Focus on relative humidity trend in Iran and its relationship with temperature changes during 1960–2005 View Full Text


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Article Info

DATE

2015-12

AUTHORS

Masoud Noshadi, Hossein Ahani

ABSTRACT

In this research, the mean relative humidity (RH) trend was investigated in the monthly, seasonal and annual timescales during 1960–2005 in 32 synoptic meteorological stations. The Mann–Kendall test after the removal of the significant lag-1 serial correlation effect from the RH time series by pre-whitening was used to determine significant trends. Sen’s slope estimator was used to determine the median slope of positive or negative RH trends in seasonal and annual timescales. Also, in order to facilitate trend analysis and exploring in datasets, 10-year moving average low-pass filter was applied on mean annual normalized RH. Furthermore, smoothed time series by the mentioned filter were classified in four clusters and then they were mapped to show the spatial distribution of trend patterns in Iran. Results showed both significant downward and upward trends, but the number of negative trends was more than positive ones. In general, the stations located in arid central and eastern parts of country had more negative trends. Results of the Sen’s slope estimator showed that in annual timescale, Gorgan synoptic station had the most increasing slope by (+) 2 % per decade, while the most negative slope was detected in Bam by (−) 2.79 % per decade. Also, the analysis of smoothed time series of RH and their relationship with smoothed temperatures showed a strong inverse relationship particularly after 1995. It can be concluded that alongside the increasing of temperature in many parts of Iran, lack of sufficient water vapor has led to decreasing trend of RH in the country. More... »

PAGES

1451-1469

References to SciGraph publications

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  • Journal

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    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10668-014-9615-9

    DOI

    http://dx.doi.org/10.1007/s10668-014-9615-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1041960050


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