: RRtnp1-EDQM-A38aaL01K00_rcp85_r1i1p1",
"links": [
{
"rel": "root",
diff --git a/catalog/Red_River_MPI-ESM-LR_historical/collection.json b/catalog/Red_River_MPI-ESM-LR_historical/collection.json
index 5190362f179e85a865c418a245c38487e2b312de..c3bafb1b79aaea161e76d4e905284a3a4417b53e 100644
--- a/catalog/Red_River_MPI-ESM-LR_historical/collection.json
+++ b/catalog/Red_River_MPI-ESM-LR_historical/collection.json
@@ -2,7 +2,7 @@
"type": "Collection",
"id": "Red_River_MPI-ESM-LR_historical",
"stac_version": "1.0.0",
- "description": "Red_River_MPI-ESM-LR_historical",
+ "description": "downscaled estimate of tasmin for fudge experiment: RRtnp1-CDFt-B30aaL01K00_historical_r1i1p1",
"links": [
{
"rel": "root",
diff --git a/catalog/Red_River_future/collection.json b/catalog/Red_River_future/collection.json
index 89fc1a3fe4eeba6bd07cdbafc2feb309dfb29c0f..eb35533c0dab2f04c89d69ca458c50bb31623873 100644
--- a/catalog/Red_River_future/collection.json
+++ b/catalog/Red_River_future/collection.json
@@ -2,7 +2,7 @@
"type": "Collection",
"id": "Red_River_future",
"stac_version": "1.0.0",
- "description": "Red_River_future",
+ "description": "Auxiliary QC mask tasmin_qcmask for fudge experiment: RRtnp1-BCQM-A28aaL01K00_rcp85_r1i1p1",
"links": [
{
"rel": "root",
diff --git a/catalog/Red_River_historical/collection.json b/catalog/Red_River_historical/collection.json
index 7ee74a9faafad3b1fe741cc4e9fa7e791e3c7dda..f5f815f42c7939105fdfa5711bce256f240108f7 100644
--- a/catalog/Red_River_historical/collection.json
+++ b/catalog/Red_River_historical/collection.json
@@ -2,7 +2,7 @@
"type": "Collection",
"id": "Red_River_historical",
"stac_version": "1.0.0",
- "description": "Red_River_historical",
+ "description": "downscaled estimate of tasmax for fudge experiment: RRtxp1-BCQM-A10aaL01K00_historical_r6i1p1",
"links": [
{
"rel": "root",
diff --git a/workflows/archive/Red_River_MPI-ESM-LR_future_create_collection_from_zarr.ipynb b/workflows/archive/Red_River_MPI-ESM-LR_future_create_collection_from_zarr.ipynb
index 79739bf7aee3ae21ac12650e976a528b22578a86..0353d4a35d0a6c40629d0473bd568c7f09b7bab6 100644
--- a/workflows/archive/Red_River_MPI-ESM-LR_future_create_collection_from_zarr.ipynb
+++ b/workflows/archive/Red_River_MPI-ESM-LR_future_create_collection_from_zarr.ipynb
@@ -36,57 +36,39 @@
"import metpy\n",
"import cartopy.crs as ccrs\n",
"import cfunits\n",
- "import json"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "20b00e88-5a13-46b3-9787-d9ac2d4e7bd6",
- "metadata": {},
- "source": [
- "## Open up NHGF STAC Catalog"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
- "outputs": [],
- "source": [
- "# define folder location where your STAC catalog json file is\n",
- "catalog_path = os.path.join('..', '..', 'catalog')\n",
- "# open catalog\n",
- "catalog = pystac.Catalog.from_file(os.path.join(catalog_path, 'catalog.json'))"
+ "import json\n",
+ "import sys\n",
+ "sys.path.insert(1, '..')\n",
+ "import stac_helpers"
]
},
{
"cell_type": "markdown",
- "id": "996e60ba-13e4-453a-8534-e62ce747f0fa",
+ "id": "5c57d1f0-db77-4c9a-9837-9673b11f9067",
"metadata": {},
"source": [
- "## Collection Metadata Input"
+ "## Collection ID"
]
},
{
"cell_type": "code",
"execution_count": null,
- "id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "id": "113378fe-c9d9-4734-a037-d5d470d15d31",
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection\n",
- "collection_id = 'Red_River_MPI-ESM-LR_future'\n",
- "# description of STAC collection\n",
- "collection_description = 'Red_River_MPI-ESM-LR_future'\n",
- "# license for dataset\n",
- "collection_license = 'CC0-1.0'"
+ "collection_id = 'Red_River_MPI-ESM-LR_future'"
]
},
{
"cell_type": "markdown",
"id": "116b5837-8e85-4ae7-964a-803533ded714",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"source": [
"## Asset Metadata Input"
]
@@ -101,7 +83,7 @@
"outputs": [],
"source": [
"# url to zarr store that you want to create a collection for\n",
- "zarr_url = 's3://mdmf/gdp/Red_River_MPI-ESM-LR_future.zarr/'\n",
+ "zarr_url = f's3://mdmf/gdp/{collection_id}.zarr/'\n",
"\n",
"# define keyword arguments needed for opening the dataset with xarray\n",
"# ref: https://github.com/stac-extensions/xarray-assets\n",
@@ -123,7 +105,7 @@
"outputs": [],
"source": [
"# url to zarr store that you want to create a collection for\n",
- "zarr_url2 = 's3://nhgf-development/workspace/DataConversion/Red_River_MPI-ESM-LR_future.zarr/'\n",
+ "zarr_url2 = f's3://nhgf-development/workspace/DataConversion/{collection_id}.zarr/'\n",
"\n",
"# define keyword arguments needed for opening the dataset with xarray\n",
"# ref: https://github.com/stac-extensions/xarray-assets\n",
@@ -152,27 +134,45 @@
"metadata": {},
"outputs": [],
"source": [
- "# # open and view zarr dataset\n",
- "# fs2 = fsspec.filesystem('s3', anon=True, endpoint_url='https://usgs.osn.mghpcc.org/')\n",
- "# ds = xr.open_dataset(fs2.get_mapper(zarr_url), engine='zarr', \n",
- "# backend_kwargs={'consolidated':True}, chunks={})\n",
- "# ds"
+ "# open and view zarr dataset\n",
+ "fs2 = fsspec.filesystem('s3', anon=True, endpoint_url='https://usgs.osn.mghpcc.org/')\n",
+ "ds = xr.open_dataset(fs2.get_mapper(zarr_url), engine='zarr', \n",
+ " backend_kwargs={'consolidated':True}, chunks={})\n",
+ "ds"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "996e60ba-13e4-453a-8534-e62ce747f0fa",
+ "metadata": {},
+ "source": [
+ "## Collection Metadata Input"
]
},
{
"cell_type": "code",
"execution_count": null,
- "id": "83f0ec9d-02a4-42bd-aee2-4dfdf8b06235",
+ "id": "482d204d-b5b6-40e5-ac42-55b459be1097",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# description of STAC collection\n",
+ "collection_description = ds.attrs['title']\n",
+ "print(f'collection description: {collection_description}')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "977050a7-9c78-4eec-bbaf-bb9da06b3258",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
- "# open and view zarr dataset\n",
- "fs2 = fsspec.filesystem('s3', requester_pays=True)\n",
- "ds = xr.open_dataset(fs2.get_mapper(zarr_url2), engine='zarr', \n",
- " backend_kwargs={'consolidated':True}, chunks={})\n",
- "ds"
+ "# license for dataset\n",
+ "# no license in dataset attrs, but this is a NOAA dataset, so we will treat it as public domain\n",
+ "collection_license = 'CC0-1.0'"
]
},
{
@@ -230,53 +230,6 @@
"crs = ds[list(ds.keys())[0]].metpy.cartopy_crs"
]
},
- {
- "cell_type": "markdown",
- "id": "8fbfecfb-9886-4d06-a34c-6471cb0a6053",
- "metadata": {},
- "source": [
- "## Plot a map"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "4eb4d027-4266-4a0b-8f16-bacfbef06242",
- "metadata": {},
- "outputs": [],
- "source": [
- "# # plot a map of a single variable\n",
- "# var_to_plot = 'SNOW'\n",
- "# da = ds[var_to_plot].sel(time='2014-03-01 00:00').load()\n",
- "# da.hvplot.quadmesh(x='lon', y='lat', rasterize=True,\n",
- "# geo=True, tiles='OSM', alpha=0.7, cmap='turbo')"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "5e057a6c-06fb-4406-823b-e81c58e520e4",
- "metadata": {},
- "source": [
- "## Plot a time series at a specific point\n",
- "This can help you verify a variable's values"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "c7de2681-88c2-4597-857c-8f169c596f8b",
- "metadata": {},
- "outputs": [],
- "source": [
- "# # enter lat, lon of point you want to plot time series for\n",
- "# lat,lon = 39.978322,-105.2772194\n",
- "# time_start = '2013-01-01 00:00'\n",
- "# time_end = '2013-12-31 00:00'\n",
- "# x, y = crs.transform_point(lon, lat, src_crs=ccrs.PlateCarree()) # PlateCaree = Lat,Lon\n",
- "# da = ds[var_to_plot].sel(x=x, y=y, method='nearest').sel(time=slice(time_start,time_end)).load()\n",
- "# da.hvplot(x=dim_names_dict['T'], grid=True)"
- ]
- },
{
"cell_type": "markdown",
"id": "a8c3ed37-8564-400b-a7fb-25bd5e43d21c",
@@ -355,10 +308,25 @@
},
{
"cell_type": "markdown",
- "id": "cfb71202-03df-45b5-ac2f-0dc2ee1ab780",
+ "id": "20b00e88-5a13-46b3-9787-d9ac2d4e7bd6",
+ "metadata": {
+ "tags": []
+ },
+ "source": [
+ "## Open up NHGF STAC Catalog and create a collection"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
"metadata": {},
+ "outputs": [],
"source": [
- "## Create pystac collection"
+ "# define folder location where your STAC catalog json file is\n",
+ "catalog_path = os.path.join('..', '..', 'catalog')\n",
+ "# open catalog\n",
+ "catalog = pystac.Catalog.from_file(os.path.join(catalog_path, 'catalog.json'))"
]
},
{
diff --git a/workflows/archive/Red_River_MPI-ESM-LR_historical_create_collection_from_zarr.ipynb b/workflows/archive/Red_River_MPI-ESM-LR_historical_create_collection_from_zarr.ipynb
index 546542a9061f88965076c5732d1acb972e579b4b..00825081e48c6bc1c0bbc1e4a3958efa60a63a2f 100644
--- a/workflows/archive/Red_River_MPI-ESM-LR_historical_create_collection_from_zarr.ipynb
+++ b/workflows/archive/Red_River_MPI-ESM-LR_historical_create_collection_from_zarr.ipynb
@@ -36,57 +36,39 @@
"import metpy\n",
"import cartopy.crs as ccrs\n",
"import cfunits\n",
- "import json"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "20b00e88-5a13-46b3-9787-d9ac2d4e7bd6",
- "metadata": {},
- "source": [
- "## Open up NHGF STAC Catalog"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
- "outputs": [],
- "source": [
- "# define folder location where your STAC catalog json file is\n",
- "catalog_path = os.path.join('..', '..', 'catalog')\n",
- "# open catalog\n",
- "catalog = pystac.Catalog.from_file(os.path.join(catalog_path, 'catalog.json'))"
+ "import json\n",
+ "import sys\n",
+ "sys.path.insert(1, '..')\n",
+ "import stac_helpers"
]
},
{
"cell_type": "markdown",
- "id": "996e60ba-13e4-453a-8534-e62ce747f0fa",
+ "id": "66df9726-937b-4fef-b750-f0eab0cd50da",
"metadata": {},
"source": [
- "## Collection Metadata Input"
+ "## Collection ID"
]
},
{
"cell_type": "code",
"execution_count": null,
- "id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "id": "765226f7-32c2-4bc2-82b4-e00528cb8daf",
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection\n",
- "collection_id = 'Red_River_MPI-ESM-LR_historical'\n",
- "# description of STAC collection\n",
- "collection_description = 'Red_River_MPI-ESM-LR_historical'\n",
- "# license for dataset\n",
- "collection_license = 'CC0-1.0'"
+ "collection_id = 'Red_River_MPI-ESM-LR_historical'"
]
},
{
"cell_type": "markdown",
"id": "116b5837-8e85-4ae7-964a-803533ded714",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"source": [
"## Asset Metadata Input"
]
@@ -101,7 +83,7 @@
"outputs": [],
"source": [
"# url to zarr store that you want to create a collection for\n",
- "zarr_url = 's3://mdmf/gdp/Red_River_MPI-ESM-LR_historical.zarr/'\n",
+ "zarr_url = f's3://mdmf/gdp/{collection_id}.zarr/'\n",
"\n",
"# define keyword arguments needed for opening the dataset with xarray\n",
"# ref: https://github.com/stac-extensions/xarray-assets\n",
@@ -123,7 +105,7 @@
"outputs": [],
"source": [
"# url to zarr store that you want to create a collection for\n",
- "zarr_url2 = 's3://nhgf-development/workspace/DataConversion/Red_River_MPI-ESM-LR_historical.zarr/'\n",
+ "zarr_url2 = f's3://nhgf-development/workspace/DataConversion/{collection_id}.zarr/'\n",
"\n",
"# define keyword arguments needed for opening the dataset with xarray\n",
"# ref: https://github.com/stac-extensions/xarray-assets\n",
@@ -152,27 +134,45 @@
"metadata": {},
"outputs": [],
"source": [
- "# # open and view zarr dataset\n",
- "# fs2 = fsspec.filesystem('s3', anon=True, endpoint_url='https://usgs.osn.mghpcc.org/')\n",
- "# ds = xr.open_dataset(fs2.get_mapper(zarr_url), engine='zarr', \n",
- "# backend_kwargs={'consolidated':True}, chunks={})\n",
- "# ds"
+ "# open and view zarr dataset\n",
+ "fs2 = fsspec.filesystem('s3', anon=True, endpoint_url='https://usgs.osn.mghpcc.org/')\n",
+ "ds = xr.open_dataset(fs2.get_mapper(zarr_url), engine='zarr', \n",
+ " backend_kwargs={'consolidated':True}, chunks={})\n",
+ "ds"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "996e60ba-13e4-453a-8534-e62ce747f0fa",
+ "metadata": {},
+ "source": [
+ "## Collection Metadata Input"
]
},
{
"cell_type": "code",
"execution_count": null,
- "id": "83f0ec9d-02a4-42bd-aee2-4dfdf8b06235",
+ "id": "482d204d-b5b6-40e5-ac42-55b459be1097",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# description of STAC collection\n",
+ "collection_description = ds.attrs['title']\n",
+ "print(f'collection description: {collection_description}')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "749dbcdb-6ad6-48fe-9938-f1b706aaee8e",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
- "# open and view zarr dataset\n",
- "fs2 = fsspec.filesystem('s3', requester_pays=True)\n",
- "ds = xr.open_dataset(fs2.get_mapper(zarr_url2), engine='zarr', \n",
- " backend_kwargs={'consolidated':True}, chunks={})\n",
- "ds"
+ "# license for dataset\n",
+ "# no license in dataset attrs, but this is a NOAA dataset, so we will treat it as public domain\n",
+ "collection_license = 'CC0-1.0'"
]
},
{
@@ -230,53 +230,6 @@
"crs = ds[list(ds.keys())[0]].metpy.cartopy_crs"
]
},
- {
- "cell_type": "markdown",
- "id": "8fbfecfb-9886-4d06-a34c-6471cb0a6053",
- "metadata": {},
- "source": [
- "## Plot a map"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "4eb4d027-4266-4a0b-8f16-bacfbef06242",
- "metadata": {},
- "outputs": [],
- "source": [
- "# # plot a map of a single variable\n",
- "# var_to_plot = 'SNOW'\n",
- "# da = ds[var_to_plot].sel(time='2014-03-01 00:00').load()\n",
- "# da.hvplot.quadmesh(x='lon', y='lat', rasterize=True,\n",
- "# geo=True, tiles='OSM', alpha=0.7, cmap='turbo')"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "5e057a6c-06fb-4406-823b-e81c58e520e4",
- "metadata": {},
- "source": [
- "## Plot a time series at a specific point\n",
- "This can help you verify a variable's values"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "c7de2681-88c2-4597-857c-8f169c596f8b",
- "metadata": {},
- "outputs": [],
- "source": [
- "# # enter lat, lon of point you want to plot time series for\n",
- "# lat,lon = 39.978322,-105.2772194\n",
- "# time_start = '2013-01-01 00:00'\n",
- "# time_end = '2013-12-31 00:00'\n",
- "# x, y = crs.transform_point(lon, lat, src_crs=ccrs.PlateCarree()) # PlateCaree = Lat,Lon\n",
- "# da = ds[var_to_plot].sel(x=x, y=y, method='nearest').sel(time=slice(time_start,time_end)).load()\n",
- "# da.hvplot(x=dim_names_dict['T'], grid=True)"
- ]
- },
{
"cell_type": "markdown",
"id": "a8c3ed37-8564-400b-a7fb-25bd5e43d21c",
@@ -355,10 +308,25 @@
},
{
"cell_type": "markdown",
- "id": "cfb71202-03df-45b5-ac2f-0dc2ee1ab780",
+ "id": "20b00e88-5a13-46b3-9787-d9ac2d4e7bd6",
+ "metadata": {
+ "tags": []
+ },
+ "source": [
+ "## Open up NHGF STAC Catalog and create a collection"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
"metadata": {},
+ "outputs": [],
"source": [
- "## Create pystac collection"
+ "# define folder location where your STAC catalog json file is\n",
+ "catalog_path = os.path.join('..', '..', 'catalog')\n",
+ "# open catalog\n",
+ "catalog = pystac.Catalog.from_file(os.path.join(catalog_path, 'catalog.json'))"
]
},
{
diff --git a/workflows/archive/Red_River_future_create_collection_from_zarr.ipynb b/workflows/archive/Red_River_future_create_collection_from_zarr.ipynb
index cbc663bf59c7ba3913ad31ea70a049a967c630cb..e75a2459a96cc9ce5d791fc7f15903dc42bee1b7 100644
--- a/workflows/archive/Red_River_future_create_collection_from_zarr.ipynb
+++ b/workflows/archive/Red_River_future_create_collection_from_zarr.ipynb
@@ -36,57 +36,39 @@
"import metpy\n",
"import cartopy.crs as ccrs\n",
"import cfunits\n",
- "import json"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "20b00e88-5a13-46b3-9787-d9ac2d4e7bd6",
- "metadata": {},
- "source": [
- "## Open up NHGF STAC Catalog"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
- "outputs": [],
- "source": [
- "# define folder location where your STAC catalog json file is\n",
- "catalog_path = os.path.join('..', '..', 'catalog')\n",
- "# open catalog\n",
- "catalog = pystac.Catalog.from_file(os.path.join(catalog_path, 'catalog.json'))"
+ "import json\n",
+ "import sys\n",
+ "sys.path.insert(1, '..')\n",
+ "import stac_helpers"
]
},
{
"cell_type": "markdown",
- "id": "996e60ba-13e4-453a-8534-e62ce747f0fa",
+ "id": "e157f566-fd9f-4f90-af46-8e53fd570c12",
"metadata": {},
"source": [
- "## Collection Metadata Input"
+ "## Collection ID"
]
},
{
"cell_type": "code",
"execution_count": null,
- "id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "id": "9512821f-d4e9-4fc8-a87d-152b4b70e862",
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection\n",
- "collection_id = 'Red_River_future'\n",
- "# description of STAC collection\n",
- "collection_description = 'Red_River_future'\n",
- "# license for dataset\n",
- "collection_license = 'CC0-1.0'"
+ "collection_id = 'Red_River_future'"
]
},
{
"cell_type": "markdown",
"id": "116b5837-8e85-4ae7-964a-803533ded714",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"source": [
"## Asset Metadata Input"
]
@@ -101,7 +83,7 @@
"outputs": [],
"source": [
"# url to zarr store that you want to create a collection for\n",
- "zarr_url = 's3://mdmf/gdp/Red_River_future.zarr/'\n",
+ "zarr_url = f's3://mdmf/gdp/{collection_id}.zarr/'\n",
"\n",
"# define keyword arguments needed for opening the dataset with xarray\n",
"# ref: https://github.com/stac-extensions/xarray-assets\n",
@@ -123,7 +105,7 @@
"outputs": [],
"source": [
"# url to zarr store that you want to create a collection for\n",
- "zarr_url2 = 's3://nhgf-development/workspace/DataConversion/Red_River_future.zarr/'\n",
+ "zarr_url2 = f's3://nhgf-development/workspace/DataConversion/{collection_id}.zarr/'\n",
"\n",
"# define keyword arguments needed for opening the dataset with xarray\n",
"# ref: https://github.com/stac-extensions/xarray-assets\n",
@@ -152,27 +134,45 @@
"metadata": {},
"outputs": [],
"source": [
- "# # open and view zarr dataset\n",
- "# fs2 = fsspec.filesystem('s3', anon=True, endpoint_url='https://usgs.osn.mghpcc.org/')\n",
- "# ds = xr.open_dataset(fs2.get_mapper(zarr_url), engine='zarr', \n",
- "# backend_kwargs={'consolidated':True}, chunks={})\n",
- "# ds"
+ "# open and view zarr dataset\n",
+ "fs2 = fsspec.filesystem('s3', anon=True, endpoint_url='https://usgs.osn.mghpcc.org/')\n",
+ "ds = xr.open_dataset(fs2.get_mapper(zarr_url), engine='zarr', \n",
+ " backend_kwargs={'consolidated':True}, chunks={})\n",
+ "ds"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "996e60ba-13e4-453a-8534-e62ce747f0fa",
+ "metadata": {},
+ "source": [
+ "## Collection Metadata Input"
]
},
{
"cell_type": "code",
"execution_count": null,
- "id": "83f0ec9d-02a4-42bd-aee2-4dfdf8b06235",
+ "id": "482d204d-b5b6-40e5-ac42-55b459be1097",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# description of STAC collection\n",
+ "collection_description = ds.attrs['title']\n",
+ "print(f'collection description: {collection_description}')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "5ef08688-2e57-4ba1-9ab4-3bed1214b4b4",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
- "# open and view zarr dataset\n",
- "fs2 = fsspec.filesystem('s3', requester_pays=True)\n",
- "ds = xr.open_dataset(fs2.get_mapper(zarr_url2), engine='zarr', \n",
- " backend_kwargs={'consolidated':True}, chunks={})\n",
- "ds"
+ "# license for dataset\n",
+ "# no license in dataset attrs, but this is a NOAA dataset, so we will treat it as public domain\n",
+ "collection_license = 'CC0-1.0'"
]
},
{
@@ -230,53 +230,6 @@
"crs = ds[list(ds.keys())[0]].metpy.cartopy_crs"
]
},
- {
- "cell_type": "markdown",
- "id": "8fbfecfb-9886-4d06-a34c-6471cb0a6053",
- "metadata": {},
- "source": [
- "## Plot a map"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "4eb4d027-4266-4a0b-8f16-bacfbef06242",
- "metadata": {},
- "outputs": [],
- "source": [
- "# # plot a map of a single variable\n",
- "# var_to_plot = 'SNOW'\n",
- "# da = ds[var_to_plot].sel(time='2014-03-01 00:00').load()\n",
- "# da.hvplot.quadmesh(x='lon', y='lat', rasterize=True,\n",
- "# geo=True, tiles='OSM', alpha=0.7, cmap='turbo')"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "5e057a6c-06fb-4406-823b-e81c58e520e4",
- "metadata": {},
- "source": [
- "## Plot a time series at a specific point\n",
- "This can help you verify a variable's values"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "c7de2681-88c2-4597-857c-8f169c596f8b",
- "metadata": {},
- "outputs": [],
- "source": [
- "# # enter lat, lon of point you want to plot time series for\n",
- "# lat,lon = 39.978322,-105.2772194\n",
- "# time_start = '2013-01-01 00:00'\n",
- "# time_end = '2013-12-31 00:00'\n",
- "# x, y = crs.transform_point(lon, lat, src_crs=ccrs.PlateCarree()) # PlateCaree = Lat,Lon\n",
- "# da = ds[var_to_plot].sel(x=x, y=y, method='nearest').sel(time=slice(time_start,time_end)).load()\n",
- "# da.hvplot(x=dim_names_dict['T'], grid=True)"
- ]
- },
{
"cell_type": "markdown",
"id": "a8c3ed37-8564-400b-a7fb-25bd5e43d21c",
@@ -355,10 +308,25 @@
},
{
"cell_type": "markdown",
- "id": "cfb71202-03df-45b5-ac2f-0dc2ee1ab780",
+ "id": "20b00e88-5a13-46b3-9787-d9ac2d4e7bd6",
+ "metadata": {
+ "tags": []
+ },
+ "source": [
+ "## Open up NHGF STAC Catalog and create a collection"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
"metadata": {},
+ "outputs": [],
"source": [
- "## Create pystac collection"
+ "# define folder location where your STAC catalog json file is\n",
+ "catalog_path = os.path.join('..', '..', 'catalog')\n",
+ "# open catalog\n",
+ "catalog = pystac.Catalog.from_file(os.path.join(catalog_path, 'catalog.json'))"
]
},
{
diff --git a/workflows/archive/Red_River_historical_create_collection_from_zarr.ipynb b/workflows/archive/Red_River_historical_create_collection_from_zarr.ipynb
index 9e862256f0a6a7212b66923b45269c19a3e66fe3..19ca03157ebe6aac5a580c89615e377398d5a42a 100644
--- a/workflows/archive/Red_River_historical_create_collection_from_zarr.ipynb
+++ b/workflows/archive/Red_River_historical_create_collection_from_zarr.ipynb
@@ -36,57 +36,39 @@
"import metpy\n",
"import cartopy.crs as ccrs\n",
"import cfunits\n",
- "import json"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "20b00e88-5a13-46b3-9787-d9ac2d4e7bd6",
- "metadata": {},
- "source": [
- "## Open up NHGF STAC Catalog"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
- "outputs": [],
- "source": [
- "# define folder location where your STAC catalog json file is\n",
- "catalog_path = os.path.join('..', '..', 'catalog')\n",
- "# open catalog\n",
- "catalog = pystac.Catalog.from_file(os.path.join(catalog_path, 'catalog.json'))"
+ "import json\n",
+ "import sys\n",
+ "sys.path.insert(1, '..')\n",
+ "import stac_helpers"
]
},
{
"cell_type": "markdown",
- "id": "996e60ba-13e4-453a-8534-e62ce747f0fa",
+ "id": "277e6724-a7c3-4ad1-ae11-eba53eb76af1",
"metadata": {},
"source": [
- "## Collection Metadata Input"
+ "## Collection ID"
]
},
{
"cell_type": "code",
"execution_count": null,
- "id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "id": "2e75e1c7-0f3a-4d34-88c2-da200a1342a5",
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection\n",
- "collection_id = 'Red_River_historical'\n",
- "# description of STAC collection\n",
- "collection_description = 'Red_River_historical'\n",
- "# license for dataset\n",
- "collection_license = 'CC0-1.0'"
+ "collection_id = 'Red_River_historical'"
]
},
{
"cell_type": "markdown",
"id": "116b5837-8e85-4ae7-964a-803533ded714",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"source": [
"## Asset Metadata Input"
]
@@ -101,7 +83,7 @@
"outputs": [],
"source": [
"# url to zarr store that you want to create a collection for\n",
- "zarr_url = 's3://mdmf/gdp/Red_River_historical.zarr/'\n",
+ "zarr_url = f's3://mdmf/gdp/{collection_id}.zarr/'\n",
"\n",
"# define keyword arguments needed for opening the dataset with xarray\n",
"# ref: https://github.com/stac-extensions/xarray-assets\n",
@@ -123,7 +105,7 @@
"outputs": [],
"source": [
"# url to zarr store that you want to create a collection for\n",
- "zarr_url2 = 's3://nhgf-development/workspace/DataConversion/Red_River_historical.zarr/'\n",
+ "zarr_url2 = f's3://nhgf-development/workspace/DataConversion/{collection_id}.zarr/'\n",
"\n",
"# define keyword arguments needed for opening the dataset with xarray\n",
"# ref: https://github.com/stac-extensions/xarray-assets\n",
@@ -152,27 +134,45 @@
"metadata": {},
"outputs": [],
"source": [
- "# # open and view zarr dataset\n",
- "# fs2 = fsspec.filesystem('s3', anon=True, endpoint_url='https://usgs.osn.mghpcc.org/')\n",
- "# ds = xr.open_dataset(fs2.get_mapper(zarr_url), engine='zarr', \n",
- "# backend_kwargs={'consolidated':True}, chunks={})\n",
- "# ds"
+ "# open and view zarr dataset\n",
+ "fs2 = fsspec.filesystem('s3', anon=True, endpoint_url='https://usgs.osn.mghpcc.org/')\n",
+ "ds = xr.open_dataset(fs2.get_mapper(zarr_url), engine='zarr', \n",
+ " backend_kwargs={'consolidated':True}, chunks={})\n",
+ "ds"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "996e60ba-13e4-453a-8534-e62ce747f0fa",
+ "metadata": {},
+ "source": [
+ "## Collection Metadata Input"
]
},
{
"cell_type": "code",
"execution_count": null,
- "id": "83f0ec9d-02a4-42bd-aee2-4dfdf8b06235",
+ "id": "482d204d-b5b6-40e5-ac42-55b459be1097",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# description of STAC collection\n",
+ "collection_description = ds.attrs['title']\n",
+ "print(f'collection description: {collection_description}')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "dbd16e3c-7a58-4f60-9cb1-7ee31994b6ab",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
- "# open and view zarr dataset\n",
- "fs2 = fsspec.filesystem('s3', requester_pays=True)\n",
- "ds = xr.open_dataset(fs2.get_mapper(zarr_url2), engine='zarr', \n",
- " backend_kwargs={'consolidated':True}, chunks={})\n",
- "ds"
+ "# license for dataset\n",
+ "# no license in dataset attrs, but this is a NOAA dataset, so we will treat it as public domain\n",
+ "collection_license = 'CC0-1.0'"
]
},
{
@@ -230,53 +230,6 @@
"crs = ds[list(ds.keys())[0]].metpy.cartopy_crs"
]
},
- {
- "cell_type": "markdown",
- "id": "8fbfecfb-9886-4d06-a34c-6471cb0a6053",
- "metadata": {},
- "source": [
- "## Plot a map"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "4eb4d027-4266-4a0b-8f16-bacfbef06242",
- "metadata": {},
- "outputs": [],
- "source": [
- "# # plot a map of a single variable\n",
- "# var_to_plot = 'SNOW'\n",
- "# da = ds[var_to_plot].sel(time='2014-03-01 00:00').load()\n",
- "# da.hvplot.quadmesh(x='lon', y='lat', rasterize=True,\n",
- "# geo=True, tiles='OSM', alpha=0.7, cmap='turbo')"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "5e057a6c-06fb-4406-823b-e81c58e520e4",
- "metadata": {},
- "source": [
- "## Plot a time series at a specific point\n",
- "This can help you verify a variable's values"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "c7de2681-88c2-4597-857c-8f169c596f8b",
- "metadata": {},
- "outputs": [],
- "source": [
- "# # enter lat, lon of point you want to plot time series for\n",
- "# lat,lon = 39.978322,-105.2772194\n",
- "# time_start = '2013-01-01 00:00'\n",
- "# time_end = '2013-12-31 00:00'\n",
- "# x, y = crs.transform_point(lon, lat, src_crs=ccrs.PlateCarree()) # PlateCaree = Lat,Lon\n",
- "# da = ds[var_to_plot].sel(x=x, y=y, method='nearest').sel(time=slice(time_start,time_end)).load()\n",
- "# da.hvplot(x=dim_names_dict['T'], grid=True)"
- ]
- },
{
"cell_type": "markdown",
"id": "a8c3ed37-8564-400b-a7fb-25bd5e43d21c",
@@ -355,10 +308,25 @@
},
{
"cell_type": "markdown",
- "id": "cfb71202-03df-45b5-ac2f-0dc2ee1ab780",
+ "id": "20b00e88-5a13-46b3-9787-d9ac2d4e7bd6",
+ "metadata": {
+ "tags": []
+ },
+ "source": [
+ "## Open up NHGF STAC Catalog and create a collection"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
"metadata": {},
+ "outputs": [],
"source": [
- "## Create pystac collection"
+ "# define folder location where your STAC catalog json file is\n",
+ "catalog_path = os.path.join('..', '..', 'catalog')\n",
+ "# open catalog\n",
+ "catalog = pystac.Catalog.from_file(os.path.join(catalog_path, 'catalog.json'))"
]
},
{