EPT-2 Family
Jua's flagship state-of-the-art weather model, released in April 2025. EPT-2 outperforms leading public AI weather models including Microsoft Aurora, DeepMind's GraphCast, ECMWF's AIFS, and our previous EPT-1.5 model. For more information on our EPT-2 family of models, take a look at our EPT-2 Technical Report.
EPT-2 Early offers dissemination 2.5 hours earlier than EPT-2 to anticipate market movements.
EPT-2 RR is our rapid refresh forecast model, with our fastest dissemination times and 24 updates per day.
EPT-2e is our 30 member, perturbation-based ensemble model of EPT-2 for probabilistic forecasting. EPT-2e significantly surpasses the HRES ensemble mean—long considered the gold standard for medium- to long-range forecasting—while operating. Ensemble statistics are also available for EPT-2e through the platform, API and SDK.
Technical Specifications
Coordinates
Name
Description
Units
time
Initialization time of forecast at UTC
Absolute time (UTC)
prediction_timedelta
Lead time relative to initialization time
Timedelta
latitude
Latitudinal coordinate
Degrees true, range [90, -90)
longitude
Longitudinal coordinate
Degrees true, range [-180, 180)
Available Weather Parameters
EPT-2 uses standardized variable naming conventions. For full details on the naming structure, see Weather Variable Naming.
2t
air_temperature_at_height_level_2m
Air temperature at 2m
Kelvin
2d
dew_point_temperature_at_height_level_2m
Dew point temperature at 2m
Kelvin
r
relative_humidity_at_height_level_2m
Relative humidity at 2m
%
10si
wind_speed_at_height_level_10m
Horizontal wind speed at 10m
m s⁻¹
10wdir
wind_direction_at_height_level_10m
Horizontal wind direction at 10m
Degrees true
100si
wind_speed_at_height_level_100m
Horizontal wind speed at 100m
m s⁻¹
100wdir
wind_direction_at_height_level_100m
Horizontal wind direction at 100m
Degrees true
msl
air_pressure_at_mean_sea_level
Mean Sea-level Pressure
Pa
lcc
low_type_cloud_area_fraction
Low Cloud Cover
%
mcc
medium_type_cloud_area_fraction
Medium Cloud Cove
%
hcc
high_type_cloud_area_fraction
High Cloud Cover
%
tp
precipitation_amount_sum_1h
Total Precipitation
mm m⁻²
ssrd
surface_downwelling_shortwave_flux_sum_1h
Surface solar downward irradiance
J m⁻²
fdir
surface_direct_downwelling_shortwave_flux_sum_1h
Direct solar radiation at the surface
J m⁻²
z_500
wind_direction_at_height_level_100m
Geopotential
m² s⁻²
Note: For information on the previous naming convention used in EPT-1.5, see Legacy Naming.
Additional Variables on request:
tcwv
atmosphere_mass_content_of_water_vapor
Total column vertically-integrated water vapour
kg m⁻²
t
air_temperature_at_pressure_level
Temperature at a specified pressure level
K
u
eastward_wind_at_pressure_level
U component of wind
m s⁻¹
v
northward_wind_at_pressure_level
V component of wind
m s⁻¹
q
specific_humidity_at_pressure_level
The mass of water vapour per kilogram of moist air at a pressure level
kg
z
geopotential_at_pressure_level
The gravitational potential energy of a unit mass
m² s⁻²
Pressure levels: 5000, 10000, 15000, 20000, 25000, 30000, 40000, 50000, 60000, 70000, 85000, 92500, 100000
Hindcasts Details
Full hindcast dataset available for performance analysis and evaluation
Hindcasts are global with a grid of 2160x4320
Hindcasts are from
2023-01-01
to2024-12-28
Hindcasts are run 4 times a day at 00, 06, 12, 18
Hindcasts are chunked as
(time: 1, prediction_timedelta: 144, lat: 120, lon: 240)
Each chunk is 10 GB
Forecasts are hourly for the first 10 days and 6 hourly from days 10 to 20
Hindcasts are not available for EPT-2e
For migration information from EPT-1.5 to EPT-2, including parameter naming changes, see EPT-1.5 to EPT-2 Migration Guide.
Performance Benchmarks
EPT-2 consistently outperforms other leading weather models, including:
Microsoft Aurora
DeepMind's GraphCast
ECMWF's AIFS
Our previous EPT-1.5 model
Dissemination times
EPT-2 also features an Early version disseminated 2.5 hours earlier.
For detailed dissemination times of EPT-2 and EPT-2 Early, please refer to the Dissemination Times page.
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