جستجوی مقالات مرتبط با کلیدواژه "مدل precis" در نشریات گروه "جغرافیا"

Any changes in the concentrations of greenhouse gases are causing imbalance status in system components. However, these changes along whit their effects the future should be simulated. There are different methods for the use of climate models is the most reliable.Here in this research, climate change status in Dez river basin where a major basin for water and agricultural yields is studied. For this purpose, the PRECIS model was used. PRECIS is an exponential dynamics downscaling model used to estimate the temperature and precipitation rates for the period of 2070 to 2100 under A2 and B2 scenarios. According to the results of climate change assessment under scenario A2 for Dez river basin, precipitation would decrease up to 22% and up to 5 degrees centigrade would rise in average maximum and minimum temperature while concerning B2 scenario, a decrease in precipitation up to 33% and a rise in temperature rise up to 3°C are estimated.

Introduction Iran has very complicated topography and climate including two mountain chains of Zagros and Elborz, two wide deserts of Kevir-e-lut and Dasht-e-kevir, forest lands and three large water bodies of Caspian Sea, Persian Gulf and Oman Sea. Climatically, Iran has a variable climate. Winters are cold with heavy snowfall in the northwest and below freezing temperatures during December and January. Spring and fall are relatively mild, while summers are dry and hot. In the south, winters are mild and the summers are very hot. On the Khuzestan plain, summer heat is accompanied by high humidity (Alijani, 2003). The intergovernmental Panel on Climate Change (IPCC) reported that the global mean temperature has been increased 0.6o C during 20th century while the atmospheric concentration of carbon dioxide also increased from 280ppm to 370 ppm in third Assessment Report (TAR) published in 2001(Kwon, 2005). Validation of PRECIS regional climate model in Bangladesh is performed with the surface observational data of rainfall and temperature (maximum and minimum) at 26 observational sites throughout the country from 1961-1990. It is found that regional analysis provides overestimation of PRECIS values in Bangladesh whereas data extracted at some particular locations provide better performance of PRECIS. For baseline, the performance of PRECIS is about 90% for rainfall.PRECIS can detect about 96% and 100.3% of maximum and minimum temperature respectively (Islam et. al., 2005). Climate change in the past decade in Jianghuni valley is studied by using statistical techniques. Both frequency and strength of extreme climate events such as hot weather, droughts and floods have increased remarkably since 1990s. Also, the regional climate model of PRECIS is used to provide a prediction of future climate in the valley. The results give an average surface warming of 2.9oC under the SRES B2 emission scenario by the end of this century (2071-2100). Precipitation may increase on the same period (Tian, et. al., 2006). Methodology Under Article of the United Nation Framework Convention on Climate Change (UNFCC), all Parties must study the impact of climate change in their countries using regional climate models. To do this, a PC-based regional climate model named PRECIS has been developed at the Hadley Center of United Kingdom Meteorology Office. PRECIS is based on the atmospheric component of the HadCM3 general circulation model. The atmospheric dynamics module of PRECIS is a hydrostatic version of the full `primitive equations and uses a regular longitude-latitude grid in the horizontal and a hybrid vertical coordinate. In this research monthly to seasonal precipitation of Iran has been modeled using PRECIS regional climate model with HadAM3P boundary condition data. PRECIS has a horizontal resolution of 50 km with 19 levels in the atmosphere (from the surface to 30 km in the stratosphere) and four levels in the soil. The present version of PRECIS has the option to downscale to 25 km horizontal resolution. In addition to a comprehensive representation of the physical processes in the atmosphere and land-surface, it also includes the sulphur cycle. The validation of model has been done by comparing observation data and model output data with two different methods of region to region and station to station. For this study, the PRECIS model domain has been set up with a horizontal resolution of 50 x 50 km. The domain is roughly stretched over the latitude 23 to 45?N and longitude 43 to 68?E. The HadAM3P global data set is used to drive the PRECIS model. The horizontal resolution of the HadAM3P boundary data is 150 km and for the present and future climate, it covers the period 1960-1990 and 2070-2100 respectively (Wilson et al., 2005). For the future climate, both SRES A2 and B2 greenhouse gas emission scenario is selected. Results and Discussion Seasonal to annual error and bias of the model outputs have been calculated using to different approach of region to region and station to station methods. We considered Masoudian's zoning (Masoudian, 1387) approach of the precipitation of Iran for computing regional error and bias of the model. In this approach precipitation region of Iran have been categorized in 12 regimes of South Central, Farsi, Kordi, Sistani, West Khorasan, East-Khorasan, North Central, Khuzi, Hormozi, Azari, Baluchi and Khazari. It is found that overall error of model is 5.3%. Maximum error has occurred over Farsi, Hormozi, Khuzi and Khazari regions with errors of 24.9, 16.9, 12.2 and -10.2 respectively. Minimum errors occurred over Kordi, Azari, and Northern central and eastern Khorasan regions. Maximum monthly errors occurred in September, the transition month between summer and autumn and minimum monthly precipitation has happened in May. It seems that wet bias of simulations in Southern regions can be due to transferring of high amount of humidity from large-scale GCM’s cells into RCM’s fine cells. Also dry bias of simulations in Caspian region is because of low ability of PRECIS in parameterizations of convective precipitations. Results show the regional errors are found in Farsi and Hormozi regions and minimum errors are in Kordi and North-Central regions. Maximum and minimum monthly errors are found in September and December, respectively. Conclusion As a main result, PRECIS skill in modeling regional precipitation, especially over the regions with high amount of convective and local precipitation is low, but it can model well the total precipitation of Iran. Average error of modeling over the country is less than 2%, but maximum regional error of modeling is 10% in Farsi region. Maximum precipitation errors are found in transition months. We found that PRECIS can model overall precipitation of Iran well, but it has some deficiency in modeling convective precipitation in Caspian region and southern part of Iran. There is no significant difference between PRECIS-modeled data and actual data retrieved from weather stations. So, as a powerful regional model, PRECIS can be used for regional climate modeling over Iran and future climate change projections.

Precipitation and temperature patterns have especial role in the accuracy of hydrologic models. The future patterns of rainfall and temperature can lead to better hydrological predictions. Hence, according to their importance, we try to derive the future rain and temperature patterns of the Gharehsoo River’s watershed. This watershed has been placed in the northwest of Iran in Ardebil province and it has high amount of agriculture productions. Interpolation schemes are utilized in this study to determine the rain and temperature patterns. The utilized software package is ArcGIS software. These interpolation techniques are included of Inverse Distance Weighting (IDW), Global polynomial, Local polynomial, Radial Basis Functions (RBF), ordinary Kriging and simple Kriging. Firstly, we gather the monthly temperature and precipitation data of 10 synoptic stations in 2004. Then, the interpolation schemes are evaluated in order to determine the best temperature and precipitation patterns. The evaluation criteria in this study were Root Mean Square Error (RMSE) and Mean Error (ME). The results of evaluation of different interpolation schemes demonstrated that IDW and RBF method are the best schemes for the spatial modeling of temperature and precipitation patterns, respectively. Using these patterns, it is straightforward to predict runoff using hydrological models. In this paper, a new algorithm is proposed for the prediction of temperature and precipitation patterns for future (2100). To predict temperature and precipitation pattern, it is necessary to utilize of a predictor model to predict the amount of precipitation and temperature. Then the amount of precipitation and temperature are converted to spatial pattern of precipitation and temperature using the developed algorithm in this study. PRECIS model that is a regional climate model was utilized as predictor model in this study. a) case study: The studied area (Gharehsoo river watershed) is located in the Northwest of Iran, between longitudes coordinates 47°45’ and 48°42’ E, and between latitude coordinates 37°46’ and 38°34’ N. The Gharehsoo river watershed area is approximately 4100 km2 and plays significant agricultural role in Iran. the mountainous areas have been located in the western and southeastern parts of watershed. Furthermore, there are many pasture and agriculture lands in this watershed. Watershed elevation varies from 1170 m in Gharehsoo river outflow to 4732 m in Sabalan mountainous. The precipitation in the watershed is highly related to the topography and wind in the watershed.. The sea fronts and orographic conditions are the main factors for precipitation in the western and eastern parts of watershed. In the winter, the cold front of Mediterranean Sea, coupled with the local effects of Sabalan Mountains lead to orographic rainfalls. In summer, weather conditions are predominant of Caspian Sea front is the major factor for precipitation in the eastern part of catchment. Autumn and spring rainfalls are the results of interaction between African-Mediterranean and Caspian Sea fronts. b) Data: Temperature and precipitation data are two basic climatologically variables, measured at meteorological stations. Monthly precipitation (mm) and temperature data for 2004 was provided through Iran Meteorological Organization. The number of stations in the watershed and near to watershed was 11 stations. c) PRECIS ModelPRECIS (Providing Regional Climates for Impacts Studies) is a regional modeling system that can be run over any area of the globe on a relatively inexpensive, fast PC to provide regional climate information for impacts studies. The idea of constructing a flexible regional modeling system originated from the growing demand of many countries for regional-scale climate projections. Only a few modeling centers in the world have been developed RCMs (Regional Climate Models) and utilize them to generate projections over specific areas, because it needs high amount of computational effort and time. The Hadley Centre has configured the third-generation of Hadley Centre RCM, named PRECIS that is easy to set up. The past (1961-1990) and future climate SRES B2 scenario (2071-2100) were simulated by PRECIS model at a spatial resolution of 50×50 km for Iran. It’s necessary to have a series of precipitation and temperature patterns to produce monthly patterns for future. These series of maps are generated using the precipitation and temperature patterns of 2004. The hyetograph maps are calculated by the ration of total volume of precipitation in January and the area of watershed. The calculated total volume of precipitation in January using the precipitation pattern map was about 490 million m3. The ration of volume and the area of watershed was about 0.117 m. This number shows the average precipitation of January. Similarly, these operations can be performed for the other months of 2004. The unit hyetograph and thermograph maps are generated by dividing the precipitation and temperature patterns in 2004 to their corresponding monthly precipitation and temperature values. The precipitation and temperature data were extracted from the PRECIS model for 2100. The monthly temperature data of 2100 shows an increase of temperature about 2 to 5 degrees in future, but there is no specific trend in precipitation data. If the amount of the monthly temperature and precipitation of 2100 are divided by these amounts in 2004, the amount of B parameters are calculated for precipitation and temperature in different months. Finally, the precipitation and temperature patterns will be obtained by the product value of B parameters and unit hyetograph or thermograph maps in each month, respectively. A new method was developed for reasonable prediction of spatial patterns of precipitation and temperature. This new method uses of the results of a Regional Climate Model (e.g. PRECIS model) coupled with the appropriate spatial modeling techniques (interpolation techniques). The derived precipitation and temperature patterns in 2100 in Gharehsoo River watershed show a reasonable similarity with the topography and the climate of the region, Hence This method can be introduced as an appropriate method for the hydrological forecasts and water resource management.