earth2studio.models: Models

earth2studio.models.px: Prognostic

Prognostic models are a class of models that perform time-integration. Thus are typically used to generate forecast predictions.

Warning

Pre-trained prognostic models provided in Earth2Studio may be provided under different licenses. We encourage users to familiarize themselves with each prior to use.

models.px.Aurora	Aurora 0.25 degree global forecast model.
models.px.DLWP	Deep learning weather prediction (DLWP) prognostic model.
models.px.FCN	FourCastNet global prognostic model.
models.px.FengWu	FengWu (operational) weather model consists of single auto-regressive model with a time-step size of 6 hours.
models.px.FuXi	FuXi weather model consists of three auto-regressive U-net transfomer models with a time-step size of 6 hours.
models.px.InterpModAFNO	ModAFNO interpolation for global prognostic models.
models.px.Pangu24	Pangu Weather 24 hour model.
models.px.Pangu6	Pangu Weather 6 hour model.
models.px.Pangu3	Pangu Weather 3 hour model.
models.px.Persistence	Persistence model that generates a forecast by applying the identity operator on the initial condition and indexing the lead time by 6 hours.
models.px.SFNO	Spherical Fourier Operator Network global prognostic model.
models.px.StormCast	StormCast generative convection-allowing model for regional forecasts consists of two core models: a regression and diffusion model.

earth2studio.models.dx: Diagnostic

Diagnostic models are a class of models that do not perform time-integration. These may be used to map between weather/climate variables to other quantities of interest, used to enbable additional analysis, improve prediction accuracy, downscale, etc.

Warning

Pre-trained diagnostic models provided in Earth2Studio may be provided under different licenses. We encourage users to familiarize themselves with each prior to use.

models.dx.CorrDiffTaiwan	CorrDiff is a Corrector Diffusion model that learns mappings between low- and high-resolution weather data with high fidelity.
models.dx.ClimateNet	Climate Net diagnostic model, built into Earth2Studio.
models.dx.DerivedRH	Calculates the relative humidity (RH) from specific humidity and temperature for specified pressure levels.
models.dx.DerivedRHDewpoint	Calculates the surface relative humidity (RH) from dewpoint temperature and air temperature.
models.dx.DerivedVPD	Calculates the Vapor Pressure Deficit (VPD) in hPa from relative humidity and temperature fields.
models.dx.DerivedWS	Calculates the Wind Speed (WS) magnitude from eastward and northward wind components for specified levels.
models.dx.PrecipitationAFNO	Precipitation AFNO diagnsotic model.
models.dx.PrecipitationAFNOv2	Improved Precipitation AFNO diagnostic model.
models.dx.TCTrackerWuDuan	Finds a list of tropical cyclone (TC) centers using an adaption of the method described in the conditions in Wu and Duan 2023.
models.dx.TCTrackerVitart	Finds a list of tropical cyclone centers using the conditions in Vitart 1997
models.dx.WindgustAFNO	Wind gust AFNO diagnsotic model.
models.dx.Identity	Identity diagnostic that is coordinate insensitive.

earth2studio.models: Utilities

models.auto.Package	A generic file system abstraction with local caching, uses Fsspec WholeFileCacheFileSystem to manage files.
models.batch.batch_func	Batch utility decorator which can be added to prognostic and diagnostic models to help enable support for automatic batching of data.