Abstract

ABSTRACT: Records of extreme precipitation were investigated using the Discrete Autoregressive Moving Average (DABMA) process, which can explain long persistences of wet and dry spells that exist in daily precipitation data. The results show that the daily precipitation with strong autocorrelation is inclined to be better fit by a Discrete Autoregressive (DAB) model. On the other hand, those data with weak autocorrelations tend to be best fit by a Discrete Moving Average (DMA) model. It can also be concluded that based on the records from extremely wet and dry regions there is no geographic preference regarding the selection of the best model.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.