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Observed trends in climate extremes over Bangladesh from 1981 to 2010
Abstract
A set of extreme indices developed by the joint CCI/WCRP/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI) has been calculated by standard tools using the precipitation and temperature data from 26 selected meteorological stations over Bangladesh. The trends in the indices have been calculated using Sen's slope estimator and significance has been tested using non-parametric Mann-Kendall trend test. The period of analysis is from 1981 to 2010. An overall increasing warming trend has been found for the temperature indices. The average annual maximum and minimum temperatures have increased 0.3 and 0.4°C decade–1 respectively. A faster rise of both the maximum and minimum temperature of this region was found compared with previous studies. The frequency of warm days has increased by 12 d decade–1. Similarly, the frequency of warm (cold) nights has increased (decreased) by 7 (11) d decade–1. The overall warming was accelerated at the end of the climatic period (2001–2010). Precipitation indices have registered an overall decreasing trend over Bangladesh which is in contrast to other studies in this region. Trends in consecutive dry days (CDD) indicating a drying tendency at a rate of 10 d decade–1. A decreasing rate of about 84 mm decade–1 has been observed in annual average total precipitation. However, except for CDD most of the precipitation trends are statistically not significant and spatially incoherent. On the other hand, statistically significant change is observed in extreme temperature events with a strong and consistent spatial pattern.
... All previous studies focussing on observed trends in extreme climate in Bangladesh have relied on station data (Ahmed et al., 2017;Caesar et al., 2015;Immerzeel, 2008;A. S. Islam, 2009;Khan et al., 2019;Shahid et al., 2012). Due to the large distances between the stations and the large amount of missing data, a few stations across the country were insufficient for examining the spatial patterns of trends in extreme climate across the country (Khan et al., 2019). ...
... S. Islam, 2009;Khan et al., 2019;Shahid et al., 2012). Due to the large distances between the stations and the large amount of missing data, a few stations across the country were insufficient for examining the spatial patterns of trends in extreme climate across the country (Khan et al., 2019). Additionally, more rigorous research incorporating is required to have a better understanding of the behavior pattern of extreme climatic events in Bangladesh, as well as for policy formulation and development strategy in the country. ...
... Dramatically, the southwest corner (coastal areas) shows significant upward trends in both CDD and CWD. This unexpected similarity between CDD and CWD was reported by Khan et al. (2019) and Abdullah et al. (2020) in Bangladesh. Similarly, Oliveira et al. (2016) and Costa et al. (2020) observed similar trends in Northeast Brazil. ...
This study explores spatial changes in trends of 29 climate extremes indices between 1981 and 2020 in Bangladesh, a country that frequently experiences the impacts of extreme events. This is the first study to examine trends in extreme climate over Bangladesh using a high resolution (0.05° × 0.05°) gridded daily temperature and precipitation data rather than individual stations. Trends in mean daily maximum and minimum temperatures were +0.38 °C and +0.25 °C per decade, respectively, for the last 40 years. The maximum increases in both warm days and nights were 12.75 days per decade with the fastest rate of warming in the eastern part of the country, whereas the maximum decreases in both cold days and nights were 7 days per decade with the western part experiencing the greatest increase in extreme cold. Significant reductions in total precipitation (225 mm per decade) were observed in the major parts of the country. However, the number of very heavy precipitation days (R20mm) showed a statistically significant increase (2.25 days per decade) in the southern coastal areas, with the tendency of more extreme wet days (R30mm). The maximum decrease in annual total precipitation was 225 mm per decade while the consecutive dry days increased by 12.5 days per decade. While previous studies reported a faster rise in minimum temperature than maximum temperature, this study shows a faster increase in maximum temperature instead of minimum temperature in the study area. Extreme temperature changes were statistically more significant than changes in extreme precipitation. This study also shows statistically significant and consistent spatial trends of extreme temperature and precipitation when using high-resolution gridded observational datasets instead of station data.
... Studies showed that there were increasing or decreasing trends of extreme rainfall indices (wet and dry indices) in recent decades (Klein Tank and Können 2003;Aguilar et al. 2005;Alexander et al. 2006;Omondi et al. 2014;Sheikh et al. 2015;Shahid et al. 2016;Lin et al. 2017;Xiong et al. 2019;Liu et al. 2019;Khan et al. 2019;Sun et al. 2016;Vincent and Mekis 2006;Tong et al. 2019). These studies used the linear least squares method, linear regression, Pearson correlation coefficient, Mann-Kendell trend test, and Sen's slope. ...
... These studies used the linear least squares method, linear regression, Pearson correlation coefficient, Mann-Kendell trend test, and Sen's slope. A significant increasing trend of wet or dry indices was found over Europe, central, and north-south parts of America, South Asia, Bangladesh, northwestern China's Qilian Mountains, areas of Yangtze River, Tibetan Plateau, Loess Plateau (China), and southern Iberian Peninsula (Klein Tank and Können 2003;Aguilar et al. 2005;Alexander et al. 2006;Sheikh et al. 2015;Shahid et al. 2016;Lin et al. 2017;Liu et al. 2019;Xiong et al. 2019;Liu et al. 2019;Khan et al. 2019;Sun et al. 2016). On the other hand, some studies showed a significant decreasing trend in dry or wet indices, for example, consecutive wet days (CWD), total wet-day rainfall (PRCPTOT), the number of heavy rain days (R10mm; rainfall $ 10 mm), the number of heavy rain days (R20mm; rainfall $ 20 mm), and consecutive dry days (CDD), over areas of Yangtze River, the Tibetan Plateau, Inner Mongolia, northwestern China's Qilian Mountains, and Canada (Omondi et al. 2014;Liu et al. 2019;Xiong et al. 2019;Vincent and Mekis 2006;Lin et al. 2017;Tong et al. 2019). ...
... This finding suggests that the number of dry indices increased significantly over Bangladesh during the 38 years, whereas the number of wet indices decreased significantly. Our results are consistent with previous studies (e.g.,Xiong et al. 2019;Liu et al. 2019;Khan et al. 2019;Sun et al. 2016) who also found a significant increasing trend in CDD in the Tibetan Plateau, Yangtze River, Bangladesh, Loess Plateau (China), southern Iberian Peninsula, respectively. The results of this study can also be compared withXiong et al. (2019) andLiu et al. (2019) who have found a significant decreasing trend in R10mm and R20mm in the Tibetan Plateau and the areas of the Yangtze River, respectively. ...
Globally, extreme rainfall has intense impacts on ecosystems and human livelihoods. However, no effort has yet been made to forecast the extreme rainfall indices through machine learning techniques. In this paper, a new extreme rainfall indices forecasting model is proposed using Random Forest (RF) model to provide effective forecasts of monthly extreme rainfall indices. In addition, RF feature importance is proposed in this study to identify the most and least important features for the proposed model. This study forecasts only statistical significant extreme rainfall indices over Bangladesh including consecutive dry days (CDD), the number of heavy rain days (R10mm; rainfall ≥ 10 mm), and the number of heavy rain days (R20mm; rainfall ≥ 20 mm) within 1–3 months lead-time. The proposed model uses monthly antecedent CDD, R10mm, and R20mm including atmospheric parameters and ocean-atmospheric teleconnections, namely, convective available potential energy (CAPE), relative humidity (RH), air temperature (TEM), El Niño–southern oscillation (ENSO), Indian Ocean Dipole (IOD), and North Atlantic oscillation (NAO) as the inputs to the model. Results show that the proposed model yields the best performance to forecast CDD, R10mm, and R20mm with only antecedent of these indices as input. Ocean-atmospheric teleconnections (IOD, ENSO, and NAO) are useful for CDD forecasting, and local atmospheric parameters (CAPE, RH, and TEM) are useful for R10mm and R20mm forecasting. The results suggest that adding atmospheric parameters and ocean-atmospheric teleconnections is useful to forecast extreme rainfall indices.
... However, the ETCCDI has defined 27 climate indices (i.e. 17 indices for temperature and 10 indices for precipitation) which are generally used to investigate extreme temperature and precipitation. These indices have been used by many researchers (Chhabra & Haris, 2015;Khomsi et al., 2016;Khan et al., 2019). The precipitation indices are shown in Table 1. ...
... Many research works on rainfall variability, spatial distribution of rainfall, variation trends of rainfall, extreme rainfall, characteristic of extreme rainfall, climate variability, climate and weather extremes among others have been carried out over the years (Manta, 2010;Emily & Barry, 2014;Akisanola & Ogunjobi, 2014;Chhabra & Haris, 2015;Khomsi et al., 2016;Audu & Okeke, 2018;Nashwan & Shahid, 2019;Yin & Sun, 2018;Iqbal et al., 2019;Khan et al., 2019). Working on trends in climate extremes over Bangladesh, (Khan et al., 2019) observed from precipitation indices a decreasing trend in precipitation. ...
... Many research works on rainfall variability, spatial distribution of rainfall, variation trends of rainfall, extreme rainfall, characteristic of extreme rainfall, climate variability, climate and weather extremes among others have been carried out over the years (Manta, 2010;Emily & Barry, 2014;Akisanola & Ogunjobi, 2014;Chhabra & Haris, 2015;Khomsi et al., 2016;Audu & Okeke, 2018;Nashwan & Shahid, 2019;Yin & Sun, 2018;Iqbal et al., 2019;Khan et al., 2019). Working on trends in climate extremes over Bangladesh, (Khan et al., 2019) observed from precipitation indices a decreasing trend in precipitation. They noted that the annual total precipitation decreased at the rate of about 84 mm/decade. ...
This study analyzed the spatial distribution and temporal trends of precipitation and its extremes over Nigeria from 1979-2013 using climate indices, in order to assess climatic extremes in the country. Daily precipitation data used in this study were obtained from Nigeria Meteorological Agency (NIMET), Lagos. The study used climate indices developed by the Expert Team on Climate Change Detection (ETCCDI) for assessing extreme precipitation. Sen’s slope estimator and Mann-Kendall trend test were employed in data analysis. Results revealed that precipitation and its extremes varied spatially across
Nigeria. Significant negative trends were observed in most of the precipitation indices for the period under study. Furthermore, significant downward trends were observed in the CWD (Consecutive Wet Day) while the CDD (Consecutive Dry Day) showed significant upward trends in all the regions. These spatial and temporal changes indicate that Nigeria’s climate is trending towards a warmer and drier condition, which could be attributed to global warming-induced climate change; which altered historical rainfall patterns thereby leading to extreme events. The findings of this study have provided
useful information in understanding the extreme events that are assumed by the general populace to be normal recurrent events in Nigeria. The results of the analysis of yearly and decadal changes in precipitation totals and extreme values for the last 35 years (1979-2013) suggest the likelihood of severe impacts on water resources, agriculture, and water-sensitive economic activities.
... A huge number of investigations has been performed to assess the changes of different rainfall and temperature extremes of Bangladesh (Shahid, 2009;SMRC, 2009;Shahid, 2011;Nowreen et al., 2012;Khan et al., 2019Khan et al., , 2020. Nevertheless, most of the studies were either at the regional level (coastal and inland region) or the local scale (cities or districts) (Endo et al., 2015;Shahid et al., 2016;Basher et al., 2017;Basher et al., 2020;Mahmud et al., 2018;Khan et al., 2019Khan et al., , 2020Abdullah et al., 2021;Islam et al., 2021a). ...
... A huge number of investigations has been performed to assess the changes of different rainfall and temperature extremes of Bangladesh (Shahid, 2009;SMRC, 2009;Shahid, 2011;Nowreen et al., 2012;Khan et al., 2019Khan et al., , 2020. Nevertheless, most of the studies were either at the regional level (coastal and inland region) or the local scale (cities or districts) (Endo et al., 2015;Shahid et al., 2016;Basher et al., 2017;Basher et al., 2020;Mahmud et al., 2018;Khan et al., 2019Khan et al., , 2020Abdullah et al., 2021;Islam et al., 2021a). Though numerous investigations have also been performed at the national, the results of those studies were inconsistent for the use of data for diverse periods in different studies. ...
... The average annual precipitation is the lowest in the southwest (1527 mm) and highest in the northeast (4197 mm) (Shahid, 2011). A substantial regional variation in precipitation and temperature extremes can be noticed (Khan et al., 2019;Islam et al., 2021b). Generally, the western region is drier compared to the other regions of the country . ...
Spatiotemporal changes in six precipitation and five temperature extreme indices of Bangladesh and their linkage with nine ocean-atmospheric oscillation indices have been evaluated in this study to provide necessary information for adaptation planning and development of early warning systems. Daily maximum and minimum temperatures and precipitation for the period 1980–2017 recorded at 20 stations, homogeneously distributed over the country, were employed for this purpose. Modified Mann-Kendall (MMK) test was used to evaluate trends in weather extremes, and detrended fluctuation analysis (DFA) was employed to anticipate the possible continuation of existing trends in the future. The cross-wavelet transform (CWT) was used to evaluate the linkage of weather extremes with oscillation indices in the time-frequency domain. The results indicate an increase in hot extremes and a decrease in cool indices in Bangladesh. An increase in the continuous dry day (CDD) and one-day maximum precipitation (RX1day) was also observed, indicating gradual drying and more susceptibility to flash floods at the same time. DFA revealed the possible continuation of existing trends in temperature and precipitation indices. Almost all the climatic extreme indices of Bangladesh were found to follow periodic cycles with different frequencies. The hot extremes were significantly associated with five out of nine oscillation indices, including Atlantic Multidecadal Oscillation (AMO), Arctic Oscillation (AO), East Asian Summer Monsoon Index (EASMI), Sunspot, and South Asian Summer Monsoon Index (SASMI), while cool indices were linked with AMO only. Among the precipitation indices, only CDD was positively related to AO, El Niño Southern Oscillation (ENSO), and Southern Oscillation Index (SOI) and negatively associated with the Pacific Decadal Oscillation (PDO). Analysis of circulation patterns using reanalysis datasets explored that elevated summer geopotential height, no visible anticyclonic center, reduced high cloud cover, and enhanced low cloud covers contributed to increasing hot extremes in Bangladesh.
... Six temperature and three extreme precipitation indices were chosen in the present study from the list of 27 extreme climatic indices endorsed by the Expert Team for Climate Change Detection Monitoring and Indices (ETCCDMI) (Zhang et al., 2011;Sun et al., 2016;Ullah et al., 2019;Khan et al., 2019). The chosen extreme indices include both the percentile-based (four temperature extremes) and absolute value-based (two temperature and three precipitation extremes) indices. ...
... The chosen extreme indices include both the percentile-based (four temperature extremes) and absolute value-based (two temperature and three precipitation extremes) indices. These nine extreme indices are important for the climatology of Bangladesh, and therefore, these indices are chosen after a detailed literature review to assess their influence on vegetation (Ullah et al., 2019;Khan et al., 2019;Luo et al., 2020). The detail information of the chosen indices is provided in Table 2. ...
... Moreover, maximum temperature (TXx) increased substantially, and the minimum temperature (TNn) declined, which agrees with the findings across the globe (Sun et al., 2016;Tong et al., 2019;Luo et al., 2020). Besides, the trend magnitude of T×90p, TX10p, and TXx was higher in the daytime than in the nighttime, which implies that daytime warming was higher than nighttime warming in Bangladesh (Shahid et al., 2016;Khan et al., 2019). This is due to thermodynamic processes such as increased cloud cover and soil Fig. 6. ...
Climate extremes have a significant impact on vegetation. However, little is known about vegetation response to climatic extremes in Bangladesh. The association of Normalized Difference Vegetation Index (NDVI) with nine extreme precipitation and temperature indices was evaluated to identify the nexus between vegetation and climatic extremes and their associations in Bangladesh for the period 1986-2017. Moreover, detrended fluctuation analysis (DFA) and Morlet wavelet analysis (MWA) were employed to evaluate the possible future trends and decipher the existing periodic cycles, respectively in the time series of NDVI and climate extremes. Besides, atmospheric variables of ECMWF ERA5 were used to examine the casual circulation mechanism responsible for climatic extremes of Bangladesh. The results revealed that the monthly NDVI is positively associated with extreme rainfall with spatiotemporal heterogeneity. Warm temperature indices showed a significant negative association with NDVI on the seasonal scale, while precipitation and cold temperature extremes showed a positive association with yearly NDVI. The DEA revealed a continuous increase in temperature extreme in the future, while no change in precipitation extremes. NDVI also revealed a significant association with extreme temperature indices with a time lag of one month and with precipitation extreme without time lag. Spatial analysis indicated insensitivity of marshy vegetation type to climate extremes in winter. The study revealed that elevated summer geopotential height, no visible anticyclonic center, reduced high cloud cover, and low solar radiation with higher humidity contributed to climatic extremes in Bangladesh. The nexus between NDVI and climatic extremes established in this study indicated that increasing warm temperature extremes due to global warming might have severe implications on Bangladesh's ecology and the environment in the future.
... A consensus is that there would be a marked change in temperature and rainfall patterns in the country because of global climate change. Consequently, extreme climatic events are likely to become severe (Shahid, 2010(Shahid, , 2011Khan et al., 2019a;2019b). However, due to contrasting physiographic and climatic settings, spatiotemporal dynamics of these extreme events could differ substantially between coastal and inland areas. ...
... Only a few studies are available that examine extreme climate events in Bangladesh (Shahid, 2011;Endo et al., 2015;Khan et al., 2019a;2019b). Unfortunately, they are either at the regional (e.g., entire Bangladesh) or at the local scale (e.g., sub-district). ...
... The use of varying temporal records and analytical techniques are also making some existing works incomparable (Shahid, 2011;Endo et al., 2015;Khan et al., 2019a;2019b). As the selection of climate normal significantly affects computation of percentile-based indices (Peterson et al., 2008;Zhang et al., 2011), existing studies appear to be inconsistent due to the use of different periods for climate normal. ...
Although coastal and inland areas of Bangladesh exhibit distinct physiographic and climatic characteristics, spatiotemporal variation of extreme climatic events are poorly understood in these two areas. This study was an attempt to understand the trends in extreme climatic events in coastal and inland areas over the period 1968‐2018. The missing data in daily maximum and minimum temperature, and daily rainfall datasets were imputed using the multiple imputation by chained equations (MICE) technique and implementing a predictive mean matching algorithm. The imputed datasets were then tested for inhomogeneity using the penalized maximal t (PMT) and modified penalized maximal F (PMF) tests. A quantile matching (QM) algorithm was then applied to homogenize the datasets, which were then used for generating thirteen extreme temperature and nine extreme rainfall indices. The trends were assessed using the Trend Free Pre‐whitened (TFPW) Mann‐Kendall (MK) test and the magnitudes of the changes were determined using the Thiel‐Sen slope estimator. Additionally, standardized anomalies were calculated to understand the seasonal variability of temperature and rainfall over the past five decades. Results suggested that both coastal and inland areas were warming significantly but coastal areas exhibited a higher rate of warming. Although most of the extreme rainfall indices showed statistically non‐significant changes for coastal and inland stations, there is evidence of localized dryness and increased rainfall at individual stations. In particular, the drought‐prone northwestern region of the country experienced decreased rainfall, which is discordant to the results of previous studies. Findings from this study highlighted important local and regional‐scale changes in extreme climate events that were previously overlooked. The findings of this study can help undertake targeted climate change adaptation strategies to save population and resources.
... In this concern, it is imperative to understand the characteristics of rainfall extremes in South Asian countries. In this perspective, many studies have used the Expert Team on Climate Change Detection and Indices (ETCCDI) for investigating hydrometeorological extremes at regional, local, and basin scales [14][15][16][17][18]. ...
... Panda and Kumar [18] found that most ETCCDI wet extreme indices show a general increase during the rapid warming period over large parts of India during 1971-2005. In Bangladesh, consecutive dry days (CDD) showed a statistically significant increasing trend of ten days per decade [15]. According to Basher, et al. [19], the northeast part of Bangladesh showed a statistically decreasing trend of rainfall extremes during monsoon seasons from 1984 to 2016. ...
In recent years, rainfall extremes have increased significantly and have threatened the socio-economic development in Sri Lanka. This study investigates the rainfall extremes in the Mahaweli River Basin (MRB) of Sri Lanka with daily station datasets from 1985 to 2015. The extreme rainfall indices recommended by the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI) have been used in this study. Results showed a strong seasonal variation of rainfall extreme events over the MRB and a significant interdecadal change of extreme rainfall indices between 1985–1999 and 2000–2015 in the wet region of MRB, which is coherent with the decadal shift of southwest monsoon (SWM) rainfall from wet to dry situations since the year 2000. Based on the General Extreme Value distributions, the long-term mean of SWM rainfall in the wet region (814 mm) moved leftward for the 2000–2015 period (704 mm) and rightward for the 1985–2000 period, suggesting that SWM rainfall is decreased in the late period. The observed above-average (below-average) rainfall and associated rainfall extremes during the SWM can be ascribed to strengthening (weakening) moisture flux from the Arabian Sea direction and strong (weak) convergence over the study domain. The results further identified the negative correlation between Dipole Mode Index and SWM rainfall and associated rainfall extremes in the wet region, signifying that the negative Indian Ocean Dipole phase can enhance the SWM rainfall over the MRB. The negative correlation between Nino3.4 and SWM rain and extreme indices suggested that high probability of wet rainfall extremes in the La Nina phase. The findings of this study can be used to understand precipitation extremes in the context of climate change at the river basin scale and benefit policymakers in building local adaptation strategies in response to long-term climate change.
... However, the changes in rainfall and temperature extremes have not been properly understood in the changing setting of climate at the regional extent of Bengal delta. Even though significant work [21,[27][28][29][30][31][32][33] has been performed in this region to investigate the characteristic changes in overall temperature and rainfall values, there has hardly been any attempt to quantify the combined assessment of changes of extreme temperature and rainfall under climate change. Additionally, relatively less effort has been invested to unearth the changes in extremes in Bangladesh's coastal regions. ...
... As a result, it can be said that the coastal region is expected to be more vulnerable to heavy storm and subsequent severe flooding. In regard to temperature extremes, both coastal and inland locations are expected to increase appreciably, which is in line with the previous studies [21,22,27], but the inland region displayed a slight increase in Tx, which is quite in agreement with the outcome in Bangladesh [28,83]. With Tn, the increase rate is higher in inland locations than in the coastal region. ...
Climate change is perceived to be the primary reason for the amplification of extreme climatic phenomena. Estimation of changes in extreme values under climate change thus plays an important role in disaster risk assessment and management. However, the different changes in extremes in two distinct regions: inland and coast under climate change are yet to be investigated meticulously. This study is intended to assess the changes in frequency of rainfall and temperature extremes under the impact of climate change in two distinct locations: coast and inland of Bengal delta, a region highly vulnerable to climate change. The multi-model ensemble (projections from CMIP6 framework) technique with the application of frequency analysis was employed to appraise the impact in two future time horizons. Results suggest that the inland estimate of extreme rainfall by the end of this century is barely able to exceed the coastal estimate of extreme rainfall in present conditions. The rate of increase of warm extremes is almost similar; however, with the cold extreme, the increase rate is a little higher inland than on the coast. In both regions, a greater rise in climate extremes is expected in the far future than in the near future. Overall, the coastal area is expected to be more vulnerable to flooding while the inland to drought under climate change in the Bengal delta region.
... However, the changes in rainfall and temperature extremes have not been properly understood in the changing setting of climate at the regional extent of Bengal delta. Even though significant work [21,[27][28][29][30][31][32][33] has been performed in this region to investigate the characteristic changes in overall temperature and rainfall values, there has hardly been any attempt to quantify the combined assessment of changes of extreme temperature and rainfall under climate change. Additionally, relatively less effort has been invested to unearth the changes in extremes in Bangladesh's coastal regions. ...
... As a result, it can be said that the coastal region is expected to be more vulnerable to heavy storm and subsequent severe flooding. In regard to temperature extremes, both coastal and inland locations are expected to increase appreciably, which is in line with the previous studies [21,22,27], but the inland region displayed a slight increase in Tx, which is quite in agreement with the outcome in Bangladesh [28,83]. With Tn, the increase rate is higher in inland locations than in the coastal region. ...
Climate change is perceived to be the primary reason for the amplification of extreme climatic phenomena. Estimation of changes in extreme values under climate change thus plays an important role in disaster risk assessment and management. However, the different changes in extremes in two distinct regions: inland and coast under climate change are yet to be investigated meticulously. This study is intended to assess the changes in frequency of rainfall and temperature extremes under the impact of climate change in two distinct locations: coast and inland of Bengal delta, a region highly vulnerable to climate change. The multi-model ensemble (projections from CMIP6 framework) technique with the application of frequency analysis was employed to appraise the impact in two future time horizons. Results suggest that the inland estimate of extreme rainfall by the end of this century is barely able to exceed the coastal estimate of extreme rainfall in present conditions. The rate of increase of warm extremes is almost similar; however, with the cold extreme, the increase rate is a little higher inland than on the coast. In both regions, a greater rise in climate extremes is expected in the far future than in the near future. Overall, the coastal area is expected to be more vulnerable to flooding while the inland to drought under climate change in the Bengal delta region.
... Daily rainfall monitored at all 28 gauges of BMD successfully passed the homogeneity test by various literatures [32][33][34][35]. Notably, for all 28 BMD stations Khan et al. [34] found almost straight lines with no breakpoint in the double mass curves and Mahmud et al. [35] observed homogenous using Standard Normal Homogeneity test, Von Neumann Ratio test, Buishand Range test and Pettitt test. ...
... Daily rainfall monitored at all 28 gauges of BMD successfully passed the homogeneity test by various literatures [32][33][34][35]. Notably, for all 28 BMD stations Khan et al. [34] found almost straight lines with no breakpoint in the double mass curves and Mahmud et al. [35] observed homogenous using Standard Normal Homogeneity test, Von Neumann Ratio test, Buishand Range test and Pettitt test. Thereby, the BMD rainfall data are considered reliable and is widely used in scientific studies [36][37][38] and government documents. ...
The regional climate model, Providing REgional Climates for Impact Studies (PRECIS), has been widely used throughout the world to generate climate change projections for impact studies and adaptations. Its recent application in South Asia also includes the projection of rainfall extremes. In spite of its wide application, a stringent validation of the model is yet to be reported. In this study, we assessed the performance of the model in simulating annual, monthly and extreme rainfalls over Bangladesh by using a number of statistical techniques, e.g., pattern (both spatial and temporal) correlation, root mean square difference (RMSD), mean absolute difference (MAD), Student’s t-test for significance, probability density functions, etc. The results indicated that the PRECIS model could capture the overall spatial pattern of mean annual and monthly rainfalls very well. However, the inter-annual variability was poorly simulated by the model. In addition, the model could not capture the rainfall extremes. A spatial aggregation of rainfall data did not improve the reliability of the model as far as variability and extremes are concerned. Therefore, further improvements of the model and/or its driving global climate model are warranted for its practical use in the generation of rainfall scenarios.
... Research on climate variables for the Jessore region, such as rainfall, temperature, and cloud coverage, is not emphasized. A number of researchers have published papers regarding the trend of climate variables in the last 10 years such as Mann-Kendall trend detection for precipitation and temperature in Bangladesh [2]; Observed trends in climate extremes over Bangladesh from 1981 to 2010 [3]; Trend analysis of major hydroclimatic variables in the Langat River basin, Malaysia. [4]; A Trend Analysis of Temperature and Rainfall to Predict Climate Change for Northwestern Region of Bangladesh [5] and Trends of Climatic Variables (Rainfall and Temperature) at Sylhet, Bangladesh [6]. ...
The aim of the study was to detect trends in salient key climate variables in the Jessore region of Bangladesh for the years 1985–2014, and the data was collected from the Bangladesh Meteorological Department (BMD). Annual rainfall, annual maximum temperature, and annual cloud coverage were analyzed using the non-parametric Mann-Kendall test, linear regression, and LOWESS curve to detect trends in the series. The rainfall and cloud coverage showed a decline trend at a rate of (4.50 mm/year; 45.02 mm/decade) and (0.045 octas/year; 0.45829 oktas/decade), respectively, whereas temperature manifested an increment trend (0.0285°C/year; 0.2854°C/decade), where cloud coverage was the only significant variable. The structural breakdown point was found using the graphical method and the Chow test, which showed in 2004 that both the series containing breakdown points and cloud coverage exhibit statistical significance.
... Most studies have focused on rainfall, specifically the spatiotemporal patterns of monsoon rainfall, variability of annual rainfall, arrival and withdrawal dates of the summer monsoon period, and intra-annual and interannual variations of rainfall across different regions of Bangladesh [41][42][43][44][45][46][47][48][49][50][51]. However, there is limited research conducted on a regional basis. ...
Rainfall, temperature, and reference evapotranspiration (ET0) have a significant influence on irrigation, aridity, flooding, and crop water requirements. The primary aims of this study were to analyze the trends in rainfall, temperature, and ET0 in seven sub-climatic zones of Bangladesh from 1989 to 2020, as well as examine their interrelationships. The Modified Mann-Kendall method was employed to assess trends, while linear regression was used for trend validation. ET0 was calculated using the FAO-56 Penman-Monteith method, and Sen’s slope was utilized to quantify the magnitude. Spatial analysis was conducted using Inverse Distance Weighting techniques. The findings revealed that annual rainfall increased only in the south-eastern zone, while the other zones experienced a decline. No significant changes were observed in annual maximum temperature, except in the south-eastern, north-eastern, and south-central zones, which showed variations ranging from 0.02 to 0.05 (°C/year). However, the yearly minimum temperature increased in all zones. Additionally, negative changes were observed in the annual magnitude of ET0 for all zones and seasons, except for the south-eastern and north-eastern zones, with a range of 0.01–0.02 mm/year. It was also noted that rainfall and ET0 displayed a strong decreasing relationship, except during the pre-monsoon season. Regarding regional variation, the northern regions exhibited a significant decreasing trend in both rainfall and ET0. The study identified key challenges, including water scarcity and irrigation difficulties due to declining rainfall and evapotranspiration, increased aridity, changing flood patterns, temperature-related impacts on crop growth, regional disparities in climate trends, and the need for effective climate change adaptation measures. Therefore, the study’s findings can contribute to knowledge in areas such as irrigation scheduling, promoting climate-smart agricultural practices, encouraging crop diversification to reduce dependence on water-intensive crops cultivation, and planning resilient water resource management to minimize the effects of environmental shifts, regulate human operations, and implement disaster remedial actions in Bangladesh.
... Basher et al. (2018) assessed the trends of pre-monsoon and monsoon rainfall over the northeast area. Very recently, Khan et al. (2019) quantified the trend of precipitation and temperature of Bangladesh for the period 1981−2010. Besides, Nowreen et al. (2015); Sultana (2015) and Roy et al. (2019) also studied the extreme hydrological variables of the northeast Haor region of Bangladesh. ...
Introduction: Pre-monsoon (March-May) flash floods observed in the northeast of Bangladesh, known as the "Haor" (saucer or bowl-shaped large tectonic depression) region, have drawn much attention in recent years due to early onset, high frequency, large magnitude, and destructive nature. The Boro crop, which is the primary agricultural production of this region, is adversely damaged by the flash floods. In this study, the trend of the flash floods of the northeast Haor region has been studied to understand past changes and future occurrences and to assess the overall impact on Boro crop productivity.
Material and methods: The trend analysis was carried out on the observed 3 - hourly water level data of 13 hydrological gage stations and daily rainfall data of 2 meteorological gage stations of the Haor region collected from the Bangladesh Water Development Board (BWDB) and Bangladesh Meteorological Department (BMD), respectively. All these stations were located near the Bangladesh-India border, where the flash flood water comes first from the surrounding hilly areas of India; otherwise, the flashy nature may not be discernible in the time series data. The data were processed from 1st March to 15th May, considering the start of the flash flood season and the end of the Boro crop harvesting period, respectively.
The statistical Mann-Kendall (MK) test has been used to analyze the trend at a 5% significance level, and Sen's slope has been used to compute the magnitude of the trend at the same significance level. Lag-1 autocorrelation has been determined before statistical trend analysis. The MK test was directly applied to the data with no autocorrelation, whereas the data showing significant autocorrelation were analyzed through the Trend-Free Pre-Whitening Mann-Kendall (TFPWMK) test. TFPWMK was selected because it can effectively detect trends in significantly serially correlated hydrological data. The trend of early onset of flash floods has also been assessed. Based on the trend analysis results, the impact of flash floods on the key varieties of Boro crops produced in the Haor region was evaluated.
Results: The trend analysis results showed that the trends of maximum water level and relative water level varied from station to station. The study revealed that 6 and 9 stations out of the 13 hydrological stations, respectively, showed an increasing trend in maximum water level and relative water level, among which only 2 and 3, respectively, showed a statistically significant increasing trend at a 5% significance level. More increasing trends were found for the relative water level, which meant that though the peak of flash floods was not increasing, the relative water level in the pre-monsoon season was increasing in recent years compared to past ones. The rainfall trend was also increasing, though it was not statistically significant. Overall, the vulnerability of the Boro crop was increasing.
The trend analysis on peak periods of flash floods showed a decreasing trend, which revealed an early onset of flash floods in recent years. The peak of the flash floods was found to be arriving early in late March-early April (instead of late April-early May), coinciding with the harvesting period of the Boro crop. This early onset of the flash flood warrants catastrophic damage to the Boro crop in future flash floods.
The study further showed that the current Boro varieties- BRRI dhan28, BRRI36, BRRI dhan69, BRRI dhan88 were safer in 'normal flash floods' (late April-early May) but not anymore safer in 'early flash floods' (late March-early April) experienced in recent years.
Conclusion: The study found an increasing trend in the water level, and rainfall in the Haor region. Though the trend hasn’t crossed the limit of a 5% significance level in most stations, this could increase exponentially in the future due to climate change impact. Also, changing timelines and the early onset of the flash flood can destroy Boro cultivation in the Haor area and imbalance the food security of the local people. Hence, the changing trend of flash floods in magnitude, pattern, duration, and early onset must be considered for flood risk management and sustainable agricultural production in the Haor region. For example, more varieties of Boro should be introduced, which can be harvested by the last week of March before the flash flood hits the Haor region. Also, varieties with a shorter growth duration and cold tolerance at the reproductive phase should be prioritized.
... by land managers and farmers, and for decision-making by policymakers. Like previous studies(Hossain et al. 2014; Bari et al. 2016;Khan et al. 2019;Sarker 2021), all five studied regions in northwestern regions of Bangladesh in our study exhibited large fluctuations of temperature and precipitation variability350 over the period 1980-2019. The observed highest mean Tmax in the Rajshahi region in our study is consistent with Sarker 2021, which reported higher Tmax and Tmin in the Rajshahi region compared to other regions in the north-western regions. ...
Drought is one of the most significant repercussions of climate change. Worldwide droughts affect food security and ecological productivity. Bangladesh has faced a series of droughts over the past few decades, with significant economic and environmental consequences. The north-western region of Bangladesh is the most affected by drought because of its geographical location and semi-arid climate. With the increasing frequency and severity of droughts, rapid and reliable drought information is essential for agro-ecological production and food security. Using the Standardized Precipitation Index (SPI) and three models (Auto Regressive Moving Average (ARMA), PROPHET, and ARMA-Generalized Autoregressive Conditional Heteroskedasticity (ARMA-GARCH)), we assessed the trends of drought in the five meteorological stations (Bogra, Dinajpur, Ishwardi, Rajshahi, and Rangpur) in the north-western region of Bangladesh for the period 1980–2019. Results show that the SPI trends were significant for Dinajpur and Ishwardi stations but insignificant for the other three stations (Bogra, Rajshahi, and Rangpur). Among the three models, the hybrid model (ARMA-GARCH) outperformed the individual models (ARMA and PROPHET), which suggests that the ARMA-GARCH model could be utilized to predict droughts as it showed higher accuracy than that of individual models. This study provides empirical evidence of (i) the intensification of drier climates in the north-western region of Bangladesh over the 40 years, which has practical implications for introducing climate adaptive practices in agriculture and other livelihood sectors, and (ii) the better performance of a hybrid model compared to individual models in predicting drought, which is of great significance for government decision-making.
... The Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDI) have been the most popular choice for extreme temperature analysis and trend detection, with recent applications in large cities globally, e.g., China (Qian, 2016;Ren and Zhou, 2014;Yu et al., 2020), Singapore (Li et al., 2018), Mexico (García-Cueto et al., 2019), Saudi Arabia (Alghamdi and Moore, 2014), Malaysia (Tan et al., 2021), Nigeria (Gbode et al., 2019), India (Manikandan et al., 2019), and Bangladesh (Khan et al., 2019). Perkins (2015) and Russo et al. (2014) highlight the importance of the establishment of a unified framework for extreme temperature measurements, which would facilitate the comparison of HW characteristics across the world. ...
Globally, extreme temperatures have severe impacts on the economy, human health, food and water security, and ecosystems. Mortality rates have been increased due to heatwaves in several regions. Specifically, megacities have high impacts with the increasing temperature and ever-expanding urban areas; it is important to understand extreme temperature changes in terms of duration, magnitude, and frequency for future risk management and disaster mitigation. Here we framed a novel Semi-Parametric quantile mapping method to bias-correct the CMIP6 minimum and maximum temperature projections for 199 megacities worldwide. The changes in maximum and minimum temperature are quantified in terms of climate indices (ETCCDI and HDWI) for the four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Cities in northern Asia and northern North America (Kazan, Samara, Heihe, Montréal, Edmonton, and Moscow) are warming at a higher rate compared to the other regions. There is an increasing and decreasing trend for the warm and cold extremes respectively. Heatwaves increase exponentially in the future with the increase in warming, that is, from SSP1-2.6 to SSP5-8.5. Among the CMIP6 models, a huge variability is observed, and this further increased as the warming increases. All climate indices have steep slopes for the far future (2066-2100) compared to the near future (2031-2065). Yet the variability among CMIP6 models in near future is high compared to the far future for cold indices.
... Several previous studies in Bangladesh showed the trend of temperature change due to climate change. For example, Khan et al. (2019) showed the average annual maximum and minimum temperatures increased by 0.3 and 0.4 °C per decade, respectively, between 1981 and 2010. Another study by Mullick et al. (2018) revealed the increasing trend of temperature on annual basis with a value of 0.4 °C for the study period of 1966-2015. ...
Urbanization leads to the construction of various urban infrastructures in the city area for residency, transportation, industry, and other purposes, which causes major land use change. Consequently, it substantially affects Land Surface Temperature (LST) by unbalancing the surface energy budget. Higher LST in city areas decreases human thermal comfort for the city dwellers and affects the urban environment and ecosystem. Therefore, a comprehensive investigation is needed to evaluate the impact of land use change on the LST. Remote Sensing (RS) and Geographic Information System (GIS) techniques were used for the detailed investigation. RS data for the years 1993, 2007 and 2020 during summer (March–May) in Dhaka city were used to prepare land cover maps, analyze LST, generate hazard maps and relate the land cover change with LST by using GIS. The results show that the built-up area in Dhaka city increased by 67% from 1993 to 2020 by replacing lowland mainly, followed by vegetation, bare soil and water bodies. LSTs found in the study area were ranged from 23.26 to 39.94 °C, 23.69 to 43.35 °C and 24.44 to 44.58 °C for the years 1993, 2007 and 2020, respectively. The increases of spatially distributed maximum and mean LST were found 4.62 °C and 6.43 °C, respectively, for the study period of 27 years while the change in minimum LST was not substantial. LST increased by around 0.24 °C per year and human thermal discomfort shifted from moderate to strong heat stress for the total study period due to the increase of built-up and bare lands. This study also shows that normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were negatively correlated with LST while normalized difference built-up Index (NDBI) and normalized difference built-up Index (NDBAI) were positively correlated with LST. The methodology developed in this study can be adapted to other cities around the globe.
... The mean annual temperature of Bangladesh is about 25°C (Kamruzzaman et al. 2018). A noticeable regional variation in rainfall and temperature is seen in Bangladesh, despite being located in a monsoon-dominated area (Khan et al. 2019). The rainfall varies from nearly 1600 mm in the northwest to more than 4000 mm in the northeast, and the mean temperature varies between 11 and 29°C in winter and between 21 and 34°C during summer (Kamruzzaman et al. 2019b). ...
The relative performance of global climate models (GCMs) of phases 5 and 6 of the coupled model intercomparison project (CMIP5 and CMIP6, respectively) was assessed in this study based on their ability to simulate annual and seasonal mean rainfall and temperature over Bangladesh for the period 1977–2005. Multiple statistical metrics were used to measure the performance of the GCMs at 30 meteorological observation stations. Two robust multi-criteria decision analysis methods were used to integrate the results obtained using different metrics for an unbiased ranking of the GCMs. The results revealed MIROC5 as the most skillful among CMIP5 GCMs and ACCESS-CM2 among CMIP6 GCMs. Overall, CMIP6 MME showed a significant improvement in simulating rainfall and temperature over Bangladesh compared to CMIP5 MME. The highest improvements were found in simulating cold season (winter and post-monsoon) rainfall and temperature in higher elevated areas. The improvement was relatively more for rainfall than for temperature. The models could capture the interannual variability of annual and seasonal rainfall and temperature reliably, except for the winter rainfall. However, systematic wet and cold/warm biases still exist in CMIP6 models for Bangladesh. CMIP6 GCMs showed higher spatial correlations with observed data, but the higher difference in standard deviations and centered root mean square errors compared to CMIP5 GCMs indicates better performance in simulating geographical distribution but lower performance in simulating spatial variability of most of the climate variables except for minimum temperature at different timescales. In terms of Taylor skill score, the CMIP6 MME showed higher performance in simulating rainfall but lower performance in simulating temperature than CMIP5 MME for most of the timeframes. The findings of this study suggest that the added value of rainfall and temperature simulations in CMIP6 models is not consistent among the climate models used in this research. However, it sets a precedent for future research on climate change risk assessment for the scientific community.
... Unlike temperature extremes, the distribution of extreme precipitation is spatially and temporally incoherent in many regions (Frich et al., 2002;Alexander et al., 2006;Donat et al., 2013). Precipitation extremes have been studied in many regions all over the world, e.g., in Asia (Limsakul and Singhruck, 2016;Khan et al., 2019;Wang et al., 2012;Liu et al., 2013;Tong et al., 2019;Yang et al., 2019;Nie et al., 2019), Europe (Klein Tank and Konnen, 2003;Mathbout et al., 2018;Popov et al., 2018;Bartolomeu et al., 2016;Lupikasza, 2010), and North America (Brown et al., 2010;Sayemuzzaman and Jha, 2014). ...
Based on daily meteorological data, spatial and temporal distributions of extreme precipitation in 1961–2018 were examined for the North Caucasus and the Crimean Peninsula. Extreme precipitation indices recommended by the Expert Team for Climate Change Detection and Indices were calculated for 45 meteorological stations. Analysis shows that the highest values of extreme precipitation indices are on the Black Sea coast of the Caucasus, except duration of dry spell, because of the atmospheric circulation features and the complex orography of studied area. Extreme precipitation trends are spatially incoherent and mostly statistically insignificant over the studied territory. Significant upward trends on the Caspian Sea coast and Stavropol Upland and statistically significant decreasing trends in the fixed threshold-based indices and all intensity indices over the Crimean Peninsula were detected. Positive and significant correlation between precipitation indices (except consecutive dry days) and altitude was obtained.
... The mean annual temperature of Bangladesh is about 25°C. A noticeable regional variation in rainfall and temperature is seen in Bangladesh, despite being located in a monsoon-dominated area (Khan et al. 2019). The rainfall varies from nearly 1600 mm in the northwest to more than 4000 mm in the northeast, and the mean temperature varies between 11 and 29°C in winter, and between 21 and 34°C during summer (Kamruzzaman et al. 2019). ...
The relative performance of global climate models (GCMs) of phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively) was assessed in this study based on their ability to simulate annual and seasonal mean rainfall and temperature over Bangladesh for the period 1977–2005. The multiple statistical metrics were used to measure the performance of the GCMs at 30 meteorological observation stations. Two robust multi-criteria decision analysis methods were used to integrate the results obtained using different metrics for an unbiased ranking of the GCMs. The results revealed MIROC5 as the most skilful among CMIP5 GCMs and ACCESS-CM2 among CMIP6 GCMs. Overall, a significant improvement in CMIP6 MME compared to CMIP5 MME was noticed in simulating rainfall over Bangladesh at annual and seasonal scales. CMIP6 MME also showed significant reduction in maximum and minimum temperature biases over Bangladesh. However, systematic wet and cold biases still exist in CMIP6 models for Bangladesh. CMIP6 GCMs showed higher spatial correlation with observed data compared to CMIP5 GCMs, but higher difference in terms of standard deviations and centered root mean square errors, indicating better performance in simulating geographical distribution but lower performance in simulating spatial variability of most of the climate variables for different timescales. In terms of Taylor skill score, the CMIP6 MME showed higher performance in simulating rainfall but lower performance in simulating temperature compared to CMIP5 MME for most of the timeframes. The findings of this study suggest that the added value of rainfall and temperature simulations in CMIP6 models is incompatible with the climate models used in this research.
... Bangladesh experiences diverse threats including oods, cyclones, hurricanes, waves, sea level rise, and landslides invariably in various locations, and accordingly, has been underlined as one of the most vulnerable countries in the world towards climate change [30,31,64]. The northwest part, focus of this research, experiences extreme weather, recurrent drought and irregular precipitation [2,5,23], which is also in line with the evidenced a rmation made by the Intergovernmental Panel on Climate Change (IPCC) about global warming and climate change [21,22]. ...
... Bangladesh experiences diverse threats including oods, cyclones, hurricanes, waves, sea level rise, and landslides invariably in various locations, and accordingly, has been underlined as one of the most vulnerable countries in the world towards climate change [30,31,64]. The northwest part, focus of this research, experiences extreme weather, recurrent drought and irregular precipitation [2,5,23], which is also in line with the evidenced a rmation made by the Intergovernmental Panel on Climate Change (IPCC) about global warming and climate change [21,22]. ...
Seasons are the divisions of the year into months or days according to the changes in weather, ecology and the intensity of sunlight in a given region. The temperature cycle plays a major role in de ning the meteorological seasons of the year. This study aims at investigating seasonal boundaries applying harmonic analysis in daily temperature for the duration of 30 years, recorded at six stations from 1988 to 2017, in northwest part of Bangladesh. Year by year harmonic analyses of daily temperature data in each station have been carried out to observe temporal and spatial variations in seasonal lengths. Periodic nature of daily temperature has been investigated employing spectral analysis, and it has been found that the estimated periodicities have higher power densities of the frequencies at 0.0027 and 0.0053 cycles/day. Some other minor periodic natures have also been observed in the analyses. Using the frequencies between 0.0027 to 0.0278 cycles/day, the observed periodicities in spectral analysis, harmonic analyses of minimum and maximum temperatures have found four seasonal boundaries every year in each of the stations. The estimated seasonal boundaries for the region fall between 19-Since seasonal variability results in imbalance in water, moisture and heat, it has the potential to signi cantly a ect agricultural production. Hence, the seasons and seasonal lengths presented in this research may help the concerned authorities take measures to reduce the risks for crop productivity to face the challenges arise from changing climate. Moreover, the results obtained are likely to contribute in introducing local climate calendar.
... Bangladesh experiences diverse threats including oods, cyclones, hurricanes, waves, sea level rise, and landslides invariably in various locations, and accordingly, has been underlined as one of the most vulnerable countries in the world towards climate change [30,31,64]. The northwest part, focus of this research, experiences extreme weather, recurrent drought and irregular precipitation [2,5,23], which is also in line with the evidenced a rmation made by the Intergovernmental Panel on Climate Change (IPCC) about global warming and climate change [21,22]. ...
Seasons are the divisions of the year into months or days according to the changes in weather, ecology and the intensity of sunlight in a given region. The temperature cycle plays a major role in defining the meteorological seasons of the year. This study aims at investigating seasonal boundaries applying harmonic analysis in daily temperature for the duration of 30 years, recorded at six stations from 1988 to 2017, in northwest part of Bangladesh. Year by year harmonic analyses of daily temperature data in each station have been carried out to observe temporal and spatial variations in seasonal lengths. Periodic nature of daily temperature has been investigated employing spectral analysis, and it has been found that the estimated periodicities have higher power densities of the frequencies at 0.0027 and 0.0053 cycles/day. Some other minor periodic natures have also been observed in the analyses. Using the frequencies between 0.0027 to 0.0278 cycles/day, the observed periodicities in spectral analysis, harmonic analyses of minimum and maximum temperatures have found four seasonal boundaries every year in each of the stations. The estimated seasonal boundaries for the region fall between 19-25 February, 19-23 May, 18-20 August and 17-22 November. Since seasonal variability results in imbalance in water, moisture and heat, it has the potential to significantly affect agricultural production. Hence, the seasons and seasonal lengths presented in this research may help the concerned authorities take measures to reduce the risks for crop productivity to face the challenges arise from changing climate. Moreover, the results obtained are likely to contribute in introducing local climate calendar.
... Basher et al. (2018) assessed the trends of pre-monsoon and monsoon rainfall over the northeast area. Very recently, Khan et al. (2019) quantified the trend of precipitation and temperature of Bangladesh for the period 1981−2010. Besides, Nowreen et al. (2015); Sultana (2015) and Roy et al. (2019) also studied the extreme hydrological variables of the northeast Haor region of Bangladesh. ...
Climate change and human activities have highly influenced the hydrological cycle in recent years. So, it has become essential to analyse the hydrological trends that occurred in past decades to understand past changes, predict future trends and identify climate change impacts on hydrological variables. Flash floods observed in the north-east of Bangladesh, known as the “Haor” (saucer or bowl-shaped large tectonic depression) region, has drawn much attention in recent years due to its early onset, high frequency and destructive nature. The Boro crop, which is the primary agricultural production of this region, is being adversely damaged by pre-monsoon (March – mid-May) flash floods. Generally, flash floods are observed in the north-eastern region every two or three years. However, the flash floods of two consecutive years of 2016 and 2017 were observed in two successive years and resulted in huge damages. The usual onset of a flash flood in the Haor region is generally from end of April to mid of May. However, the flash flood of 2017 occurred on 28th March, earlier than the usual time. The flood water level of the 2017 flood has been the highest pre-monsoon flood level in the last 100 years. It is anticipated that flash floods are appearing earlier with higher frequency and larger magnitude. This study is formulated to investigate the trend of the hydro-meteorological variables of flash floods of the north-eastern Haor region of Bangladesh. The analysis has been carried out using 3-hourly water level data of 13 hydrological gauging stations and daily rainfall data of 2 meteorological gauging of the northeast Haor region collected from the Bangladesh Water Development Board and Bangladesh Meteorological Department, respectively. The gauging stations in close proximity with the surrounding hills were selected in order to capture the peak of flash floods before it is attenuated. In this study, the trend of two important hydro-meteorological variables flood level (maximum and relative water level) and rainfall (maximum, average and total rainfall) is studied with non-parametric monotonic Mann-Kendall (MK) test and Sen’s Slope test at 5% significance level. The trend of the onset of the peak period of flash floods has been assessed too. Simultaneously, visual trend analysis has been inspected too by graphical plotting. The statistical Lag 1 autocorrelation was determined prior to trend analysis. The stations having no autocorrelation, were directly investigated by the MK test whereas the stations showing autocorrelation were analyzed through Trend-Free Pre-Whitening Mann-Kendall (TFPWMK) as introduced by Yue et al. (2002) for detecting trends in significantly serially correlated hydrological series.
The purpose of this study was to analyze the trend of change in land use land cover (LULC) and land surface temperature (LST) in Mirpur and its surrounding area over the last 30 years using Landsat satellite images and remote sensing indices, and to develop relationships between LULC types and LST, as well as to analyze their impact on local warming. Using this analyzed data, a further projection of LULC and LST change over the next two decades was made. From 1989 to 2019, 5-year intervals of Landsat 4–5 TM and Landsat 8 OLI images were utilized to track the relationship between LULC changes and LST. The modeled LST was validated with MODIS-derived LST within the study area. Cellular automata-based artificial neural network (CA-ANN) algorithm was used to model the LULC and LST maps for the year 2039. The Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-up Index (NDBI) were analyzed to determine their link with LST. The relation between LST and LULC types indicates that built-up area raises LST by substituting non-evaporating surfaces for natural vegetation. The average surface temperature was increasing steadily for the last 30 years. For the year 2019, it was determined that roughly 86% of total land area has been converted to built-up area and that 89% of land area had an LST greater than 28 °C. According to the study, if the current trend continues, 72% of the Mirpur area is predicted to see temperatures near 32 °C in 2039. Additionally, LST had a significant positive association with NDBI and a negative correlation with NDVI. The overall accuracy of LULC was greater than 90%, with a kappa coefficient of 0.83. The study may assist urban planners and environmental engineers in comprehending and recommending effective policy measures and plans to mitigate the consequences of LULC.
Extreme temperature is the key indicator of extreme climatic events. The goal of this research was to better understand the long-term trends and shifting behaviors associated with Bangladesh’s record-breaking high temperatures in the country’s atmosphere. Data from 26 Bangladeshi meteorological stations collected between 1981 and 2018 was analyzed with RClimDex. The annual count of warm (cold) spell duration increased, according to the findings (decrease). In the coastal regions, this rising temperature trend is more pronounced. There were longer (shorter) periods of warm (cold) weather in the twentieth century than there were in the previous decade. As a result, the length of warm (cold) spells has become longer since the beginning of the twenty-first century, as compared to the last quarter of the twentieth century. There is little fluctuation in diurnal temperatures, but they are getting smaller and smaller. There is a 13% decrease in the Cold Spell Duration Indicator (CSDI), which indicates that we are in for a long, cold winter. At a rate of 14% per year, the Warm Spell Duration Indicator (WSDI) annual count suggests an extremely hot summer is imminent. Diurnal temperature range (DTR) values decreased by 1.1% year-round, raising the specter of climate extremes like the CSDI and WSD. An increasing (decreasing) trend in indicators of how long hot (cold) weather lasts indicates an increase (decrease) in Bangladesh’s warm atmosphere. As a result, an increase in the number of extreme weather events, particularly along the coasts, should be expected across the country.
Understanding changes in monsoon precipitation patterns is crucial as it determines the occurrence, intensity, and duration of floods and droughts in Bangladesh. This study investigates changes in monsoon precipitation patterns in different intensities and durations over Bangladesh and their possible teleconnection with large-scale atmospheric oscillations. The changes in different thresholds at 29 stations in Bangladesh were analyzed using the Mann–Kendall (MK) test. Pearson correlation, wavelet coherence (WTC), and multiple wavelet coherence (MWC) methods were also employed to analyze and understand the potential linkage between the large-scale atmospheric circulations and monsoon precipitation indices. The results showed a significant decreasing trend in light and moderate precipitation indices, P10, D10, P20, and D20, while an increasing trend in heavy precipitation indices such as P60, D60, P60plus, and D60plus. The Pearson correlation analysis exhibited a significant correlation between the monsoon precipitation indices and the atmospheric circulation indices. WTC analysis revealed substantial coherence in the time–frequency bands of P10-Nino3.4, D10-Nino3.4, P20-SASMI (South Asian Summer Monsoon Index), P20-EASMI (East Asian Summer Monsoon Index), D20-SASMI, and P60plus-SOI (Southern Oscillation Index) indices. MWC analysis affirmed the correlation and showed the influence of the ERA5 reanalysis parameters, i.e., temperature (T850) and geopotential height at 850 hPa (G850), mean total precipitation rate (MTPR), mean vertically integrated moisture divergence (MVIMD), and summer evaporation (SEV) on the monsoon precipitation indices. The circulation pattern changes, like increasing sea surface temperature, T850, and G850, MTPR, SEV, and decreasing MVIMD, might work as the drivers of monsoon precipitation changes in Bangladesh. The findings can be helpful to address agro-economy losses due to monsoon variability through agricultural planning, flood, landslide and water resources management.
Bangladesh is sensitive to weather and climate extremes, which have a serious impact on agriculture, ecosystem, and livelihood. However, there is no systematic investigation to explore the effect of climate modes on temperature extremes over Bangladesh. A total of 11 temperature extreme indices based on the daily maximum and minimum temperature data for 38 years (1980–2017) have been calculated. Cross-wavelet transform and Pearson correlation coefficient have been used to identify the relationship between temperature extremes and three climate modes namely El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and North Atlantic Oscillation (NAO). Detrended fluctuation analysis (DFA) method was applied to predict the long-term relationship among temperature indices. Results showed that warm (cold) temperature extreme indices increased (decreased) significantly. There was a significant upward trend in the diurnal temperature range and tropical nights except for growing season length. ENSO and IOD had a strong negative impact on warm temperature indices, whereas NAO had a strong negative influence on variability temperature indices in Bangladesh. Temperature extreme had a long-term relationship based on DFA (a > 0.5), implying that the temperature extremes will remain their present trend line in the future period. The Poisson regression model showed that the highest probability (65%) of having a 2–4 warm spell duration indicator (days/decade) is consistent with the observation, which is shown in the cross-wavelet transform and spatial analysis.
Understanding the effects of vegetative land cover in Bangladesh on climatic variability and dynamics is still a critical issue for environmental sustainability as well as global and regional climate policy formulation. This study aimed to gain a better understanding of the responses of vegetation changes and built-up area changes to climatic variability in Bangladesh during 1990–2020. Based on the Normalized Difference Vegetation Index (NDVI) dataset, we analyzed the spatiotemporal characteristics of vegetation dynamics and the proportion of urban land changes across all the urban and rural areas of Bangladesh and investigated the relationships between the variability of temperature, precipitation, and humidity through Pearson’s correlation (PC) and geographically weighted regression (GWR) models. This study found complex variations in growing-season NDVI and climatic factors across the country. The results indicate a declination of vegetation areas and precipitation, with an increase in built-up areas (12.60% in urban and 11.68% in rural areas), temperature, and humidity. The correlation between growing-season NDVI and climatic factors demonstrates a strong inverse influence of temperature up to − 0.78; and positive influences of rainfall up to + 0.51 and humidity up to + 0.06, but in the case of built-up area changes, temperature change is positively correlated, while rainfall and humidity are negatively correlated to built-up expansion. Findings suggest that climatic factors are more responsive to built-up land expansion than vegetation dynamics in the urban and rural areas of Bangladesh. The unplanned development activities would persist and continue to affect the environment and sustainability. This study provides policymakers and the Bangladesh government with critical information on environmental development and sustainability improvements that will lead to the long-term sustainability of natural resources and environmental health.
Water is one of the most important natural resources, which is essential to ensure a sustainable life on the planet. Water security for everyone is a prerequisite for an area’s economic growth, social stability, and environmental sustainability. The peri-urban area is a transition zone with water insecurity in a severe manner. This study has assessed the condition of water security of six unions with peri-urban characteristics of Singair Upazila of Manikganj District of Bangladesh through conducting a total of 182 household surveys, 6 Focus Group Discussions, and 12 Key Informant Interviews. Singair Upazila has experienced mixed land use, industrial growth, infrastructural development, and transformation of economic activities. Here, water security is derived not only from the availability and accessibility of water sources, but also socioeconomic factors. Water security index has been calculated by aggregating the considered values of associated indicators and sub-indicators. Obtained water security index varies from dissatisfaction to highly satisfaction on a scale of 1 to 5. The results show that Saista scored the lowest and marked dissatisfaction among the six unions, while Jamsha scored highest with the highly satisfactory water security status. The study opts to mention that cooperation and partnership development among significant stakeholders, i.e., local people, policymakers, and non-government organizations, can enhance the water security systems in similar peri-urban settings.
The rise in the frequency and magnitude of extreme temperature phenomena across the globe has led to the recurrent incidence of global climate hazards, which have had severe effects on socioeconomic development. The daily maximum and minimum temperature datasets of 27 sites in Bangladesh were used to detect spatiotemporal trends of temperature extremes over Bangladesh during 1980–2017 based on ten temperature extreme indices using multi-statistical modeling namely linear regression, Pearson correlation coefficient, and factor analyses. Besides, mutation analyses based on the Mann-Kendall test, Sen’s slope estimator, and Pettit test were employed to show the changing trend in extreme temperature. Results show that except for warmest days, the warm indices showed an increasing trend, mainly since the 2000s, while the growth rate was faster, and the response to global climate warming was sensitive. The cold indices were demonstrated a reverse trend since the 2010s. Diurnal temperature range (DTR) and summer days (SU) increased faster, implying that the rising speed of daily max temperature was higher than of daily min-temperature in Bangladesh. The de-trended fluctuation analysis (DFA) revealed a continuous increase in temperature extreme in the future except for cold days. The probability distribution functions (PDF) analysis revealed an evident variation of the curves in recent decades compared to the past three decades. Besides the warm night, DTR and SU primarily control the general warming trend of temperature extremes over Bangladesh during the study period. The mutation of the warm indices occurred before the cold index, indicating that the warm indices were more sensitive to global climate warming. The temperature extremes recognized in our research suggest that elevated warm temperature extremes due to global climate warming may have huge implications on the sustainable development of Bangladesh in the forthcoming period.
The spatial and temporal variation of rainfall, Tmax and Tmin (mean maximum and minimum temperature) and ΔT (Tmax -Tmin) of different Regions of Bangladesh and Sea Surface Temperature (SST) of Northern Bay of Bengal at seasonal and annual timescales for the period of 1981–2019 have been investigated using a Linear regression test (LRT) and a student t-test in this study. Correlation analysis has been investigated between SST of the Bay of Bengal, and temperature or rainfall of the entire Coast. The regional differences of climatic trends were tested in each region against other regions via a student t-test. Results suggest that there is regional climatic variation between the Northwest and South Zones. There are significant regional differences in climatic trends found in this study. All seasons mean Tmax and Tmin are increasing except in winter when mean Tmax for the Northwest Region (- 0.005 °C/year), and Middile Zone (-0.003#x00A0;°C/year) and mean Tmin for some Southern Regions (e.g., Hilly Region) are decreasing in some seasons. Hilly Region is showing the highest increasing rates of mean Tmax across all seasons (annually at the rate of 0.04 °C/ year (p
Drought is an inconspicuous natural disaster. In a warmer world, the severity and coverage of drought are expected to change, and it is essential to study these changes at smaller scale. This study detected changes in drought frequency, severity, and intensity in Bangladesh from a bias-corrected CMIP-5 multi-model projection of 11 members under a business-as-usual RCP8.5 scenario. We have used two well-known meteorological drought indices, Standardized Precipitation Index (SPI) and Standardized Precipitation and Evaporation Index (SPEI). SPI is solely based on precipitation, while SPEI considers climatic water balance and incorporates the effect of temperature. Two different methods of estimation of potential evapotranspiration (PET), namely Thornthwaite and Hargreaves methods, are explored. SPEI-based drought identification is found to have high sensitivity among these PET estimation methods. In Bangladesh, SPI-based analysis suggests virtually no change in the long-term drought (12-monthly) condition and a minor change in short-term (6-monthly or less) droughts. SPEI evaluated with Hargreaves method projects a similar scenario for long-term droughts but an increase in both drought frequency and severity in short timescales. At seasonal scale, winter and pre-monsoon are projected to be potentially more affected by water stress in the future. A spatially coherent shift in wet-dry regime is also found over the northern part of Bangladesh under the warming world.
Global mean temperature is continuously rising and causing changes in the extreme climatic events. Following these changes, climate extremes—the rare events that reside in the tail of the distribution of essential climate variables—are expected to be further intensified, more frequent, and prolonged. Changes in extremes would vary spatially from region to region and thus need regional assessment for future adaptation planning. This study assesses the climate extremes at 1.5 °C, 2 °C, and 4 °C of global warming over Bangladesh which is one of the most vulnerable countries to climate change. Future changes in climate extremes are assessed using a subset of extreme temperature and precipitation indices devised by Expert Team on Climate Change Detection and Indices (ETCCDI). Projections from high-resolution regional climate model ensembles are used to derive extreme climate indices. Our analysis shows overall upward changes in warm indices and downward changes in cold indices at higher specific warming levels. We found a much higher increase in extreme rainfall compared with the annual total rainfall. Increasing variability of rainfall indices is found at higher specific warming levels. Our analysis also suggests a higher increase of temperature during the winter and post-monsoon seasons, as well as an increase in the 1-day and 5-day maximum rainfall during pre- and post-monsoon seasons. A significant regional difference is found in almost all the rainfall indices. The forecasted increase of extreme rainfall and consecutive dry days (CDD) over the northeast region indicates a possibility of an increase of flash floods in the future. Moreover, the increase in the extreme rainfall over the southeast region will increase the chances of landslides.
Flash flood and related hazards occurred over the Haor (wetland) areas of northeast Bangladesh during 17–18 April 2010. Prediction of this sudden incident is challenging when it happened on the high terrain of Meghalaya Plateau and adjoining Bangladesh. Flash flood event occurred when convective cells assembled into a mesoscale convective system (MCS) over the steep edge of the Plateau. The MCS obtained its extreme point after getting moisture support from the southerly flow of the Bay of Bengal (BoB). This study investigated the synoptic flow patterns and large-scale characteristics of the flash flood-producing storm and its associated tropospheric conditions in northeast Bangladesh using the Weather Research and Forecasting (WRF) model. The model used a 3-nested domain with the horizontal resolution of 27 km, 9 km, and 3 km, respectively. The study revealed that the model underestimated the strength of the flash flood in general in respect of rainfall. The 48-h simulated rainfall was about 152 mm for outer domain-1, about 195 mm for inner domain-2 and about 209 mm for the innermost domain-3 whereas actual rainfall was 223 mm as recorded by Bangladesh Meteorological Department (BMD). The southerly wind was strong at 950 hPa and the westerly wind prevailed at 500 hPa level. The model simulated results show that cloud water mixing ratio was 1.8 mg m⁻³ and extended vertically up to 17 km. Ice water mixing ratio was 200 mg m⁻³ and found in between 12 and 20 km, indicating the formation of ice in the upper troposphere. The maximum values of x, y, and z-wind components over Cherrapunji were − 11 ms⁻¹, − 21 ms⁻¹ and − 2.8 ms⁻¹, respectively which indicated the strengthening of the convective system to produce flash flood.
This study analyzes the trends of extreme rainfall indices over northeast Bangladesh for the period of 1984 to 2016 for the pre-monsoon and monsoon seasons. The research was framed as part of a project co-producing knowledge of climate variability and impacts through collaboration between scientific and local communities in northeast Bangladesh, which found pre-monsoon and monsoon rainfall to be most important. With access to a greater number of rainfall stations than previous work in northeast Bangladesh, we investigated trends in extreme rainfall events using the Mann–Kendall trend test and Sen’s slope estimator. To appraise the quality of the data, we used the Standard Normal Homogeneity and the Pettitt tests to check its homogeneity. Among the seven stations, only Sunamganj was found inhomogeneous, and was not considered for trend analysis. All indices of rainfall extremes showed a decreasing trend in both seasons, with the most significant decrease during the monsoon. Importantly, we saw a decreasing trend in the seasonal total rainfall and consecutive wet days, whereas there was an increasing trend in consecutive dry days. Moreover, we saw a decreasing trend in 1-day maximum rainfall, 5-day maximum rainfall, the intensity of the daily rainfall over 25 mm during the pre-monsoon and 50 mm during monsoon, which together may indicate a future decrease in the magnitude and intensity of flash floods and monsoon floods. If this trend continues, the northeast Bangladesh may suffer from water stress, which could affect the lives and livelihoods of communities living there.
Bangladesh is a densely populated developing country. Hilly or mountainous terrain occupies around 12% of the total area of Bangladesh. Due to scarcity of land, people are forced to live at foothills or on the slopes of hills. Landslide has become a major disaster in the hilly regions of Bangladesh, occurring almost every year. From physical survey, it is observed that soil characteristic of Chittagong Hill Tracts (CHT) is alluvial, silty clay which is vulnerable to landslides. Human activities such as deforestation, jhoom cultivation and hill cutting have made the slopes unstable. In addition, excessive rainfall during monsoon cause rain cut erosion which results to landslides. During the last five decades, CHT suffered about 12 major landslides. Most devastating landslides occurred in 2007 and 2017. The landslide on 11 th June, 2007 which occurred in several areas near Chittagong city was one of the severest of such occurrences in the country's history causing death of 127 people. Very recently, on 13 th June, 2017 CHT experienced massive landslides. A large number of foothill settlements and slums were demolished; more than 152 people died and huge resource destruction took place. It is observed from the field survey that, failure patterns of some landslides are transitional whether others are rotational. This paper mainly discusses the extent of these two landslides (2007 and 2017) and possible measures that can be taken to prevent future landslides. Current practices of slope protection in hill are construction of RC retaining walls and masonry toe wall which are quite expensive. It is suggested to implement some new and modified structural measures such as vegetation with jute geo-textile can significantly improve the stability of hill slopes. Furthermore, development of early warning, improvement of drainage condition, landslide mapping and geophysical analysis should also be done alongside in order to reduce the devastating effects of the disaster.
A long-term (1948 to 2012) trend of precipitation (annual, pre-monsoon, monsoon, and post-monsoon seasons) in Bangladesh was analyzed in different regions using both parametric and nonparametric approaches. Moreover, the possible teleconnections of precipitation (annual and monsoon) variability with El Niño/Southern Oscillation (ENSO) episode and Indian Ocean Dipole (IOD) were investigated using both average and individual (both positive and negative) values of ENSO index and IOD. Our findings suggested that for annual precipitation, a significant increasing monotonic trend was found in whole Bangladesh (4.87 mm/year), its western region (5.82 mm/year) including Rangpur (9.41 mm/year) and Khulna (4.95 mm/year), and Sylhet (10.12 mm/year) and Barisal (6.94 mm/year) from eastern region. In pre-monsoon, only Rangpur (2.88 mm/year) showed significant increasing trend, while in monsoon, whole Bangladesh (3.04 mm/year), Sylhet (7.17 mm/year), and Barisal (6.94 mm/year) showed similar trend. In post-monsoon, there was no significant trend. Our results also revealed that the precipitation (annual or monsoon) of whole Bangladesh and almost all of the spatial regions did not show any significant correlation with ENSO events, whereas the average IOD values showed significant correlation only in monsoon precipitation of western region. The individual positive IODs showed significant correlation in whole Bangladesh, western region, and its two divisions (Rajshahi and Khulna). So, in the context of Bangladesh climate, IOD has the more teleconnection to precipitation than that of ENSO. Our findings indicate that the co-occurrence of ENSO and IOD events may suppress their influence on each other.
In this study, changes in the spatial and temporal patterns of climate extreme indices were analyzed. Daily maximum and minimum air temperature, precipitation, and their association with climate change were used as the basis for tracking changes at 50 meteorological stations in Iran over the period 1975–2010. Sixteen indices of extreme temperature and 11 indices of extreme precipitation, which have been quality controlled and tested for homogeneity and missing data, are examined. Temperature extremes show a warming trend, with a large proportion of stations having statistically significant trends for all temperature indices. Over the last 15 years (1995–2010), the annual frequency of warm days and nights has increased by 12 and 14 days/decade, respectively. The number of cold days and nights has decreased by 4 and 3 days/decade, respectively. The annual mean maximum and minimum temperatures averaged across Iran both increased by 0.031 and 0.059 °C/decade. The probability of cold nights has gradually decreased from more than 20 % in 1975–1986 to less than 15 % in 1999–2010, whereas the mean frequency of warm days has increased abruptly between the first 12-year period (1975–1986) and the recent 12-year period (1999–2010) from 18 to 40 %, respectively. There are no systematic regional trends over the study period in total precipitation or in the frequency and duration of extreme precipitation events. Statistically significant trends in extreme precipitation events are observed at less than 15 % of all weather stations, with no spatially coherent pattern of change, whereas statistically significant changes in extreme temperature events have occurred at more than 85 % of all weather stations, forming strongly coherent spatial patterns.
Using a standard set of annual and seasonal climate extremes indices derived from daily temperature and precipitation data, relationships between mean and extremes trends across Australia and the globe are analysed. Extremes indices are calculated using station data from Australian high-quality daily temperature and precipitation datasets and pre-existing high-quality datasets of climate extremes for the globe. Spatial correlations are calculated between the trends in means and extremes both annually and seasonally for maximum and minimum temperature and precipitation across Australia, and annually for precipitation across the rest of the globe. In Australia, trends in extremes of both temperature and precipitation are very highly correlated with mean trends. Annually, the spatial correlation between trends in extremes and trends in the mean is stronger for maximum temperature than for minimum temperature. However, this relationship is reversed in winter, when minimum temperatures show the stronger correlations. Analysis of the rate of change of extremes and means across Australia as a whole shows most stations have greater absolute trends in extremes than means. There is also some evidence that the trends of the most extreme events of both temperature and precipitation are changing more rapidly in relation to corresponding mean trends than are the trends for more moderate extreme events. The annual relationships between means and extremes of precipitation in Australia are consistent with all other global regions studied.
There is a broad consensus amongst the scientific community that South Asia is amongst the regions most affected by climate change. According to the International Panel on Climate Change (IPCC) Fourth Assessment Report (2007) the main climate change impacts in the region are as follows: increased frequency of droughts and floods negatively affecting local production; sea level rise exposing coasts to increasing risks, including coastal erosion and growing human-induced pressures on coastal areas; and glacier melt in the Himalayas with more flooding and rock avalanches. Crop yields could decrease up to 30% in Central and South Asia by the mid-twenty-first century. Within South Asia, Bangladesh is the most vulnerable country because of its regional connectivity through geo-physical and hydrological features and its livelihood reliance on trade (ELIAMEP, 2008).
This article aims to review studies pertaining to trends in rainfall, rainy days and temperature over India. Sen's non-parametric estimator of slope has been frequently used to estimate the magnitude of trend, whose statistical significance was assessed by the Mann-Kendall test. Spatial units for trend analysis vary from station data to sub-division to sub-basin/ river basins. There are differences in the results of the various studies, and a clear and consistent picture of rainfall trend has not emerged. Although the different units (sub-basins or sub-divisions) may have a nonzero slope value, few values are statistically significant. In a study on basin-wise trend analysis, 15 basins had decreasing trend in annual rainfall; only one basin showed significant decreasing trend at 95% confidence level. Among six basins showing increasing trend, one basin showed significant positive trend. Most of the basins had the same direction of trend in rainfall and rainy days at the annual and seasonal scale. Regarding trends in temperature, the mean maximum temperature series showed a rising trend at most of the stations; it showed a falling trend at some stations. The mean minimum temperature showed a rising as well as a falling trend. At most of the stations in the south, central and western parts of India a rising trend was found. Some stations located in the north and northeastern India showed a falling trend in annual mean temperature. Most of the data used in trend analysis pertained to the stations located in urban areas and these areas are sort of heat islands. This article also highlights the need of a network of baseline stations for climatic studies.
Climate extremes have profound implications for urban infrastructure and human society, but studies of observed changes in climate extremes over the global urban areas are few, even though more than half of the global population now resides in urban areas. Here, using observed station data for 217 urban areas across the globe, we show that these urban areas have experienced significant increases (p-value <0.05) in the number of heat waves during the period 1973–2012, while the frequency of cold waves has declined. Almost half of the urban areas experienced significant increases in the number of extreme hot days, while almost 2/3 showed significant increases in the frequency of extreme hot nights. Extreme windy days declined substantially during the last four decades with statistically significant declines in about 60% in the urban areas. Significant increases (p-value <0.05) in the frequency of daily precipitation extremes and in annual maximum precipitation occurred at smaller fractions (17 and 10% respectively) of the total urban areas, with about half as many urban areas showing statistically significant downtrends as uptrends. Changes in temperature and wind extremes, estimated as the result of a 40 year linear trend, differed for urban and non-urban pairs, while changes in indices of extreme precipitation showed no clear differentiation for urban and selected non-urban stations.
Based on daily maximum and minimum temperature records at 78 meteorological stations in the Basin of China’s largest fresh water lake (Poyang Lake Basin), the temporal and spatial variability of 11 extreme temperature indices are investigated for the period 1959–2010. The analysis indicates that the annual mean of daily minimum temperature (Tmin) has increased significantly, while no significant trends were observed in the annual mean of daily maximum temperature (Tmax), resulting in a significant decrease in the diurnal temperature range. Trends and percentages of stations with significant trends in Tmin-related indices are generally stronger and higher than those in Tmax-related indices; however, no significant trends can be found in Tmax-related indices (TXMean, TX90p, TXx and TX10p) at both seasonal and annual time scale. Low correlations with Global-SST ENSO index are also detected in Tmax-related indices. Significant positive relationships can be found in Tmin-related indices (TNMean, TNx, TNn and TN90p), however, the most significant negative coefficient was also found in cold nights (TN10p) with the Global-SST ENSO index. Singular value decomposition (SVD) correlating extreme temperatures over the Poyang Lake Basin and the North Pacific SST indicates the East China Sea, Western Pacific and Bering Sea to be stronger linked with Tmin than Tmax with the first mode (SVD-1) explaining 90 and 94 % of annual Tmax and Tmin respectively.
The main objective of this study was to obtain analysis of the trends in eleven annual extreme indices of temperature for Utah, United State of America (USA). The analyses have been obtained for 28 meteorological stations, in general, for the period of 1930 to 2006, characterizing a long-term period and with high quality data. The software used to process the data was the RClimdex 1.0. The analysis has identified that the temperature increased in Utah during the last century, evidencing the importance of the ongoing research on climate change in many parts of the world.
The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally-based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades. This article is protected by copyright. All rights reserved.
Based on homogeneity-adjusted daily temperature data from national stations, the spatial and temporal change in extreme temperature events in mainland China have been analyzed for the period 1961−2008. The analysis shows that the numbers of frost days and ice days were significantly reduced, with the most significant reduction generally in northern China for ice days but more extensively across the country for frost days. Summer days and tropical nights significantly increased along the middle and lower reaches of the Yangtze River and in southern Southwest China. The maximum values of Tmax (TXx) and Tmin (TNx) and the minimum values of Tmax (TXn) and Tmin (TNn) generally rose, and TXx and TNx significantly increased in northern China, while TXn and TNn significantly increased across the whole country. A significant reduction at a rate of −8.23 d decade−1 (−3.26 d decade–1) occurred for cool nights (days), and a significant increase at a rate of
8.16 d decade–1 (5.22 d decade–1) occurred for warm nights (days). The reduction of cool nights and cool days occurred mainly in winter, but the increase of warm days and warm nights occurred mostly in autumn and summer. Extreme cold indices were reduced, mainly after the mid-1980s, while extreme warm indices increased remarkably after the mid-1990s. The analysis also shows that, for North China, the urbanization effect on the series of extreme temperature indices was statistically significant for the negative trends of frost days, diurnal temperature range, cool nights and cool days, and for the positive trends of summer days, tropical nights, TNx, TNn, and warm nights.
A climate change workshop for the Middle East brought together scientists and data for the region to produce the first area-wide analysis of climate extremes for the region. This paper reports trends in extreme precipitation and temperature indices that were computed during the workshop and additional indices data that became available after the workshop. Trends in these indices were examined for 1950–2003 at 52 stations covering 15 countries, including Armenia, Azerbaijan, Bahrain, Cyprus, Georgia, Iran, Iraq, Israel, Jordan, Kuwait, Oman, Qatar, Saudi Arabia, Syria, and Turkey. Results indicate that there have been statistically significant, spatially coherent trends in temperature indices that are related to temperature increases in the region. Significant, increasing trends have been found in the annual maximum of daily maximum and minimum temperature, the annual minimum of daily maximum and minimum temperature, the number of summer nights, and the number of days where daily temperature has exceeded its 90th percentile. Significant negative trends have been found in the number of days when daily temperature is below its 10th percentile and daily temperature range. Trends in precipitation indices, including the number of days with precipitation, the average precipitation intensity, and maximum daily precipitation events, are weak in general and do not show spatial coherence. The workshop attendees have generously made the indices data available for the international research community.
A new global dataset of derived indicators has been compiled to clarify whether frequency and/or severity of climatic extremes changed during the second half of the 20th century, This period provides the best spatial coverage of homogenous daily series, which can be used for calculating the proportion of global land area exhibiting a significant change in extreme or severe weather. The authors chose 10 indicators of extreme climatic events, defined from a larger selection, that could be applied to a large variety of climates. It was assumed that data producers were more inclined to release derived data in the form of annual indicator time series than releasing their original daily observations. The indicators are based on daily maximum and minimum temperature series, as well as daily totals of precipitation, and represent changes in all seasons of the year. Only time series which had 40 yr or more of almost complete records were used, A total of about 3000 indicator time series were extracted from national climate archives and collated into the unique dataset described here. Global maps showing significant changes from one multi-decadal period to another during the interval from 1946 to 1999 were produced. Coherent spatial patterns of statistically significant changes emerge, particularly an increase in warm summer nights, a decrease in the number of frost days and a decrease in intra-annual extreme temperature range. All but one of the temperature-based indicators show a significant change. Indicators based on daily precipitation data show more mixed patterns of change but significant increases have been seen in the extreme amount derived from wet spells and number of heavy rainfall events. We can conclude that a significant proportion of the global land area was increasingly affected by a significant change in climatic extremes during the second half of the 20th century. These clear signs of change are very robust; however, large areas are still not represented, especially Africa and South America.
Rise in temperature and annual precipitation, changes in seasonal rainfall patterns, more frequent and severe extreme weather events, and increased salinity in river water have been observed in Bangladesh in the recent years. Rising temperature will elevate total power consumption and peak power demand especially during the pre-monsoon hot summer season, reduce power plant efficiency and transformer lifetime, and increase the transmission loss. More frequent and severe extreme weather events may cause more disruption in power generation and distribution, and more damage of power infrastructure. Lower river flow in dry season may cause water scarcity in power plants and hamper the production. Increased salinity in river water due to sea level rise may lead to corrosion and leakages in power plants located in the coastal region of Bangladesh. A diversified, decentralized, and climate resilient power system can reduce negative impacts of climate change on power sector of Bangladesh. Adaptation and mitigation strategies must be incorporated in the planning and development of new power systems and the reformation of existing power systems of Bangladesh.
Diurnal temperature range (DTR) is a meteorological indicator independent of internal climate variation and therefore, considered as a signature of observed climate change. It has been observed that global averaged DTR has decreased significantly in the last fifty years. However, the change in DTR has regional and seasonal characteristics. A study has been carried out in this paper to analyze the spatial and seasonal patterns in the trends of DTR in Bangladesh. Daily temperature data from 18 stations for the time period 1961-2008 has been used for the study. The result shows that both mean minimum and mean maximum temperatures of Bangladesh have increased significantly at a rate of 0.15 °C/decade and 0.11 °C/decade, respectively. However, the increase of minimum temperature compared to maximum temperature is not high enough to cause a significant change in average diurnal temperature range in Bangladesh. Seasonal DTR trends show a decrease in winter and pre-monsoon DTR, and an increase in monsoon DTR. Spatial distribution of DTR trends shows an increase of annual DTR in the southeastern coastal stations and decrease in the northern stations of Bangladesh. Significant negative relation between rainfall and DTR is observed in Bangladesh. Regression analysis shows that an annual increase of 1% of rainfall is correlated with a decrease of DTR by 0.1 °C.
Trends in Canadian temperature and precipitation during the 20th century are analyzed using recently updated and adjusted station data. Six elements, maximum, minimum and mean temperatures along with diurnal temperature range (DTR), precipitation totals and ratio of snowfall to total precipitation are investigated. Anomalies from the 1961–1990 reference period were first obtained at individual stations, and were then used to generate gridded datasets for subsequent trend analyses. Trends were computed for 1900–1998 for southern Canada (south of 60°N), and separately for 1950–1998 for the entire country, due to insufficient data in the high arctic prior to the 1950s.
Rainfall and temperature data recorded at 17 meteorological stations over the time period 1958–2007 were used to assess recent changes in the climate of Bangladesh. The results show increasing mean, mean maximum and mean minimum temperatures at a rate of 0.103, 0.091 and 0.097°C per decade, respectively. More warming was observed for winter compared to other seasons. Increases in annual and pre-monsoon rainfall were also observed at a rate of 5.53 and 2.47 mm yr–1, respectively. The spatial pattern of rainfall trends shows an increase in annual, monsoon and pre-monsoon rainfall in the western part of Bangladesh. The findings of the present study are consistent with the results obtained in other parts of the Indian subcontinent.
In this study, spatial and temporal patterns of changes in extreme events of temperature and precipitation at 143 weather stations in ten Asia-Pacific Network (APN) countries and their associations with changes in climate means are examined for the 1955–2007 period. Averaged over the APN region, annual frequency of cool nights (days) has decreased by 6.4 days/decade (3.3 days/decade), whereas the frequency of warm nights (days) has increased by 5.4 days/decade (3.9 days/decade). The change rates in the annual frequency of warm nights (days) over the last 20 years (1988–2007) have exceeded those over the full 1955–2007 period by a factor of 1.8 (3.4). Seasonally, the frequencies of summer warm nights and days are changing more rapidly per unit change in mean temperatures than the corresponding frequencies for cool nights and days. However, normalization of the extreme and mean series shows that the rate of changes in extreme temperature events are generally less than that of mean temperatures, except for winter cold nights which are changing as rapidly as the winter mean minimum temperature. These results indicate that there have been seasonally and diurnally asymmetric changes in extreme temperature events relative to recent increases in temperature means in the APN region.
There are no systematic, regional trends over the study period in total precipitation, or in the frequency and duration of extreme precipitation events. Statistically significant trends in extreme precipitation events are observed at fewer than 30% of all weather stations, with no spatially coherent pattern of change, whereas statistically significant changes in extreme temperature events have occurred at more than 70% of all weather stations, forming strongly coherent spatial patterns. Copyright
Climate change will affect irrigation water demand of rice via changes in rice physiology and phenology, soil water balances,
evapotranspiration and effective precipitation. As agriculture is the main sector of water use in Bangladesh, estimation of
the agricultural water demand in the changing environment is essential for long-term water resources development and planning.
In the present paper, a study has been carried out to estimate the change of irrigation water demand in dry-season Boro rice field in northwest Bangladesh in the context of global climate change. The study shows that there will be no appreciable
changes in total irrigation water requirement due to climate change. However, there will be an increase in daily use of water
for irrigation. As groundwater is the main source of irrigation in northwest Bangladesh, higher daily pumping rate in dry
season may aggravate the situation of groundwater scarcity in the region.
A study of the variability of the extreme rainfall events in Bangladesh during the time period 1958–2007 has been carried
out in this paper. Quality-controlled homogeneous daily precipitation records of nine stations distributed over Bangladesh
are used for the study. A total of 15 annual and seasonal indices of rainfall are examined. Variability of annual and seasonal
rainfall trends is also assessed. The Mann–Kendall statistic and Sen's Slope model are used to reveal the trends and estimate
the magnitude of change, respectively. A significant increase of annual and pre-monsoon rainfall in Bangladesh is observed.
In general, an increasing trend in heavy precipitation days and decreasing trends in consecutive dry days are observed. Significant
change in most of the extreme rainfall indices are observed in Northwest Bangladesh.
The consequences of environmental change for human migration have gained increasing attention in the context of climate change and recent large-scale natural disasters, but as yet relatively few large-scale and quantitative studies have addressed this issue. We investigate the consequences of climate-related natural disasters for long-term population mobility in rural Bangladesh, a region particularly vulnerable to environmental change, using longitudinal survey data from 1,700 households spanning a 15-y period. Multivariate event history models are used to estimate the effects of flooding and crop failures on local population mobility and long-distance migration while controlling for a large set of potential confounders at various scales. The results indicate that flooding has modest effects on mobility that are most visible at moderate intensities and for women and the poor. However, crop failures unrelated to flooding have strong effects on mobility in which households that are not directly affected but live in severely affected areas are the most likely to move. These results point toward an alternate paradigm of disaster-induced mobility that recognizes the significant barriers to migration for vulnerable households as well their substantial local adaptive capacity.
This book outlines disaster risk reduction (DRR) approaches in Bangladesh, drawing examples and lessons from the national and community-level programs, projects, and relevant experiences of the country. The content is based on a selection of available documents, a consultative workshop with academicians from different universities undertaking DRR higher education programs, and the editors’ own knowledge and experience in the field. Special emphasis is given to analyzing field experiences from academic perspectives, and to highlighting key issues and the policy relevance of disaster risk reduction.
The book has three parts: Part I provides the outline and basics of DRR, with examples from a global review and from national policies and priorities. Part II covers seven different hazards in Bangladesh, focusing on both shocks and stresses. Part III provides examples of approaches and issues of DRR practices.
The primary target groups for this book are students and researchers in the fields of environment, disaster risk reduction, and climate change studies. The book will provide them with a good idea of the current trend of research in the field and will furnish basic knowledge on this important topic in Bangladesh. Another target group comprises practitioners and policy makers, who will be able to apply collective knowledge to policy and decision making.
(pdf available at http://rdcu.be/urEu) A significant reduction in summer monsoon rainfall has been observed in northern central India during the second half of the twentieth century, threatening water security and causing widespread socio-economic impacts. Here, using various observational data sets, we show that monsoon rainfall has increased in India at 1.34 mm d⁻¹ decade⁻¹ since 2002. This apparent revival of summer monsoon precipitation is closely associated with a favourable land–ocean temperature gradient, driven by a strong warming signature over the Indian subcontinent and slower rates of warming over the Indian Ocean. The continental Indian warming is attributed to a reduction of low cloud due to decreased ocean evaporation in the Arabian Sea, and thus decreased moisture transport to India. Global climate models fail to capture the observed rainfall revival and corresponding trends of the land–ocean temperature gradient, with implications for future projections of the Indian monsoon.
Interactions between the carbon cycle, climate and human societies are subject to several major vulnerabilities, broadly defined as factors contributing to the risk of harm from human-induced climate change. We assess five vulnerabilities: (1) effects of increasing CO2 on the partition of anthropogenic carbon between atmospheric, land and ocean reservoirs; (2) effects of climate change (quantified by temperature) on CO2 fluxes; (3) uncertainty in climate sensitivity; (4) non-CO2 radiative forcing and (5) anthropogenic CO2 emissions. Our analysis uses a physically based expression for T p(Qp), the peak warming T p associated with a cumulative anthropogenic CO2 emission Qp to the time of peak warming. The approximations in this expression are evaluated using a non-linear box model of the carbon‐climate system, forced with capped emissions trajectories described by an analytic form satisfying integral and smoothness constraints. The first four vulnerabilities appear as parameters that influence T p(Qp), whereas the last appears through the independent variable. In terms of likely implications for T p(Qp), the decreasing order of the first four vulnerabilities is: uncertainties in climate sensitivity, effects of non-CO2 radiative forcing, effects of climate change on CO2 fluxes and effects of increasing CO2 on the partition of anthropogenic carbon.
The mean and extreme matrices of the monsoon rainfall in India not only play an important role in depicting the global monsoon climate, but also their spatiotemporal patterns influence the socio-economic profile of a major proportion of the country’s huge population. Given the reported conflicting trends at the global and national scales, the present study investigates the 20th century (1901–2004) changes in monsoon rainfall of India, particularly focusing the indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI) to facilitate a global comparison. Result of this comprehensive analysis, which includes the response of fifteen indices over two study periods (i.e., 1901–1940 and 1961–2004), indicates clear signals of change with respect to the period and region of study and the choice of the ETCCDI indices. While wet day frequency, low-to-moderate events and consecutive wet days (CWD) exhibit a prominent transition from a pre-1940 wetting to a post-1960 drying tendency over a large part of the central-north India (CNI), both the wet and dry extremes have occurred in a spatially less consistent manner during the recent decades. For consecutive dry days (CDD), the reported less clear global signals could be related to the timescale of analysis, as our sub-seasonal scale results display consistent changes compared to that of the seasonal and annual scales. The Palmer Drought Severity Index (PDSI) provides clear indications of a post-1960 non-stationarity, showing changes in the mean as well as variance. Based on the partial Mann–Kendall test (PMK), some of the identified rainfall trends during 1961–2004 are found to be influenced more by the tropical Indian Ocean sea surface temperatures than the El Niño–Southern Oscillation index. These results have important implications for formulating the water resource management strategy, particularly over the drying central and northern parts of the country.
Flashflood and associated landslide are become major disasters in the hilly regions of Bangladesh, occurring almost every year. Flashflood and landslide disasters are caused by a set of preliminary and triggering factors which determine their location, frequency and magnitude. Excessive rainfall in the piedmont area with a high intensity is the main source of flashflood in the hilly area and resultant landslide specifically in the areas composed of unconsolidated rocks. The annual rainfall ranges from 2,200 mm along the western boundary to 5,800 mm in the north-east corner and even higher in different catchments due to monsoon depression. Being the higher order basin of the three largest basins Brahmaputra, Ganges and Meghna all the water discharges through the three major rivers of the country. Due to the higher intensity of rainfall with a shorter period of time these channels could not manage to discharges this deluge amount of water to the downstream to Bay of Bengal resultant sudden flood and associated landslide. Apart from physiology, hydrology and climatology, the changes in the geomorphology in relation to land use changes as well as deforestation, hill cutting and unplanned infrastructural development influences flashflood and landslide disaster impact further. Among the hilly region part of the north-eastern, north–south and northern regions are susceptible to and facing these disaster almost each year. Lack of proper landuse planning, weak enforcement by the local authorities increases risks and progress vulnerability significantly. Although the authority has taken initiatives of integrated planning including structural and non-structural measure to mitigate the damages by the disasters, lack of capacity of forecasting appropriately does not provide with sufficient lead time to reduce damages of personal property and economic assets. Further initiatives requires for basin wide integrated water resources management, increasing water retention capacity, early warning, landuse zoning and public awareness for effective management of flashflood and landslide disasters. The main objective of this chapter is to identify mountain risks and vulnerability of Bangladesh due to flashflood and landslide hazard and their underlying causes and effects. This discussion will also provide with some recommendations and policy implication for effective adaptation and mitigation measures.
The disastrous floods in Bangladesh in 1987 and 1988 captured world-wide attention. That country is particularly prone to natural disasters which constantly undermine government and international efforts to improve social and economic conditions. The floodplains which occupy 80 per cent of Bangladesh have diverse characteristics and are affected by flash floods, river floods and rainwater floods to different extents. The 1987 floods were predominantly rainwater floods caused by exceptionally heavy monsoon rainfall over northern parts of the country. The 1988 floods were mainly river floods caused by heavy monsoon rainfall over a wider area of the Ganges and Brahmaputra river catchments (more than 90 per cent of which lie outside Bangladesh). In both years, breaching or cutting of embankments aggravated flooding. Despite considerable crop damage, there were compensatory increases in production in areas not affected by the floods and in the following dry season.
Efforts to limit climate change below a given temperature level require that global emissions of CO2 cumulated over time remain below a limited quota. This quota varies depending on the temperature level, the desired probability of staying below this level and the contributions of other gases. In spite of this restriction, global emissions of CO2 from fossil fuel combustion and cement production have continued to grow by 2.5% per year on average over the past decade. Two thirds of the CO2 emission quota consistent with a 2 [deg]C temperature limit has already been used, and the total quota will likely be exhausted in a further 30 years at the 2014 emissions rates. We show that CO2 emissions track the high end of the latest generation of emissions scenarios, due to lower than anticipated carbon intensity improvements of emerging economies and higher global gross domestic product growth. In the absence of more stringent mitigation, these trends are set to continue and further reduce the remaining quota u
Haors are large, round-shaped floodplain depressions located in the North-Eastern region of Bangladesh. Extreme events such as heavy rainfall routinely affect the haor basin with flash floods. These haors are predicted to experience severe stress because of changes in rainfall and temperature patterns. The biotic community of the wetlands may not have enough time to adjust itself in such varying temperature and rainfall extremes. This paper evaluates various aspects of the future projections of rainfall and temperature extremes, including magnitudes and frequencies thereof. The impacts of extreme events are examined using Hadley Centre's high-resolution regional climate model known as PRECIS (Providing REgional Climates for Impact Studies). Daily temperature and rainfall simulations of the 17-member ensembles are generated through Hadley Centre Coupled Model (HadCM3). These simulations are used in Rclimdex—a software specially designed for this study. A total of 12 core climate indices are computed, analyzed, and statistically examined (Mann-Whitney U test) over the space of three time slices—(1) short (2020s, i.e., 2011-2040), (2) medium (2050s, i.e., 2041-2070), and (3) long (2080s, i.e., 2071-2098). Here, the 1980s (1971-2000) are considered as the baseline period. The study has found that the highest significant variability in both rainfalls and temperatures was during the pre-monsoon season when flash floods normally occur. Also, rainy days are projected to be less frequent albeit more intense where the deeply flooded haors are located. Though the annual total rainfall does not show any difference in spatial distribution (except for in magnitude), the seasonal patterns of most extreme events show that the probable affected areas have shifted from North-east to further North. In addition, a significant increase in both RX1 (1-day maximum rainfall) and RX5 (5-day maximum rainfall) are projected during the 2080's pre-monsoon season near Sunamganj. This projection also indicates the possible frequent occurrence of flash floods with high volumes. Probability distribution frequencies (PDF) show a rightward shift in time indicating an increase in the amount of total rainfall in the future. Exceptions are, however, found in case of PDFs for consecutive dry days (CDD) and consecutive wet days (CWD). The decrease in CWD is found to be more pronounced than that of CDD. All these projections made in this study are expected to contribute further in the advancements of the Master Planning of the haor area that was done by the government of Bangladesh in 2012.
A statistical framework is presented for the assessment of climatological trends in the frequency of rare and extreme weather events. The methodology applies to long-term records of event counts and is based on the stochastic concept of binomial distributed counts. It embraces logistic regression for trend estimation and testing, and includes a quantification of the potential/limitation to discriminate a trend from the stochastic fluctuations in a record. This potential is expressed in terms of a detection probability, which is calculated from Monte Carlo-simulated surrogate records, and determined as a function of the record length, the magnitude of the trend and the average return period (i.e., the rarity) of events.Calculations of the detection probability for daily events reveal a strong sensitivity upon the rarity of events:in a 100-yr record of seasonal counts, a frequency change by a factor of 1.5 can be detected with a probability of 0.6 for events with an average return period of 30 days; however, this value drops to 0.2 for events with a return period of 100 days. For moderately rare events the detection probability decreases rapidly with shorter record length, but it does not significantly increase with longer record length when very rare events are considered. The results demonstrate the difficulty to determine trends of very rare events, underpin the need for long period data for trend analyses, and point toward a careful interpretation of statistically nonsignificant trend results.The statistical method is applied to examine seasonal trends of heavy daily precipitation at 113 rain gauge stations in the Alpine region of Switzerland (1901-94). For intense events (return period: 30 days) a statistically significant frequency increase was found in winter and autumn for a high number of stations. For strong precipitation events (return period larger than 100 days), trends are mostly statistically nonsignificant, which does not necessarily imply the absence of a trend.
Long term changes of near surface air temperature over Bangladesh have been studied using the available historical data collected by the Bangladesh Meteorological Department (BMD). Maximum and minimum daily temperature data of last sixty years (1948-2007) collected from 34 stations of BMD located all over the Bangladesh have been used in this study. It has been found that daily maximum temperature shows a positive trend of increase at a rate of 0.621 ± 0.491 0C per 100 year. The maximum increase occurred during November at a rate of 2.7 0C per 100 year. However, daily minimum temperature shows more significant trend of increase at a rate of 1.536 ± 0.461 0 C per 100 year. The maximum increase occurred during February at a rate of 3.4 0C per 100 year. Daily mean temperature shows positive trend of increase at a rate of 1.026 ± 0.403 0C per 100 year. It has been clearly found that temperature of winter season (December to February) has been raised much higher rate than that of summer season (June to August). This study also reveals that temperature has been increase predominantly over the last 30 years (1978-2007) than last 60 years (1948-2007).
Changes in indices of climate extremes are analyzed on the basis of daily maximum and minimum surface air temperature and precipitation at 71 meteorological stations with elevation above 2000 m above sea level in the eastern and central Tibetan Plateau (TP) during 1961–2005. Twelve indices of extreme temperature and nine indices of extreme precipitation are examined. Temperature extremes show patterns consistent with warming during the studied period, with a large proportion of stations showing statistically significant trends for all temperature indices. Stations in the northwestern, southwestern, and southeastern TP have larger trend magnitudes. The regional occurrence of extreme cold days and nights has decreased by −0.85 and −2.38 d/decade, respectively. Over the same period, the occurrence of extreme warm days and nights has increased by 1.26 and 2.54 d/decade, respectively. The number of frost days and ice days shows statistically significant decreasing at the rate of −4.32 and −2.46 d/decade, respectively. The length of growing season has statistically increased by 4.25 d/decade. The diurnal temperature range exhibits a statistically decreasing trend at a rate of −0.20°C per decade. The extreme temperature indices also show statistically significant increasing trends, with larger values for the index describing variations in the lowest minimum temperature. In general, warming trends in minimum temperature indices are of greater magnitude than those for maximum temperature. Most precipitation indices exhibit increasing trends in the southern and northern TP and show decreasing trends in the central TP. On average, regional annual total precipitation, heavy precipitation days, maximum 1-day precipitation, average wet days precipitation, and total precipitation on extreme wet days show nonsignificant increases. Decreasing trends are found for maximum 5-day precipitation, consecutive wet days, and consecutive dry days, but only the last is statistically significant.
In this paper, the development of a statistical forecasting method for summer monsoon rainfall over Bangladesh is described. Predictors for Bangladesh summer monsoon (June–September) rainfall were identified from the large scale ocean–atmospheric circulation variables (i.e., sea-surface temperature, surface air temperature and sea level pressure). The predictors exhibited a significant relationship with Bangladesh summer monsoon rainfall during the period 1961–2007. After carrying out a detailed analysis of various global climate datasets; three predictors were selected. The model performance was evaluated during the period 1977–2007. The model showed better performance in their hindcast seasonal monsoon rainfall over Bangladesh. The RMSE and Heidke skill score for 31 years was 8.13 and 0.37, respectively, and the correlation between the predicted and observed rainfall was 0.74. The BIAS of the forecasts (% of long period average, LPA) was −0.85 and Hit score was 58%. The experimental forecasts for the year 2008 summer monsoon rainfall based on the model were also found to be in good agreement with the observation.
The least squares estimator of a regression coefficient β is vulnerable to gross errors and the associated confidence interval is, in addition, sensitive to non-normality of the parent distribution. In this paper, a simple and robust (point as well as interval) estimator of β based on Kendall's [6] rank correlation tau is studied. The point estimator is the median of the set of slopes (Yj - Yi)/(tj-ti) joining pairs of points with ti ≠ ti, and is unbiased. The confidence interval is also determined by two order statistics of this set of slopes. Various properties of these estimators are studied and compared with those of the least squares and some other nonparametric estimators.
Within the field of hazard research, vulnerability studies have been central to inducing a shift in the perspective on disasters as being primarily inflicted by geophysical events to that of apprehending disasters as destructive outcomes of particular social as well as hazardous environmental conditions. However, the inherent tendency within vulnerability studies to classify certain areas or people as ‘vulnerable’ may in some cases also serve to reinforce popular and/or ingrained prejudices, negative stereotypes and dubious explanations of the living conditions and fate of specific communities that become so labelled. The riverbanks and islands in river courses of Bangladesh have long been portrayed as home to the ‘poorest’ and most vulnerable communities, the widespread assumption being that people would only live in such riverine environments because they have no other options. Drawing on an examination of existing literature on char settlements in Bangladesh and data from a field site in the Jamuna River, this paper argues that the prevailing perceptions and labelling of char dwellers as ‘vulnerable’ people is based on a far too simplistic understanding of both rural migration patterns and the livelihoods obtained in these riverine areas.
We analyse 20th century trends in six indices for precipitation extremes and four indices for temperature extremes, calculated from daily observational data for European stations. The indices chosen reflect rather moderate extremes. Most of the ∼80 stations used are situated in central and western Europe; therefore, results mainly refer to this region. Trends are calculated over 1901–99, 1921–99, 1901–50 and 1946–99. Two different trend estimators are used, and significance is assessed with a bootstrap technique. We find that:
Indices for climate variability and extremes have been used for a long time, often by assessing days with temperature or precipitation observations above or below specific physically‐based thresholds. While these indices provided insight into local conditions, few physically based thresholds have relevance in all parts of the world. Therefore, indices of extremes evolved over time and now often focus on relative thresholds that describe features in the tails of the distributions of meteorological variables. In order to help understand how extremes are changing globally, a subset of the wide range of possible indices is now being coordinated internationally which allows the results of studies from different parts of the world to fit together seamlessly. This paper reviews these as well as other indices of extremes and documents the obstacles to robustly calculating and analyzing indices and the methods developed to overcome these obstacles. Gridding indices are necessary in order to compare observations with climate model output. However, gridding indices from daily data are not always straightforward because averaging daily information from many stations tends to dampen gridded extremes. The paper describes recent progress in attribution of the changes in gridded indices of extremes that demonstrates human influence on the probability of extremes. The paper also describes model projections of the future and wraps up with a discussion of ongoing efforts to refine indices of extremes as they are being readied to contribute to the IPCC's Fifth Assessment Report. WIREs Clim Change 2011, 2:851–870. doi: 10.1002/wcc.147
This article is categorized under: Paleoclimates and Current Trends > Modern Climate Change
The detection of the spatio-temporal extent of inundation resulting from the floods in 2004 and 2007 in Bangladesh has been studied using time-series MODIS surface reflectance data. Flood inundation maps were developed from vegetation and land water surface indices derived using surface reflectance. The inundation map developed using MODIS data was compared with a corresponding RADARSAT image, where both images refer to the satellite-based remote-sensing data. The estimates show a strong correlation with the inundation area derived from the RADARSAT products (coefficient of determination of R2: 0.96). The paper shows that it is possible to study flood dynamics by assessing inundation and recession patterns and to perform flood assessments similar to the high-resolution (50 m) microwave satellite, RADARSAT-based flood assessments using products derived from MODIS 500 m imagery. MODIS has advantages over microwave satellite because it has a high observational frequency and these data are available free of cost. We have concluded that this is a useful method to assess the extent of the temporal floods in the People's Republic of Bangladesh.
The intensity distribution of daily precipitation amounts in the UK has changed over the period 1961 – 1995, becoming on average more intense in winter and less intense in summer. This result is based on an analysis of 110 UK station records. In winter, and in terms of their relative contributions to total winter precipitation, there has been a decline in light and medium events and an increase in the heaviest events. This change is fairly uniform across the whole country and is apparent even when longer records (with reduced spatial coverage/detail) are analysed back to 1931 or 1908. The reverse is found in summer: over 1961 – 1995 there has been a decline in the proportion of the seasonal total being provided by the heaviest events. In the longer term context, however, the summer changes appear to be a return to earlier levels after a period in the 1960s when heavy summer rainfall made a greater than normal contribution. More complex changes have occurred in the intensity distribution of spring and autumn precipitation, with opposite changes in different regions of the UK. Copyright © 2000 Royal Meteorological Society.
Five ideas constitute the central message of this study. First, urban rickshaw pullers come from a very poor economic background consistent with the characteristics of chronic poverty. Second, rickshaw pulling provides a route of modest upward mobility for those among the rural chronically poor who come to the city for work. Third, the rickshaw pullers are susceptible to systematic health risks. Deteriorating health combined with health shocks can impose a significant burden on the urban poor, dragging down the pace of upward mobility during their lifetime. Fourth, the activity of rickshaw pulling represents an unsustainable livelihood, as the initial welfare gain tapers off with length of involvement in the sector. As longitudinal data is lacking, this story has emerged through an inductive comparison of younger, recent joiners and long duration, older rickshaw pullers, as well as current and former pullers. Fifth, intergenerational mobility of rickshaw puller households is constrained by very limited schooling and the poor range of occupational choices for children. Public policy has an important role to play in mitigating health shocks, as well as supporting targeted education for the urban poor in the informal sector, for sustainable urban poverty reduction.
Trends in daily temperature and rainfall indices are described for New Zealand. Two periods were examined: 1951–1998, to describe significant trends in temperature and rainfall parameters; and 1930–1998, to ascertain the effects of two main circulation changes that have occurred in the New Zealand region around 1950 and 1976.Indices examined included frequencies of daily maximum and minimum temperatures, above and below specified percentile levels and at those levels, as well as frequencies of these above and below fixed temperature thresholds. Extreme daily rainfall intensity and frequency above the 95th percentile and the length of consecutive dry day sequences were the rainfall indices selected.There were no significant trends in maximum temperature extremes (‘hot days’) but a significant increase in minimum temperatures was associated with decreases in the frequency of extreme ‘cold nights’ over the 48-year period. There was a non-significant tendency for an increase in the frequency of maximum temperature extremes in the north and northeast of New Zealand. A decline occurred in frequency of the minimum temperature 5th percentile (‘cold nights’) of 10–20 days a year in many locations. Trends in rainfall indices show a zonal pattern of response, with the frequency of 1-day 95th percentile extremes decreasing in the north and east, and increasing in the west over the 1951–1996 period.Changes in the frequency of threshold temperatures above 24.9°C (25°C days) and below 0°C (frost days) are strongly linked to atmospheric circulation changes, coupled with regional warming. From 1930–1950 more south to southwest anomalous flow occurred relative to later years. In this period, 25°C days were less frequent in all areas except the northeast, and there was markedly more frost days in all but inland areas of the South Island compared with the 1951–1975 period. There was more airflow from the east and northeast from 1951 to 1975, the frequency of 25°C days increased and frost days decreased in many areas of New Zealand. In the final period examined (1976–1998), more prevalent airflow from the west and southwest was accompanied by more anticyclonic conditions. Days with a temperature of 25°C increased in the northeast only. Frost day frequencies decreased between 5 and 15 days a year in many localities, with little change in the west of the South Island and at higher elevation locations. Copyright © 2001 Royal Meteorological Society
This study investigated using Monte Carlo simulation the interaction between a linear trend and a lag-one autoregressive (AR(1)) process when both exist in a time series. Simulation experiments demonstrated that the existence of serial correlation alters the variance of the estimate of the Mann–Kendall (MK) statistic; and the presence of a trend alters the estimate of the magnitude of serial correlation. Furthermore, it was shown that removal of a positive serial correlation component from time series by pre-whitening resulted in a reduction in the magnitude of the existing trend; and the removal of a trend component from a time series as a first step prior to pre-whitening eliminates the influence of the trend on the serial correlation and does not seriously affect the estimate of the true AR(1). These results indicate that the commonly used pre-whitening procedure for eliminating the effect of serial correlation on the MK test leads to potentially inaccurate assessments of the significance of a trend; and certain procedures will be more appropriate for eliminating the impact of serial correlation on the MK test. In essence, it was advocated that a trend first be removed in a series prior to ascertaining the magnitude of serial correlation. This alternative approach and the previously existing approaches were employed to assess the significance of a trend in serially correlated annual mean and annual minimum streamflow data of some pristine river basins in Ontario, Canada. Results indicate that, with the previously existing procedures, researchers and practitioners may have incorrectly identified the possibility of significant trends. Copyright © Environment Canada. Published by John Wiley & Sons, Ltd.
Climate change in the future would have implications for river discharges in Bangladesh. In this article, possible changes in the magnitude, extent and depth of floods of the Ganges, Brahmaputra and Meghna (GBM) rivers in Bangladesh were assessed using a sequence of empirical models and the MIKE11-GIS hydrodynamic model. Climate change scenarios were constructed from the results of four General Circulation Models (GCMs) –CSIRO9, UKTR, GFDL and LLNL, which demonstrate a range of uncertainties. Changes in magnitude, depth and extent of flood discharge vary considerably between the GCMs. Future changes in the peak discharge of the Ganges River are expected to be higher than those for the Brahmaputra River. Peak discharge of the Meghna River may also increase considerably. As a result, significant changes in the spatial extent and depths of inundation in Bangladesh may occur. Faster changes in inundation are expected at low temperature increases than of higher temperature changes. Changes in land inundation categories may introduce substantial changes in rice agriculture and cropping patterns in Bangladesh. Reduction of increased flood hazard due to climate change requires strengthening of flood management policies and adaptation measures in Bangladesh.
Bangladesh is known to behighly vulnerable to floods. Frequent floods have put enormous constraints on its development potential. Unfortunately, the frequency of high intensity floods is on the rise. So far the country has struggled to put a sizeable infrastructure in place to prevent flooding in may parts of the country with limited success. In recent times, it was found that losses of lives and valuable assets could be significantly minimized by implementing non-structural measures including the improvement of flood forecasting and warning system. The existing flood forecasting and warning capacity of Bangladesh could be more effective if real-timedata could be acquired from upstreamareas within the Ganges-Brahmaputra-Meghna (GBM) catchment, where runoff is generated. In order to do so, Bangladesh needs to foster an effective regional cooperationwith the other GBM regional countries of India, Nepal, and Bhutan. This article examines how GBM regional cooperation could be useful towards managing floods in Bangladesh in particularand the region in general.