Seyyed Keramat Hashemi-Ana; Mahmud Khosravi; Taghi Tavousi; Hamid Nazaripour
Abstract
Extended Abstract Introduction Precipitation is one of the vital climatic parameters that plays a major role in human life. Therefore, the impact of Precipitation in occurrence or non-occurrence of droughts and dry spells have been very effective. Identification and extraction length of dry spells ...
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Extended Abstract Introduction Precipitation is one of the vital climatic parameters that plays a major role in human life. Therefore, the impact of Precipitation in occurrence or non-occurrence of droughts and dry spells have been very effective. Identification and extraction length of dry spells in arid and semi-arid regions are very important. According to the most recent climate classification that has been done, about 90 percent of the areas of Iran are located in arid and semi-arid climate, and more than 40 percent are facing a severe water crisis. Therefore, understanding the behavioral mechanisms of dry spells have a great significance in arid and semi-arid areas like Iran, especially with the pose of the phenomenon of climate change that caused the worsening dryness and desertification in some of the regions. Many researches simulated dry spells with climate change approach and use of the output of AOGCM models. Researches in this category are in less numbers, but the most recent research has been done by the authors (hashmy titles et al., 2015), investigating and modeling the length of dry spells in the Southwestern area of Iran. The aim of this research is to examine the Validation of AOGCMs Capabilities for Simulation Length of Dry Spells under the Climate Change and Uncertainty in Iran Materials & Methods According to the aim of this research, we used two databases in this study. The first database involves collecting and analyzing all data base information (minimum temperature, maximum temperature, rainfall and sunshine) on a daily scale in 234 synoptic stations (with different statistical period). But the format for the data station and point during the period of statistical modeling was needed for more than 30 years, which has a large statistical defects were excluded, and finally 45 synoptic stations that have favorable conditions (the maximum area coverage and continuous and reliabledata) were selected for the final processing of the first data base. The period of 1981-2010 was used as the base period.The second database contains data provided by version 5 models (LARS-WG) and on emission scenarios (B1, A1B, A2) from AOGCM models for the 2050s to be downscaled. In fact, this data is the first data base (minimum temperature, maximum, precipitation and sunshine) prepared based on the format models for analysis and predicting climate change, after downscaling it. Because this research was based on study and extraction length of dry spells in the range of long-term with the approach to climate change, so the methodology is based on several stages. At first, verification (validation) of LARS-WG, to ensure efficiency in the process model simulation will be discussed. Then the performance and capabilities of 15 AOGCM models in the new version of Lars-wg will be assessed. At the end, the precipitation threshold is defined and extraction of the longest length of dry spells and comparing it with the maximum length of the dry spells will be simulated. Results & Discussion After calibrating the model of statistical properties (comparison tests T, F and P values (decision criteria), all stations were used to confirm the validity of the model. The results of this calibration indicate that in more than 96% of the stations, for the minimum and maximum temperature and sunshine model, show high accuracy (results of error in Dezful and Gorgan stations were greater). In all of these stations like Abadan station, variables significant (P-value) were at./05. It is acceptable that the data generated is random.Considering the bias error, at more than 95 percent of stations there were very good agreements between the observed and modeling data (for every 4 variables). Based on the principles of (1 to 3), and using statistical methods and indicators, the AOGCM models to simulate and extract during dry spells were examined and it was found that two models (Hadcm3 and GFDL-CM2.1) had maximum performance (correlation) and the lowest error in estimating for simulation data precipitation. The model (INM-CM3 and NCPCM) have least amount of correlation and efficiency. To estimate the maximum length of dry spells Hadcm3 results were used under scenario (A2 and B1) for the decade 2050 and the use of the results of other models was skipped in this research. Maximum dry spells in Iran comply with dryness condition in central and eastern areas. So that the country could be on the threshold of ./1 mm divided into 6 orbital regions of the northern circuit during the period of 37 days (in Rasht station) minimum and 351-day observation period in Southeastern Chabahar stations. The values show that the threshold of ./1 mm at more than 65 percent of the area’s dry spells over 7 months there was no rain on them yet. With a threshold of 5 mm needs maximum length of dry spells that lasted about a year with 364 days in Yazd station. That is roughly the size of 5 mm precipitation a year not registered at this station. Conclusion Modeling dry spells by computing scenarios of climate change and taking into consideration uncertain resources at the AOGCM models output, showed that based on the worst-case scenario (A2), and the most critical situation (2080), the average temperature of the country has increased 2.7 degrees (ºC) and Despite increased precipitation in some Stations, the average rainfall is facing a 33% reduction in the whole country. According to the most optimistic scenario (B1), the average temperature of the country is increasing by 1.4 (ºC) and the precipitation is decreasing by 14% in relation to the observation period. The results of the uncertainty examination for dry spells in Iran showed that in both 2050s and 2080s and based on all three scenarios (B1, A1B, A2), length of dry spells increases in all areas of Iran. Most of the changes in length of dry spells belong to the northwestern areas of Iran (Urmia, Khoy, Kermanshah, Hamedan and Lorestan).
