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57 lines
1.3 KiB
Python
57 lines
1.3 KiB
Python
"""get_ww3.py
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Download records from WaveWatch III (WW3) global wave model.
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D. Howe
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2019-07-31
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"""
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import netCDF4
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import pandas as pd
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import xarray as xr
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from tqdm import tqdm
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# Set coordinates
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lon = 136.62
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lat = -36.07
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# Set product code
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product_code = 'ww3.aus_4m'
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# Select output variables
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var_names = ['hs', 'dp', 'fp']
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# Set time period
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start_date = '1980-01'
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end_date = '1980-12'
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url = ('http://data-cbr.csiro.au/thredds/dodsC/catch_all/'
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'CMAR_CAWCR-Wave_archive/CAWCR_Wave_Hindcast_aggregate/gridded/')
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# Generate list of dates
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t0 = pd.to_datetime(start_date)
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t1 = pd.to_datetime(end_date) + pd.DateOffset(months=1)
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dates = pd.date_range(t0, t1, freq='M')
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# Create output dataframe
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master = pd.DataFrame()
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for date in tqdm(dates):
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# Get date string for current month
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date_str = date.strftime('%Y%m')
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# Open dataset
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ds = xr.open_dataset(url + f'{product_code}.{date_str}.nc')
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# Extract variables from dataset
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ds = ds.sel(longitude=lon, latitude=lat, method='nearest')
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df = ds[var_names].to_dataframe()
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# Add to output dataframe
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master = master.append(df)
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# Get lat and lon bearings
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ew = 'E' if lon > 0 else 'W'
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ns = 'N' if lat > 0 else 'S'
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# Export to csv
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csv_name = f'{product_code}_{abs(lon)}{ew}_{abs(lat)}{ns}.csv'
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master.to_csv(csv_name)
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