The spatial distribution of December temperature in Pakistan has been assessed by statistical method based on mean monthly data from 51 ground stations. The analysis is performed at decadal scale over the period of 1950-2000. December is one of the representative months of winter season in Pakistan, the country with subtropical location and complex rugged terrains, plateaus and plains. The results support a slight rising temperature trend in December. However, this change in temperature varies from region to region as well as from decade to decade and reflects a complicated spatial-temporal structure of temperature anomalies. The assessment shows that the temperature anomalies in different national territories at local scale do not follow the assumption that winter months are warming in northern hemisphere. Both the isothermal shift and temperature anomalies confirm that the mountainous areas of Pakistan face more temperature variability than plains.
The true essence of climate change is hard to be understood without the temperature analysis at different temporal and spatial scales. Pakistan faces extreme weather events like drought, floods and heat waves [
This paper is focused on the analysis of December temperature variability with emphasis on spatial distribution and its regional detail in Pakistan. Most of climatic studies are supported by “time series figures of temperature”, while rarer studies map the anomalies and also neglect the spatial distribution of the observations. In this paper, we mapped the isotherms through which we learned about the shifts of average temperature at regional scale and recognized their anomalies by simulating temperature coefficient at decadal scale.
The monthly temperature data of surface air temperature were obtained from Pakistan Meteorological Department (PMD). The 51 stations (
The isothermal maps (
The following technique was adopted to calculate the temperature coefficient trend,
The above relation establishes linear regression between, the time series ti and variable xi (temperature) for the specified period.
By taking into account ti as independent and xi dependent variable, regression coefficient “b” and the regression constant “a” of least-squares estimation have been calculated, respectively by using the following principle.
Serial No. | Stations | Latitude | Longitude | Region |
---|---|---|---|---|
1 | Astor | 35˚20' | 74˚54' | Gilgit-Baltistan |
2 | Badin | 24˚38' | 68˚54' | Sindh |
3 | Bahawal Nagar | 29˚57' | 73˚51' | Punjab |
4 | Bahawal Pur | 29˚24' | 71˚47' | Punjab |
5 | Balakot | 34˚23' | 73˚21' | KPK |
6 | Bar Khan | 29˚53' | 69˚43' | Balcohistan |
7 | Bunji | 35˚67' | 74˚63' | Gilgit-Baltistan |
8 | Cherat | 33˚49' | 71˚53' | KPK |
9 | Chhor | 25˚31' | 69˚47' | Sindh |
10 | Chilas | 35˚25' | 74˚06' | Gilgit-Baltistan |
11 | Chitral | 35˚51' | 71˚50' | KPK |
12 | Dalbandin | 28˚53' | 64˚24' | Balochistan |
13 | Dera Ismail Khan | 31˚55' | 70˚52' | KPK |
14 | Dir | 35˚12' | 71˚51' | KPK |
15 | Drosh | 35˚34' | 71˚47' | KPK |
16 | Faisalabad | 31˚26' | 73˚08' | Punjab |
17 | Garhi Dupatta | 34˚13' | 73˚37 | AJK |
18 | Gilgit | 35˚55' | 74˚20' | Gilgit-Baltistan |
19 | Hyderabad | 25˚23' | 68˚25' | Sindh |
20 | Islamabad | 33˚43' | 73˚05' | Punjab |
21 | Jacobabad | 28˚18' | 68˚28' | Sindh |
22 | Jhang | 31˚27' | 73˚32' | Punjab |
23 | Jiwani | 25˚04' | 61˚48' | Balochistan |
24 | Kakul | 34˚11' | 73˚15' | KPK |
25 | Kalat | 29˚02' | 66˚35' | Balochistan |
26 | Karachi | 24˚54' | 66˚56 | Sindh |
27 | Khanpur | 28˚39' | 70˚41' | Punjab |
28 | Kohat | 33˚57' | 71˚43' | KPK |
29 | Kotli | 33˚31' | 73˚54' | Sindh |
30 | Lahore | 3 1˚35' | 74˚24' | Punjab |
31 | Larkana | 27˚32' | 68˚14' | Sindh |
32 | Mianwali | 32˚55' | 71˚52' | Punjab |
33 | Multan | 30˚12' | 71˚26' | Punjab |
34 | Murree | 33˚55' | 73˚23' | Punjab |
35 | Muzaffarabad | 34˚22' | 73˚29' | AJK |
36 | Nawabshah | 26˚15' | 68˚22' | Sindh |
37 | Ormara | 25˚12' | 64˚40' | Balochistan |
38 | Padidan | 26˚51' | 68˚08' | Sindh |
39 | Panjgur | 26˚58' | 64˚06' | Balochistan |
40 | Parachinar | 33˚52' | 70˚05' | FATA |
---|---|---|---|---|
41 | Pasni | 25˚16' | 63˚29' | Balochistan |
42 | Peshawar | 34˚01 | 71˚35 | KPK |
43 | Quetta | 30˚05' | 66˚57' | Balochistan |
44 | Risalpur | 71˚98' | 34˚07' | KPK |
45 | Rohri | 27˚40' | 68˚54' | Sindh |
46 | Saidu Sharif | 34˚44' | 72˚33' | KPK |
47 | Sarghoda | 32˚05' | 72˚67' | Punjab |
48 | Sialkot | 32˚31' | 74˚32' | Punjab |
49 | Sibbi | 29˚33' | 67˚53' | Balochistan |
50 | Skardu | 35˚18' | 75˚41' | Gilgit-Baltistan |
51 | Zhob | 31˚21' | 69˚28' | Balochistan |
Based on results
Pakistan have variety of temperatures from south (north) to north (south) and east (west) to west (east) in December. The reason for this obvious difference in temperature in the same month is latitudinal extent and landforms. Obviously, the temperature divides Pakistan into parts of high and low temperatures in Indus Plains and north/western rugged parts respectively. The said reasons are (were) only true for the distribution of average temperatures in normal atmospheric condition but the distribution of spatial anomalies was quite complex and varied from area to area. The comparison of various decades is evident of the isothermal shift for a selected temperature (e.g. 15˚C or 12˚C or any other isotherm), it means temperature change occurs at local scale in the study period. It has been observed that where the isotherms were closely spaced the temperature anomalies were more obvious and vice versa. This mostly happened in mountains and confirmed that rugged lofty portions of the country were more susceptible to temperature variability.
Reference to
Reference to
plains (in both Punjab and Sindh) and Khyber-Pakhtoonkhwa (KPK), the observed anomalies were
The area in Indus plains between the isotherms of 15˚C and 12˚C is wider (
(
Now consider the temperature anomalies (
The comparison between 1960s and 1970s acknowledged that in 1970s (
In the decade of 1970s (
The coastal areas reflected variation of temperature averages almost in all decades, here one thing can not be ignored that is the impact of changes in sea surface temperature (SST) of Arabian Sea [
The 1980s (
The comparison of 1980s (
The temperature anomaly in 1990s (
The shift of isothermal lines in 2000s (
Reference to the decade of 2000s (
In Pakistan, the temperature anomalies in December vary from decade to decade and region to region within the same decade. It was noticed that after 1980s, the warming tendency was obvious in most of the national territories. Nevertheless, the regional detail of temperature anomalies at local scale were complex and did not comply with the assumption totally that winter months were warming. Generally, by shift from mountainous territories to the plains, the temperature coefficient values are generally increasing. Therefore, in the 2000 decade warming was much obvious in the plains than that in mountainous regions while in 1990s the mountains regions showed more warming than the plains. This sort of study could be useful for local agriculture especially in various enclosed valleys in rugged parts of the country.
It has been observed that wherever the isotherms were closely spaced, the temperature anomalies found were with high statistical significance on the contrary where the isotherms were widely spaced and the temperature change per unit area was less. Generally, it is clear that the shift of isotherm was obvious in the northern and western parts of the study domain acknowledged by high level of statistical significance pertaining to temperature anomalies there. Both the isothermal shift and temperature anomalies confirm that the mountainous areas of Pakistan face more temperature variability (warming) than plains.
The help and cooperation of PMD is highly recognized. The comments and suggestions of anonymous reviewers substantially improved the paper.