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Last Updated: 02/29/2024

DAFFS

Version: 0.37

DAFFS is a probabilistic near-real-time region- and full-disk solar flare forecasting facility based on magnetic field data, prior flare history, and multi-variable discriminant analysis. The forecasts arise from probability functions constructed from 2-variable combinations, where different combinations are selected according to performance, separately for each event definition.

Initially developed under a NOAA SBIR, it includes multiple layers of redundancy and potential flexibility, although by default it produces NOAA-like forecasts (see below).
Redundancy includes providing forecasts based on GONG data if HMI data are not available, then based only on GOES events if GONG data are not available, and finally providing a climatology forecast if no data are available. Potential flexibility includes numerous options for customization (of threshold, issuing schedule, validity/latency timing, event type). DAFFS (and separately, DAFFS-G, the “GONG-data-focused” facility) were evaluated in the “Nagoya Workshop” papers (see below). 2023.12: updates coming as DAFFS gets some TLC.

Caveats:

Full-disk probabilities (valid for full disk) are calculated from region probabilities. HMI Active Region Patches are used by default, with relevant NOAA regions associated. Presently relies on netDRMS/SUMS access. It would not be difficult to forecast for other event definitions but would require re-training.

Inputs

NOAA near real time (NRT) region identifications and event data, vector magnetic photospheric data (HMI), line-of-sight magnetic photospheric data (GONG).

Outputs

Probabilistic forecasts for solar flares matching NOAA event definitions: C+, M+, X+ for 24hr validity periods with effectively 0,24, and 48hr latencies. If HMI data are not available, GONG-based NOAA-region forecasts are issued. If GONG data are also not available, forecasts based on prior flare history and climatology are issued.

Domains

  • Solar

Space Weather Impacts

  • Ionosphere variability (navigation, communications)
  • Atmosphere variability (satellite/debris drag)
  • Near-earth radiation and plasma environment (aerospace assets functionality)

Phenomena

  • Solar Flares

Publications

Code

Code Languages: Python, Fortran, C, IDL, bash

Contacts

Publication Policy

In addition to any model-specific policy, please refer to the General Publication Policy.