Thermal Classification of Pakistan

Zahid, Muhammad; Rasul, Ghulam

doi:10.4236/acs.2011.14023

Cited by 11 publications

(17 citation statements)

References 4 publications

(6 reference statements)

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“…Southern Canada experienced increasing trends in the 5th and 95th percentiles of the daily minimum and maximum temperature during twentieth century with no consistent trends in extreme hot summer days (Bonsal et al 2001). Warming trends were reported by Cheema et al (Cheema et al 2006) for the Faisalabad region (Punjab, Pakistan) with an overall increase in temperature by 0.228C for the analysis period of 1945-2004. In the recent past, semiarid Pakistan experienced a great variability in temperature resulting into prolonged droughts and uneven monsoon periods leading to adverse flooding (Chaudhary and Rasul 2004;Zahid and Rasul 2011). For the period of 1961-2000, Vincent et al (Vincent et al 2005) calculated significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations located closer to the western and eastern coasts of South America.…”

Section: Introductionmentioning

confidence: 99%

Analysis of a Historical (1981–2010) Temperature Record of the Punjab Province of Pakistan

Abbas

2013

Earth Interactions

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Prolonged droughts and uneven monsoons have adversely affected socioeconomic and environmental conditions of Pakistan, especially of the Punjab province. Analysis of historical (1981-2010) daily minimum and maximum temperatures from five cities in semiarid Punjab, Pakistan, was carried out to evaluate spatial and temporal patterns in thermal regimes. A total of 13 climate change indices were calculated using daily minimum and maximum temperatures and analyzed for trend using RClimDex, a program written in the statistical software package R. A nonparametric Mann-Kendall test and Sen's slope estimates were used to determine the statistical significance and magnitude of a trend, respectively. Observed trends in selected indices during 1981-2010 suggest an overall warming in the region. Over the analysis period, the regionally averaged occurrence of extreme cold (10th percentile) nights and days has decreased by 23.94 nights per decade and 20.61 days per decade, respectively. Occurrence of extreme hot (90th percentile) nights and days has increased by 4.19 nights per decade and 0.92 days per decade, respectively. The number of summer days has increased by almost 3 days per decade on average at four out of the five cities. Multan was the only city where the number of summer days has declined by 5 days per decade. Regionally averaged increase in tropical nights was 8.35 nights per decade.Regional warming will dictate increased crop water requirements in this semiarid region agriculture, which is already under water-scarce conditions, especially in the Faisalabad district, where saline groundwater is not suitable for crops.

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Section: Introductionmentioning

confidence: 99%

Analysis of a Historical (1981–2010) Temperature Record of the Punjab Province of Pakistan

Abbas

2013

Earth Interactions

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“…Zahid and Rasul () used Thornthwaite's thermal efficiency index based on temperature and evapotranspiration for thermal classification of Pakistan on seasonal and annual basis. According to them, southern Pakistan is mesothermal and mega thermal type of climate (arid in SD), central part is microthermal, mild microthermal, moderate microthermal, and strong mesothermal type of climate (semi‐arid in SD) and extreme northern part is mild microthermal, frost and tundra type of climate (humid in SD).…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…For Pakistan, there is no such SD analysis for wet and dry spells. Earlier climate classifications in Pakistan are based on: characteristic variations in temperature and precipitation (Ahmad, 1951;Shamshad, 1988), using ratio of precipitation and evaporation (Bharucha and Shanbhag, 1956), factor and cluster analysis (Oliver et al, 1978;Hussain and Lee, 2009), AI (Zahid and Rasul, 2011;Haider and Adnan, 2014), Köppen classification (Sarfaraz et al, 2014) and principal component analysis (Sarfaraz, 2014). Oliver et al (1978) used 30 years of data from 53 weather stations in Pakistan to classify the study area into nine climate regimes using factor and cluster analysis, then with the same technique Hussain and Lee (2009) used 27 years of data from 32 weather stations to classify Pakistan into six climate regimes.…”

Section: Introductionmentioning

confidence: 99%

“…Oliver et al (1978) used 30 years of data from 53 weather stations in Pakistan to classify the study area into nine climate regimes using factor and cluster analysis, then with the same technique Hussain and Lee (2009) used 27 years of data from 32 weather stations to classify Pakistan into six climate regimes. The thermal efficiency index was used by Zahid and Rasul (2011) to regionalize climate of Pakistan into nine thermal regimes using 30 years of data from 50 weather stations. Sarfaraz (2014) utilized principal component analysis to divide Pakistan into six different climate regimes, whereas Sarfaraz et al (2014) used Köppen classification scheme to classify Pakistan into 11 climate regimes, using 59 weather station data with a time span of 30 years.…”

Section: Introductionmentioning

confidence: 99%

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Classification of precipitation regimes in Pakistan using wet and dry spells

Nabeel

Athar

2017

Intl Journal of Climatology

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Wet (dry) spells can cause extreme climatic conditions, such as floods (droughts) which can adversely influence the natural resources. A spatio‐temporal analysis of observed wet and dry spells is carried out for vulnerable and data sparse region of Pakistan (24°–38°N and 61°–78°E). Observed monthly precipitation data sets from 46 weather station are used for a length of consecutive 32 years (1976−2007). Additionally, after bias adjustment, the Asian Precipitation Highly‐Resolved Observational Data Integration Towards Evaluation (APHRODITE) precipitation data set, abbreviated as APH, is utilized to corroborate the findings. For both data sets, a threshold of 1 mm is used to define a wet spell. Decadal variability of precipitation for observed and APH data sets indicates that there is gradual decrease in wet spell length for arid and humid regimes, as compared to semi‐arid regimes where there is no change in wet spell length. Monthly dry and wet slope difference (SD), on a log–log plot between number of spells and spell length, is used to classify precipitation regimes in Pakistan, for the first time. A weather station is categorized as humid if SD is less than −2.38 in units of number of spells per length of spells. If SD lies between −2.37 and −0.51, then the weather station is classified as semi‐arid and if SD is greater than −0.51, then it is classified as arid. Thus, according to SD classification, 66% of area in Pakistan is arid, whereas 30% (4%) is semi‐arid (humid). Comparison of precipitation regimes based upon observed and APH data sets with other climate classification schemes that involve both precipitation and temperature is presented.

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Shifting of agro‐climatic zones, their drought vulnerability, and precipitation and temperature trends in Pakistan

Adnan

Ullah

Gao

et al. 2017

Intl Journal of Climatology

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Agro‐climatic classification helps to determine the different features of a region. This climatic classification provides a useful insight for a farmer to grow their crops according to the conditions of their region. This study identifies the shifting of moisture index from average values in different agro‐climatic zones of Pakistan. Unpredictable climate remains dominant over long periods. Observational data of precipitation and evapotranspiration were used to determine the agro‐climatic zone during the period 1951–2010. This study reveals that almost 87% of Pakistan is in extremely arid to semi‐arid zones, a 5% decrease in over the last 30 years (1981–2010). The largest decrease of 8% and increase of 5% were observed in the extremely arid and humid zones, respectively. The semi‐arid zone is more vulnerable to drought, while intensity and severity are greater in the extremely arid region. An agro‐climatic regional analysis identifies 1952, 1969, 2000, 2001 and 2002 as years when the most severe droughts were observed during the study period. The trends of precipitation and temperature were performed at 95% significance level on a monthly, seasonal and annual basis over the entire agro‐climatic zone of Pakistan during 1951–2014. The annual precipitation trends show a significant increase of 0.828 mm year−1 in arid regions, whereas the maximum temperature trends shows a significant increase of 0.014 °C year−1 and 0.018 °C year−1 in extremely arid and humid regions, respectively. The trend of minimum temperature shows an increase over the whole region, which may place pressure on the water demands of crops.

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Thermal Classification of Pakistan

Cited by 11 publications

References 4 publications

Analysis of a Historical (1981–2010) Temperature Record of the Punjab Province of Pakistan

Analysis of a Historical (1981–2010) Temperature Record of the Punjab Province of Pakistan

Classification of precipitation regimes in Pakistan using wet and dry spells

Shifting of agro‐climatic zones, their drought vulnerability, and precipitation and temperature trends in Pakistan

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