From 2bf7ce680dc6eded5692d384ce6e3655a0da3577 Mon Sep 17 00:00:00 2001
From: Dan Howe <d.howe@wrl.unsw.edu.au>
Date: Thu, 1 Aug 2019 09:36:04 +1000
Subject: [PATCH] Add ww3

---
 ww3/get_ww3.py | 54 ++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 54 insertions(+)
 create mode 100644 ww3/get_ww3.py

diff --git a/ww3/get_ww3.py b/ww3/get_ww3.py
new file mode 100644
index 0000000..13eafea
--- /dev/null
+++ b/ww3/get_ww3.py
@@ -0,0 +1,54 @@
+"""get_ww3.py
+Download records from WaveWatch III (WW3) global wave model.
+D. Howe
+2019-07-31
+"""
+import netCDF4
+import pandas as pd
+import xarray as xr
+from tqdm import tqdm
+
+# Set coordinates
+lon = 136.62
+lat = -36.07
+
+# Set product code
+product_code = 'ww3.aus_4m'
+
+# Select output variables
+var_names = ['hs', 'dp', 'fp']
+
+# Set time period
+start_date = '1980-01-01'
+end_date = '2019-01-01'
+
+url = ('http://data-cbr.csiro.au/thredds/dodsC/catch_all/'
+       'CMAR_CAWCR-Wave_archive/CAWCR_Wave_Hindcast_aggregate/gridded/')
+
+# Generate list of dates
+dates = pd.date_range(start_date, end_date, freq='M')
+
+# Create output dataframe
+master = pd.DataFrame()
+
+for date in tqdm(dates):
+    # Get date string for current month
+    date_str = date.strftime('%Y%m')
+
+    # Open dataset
+    ds = xr.open_dataset(url + f'{product_code}.{date_str}.nc')
+
+    # Extract variables from dataset
+    ds = ds.sel(longitude=lon, latitude=lat, method='nearest')
+    df = ds[var_names].to_dataframe()
+
+    # Add to output dataframe
+    master = master.append(df)
+
+# Get lat and lon bearings
+ew = 'E' if lon > 0 else 'W'
+ns = 'N' if lat > 0 else 'S'
+
+# Export to csv
+csv_name = f'{product_code}_{abs(lon)}{ew}_{abs(lat)}{ns}.csv'
+master.to_csv(csv_name)