Browsing by Author "Mallick, Javed"

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A review of recent advances and future prospects in calculation of reference evapotranspiration in Bangladesh using soft computing models
(Scopus, 2024) Alam, Md Mahfuz; Akter, Mst. Yeasmin; Reza, Abu; Islam, Md Towfiqul; Mallick, Javed; Kabir, Zobaidul; Chu, Ronghao; Arabameri, Alireza; Pal, Subodh Chandra; Masud, Md Abdullah Al; Costache, Romulus; Senapathi, Venkatramanan
Evapotranspiration (ETo) is a complex and non-linear hydrological process with a significant impact on efficient water resource planning and long-term management. The Penman-Monteith (PM) equation method, developed by the Food and Agriculture Organization of the United Nations (FAO), represents an advancement over earlier approaches for estimating ETo. Eto though reliable, faces limitations due to the requirement for climatological data not always available at specific locations. To address this, researchers have explored soft computing (SC) models as alternatives to conventional methods, known for their exceptional accuracy across disciplines. This critical review aims to enhance understanding of cutting-edge SC frameworks for ETo estimation, highlighting advancements in evolutionary models, hybrid and ensemble approaches, and optimization strategies. Recent applications of SC in various climatic zones in Bangladesh are evaluated, with the order of preference being ANFIS > Bi-LSTM > RT > DENFIS > SVR-PSOGWO > PSO–HFS due to their consistently high accuracy (RMSE and ). This review introduces a benchmark for incorporating evolutionary computation algorithms (EC) into ETo modeling. Each subsection addresses the strengths and weaknesses of known SC models, offering valuable insights. The review serves as a valuable resource for experienced water resource engineers and hydrologists, both domestically and internationally, providing comprehensive SC modeling studies for ETo forecasting. Furthermore, it provides an improved water resources monitoring and management plans.
Application of Optimal Subset Regression and Stacking Hybrid Models To Estimate COVID-19 Cases in Dhaka, Bangladesh
(Springer, 2023-08-16) Md, Abu Reza; Islam, Towfiqul; Elbeltagi, Ahmed; Mallick, Javed; Fattah, Md. Abdul; Roy, Manos Chandro; Pal, Subodh Chandra; Shahjaman, Md.; Patwary, Masum A.
The COVID-19 outbreaks revealed a severe healthcare crisis with many loopholes in the global healthcare system. It is more crucial to quantify COVID-19 cases when COVID-19 occurs in humid to semi-humid climatic conditions. There are issues with a lack of meteorological and air pollution data and future information on COVID-19 mortality, as is the case in Bangladesh. To deal with this issue, the present research aims to apply four single artificial intelligence models, including additive regression (AR), M5P tree (M5P), random subspace (RSS), and support vector machine (SVM), and construct their stacking hybrid ensemble models for predicting COVID-19 mortality cases at five sites in greater Dhaka City, Bangladesh. The proposed methods were developed using a total of eight input datasets that included climatic factors such as relative humidity, temperature, precipitation, wind speed, and air pollutants including sulfur dioxide (SO2), ozone (O3), carbon monoxide (CO), and nitrate oxide (NO2). Various input data combinations are appraised according to predictive performance, utilizing statistical tests and graphical presentation. The datasets were categorized into two classes (68:32) for model generation (training data) and model validation (testing data) with a fivefold cross-validation technique. Results show that SVM is superior to other AR, M5P, and RSS models (R2 testing = 0.86–0.91, MAE = 1.33–2.02, RMSE = 3.12–3.85, RAE% = 19.68–29.86, and RRSE% = 40.58–41.01). The sensitivity analysis findings reveal a higher sensitivity for all input parameters selected except CO in the predictive results. Relative humidity, wind speed, and SO2 were the three input parameters that most influenced the results of subset regression and sensitivity analysis. The SVM is a promising method because it can predict COVID-19 mortality in greater Dhaka City with fewer input parameters. The suggested model developed in this research produced satisfactory outcomes in COVID-19 mortality prediction. It will be a new method for future COVID-19 prevention for policymakers and health experts. Serious social concern and robust public health measures may lessen the environmental impact of COVID-19 cases.
Assessing Seismicity in Bangladesh: An Application of Guttenberg-Richter Relationship and Spectral Analysis
(Taylor & Francis Group, 2023-08-21) Islam, Abu Reza Md. Towfiqul; Akter, Mst. Yeasmin; Amanat, Sumaia; Alam, Edris; Sultana, Mst. Laila; Shahid, Shamsuddin; Das, Arnob; Peu, Susmita Datta; Mallick, Javed
Bangladesh has a high risk of earthquakes because the Dauki, Jamuna, and Chittagong-Myanmar faults are still active. However, the assessment of seismicity remains a big challenge due to the complex geologic setting of Bangladesh. This study employed the Guttenberg-Richter relationship and the spectral models to assess and analyze the earthquake conditions in Bangladesh. Besides, an instrumental earthquake catalogue, obtained from the Bangladesh Meteorological Department (BMD), covering 1985–2017, is established. The results revealed that the Guttenberg-Richter constants of a and b were 2.981 and 0.392, which propagated a strain release from 1992 to 2017. The spectral model analyses, e.g. wavelet transform (WT), short-time Fourier transformation (STFT), and multitaper model (MTM), demonstrated the magnitude and strain release anomalies of the same magnitude ranging from 4.8 to 5.7, indicating the probable precursor of an upcoming earthquake. Notably, magnitudes have been running around 4.5–5.8, which may act as a signal to major earthquakes that have not been evident before. The proposed models allowed for the completion of the Bangladesh earthquake catalogue and provided a platform for future seismicity assessment and earthquake probability analysis. These results should be considered in determining how likely earthquakes are to happen in an area or region.
Comparative Trend Variability Analysis of Reference Evapotranspiration in Bangladesh Using Multiple Trend Detection Approaches
(Scopus, 2024-06-10) Dia, Radia Biswas; Mallick, Javed; Aziz, Tarak; Fattah, Md Abdul; Ullah, Sami; Salam, Mohammed Abdus; Talukdar, Swapan; Chu, Ronghao; Islam, Abu Reza Md Towfiqul
The identification of trends in reference evapotranspiration (ETo) has an impact on regional and seasonal water resources, contributing to hydrological studies and effective water resource management. To that end, this study is intended to analyze the annual ETo variability and trend from eighteen meteorological stations in Bangladesh from 1975 to 2017 using the Mann-Kendall (MK) test, the Modified Mann-Kendall (MMK) test, the trend-free pre-whitening Mann-Kendall (TFPW MK) test, and the Innovative Trend Analysis (ITA). A comparative investigation of those trend detection methods was carried out using the Pearson and Spearman correlation coefficient matrices. The detrended fluctuation model (DFM) was also used to examine the future sustainability of the ETo trend. The MK and MMK test results show that fifteen and sixteen stations reported a negative trend, and of them, thirteen stations had significant negative trends (p < 0.01). The TFPW-MK test findings also reveal that thirteen stations had a significant negative trend (p < 0.01), while ITA identified seventeen stations as having significant negative trends (p < 0.01). Based on this study’s test results and performance, the MK test appeared to be the best-performing method within the MK test family because it outperformed the others (p < 0.01). DFM results depicted improved future ETo trends at seventeen locations, of which fourteen were significant. This study will be beneficial to climate-induced risks and provide a scientific base for rational guidelines for agricultural production in Bangladesh.
Comparative Trend Variability Analysis of Reference Evapotranspiration in Bangladesh Using Multiple Trend Detection Approaches
(Springer Nature, 2024-06-10) Dia, Radia Biswas; Mallick, Javed; Aziz, Tarak; Fattah, Md Abdul; Ullah, Sami; Salam, Mohammed Abdus; Talukdar, Swapan; Chu, Ronghao; Islam, Abu Reza Md Towfiqul
The identification of trends in reference evapotranspiration (ETo) has an impact on regional and seasonal water resources, contributing to hydrological studies and effective water resource management. To that end, this study is intended to analyze the annual ETo variability and trend from eighteen meteorological stations in Bangladesh from 1975 to 2017 using the Mann-Kendall (MK) test, the Modified Mann-Kendall (MMK) test, the trend-free pre-whitening Mann-Kendall (TFPW MK) test, and the Innovative Trend Analysis (ITA). A comparative investigation of those trend detection methods was carried out using the Pearson and Spearman correlation coefficient matrices. The detrended fluctuation model (DFM) was also used to examine the future sustainability of the ETo trend. The MK and MMK test results show that fifteen and sixteen stations reported a negative trend, and of them, thirteen stations had significant negative trends (p < 0.01). The TFPW-MK test findings also reveal that thirteen stations had a significant negative trend (p < 0.01), while ITA identified seventeen stations as having significant negative trends (p < 0.01). Based on this study’s test results and performance, the MK test appeared to be the best-performing method within the MK test family because it outperformed the others (p < 0.01). DFM results depicted improved future ETo trends at seventeen locations, of which fourteen were significant. This study will be beneficial to climate-induced risks and provide a scientific base for rational guidelines for agricultural production in Bangladesh.
Estimation of solar radiation in data-scarce subtropical region using ensemble learning models based on a novel CART-based feature selection
(2023-09-15) Azad, Md. Abul Kalam; Mallick, Javed; Towfiqul Islam, Abu Reza Md.; Ayen, Kurratul; Hasanuzzaman, Md.
Solar radiation estimation is essential with increasing energy demands for industrial and agricultural purposes to create a cleaner environment, negotiate climate change impacts, and attain sustainable development. However, the maintenance and operation of solar radiation measurements are costly due to the lack of pyranometers or their failure; hence, obtaining reliable solar radiation data is challenging in many subtropical regions. Despite its importance, a few studies use machine learning algorithms for solar radiation estimation in Bangladesh. To this end, this study contributes to filling the gap twofold. First, we presented the potentials of ensemble models, such as Bagging-REPT (reduced error pruning tree), random forest (RF), and Bagging-RF, which were compared to three standalone models, namely, Gaussian process regression (GPR), artificial neural network (ANN), and support vector machine (SVM), for estimating daily global solar radiation in three Bangladeshi regions. Second, we explore the optimal input parameters influencing solar radiation change at the regional scale using a classification and regression tree (CART)-based feature selection tool. Satellite-derived ERA5 reanalysis and NASA POWER project datasets were used as input parameters. The performance of the models was compared using performance evaluation metrics like correlation coefficient (r), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE), index of agreement (IA), and Taylor diagram. Results suggested that the RF model performed 5.47–37.22% better than the standalone models in estimating daily solar radiation at Chuadanga in terms of RMSE. Besides, the other ensemble model Bagging-RF showed 14.9–25.03% and 11.46–30.97% greater performances in Dinajpur and Satkhira than the conventional models in RMSE metric. Besides, this study may provide knowledge to the policymakers to make critical judgments on future energy yield, efficiency, productivity, and operation, which are essential elements for investments and solar energy conversion applications in the subtropical areas of the world.
Groundwater Level Fluctuations and Associated Influencing Factors in Rangpur District, Bangladesh, Using Modified Mann-Kendall and GIS-Based AHP Technique
(Springer Nature, 2023-06-22) Monir, Md. Moniruzzaman; Sarker, Subaran Chandra; Sarkar, Showmitra Kumar; Ahmed, Mohd.; Mallick, Javed; Islam, Abu Reza Md. Towfiqul
Analysis of groundwater level fluctuations is critical to understanding groundwater system dynamics and the factors that cause groundwater level fluctuations. Although most of the earlier studies focused on time series trend analysis using typical non-parametric tests, groundwater level fluctuations in drought-prone areas of northern Bangladesh are still poorly understood. To this end, the present study aims to analyze groundwater level fluctuations from 1980 to 2019 and associated influencing factors on groundwater level oscillation using the modified Mann-Kendall test and Pearson’s correlation method. Using GIS-based analytical hierarchical process (AHP) techniques, this study also identifies potential groundwater zones in the designated area. The result showed that 42.5% of monitoring wells had groundwater levels from 4.5 to 5.5 m during the pre-monsoon, whereas 57.5% had groundwater levels from 2.5 to 3.5 m during the monsoon in recent years. Based on the annual average groundwater level, the result showed that 62.5% of monitored wells had a declining trend, and 37.5% had an increasing trend from 2000 to 2019. A negative correlation was observed between groundwater level and rainfall in all monitoring wells, as the area’s rainfall impacted the groundwater level fluctuations. There was also a substantial positive correlation between groundwater levels, extraction, and potential evapotranspiration. The groundwater potential zone mapping shows three primary groundwater prospect categories: poor (1.9%), moderate (34.16%), and excellent (63.94%). The findings will assist planners and policymakers in allocating groundwater resources in various sectors such as agriculture, drinking water, and industry.
Impact of climate change on vector-borne diseases: Exploring hotspots, recent trends and future outlooks in Bangladesh
(2024-11-24) Jibon, Md. Jannatul Naeem; Prodhan Ruku, S.M. Ridwana; Towfiqul Islam, Abu Reza Md; Khan, Md. Nuruzzaman; Mallick, Javed; Mainul Bari, A.B.M.; Senapathi, Venkatramanan
Climate change is a significant risk multiplier and profoundly influences the transmission dynamics, geographical distribution, and resurgence of vector-borne diseases (VBDs). Bangladesh has a noticeable rise in VBDs attributed to climate change. Despite the severity of this issue, the interconnections between climate change and VBDs in Bangladesh have yet to be thoroughly explored. To address this research gap, our review meticulously examined existing literature on the relationship between climate change and VBDs in Bangladesh. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, we identified 3849 records from SCOPUS, Web of Science, and Google Scholar databases. Ultimately, 22 research articles meeting specific criteria were included. We identified that the literature on the subject matter of this study is non-contemporaneous, with 68% of studies investing datasets before 2014, despite studies on climate change and dengue nexus having increased recently. We pinpointed Dhaka and Chittagong Hill Tracts as the dengue and malaria research hotspots, respectively. We highlighted that the 2023 dengue outbreak illustrates a possible shift in dengue-endemic areas in Bangladesh. Moreover, dengue cases surged by 317% in 2023 compared to 2019 records, with a corresponding 607% increase in mortality compared to 2022. A weak connection was observed between dengue incidents and climate drivers, including the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). However, no compelling evidence supported an association between malaria cases, and Sea Surface Temperature (SST) in the Bay of Bengal, along with the NINO3 phenomenon. We observed minimal microclimatic and non-climatic data inclusion in selected studies. Our review holds implications for policymakers, urging the prioritization of mitigation measures such as year-round surveillance and early warning systems. Ultimately, it calls for resource allocation to empower researchers in advancing the understanding of VBD dynamics amidst changing climates.
Impact of Climate Change on Vector-borne Diseases: Exploring Hotspots, Recent Trends and Future Outlooks in Bangladesh
(Elsevier, 2024-11-15) Jibon, Md. Jannatul Naeem; Ruku, S.M. Ridwana Prodhan; Islam, Abu Reza Md Towfiqul; Khan, Md. Nuruzzaman; Mallick, Javed; Bari, A.B.M. Mainul; Senapathi, Venkatramanan
Climate change is a significant risk multiplier and profoundly influences the transmission dynamics, geographical distribution, and resurgence of vector-borne diseases (VBDs). Bangladesh has a noticeable rise in VBDs attributed to climate change. Despite the severity of this issue, the interconnections between climate change and VBDs in Bangladesh have yet to be thoroughly explored. To address this research gap, our review meticulously examined existing literature on the relationship between climate change and VBDs in Bangladesh. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, we identified 3849 records from SCOPUS, Web of Science, and Google Scholar databases. Ultimately, 22 research articles meeting specific criteria were included. We identified that the literature on the subject matter of this study is non-contemporaneous, with 68% of studies investing datasets before 2014, despite studies on climate change and dengue nexus having increased recently. We pinpointed Dhaka and Chittagong Hill Tracts as the dengue and malaria research hotspots, respectively. We highlighted that the 2023 dengue outbreak illustrates a possible shift in dengue-endemic areas in Bangladesh. Moreover, dengue cases surged by 317% in 2023 compared to 2019 records, with a corresponding 607% increase in mortality compared to 2022. A weak connection was observed between dengue incidents and climate drivers, including the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). However, no compelling evidence supported an association between malaria cases, and Sea Surface Temperature (SST) in the Bay of Bengal, along with the NINO3 phenomenon. We observed minimal microclimatic and non-climatic data inclusion in selected studies. Our review holds implications for policymakers, urging the prioritization of mitigation measures such as year-round surveillance and early warning systems. Ultimately, it calls for resource allocation to empower researchers in advancing the understanding of VBD dynamics amidst changing climates.
Modulation of coupling climatic extremes and their climate signals in a subtropical monsoon country
(2024-03-09) Md. Towfiqul Islam, Abu Reza; Akter, Mst. Yeasmin; Abdul Fattah, Md.; Mallick, Javed; Parvin, Ishita; Touhidul Islam, H. M.; Shahid, Shamsuddin; Kabir, Zobaidul; Kamruzzaman, Mohammad
The interaction between extreme precipitation and temperature events has significant implications for society, the economy, and the ecosystem. While numerous studies have explored changes in precipitation and temperature extremes in subtropical monsoon country, there is a dearth of knowledge regarding the coupling of these extremes, particularly the simultaneous occurrence of extreme events. To bridge this research gap, our study aims to investigate the modulation of coupling climatic extremes, their climate signals in subtropical monsoon country, and the underlying causes of changes. To accomplish this, we utilized monthly precipitation and temperature datasets from 20 sites across Bangladesh, along with two climate signal indices, covering the period from 1980 to 2017. We employed four indices, namely consecutive dry days (CDD), consecutive wet days (CWD), minimum daily temperature (TNn), and maximum daily temperature (TXx), to assess temperature and precipitation modulation patterns. Our findings indicate a positive trend in temperature indices, with warm days and nights exhibiting a more rapid increase compared to cool days and nights in Bangladesh. Analysis of precipitation indices reveals a mixed pattern of changes, with an increase in CWD and a decrease in CDD. However, when examining specific regions, we observe an increasing trend in monsoon CDD in the northwest and coastal districts, suggesting a shift towards drier conditions. Conversely, a declining trend in winter CDD in the southeast and northwest indicates a shift towards wetter conditions. Comparing coupled precipitation and temperature extremes between 1999 and 2017 and 1980–1998 reveals a broader impact of these extremes in recent decades. Detrended fluctuation analysis further suggests that the current trend in extremes is likely to persist in the future. Our study also establishes a relationship between the El Niño-Southern Oscillation (ENSO) and climate extremes in Bangladesh, albeit with modulations in cycles. Overall, a combination of elevated summer geopotential height, the absence of a visible anticyclonic center, reduced high cloud cover, and enhanced low cloud covers collectively contribute to increased frequency and intensity of warm extremes in subtropical country.
Quantification of Radiological Hazards Associated With Natural Radionuclides in Soil, Granite and Charnockite Rocks at Selected Fields in Ekiti State, Nigeria
(Springer Nature, 2023-11-02) Khan, M. Selimul Hasnian; Haque, Md. Emdadul; Ahmed, Mohd; Mallick, Javed; Islam, Abu Reza Md. Towfiqul; Fattah, Md. Abdul
"Despite being a vital agricultural zone and livable land for millions of people, the northwest region of Bangladesh is facing a scarcity of groundwater, which has become a major environmental stress in recent years. To this end, the present study intends to evaluate the current groundwater condition and simulate it to predict groundwater flow in the Phulbari and Parbatipur upazilas in the Dinajpur district of subtropical coal mine, northwest Bangladesh, by applying the Visual MODFLOW model. Water table data was analyzed to assess the linear trends of groundwater levels. The exploration of coal mining influenced the groundwater resources in the study area, where the groundwater table declined at a rate of 0.142 m/year. During the last 35 years (1985–2020), the groundwater table decreased by 2.28 m at Parbatipur Upazila. In Phulbari Upazila, the water table has been declining at a rate of 0.201 m/year and has declined by 4.58 m over the last 35 years. The average recharge and discharge of 658,207.56 m3/day and 658,209.81 m3/day, respectively, indicate a deficit in recharge of 2.25 m3/day or 2250 L/day in the study area. The prediction results show that the shortage of groundwater will increase to 246,375,000 L annually by 2050. The progressive decline of the groundwater table is possibly due to a lack of replenishment, overexploitation of groundwater resources, and underground coal mining impacts. Overall, the study will help in policy planning for sustainable water resource management, waste supply, environmental protection and disaster preparedness."
Quantitative analysis and modeling of groundwater flow using visual MODFLOW: a case from subtropical coal mine, northwest Bangladesh
(Scopus, 2023-11-03) Khan, M. Selimul Hasnian; Haque, Md. Emdadul; Ahmed, Mohd.; Mallick, Javed; Reza, Abu; Islam, Md. Towfiqul; Fattah, Md. Abdul
Despite being a vital agricultural zone and livable land for millions of people, the northwest region of Bangladesh is facing a scarcity of groundwater, which has become a major environmental stress in recent years. To this end, the present study intends to evaluate the current groundwater condition and simulate it to predict groundwater flow in the Phulbari and Parbatipur upazilas in the Dinajpur district of subtropical coal mine, northwest Bangladesh, by applying the Visual MODFLOW model. Water table data was analyzed to assess the linear trends of groundwater levels. The exploration of coal mining influenced the groundwater resources in the study area, where the groundwater table declined at a rate of 0.142 m/year. During the last 35 years (1985–2020), the groundwater table decreased by 2.28 m at Parbatipur Upazila. In Phulbari Upazila, the water table has been declining at a rate of 0.201 m/year and has declined by 4.58 m over the last 35 years. The average recharge and discharge of 658,207.56 m3/day and 658,209.81 m3/day, respectively, indicate a deficit in recharge of 2.25 m3/day or 2250 L/day in the study area. The prediction results show that the shortage of groundwater will increase to 246,375,000 L annually by 2050. The progressive decline of the groundwater table is possibly due to a lack of replenishment, overexploitation of groundwater resources, and underground coal mining impacts. Overall, the study will help in policy planning for sustainable water resource management, waste supply, environmental protection and disaster preparedness.
Quantitative Analysis and Modeling of Groundwater Flow Using Visual Modflow: A Case from Subtropical Coal Mine, Northwest Bangladesh
(Springer Nature, 2023-11-02) Khan, M. Selimul Hasnian; Haque, Md. Emdadul; Ahmed, Mohd.; Mallick, Javed; Islam, Abu Reza Md. Towfiqul; Fattah, Md. Abdul
Despite being a vital agricultural zone and livable land for millions of people, the northwest region of Bangladesh is facing a scarcity of groundwater, which has become a major environmental stress in recent years. To this end, the present study intends to evaluate the current groundwater condition and simulate it to predict groundwater flow in the Phulbari and Parbatipur upazilas in the Dinajpur district of subtropical coal mine, northwest Bangladesh, by applying the Visual MODFLOW model. Water table data was analyzed to assess the linear trends of groundwater levels. The exploration of coal mining influenced the groundwater resources in the study area, where the groundwater table declined at a rate of 0.142 m/year. During the last 35 years (1985–2020), the groundwater table decreased by 2.28 m at Parbatipur Upazila. In Phulbari Upazila, the water table has been declining at a rate of 0.201 m/year and has declined by 4.58 m over the last 35 years. The average recharge and discharge of 658,207.56 m3/day and 658,209.81 m3/day, respectively, indicate a deficit in recharge of 2.25 m3/day or 2250 L/day in the study area. The prediction results show that the shortage of groundwater will increase to 246,375,000 L annually by 2050. The progressive decline of the groundwater table is possibly due to a lack of replenishment, overexploitation of groundwater resources, and underground coal mining impacts. Overall, the study will help in policy planning for sustainable water resource management, waste supply, environmental protection and disaster preparedness.
Seasonality of Meteorological Factors Influencing the COVID-19 Era in Coastal and Inland Regions of Bangladesh
(Taylor & Francis Group, 2023-04-25) Sakib, Syed Nazmus; Islam, Abu Reza Md. Towfiqul; Azad, Md. Abul Kalam; Mallick, Javed; Ahmed, Mohd.; Pal, Subodh Chandra; Islam, Md. Saiful; Hu, Zhenghua; Alam, Edris; Malafaia, Guilherme
We aim to explore the seasonal influences of meteorological factors on COVID-19 era over two distinct locations in Bangladesh using a generalized linear model (GLM) and wavelet analysis. GLM model findings show that summer humidity drives COVID-19 transmission to coastal and inland locations. During the summer in the coastal area, a 1 °C earth’s skin temperature increase causes a 41.9% increase in COVID (95% CL 86.32%-2.54%) transmission compared to inland. Relative humidity was recorded as the highest at 73.97% (95% CL, 99.3%, and 48.63%) for the coastal region, while wind speed and precipitation reduced confirmed cases by −38.62% and −22.15%, respectively. Wavelet analysis showed that coastal meteorological parameters were more coherent with COVID-19 than inland ones. The outcomes of this study are consistent with subtropical climate regions. Seasonality and climatic similarity should address to estimate COVID-19 trends. High societal concern and strong public health measures may decrease meteorological effect on COVID-19.
Temperature extremes Projections over Bangladesh from CMIP6 Multi-model Ensemble
(Scopus, 2024-08-31) Akter, Mst Yeasmin; Islam, Abu Reza Md Towfiqul; Mallick, Javed; Alam, Md Mahfuz; Alam, Edris; Shahid, Shamsuddin; Biswas, Jatish Chandra; Alam, GM Manirul; Pal, Subodh Chandra; Oliver, Md Moinul Hosain
Bangladesh, a sub-tropical monsoon climate with low-lying areas, is very susceptible to the impacts of climate change. However, there has been a shortage of studies about the periodicity and projected changes in extreme temperature in this area, which is a crucial part of adapting to climate change. A study employed a multimodal ensemble (MME) mean of 13 bias-corrected CMIP6 GCMs to fill this knowledge gap. The purpose of this study was to project changes in 8 extreme temperature indices (ETIs) across Bangladesh for the near future (2021–2060) and far future (2061–2100) under two different Shared Socioeconomic Pathways (SSPs): medium (SSP2-4.5) and high (SSP5-8.5) scenarios. The research analyzed the average spatiotemporal changes by considering the reference period from 1995 to 2014 for each indicator in future periods. The results indicate that Bangladesh is projected to see a rise in average annual temperature in the 21st century, aligning with the global average. Warm days (TX90p) and nights (TN90p) were projected to increase, while cold days (TX10p) and nights (TN10p) were expected to decrease across the country for both the near (2021–2060) and far future (2061–2100). The projected highest increase in TX90p and TN90p was 6.90 days/decade in the northeast, and the highest decrease in TX10p and TN10p was 6.22 days/decade in the southwest. The study revealed a higher rise in TN90p than TX90p, indicating a faster decline in cold extremes than a rise in hot extremes. The rising temperature would cause an increase in the spell duration index (WSDI) and growing degree day (GDD) by 5–6 and 6–7 days/decade, respectively. Therefore, immediate measures must be taken to mitigate the detrimental effects of extreme temperatures, leading to heat stress. To reduce the effects on agriculture, ecosystems, human health, and biodiversity, policymakers and stakeholders must understand these anticipated changes and adopt appropriate actions.
Temperature extremes Projections over Bangladesh from CMIP6 Multi-model Ensemble
(Springer Nature, 2024-08-24) Akter, Mst Yeasmin; Islam, Abu Reza Md Towfiqul; Mallick, Javed; Alam, Md Mahfuz; Alam, Edris; Shahid, Shamsuddin; Biswas, Jatish Chandra; Alam, GM Manirul; Pal, Subodh Chandra; Oliver, Md Moinul Hosain
Bangladesh, a sub-tropical monsoon climate with low-lying areas, is very susceptible to the impacts of climate change. However, there has been a shortage of studies about the periodicity and projected changes in extreme temperature in this area, which is a crucial part of adapting to climate change. A study employed a multimodal ensemble (MME) mean of 13 bias-corrected CMIP6 GCMs to fill this knowledge gap. The purpose of this study was to project changes in 8 extreme temperature indices (ETIs) across Bangladesh for the near future (2021–2060) and far future (2061–2100) under two different Shared Socioeconomic Pathways (SSPs): medium (SSP2-4.5) and high (SSP5-8.5) scenarios. The research analyzed the average spatiotemporal changes by considering the reference period from 1995 to 2014 for each indicator in future periods. The results indicate that Bangladesh is projected to see a rise in average annual temperature in the 21st century, aligning with the global average. Warm days (TX90p) and nights (TN90p) were projected to increase, while cold days (TX10p) and nights (TN10p) were expected to decrease across the country for both the near (2021–2060) and far future (2061–2100). The projected highest increase in TX90p and TN90p was 6.90 days/decade in the northeast, and the highest decrease in TX10p and TN10p was 6.22 days/decade in the southwest. The study revealed a higher rise in TN90p than TX90p, indicating a faster decline in cold extremes than a rise in hot extremes. The rising temperature would cause an increase in the spell duration index (WSDI) and growing degree day (GDD) by 5–6 and 6–7 days/decade, respectively. Therefore, immediate measures must be taken to mitigate the detrimental effects of extreme temperatures, leading to heat stress. To reduce the effects on agriculture, ecosystems, human health, and biodiversity, policymakers and stakeholders must understand these anticipated changes and adopt appropriate actions.
Temperature Extremes Projections Over Bangladesh From Cmip6 Multi-model Ensemble
(Springer Nature, 2024-08-31) Akter, Mst Yeasmin; Islam, Abu Reza Md Towfiqul; Mallick, Javed; Alam, Md Mahfuz; Alam, Edris; Shahid, Shamsuddin; Biswas, Jatish Chandra; Alam, GM Manirul; Pal, Subodh Chandra; Oliver, Md Moinul Hosain
Bangladesh, a sub-tropical monsoon climate with low-lying areas, is very susceptible to the impacts of climate change. However, there has been a shortage of studies about the periodicity and projected changes in extreme temperature in this area, which is a crucial part of adapting to climate change. A study employed a multimodal ensemble (MME) mean of 13 bias-corrected CMIP6 GCMs to fill this knowledge gap. The purpose of this study was to project changes in 8 extreme temperature indices (ETIs) across Bangladesh for the near future (2021–2060) and far future (2061–2100) under two different Shared Socioeconomic Pathways (SSPs): medium (SSP2-4.5) and high (SSP5-8.5) scenarios. The research analyzed the average spatiotemporal changes by considering the reference period from 1995 to 2014 for each indicator in future periods. The results indicate that Bangladesh is projected to see a rise in average annual temperature in the 21st century, aligning with the global average. Warm days (TX90p) and nights (TN90p) were projected to increase, while cold days (TX10p) and nights (TN10p) were expected to decrease across the country for both the near (2021–2060) and far future (2061–2100). The projected highest increase in TX90p and TN90p was 6.90 days/decade in the northeast, and the highest decrease in TX10p and TN10p was 6.22 days/decade in the southwest. The study revealed a higher rise in TN90p than TX90p, indicating a faster decline in cold extremes than a rise in hot extremes. The rising temperature would cause an increase in the spell duration index (WSDI) and growing degree day (GDD) by 5–6 and 6–7 days/decade, respectively. Therefore, immediate measures must be taken to mitigate the detrimental effects of extreme temperatures, leading to heat stress. To reduce the effects on agriculture, ecosystems, human health, and biodiversity, policymakers and stakeholders must understand these anticipated changes and adopt appropriate actions.