168 lines
5.8 KiB
Python
168 lines
5.8 KiB
Python
#%% Read and Process NWS Alerts
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# Created on: 2023-01-17
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# Import Modules
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import os
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import geopandas as gp
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import pandas as pd
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import numpy as np
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import xarray as xr
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import nwswx
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import requests
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from shapely.geometry import Polygon
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import shapely.wkt
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#%% Setup NWS ID
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nws = nwswx.WxAPI('api@alexanderrey.ca')
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#%% Read NWS Alerts
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# All alerts
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# alertsIN = nws.alerts(return_format=nwswx.formats.JSONLD)
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# Active alerts
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alertsIN = nws.active_alerts(return_format=nwswx.formats.JSONLD)
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nws_alerts = alertsIN['@graph']
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# If more than one page of alerts, loop through an append
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while 'pagination' in alertsIN:
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# Get the next page of alerts
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result = requests.get(alertsIN['pagination']['next'])
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# Convert to JSON
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alertsIN = result.json()
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nws_alerts.extend(alertsIN['features'])
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print('AWS Alerts: ', len(nws_alerts))
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#%% Create NWS Alerts DataFrame
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nws_alert_df = pd.DataFrame.from_records(nws_alerts)
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#%% Read in NWS Polygon shapefiles as GeoDataFrame
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z_shp = gp.read_file("C:/Users/arey/Downloads/z_13se22/z_13se22.shp")
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fz_shp = gp.read_file("C:/Users/arey/Downloads/fz13se22/fz13se22.shp")
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oz_shp = gp.read_file("C:/Users/arey/Downloads/oz22mr22/oz22mr22.shp")
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mz_shp = gp.read_file("C:/Users/arey/Downloads/mz13se22/mz13se22.shp")
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w_shp = gp.read_file("C:/Users/arey/Downloads/w_22mr22/w_22mr22.shp")
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# ba_shp = gp.read_file("C:/Users/arey/Downloads/ba12my15/ba12my15.shp")
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# hs_shp = gp.read_file("C:/Users/arey/Downloads/hs08mr23/hs08mr23.shp")
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# s_shp = gp.read_file("C:/Users/arey/Downloads/s_22mr22/s_22mr22.shp")
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#%% Match NWS Alerts to NWS Polygons
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# Create empty list
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nws_alert_polygons = []
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nws_alert_data = []
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nws_alert_debug = []
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# Loop through each NWS Alert and match to NWS Polygon using UGC
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for i in range(len(nws_alert_df)):
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# If alert contains geometry as a string
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if type(nws_alert_df['geometry'][i]) == str:
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nws_alert_polygons.append(shapely.wkt.loads(nws_alert_df['geometry'][i]))
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nws_alert_data.append(nws_alert_df.iloc[i, :])
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nws_alert_debug.append(i)
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# Geometry Array
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elif type(nws_alert_df['geometry'][i]) == gp.array.GeometryArray:
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nws_alert_polygons.append(nws_alert_df['geometry'][i][0])
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nws_alert_data.append(nws_alert_df.iloc[i, :])
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nws_alert_debug.append(i)
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else:
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# Get the UGC code for the alert
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UGCs = nws_alert_df['geocode'][i]['UGC']
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# Loop through each UGC code and find matching polygon
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for ugc in UGCs:
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# Zone based warning
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if (ugc[2] == 'Z') & (ugc[0:2] in z_shp['STATE'].unique()):
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alert_poly = z_shp[(z_shp['STATE'] == ugc[0:2]) & (z_shp['ZONE'] == ugc[3:6])].geometry
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# Fire Weather Zone based warning
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elif (ugc[2] == 'C') & (ugc[0:2] in z_shp['STATE'].unique()):
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alert_poly = fz_shp[(fz_shp['STATE'] == ugc[0:2]) & (fz_shp['ZONE'] == ugc[3:6])].geometry
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# Marine Zone based warning
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elif ugc in mz_shp['ID'].unique():
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alert_poly = mz_shp[mz_shp['ID'] == ugc].geometry
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# Offshore Zone based warning
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elif ugc in oz_shp['ID'].unique():
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alert_poly = oz_shp[oz_shp['ID'] == ugc].geometry
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# elif ugc[0] == 'W':
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# nws_alert_df['geometry'][i] = w_shp[w_shp['UGC'] == ugc].geometry.values
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else:
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print('No polygon found for UGC: ', ugc)
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print('Alert: ', nws_alert_df['headline'][i])
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continue
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# If no matches found
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if len(alert_poly) == 0:
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print('No polygon found for UGC: ', ugc)
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print('Alert: ', nws_alert_df['headline'][i])
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continue
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# Append polygon to list
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nws_alert_polygons.append(alert_poly.values[0])
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nws_alert_data.append(nws_alert_df.iloc[i, :])
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nws_alert_debug.append(i)
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#%% Create GeoDataFrame of alert polygons
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nws_alert_gdf = gp.GeoDataFrame(nws_alert_data, geometry=nws_alert_polygons)
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nws_alert_gdf.reset_index(inplace=True)
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#%% Create grid of points
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xs = np.arange(-127, -65, 0.075)
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ys = np.arange(24, 50, 0.075)
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lons, lats = np.meshgrid(xs, ys)
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# Create GeoSeries of Points
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gridPointsSeries = gp.GeoSeries.from_xy(lons.flatten(), lats.flatten())
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#%% Loop through each NWS Alert and find points within polygon
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alertData_1D = ['' for i in range(len(gridPointsSeries))]
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# Loop through NWS Alerts
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for alertIDX in nws_alert_gdf.index:
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alertString = ''
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# Find h3 index for point
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# Identify which points are within an alert polygon
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alertPoints = np.where(nws_alert_gdf.loc[alertIDX, 'geometry'].contains(gridPointsSeries))[0]
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# Loop through points and add alert data
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for alertPoint in alertPoints:
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# Get existing alert data and add new alert
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alertString = alertData_1D[alertPoint]
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alertString = alertString + '[' + nws_alert_gdf.loc[alertIDX, 'headline'] + \
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nws_alert_gdf.loc[alertIDX, 'description'] + \
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nws_alert_gdf.loc[alertIDX, 'areaDesc'] + \
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nws_alert_gdf.loc[alertIDX, 'onset'] + \
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nws_alert_gdf.loc[alertIDX, 'expires'] + \
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nws_alert_gdf.loc[alertIDX, 'severity'] + \
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nws_alert_gdf.loc[alertIDX, '@id'] + ']'
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alertData_1D[alertPoint] = alertString
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print(alertIDX)
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#%% Create xarray of alert data
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# Convert list to numpy
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list_alerts_1d_np = np.array(alertData_1D)
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# Reshape back to 2d array
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list_alerts_2d_np = list_alerts_1d_np.reshape(lons.shape)
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# Convert to xarray
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grid_alerts_xr = xr.DataArray(data=list_alerts_2d_np,
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dims=["x", "y"],
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coords={"lon": (("x", "y"), lons),
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"lat": (("x", "y"), lats)},
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)
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# Save as netcdf
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grid_alerts_xr.to_netcdf('grid_alerts_contains3.nc')
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