scholarly journals Time Series Trend Analysis of Rainfall and Temperature over Kolkata and Surrounding Region

2021 ◽  
Author(s):  
Arijit De ◽  
Srishty Shreya ◽  
Neel Sarkar ◽  
Animesh Maitra

Study of long term variability of temperature and rainfall in the context of climate change is of much importance particularly in the region where rainfed agriculture is predominant. Long term trends of temperature and rainfall have been investigated over Kolkata, India, a tropical region using gridded monthly precipitation and temperature data obtained from Global Precipitation and Climate Centre (GPCC V7) with 0.5° X 0.5° resolution for the period 1901 to 2014. Precipitation concentration index, coefficient of variation, rainfall anomaly have been calculated and Palmer drought severity index data have been analyzed. Furthermore, Mann-Kendall test and sen’s slope estimator have been used to detect time series trend. Annual temperature and rainfall have been increased with a rate of 0.0082°C/ year and 0.03 mm/ year respectively. Statistically significant increasing trend has been observed for most of the months for temperature and rainfall. Winter and monsoon period shows highest and lowest inter-annual variability respectively. Rainfall with high precipitation concentration index (16-20) has been observed for the period 1951-1975 and 1976-2000. It has been observed that the number of years with dry conditions have been increased. However, the intensity of dryness is very near to zero. The information from this study will be helpful for the farmers to plan for resilient farming.

2017 ◽  
Vol 43 (1) ◽  
pp. 255 ◽  
Author(s):  
P. Máyer ◽  
M.V. Marzol ◽  
J.M. Parreño

This paper pursues two objectives: first, to determine the trends of seasonal and annual precipitation in the Canary Islands and, second, to identify trends in the daily precipitation concentration index (CI). For the first objective, we used data from 1970-2013 of 23 rainfall stations located on different islands, after verifying the homogeneity of their series. For the second, the sample was reduced to eleven series since deficiencies in data records of less than 1 mm of daily precipitation were appreciated. We used the nonparametric Mann-Kendall test to determine whether the series showed linear trends in annual and seasonal precipitation and in the values of CI. The seasonal results showed negative trends in spring and winter in almost all the time series considered, especially in the north of Gran Canaria and Tenerife. Conversely, 78% of the series in autumn recorded an increase in the precipitation. The annual balance indicated a decline of rainfall in most of the locations, because of the high concentration of precipitation in winter. Finally, the majority of the time series exhibited a trend toward a greater concentration of daily rainfall, in particular those series located in areas where the main towns are settled, which is an important issue to consider because of severe flooding and other geomorphological processes.


2018 ◽  
Vol 36 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Hanene Bessaklia ◽  
Abderrahmane Nekkache Ghenim ◽  
Abdessalam Megnounif ◽  
Javier Martin-Vide

AbstractIn this study, the spatial variation of daily and monthly concentration precipitation index and its aggressiveness were used in 23 rainfall stations in the extreme north-east of Algeria over the period 1970–2010. The trend was analysed by the Mann–Kendall (MK) test. The results show that daily precipitation concentration index (CI) values are noticeably higher in places where the amount of total precipitation is low, the results of MK test show that areas of high precipitation concentration tend to increase. The seasonality and aggressiveness of precipitation are high in the eastern and western parts of the study region (eastern and central coastal of Constantine catchments), whereas a moderately seasonal distribution with low aggressiveness is found in the middle of the study area (plains and central Seybouse catchment). As a result, the modified Fournier index (MFI) has a significant correlation with annual precipitation, whereas the CI and monthly precipitation concentration index (PCI) show an opposite correlation in relation to annual precipitation.


2011 ◽  
Vol 11 (5) ◽  
pp. 1259-1265 ◽  
Author(s):  
M. de Luis ◽  
J. C. González-Hidalgo ◽  
M. Brunetti ◽  
L. A. Longares

Abstract. An analysis was made of the Precipitation Concentration Index using the new MOPREDAS database of monthly precipitation in Spain (Monthly Precipitation Data base of Spain). The database was compiled after exhaustive quality control of the complete digitalized Spanish Meterological Agency (AEMet) archives and contains a total set of 2670 complete and homogeneous monthly precipitation series from 1946 to 2005. Thus, MOPREDAS currently holds the densest information available for the 1946–2005 period for Spain and ensures a high resolution of results. The Precipitation Concentration Index (PCI) is a powerful indicator of the temporal distribution of precipitation, traditionally applied at annual scales; as the value increases, the more concentrated the precipitation. Furthermore PCI is a part of the well-known Fournier index, with a long tradition on natural system analyses, as for example soil erosion. In this paper, the mean values of annual, seasonal and wet and dry periods of PCI in the conterminous Spain and for two normal periods (1946–1975 and 1976–2005) were studied. Precipitation in Spain follows a general NW-SE spatial pattern during the wet (months) period due to the Atlantic storm track, while during the dry (months) period, it follows a predominantly N-S spatial pattern. As a result, the annual values of PCI combine the two patterns and show a SW-NE PCI gradient. The analyses of the two sub-periods show significant changes in the precipitation occurred in conterminous Spain from 1946 to 2005, and precipitation concentration increased across most of the IP. At an annual scale, PCI increases mostly due to an increase in precipitation concentration during the wet season. At a seasonal scale significant changes were detected between 1945–1975 and 1976–2005, particularly in autumn (increase of PCI values), while changes in winter, spring and summer were mostly localized and not generalized (both increase and decrease). Changes in PCI seem to be complex and appear to be related to global atmospheric features and synoptic and local factors affecting precipitation trends. We discuss the possible explanation linked to the atmospheric pattern and monthly trends and their implications.


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Milan Gocic ◽  
Shahaboddin Shamshirband ◽  
Zaidi Razak ◽  
Dalibor Petković ◽  
Sudheer Ch ◽  
...  

The monthly precipitation data from 29 stations in Serbia during the period of 1946–2012 were considered. Precipitation trends were calculated using linear regression method. Three CLINO periods (1961–1990, 1971–2000, and 1981–2010) in three subregions were analysed. The CLINO 1981–2010 period had a significant increasing trend. Spatial pattern of the precipitation concentration index (PCI) was presented. For the purpose of PCI prediction, three Support Vector Machine (SVM) models, namely, SVM coupled with the discrete wavelet transform (SVM-Wavelet), the firefly algorithm (SVM-FFA), and using the radial basis function (SVM-RBF), were developed and used. The estimation and prediction results of these models were compared with each other using three statistical indicators, that is, root mean square error, coefficient of determination, and coefficient of efficiency. The experimental results showed that an improvement in predictive accuracy and capability of generalization can be achieved by the SVM-Wavelet approach. Moreover, the results indicated the proposed SVM-Wavelet model can adequately predict the PCI.


2020 ◽  
Vol 51 (3) ◽  
pp. 562-582
Author(s):  
Huihua Du ◽  
Yimin Wang ◽  
Zongzhi Wang ◽  
Kelin Liu ◽  
Liang Cheng

Abstract Irregular precipitation has a nontrivial influence on hydrological processes and regional agriculture. The precipitation concentration index provides convenient quantitative characterizations of precipitation variability. To explore the spatial and temporal distribution of the precipitation concentration index, the long-term concentration index (LCI) and the annual concentration index (ACI) during 1979–2015 were calculated based on the China Meteorological Forcing Dataset. The results are as follows: (1) The LCI in China ranged from 0.4571 to 0.9197, and the values between 0.6 and 0.7 accounted for 61.61% of the dataset. The highest and lowest LCI values were both recorded in Northwest China, which features low precipitation levels. Additionally, there are high LCI values (greater than 0.6) in Southeast China, which features high precipitation levels. (2) Application of the Mann-Kendall test (M-K test) and Sen's slope revealed that more than 88% of the grids exhibited nonsignificant positive or negative ACI trends and that more than 10% of the grid ACI values exhibited positive trends, with approximately 2.8% showing significant changes at the 0.1 significance level. (3) Application of the Pettitt test revealed that approximately 11.9% of the grid ACI values exhibited an abrupt change at the 0.5 significance level, with abrupt changes occurring in 1991, 1992 and 1993, together accounting for 45.89% of all grids with abrupt changes.


2021 ◽  
Vol 05 (1) ◽  
pp. 50-67
Author(s):  
Surah Hussain ◽  
Safa Khalil

This research is about analysis seasonality of precipitation concentration in the north of Iraq, by using multiple methods of precipitation concentration Index .The first is the standard vectors method that determines the date of concentration and the number of the rainy months, the second, precipitation concentration index (PCI) that classify the degree of (PCI) annually, supra-seasonal, seasonal depending on monthly precipitation data from nine metrological stations For 36 years (1979-2014), using Excel, Arc map 10.8 and Oriana software in calculates and representation of precipitation concentration. the result shows that all stations in the study area share the same date (Jan.-Feb.) and the stations differ in the length of the rainy season (7-9) month. and for PCI results, PCI annual shows denote a moderate concentration in the whole study area, PCI supra-seasonal value shows (in the wet season uniform rain distribution, the dry season value shows high concentration, PCI seasonal Shows (autumn) moderate concentration, winter: low concentration in all stations, in the spring: PCI value shows the moderate concentration in Erbil, Kirkuk, Sulaymaniyah, Salaheddin, and the other stations shows uniform rain distribution. Keywords: seasonal rain concentration, mathematical vector, PCI.


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