Ruksana H. Rimi | Mawlana Bhashani Science and Technology University (original) (raw)

Papers by Ruksana H. Rimi

2017 AGU Fall Meeting, Dec 13, 2017

Journal of the Asiatic Society of Bangladesh. Science, Jun 29, 2021

The study was conducted to quantify the change of selected climatic variables (rainfall, relative... more The study was conducted to quantify the change of selected climatic variables (rainfall, relative humidity, maximum and minimum temperature) over 50 years at Rajshahi and Sylhet districts in Bangladesh. Annual, seasonal, and monthly climatic data comparisons have been executed between 1968-1992 and 1993-2017 through trend analysis. The Mann-Kendall statistic and Sen's Slope model were used to reveal the trends and estimate the magnitude of change respectively. Prediction of the climatic variable of 10 years (2018-2027) was made based on the ARAR algorithm using MaxStat Pro software. Rainfall data were used to analyze drought by using climatic indices (De Mortone Aridity Index, IdM; Seleaninov Hydrothermic Index, IhS; Donciu Climate Index, IcD). Average rainfall was decreasing dramatically in monsoon season at Rajshahi and in both premonsoon and monsoon seasons at Sylhet. The negative change of average rainfall in the monsoon at Rajshahi from 1968-1992 to 1993-2017 was found 29.17 mm. The maximum temperature was increasing in all seasons in both Rajshahi and Sylhet. Annual Mannkendall trend test and Sen's slope revealed that relative humidity was decreasing and maximum temperature was increasing significantly at Sylhet for the period 1993-2017. At Rajshahi, during 1968-1992, relative humidity was increasing by 0.247 % per year, and minimum temperature was decreasing 0.049℃ per year. Rainfall was decreasing insignificantly in both time scales. ARAR algorithm predicted that average maximum temperature might become comparatively higher than the previous 50 years.

Hydrology and Earth System Sciences, Nov 15, 2022

International Journal of Climatology, Mar 18, 2019

Potential increases in the risk of extreme weather events under climate change can have significa... more Potential increases in the risk of extreme weather events under climate change can have significant socioeconomic impacts at regional levels. These impacts are likely to be particularly high in South Asia where Bangladesh is one of the most vulnerable countries. Regional climate models (RCMs) are valuable tools for studying weather and climate at finer spatial scales than are typically available in global climate models. Quantitative assessment of the likely changes in the risk of extreme events occurring requires very large ensemble simulations due to their rarity. The weather@home setup within the climateprediction.net distributed computing project is capable of providing the necessary very large ensembles at regionally higher resolution, but has only been evaluated over the South Asia region for its representation of seasonal climatological and monthly means. Here, we evaluate how realistically the HadAM3P-HadRM3P model setup of weather@home can reproduce the observed patterns of temperature and rainfall in Bangladesh with focus on the modelled extreme events. Using very large ensembles of regional simulations, we find that there are substantial spatial and temporal variations in rainfall and temperature biases compared with observations. These are highest in the pre-monsoon, which are largely caused by timing issues in the model. Modelled mean monsoon and post-monsoon temperatures are in good agreement This article is protected by copyright. All rights reserved. This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

Bulletin of the American Meteorological Society, 2019

A bushfire that started near Leadvill, east of Duneedoo in the New South Wales (NSW) Central tabl... more A bushfire that started near Leadvill, east of Duneedoo in the New South Wales (NSW) Central tablelands, ripped through bush and grasslands in a day that NSW fire authorities classified as catastrophic. Sheep and cattle maneuver around a dam to avoid a fast running bushfire as the fire front moved east. Photograph by Dean Sewell/Oculi.

Fig. S1 shows the seasonal cycle of daily rainfall for both observations (CPC, ERA-int and GPCC) ... more Fig. S1 shows the seasonal cycle of daily rainfall for both observations (CPC, ERA-int and GPCC) and the EC-Earth model. It shows that in the model, as expected, most precipitation falls in the months JJA, with a peak in July, like in observations, though the increase in precipitation is slightly steeper in June than it is in observations. The average amount of rainfall in these months is comparable to the observational datasets, with a maximum of around 10 mm/day. It is worth noting that CPC tends to underestimate the precipitation at higher elevations due to a lack of available station data. 2 weather@home The annual cycle of 10-day running mean precipitation in the Brahmaputra basin from weather@home Historical simulations is compared to CPC, GPCC and TRMM observational records in figure S2. Note TRMM is also included for reference but since data is not available post 2015 it is excluded from the rest of the analysis. Within the monsoon season the mean magnitude of precipitation within weather@home shows reasonable agreement with observational estimates, although the variability of precipitation in this period is too small. In the pre-monsoon season weather@home precipitation is too high and therefore the monsoon onset appears to occur too early within the model. Comparing the spatial agreement of JJAS mean precipitation (not shown) shows that, although model output is noisier, the magnitude and pattern of weather@home output agrees well with GPCC and CPC observations.

Anthropogenic climate change is likely to increase the frequency of extreme weather events in fut... more Anthropogenic climate change is likely to increase the frequency of extreme weather events in future. Previous studies have robustly shown how and where climate change has already changed the risks of weather extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of seasonal extreme rainfall events in 15 Bangladesh under the Paris Agreement temperature goals of 1.5°C and 2°C warming above pre-industrial levels. In particular, we investigate the influence of anthropogenic aerosols on these risks given their likely future reduction and resulting amplification of global warming. Using large ensemble regional climate model simulations from weather@home under different forcing scenarios, we compare the risks of rainfall events under pre-industrial (natural), current (actual), 1.5°C, and 2.0°C warmer and greenhouse gas only (anthropogenic aerosols removed) conditions. We find that the risk of a 1 in 100 year rainfall event has already increased 20 significantly compared with pre-industrial levels across parts of Bangladesh, with additional increases likely for 1.5 and 2.0 degree warming (of up to 5.5 times higher, with an uncertainty range of 3.5 to 7.8 times). Impacts were observed during both the pre-monsoon and monsoon periods, but were spatially variable across the country in terms of the level of impact. Results also show that reduction in anthropogenic aerosols plays an important role in determining the overall future climate change impacts; by exacerbating the effects of GHG induced global warming and thereby increasing the rainfall intensity. We highlight that the net 25 aerosol effect varies from region to region within Bangladesh, which leads to different outcomes of aerosol reduction on extreme rainfall statistics, and must therefore be considered in future risk assessments. Whilst there is a substantial reduction in the impacts resulting from 1.5°C compared with 2°C warming, the difference is spatially and temporally variable, specifically with respect to seasonal extreme rainfall events. 30 1 Introduction The 2015 Paris Agreement of the United Nations Framework Convention on Climate Change (UNFCCC), on "Holding the increase in the global average temperature to well below 2°C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5°C" (Department of the Environment and Energy, 2015), needs strong support from research on the nature, benefits and feasibility of this challenging goal. This Agreement calls for the quantification and comparison between the 35 impacts of 1.5C versus 2.0C warmer global temperatures on different climate related aspects such as extreme weather events. While assessing both risks and vulnerabilities to incremental increases in global mean temperature, the discrimination of the impacts of different radiative forcing contributions as well as the quantification of spatially varying changes in risk are crucially important. For example, highly unusual heat extremes that are virtually absent in the present climate in South Asia, would affect around 15% of land area of this region under 1.5°C and around 20% of land area under 2°C warming (The World 40 Bank, 2012). The increase in heavy monsoon rainfall intensity for South Asia is projected to be 7% under 1.5°C and 10% under 2°C warming compared to pre-industrial conditions (Schleussner et al., 2016). Populations of this region largely depend on the stability of the monsoon, which provides water resources for agricultural production (The World Bank, 2012). It is

In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This pa... more In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This paper presents for the first time an attribution of this precipitation-induced flooding from a combined meteorological and hydrological perspective. Experiments were conducted with three observational data sets and two climate models to estimate changes in extreme 10-day precipitation event frequency over the Brahmaputra basin. The precipitation fields were then used as meteorological input for four different hydrological models to estimate the corresponding changes in river discharge, allowing for comparison between approaches and for the robustness of the attribution results to be assessed. In all three observational precipitation data sets the climate change trends for extreme precipitation similar to observed in August 2017 are not significant, however in two out of three series, the sign of this insignificant trend is positive. One climate model shows a significant positive influence of anthropogenic climate change, whereas the other simulates a cancellation between the increase due to greenhouse gases and a decrease due to sulphate aerosols. Considering discharge rather than precipitation, the hydrological models show that attribution of the change in discharge towards higher values is somewhat less uncertain than for precipitation, but the 95% confidence interval still encompasses no change in risk. For the future, all models project an increase in probability of extreme events at 2 • C global heating since pre-industrial times, becoming more than 1.7 times more likely for high 10-day precipitation, and about a factor 1.5 more likely for discharge. Our best estimate on the trend in flooding events similar to the Brahmaputra event of August 2017 is derived by synthesizing the observational and model results: We find the change in risk to be greater than one and of similar order of magnitude (between 1 and 2) for both the meteorological and hydrological approach. This study shows that, for precipitation-induced flooding events, investigating changes in precipitation is useful, either as an alternative when hydrological models are not available, or as an additional measure to confirm qualitative conclusions. Besides, it highlights the importance of using multiple models in attribution studies,

Social Science Research Network, Jul 1, 2013

This study was conducted to investigate the changes of climate, salinity and their consequent imp... more This study was conducted to investigate the changes of climate, salinity and their consequent impacts on shrimp production at Shyamnagar under Satkhira District, Bangladesh. An integrated technique was used including social survey, historical climate data, shrimp production data and field analysis. During 1980-2009, a statistically significant decreasing trend of annual average maximu m temperature but increasing trend of annual average minimu m temperature was found. Maximu m temperature exhibited significant decreasing trend in post-monsoon while, increasing trend in winter. The trend of minimu m temperature was increasing significantly in post monsoon. Significant increase in relat ive humidity trends were found in all seasons. Salin ity levels of the shrimp farm waters were found to exceed the threshold limits for proper shrimp production. Although the total production was increasin g, the rate of shrimp production was decreasing relative to total area of farms. No statistically significant relationships were found between the annual shrimp production and climatic parameters or salin ity levels. Depths of inundation at monsoon season exceeded 180 cm, on contrary, at dry season less than 30 cm which was not proper for shrimps. The surface water salinity ranged from 7-46 ppt making farm waters unsuitable for shrimp production. According to the GM (1,1) model, the production of shrimp was hampered by climat ic hazards, increasing inundations and salinity problems.

Weather and Climate Extremes, 2015

This study was conducted to investigate the changes of climate, salinity and their consequent imp... more This study was conducted to investigate the changes of climate, salinity and their consequent impacts on shrimp production at Shyamnagar under Satkhira District, Bangladesh. An integrated technique was used including social survey, historical climate data, shrimp production data and field analysis. During 1980-2009, a statistically significant decreasing trend of annual average maximu m temperature but increasing trend of annual average minimu m temperature was found. Maximu m temperature exhibited significant decreasing trend in post-monsoon while, increasing trend in winter. The trend of minimu m temperature was increasing significantly in post monsoon. Significant increase in relat ive humidity trends were found in all seasons. Salin ity levels of the shrimp farm waters were found to exceed the threshold limits for proper shrimp production. Although the total production was increasin g, the rate of shrimp production was decreasing relative to total area of farms. No statistically...

Anthropogenic climate change is likely to increase the frequency risk of extreme weather events i... more Anthropogenic climate change is likely to increase the frequency risk of extreme weather events in the future. The term ‘risk’ here means the probability of occurrence of a hazard, e.g., an extreme rainfall event that can trigger sudden flash-flood, landslide or flood. Previous studies have robustly shown how and where climate change has already changed the risks of weather 15 extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of extreme rainfall events in Bangladesh under the Paris Agreement temperature goals of 1.5°C and 2°C warming above pre-industrial levels. In particular, we investigate the influence of anthropogenic aerosols on these risks given their likely f...

Hydrology and Earth System Sciences Discussions

Anthropogenic climate change is likely to increase the frequency of extreme weather events in fut... more Anthropogenic climate change is likely to increase the frequency of extreme weather events in future. Previous studies have robustly shown how and where climate change has already changed the risks of weather extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of seasonal extreme rainfall events in 15

International Journal of Climatology

Hydrology and Earth System Sciences Discussions

In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This pa... more In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This paper presents for the first time an attribution of this precipitation-induced flooding from a combined meteorological and hydrological perspective.

Bulletin of the American Meteorological Society

Anthropogenic climate change doubled the likelihood of the 2017 pre-monsoon extreme 6-day rainfal... more Anthropogenic climate change doubled the likelihood of the 2017 pre-monsoon extreme 6-day rainfall event at northeast Bangladesh. The magnitude of this contribution is sensitive to the climatological period in use.

2017 AGU Fall Meeting, Dec 13, 2017

Journal of the Asiatic Society of Bangladesh. Science, Jun 29, 2021

The study was conducted to quantify the change of selected climatic variables (rainfall, relative... more The study was conducted to quantify the change of selected climatic variables (rainfall, relative humidity, maximum and minimum temperature) over 50 years at Rajshahi and Sylhet districts in Bangladesh. Annual, seasonal, and monthly climatic data comparisons have been executed between 1968-1992 and 1993-2017 through trend analysis. The Mann-Kendall statistic and Sen's Slope model were used to reveal the trends and estimate the magnitude of change respectively. Prediction of the climatic variable of 10 years (2018-2027) was made based on the ARAR algorithm using MaxStat Pro software. Rainfall data were used to analyze drought by using climatic indices (De Mortone Aridity Index, IdM; Seleaninov Hydrothermic Index, IhS; Donciu Climate Index, IcD). Average rainfall was decreasing dramatically in monsoon season at Rajshahi and in both premonsoon and monsoon seasons at Sylhet. The negative change of average rainfall in the monsoon at Rajshahi from 1968-1992 to 1993-2017 was found 29.17 mm. The maximum temperature was increasing in all seasons in both Rajshahi and Sylhet. Annual Mannkendall trend test and Sen's slope revealed that relative humidity was decreasing and maximum temperature was increasing significantly at Sylhet for the period 1993-2017. At Rajshahi, during 1968-1992, relative humidity was increasing by 0.247 % per year, and minimum temperature was decreasing 0.049℃ per year. Rainfall was decreasing insignificantly in both time scales. ARAR algorithm predicted that average maximum temperature might become comparatively higher than the previous 50 years.

Hydrology and Earth System Sciences, Nov 15, 2022

International Journal of Climatology, Mar 18, 2019

Potential increases in the risk of extreme weather events under climate change can have significa... more Potential increases in the risk of extreme weather events under climate change can have significant socioeconomic impacts at regional levels. These impacts are likely to be particularly high in South Asia where Bangladesh is one of the most vulnerable countries. Regional climate models (RCMs) are valuable tools for studying weather and climate at finer spatial scales than are typically available in global climate models. Quantitative assessment of the likely changes in the risk of extreme events occurring requires very large ensemble simulations due to their rarity. The weather@home setup within the climateprediction.net distributed computing project is capable of providing the necessary very large ensembles at regionally higher resolution, but has only been evaluated over the South Asia region for its representation of seasonal climatological and monthly means. Here, we evaluate how realistically the HadAM3P-HadRM3P model setup of weather@home can reproduce the observed patterns of temperature and rainfall in Bangladesh with focus on the modelled extreme events. Using very large ensembles of regional simulations, we find that there are substantial spatial and temporal variations in rainfall and temperature biases compared with observations. These are highest in the pre-monsoon, which are largely caused by timing issues in the model. Modelled mean monsoon and post-monsoon temperatures are in good agreement This article is protected by copyright. All rights reserved. This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

Bulletin of the American Meteorological Society, 2019

A bushfire that started near Leadvill, east of Duneedoo in the New South Wales (NSW) Central tabl... more A bushfire that started near Leadvill, east of Duneedoo in the New South Wales (NSW) Central tablelands, ripped through bush and grasslands in a day that NSW fire authorities classified as catastrophic. Sheep and cattle maneuver around a dam to avoid a fast running bushfire as the fire front moved east. Photograph by Dean Sewell/Oculi.

Fig. S1 shows the seasonal cycle of daily rainfall for both observations (CPC, ERA-int and GPCC) ... more Fig. S1 shows the seasonal cycle of daily rainfall for both observations (CPC, ERA-int and GPCC) and the EC-Earth model. It shows that in the model, as expected, most precipitation falls in the months JJA, with a peak in July, like in observations, though the increase in precipitation is slightly steeper in June than it is in observations. The average amount of rainfall in these months is comparable to the observational datasets, with a maximum of around 10 mm/day. It is worth noting that CPC tends to underestimate the precipitation at higher elevations due to a lack of available station data. 2 weather@home The annual cycle of 10-day running mean precipitation in the Brahmaputra basin from weather@home Historical simulations is compared to CPC, GPCC and TRMM observational records in figure S2. Note TRMM is also included for reference but since data is not available post 2015 it is excluded from the rest of the analysis. Within the monsoon season the mean magnitude of precipitation within weather@home shows reasonable agreement with observational estimates, although the variability of precipitation in this period is too small. In the pre-monsoon season weather@home precipitation is too high and therefore the monsoon onset appears to occur too early within the model. Comparing the spatial agreement of JJAS mean precipitation (not shown) shows that, although model output is noisier, the magnitude and pattern of weather@home output agrees well with GPCC and CPC observations.

Anthropogenic climate change is likely to increase the frequency of extreme weather events in fut... more Anthropogenic climate change is likely to increase the frequency of extreme weather events in future. Previous studies have robustly shown how and where climate change has already changed the risks of weather extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of seasonal extreme rainfall events in 15 Bangladesh under the Paris Agreement temperature goals of 1.5°C and 2°C warming above pre-industrial levels. In particular, we investigate the influence of anthropogenic aerosols on these risks given their likely future reduction and resulting amplification of global warming. Using large ensemble regional climate model simulations from weather@home under different forcing scenarios, we compare the risks of rainfall events under pre-industrial (natural), current (actual), 1.5°C, and 2.0°C warmer and greenhouse gas only (anthropogenic aerosols removed) conditions. We find that the risk of a 1 in 100 year rainfall event has already increased 20 significantly compared with pre-industrial levels across parts of Bangladesh, with additional increases likely for 1.5 and 2.0 degree warming (of up to 5.5 times higher, with an uncertainty range of 3.5 to 7.8 times). Impacts were observed during both the pre-monsoon and monsoon periods, but were spatially variable across the country in terms of the level of impact. Results also show that reduction in anthropogenic aerosols plays an important role in determining the overall future climate change impacts; by exacerbating the effects of GHG induced global warming and thereby increasing the rainfall intensity. We highlight that the net 25 aerosol effect varies from region to region within Bangladesh, which leads to different outcomes of aerosol reduction on extreme rainfall statistics, and must therefore be considered in future risk assessments. Whilst there is a substantial reduction in the impacts resulting from 1.5°C compared with 2°C warming, the difference is spatially and temporally variable, specifically with respect to seasonal extreme rainfall events. 30 1 Introduction The 2015 Paris Agreement of the United Nations Framework Convention on Climate Change (UNFCCC), on "Holding the increase in the global average temperature to well below 2°C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5°C" (Department of the Environment and Energy, 2015), needs strong support from research on the nature, benefits and feasibility of this challenging goal. This Agreement calls for the quantification and comparison between the 35 impacts of 1.5C versus 2.0C warmer global temperatures on different climate related aspects such as extreme weather events. While assessing both risks and vulnerabilities to incremental increases in global mean temperature, the discrimination of the impacts of different radiative forcing contributions as well as the quantification of spatially varying changes in risk are crucially important. For example, highly unusual heat extremes that are virtually absent in the present climate in South Asia, would affect around 15% of land area of this region under 1.5°C and around 20% of land area under 2°C warming (The World 40 Bank, 2012). The increase in heavy monsoon rainfall intensity for South Asia is projected to be 7% under 1.5°C and 10% under 2°C warming compared to pre-industrial conditions (Schleussner et al., 2016). Populations of this region largely depend on the stability of the monsoon, which provides water resources for agricultural production (The World Bank, 2012). It is

In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This pa... more In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This paper presents for the first time an attribution of this precipitation-induced flooding from a combined meteorological and hydrological perspective. Experiments were conducted with three observational data sets and two climate models to estimate changes in extreme 10-day precipitation event frequency over the Brahmaputra basin. The precipitation fields were then used as meteorological input for four different hydrological models to estimate the corresponding changes in river discharge, allowing for comparison between approaches and for the robustness of the attribution results to be assessed. In all three observational precipitation data sets the climate change trends for extreme precipitation similar to observed in August 2017 are not significant, however in two out of three series, the sign of this insignificant trend is positive. One climate model shows a significant positive influence of anthropogenic climate change, whereas the other simulates a cancellation between the increase due to greenhouse gases and a decrease due to sulphate aerosols. Considering discharge rather than precipitation, the hydrological models show that attribution of the change in discharge towards higher values is somewhat less uncertain than for precipitation, but the 95% confidence interval still encompasses no change in risk. For the future, all models project an increase in probability of extreme events at 2 • C global heating since pre-industrial times, becoming more than 1.7 times more likely for high 10-day precipitation, and about a factor 1.5 more likely for discharge. Our best estimate on the trend in flooding events similar to the Brahmaputra event of August 2017 is derived by synthesizing the observational and model results: We find the change in risk to be greater than one and of similar order of magnitude (between 1 and 2) for both the meteorological and hydrological approach. This study shows that, for precipitation-induced flooding events, investigating changes in precipitation is useful, either as an alternative when hydrological models are not available, or as an additional measure to confirm qualitative conclusions. Besides, it highlights the importance of using multiple models in attribution studies,

Social Science Research Network, Jul 1, 2013

This study was conducted to investigate the changes of climate, salinity and their consequent imp... more This study was conducted to investigate the changes of climate, salinity and their consequent impacts on shrimp production at Shyamnagar under Satkhira District, Bangladesh. An integrated technique was used including social survey, historical climate data, shrimp production data and field analysis. During 1980-2009, a statistically significant decreasing trend of annual average maximu m temperature but increasing trend of annual average minimu m temperature was found. Maximu m temperature exhibited significant decreasing trend in post-monsoon while, increasing trend in winter. The trend of minimu m temperature was increasing significantly in post monsoon. Significant increase in relat ive humidity trends were found in all seasons. Salin ity levels of the shrimp farm waters were found to exceed the threshold limits for proper shrimp production. Although the total production was increasin g, the rate of shrimp production was decreasing relative to total area of farms. No statistically significant relationships were found between the annual shrimp production and climatic parameters or salin ity levels. Depths of inundation at monsoon season exceeded 180 cm, on contrary, at dry season less than 30 cm which was not proper for shrimps. The surface water salinity ranged from 7-46 ppt making farm waters unsuitable for shrimp production. According to the GM (1,1) model, the production of shrimp was hampered by climat ic hazards, increasing inundations and salinity problems.

Weather and Climate Extremes, 2015

This study was conducted to investigate the changes of climate, salinity and their consequent imp... more This study was conducted to investigate the changes of climate, salinity and their consequent impacts on shrimp production at Shyamnagar under Satkhira District, Bangladesh. An integrated technique was used including social survey, historical climate data, shrimp production data and field analysis. During 1980-2009, a statistically significant decreasing trend of annual average maximu m temperature but increasing trend of annual average minimu m temperature was found. Maximu m temperature exhibited significant decreasing trend in post-monsoon while, increasing trend in winter. The trend of minimu m temperature was increasing significantly in post monsoon. Significant increase in relat ive humidity trends were found in all seasons. Salin ity levels of the shrimp farm waters were found to exceed the threshold limits for proper shrimp production. Although the total production was increasin g, the rate of shrimp production was decreasing relative to total area of farms. No statistically...

Anthropogenic climate change is likely to increase the frequency risk of extreme weather events i... more Anthropogenic climate change is likely to increase the frequency risk of extreme weather events in the future. The term ‘risk’ here means the probability of occurrence of a hazard, e.g., an extreme rainfall event that can trigger sudden flash-flood, landslide or flood. Previous studies have robustly shown how and where climate change has already changed the risks of weather 15 extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of extreme rainfall events in Bangladesh under the Paris Agreement temperature goals of 1.5°C and 2°C warming above pre-industrial levels. In particular, we investigate the influence of anthropogenic aerosols on these risks given their likely f...

Hydrology and Earth System Sciences Discussions

Anthropogenic climate change is likely to increase the frequency of extreme weather events in fut... more Anthropogenic climate change is likely to increase the frequency of extreme weather events in future. Previous studies have robustly shown how and where climate change has already changed the risks of weather extremes. However, developing countries have been somewhat underrepresented in these studies, despite high vulnerability and limited capacities to adapt. How additional global warming would affect the future risks of extreme rainfall events in Bangladesh needs to be addressed to limit adverse impacts. Our study focuses on understanding and quantifying the relative risks of seasonal extreme rainfall events in 15

International Journal of Climatology

Hydrology and Earth System Sciences Discussions

In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This pa... more In August 2017 Bangladesh faced one of its worst river flooding events in recent history. This paper presents for the first time an attribution of this precipitation-induced flooding from a combined meteorological and hydrological perspective.

Bulletin of the American Meteorological Society

Anthropogenic climate change doubled the likelihood of the 2017 pre-monsoon extreme 6-day rainfal... more Anthropogenic climate change doubled the likelihood of the 2017 pre-monsoon extreme 6-day rainfall event at northeast Bangladesh. The magnitude of this contribution is sensitive to the climatological period in use.