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.codespell-exclude
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.codespell-exclude
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<th>CAf</th>
<td>CAf</td>
"SIZ", "Size distribution"
"ALL", "All of the above retrievals (SIZ to FLUX) in one file"
hda = hysplit.combine_dataset([file1,file2], drange=[d1,d2])
print(hda)
metdata = ish_mod.ISH()
df = metdata.add_data(dates, country=None, box=area, resample=False)
"CNA",
d["CAf"] = add_multiple_lazy(d, newkeys, weights=neww)
d["CAf"] = d["CAf"].assign_attrs(
{"units": r"$\mu g m^{-3}$", "name": "CAf", "long_name": "Fine Mode particulate CA"}
"CAf": ["CAf"],
# value is tuple (filename, metdata)
Scrip file path for unstructured grid output
if "CAf" in var_list:
"PRES": "pres_pa_mid",
CMAQ model data including new CAf calculation
# allvars = Series(["TEMP", "Q", "PRES"])
# "p": dset["PRES"][:].compute().values
var_list.append("pres")
if var == "pres": # Insert special versions.
"SIZ",
df.loc[con, "variable"] = "Caf"
df.loc[con, "variable"] = "Laf"
["AZ", "CO", "ID", "KS", "MT", "NE", "NV", "NM", "ND", "SD", "UT", "WY"], dtype="|S12"
r = array(["AZ", "CO", "ID", "KS", "MT", "NE", "NV", "NM", "ND", "SD", "UT", "WY"])
ser = array(["Southeast" for i in se])
region = concatenate([ser, ner, ncr, scr, rr, pr])
"North Dakota": "ND",
fo = self.fs.open(f)
out = xr.open_dataset(fo, engine="h5netcdf")
"""Read SNPP OMPS Nadir Mapper Total Column Ozone L2 data from NASA GES DISC
a.prod = "SIZ"
df = aeronet.add_data(dates, inv_type="ALM15", product="SIZ")
df = aeronet.add_data(dates, inv_type="HYB15", product="SIZ")
# https://aeronet.gsfc.nasa.gov/cgi-bin/print_web_data_inv_v3?site=Cart_Site&year=2002&month=6&day=1&year2=2003&month2=6&day2=14&product=SIZ&AVG=20&ALM15=1&if_no_html=1
"RIN", "Refractive indices (real and imaginary)"
"RIN",