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 Statistical analysis of seasonal rainfall data in Chandigarh: A case study

2021 ◽  
Vol 889 (1) ◽  
pp. 012024
Author(s):  
Kaamun ◽  
Sahil Arora
Keyword(s):  
Statistical Analysis ◽  
Goodness Of Fit ◽  
Seasonal Forecast ◽  
Rainfall Data ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Maximum Rainfall ◽  
The Past

Abstract The following research focuses on Chandigarh’s annual rainfall of past 50 years i.e. from 1968 to 2017. Parameters like Kurtosis, Variance, Goodness of Fit, Mann-Kendall’s Test were performed along with total annual forecast as well as seasonal forecast was predicted. Seasonal rend was also studied so as to study in detail about the past, present, and future of rainfall in Chandigarh. This study was performed with the help of MS-Excel and ExcelStat. A rising trend was found in Chandigarh for total as well as seasonal rainfall with a maximum rainfall of 1510.9 mm in the year of 1996 and a minimum of 371.1 mm in year 1987, other than this Sen.’s slope was 6.431 whereas skewness was found to be 0.6018.

scholarly journals Rainfall Trend and Its Relationship with Normalized Difference Vegetation Index in a Restored Semi-Arid Wetland of South Africa

2020 ◽  
Vol 12 (21) ◽  
pp. 8919
Author(s):  
Florence M. Murungweni ◽  
Onisimo Mutanga ◽  
John O. Odiyo
Keyword(s):  
South Africa ◽  
Quantile Regression ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rainfall Data ◽  
Ecosystem Change ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Vegetation Productivity ◽  
Rainfall Trends

Clearance of terrestrial wetland vegetation and rainfall variations affect biodiversity. The rainfall trend–NDVI (Normalized Difference Vegetation Index) relationship was examined to assess the extent to which rainfall affects vegetation productivity within Nylsvley, Ramsar site in Limpopo Province, South Africa. Daily rainfall data measured from eight rainfall stations between 1950 and 2016 were used to generate seasonal and annual rainfall data. Mann-Kendall and quantile regression were applied to assess trends in rainfall data. NDVI was derived from satellite images from between 1984 and 2003 using Zonal statistics and correlated with rainfall of the same period to assess vegetation dynamics. Mann-Kendall and Sen’s slope estimator showed only one station had a significant increasing rainfall trend annually and seasonally at p < 0.05, whereas all the other stations showed insignificant trends in both rainfall seasons. Quantile regression showed 50% and 62.5% of the stations had increasing annual and seasonal rainfall, respectively. Of the stations, 37.5% were statistically significant at p < 0.05, indicating increasing and decreasing rainfall trends. These rainfall trends show that the rainfall of Nylsvley decreased between 1995 and 2003. The R2 between rainfall and NDVI of Nylsvley is 55% indicating the influence of rainfall variability on vegetation productivity. The results underscore the impact of decadal rainfall patterns on wetland ecosystem change.

scholarly journals Monthly and Seasonal Rainfall Forecasting in Southern Brazil Using Multiple Discriminant Analysis

2016 ◽  
Vol 31 (6) ◽  
pp. 1947-1960 ◽  
Author(s):  
Denilson Ribeiro Viana ◽  
Clóvis Angeli Sansigolo
Keyword(s):  
Feature Extraction ◽  
Discriminant Analysis ◽  
Principal Component ◽  
Skill Score ◽  
Seasonal Rainfall ◽  
Rainfall Time Series ◽  
Southern Brazil ◽  
Multiple Discriminant Analysis ◽  
Rainfall Forecasting ◽  
Global Precipitation Climatology Centre

Abstract A multiple discriminant analysis was employed to forecast monthly and seasonal rainfall in southern Brazil. The methodology used includes six steps: data acquisition, preprocessing, feature extraction, feature selection, classification, and evaluation. The predictors (atmospheric, surface, and oceanic variables) and predictand (rainfall) were obtained from the Twentieth Century Reanalysis (version 2), as well as from the HadISST1 (Met Office Hadley Centre) and Global Precipitation Climatology Centre (GPCC) databases. The definition of key regions (feature extraction step) was performed using spatial principal component analysis. In the selection step, the rainfall time series were allocated into terciles, which were related to the predictors via multiple discriminating analyses. The results revealed that ⅓ of the predictors are associated with atmospheric pressure and also emphasized the role of atmospheric circulation over the Antarctic region and its surroundings. Surface variables (albedo and soil moisture) were also of great importance in the forecasting. The average skill score (gain over climatology) was 29%. It is concluded that the proposed model is a reliable alternative for use in forecasting monthly and seasonal rainfall over southern Brazil.

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.

scholarly journals Spatial Variability of Rainfall Trends in Sri Lanka from 1989 to 2019 as an Indication of Climate Change

2021 ◽  
Vol 10 (2) ◽  
pp. 84 ◽  
Author(s):  
Niranga Alahacoon ◽  
Mahesh Edirisinghe
Keyword(s):  
Climate Change ◽  
Sri Lanka ◽  
Spatial Variability ◽  
Rainfall Data ◽  
Spatial Data Analysis ◽  
Annual Rainfall ◽  
Climatic Zones ◽  
Rainfall Trends ◽  
Increased Risk ◽  
Semi Arid

Analysis of long-term rainfall trends provides a wealth of information on effective crop planning and water resource management, and a better understanding of climate variability over time. This study reveals the spatial variability of rainfall trends in Sri Lanka from 1989 to 2019 as an indication of climate change. The exclusivity of the study is the use of rainfall data that provide spatial variability instead of the traditional location-based approach. Henceforth, daily rainfall data available at Climate Hazards Group InfraRed Precipitation corrected with stations (CHIRPS) data were used for this study. The geographic information system (GIS) is used to perform spatial data analysis on both vector and raster data. Sen’s slope estimator and the Mann–Kendall (M–K) test are used to investigate the trends in annual and seasonal rainfall throughout all districts and climatic zones of Sri Lanka. The most important thing reflected in this study is that there has been a significant increase in annual rainfall from 1989 to 2019 in all climatic zones (wet, dry, intermediate, and Semi-arid) of Sri Lanka. The maximum increase is recorded in the wet zone and the minimum increase is in the semi-arid zone. There could be an increased risk of floods in the southern and western provinces in the future, whereas areas in the eastern and southeastern districts may face severe droughts during the northeastern monsoon. It is advisable to introduce effective drought and flood management and preparedness measures to reduce the respective hazard risk levels.

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 EI-Nino southern oscillation and rainfall varIation over Bangladesh

MAUSAM ◽  
2021 ◽  
Vol 47 (2) ◽  
pp. 157-162
Author(s):  
A. S. M. SABBIR AHMED ◽  
A. A. MUNIM ◽  
Q. N. BEGUM ◽  
A.M. Choudhury
Keyword(s):  
Southern Oscillation ◽  
Rainfall Data ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Rainfall Analysis ◽  
Rainfall Variation ◽  
Climatic Regions

In the present study, an attempt has been made to examine the variations of rainfall over Bangladesh and to find possible correlation with EI-Nino/Southern Oscillation (ENSO). Four stations have been chosen from four different climatic regions of Bangladesh for this purpose, namely  Jessore, Dhaka. Barisal and Srimangal. The regions have been classified according to annual rainfall amounts. The rainfall data for forty three years, (1950-1992) have been analysed. The yearly mean rainfall shows a distinct negative decreasing tendency with the occurrence of ENSO.The seasonal rainfall analysis shows a somewhat better correlation.  

scholarly journals Rain Erosion Maps for Wind Turbines Based on Geographical Locations: A Case Study in Ireland and Britain

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
K. Pugh ◽  
M. M. Stack
Keyword(s):  
Wind Turbine ◽  
Western Europe ◽  
Meteorological Data ◽  
Turbine Blades ◽  
Weather Conditions ◽  
Annual Rainfall ◽  
Wind Turbine Blades ◽  
Weather Patterns ◽  
The Uk

AbstractErosion rates of wind turbine blades are not constant, and they depend on many external factors including meteorological differences relating to global weather patterns. In order to track the degradation of the turbine blades, it is important to analyse the distribution and change in weather conditions across the country. This case study addresses rainfall in Western Europe using the UK and Ireland data to create a relationship between the erosion rate of wind turbine blades and rainfall for both countries. In order to match the appropriate erosion data to the meteorological data, 2 months of the annual rainfall were chosen, and the differences were analysed. The month of highest rain, January and month of least rain, May were selected for the study. The two variables were then combined with other data including hailstorm events and locations of wind turbine farms to create a general overview of erosion with relation to wind turbine blades.

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