Detection of temperature and precipitation trends and their attribution it to the greenhouse gases (Case study: West Azerbaijan Province)

Detection of changes in climate variables during the past periods and attributing them to the identified factors plays a major role in climate studies and projection of the future. Different factors can unbalance the stationary time series of a region’s climatic variables. Part of these factors are related to the interactions between the components of the Earth’s climate system which can cause internal variability in time series of climatic variables. Two important natural factors that influence climate are the Sun’s energy and volcanic eruptions. Overall changes due to natural external factors and internal climate variability in earth climate system are called natural climate variability. The increase in the carbon dioxide concentration due to human activities has been the principle factor causing warming over the past 50 years. It should be noted that the existence of a trend in the climate data of a region can not necessarily be attributed to the increase in greenhouse gases. In other words, after proving the existence of a trend in the past climate data of a region, the relationship between the trend and the increase in greenhouse gases should be proved.
This study was carried out to detect the trend of temperature and precipitation of West Azerbaijan Province, Iran for the period of 1968-2008 and attributing them to the greenhouse gases. The Basin located at longitude 44º 00' to 47º 31.7'   north and latitude 35º 55.2' to 39º 42' east in northwest of Iran. The Basin area is 37411/1 km² that the thirteenth largest Province in Iran.
Two approaches were used to evaluate the changes in annual series of temperature and precipitation during the period 1968-2008. The first one is based on analysis of standardized departures and the second approach is based on a multiple trend tests (Mann, 1945; Kendall, 1975). This test identifies gradual monotone rising and falling trends in a time series. On the other hand distinction between gradual trend and a rapid change is important, particularly for climate- change impacts studies. Therefore to identify temporal changes in annual precipitation and temperature series of main stations in the West Azerbaijan, we conducted multiple trends tests as suggested by McCab and Wolock (2002) by varying the beginning and ending date of the time series in 5 years steps for the period of 1968-2008. Afterward, in order to separate climate changes caused by greenhouse gases from natural variability, long-term statistics (1000 years) of temperature and precipitation, resulting from control run (fix greenhouse gases) of CGCM3 model, were used for West Azerbaijan Province. To analyze the natural variability range of two “temperature” and “precipitation” variables of the study area, first, their annual anomaly time series with respect to the average base period is calculated [By definition, temperature anomaly is the temperature difference from a base temperature, while precipitation anomaly is the precipitation ratio difference from a base precipitation, (Base period, 1971-2000)].The range of natural climate variables is determined by providing two-dimensional graphs of temperature and precipitation based on two-variant normal distribution (Von Storch and Zwiers, 2002). Finally, anomaly values of the observation stations in different regions of the case study were compared with the natural climate variability range of the region.
The results show that the increase in temperature and decrease in precipitation trends are due to the climate change in 1968-2008 periods. Additionally in different parts of the studied area, the range of natural climate variables for temperature and precipitation changes is between 1.8 to -1.8°C and +40 to -40 percent, respectively. However, in the most of the regions of the West Azerbaijan Province, the last ten years of the period (1998 to 2008) have almost been located outside the range of natural climate variables. The result indicates the effect of climate changes on the climatic variables of the case study in recent years.