Siphon - A collection of Python utilities for retrieving data from Unidata data technologies.
I am currently trying to read Radar Level III storm track information from a THREDDS server using Siphon. One of the data variables is text, the second is a Structure. Is there anything I can do with that second variable? Are there any documentation online regarding these files?
``` from siphon.catalog import TDSCatalog
from siphon.radarserver import RadarServer
from siphon.cdmr import Dataset
from datetime import datetime, timedelta
cat = TDSCatalog("http://thredds.ucar.edu/thredds/radarServer/catalog.xml")
url = cat.catalog_refs['NEXRAD Level III Radar from IDD'].href
rs = RadarServer(url)
query_latest = rs.query()
now = datetime.utcnow()
query_latest.lonlat_box(292.9375, 235.0625, 25.0625, 52.9375).time(now).variables('NST')
query_latest_cat = rs.get_catalog(query_latest)
data_available = list(query_latest_cat.datasets.values())
if len(data_available) > 0:
print (data_available[0].access_urls['CdmRemote'])
data_from_thredds = Dataset(data_available[0].access_urls['CdmRemote'])
else:
print ("Empty query")
print (data_from_thredds)```
from metpy.io import Level3File
from siphon.catalog import TDSCatalog
from siphon.radarserver import RadarServer
from datetime import datetime, timedelta
cat = TDSCatalog("http://thredds.ucar.edu/thredds/radarServer/catalog.xml")
url = cat.catalog_refs['NEXRAD Level III Radar from IDD'].href
rs = RadarServer(url)
query_latest = rs.query()
now = datetime.utcnow()
query_latest.stations('GRR').time(now).variables('NST')
query_latest_cat = rs.get_catalog(query_latest)
data_available = list(query_latest_cat.datasets.values())
f = Level3File(data_available[0].remote_open())f.sym_block[0] should give you a collection of what's in the file, in order.
Hi sirs ,
I am always here to ask some questions.
but this time the problem is how can i access data of the future time that gfs forecast model predicts..
i know this data is there but i can not find it ,i need geoheight, temp, press , u-wind.v-wind properties in isobaric layers...
i am here https://thredds.ucar.edu/thredds/catalog/catalog.html
but i can not find future data 3 hourly ...
for example i need forecast of 3h or 6h after 00:00 in october 30 2020.last night
thanks
date = datetime(2021, 1, 22, 0)
station = 'INM00042369'
Station latitude: 60.13
Station longitude: -1.18
Station elevation: 82.0When I run:
WyomingUpperAir.request_data(datetime(2021, 1, 5, 12), '03005')the data also have elevation of 82. If 82 isn't correct, that's outside our control.
height column?
INM00042369 is from 6 January 2021--that's why you don't get any data.
Index(['lvltyp1', 'lvltyp2', 'etime', 'pressure', 'pflag', 'height', 'zflag',
'temperature', 'tflag', 'relative_humidity', 'direction', 'speed',
'date', 'u_wind', 'v_wind', 'dewpoint'],
dtype='object')
0 925.0
1 850.0
2 700.0
3 NaN
4 NaN
5 NaN
6 NaN
7 NaN
8 NaN
9 NaN
10 NaN
11 NaN
12 NaN
13 NaN
14 NaN
Name: pressure, dtype: float64
{'etime': 'second', 'pressure': 'hPa', 'height': 'meter', 'temperature': 'degC', 'dewpoint': 'degC', 'direction': 'degrees', 'speed': 'meter / second', 'u_wind': 'meter / second', 'v_wind': 'meter / second'}
hPa
[nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan] degree_Celsius
[nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan] degree_Celsius
[0.4 2.4 4.1 -0.0 0.4 0.7 3.4 3.3 3.5 1.7 6.2 8.7 4.7 5.4 9.5] meter / second
[344.05460409907715 294.6235647861636 335.2656974709475 0.0 349.2157021324374 315.0 305.2175929681927 324.9262455066517 340.15930191603167 350.059426966887 329.91031376122334 315.0 315.0 315.0 315.0] degree
Traceback (most recent call last):
File "igra_sounds.py", line 102, in <module>
lcl_pressure, lcl_temperature = mpcalc.lcl(p[0], T[0], Td[0])
File "/usr/local/lib/python3.8/dist-packages/metpy/xarray.py", line 677, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/metpy/units.py", line 320, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/metpy/calc/thermo.py", line 357, in lcl
lcl_p = so.fixed_point(_lcl_iter, pressure.m, args=(pressure.m, w, temperature),
File "/usr/local/lib/python3.8/dist-packages/scipy-1.5.2-py3.8-linux-x86_64.egg/scipy/optimize/minpack.py", line 937, in fixed_point
return _fixed_point_helper(func, x0, args, xtol, maxiter, use_accel)
File "/usr/local/lib/python3.8/dist-packages/scipy-1.5.2-py3.8-linux-x86_64.egg/scipy/optimize/minpack.py", line 891, in _fixed_point_helper
raise RuntimeError(msg)
RuntimeError: Failed to converge after 50 iterations, value is nan
-9999), which get translated to nans. Siphon's not doing anything wrong in this case, that's an issue with the underlying data, nothing we can do about. If you encounter any additional data oddities in the future, my recommendation would be to first try to download the data manually and see if what Siphon is giving you matches up with what's in the raw data file.
url = "https://rda.ucar.edu/thredds/dodsC/files/g/ds084.1/2020/20200101/gfs.0p25.2020010100.f000.grib2"
ds = xr.open_dataset(url, backend_kwargs={"auth": ("USER@DOMAIN.COM", "PWD")})
