جستجوی مقالات مرتبط با کلیدواژه « ریز مقیاس نمایی » در نشریات گروه « جغرافیا »

Various methods developed to convert large-scale data to regional climatic data. In few studies , the results of these methods have been statistically compared. The main purpose of this study was to compare SDSM and LARS-WG models for Downscaling output data of CANE-SM2 and HADGEM2-ES general circulation models under RCP2.6, RCP4.5 and RCP8.5 scenarios. For this study, precipitation, minimum and maximum temperature of Arak synoptic station were used as the base period (1980-2005). The results of the predictions of the SDSM and LARS-WG models were compared for three periods (2021-2040, 2041-2060 and 2061-2080). The RMSE, R2, MAE and NSE criteria were used to evaluate the performance of SDSM and LARS-WG models. Based on the results of the evaluation criteria, both models have an acceptable resuts in simulation of climate variables. Downscaling results of both models showed that minimum and maximum temperatures should increased compare to baseline in all scenarios and periods from January to June, but LARS-WG model had a over estimation compared to the SDSM model. Changes in predicted precipitation by SDSM and LARS-WG models did not have a clear trend. According to the results, the SDSM model shows more changes in precipitation, wherase, the LARS-WG model shows more changes in minimum and maximum temperature compared to the base period. Based on the results of this study, it is not possible to determine the exact superiority of each of the models, But SDSM model had a better prediction for precipitation and maximum temperature, while, LARS model had better results for maximum and minimum temperature.in general it can be said that the prediction results of both models are statistically significant (P<0.01) in most cases.

The southern coast of Caspian Sea is considered the wettest part of Iran. It is a major center of agriculture and tourism and is regarded as a great geomorphological entity in the area. In the southern coasts of Caspian Sea, rainfall, as the most important climatic element, has a complicated temporal and spatial distribution. One of the major factors that influence rainfall in this region is climate changes. The current study attempts to investigate the impact of climate changes on rainfall in the southern coasts of Caspian Sea. For this purpose, rainfall data related to 32 Rain gauges were collected from the Ministry of Energy and data related to the global climatic model (AOGCM)were collected from the American climate change website. In addition, data related to HADCM3 model were obtained from the Canadian website CCCSN. The data underwent quality control and their validity was investigated. Then, stations having records for more than 30 years were selected. After the preparation of the data, SDSM model and A2 and B2 Emission scenarios were used for the purpose of downscaling rainfall data. Findings of the study on rainfall data showed that NCEP model has a higher conformity to the observed rainfall data in estimating the amount of rainfall. The estimations made by A2 and B2 scenarios are close to the observed rainfall, except for the months with very higher or very lower rainfall than the average amount documented in the stations under investigation. The model showed a higher degree of error in months with higher rainfall (such as in the fall) compared to months with lower rates of rainfall. The highest variance of NCEP and HADCM3 models occurred in the fall (when maximum amounts of rainfall occurs) or in months in which sudden rainfalls have been documented in the areas investigated. Based on the analysis performed in the study , autumn total received rainfall in the region will increase. So for detailed planning and proper use from received precipitation it is necessary that use results of such researches .

Introduction:

 The planet's climate has been constantly changing throughout Earth history, but with the onset of the industrial revolution and human intervention on the environment in recent years, special conditions for rising global temperature have been created. Increase in Earth's temperature has modified the climatic balance and widespread climate changes have been occurred on the Earth's surface, which is referred to as "climate change". To study the effects of climate change on different systems in future, the climate variables should be initially simulated in the future. There are various methods for simulating climatic variables; the most prudent of them is the use of the outputs of atmosphere-ocean general circulation models (AO-. GCMs). Since these models simulate climatic variables in large spatial and temporal scales, to use these simulated variables in smaller scales, the output of these models should be scaled down by various techniques. The microscopic statistical method has more advantages, especially when it comes to lower costs and quicker assessment of the factors which affect climate change, including the SDSM model. Method and

The purpose of this study was to predict climate change by the SDSM model using the CanESM2 Climate Change Output based on RCP8.5, RCP4.5, RCP2.6 climate change scenarios for the coming periods of 2040-2011, 2070-2041, and 2100- 2071, as well as study the annual trend of these changes using the Man-Kendall test and the age-related slope estimator. For this purpose, daily data of rainfall and temperature parameters during the statistical period (1981-2010) were collected from the Meteorological Organization. Then, using statistical downscaling model (SDSM), these climatic parameters were simulated in a monthly scale and compared with the base period (1981-2010).In the SDSM model, for the microscopic metering, three types of data are used. The stages of working with this model are briefly summarized as follows: 1. Preparing predictive data and large scale predictors 2. Quality control of data and data conversion (for precipitation data) 3. Choosing the best predictor variables 4. Calibrating the model 5. Production of weather forecasting using observational predictors 6. Statistical analysis 7. Graphical output of model 8. Production of climate scenarios using model climate predictors.

According to the results, it was found that during the 21st century the temperature in the station of Gorgan is increasing and precipitation is decreasing. In three scenarios RCP8.5, RCP4.5, RCP2.6 in the two periods of near future (2040-2011), and the middle (2041-2070) from February to August and in the distant future period (2071-2100) from December to August there is a decrease in rainfall. The highest precipitation decline is in the near future period in June, July and August, with 19.1, 20.9, and 20 mm, and in the middle and the distant future period in each of the three scenarios belongs to May from 28.8 till 47.15 mm. Generally, in all scenarios, as we move towards the end of the 21st century, the average rainfall will be reduced, and the decrease in the RCP 8.5 scenario is more than the other two scenarios. Regarding temperature variables, the general trend of temperature variables in future periods is consistent with the trend of these variables in the base period, with the difference that the temperature will increase slightly in the winter and spring until mid-summer, but from late summer to late fall it will decrease. In the upcoming period, at first the temperatures will be higher in June and in the upcoming mid and later periods it will be higher in May than in other months. Moreover, the more moving from the near future towards the end of the century, the temperature will increase. The augmentation in the RCP 8.5 scenario is more than two other scenarios. However, Regarding the annual precipitation rate, RCP 4.5 and RCP 8.5 scenarios are meaningful and decreasing, and in the case of maximum, minimum and mean temperature variations, there is a significant increase. Also, the precipitation drop and temperature rise in the end of the century and in the RCP 8.5 scenario are more than RCP 2.6 and RCP 4.5 scenarios. According to the

In this research, the simulation of climatic parameters of temperature and precipitation was carried out using several linear models of SDSM and general atmospheric circulation models in Gorgan. The output of the CanESM2 model was simulated under RCP8.5, RCP4.5, RCP2.6 scenarios for subsequent periods in 21 steps. The results showed that temperature data, better correlation with observation data (compared with rainfall data). According to the results, it was found that during the 21st century the temperature was increasing and the precipitation was decreasing. At Gorgan Station, in three scenarios RCP8.5, RCP4.5, RCP2.6, in the two near future (2040-2011) and mid-term (2041-2070) from February to August and in the distant future period (2071-2100) between December and August we see a decline in rainfall. The highest precipitation falls in the period in June, July and August, at 19.1, 20.9, and 20 mm, and in the middle and long distances in each of the three scenarios it is from May 28.8 to 47.15 mm .In general, in all scenarios, as we move towards the end of the 21st century, the average rainfall will be reduced, and this decrease in the RCP scenario of 8.5 is more than the other two scenarios. Regarding temperature variables, the general trend of temperature variables in future periods is consistent with the trend of these variables in the base period, with the difference that the temperature increased slightly in the winter and spring until mid-summer,but from late summer to late The fall will decrease. In the upcoming period, the higher temperatures will be higher in June and in the upcoming mid and later periods in May than in other months. Also, the more coming the near future towards the end of the century, the higher the temperature will increase. This increase in the RCP 8.5 scenario is more than two other scenarios. overall result of this study, the increase in temperature and precipitation in the spring and summer and the rising rainfall and the cooling of the autumn season seems to be in the planning of water resources, and in particular, the planning of the agricultural sector This should be taken into account in order to minimize the potential negative effects of climate change in the targeted area.

In recent years downscaling models are increasingly used in predicting climate variables. One of the application of the downscaling general circulation model (GCM) is used to predict the hydrological watershed. In this study, using rainfall data during the observed period (1961-1990), in the first step using SDSM model and data HadCM3 scenario A2, were simulated runoff in Khansar watershed located in southern Yazd previence. Then anticipated rainfall-runoff Khansar basin in 30-year period (2011-2040). After downscaling and forecast rainfall Meshkan station, the nearest meteorological stations in Band-paein basin, implemented rainfall and runoff forecasting Band-paein Station at the same period. The results show that, despite the fact that rainfall in the forecast period is 6% higher than the normal period, the rate of runoff from 19.3 million cubic meters during the 30 year period (normal climate) of 1971-2000 to 17.4 million cubic meters The period will be from 2011 to 2040, which is about 9% lower. The effects of changes in the distribution of rainfall means an important issue in the future, climate change is one of consequences. Therefore, it need to planning and management of water resources, particularly for the study in arid areas.

Climate change is an accepted global phenomenon and the importance of considering this phenomenon is very important. In the present study, the effect of the phenomenon of climate change (temperature and precipitation) during the statistical periods 2020-2039 and 2040-2020 in five The applied synoptic meteorological station for Kermanshah province has been studied by entering data and doing microscopic operations on the data for the study areas. Finally, by entering the geographical information system (gis), the prediction map Rainfall is for these periods, the results of the study of the phenomenon of climate change suggest that It is expected that the temperature increase up to 4.3% for the studied stations and the increase in the average temperature of the present and also the reduction of precipitation in the tropical region and southeast and east of the province is expected, for this purpose, should be with the minimum land productivity And respecting the appropriate pattern of cultivation in these areas should be treated in a more manageable manner.

In the next decades, climate change is likely to have become a serious challenge that will alter flow regimes such as torrential flows (floods), low flows as well as the existing water resources. Climate change impact is increasingly becoming a subject matter for researchers, but the effect of this phenomena on the low flow is still not widely understood. The consequences of climate change have led the international community to further studies, which will affect the changes in the natural resources, ecosystems, and the population. Global climate cycle has been found to be intensified due to climate change, as well as it has led frequent, severe, long-term, and stable droughts in many regions. Changes in the precipitation and temperature as two major variables in the hydrological cycle will unbalance the rainfall. Also, climate change in the future decades will be very effective on high flows and low flows so that it will have a significant impact on the results of the intensity and recurrence Interval of low flows. The aim of this study is to evaluate the effects of climate change on the low flows using HEC-HMS model, as well as changes in the flow regime such as low flow frequency, the probability, and the recurrence Interval of low flow in the future period (2040-2069). Also, the uncertainties related to the downscaling methods are considered by using two statistical methods (SDSM model) and the change factor as well as it has utilized the outputs of the General Circulation Models, which are resulted from the fifth report of the IPCC. Material and methods: The Gharesou Sub-basin is located in the northwest of Karkheh basin. It covers an area of 5354 km2 and its maximum and minimum height is 3364 and 1180 m, respectively. The average annual precipitation varies between 300 and 800 mm. Three major rivers of Merck, Gharesou, and Razavar are flowing into this basin. This study has measured the project of climate change in the Gharesou basin with CANESN2 and RCP scenarios and by using SDSM downscaling model as well as using change factor downscaling. Also, the indices of low flow frequency and FL method on the flows of the future period were analyzed. GCMs are the first tool for understanding past climate variations and predicting the projection for future climate conditions. GCMs demonstrate the atmosphere and ocean in a grid of 1 to 4 latitude degrees and in a longitude from 10 to more than 200 layers vertical in each fluid. Because of the spatial and temporal scale mismatch between the GCMs’ ability and the need of hydrological modelers, the outputs of these models cannot be explicitly used in climate change studies. Various methods of downscaling are used to overcome the problem, which dynamic, statistical, and change factor are three types of downscaling. The low flow selection is done by two different methods that are 7Q10 and FL methods. In fact, FL method is one of the five groups, which has been used in low flows and/or management balances of St. Johns River in Florida. Minimum Flows and/or Levels are low flows or levels that are needed to avoid serious damages to water resources caused by water withdrawals and they are divided into five following groups of flows. The first step in selecting the low flow is done by providing long-term flow data using FL method and then drawing the FDC curve. A low flow is obtained by drawing an FDC curve. FL method was chosen in order to select the low flows on the basis of the following reasons: 1. 7Q10 method for the extreme conditions of low flow, which is appropriate between 95 to 99% of the flow duration curve time. This condition usually occurs during a short-term severe drought and a very high recurrence Interval. 2. FL method is within the low flow selection domain and FL groups are clearly determined the effects of low flow on the floodplain, animal and plant life and ecosystems. The results of statistical method showed that basin flow has been reduced in all of the scenarios during the dry season, including July, August, and September. In addition, the results of the change factor suggested an increase in flow in the November, December, January and February and its decrease in the spring and summer. It is critical to note that both of downscaling methods indicated flow reduction in the low flow period. The value of the 7Q10 index in the statistical method and change factor has reached respectively, about 0.008 m3/s and zero in the future period while this value in the corresponding historic period was respectively 0.724 and 1.429 m3/s. Also, the Q80 index has reached the value between 0.1 and 0.3 m3/s using both of downscaling methods. Generally, the results indicate a severe low flow condition in the future period

facing mankind ( Ipcc,2008 ). Infact one of the important aspects of climate change is understanding its behavior To have an outlook on future projections of climate extremes part Changes in extreme climate events has significant effects which caused a it to become as the most important challenges icularly precipitation, the outputs derived from three coupled general circulation models (HadCM3, CNCM3, NCCCSM) contributing to the Fourth Assessment Report of the IPCCAR4, under A1B emission scenarios have been downscaled by LARS-WG during three period 2011-2030, 2046-2065 for Sabzevar, station. The extremes are described by seven indices based on precipitation including (PRCPTOT,R10mm, R20mm,R95p,R99p,RX1day,RX5day,SDII) Results show that averages of Rx5day and SDII during The period of 2011-2030 will be probably increase under A2 sceranario . Inddition , alarge fraction of total annual precipitation is progected to occure in The form of heavy and showery events in 95th and 99th percentile . Regarding to The resultso incroases of 95th and 99th indices means That The frequency of flash floode and its intencity will be increased during 2011-2030 . Howerer , the intencity of precipitation and SDII will be probably to decreabse during2046-2064.

In recent decades، the increase of weather data has caused the disturbance of climatic balance of the earth which is called climate change. The aim of this study، is to predict climatic changes of Sistan-va Baluchestan province using statistical downscaling in which A2 scenario of ECHO-G atmospheric general circulation model is performed. Which were downscaled in order to evaluate climatic، drought، and glacial changes in the statistical period of 2012 - 2031 using LARS-WG model In this study، the data of minimum temperature، maximum temperature، radiation، and precipitation of ECHO-G model، and real data of seven stations of the province including Chabahar، Iranshahr، Khash، Saravan، Zabol،Zahak and Zahedan were used. Overall results of surveys shows 8 percent increase of precipitation in the province and a decrease of glacial days and the increase of average annual temperature by about 0. 3 centigrade، and the highest temperature increase will belong to the winter season by about 0. 9. Moreover، the number of dry days will decrease in Saravan and other counties and generally the droughts will decrease in the province in the 2012- 2031 period.

In spite of considerable increase in the resolution of general circulation and regional models، none of these models are capable to predict and downscale the meteorological outputs in the scale of meteorological station. In this regard، different dynamical and statistical models have been developed for downscaling outputs of GCMs. In this paper، grided meteorological outputs of General Circulation Models (ECHAM4 and HadCM2) and 18 IPCC scenarios have been downscaled over Iran for future periods by MAGICC-SCENGEN model. Each period is a 30-years period centered on a year. The range of periods is from 2000 (i. e.، 1986-2015) to 2100 (i. e.، 2086-2115). Result of HadCM2 model shows a % 2. 5 decrease in precipitation until 2100 but ECHAM4 shows a %19. 8 increase for this period. Another difference between results of these 2 models is that HadCM2 predicts an increase in precipitation in next decades for Mazandaran، Golestan، Khorasan Shomali، Khorasan Razavi، Semnan، Tehran and some parts of Guilan and Ghazvin provinces، while ECHAM4 predicts a decrease for those regions. HadCM2 predicts precipitation decrease for southeast of country (Hormozgan، Kerman، Bushehr، south of Fars and some parts of Sistan and Baloochestan)، but in ECHAM4 those regions will have precipitation increase in similar period. About temperature، both HadCM2 and ECHAM4 agree in temperature increase in next decades for all provinces. These 2 models predict، on the average، 3 to 3. 6c increases in temperature until decade 2100. Maximum increase in decadal temperature in ECHAM4 and in 2100 decad is about 1c more than HadCM2 and both of them are in conformity with each other in spatial distribution of decadal temperature.

Because of low spacial resolution of General Circulation Models, they can not predict weather and climate accurately. In this regards Weather Generator models have been developed by climatologists to downscale GCM outputs into station scale. In this research, grided meteorological outputs of ECHO-G model including precipitation, maximun temperature, minimum temperature and radiation have been downscaled over 43 synoptic stations of Iran during 2010-2039 with A1 scenario. Results show that the mean annual precipitation will be decreased by 9 percent, increasing of mean annual temperature by 0.5 degree of centigrade during period of 2010-2039. Maximum increase predicted to occure over North Khorasan, West and East Azarbaijan. Also thresholds of heavy and extreme rainfalls will be increased by 13 and 39 percent, respectively. In this regards, in the future period, the rainfalls will be heavy and flash- flooded and there is a significant decrease in the amount of snow falls and shift of precipitation in to the end of cold season.