Trend analysis of annual and seasonal rainfall time series in the Mediterranean area

2009 ◽  
pp. n/a-n/a ◽  
Author(s):  
Antonia Longobardi ◽  
Paolo Villani
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Mediterranean Area ◽  
Seasonal Rainfall ◽  
Rainfall Time Series ◽  
The Mediterranean

scholarly journals Trend Analysis of Rainfall Time Series in Shanxi Province, Northern China (1957–2019)

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2335
Author(s):  
Feng Gao ◽  
Yunpeng Wang ◽  
Xiaoling Chen ◽  
Wenfu Yang
Keyword(s):  
Time Series ◽  
Water Supply ◽  
Trend Analysis ◽  
Agricultural Production ◽  
Time Series Data ◽  
Shanxi Province ◽  
Series Data ◽  
Rainfall Time Series ◽  
Mk Test ◽  
Wutai Shan

Changes in rainfall play an important role in agricultural production, water supply and management, and social and economic development in arid and semi-arid regions. The objective of this study was to examine the trend of rainfall series from 18 meteorological stations for monthly, seasonal, and annual scales in Shanxi province over the period 1957–2019. The Mann–Kendall (MK) test, Spearman’s Rho (SR) test, and the Revised Mann–Kendall (RMK) test were used to identify the trends. Sen’s slope estimator (SSE) was used to estimate the magnitude of the rainfall trend. An autocorrelation function (ACF) plot was used to examine the autocorrelation coefficients at various lags in order to improve the trend analysis by the application of the RMK test. The results indicate remarkable differences with positive and negative trends (significant or non-significant) depending on stations. The largest number of stations showing decreasing trends occurred in March, with 10 out of 18 stations at the 10%, 5%, and 1% levels. Wutai Shan station has strong negative trends in January, March, April, November, and December at the level of 1%. In addition, Wutai Shan station also experienced a significant decreasing trend over four seasons at a significance level of 1% and 10%. On the annual scale, there was no significant trend detected by the three identification methods for most stations. MK and SR tests have similar power for detecting monotonic trends in rainfall time series data. Although similar results were obtained by the MK/SR and RMK tests in this study, in some cases, unreasonable trends may be provided by the RMK test. The findings of this study could benefit agricultural production activities, water supply and management, drought monitoring, and socioeconomic development in Shanxi province in the future.

Segmentation-based approach for trend analysis and structural breaks in rainfall time series (1851–2006) over India

2020 ◽  
Vol 65 (9) ◽  
pp. 1583-1595 ◽  
Author(s):  
Niraj Priyadarshi ◽  
Soumya Bandyopadhyay ◽  
V. M. Chowdary ◽  
K. Chandrasekar ◽  
Jeganathan Chockalingam ◽  
...  
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Structural Breaks ◽  
Rainfall Time Series

scholarly journals Variability and Trend Analysis of Rainfall Data of Shillong and Agartala Stations of North East India

2020 ◽  
pp. 134-142
Author(s):  
Mirbana Lusick K. Sangma ◽  
Hamtoiti Reang ◽  
G. T. Patle ◽  
P. P. Dabral
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Winter Season ◽  
Summer Season ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
North East ◽  
South West ◽  
Total Annual Rainfall ◽  
Sw Monsoon

This paper discusses the variability in rainfall and trend analysis of annual and seasonal rainfall time series of Shillong and Agartala stations located in the north-east region of India. Commonly used non-parametric statistical methods namely Mann-Kendall and Sen’s slope estimator was used to analyse the seasonal and annual rainfall time series. Statistical analysis showed less variation in annual and south-west monsoon rainfall for both Shillong and Agartala stations. In the total annual rainfall, the share of south-west (SW) monsoon, north-east (NE) monsoon, winter season and summer season rainfall was observed 64.60%, 13.22%, 1.40% and 20.80%, respectively for Shillong station of Meghalaya state. However, the contribution of SW monsoon, NE monsoon, winter season and summer season rainfall in the total annual rainfall was 59.59%, 9.55%, 1.14% and 29.72%, respectively for Agartala station of Tripura state. Non-significant increasing trends of rainfall was observed by 4.54 mm/year, 2.80 mm/year and 2.54 mm/year for annual, SW monsoon, and summer season, whereas, non-significant decreasing trends in rainfall for NE monsoon and winter season was observed with a magnitude of 1.83 mm/year and 1.63 mm/year for Shillong, Meghalaya during 1992 to 2017. Results also revealed that rainfall increased by 1.07 mm/year and 0.18 mm/year in SW monsoon and winter season whereas, rainfall decreased by 7.64 mm/year, 2.58 mm/year and 1.29 mm/year during annual, NE monsoon and summer season non-significantly during 1995 to 2019 in case of Agartala. The findings of present study will be useful for water management and crop planning in hill agriculture of Meghalaya and Tripura state of India.

scholarly journals Long-term trend analysis of rainfall using hybrid Discrete Wavelet Transform (DWT) based Mann-Kendall tests in central Gujarat region, India

MAUSAM ◽  
2021 ◽  
Vol 71 (2) ◽  
pp. 209-224
Author(s):  
RAJANI NIRAV V ◽  
TIWARI MUKESH K ◽  
CHINCHORKAR S S
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Trend Analysis ◽  
Time Scales ◽  
Series Data ◽  
Trend Test ◽  
Discrete Wavelet ◽  
Rainfall Time Series

Trend analysis has become one of the most important issues in hydro-meteorological variables study due to climate change and the focus given to it in the recent past from the scientific community. In this study, long-term trends of rainfall are analyzed in eight stations located in semi-arid central Gujarat region, India by considering time series data of 116 years (1901-2016). Discrete wavelet transform (DWT) as a dyadic arrangement of continuous wavelet transformation combined with the widely applied and acknowledged Mann-Kendall (MK) trend analysis method were applied for analysis of trend and dominant periodicities in rainfall time series at monthly, annual and monsoonal time scales. Initially, rainfall time series applied in this study were decomposed using DWT to generate sub-time series at high and low frequencies, before applying the MK trend test. Further, the Sequential Mann-Kendall (SQMK) test was also applied to find out the trend changing points. The result showed that at the monthly annual and monsoon time scales, the trends in rainfall were significantly decreasing in most of the station. The 4-month and 8-month components were found as dominant at the monthly time series and the 2-year and 4-year component were found as dominant at the monsoon time series, whereas the 2-year components were observed as dominant in the annual time scale.

scholarly journals Interannual Variability of GPS Heights and Environmental Parameters over Europe and the Mediterranean Area

2021 ◽  
Vol 13 (8) ◽  
pp. 1554
Author(s):  
Letizia Elia ◽  
Susanna Zerbini ◽  
Fabio Raicich
Keyword(s):  
Time Series ◽  
Interannual Variability ◽  
Environmental Parameters ◽  
Mediterranean Area ◽  
Space Time ◽  
The Arctic ◽  
Climate Indices ◽  
Geological Processes ◽  
Second Mode ◽  
The Mediterranean

Vertical deformations of the Earth’s surface result from a host of geophysical and geological processes. Identification and assessment of the induced signals is key to addressing outstanding scientific questions, such as those related to the role played by the changing climate on height variations. This study, focused on the European and Mediterranean area, analyzed the GPS height time series of 114 well-distributed stations with the aim of identifying spatially coherent signals likely related to variations of environmental parameters, such as atmospheric surface pressure (SP) and terrestrial water storage (TWS). Linear trends and seasonality were removed from all the time series before applying the principal component analysis (PCA) to identify the main patterns of the space/time interannual variability. Coherent height variations on timescales of about 5 and 10 years were identified by the first and second mode, respectively. They were explained by invoking loading of the crust. Single-value decomposition (SVD) was used to study the coupled interannual space/time variability between the variable pairs GPS height–SP and GPS height–TWS. A decadal timescale was identified that related height and TWS variations. Features common to the height series and to those of a few climate indices—namely, the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the East Atlantic (EA), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI)—were also investigated. We found significant correlations only with the MEI. The first height PCA mode of variability, showing a nearly 5-year fluctuation, was anticorrelated (−0.23) with MEI. The second mode, characterized by a decadal fluctuation, was well correlated (+0.58) with MEI; the spatial distribution of the correlation revealed, for Europe and the Mediterranean area, height decrease till 2015, followed by increase, while Scandinavian and Baltic countries showed the opposite behavior.

Trend analysis of rainfall time series for Sindh river basin in India

2015 ◽  
Vol 125 (3-4) ◽  
pp. 593-608 ◽  
Author(s):  
Sarita Gajbhiye ◽  
Chandrashekhar Meshram ◽  
Rasoul Mirabbasi ◽  
S. K. Sharma
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
River Basin ◽  
Rainfall Time Series

Spatiotemporal variability of annual and seasonal rainfall time series in Ho Chi Minh city, Vietnam

2018 ◽  
Vol 10 (3) ◽  
pp. 658-670 ◽  
Author(s):  
Dang Nguyen Dong Phuong ◽  
Vu Thuy Linh ◽  
Tran Thong Nhat ◽  
Ho Minh Dung ◽  
Nguyen Kim Loi
Keyword(s):  
Time Series ◽  
Rainy Season ◽  
Kendall Test ◽  
Dry Season ◽  
Seasonal Rainfall ◽  
Spatiotemporal Variability ◽  
Ho Chi Minh City ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Spatial And Temporal Patterns

Abstract This study analyzed spatial and temporal patterns of rainfall time series from 14 proportionally distributed stations in Ho Chi Minh City for the period 1980–2016. Both parametric and nonparametric approaches, specifically, linear regression, the Mann–Kendall test and Sen's slope estimator, were applied to detect and estimate the annual and seasonal trends after using original and notched boxplots for the preliminary interpretation. The outcomes showed high domination of positive trends in the annual and seasonal rainfall time series over the 37-year period, but most statistically significant trends were observed in the dry season. The results of trend estimation also indicated higher increasing rates of rainfall in the dry season compared to the rainy season at most stations. Even though the total amount of annual rainfall is mainly contributed by rainfall during the rainy season, the pronounced increment in the dry season can be a determining factor of possible changes in annual rainfall. Additionally, the interpolated results revealed a consistently increasing trend in the southeastern parts of the study area (i.e., Can Gio district), where annual rainfall was by far the lowest intensity compared to other regions.

scholarly journals Recent climate change in Syria: Seasonal rainfall and climatology of Syria for 1991-2009

2018 ◽  
Vol 13 (1) ◽  
pp. 77-96 ◽  
Author(s):  
Ibrahim Alkhalaf ◽  
Tatiana Solakova ◽  
Martina Zelenakova ◽  
Ibrahim Gargar
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Trend Analysis ◽  
Water Scarcity ◽  
Statistical Tests ◽  
Seasonal Rainfall ◽  
Seasonal Precipitation ◽  
Hydrologic Time Series ◽  
Recent Climate ◽  
Surface Observations

Abstract Trend analysis is one of the most commonly used tools for detecting changes in climatic and hydrologic time series. Attempts are devoted to the study of seasonal climatology in Syria, including information on the level of rainfall at various climatic stations in Syria for the period 1991-2009. Wet (from October to May) and dry (June to September) seasonal precipitation are obtained from surface observations. There are numbers of statistical tests that exist to assess the significance of trends in time series. However, the existence of positive autocorrelation in the data increases the probability of detecting trends when actually none exist, and vice versa. Most of the recent studies about climate change suggest that the behavior of some of the climatological variables has already changed and will continue to change towards increasing or decreasing magnitudes and frequencies, depending on the type of variable. Increased rainfall and following floods are expected in some regions while other regions will experience smaller rainfall and longer droughts, meaning water scarcity.

Trends and Periodicities in Rainfall, Temperature, and Relative Humidity Datasets Over Ghana

2021 ◽  
Vol 4 (1) ◽  
Keyword(s):  
Time Series ◽  
Relative Humidity ◽  
Coastal Zone ◽  
Seasonal Rainfall ◽  
Rainfall Time Series ◽  
Cyclic Pattern ◽  
Temperature And Humidity ◽  
Long Time ◽  
Northern Zone

This paper analyzed trends and periodicities in annual and seasonal rainfall, temperature, and relative humidity (RH) over Ghana using climatological datasets for twelve (12) synoptic stations spanning the periods of 30 to 52 years (1961–2010), obtained from the Ghana Meteorological Agency (GMet). The datasets were normalized by dividing with the long time mean, and grouped in decades. Findings show that 1961-1970 and 2001-2010 decades recorded significant wetter years, while 1981-1990 recorded relatively drier years within in the zones with bimodal rainfall seasons. However in the zone with mono-modal rainfall seasons wetter years occurred within the decades of 1981-1990 and 2001-2010. Furthermore, it is realised that, there is a cyclic pattern noted in the rainfall time series and a cycle of about 5 to 8 months for the Northern zone, 6 – 8 month for the middle belt and approximately 8 months for the coastal zone in the rainfall, temperature and humidity datasets suggesting a coherence in their relationship.

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