Atmospheric Research 118 (2012) 260–270

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Changes in diurnal temperature range in Bangladesh during the timeperiod 1961–2008

Shamsuddin Shahid⁎, Sobri Bin Harun, Ayob KatimonDepartment of Hydraulics and Hydrology, Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310 UTM, Johor, Malaysia

a r t i c l e i n f o

⁎ Corresponding author. Tel.: +60 7 5531624; fax:E-mail address: sshahid_ait@yahoo.com (S. Shahid

0169-8095/$ – see front matter © 2012 Elsevier B.V. Adoi:10.1016/j.atmosres.2012.07.008

a b s t r a c t

Article history:Received 13 July 2011Received in revised form 10 July 2012Accepted 10 July 2012

Diurnal temperature range (DTR) is a meteorological indicator independent of internal climatevariation and therefore, considered as a signature of observed climate change. It has beenobserved 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 inthis paper to analyze the spatial and seasonal patterns in the trends of DTR in Bangladesh. Dailytemperature data from18 stations for the timeperiod 1961–2008has beenused for the study. Theresult shows that both mean minimum and mean maximum temperatures of Bangladesh haveincreased significantly at a rate of 0.15 °C/decade and 0.11 °C/decade, respectively. However, theincrease of minimum temperature compared to maximum temperature is not high enough tocause a significant change in average diurnal temperature range in Bangladesh. Seasonal DTRtrends showa decrease inwinter and pre-monsoon DTR, and an increase inmonsoon DTR. Spatialdistribution of DTR trends shows an increase of annual DTR in the southeastern coastal stationsand decrease in the northern stations of Bangladesh. Significant negative relation between rainfalland DTR is observed in Bangladesh. Regression analysis shows that an annual increase of 1% ofrainfall is correlated with a decrease of DTR by 0.1 °C.

© 2012 Elsevier B.V. All rights reserved.

Keywords:Diurnal temperature rangeClimate changeTrend analysisBangladesh

1. Introduction

Diurnal temperature range (DTR) is a meteorologicalindicator associated with global climate change. Karoly et al.(2003) and Braganza et al. (2003) reported that a set ofmultiple climate indices, that are independent in internalclimate variations, shows a coherent response to greenhouseforcing, and provides additional information for the detectionand attribution of climate change in much the samemanner asspatial fingerprints of climate change. Braganza et al. (2004)proposed that changes in daily maximum and minimumtemperatures provide more information than the mean alonebecause trends in mean surface temperature can be due tochanges in either maximum or minimum temperature, orrelative changes in both. Therefore, the diurnal temperaturerange, i.e. the difference between maximum and minimum

+ 60 7 5566157.).

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temperatures,may be useful in defining a signature of observedclimate change that is less likely to showa common response todifferent radiative forcingmechanisms. DTR is considered as animportant index of climate change and is receiving consider-able attention in various regions of the globe in recent times(Plummer et al., 1995; Kaas and Frich, 1995; Razuvaev et al.,1995; Price et al., 1999; Roy and Balling, 2005; Englehart andDouglas, 2005; Makowski et al., 2008; Jhajharia and Singh,2011; Sang, 2012).

It has been observed that global averaged DTR hasdecreased substantially during 1950–1990 (Karl et al., 1991;Easterling et al., 1997). The decrease in DTR has regional andseasonal characteristics. For most parts of the world, nighttimetemperature has risen faster than the daytime temperature,producing a smaller DTR (Karl et al., 1991). However, in someplaces, daytime temperature has decreased while nighttimetemperature has increased (Karl et al., 1993; Kukla and Karl,1993). Though a number of studies have been carried out in therecent years on climate variability in Bangladesh (Rahman et

261S. Shahid et al. / Atmospheric Research 118 (2012) 260–270

al., 1997; Jones, 1995; Singh, 2001; Shahid, 2008; Shahid andKhairulmaini, 2009; Shahid, 2010b, 2010c, 2011b), no analysishas been carried out so far on DTR. A number of investigationson DTR have been reported in neighboring India (Rupa Kumaret al., 1994; Yadav et al., 2004; Roy and Balling, 2005; FowlerandArcher, 2006; Jhajharia and Singh, 2011). RupaKumar et al.(1994) reported an increase in daily maximum temperatureand no change in minimum temperature and consequently, anincrease in DTR over the Indian subcontinent. Yadav et al.(2004) reported an increase in DTR due to a relatively highdecrease inminimum temperature and an increase inmaximumtemperature in the western Himalayas. Roy and Balling (2005)analyzed the seasonal trends in the maximum and minimumtemperature, DTR, and cloud cover over India for the time period1931–2002 and found that the trends in DTR are not significantfor most of the country except for a decrease in NorthwestKashmir in summer. Fowler and Archer (2006) reported largeincreases in DTR in all the seasons over the Karakoram andHindu Kush Mountains of the Upper Indus basin during theperiod 1961–2000. Bhutiyani et al. (2007) observed increasingtrends in temperature range in northwestern Himalayan region.Jhajharia and Singh (2011) found a decrease in DTR in northeastIndia bordering Bangladesh. The studies reveal spatial pattern ofincreasing and decreasing DTR in Indian subcontinent.

Trends in annual and seasonal DTRs of Bangladesh during thetime period 1961–2008 are assessed and their spatial patternsare presented in this paper. Daily temperature data from 18stations distributed over Bangladesh are used for the study. Forseasonal analysis of DTRs, each year is divided into four seasonsdepending upon climatic conditions prevailing over the country.Mann–Kendall test (Mann, 1945; Kendall, 1975) is used to detectthe trend and the Sen's slope method (Sen, 1968) is used todetermine the magnitude of change in temperature time series.The Monte Carlo simulation technique is used to determine thesignificance of the regional trend pattern of Bangladesh (Serra etal., 2006). Climate is a dynamic phenomenon, which changesover time and space. Complete analysis of climatic eventsrequires to study both spatial and temporal extents (Shahidand Khairulmaini, 2009; Shahid, 2010b). Climatic investigationover a large area requires assimilation of information frommanysites each with a unique geographic location. GeographicalInformation System (GIS) maintains the spatial location ofsampling points, and provides tools to relate the sampling datacontained through a relational database (Shahid et al., 2000). Inthe present paper, GIS is used to analyse the spatial variation oftemperature and DTR trends.

2. Climate of Bangladesh

Situated in lower Gangetic plains, Bangladesh has atropical humid climate characterized by wide seasonalvariations in rainfall, moderately warm temperatures, andhigh humidity (Rashid, 1991). Four distinct seasons can berecognized in Bangladesh from climatic point of view (Shahidand Khairulmaini, 2009): (i) the dry winter season fromDecember to February, (ii) the pre-monsoon hot summerseason from March to May, (iii) the rainy monsoon seasonfrom June to September, and (iv) the post-monsoon autumnseason which lasts from October to November. Rainfallvariability in space and time is one of the most relevantcharacteristics of the climate of Bangladesh (Shahid and

Khairulmaini, 2009). Average annual rainfall in Bangladeshvaries from1400 mm in thewest tomore than4400 mmin theeast. The gradient of rainfall is almost 7 mm/km from west toeast of the country (Shahid and Khairulmaini, 2009). Monthlydistribution of maximum and minimum temperatures ofBangladesh is shown in Fig. 1. The average temperature of thecountry ranges from 19.2 °C to 22.0 °C during winter and from29.7 °C to 31.3 °C during summer. January is the coldestmonthand May is the hottest month in Bangladesh. Spatial distribu-tion of average maximum and minimum temperatures ofBangladesh for the years 1961–2008 are shown in Fig. 2(a) and(b) respectively. The figures show that the mean maximumtemperature gradient is oriented in northeast to southwest withthe warmer zone in the southwest and the cooler zone in thenortheast. On the other hand, the mean minimum temperaturegradient is oriented in north to south directionwith the southernpart is 5 °C warmer than the northern part of Bangladesh.

3. Data and methods

Long-term daily temperature data (1961–2008) recordedby Bangladesh Meteorological Department (BMD) availableat 18 stations are used in the present study to assess thechanges in DTRs of Bangladesh. Location of meteorologicalstations in the map of Bangladesh is shown in Fig. 3. It can beseen from the figure that meteorological stations under studyare distributed over the country. The topography of Bangladeshis extremely flat with some upland in the northeast and thesoutheast. Therefore, it can be considered that the meteoro-logical stations under study represent the climate of wholeBangladesh.

Before analyzing the trend in DTR, homogeneity of tem-perature time series data is tested. Several strategies have beendescribed in the literature to detect non-homogeneities in thedata series (Peterson et al., 1998; Aguilar et al., 2005; You et al.,2008; Tabari et al., 2011). In this paper, both the subjectivedouble mass curve method (Kohler, 1949) and the objectivestudent's T test (Panofsky and Brier, 1968) are applied to theannual average temperature time series of each station. Resultsof the doublemass curves of all stations are almost a straight line.No breakpoints are detected in the time series of temperature.Student's T test is also used to assess homogeneity by determin-ing whether or not various samples are derived from the samepopulation (Panofsky and Brier, 1968). The results reveal thatthere is no statistically significant variation exists in the tem-perature time series.

Mann–Kendall test is applied to detect the trends in DTRtime series and the Sen's slope method is used to determinethe magnitude of changes. Confidence levels of 95% and 99%are taken as thresholds to classify the significance of positiveand negative trends. The significance of the regional trendpattern is determined by using Monte Carlo simulationtechnique. Themethods used in the present study are discussedbelow.

3.1. Trend analysis by Mann–Kendall test

In Mann–Kendall trend test (Mann, 1945; Kendall, 1975)the data are evaluated as an ordered time series. Each data iscompared to all subsequent data. The initial value of theMann–Kendall statistic, S, is assumed to be 0 (e.g., no trend).

Fig. 1. Monthly distribution of maximum and minimum temperatures ofBangladesh.

Fig. 2. Maps showing spatial distribution of (a) mean maximum temperature;(b) mean minimum temperatures of Bangladesh.

262 S. Shahid et al. / Atmospheric Research 118 (2012) 260–270

If a data from a later time period is higher than a data from anearlier time period, S is incremented by 1. On the other hand,if the data from a later time period is lower than a datasampled earlier, S is decremented by 1. The net result of allsuch increments and decrements yields the final value of S. Ifx1, x2, x3 … xi represent n data points where xj represents thedata point at time j, then S is given by,

S ¼Xn−1

k¼1

Xnj¼kþ1

sign xj−xk� �

: ð1Þ

Where:

sign xj−xk� �

¼ 1 if xj−xk > 0¼ 0 if xj−xk ¼ 0¼ −1 if xj−xk b 0:

The probability associated with S and the sample size, n,are then computed to statistically quantify the significance ofthe trend. Normalized test statistic Z is computed as follows:

Z ¼ S−1ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiVAR Sð Þp if S > 0

¼ 0 if S ¼ 0¼ S−1ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

VAR Sð Þp if S > 0:

ð2Þ

At the 99% significance level, the null hypothesis of notrend is rejected if |Z|>2.575; at 95% significance level, thenull hypothesis of no trend is rejected if |Z|>1.96; and at 90%significance level, the null hypothesis of no trend is rejected if|Z|>1.645. More details of Mann–Kendall test can be found inSneyers (1990).

3.2. Sen's slope method

Sen's slope method (Sen, 1968) involves computing slopesfor all the pairs of ordinal time points and then using themedian of these slopes as an estimate of the overall slope. TheSen's method assumed that the trend is linear. This means thatthe continuous monotonic increasing or decreasing function oftime, f(t), is equal to

f tð Þ ¼ Qt þ B ð3Þ

where, Q is the slope and B is a constant. To get the slope, Q inEq. (3) first the slopes of all data pairs are calculated,

Q ′ ¼ xt′−xtt′−t

: ð4Þ

Fig. 3. Location of meteorological stations in Bangladesh.

263S. Shahid et al. / Atmospheric Research 118 (2012) 260–270

Where, Q′ = slope between data points xt′ and xtxt′ = data measurement at time t′xt = data measurement at time t.

Sen's estimator of slope is simply given by themedian slope,

Q ¼ Q ′ N þ 12

� � if N is odd

¼ Q ′ N2

� � þ Q ′ N þ 22

� �0B@

1CA=2 if N is even: ð5Þ

Where, N is the number of calculated slopes.Details of Sen's slope estimation can be found in Sen (1968).For themapping of spatial pattern of trends from point data

kriging interpolation method is used. Geostatistical analysistool of ArcMap 9.1 (ESRI, 2004) is used for this purpose.

3.3. Monte Carlo simulation for field significance

Monte Carlo simulation allows an assessment of whethertrends have occurred by chance and it is especially appropriatewhen spatial correlation between time series exists.Monte Carlosimulations have been used widely to detect field significanttrends (Chu and Wang, 1997; Zhang et al., 2004; Serra et al.,2006).

Time series of DTR at each station are concurrently shuffledusing a random number generator and linear regression slopeis estimated at each station. The total number of stationsshowing significance at 95% (or 99%) confidence levels iscounted and denoted as Ni

mc, where the superscript i denotesthe i-th trial and the subscript mc denotes the Monte Carloexperiments. The procedure is repeated for 1000 times. Thefield is considered to be significant at the 95% (99%) level whenN exceeds N*mc, where N*mc is the 95 (or 99) percentile of alocally significant trend from 1000 trials.

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4. Results and discussion

The analysis of temperature time series reveals changes inboth temperature and DTR of Bangladesh over the time period1961–2008. The obtained results are described in the followingsections.

4.1. Diurnal temperature range characteristics

Averaged daily minimum and maximum temperatures inBangladesh are shown in Fig. 4(a). The figure shows that theDTR in Bangladesh is higher in winter and lower in monsoon.Average DTR in monsoon is 6.1 °C. It increases to 12.9 °C inwinter. The reason is that cloudiness and rainfall are morecommon during monsoon.

There is a strong relation between cloud cover and DTR(Karl et al., 1993; Dai et al., 1997, 1999; Jackson and Forster,2010). Greater cloud cover is strongly associated with smallerDTR (Karl et al., 1993; Dai et al., 1997, 1999; Travis et al., 2004;Zhou et al., 2009; Rai et al., 2012). Low-level clouds are moreinfluential for DTR than medium- or high-level clouds (Karl et

Fig. 4. (a) Seasonal distribution of average daily minimum and maximumtemperatures; and (b) spatial distribution of average DTR in Bangladesh.

al., 1993; Geerts, 2003; Dai et al., 1999). The increase in cloudstends to decrease maximum temperature, whereas its neteffect on minimum temperature is relatively small due to thefact that clouds reflect sunlight which reduces afternoontemperatures and thus minimum temperature, but on theother hand it also enhances downward long-wave radiationwhich increasesminimum temperature andhence causesDTR todecrease (Rai et al., 2012). Karl et al. (1993) found a correlationbetween cloud cover and DTR for the United States. Dai et al.(1997) observed that regions where cloud cover increased overthe 20th century, DTR has decreased. Dai et al. (1999) reportedthat the reduction in DTR in the United States and Eurasia isassociated with cloud cover. Zhou et al. (2009) found thatinverse relationship between DTR and clouds/precipitationreported previously by Karl et al. (1993) and Dai et al. (1999) isrobust over almost all regions after the dominant long-termtrends are removed. Jhajharia and Singh (2011) also found asignificant correlation between DTR and sunshine duration innortheast India bordering Bangladesh.

The cloud cover has two opposing seasonal patterns inBangladesh. Duringwinter the cloud cover is at aminimum, onan average of about 10% almost all over the country. With theprogression of the season the cloud cover increases. It reaches50–60% by the end of the pre-monsoon hot season, 85–90%during the summer monsoon season, and drops to 25–50%after the withdrawal of the summer monsoon (Banglapedia,2003). It has been remarked that like other parts of the world,cloud cover is themain responsible factor for seasonal variationof DTRs in Bangladesh. High cloud covers in monsoon reducedaytime solar radiation reaching the surface, lessen maximumtemperatures and reduce the DTR. On the other hand, lowcloud covers in winter allow more daytime solar radiationreaching the surface and hencewarmup the surfacemore fromthe morning low temperature compared to that in monsoon.

Spatial distribution of average DTR over Bangladesh isshown in Fig. 4(b). The figure shows that DTR is lower in thecoastal areas and higher in the inlands. The result is consistentwith the findings of other researchers (Geerts, 2003; Jacksonand Forster, 2010). Jackson and Forster (2010) reported thatcoastal areas have relatively low DTR values due to theinfluence of the marine environment. Greater distance inlandis usually associated with larger DTR. Geerts (2003) reportedthat in the 30–150-km range, DTR is greater the further inlandone goes and this effect is more pronounced in the tropicalregion. Up to 150 km, distance inland shows the amelioratingeffects of sea breezes on DTR in coastal regions (which cooldaytime temperatures) and also the influence of cloud coverchanges. The increase in DTR with an increasing distanceinland beyond 150 km is also statistically significant (Geerts,2003).

Fig. 4(b) also shows that inland DTRs are higher in thenorthwest part of Bangladesh and lower in the southeastBangladesh. This is due to the spatial variation of cloud coverin Bangladesh. The cloud cover is more extensive in thesoutheastern parts compared to that in the northwesternpart. During monsoon and post-monsoon the cloud cover isabout 90% and 50%, respectively in the southern and easternparts compared to 75% and 25%, respectively in the northwest-ern part of the country. Rainfall in the west of Bangladesh isless compared to that in the east (Shahid and Khairulmaini,2009).

Table 1Trends in diurnal temperature range in different stations of Bangladesh. Values in the table are changes per decade.

Stations Winter Pre-monsoon Monsoon Post-monsoon Annual

Barisal 0.00 0.08 0.22⁎⁎ 0.16 0.14⁎⁎

Bogra −0.37⁎⁎ −0.56⁎⁎ 0.22⁎⁎ 0.15 −0.14⁎⁎

Chittagong 0.19⁎ 0.04 0.09⁎ 0.31⁎⁎ 0.17⁎⁎

Comilla −0.20⁎ 0.02 0.16⁎ 0.14 0.03Cox's Bazar 0.14⁎⁎ 0. 29⁎⁎ 0.37⁎⁎ 0.35⁎⁎ 0.28⁎⁎

Dhaka −0.48⁎⁎ −0.11 0.27⁎⁎ 0.05 −0.04Dinajpur −0.35⁎⁎ −0.11 0.10 0.19 −0.03Faridpur −0.28⁎ −0.180⁎ 0.08 0.06 −0.10Ishurdi −0.36⁎⁎ −0.38⁎⁎ 0.15⁎⁎ 0.13 −0.13⁎

Jessore −0.26 0.17 0.23⁎⁎ 0.40⁎ 0.13Khulna 0.00 0.06 0.23⁎⁎ 0.04 0.11M. court −0.51⁎⁎ 0.13 0.16⁎⁎ −0.06 −0.03Mymensing −0.25⁎ −0.42⁎⁎ −0.08 0.25⁎ −0.15⁎⁎

Rangamati 0.64⁎⁎ 0.26⁎ 0.35⁎⁎ 0.62⁎⁎ 0.44⁎⁎

Rangpur −0.82⁎⁎ −0.78⁎⁎ 0.01 −0.24⁎⁎ −0.39⁎⁎

Satkhira −0.11 −0.18 0.03 0.08 −0.05Srimangal −0.24⁎ −0.20⁎ 0.07 −0.13 −0.16⁎

Sylhet −0.17⁎ −0.02 0.30⁎⁎ 0.07 0.04Averaged −0.24⁎⁎ −0.19⁎⁎ 0.11⁎ 0.09 −0.04

⁎ Significant at 95% level of confidence.⁎⁎ Significant at 99% level of confidence.

265S. Shahid et al. / Atmospheric Research 118 (2012) 260–270

4.2. Trends in DTR

The results of trend analysis of annual and seasonaldiurnal temperature ranges at 18 stations of Bangladesh aregiven in Table 1. The values in the table represent the changesof temperature in °C/decade. The DTR records of all stations areaveraged to get the time series of mean DTR over Bangladesh.Changes in average annual and seasonal DTRs over Bangladeshare estimated by using Sen's slopemethod. The field significanceof the regional DTR trend pattern of Bangladesh is determinedby using Monte Carlo simulation technique. The result is alsogiven in Table 1. The result shows no change in annual DTR overBangladesh. Trends in mean minimum and mean maximumtemperatures over Bangladesh are shown in Fig. 5. The trendsshow that both mean minimum and mean maximum temper-atures of Bangladesh have increased significantly during thetime period 1961–2008. Though the increase of mean mini-mum temperature is relative higher (0.15 °C/decade) than theincrease ofmeanmaximum temperature (0.11 °C/decade), it isnot high enough to cause a significant change in diurnaltemperature range in Bangladesh.

Fig. 5. Trends in annual mean of maximum and minimum daily temperatureover Bangladesh during the time period 1961–2008. Slopes of the trend linesare given in °C/decade.

Field significance of seasonal DTR trends in Bangladeshobtained through Monte Carlo simulation technique showsthat significant changes have occurred during the winter,pre-monsoon and monsoon seasons. DTR has decreasedsignificantly in winter and pre-monsoon, and increased signif-icantly during monsoon over the time period 1961–2008. Timeseries of winter, pre-monsoon andmonsoonDTRs of Bangladeshare shown in Fig. 6(a), (b) and (c), respectively. Fig. 6(a) and (b)shows a high decrease of winter and pre-monsoon DTRs overBangladesh at a rate of −0.24 °C/decade and −0.19 °C/decade,respectively at 99% level of significance. Fig. 6(c) shows amoderate increase of monsoon DTR over Bangladesh at a rate of0.11 °C/decade at 95% level of significance.

Trends inwinter, pre-monsoon,monsoon and post-monsoonmean minimum and mean maximum temperatures ofBangladesh are shown in Fig. 7(a), (b), (c) and (d), respectively.Fig. 7(a) and (b) shows a significant increase ofmeanminimumtemperatures in contrast of no change in mean maximumtemperatures duringwinter and pre-monsoon seasons. This hascaused a significant decrease of DTRs during winter and pre-monsoon. As the warming rate in winter is higher than pre-monsoon, more declination of winter DTR compared topre-monsoonDTR is observed. Fig. 7(c) shows that themonsoonmaximum temperature has increased rapidly compared tominimum temperature during the time period 1961–2008.Consequently, significant increase in DTR is observed duringmonsoon in Bangladesh. Post-monsoon temperature changeis similar to monsoon change. However, as the increase ofpost-monsoon maximum temperature is not much highercompared to theminimum temperature (Fig. 7(d)), the increaseof DTR during post-monsoon is still not significant.

Temperature of Bangladesh has increased significantly in thelast fifty years, with more increase in minimum temperaturethan in maximum temperatures. Seasonal analysis of tempera-ture shows a more winter warming compared to summerwarming in Bangladesh (Shahid, 2010c, 2011a). The decrease ofDTRs during winter and pre-monsoon results from largeincrease of minimum temperature. Due to the monsoon-driven

Fig. 6. Trends in mean diurnal temperature range during (a) winter;(b) pre-monsoon; and (c) monsoon during the time period 1961–2008.

266 S. Shahid et al. / Atmospheric Research 118 (2012) 260–270

climate of Bangladesh, precipitation mainly concentrates in themonsoon months. More than 80% of total rainfall of Bangladeshoccurs during monsoon and post-monsoon months. Though nosignificant change in average monsoon rainfall is observed overBangladesh, it is found to decrease significantly in some stationsof Bangladesh (Shahid, 2010c). Decrease of monsoon rainfallmay cause an increase in daytime temperature and consequentlyan increase in DTR during monsoon in Bangladesh.

Though many scientists have proposed that the widespreaddeclining trends in DTR appear to be related to increasing con-centrations of greenhouse gases and sulfate aerosols (Mitchell etal., 1995; Stone and Weaver, 2003; Wild et al., 2007) and/orincreases in vegetation and soil moisture (Collatz et al., 2000;Jackson and Forster, 2010), most of the studies indicate that thedownward trends in DTR are ultimately related to upwardtrends in cloud cover (Karl et al., 1993; Dai et al., 1997, 1999;Zhou et al., 2009). Due to unavailability of long-term time seriesof cloud cover data, it was not possible to establish the links

between trends in cloud cover andDTR in Bangladesh. However,studies carried out in the India states adjoining to Bangladeshreveal that downward trends in DTR are related to upwardtrends in cloud cover. Jaswal (2010) studied the spatialdistribution of total cloud cover climatology over India basedupon 1961–2007 and reported that significant increasing trendsin cloud cover duringwinter and pre-monsoon summer inWestBengal and northeastern Indian states bordering Bangladesh. Healso reported decreasing trends of total cloud cover duringmonsoon in the northeastern states of India. As cloud cover hasnegative relationship with DTR, Jaswal (2010) also found thedecreasing trends in DTRs during winter and pre-monsoonsummer, and increasing trend in DTR during monsoon in theregions bordering Bangladesh. Therefore, it may be remarkedthat significant increase in total cloud cover is responsible forsignificant decrease in DTRs during winter and pre-monsoonseasons in Bangladesh. However, stronger decreasing trend inDTR in winter compared to pre-monsoon suggests the role ofother factors. A study by Venkataraman et al. (2005) has shownthat biomass-burning smoke and dust storms are the majorsources of black carbon and aerosols in the Indo-Gangetic plainswhich along with the low topography of the indo-Gangeticplains adjacent to the Himalayan ranges leads to formation oflow clouds and dense fogs during thewinter season. Sarkar et al.(2006) reported strong increasing trends of anthropogenicpollution in the Indo-Gangetic plains. De et al. (2001) found thatthe number of foggy days in the Gangetic plains during thewinter seasonhas been increasing in recent years as compared toearlier decades with strong increasing trends of anthropogenicpollution in the Indo-Gangetic plains. Fogs reduce the diurnaltemperature range by shielding off solar radiation in daytimecausing lower maximum temperatures. Therefore, a strongerdecreasing trend in DTR is found in winter in Bangladesh.

4.3. Correlation between rainfall and DTR

Long term climate change and some local anthropogeniceffects are often related to changes in diurnal temperaturerange. Local anthropogenic activities such as urbanization andchanges in irrigation can cause a change in diurnal temperaturerange (Price et al., 1999). However, Karl et al. (1988) haveshown that even after correcting for the urbanization effect, thediurnal range trends remain basically unchanged. No connec-tion has also been found between large changes in diurnaltemperature range and increased irrigation (Karl et al., 1995).Long term changes in cloud cover, soil moisture, precipitation,atmospheric water vapor are often cited as the most likelycauses of diurnal range of temperature changes (Plantico et al.,1990; Karl et al., 1993; Dai et al., 1997, 1999; Liu et al., 2004). Toinvestigate the factors influencing DTR, Dai et al. (1999) foundthat clouds, combinedwith secondary damping effects from soilmoisture and precipitation can reduce DTR; while atmosphericwater vapor increases both nighttime and daytime temperaturesand has small effects on DTR. Clouds, which largely determinethe geographic patterns of DTR, greatly reduce DTR by sharplydecreasing surface solar radiation while soil moisture decreasesDTRby increasing daytime surface evaporative cooling (Dai et al.,1999).

Due to unavailability of long-term time series of cloud coverand soil moisture data at all stations, the rainfall is used as aproxy data to find their effect on DTR in Bangladesh. The

Fig. 7. Trends in mean maximum and minimum daily temperature over Bangladesh in (a) winter; (b) pre-monsoon; (c) monsoon; and (d) post-monsoon duringthe time period 1961–2008.

267S. Shahid et al. / Atmospheric Research 118 (2012) 260–270

connections between, firstly, rainfall and cloud, and, secondly,cloud and dew point depression, and, thirdly, dew pointdepression and DTR, suggest direct relation between rainfalland DTR (Geerts, 2003). Usually, high percentage cloud coverresults in high amount of rainfall. On the other hand, as the soilwater content is largely controlled by precipitation, Verdecchiaet al. (1994) found a strong relation between changes inprecipitation and in diurnal temperature range. In the present

Table 2Spearman Rho's correlation coefficient between rainfall and diurnal temperature ra

Station Winter Pre-monsoon

Barisal −0.41⁎⁎ −0.05Bogra −0.38⁎⁎ −0.46⁎⁎

Chittagong −0.35⁎ 0.24Comilla −0.38⁎ −0.08Cox's Bazar −0.35⁎ 0.01Dhaka −0.47⁎⁎ −0.22Dinajpur −0.42⁎ −0.36Faridpur −0.36⁎ 0.01Ishurdi −0.34⁎ −0.35⁎

Jessore −0.49⁎⁎ −0.05Khulna −0.31⁎ −0.03M. Court −0.46⁎⁎ 0.03Mymensingh 0.02 −0.15Rangamati −0.21 0.04Rangpur −0.43⁎⁎ −0.44⁎⁎

Satkhira −0.35⁎ −0.04Srimangal −0.52⁎⁎ −0.16Sylhet −0.34⁎ −0.56⁎⁎

Average −0.46⁎⁎ −0.43⁎⁎

⁎ Significant at 95% level of confidence.⁎⁎ Significant at 99% level of confidence.

paper, long-term rainfall records are analyzed to reveal therole of precipitation in DTR change in Bangladesh. For thispurpose the correlation coefficient values between DTR andrainfall at different stations of Bangladesh are obtained bynon-parametric Spearman's Rho test. The obtained result isgiven in Table 2. The result shows a significant negativecorrelation between annual average DTR and annual rainfall inBangladesh. Seasonal analysis of rainfall and DTR also shows a

nge in different stations of Bangladesh.

Monsoon Post-monsoon Annual

−0.15 −0.41⁎⁎ −0.23−0.07 −0.38⁎⁎ −0.32⁎

−0.15 −0.35⁎ −0.32⁎

−0.29 −0.38⁎ −0.19−0.10 −0.35⁎ −0.21−0.07 −0.47⁎⁎ −0.37⁎

−0.19 −0.42⁎ −0.42⁎

0.00 −0.36⁎ −0.10−0.09 −0.34⁎ −0.25−0.24 −0.49⁎⁎ −0.44⁎⁎

0.29 −0.31⁎ −0.09−0.01 −0.46⁎⁎ −0.03−0.29⁎ 0.02 −0.38⁎

−0.05 −0.21 0.13−0.36⁎ −0.43⁎⁎ −0.48⁎⁎

0.00 −0.35⁎ −0.04−0.05 −0.52⁎⁎ −0.10−0.21 −0.34⁎ −0.40⁎⁎

−0.23 −0.46⁎⁎ −0.42⁎⁎

268 S. Shahid et al. / Atmospheric Research 118 (2012) 260–270

negative correlation between rainfall and DTR for all the seasonsin Bangladesh. However, the correlations are significant forwinter, pre-monsoon and post-monsoon seasons. The obtainedresult is consistent with the findings of other researchers inneighboring India. Jhajharia and Singh (2011) found a negativerelation between rainfall and DTR in northeastern Indiabordering Bangladesh. Geerts (2003) found a direct relationshipbetween monthly rainfall total and monthly-mean DTR in theUSA, India and China. Verdecchia et al. (1994) also found anegative correlation between changes in precipitation and indiurnal temperature range.

Regression analysis of annual rainfall and annual averageDTR shows that an increase of 1% of rainfall is correlated with adecrease of DTR by 0.1 °C. It can be noted that rainfall ofBangladesh has increased at a rate of 5.25 mm/year in the lastfifty years (Shahid, 2010c).

4.4. Spatial analysis of DTR trends

Station wise analysis of DTR trends (Table 1) shows asignificant increase of annual DTR in the southeastern coastalstations and a significant decrease ofDTR in the northern stationsof Bangladesh. DTR is lower in the southeastern coastal areas andhigher in the north and northwest of Bangladesh. It is found thatDTRs have increased mostly in the areas where their values arelower and decreased mostly where their values are higher.Maximum decrease of DTR by an amount of−0.39 °C/decade isobserved in Rangpur station located in northwest Bangladeshwhich has the highest annual averaged DTR.

Seasonal analysis of DTR trends shows a significant decreaseof DTRs during winter in 11 stations out of 18 stations understudy. Significant increase of DTR is observed only in onestation situated in southeastern hilly region of Bangladesh.Maximumdecrease ofwinter DTR by−0.82 °C/decade is notedin northwest Rangpur Station. Pattern of pre-monsoon DTR issimilar to annualDTR. Significant decrease of pre-monsoonDTRis observed in six stations located in the north and northwestBangladesh. On the other hand, significant increase is observedin two stations in the southeast Bangladesh. Monsoon DTR isfound to increase almost in all stations of Bangladesh with asignificant increase in 12 stations at 99% level of confidence.Maximum increase is observed in southeastern coastal Cox'sBazar station by 0.37 °C/decade at 99% level of significance.Post-monsoon DTR is found to increase significantly in thecoastal stations. It is found to decrease significantly only inRangpur station located in northwest Bangladesh.

Spatial pattern of DTR trends are more or less consistentwith rainfall trends in Bangladesh. As there is an inverserelationship between rainfall and DTR, it has been found thatin most of the cases DTR showing decreasing trends whererainfall has been reported to increase. Shahid (2010b, 2010c)performed trend analysis of annual rainfall during the timeperiod 1958–2007 and reported that annual rainfall is increas-ing significantly in the western part of Bangladesh. Results oftrend analysis show that DTRs are decreasing significantly inmost of the stations situated in the western part of Bangladesh.Through the seasonal rainfall trend analysis, Shahid, 2010b,2010c) showed significant increase of pre-monsoon rainfall innorthwestern and southeastern stations, significant increase ofmonsoon and post-monsoon rainfalls in the northern stationssituated at the foothill of Himalaya, and no change in winter

rainfall in any station of Bangladesh. Spatial distribution ofseasonal DTR trends shows decreasing trends in northwesternand southeastern stations during pre-monsoon and in thenorthern stations during monsoon and post-monsoon. Thoughthere is no change in winter rainfall, DTR duringwinter is foundto decrease significantly in most of the stations of Bangladesh.This is due to increasing trends in foggy days inwinter (De et al.,2001).

Changes in DTR can affect agriculture and public health ina number of ways (Peng et al., 2004; Sheehy et al., 2006; Kanet al., 2007; Lobell, 2007). Peng et al. (2004) studied theeffects of DTR on rice yield and found that rice yields declinewith higher night temperature or decrease of DTR. Decrease inDTR can lead to human discomfort (Tam et al., 2009). Increasedminimum temperature in summer does not allow the necessarynocturnal cooling to neutralize the highmaximum temperatureduring a heat wave epoch (De et al., 2005). Bangladesh is anagriculture-based country whose 84% of the 145 millionspeople are directly or indirectly engaged in a wide range ofagricultural activities. Crop is the main sector of agriculture inBangladesh. Within the crop sector, rice dominates with anaverage 71% share of the gross output of all crops (Shahid,2011b). A major part of rice is grown during the pre-monsoondry season. Increase of minimum (night) temperature anddecrease of DTR during pre-monsoon season can hamper therice based agriculture of Bangladesh. Public health effect mightbe one of the most significant impacts of climate change inBangladesh (Shahid, 2010a). Increase of night temperature andchanges in DTR may increase the risks to human health inBangladesh, especially in light of the poor state of the country'spublic health infrastructure.

5. Conclusion

Field significant trends investigated bymeans ofMonte Carlosimulation reveal no change in annual DTR in Bangladesh overthe time period 1961–2008. However, the field significance ofseasonal trends shows that DTR in Bangladesh has decreased inwinter and pre-monsoon, and increased in monsoon. Temper-ature of Bangladesh has increased significantly in the last fiftyyearswithmore increase has beennoted in nighttimeminimumtemperature compared to daytime maximum temperature.More winter warming compared to summer warming is alsoreported in Bangladesh. Large increase of nighttime tempera-ture and no significant change in daytime maximum temper-ature have reduced DTR in winter and pre-monsoon seasons.Significant negative correlation between annual rainfall andannual average DTR has been observed in Bangladesh. Thisimplies that future change in rainfall in Bangladesh due toglobal warming will change DTR. DTR is a meteorologicalindicator which is often associated with global climate change.However, from the present study it is not possible to come to aconclusion about impact of global warming on the climate ofBangladesh. Further study can be carried outwith climatemodelprojections to show the impact of global warming on DTR ofBangladesh.

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