Maesters-of-Clim tempt to help retriving climate data (climate index, reanalysis) from the main-stream climate insitution (like IRI, PSL, NCEI, RDA).
The following support
Institution | Source | DataType | DataName | FetchData |
---|---|---|---|---|
IRI | IRI | forecast | ENSO Probability | Climate_Maester(['enso'], 'iri').forecast(pred_at=date) |
IRI | CPC | forecast | ENSO Probability | Climate_Maester(['enso'], 'cpc').forecast(pred_at=date) |
JAMSTEC | JAMSTEC | forecast | Dipole Mode Index | Climate_Maester(['dmi'], 'jamstec').forecast() |
PSL/NCEI | PSL/NCEI | history | Nina 34 Anomaly | Climate_Maester(['nina34a'], 'ncei').history() |
PSL/NCEI | PSL/NCEI | history | Nina 3 Anomaly | Climate_Maester(['nina3'], 'ncei').history() |
PSL/NCEI | PSL/NCEI | history | Nina 4 Anomaly | Climate_Maester(['nina4'], 'ncei').history() |
PSL | PSL | history | Nina 1 Anomaly | Climate_Maester(['nina1a'], 'psl').history() |
NCEI | NCEI | history | Nina 1.2 Anomaly | Climate_Maester(['nina12a'], 'ncei').history() |
NCEI | NCEI | history | Nina 1.2 SST | Climate_Maester(['nina12'], 'ncei').history() |
NCEI | NCEI | history | Nina 3 SST | Climate_Maester(['nina3'], 'ncei').history() |
NCEI | NCEI | history | Nina 3.4 SST | Climate_Maester(['nina34'], 'ncei').history() |
NCEI | NCEI | history | Nina 4 SST | Climate_Maester(['nina4'], 'ncei').history() |
NCEI | NCEI | history | Indian Ocean Dipole | Climate_Maester(['iod'], 'ncei').history() |
PSL | PSL | history | Southern Oscillation Index | Climate_Maester(['soi'], 'psl').history() |
PSL | PSL | history | Oceanic Nino index | Climate_Maester(['oni'], 'psl').history() |
PSL | PSL | history | Trans Nino index | Climate_Maester(['tni'], 'psl').history() |
PSL | PSL | history | Arctic Oscillation | Climate_Maester(['ao'], 'psl').history() |
PSL | PSL | history | Bivariate ENSO from nina3.4 & soi | Climate_Maester(['censo'], 'psl').history() |
PSL | PSL | history | Western Pacific Index | Climate_Maester(['wp'], 'psl').history() |
PSL | PSL | history | AMO smoothed | Climate_Maester(['amo_sm'], 'psl').history() |
PSL | PSL | history | Dipole Mode Index | Climate_Maester(['dmi'], 'psl').history() |
PSL | PSL | history | Dipole Mode Index West | Climate_Maester(['dmiwest'], 'psl').history() |
PSL | PSL | history | Dipole Mode Index East | Climate_Maester(['dmieast'], 'psl').history() |
PSL | PSL | history | North Atlantic Oscillation | Climate_Maester(['nao'], 'psl').history() |
PSL | PSL | history | North Pacific Index | Climate_Maester(['np'], 'psl').history() |
PSL | PSL | history | Trans Polar Index | Climate_Maester(['tpi'], 'psl').history() |
PSL | PSL | history | Global Average Temperature Anomaly from Station | Climate_Maester(['glbts'], 'psl').history() |
PSL | PSL | history | Global Average Temperature Anomaly from Station and SST | Climate_Maester(['glbtssst'], 'psl').history() |
PSL/NCEI | PSL/NCEI | history | AMO unsmoothed | Climate_Maester(['amo'], 'ncei').history() |
PSL/NCEI | PSL/NCEI | history | Pacific Decadal Oscillation | Climate_Maester(['pdo'], 'ncei').history() |
pip install maesters-clim
from maesters_of_clim import Climate_Maester
from datetime import datetime
# retrive history climate index from nina
c = Climate_Maester(
indexes=['nina34a', 'pdo', 'soi'],
source='psl'
)
df = c.history()
# retrive half-year ENSO forecast probability
c = Climate_Maester(
indexes='enso',
source='iri'
)
iridf = c.forecast(pred_at=datetime(2022, 10, 1))
c = Climate_Maester(
indexes='enso',
source='cpc'
)
cpcdf = c.forecast(pred_at=datetime(2022, 10, 1))
# calculate ENSO event from nina34a/nina3a/soi ...
from maesters_of_clim.analysis import enso_event
df['enso_event'] = enso_event(df, column='nina34a', temp=0.5, months=6)
df[~df['enso_event'].isna()]
The following support is on the way. 🚀🚀🚀
- Data
- ERA5 reanalysis from RDA and AWS
- Basic Computation
- Compiste Analysis