Articles | Volume 12, issue 7
Geosci. Model Dev., 12, 2915–2940, 2019
https://doi.org/10.5194/gmd-12-2915-2019
Geosci. Model Dev., 12, 2915–2940, 2019
https://doi.org/10.5194/gmd-12-2915-2019

Model description paper 12 Jul 2019

Model description paper | 12 Jul 2019

AtmoSwing: Analog Technique Model for Statistical Weather forecastING and downscalING (v2.1.0)

Pascal Horton

Model code and software

AtmoSwing v2.1.0 Horton, Pascal https://doi.org/10.5281/zenodo.3208134

AtmoSwing R tools Horton, Pascal and Burkart, Kathrin https://doi.org/10.5281/zenodo.1305098

AtmoSwing Python tools Horton, Pascal https://doi.org/10.5281/zenodo.1495057

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Short summary
Analog methods rely on the principle that similar atmospheric situations are likely to result in a similar local effect, such as precipitation. By using archives of measured atmospheric parameters and observed precipitation, one can establish a probabilistic forecast, for example, of the precipitation for a chosen target day. Analog methods require low computing capacity and have demonstrated useful potential for application in both operational forecasting and the context of climate studies.