The effect of autocorrelation on the meteorological parameters trend
- PDF / 1,499,159 Bytes
- 13 Pages / 595.276 x 790.866 pts Page_size
- 88 Downloads / 248 Views
ORIGINAL PAPER
The effect of autocorrelation on the meteorological parameters trend Neda Khanmohammadi1 · Hossein Rezaie1 · Javad Behmanesh1 Received: 14 May 2019 / Accepted: 6 October 2020 © Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract The trend analysis of the meteorological parameters has an important role in climate change studies. One of the most important factors which affects the trend analysis is the existence of the autocorrelation in meteorological parameters’ time series. Therefore, in this research, the effect of autocorrelation on trend of some meteorological parameters such as precipitation, relative humidity, solar radiation, wind speed and mean temperature was analyzed. For this purpose, the annual values of mentioned parameters were calculated using daily recorded data in 30 synoptic stations of Iran during 1960–2014. Then the trend of calculated annual time series was analyzed using the Mann Kendall (M–K) and modified Mann–Kendall (MM-K) tests (with considering all significant autocorrelation coefficients). The comparison of two mentioned tests showed that the autocorrelation affects the trend of the studied parameters. On the basis of the Root Mean Square Error (RMSE) results, in the trend analysis of temperature and precipitation, there were maximum and minimum differences between the statistic (Z) of the M–K and MM-K tests, respectively. The most linear relationship between results of two used trend tests was observed for precipitation and other parameters including wind speed, solar radiation, temperature and relative humidity were placed in the next steps, respectively. The trend results of the MM-K test showed that the precipitation, relative humidity and wind speed parameters had decreasing trend, while the trend of the solar radiation and temperature parameters was positive in more than 50% of studied stations. Also, the precipitation, relative humidity and wind speed parameters had negative trend slope in 63.3%, 80% and 60%, of stations, while, the solar radiation and temperature parameters had positive slope in 63.3% and 90% of studied stations, respectively.
1 Introduction Trend detection in the meteorological or hydrological time series has been as one of the popular and common issues in the past decades. This issue has received considerable concentration because of increasing greenhouse gases of the Earth’s atmosphere and changing climate. Climate change phenomena affects the changes of meteorological or hydrological time series such as precipitation, relative humidity, solar radiation, wind speed and temperature. Trend analysis can be carried out using proposed methods which can be classified as parametric and non-parametric tests (Zhang et al. 2006). Because of the parametric methods’ limitations, researchers prefer to apply non-parametric
Responsible Editor: Stephanie Fiedler. * Neda Khanmohammadi [email protected] 1
Department of Water Engineering, Urmia University, 11 Km Sero Road, Urmia, Iran
tests. Two example of non-parametric methods
Data Loading...
