Python interfaces for observational data surrounding named storm events
Project description
StormEvents
stormevents
provides Python interfaces for observational data surrounding named storm events.
pip install stormevents
Full documentation can be found at https://stormevents.readthedocs.io
Usage
storm interface
You can instantiate a new StormEvent
object from its identifiers:
from stormevents import StormEvent
# from NHC storm name and year
StormEvent('florence', 2018)
# from NHC storm code
StormEvent.from_nhc_code('EP172016')
# from USGS flood event ID
StormEvent.from_usgs_id(310)
StormEvent('FLORENCE', 2018)
StormEvent('PAINE', 2016)
StormEvent('HENRI', 2021)
storm time interval
To constrain the time interval, do the following:
from stormevents import StormEvent
from datetime import datetime, timedelta
# constrain to an absolute datetime range
paine2016 = StormEvent('paine', 2016, start_date='2016-09-18', end_date=datetime(2016, 9, 19, 12))
# constrain to relative times (compared to storm start and end times provided by the NHC)
florence2018 = StormEvent('florence', 2018, start_date=timedelta(days=2)) # <- start 2 days after NHC start time
henri2021 = StormEvent(
'henri',
2021,
start_date=timedelta(days=-3), # start 3 days before NHC end time
end_date=timedelta(days=-2), # <- end 2 days before NHC end time
)
ida2021 = StormEvent('ida', 2021, end_date=timedelta(days=2)) # <- end 2 days after NHC start time
StormEvent('PAINE', 2016, end_date='2016-09-19 12:00:00')
StormEvent('FLORENCE', 2018, start_date='2018-09-01 06:00:00')
StormEvent('HENRI', 2021)
StormEvent('IDA', 2021)
storm data
You can then retrieve data for this storm:
from stormevents import StormEvent
florence2018 = StormEvent('florence', 2018)
# track dataset from the NHC
florence2018.track()
# high-water mark data from the USGS
florence2018.high_water_marks
# water level products from NOAA CO-OPS tidal buoys
florence2018.tidal_data_within_isotach(isotach=34, start_date='20180913230000', end_date='20180914')
VortexTrack('AL062018', Timestamp('2018-08-29 06:00:00'), Timestamp('2018-09-22 18:00:00'), ATCF_FileDeck.a, ATCF_Mode.historical, None, None)
latitude ... siteZone
hwm_id ...
33496 37.298440 ... NaN
33502 35.342089 ... NaN
33503 35.378963 ... NaN
33505 35.216282 ... NaN
33508 35.199859 ... NaN
... ... ... ...
34191 33.724722 ... NaN
34235 34.936308 ...
34840 34.145930 ... NaN
34871 35.424707 ... NaN
34876 35.301135 ... NaN
[509 rows x 51 columns]
Dimensions: (t: 11, nos_id: 10)
Coordinates:
* t (t) datetime64[ns] 2018-09-13T23:00:00 ... 2018-09-14
* nos_id (nos_id) int64 8639348 8651370 8652587 ... 8661070 8662245 8665530
nws_id (nos_id) <U5 'MNPV2' 'DUKN7' 'ORIN7' ... 'MROS1' 'NITS1' 'CHTS1'
x (nos_id) float64 -76.31 -75.75 -75.56 ... -78.94 -79.19 -79.94
y (nos_id) float64 36.78 36.19 35.78 35.22 ... 33.66 33.34 32.78
Data variables:
v (nos_id, t) float32 7.271 7.274 7.27 7.27 ... 1.549 1.587 1.624
s (nos_id, t) float32 0.005 0.004 0.005 0.004 ... 0.005 0.007 0.006
f (nos_id, t) object '0,0,0,0' '0,0,0,0' ... '0,0,0,0' '0,0,0,0'
q (nos_id, t) object 'v' 'v' 'v' 'v' 'v' 'v' ... 'v' 'v' 'v' 'v' 'v'
By default, these functions operate within the time interval defined by the NHC.
storm data from the National Hurricane Center (NHC)
list storm events defined by the NHC
from stormevents.nhc import nhc_storms
nhc_storms = nhc_storms()
name class ... start_date end_date
nhc_code ...
AL021851 UNNAMED HU ... 1851-07-05 12:00:00 1851-07-05 12:00:00
AL031851 UNNAMED TS ... 1851-07-10 12:00:00 1851-07-10 12:00:00
AL041851 UNNAMED HU ... 1851-08-16 00:00:00 1851-08-27 18:00:00
AL051851 UNNAMED TS ... 1851-09-13 00:00:00 1851-09-16 18:00:00
AL061851 UNNAMED TS ... 1851-10-16 00:00:00 1851-10-19 18:00:00
... ... ... ... ... ...
EP922021 INVEST DB ... 2021-06-05 06:00:00 NaT
AL952021 INVEST DB ... 2021-10-28 12:00:00 NaT
AL962021 INVEST EX ... 2021-11-07 12:00:00 NaT
EP712022 GENESIS001 DB ... 2022-01-20 12:00:00 NaT
EP902022 INVEST LO ... 2022-01-20 12:00:00 NaT
[2729 rows x 8 columns]
retrieve storm tracks provided by the NHC
from stormevents.nhc import VortexTrack
from stormevents.nhc.atcf import ATCF_FileDeck
# retrieve vortex data from the Internet from its ID
vortex = VortexTrack('AL112017')
# you can specify the file deck with `file_deck`
vortex = VortexTrack('AL112017', file_deck=ATCF_FileDeck.b)
# you can also use the storm name and year in the lookup
vortex = VortexTrack('irma2017')
# write to a file in the ADCIRC `fort.22` format
vortex.write('fort.22')
# read vortex data from an existing ATCF track file (`*.trk`)
vortex = VortexTrack.from_atcf_file('atcf.trk')
# read vortex data from an existing file in the ADCIRC `fort.22` format
vortex = VortexTrack.from_fort22('fort.22')
high water mark (HWM) surveys from the United States Geological Survey (USGS)
list storm flood events that have HWM surveys
from stormevents.usgs import usgs_highwatermark_storms
hwm_storms = usgs_highwatermark_storms()
year usgs_name nhc_name nhc_code
usgs_id
7 2013 FEMA 2013 exercise None None
8 2013 Wilma None None
18 2012 Isaac Aug 2012 ISAAC AL092012
19 2005 Rita RITA AL182005
23 2011 Irene IRENE AL092011
... ... ... ... ...
303 2020 2020 TS Marco - Hurricane Laura MARCO AL142020
304 2020 2020 Hurricane Sally SALLY AL192020
305 2020 2020 Hurricane Delta DELTA AL262020
310 2021 2021 Tropical Cyclone Henri HENRI AL082021
312 2021 2021 Tropical Cyclone Ida IDA AL092021
[24 rows x 4 columns]
retrieve HWM data for a specific storm
from stormevents.usgs import StormHighWaterMarks
hwm_florence2018 = StormHighWaterMarks('florence', 2018)
hwm_florence2018.data
hwm_florence2018.data.columns
latitude ... siteZone
hwm_id ...
33496 37.298440 ... NaN
33502 35.342089 ... NaN
33503 35.378963 ... NaN
33505 35.216282 ... NaN
33508 35.199859 ... NaN
... ... ... ...
34191 33.724722 ... NaN
34235 34.936308 ...
34840 34.145930 ... NaN
34871 35.424707 ... NaN
34876 35.301135 ... NaN
[509 rows x 51 columns]
Index(['latitude', 'longitude', 'eventName', 'hwmTypeName', 'hwmQualityName',
'verticalDatumName', 'verticalMethodName', 'approvalMember',
'markerName', 'horizontalMethodName', 'horizontalDatumName',
'flagMemberName', 'surveyMemberName', 'site_no', 'siteDescription',
'sitePriorityName', 'networkNames', 'stateName', 'countyName',
'sitePermHousing', 'site_latitude', 'site_longitude', 'waterbody',
'site_id', 'event_id', 'hwm_type_id', 'hwm_quality_id',
'hwm_locationdescription', 'latitude_dd', 'longitude_dd', 'survey_date',
'elev_ft', 'vdatum_id', 'vcollect_method_id', 'bank', 'marker_id',
'hcollect_method_id', 'hwm_environment', 'flag_date', 'stillwater',
'hdatum_id', 'flag_member_id', 'survey_member_id', 'uncertainty',
'hwm_uncertainty', 'hwm_label', 'files', 'approval_id',
'height_above_gnd', 'hwm_notes', 'siteZone'],
dtype='object')
tidal station data from the Center for Operational Oceanographic Products and Services (CO-OPS)
list CO-OPS tidal stations
from stormevents.coops import coops_stations
stations = coops_stations()
nws_id x y name state removed
nos_id
1600012 46125 122.6250 37.750000 QREB buoy NaT
1611400 NWWH1 -159.3750 21.953125 Nawiliwili HI NaT
1612340 OOUH1 -157.8750 21.312500 Honolulu HI NaT
1612480 MOKH1 -157.7500 21.437500 Mokuoloe HI NaT
1615680 KLIH1 -156.5000 20.890625 Kahului, Kahului Harbor HI NaT
... ... ... ... ... ...
9759394 MGZP4 -67.1875 18.218750 Mayaguez PR NaT
9759938 MISP4 -67.9375 18.093750 Mona Island NaT
9761115 BARA9 -61.8125 17.593750 Barbuda NaT
9999530 FRCB6 -64.6875 32.375000 Bermuda, Ferry Reach Channel NaT
9999531 -93.3125 29.765625 Calcasieu Test Station LA NaT
[363 rows x 6 columns]
list CO-OPS tidal stations within a region
from shapely.geometry import Polygon
from stormevents.coops import coops_stations_within_region
polygon = Polygon(...)
stations = coops_stations_within_region(region=polygon)
retrieve CO-OPS tidal data within a region
from datetime import datetime, timedelta
from shapely.geometry import MultiPolygon
from stormevents.coops import coops_data_within_region
polygon = MultiPolygon(...)
coops_data_within_region(region=polygon, start_date=datetime.now() - timedelta(days=2), end_date=datetime.now())
Related Projects
searvey
- https://github.com/pmav99/searveypyStorms
- https://github.com/brey/pyStormstropycal
- https://tropycal.github.io/tropycal/index.htmlpyoos
- https://github.com/ioos/pyooscsdllib
- https://github.com/noaa-ocs-modeling/csdllibpyPoseidon
- https://github.com/ec-jrc/pyPoseidonThalassa
- https://github.com/ec-jrc/Thalassaadcircpy
- https://github.com/zacharyburnettNOAA/adcircpy
Acknowledgements
This code was initially written by @jreniel
for adcircpy
. Additionally, methodology for retrieving USGS high water marks data and CO-OPS tidal station data came
from @moghimis and @Sergey.Vinogradov
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