ITM Web Conf.
Volume 23, 2018XLVIII Seminar of Applied Mathematics
|Number of page(s)||5|
|Published online||07 November 2018|
Markov chain as a tool for forecasting daily precipitation in the vicinity of the city of Bydgoszcz, Poland
UTP University of Science and Technology, Faculty of Management, Engineering Management Department, ul. Fordońska 430, 85-790 Bydgoszcz, Poland
2 UTP University of Science and Technology, Faculty of Agriculture and Biotechnology, Department of Agrometeorology, Plant Irrigation and Horticulture, ul. Bernardyńska 6, 85-029 Bydgoszcz, Poland
* Corresponding author: firstname.lastname@example.org
The crop yield depends on numerous weather factors, but mainly on the rainfall pattern and course of air temperature during vegetation period. Investigating the dependence of yields on rainfall, apart from its amount, there also should be taken into account dry spell periods. The two-state Markov chain was considered as a precipitation pattern in the investigation, since it is generally recognized as a simple and effective model of the precipitation occurrence. Based on the daily precipitation totals from the period 1971—2013, the Markov chain was designated. The data were derived from a measuring point of the University of Science and Technology in Bydgoszcz, Poland. As one of the objectives was to determine the order of the Markov chain examined describing the change of precipitation in subsequent days. Another aim was to investigate rainfall dependencies on a month of a year. An analysis of this data leads to the conclusion that the chain is second order. This is confirmed by the two criteria used: BIC (Bayesian Information Criteria) and AIC (Akaike Information Criteria). The research regarded the precipitation volume dependence on a month of the year.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.