Changes in monsoon rainfall distribution of Bangladesh using quantile regression model

Mohsenipour, Morteza; Shahid, Shamsuddin; Ziarh, Ghaith Falah; Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Zaher Mundher

doi:10.1007/s00704-020-03387-x

Cited by 23 publications

(19 citation statements)

References 55 publications

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“…The frequency of ESL events showed a similar seasonal variation with the heavy precipitation event, indicating that ESL events are triggered by high precipitation events (Figure 9a). The seasonal variation of high precipitation was also noticed in earlier studies [29,38,[56][57][58].…”

Section: Seasonal Variations Of the Impact Of Precipitationsupporting

confidence: 79%

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Influence of Terrestrial Precipitation on the Variability of Extreme Sea Levels along the Coast of Bangladesh

Islam

Sato

2021

Water

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The coastal area of Bangladesh is highly vulnerable to extreme sea levels because of high population exposure in the low-lying deltaic coast. Since the area lies in the monsoon region, abundant precipitation and the resultant increase in river discharge have raised a flood risk for the coastal area. Although the effects of atmospheric forces have been investigated intensively, the influence of precipitation on extreme sea levels in this area remains unknown. In this study, the influence of precipitation on extreme sea levels for three different stations were investigated by multivariate regression using the meteorological drivers of precipitation, sea level pressure, and wind. The prediction of sea levels considering precipitation effects outperformed predictions without precipitation. The benefit of incorporating precipitation was greater at Cox’s Bazar than at Charchanga and Khepupara, reflecting the hilly landscape at Cox’s Bazar. The improved prediction skill was mainly confirmed during the monsoon season, when strong precipitation events occur. It was also revealed that the precipitation over the Bangladesh area is insensitive to the El Niño-Southern Oscillation and Indian Ocean Dipole mode. The precipitation over northern Bangladesh tended to be high in the year of a high sea surface temperature over the Bay of Bengal, which may have contributed to the variation in sea level. The findings suggest that the effect of precipitation plays an essential role in enhancing sea levels during many extreme events. Therefore, incorporating the effect of terrestrial precipitation is essential for the better prediction of extreme sea levels, which helps coastal management and reduction of hazards.

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Section: Seasonal Variations Of the Impact Of Precipitationsupporting

confidence: 79%

“…Water 2021, 13, x FOR PEER REVIEW 12 of 20 events (Figure 9a). The seasonal variation of high precipitation was also noticed in earlier studies [29,38,[56][57][58]. Figure 10 shows the relationship between SLA and the R 2 difference between two predictions.…”

Section: Seasonal Variations Of the Impact Of Precipitationsupporting

confidence: 75%

Influence of Terrestrial Precipitation on the Variability of Extreme Sea Levels along the Coast of Bangladesh

Islam

Sato

2021

Water

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“…Over the last few decades, artificial intelligence (AI) models have found vast application in the modeling and estimation of various engineering and sciences problems [9]- [12]. However, a remarkable advancement has been observed within the natural process applications such as hydrology [13], [14], climate [15], morphologies [16], [17] and environnement [18], [19].…”

Section: Introductionmentioning

confidence: 99%

Dew Point Time Series Forecasting at the North Dakota

Arikan¹,

Jiechen²,

Sabbah³

et al. 2021

Kbes

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Hydrological time series forecasting is one of the hot topics in the domain of statistical hydrology. Providing accurate forecasting can contribute to diverse applications for catchment sustainability and management. Dew point temperature (Tdew) is one of the complex hydrological processes that highly essential to be quantified accurately for several catchment activities such as crops, agriculture, and others. In this study, three types of models’ recursive strategy, direct strategy, and DirRec which is the combination of recursive and direct strategies were adopted to obtain h-steps ahead predictions of Tdew. Ten years monthly scale dataset of Tdew at two meteorological stations (Beach and Cavalier) located at the North Dakota, USA, were used for the modeling development. The performance of the considered models was compared with two benchmark models: autoregressive moving average (ARIMA) and exponential smoothing (ETS). Modeling results indicated that, compared with the benchmark models, the proposed methods gave good results for the multi-ahead forecasting. For instance, for Cavalier station, the root mean squared prediction errors obtained from the proposed and benchmark methods when the forecast horizon is 12 are as follows: recursive strategy (RMSPE = 3.731) direct strategy (RMSPE = 3.385), DirRec (RMSPE = 3.141), ARIMA (RMSPE = 12.957), and ETS (RMSPE = 27.479).

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“…There are large variations of annual precipitation amount across the country, with maximum precipitation occurring in the northeastern region and the southeastern coastal region and minimum precipitation occurring in the western region (Tarek et al 2017;Ahmed et al 2020). Recent studies report a significant decreasing trend of precipitation in the western region of Bangladesh (Chowdhury et al 2019) and frequent precipitation extremes in the northeastern region of Bangladesh (Mohsenipour et al 2020), making Bangladesh more vulnerable to natural disasters.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of IMERG data in Bangladesh and surrounding regions and their application to studying diurnal variation of precipitation

Ahmed

Hong

Jin

et al. 2021

Theor Appl Climatol

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Satellite retrieval-based precipitation data with high spatial and temporal resolutions give an opportunity for precipitation research in regions with coarse networks of precipitation measuring instruments. This study evaluates the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) data in Bangladesh and surrounding regions and then examines the diurnal variation of precipitation in these regions using the cyclostationary empirical orthogonal function (CSEOF) analysis method. The IMERG data capture the overall patterns of the diurnal variation of precipitation well, except for the overestimation of the degree of diurnal variability in the pre-monsoon season. The spatial distribution of precipitation is also captured well, except for the drastic horizontal change in precipitation within the northeastern region of Bangladesh. These encourage the use of the IMERG data for studying precipitation characteristics in Bangladesh and surrounding regions. Through the CSEOF analysis, the pre-monsoonal precipitation is characterized by the enhanced precipitation in the northern region of Bangladesh and the Meghalaya Plateau region in the late night to early morning. The monsoonal precipitation consists of two contrasting CSEOF modes. One shows enhanced precipitation in the northern region of the Bay of Bengal during 0600-1500 LST, related to the strong westerly moisture transport over the Bay of Bengal. The other shows enhanced precipitation in the southern slopes of the Meghalaya Plateau and Himalayan Foothills during 0000-0600 LST, associated with the strong southwesterly moisture transport toward these slopes that is neither blocked nor deflected by the Arakan Mountains.

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Changes in monsoon rainfall distribution of Bangladesh using quantile regression model

Cited by 23 publications

References 55 publications

Influence of Terrestrial Precipitation on the Variability of Extreme Sea Levels along the Coast of Bangladesh

Influence of Terrestrial Precipitation on the Variability of Extreme Sea Levels along the Coast of Bangladesh

Dew Point Time Series Forecasting at the North Dakota

Evaluation of IMERG data in Bangladesh and surrounding regions and their application to studying diurnal variation of precipitation

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