scholarly journals Analysis of Long-term Rainfall Trends in Bangladesh

2021 ◽  
Author(s):  
Md. Mizanur Rahman ◽  
Md. Hasan Imam ◽  
Sabuj Roy ◽  
Farhana Hoque ◽  
Urmee Ahsan
Keyword(s):  
Significant Trend ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Data Series ◽  
National Scale ◽  
Winter Rainfall ◽  
Monthly Data ◽  
Rainfall Trends ◽  
Annual Scale

Abstract The study of rainfall trends is critically important for Bangladesh whose food security and
economy are dependent on the timely availability of water. Trends in monthly, seasonal, and annual rainfall on the eight divisions as well as all Bangladesh were examined in this study using a monthly data series of 40 years (1981–2020). Most of the divisions showed decreasing trend in monsoon seasonal rainfall but for only three divisions namely Dhaka, Rajshahi and Rangpur were statistically significant except in Chattogram division, whereas rainfall trend showed positive but not significant. On an annual scale, all divisions also showed a decreasing trend with insignificant exceptions in Dhaka and Rajshahi divisions, which showed a statistically significant trend. For all Bangladesh, no significant trend was detected for seasonal rainfall. Annual, pre-monsoon, monsoon and winter rainfall decreased, while post-monsoon rainfall increased at the national scale but was not significant. Only annual rainfall was detected as statistically significant for all Bangladesh.

scholarly journals Analisis Indeks Harga Konsumen di Indonesia Melalui Pendekatan Kointegrasi

2019 ◽  
Vol 4 (2) ◽  
pp. 110-118
Author(s):  
Muhamad Muin ◽  
Keyword(s):  
Exchange Rate ◽  
Empirical Study ◽  
Money Supply ◽  
Price Index ◽  
Consumer Price Index ◽  
Data Series ◽  
Short Term ◽  
Monthly Data ◽  
The Relationship

This study aims to analyze the relationship between the rupiah exchange rate (RER) and the money supply (M1) on the outgrowth of the consumer price index (CPI) in Indonesia. The data used in this study are monthly data series from January 2005 to January 2019. The results of this empirical study shows that there is a relationship between RER and M1 on CPI in the long term and there is a correction in the short term balance (ECM) which is influenced by M1. All of these variables are significant at α = 5% and partly significant at α = 1%.

scholarly journals Analysis of Long-Term Trends of Annual and Seasonal Rainfall in the Awash River Basin, Ethiopia

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1498 ◽  
Author(s):  
Solomon Mulugeta ◽  
Clifford Fedler ◽  
Mekonen Ayana
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Summer Rainfall ◽  
Seasonal Rainfall ◽  
Winter Rainfall ◽  
Adaptation Measures ◽  
Awash River Basin ◽  
Long Term Trends ◽  
Increasing Trends

With climate change prevailing around the world, understanding the changes in long-term annual and seasonal rainfall at local scales is very important in planning for required adaptation measures. This is especially true for areas such as the Awash River basin where there is very high dependence on rain- fed agriculture characterized by frequent droughts and subsequent famines. The aim of the study is to analyze long-term trends of annual and seasonal rainfall in the Awash River Basin, Ethiopia. Monthly rainfall data extracted from Climatic Research Unit (CRU 4.01) dataset for 54 grid points representing the entire basin were aggregated to find the respective areal annual and seasonal rainfall time series for the entire basin and its seven sub-basins. The Mann-Kendall (MK) test and Sen Slope estimator were applied to the time series for detecting the trends and for estimating the rate of change, respectively. The Statistical software package R version 3.5.2 was used for data extraction, data analyses, and plotting. Geographic information system (GIS) package was also used for grid making, site selection, and mapping. The results showed that no significant trend (at α = 0.05) was identified in annual rainfall in all sub-basins and over the entire basin in the period (1902 to 2016). However, the results for seasonal rainfall are mixed across the study areas. The summer rainfall (June through September) showed significant decreasing trend (at α ≤ 0.1) over five of the seven sub-basins at a rate varying from 4 to 7.4 mm per decade but it showed no trend over the two sub-basins. The autumn rainfall (October through January) showed no significant trends over four of the seven sub-basins but showed increasing trends over three sub-basins at a rate varying from 2 to 5 mm per decade. The winter rainfall (February through May) showed no significant trends over four sub-basins but showed significant increasing trends (at α ≤ 0.1) over three sub-basins at a rate varying from 0.6 to 2.7 mm per decade. At the basin level, the summer rainfall showed a significant decreasing trend (at α = 0.05) while the autumn and winter rainfall showed no significant trends. In addition, shift in some amount of summer rainfall to winter and autumn season was noticed. It is evident that climate change has shown pronounced effects on the trends and patterns of seasonal rainfall. Thus, the study contribute to better understanding of climate change in the basin and the information from the study can be used in planning for adaptation measures against a changing climate.

scholarly journals Incorporating large-scale atmospheric variables in long-term seasonal rainfall forecasting using artificial neural networks: an application to the Ping Basin in Thailand

2016 ◽  
Vol 48 (3) ◽  
pp. 867-882 ◽  
Author(s):  
M. S. Babel ◽  
T. A. J. G. Sirisena ◽  
N. Singhrattna
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Large Scale ◽  
Resource Planning ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Rainfall Forecasting ◽  
Artificial Neural ◽  
Atmospheric Variables

Understanding long-term seasonal or annual or inter-annual rainfall variability and its relationship with large-scale atmospheric variables (LSAVs) is important for water resource planning and management. In this study, rainfall forecasting models using the artificial neural network technique were developed to forecast seasonal rainfall in May–June–July (MJJ), August–September–October (ASO), November–December–January (NDJ), and February–March–April (FMA) and to determine the effects of climate change on seasonal rainfall. LSAVs, temperature, pressure, wind, precipitable water, and relative humidity at different lead times were identified as the significant predictors. To determine the impacts of climate change the predictors obtained from two general circulation models, CSIRO Mk3.6 and MPI-ESM-MR, were used with quantile mapping bias correction. Our results show that the models with the best performance for FMA and MJJ seasons are able to forecast rainfall one month in advance for these seasons and the best models for ASO and NDJ seasons are able do so two months in advance. Under the RCP4.5 scenario, a decreasing trend of MJJ rainfall and an increasing trend of ASO rainfall can be observed from 2011 to 2040. For the dry season, while NDJ rainfall decreases, FMA rainfall increases for the same period of time.

scholarly journals Long term effect of climate change on rainfall in northwest Iraq

2014 ◽  
Vol 4 (3) ◽  
Author(s):  
Nadhir Al-Ansari ◽  
Mawada Abdellatif ◽  
Salahalddin Ali ◽  
Sven Knutsson
Keyword(s):  
Climate Change ◽  
Management Strategies ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Water Shortages ◽  
Intergovernmental Panel ◽  
Continuous Decrease ◽  
Rainfall Trends ◽  
Semi Arid Region

AbstractMiddle East, like North Africa, is considered as arid to semi-arid region. Water shortages in this region, represents an extremely important factor in stability of the region and an integral element in its economic development and prosperity. Iraq was an exception due to presence of Tigris and Euphrates Rivers. After the 1970s the situation began to deteriorate due to continuous decrease in discharges of these rivers, are expected to dry by 2040 with the current climate change. In the present paper, long rainfall trends up to the year 2099 were studied in Sinjar area, northwest of Iraq, to give an idea about its future prospects. Two emission scenarios, used by the Intergovernmental Panel on Climate Change (A2 and B2), were employed to study the long term rainfall trends in northwestern Iraq. All seasons consistently project a drop in daily rainfall for all future periods with the summer season is expected to have more reduction compared to other seasons. Generally the average rainfall trend shows a continuous decrease. The overall average annual rainfall is slightly above 210 mm. In view of these results, prudent water management strategies have to be adopted to overcome or mitigate consequences of future severe water crisis.

Rainfall trends in hindsight and in foresight

2020 ◽  
Author(s):  
Theano Iliopoulou ◽  
Demetris Koutsoyiannis
Keyword(s):  
Daily Rainfall ◽  
Predictive Performance ◽  
Predictive Modelling ◽  
Annual Rainfall ◽  
Methodological Framework ◽  
Rainfall Trends ◽  
Out Of Sample ◽  
Linear Trends

<p>Trends are customarily identified in rainfall data in the framework of explanatory modelling. Little insight however has been gained by this type of analysis with respect to their performance in foresight. In this work, we examine the out-of-sample predictive performance of linear trends through extensive investigation of 60 of the longest daily rainfall records available worldwide. We devise a systematic methodological framework in which linear trends are compared to simpler mean models, based on their performance in predicting climatic-scale (30-year) annual rainfall indices, i.e. maxima, totals, wet-day average and probability dry, from long-term daily records. Parallel experiments from synthetic timeseries are performed in order to provide theoretical insights to the results and the role of parsimony in predictive modelling is discussed. In line with the empirical findings, it is shown that, prediction-wise, simple is preferable to trendy.</p>

scholarly journals Analysis of rainfall trends over Tripura

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 27-36
Author(s):  
RANJAN PHUKAN ◽  
D. SAHA
Keyword(s):  
Heavy Rainfall ◽  
Monsoon Season ◽  
Rainfall Variability ◽  
Kendall Test ◽  
Annual Rainfall ◽  
The North ◽  
Rainfall Trends ◽  
Annual Scale ◽  
Increasing Trends ◽  
Rainy Days

Rainfall in India has very high temporal and spatial variability. The rainfall variability affects the livelihood and food habits of people from different regions. In this study, the rainfall trends in two stations in the north-eastern state of Tripura, namely Agartala and Kailashahar have been studied for the period 1955-2017. The state experiences an annual mean of more than 2000 mm of rainfall, out of which, about 60% occurs during the monsoon season and about 30% in pre-monsoon. An attempt has been made to analyze the trends in seasonal and annual rainfall, rainy days and heavy rainfall in the two stations, during the same period.Non-parametric Mann-Kendall test has been used to find out the significance of these trends. Both increasing and decreasing trends are observed over the two stations. Increasing trends in rainfall, rainy days and heavy rainfall are found at Agartala during pre-monsoon season and decreasing trends in all other seasons and at annual scale. At Kailashahar, rainfall amount (rainy days & heavy rainfall) is found to be increasing during pre-monsoon and monsoon seasons (pre-monsoon season). At annual scale also, rainfall and rainy days show increasing trends at Kailashahar. The parameters are showing decreasing trends during all other seasons at the station. Rainy days over Agartala show a significantly decreasing trend in monsoon, whereas no other trend is found to be significant over both the stations.  

scholarly journals Uncertainty in Estimated Trends Using Gridded Rainfall Data: A Case Study of Bangladesh

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 349 ◽  
Author(s):  
Mohamed Salem Nashwan ◽  
Shamsuddin Shahid ◽  
Xiaojun Wang
Keyword(s):  
Spatial Patterns ◽  
Similarity Index ◽  
Skill Score ◽  
Rainfall Data ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Global Precipitation Climatology Centre ◽  
Rainfall Trends ◽  
Grid Points

This study assessed the uncertainty in the spatial pattern of rainfall trends in six widely used monthly gridded rainfall datasets for 1979–2010. Bangladesh is considered as the case study area where changes in rainfall are the highest concern due to global warming-induced climate change. The evaluation was based on the ability of the gridded data to estimate the spatial patterns of the magnitude and significance of annual and seasonal rainfall trends estimated using Mann–Kendall (MK) and modified MK (mMK) tests at 34 gauges. A set of statistical indices including Kling–Gupta efficiency, modified index of agreement (md), skill score (SS), and Jaccard similarity index (JSI) were used. The results showed a large variation in the spatial patterns of rainfall trends obtained using different gridded datasets. Global Precipitation Climatology Centre (GPCC) data was found to be the most suitable rainfall data for the assessment of annual and seasonal rainfall trends in Bangladesh which showed a JSI, md, and SS of 22%, 0.61, and 0.73, respectively, when compared with the observed annual trend. Assessment of long-term trend in rainfall (1901–2017) using mMK test revealed no change in annual rainfall and changes in seasonal rainfall only at a few grid points in Bangladesh over the last century.

scholarly journals Spatial distribution and estimation of rainfall trends and erosivity in the Epitácio Pessoa reservoir catchment, Paraíba, Brazil

2020 ◽  
Vol 102 (3) ◽  
pp. 829-849 ◽  
Author(s):  
Richarde Marques da Silva ◽  
Celso Augusto Guimarães Santos ◽  
Jorge Flávio Cazé Braga da Costa Silva ◽  
Alexandro Medeiros Silva ◽  
Reginaldo Moura Brasil Neto
Keyword(s):  
Regional Scale ◽  
Temporal Analysis ◽  
Northeastern Brazil ◽  
Annual Rainfall ◽  
Positive Trend ◽  
Monthly Data ◽  
Rainfall Trends ◽  
Detailed Statistical Analysis ◽  
The Mean ◽  
Spatial Temporal Analysis

Abstract The main goals of this study are to better understand the spatial and temporal variabilities in rainfall and to identify rainfall trends and erosivity for the period from 1963 to 1991 in the Epitácio Pessoa reservoir catchment, which is located in Paraíba, northeastern Brazil. This study analyzes annual rainfall trends on a regional scale by using monthly data from 13 rainfall stations. For this purpose, the nonparametric Mann–Kendall and Sen methods were used in the analysis. Descriptive statistics methods and interpolation techniques were also used for spatial–temporal analysis of the annual rainfall. A detailed statistical analysis applied to the time series of all the stations indicates that the rainfall presents substantial annual spatial–temporal variability and a negative trend (decrease) in the mean rainfall at most of the rainfall stations in the catchment during the study period. The results only showed a positive trend for the Soledade and Pocinhos stations. The distribution of positive and negative trends in the Epitácio Pessoa reservoir catchment is extremely irregular, and the changes in the study area are more significant compared to those identified in other studies. Graphic abstract

Yet more on a stochastic economic model: Part 3C: stochastic bridging for share yields and dividends and interest rates

2016 ◽  
Vol 11 (1) ◽  
pp. 128-163 ◽  
Author(s):  
A. D. Wilkie ◽  
Şule Şahin
Keyword(s):  
Interest Rates ◽  
Brownian Bridge ◽  
Data Series ◽  
Similar Model ◽  
Short Term ◽  
Monthly Data ◽  
The Third ◽  
Brownian Bridges ◽  
Retail Prices

AbstractThis is the third and last subpart of a long paper in which we consider stochastic interpolation for the Wilkie asset model, considering both Brownian bridges and Ornstein–Uhlenbeck (OU) bridges. In Part 3A, we developed certain properties for both these types of stochastic bridge, and in Part 3B we investigated retail prices and wages. In this paper, we investigate the remainder of many of our data series, relating to shares and interest rates. We conclude that, regardless of the form of the annual model, the monthly data within each year can be modelled by Brownian bridges, usually on the logarithm of the principal variable. But in no case is a simple Brownian bridge enough, and all series have their own peculiarities. Overall, however, our modelling produces simulations that are realistic in comparison with the known data. Many of our findings would apply to any similar model used for simulation over time. Our results have considerable importance for financial economics. We reconcile the conflict between the long-term mean-reverting modelling of Schiller and the short-term random walk modelling of Fama. This conclusion therefore has very wide significance.

scholarly journals Trend Analysis of Rainfall Data in Magelang District Using Mann-Kendall Test and Modification Mann-Kendall Variation

AGRIFOR ◽  
2018 ◽  
Vol 17 (2) ◽  
pp. 293 ◽  
Author(s):  
Joko Suryanto ◽  
Joko Krisbiyantoro
Keyword(s):  
Kendall Test ◽  
Significant Trend ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Partial Sums ◽  
Trend Test ◽  
Positive Trend ◽  
Mk Test ◽  
Rainfall Trends ◽  
Negative Significant Trend

The objective of the research was to analyzed rainfall trends from 6 rainfall stations Kajoran, Mendut, Muntilan, Ngablak, Salaman and Tempuran rainfall station in different time scales (monthly, 3-months periodicityand annual). Identification homogenity of the rainfall data period 1986-2016 for Magelang district using Rescaled Adjusted Partial Sums (RAPS) methode. The three non-parametric tests, Mann-Kendall (MK), modified Mann-Kendall (MMK), trend free prewhitening Mann-Kendall (TFPW-MK) and Sen’s slope wereemployed to assess significance of trends and detecting magnitude of trends.The results shows that monthly rainfall have no significant trend using MK, MMK, and TFPW-MK test at 0.05 level significance. Rainfall 3-month based January-February-March (JFM) period Kajoran station have negative significant trend with magnitude 19.4 mm/3-month. Mendut station have positive trend for April-May-June (AMJ) period with magnitude 6.75 mm/3-month. No significant trends at 0.05 level significance using MK trend test were detected in annual rainfall for 6 rainfall stations.

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