Authors
Abstract
Introduction
In the recent years, a CSG (Climate change Scenario Generators) model was developed and made a simple model for climate change that is called MAGICC and a scenario of climate information which organizes production that is called SCENGEN. M and SCENGEN models are divided into two main parts: parts that assess the climate change issued by the spreading circulation of green house gases (MAGICC) to organize sets of simple models. (Harvey et aL, 1997, 50)
Magicc is not the GCM model, but it can simulate using GCM in several areas in the world (Wigley et al 2002, 2690).
MAGICC can predict the annual average of ground temperature and mean annual sea surface temperature of spreading green house gases and CO2. This part includes the observation of climatic data and outputs of general circulation at atmospheric models that users can consider and assess in different situations. There are different couple of models that are mixed at the software Network, and users can use this network to change the concentration of CO2 and the mean temperature of ground and sea surface, to appoint climate circulation scenarios of CO2, CH4, N2O (PFC, HFC, HCFC).This model is used by IPCC in different assessment . Users can edit and update their scenarios into their models. Scenarios show base data of general circulation atmospheric model and global observation data of Europe, South Asia, America, and southern Africa.
SCEGEN model has been developed in several years. Scenario of green house gases and SO2 can change by Magicc and SCENGEN and as well as the temperature of the ground and sea surface.
Materials and Methods
There are some limitations for modeling the climate in future decades using dynamically-developed models. Here we have used Magicc-Scengen statistical model, which uses ECHAM4 and HADCAM2 models data. In this model, Iran is divided into 9 parts and the precipitations and temperatures have been simulated for the decades of 2000, 2025 and 2075. Climate change scenarios have monthly, seasonal and yearly time scales. This model can use 16 GCM data. In this paper, calculations have been done on the basis of ECHAM4 and HADCAM2 outputs.
Temperature and precipitation were analyzed during: 1986 to 2015 (2000 decade), 2011 to 2040 (2025 decade) 2036 to 2065(2050 decade), 2090 (2075 decade) and 2086 to 2115 (2100 decade)
Results and Discussion
mean precipitation
The results of downscaling from HADCM2 data show that mean precipitation will reduce during the future decades.
In contrast to the other decades, the largest decrease will happen during 2100 decade (figure 1)
The largest decrease of precipitation is related to Is92D, which is about 6 percent.
Precipitation will increase during the future decades in Mazandaran, Golestan, North khorasan, North of khorasan Razavi, Tehran, parts of Gillan, Ghazvin and Markazi.
The largest increase in precipitation will happen in north east and east of khorasan Razavi province. We do not have a remarkable precipitation change on southern and eastern coasts of the Caspian sea. Also precipitation will decrease in southern and south-eastern provinces, parts of Sistan-O-Bluchestan, and kerman, bushehr, south Fars. The different changes of precipitation during the future decades are shown at figure 1.
The results show that precipitation has increased and the highest precipitation will happen in the decade of 2100. On the basis of WKE450 and IS92E Scenarios, change in precipitation will occur at about 13.3 and 29.1 percent. The Results indicate that precipitation will decrease in the future decade in Mazandaran, Golestan, North of Khorasan, Parts of Khorasan Razavi north parts of Markazi, Tehran, parts of Gillan, Ghazvin and Markazi and the largest decrease of precipitation will happen on the southern and eastern coasts of Caspian sea, Markazi, Ghazvin, Semnan, Golestan, parts of Gillan and Mazandaran. In these provinces, precipitation will decrease about 9 to 18 percent. Precipitation will increase in sistan- O-Bluchestan, Hormozgan, Kerman, Fars, Bushehr, South- Khorasan, Yazd, Esfehan, Tehran, Kerman, Parts of Semnan, Southern parts of khorasan Razavi and Markazi, Persian Gulf plateau of Iran, and Oman sea. Certainly the highest precipitation will happen in Oman sea and Persian Gulf. The changes of precipitation with different scenarios are shown in figure 2.
Mean Temperature
The Whole mean temperatures were estimated and compared to the base data, the data of temperatures and the general circulation atmospheric model. (Figures 3 and 4). Mean Temperature has increased and the maximum increase will happen in 2100 decade.
The results show the increase of temperature over Iran. On the other hand, we will have an increase of temperature of about 0.4 to 3 degrees in the HADCM2 model and of 5 to 4 degrees in the ECHAM4 model in the future decade; the maximum change in the temperature will happen at about 4.4 to 5.3 degrees in 2100 decade. Increases of temperature will occur in south of khorasan, Yazd, Esfehan, parts of khorasan razavi, Semnan, Tehran, Markazi, Ghazvin and Gillan, Hormozgan ,Sistan o Baluchistan, Kerman and Fars.
The largest increase will occur in Fars, Isfahan, Bushehr, Mazandarn, Tehran, Yazd, Semnan , Ghazvin, Gillan and Markazi.
Conclusion
According to the results of the Hadcm2 model, precipitation will decrease about 2.5 percent, but in the ECHAM4 model, in the same period of time, raining will decrease about 19.8 percent.
The Hadcm2 model forecasted that precipitation will increase in Mazandaran, Golestan, north of khorasan, Semnan, Tehran and parts of Gillan, but will decrease in Kerman, Hormozgan, Bushehr, south of Fars and parts of Sistan- O - Baluchestan and according to ECHAM4, precipitation will increase in these areas.
This model has predicted that the temperature increases about 3 to 3.6 (2100 decade).
We suggest that using the general circulation model for precipitation and its assessment during the future decade over Iran is necessary.
Keywords
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