This study aims to determine trends in the long-term monthly total data series using non-parametric methods like Mann-Kendall and Sen's T test. The change per unit time in a time series having a linear trend is estimated by applying a simple non-parametric procedure, namely Sen's estimator of slope. Serial correlation structure in the data is accounted for determining the significance level of the results of the Mann-Kendall test. The data used in this study, consists of seven divisional meteorological stations across Bangladesh. Station basis trend analysis has been performed for temperature data. For temperature data most of the stations show significant trend. There are rising rates of temperature in some months and decreasing trend in some other months obtained by these statistical tests suggesting overall significant changes in the area.
Published in | International Journal of Environmental Monitoring and Analysis (Volume 1, Issue 5) |
DOI | 10.11648/j.ijema.20130105.12 |
Page(s) | 175-181 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2013. Published by Science Publishing Group |
Temperature, Mann-Kendall, Sen's T, Trend Analysis, Serial Correlation
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APA Style
Mst. Noorunnahar, Md. Arafat Rahman. (2013). Estimating Regional Trends of Temperature in Bangladesh. International Journal of Environmental Monitoring and Analysis, 1(5), 175-181. https://doi.org/10.11648/j.ijema.20130105.12
ACS Style
Mst. Noorunnahar; Md. Arafat Rahman. Estimating Regional Trends of Temperature in Bangladesh. Int. J. Environ. Monit. Anal. 2013, 1(5), 175-181. doi: 10.11648/j.ijema.20130105.12
AMA Style
Mst. Noorunnahar, Md. Arafat Rahman. Estimating Regional Trends of Temperature in Bangladesh. Int J Environ Monit Anal. 2013;1(5):175-181. doi: 10.11648/j.ijema.20130105.12
@article{10.11648/j.ijema.20130105.12, author = {Mst. Noorunnahar and Md. Arafat Rahman}, title = {Estimating Regional Trends of Temperature in Bangladesh}, journal = {International Journal of Environmental Monitoring and Analysis}, volume = {1}, number = {5}, pages = {175-181}, doi = {10.11648/j.ijema.20130105.12}, url = {https://doi.org/10.11648/j.ijema.20130105.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20130105.12}, abstract = {This study aims to determine trends in the long-term monthly total data series using non-parametric methods like Mann-Kendall and Sen's T test. The change per unit time in a time series having a linear trend is estimated by applying a simple non-parametric procedure, namely Sen's estimator of slope. Serial correlation structure in the data is accounted for determining the significance level of the results of the Mann-Kendall test. The data used in this study, consists of seven divisional meteorological stations across Bangladesh. Station basis trend analysis has been performed for temperature data. For temperature data most of the stations show significant trend. There are rising rates of temperature in some months and decreasing trend in some other months obtained by these statistical tests suggesting overall significant changes in the area.}, year = {2013} }
TY - JOUR T1 - Estimating Regional Trends of Temperature in Bangladesh AU - Mst. Noorunnahar AU - Md. Arafat Rahman Y1 - 2013/09/10 PY - 2013 N1 - https://doi.org/10.11648/j.ijema.20130105.12 DO - 10.11648/j.ijema.20130105.12 T2 - International Journal of Environmental Monitoring and Analysis JF - International Journal of Environmental Monitoring and Analysis JO - International Journal of Environmental Monitoring and Analysis SP - 175 EP - 181 PB - Science Publishing Group SN - 2328-7667 UR - https://doi.org/10.11648/j.ijema.20130105.12 AB - This study aims to determine trends in the long-term monthly total data series using non-parametric methods like Mann-Kendall and Sen's T test. The change per unit time in a time series having a linear trend is estimated by applying a simple non-parametric procedure, namely Sen's estimator of slope. Serial correlation structure in the data is accounted for determining the significance level of the results of the Mann-Kendall test. The data used in this study, consists of seven divisional meteorological stations across Bangladesh. Station basis trend analysis has been performed for temperature data. For temperature data most of the stations show significant trend. There are rising rates of temperature in some months and decreasing trend in some other months obtained by these statistical tests suggesting overall significant changes in the area. VL - 1 IS - 5 ER -