Articles | Volume 20, issue 11
https://doi.org/10.5194/hess-20-4605-2016
https://doi.org/10.5194/hess-20-4605-2016
Research article
 | 
17 Nov 2016
Research article |  | 17 Nov 2016

A statistically based seasonal precipitation forecast model with automatic predictor selection and its application to central and south Asia

Lars Gerlitz, Sergiy Vorogushyn, Heiko Apel, Abror Gafurov, Katy Unger-Shayesteh, and Bruno Merz

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Cited articles

Ashok, K., Guan, Z., and Yamagata, T.: Impact of the Indian Ocean dipole on the relationship between the Indian monsoon rainfall and ENSO, Geophys. Res. Lett., 28, 4499–4502, https://doi.org/10.1029/2001GL013294, 2001.
Barlow, M., Cullen, H., and Lyon, B.: Drought in Central and Southwest Asia: La Niña, the Warm Pool, and Indian Ocean Precipitation, J. Climate, 15, 697–700, https://doi.org/10.1175/1520-0442(2002)015<0697:DICASA>2.0.CO;2, 2002.
Barlow, M., Zaitchik, B., Paz, S., Black, E., Evans, J., and Hoell, A.: A Review of Drought in the Middle East and Southwest Asia, J. Climate, https://doi.org/10.1175/JCLI-D-13-00692.1, 2015.
Barlow, M. A. and Tippett, M. K.: Variability and Predictability of Central Asia River Flows: Antecedent Winter Precipitation and Large-Scale Teleconnections, J. Hydrometeorol., 9, 1334–1349, https://doi.org/10.1175/2008JHM976.1, 2008.
Bastos, A., Janssens, I. A., Gouveia, C. M., Trigo, R. M., Ciais, P., Chevallier, F., Peñuelas, J., Rödenbeck, C., Piao, S., Friedlingstein, P., and Running, S. W.: European land CO2 sink influenced by NAO and East-Atlantic Pattern coupling, Nat. Commun., 7, 10315, https://doi.org/10.1038/ncomms10315, 2016.
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Short summary
Most statistically based seasonal precipitation forecast models utilize a small set of well-known climate indices as potential predictor variables. However, for many target regions, these indices do not lead to sufficient results and customized predictors are required for an accurate prediction. This study presents a statistically based routine, which automatically identifies suitable predictors from globally gridded SST and climate variables by means of an extensive data mining procedure.