In general, Garmesh wind in RASHT province increases the temperature by 9°C and reduces relative humidity by 47%. The direction of prevailing wind during the Garmesh wind is Southern and its average speed increases by 2 m/s to 5 m/s. The highest frequency of Garmesh wind occurs at 09 and 12 UTC in December and January. The occurrence of this phenomenon substantially increases the horizontal visibility, so the sky would be clear in more than 40% of the cases.

Wind element is one of the main factors in climate of a region that plays determining role in different plans for urban, rural, industrial positioning and architecture, agricultural, industrial, climate, etc. Regarding the changes in the RASHT region, it is particularly important. In this research, wind changes trend is considered on the periods 33 years (1977-2009). This data is obtained from annual and monthly reports of Guilan meteorological head office by the use of Excel software. Statistical test is used for data analysis. Mann-Kendall test is used to analyze wind mean speed and to observe Wind speed changes trend. The result obtained showed that annual mean of wind speed in RASHT represent change in these trends. The result showed that the Wind mean speed followed significantly decreasing trend. The time of occurrence and kind of change were seen abruptly increasing and decreasing, in different months of year.

This study is designed, aiming to detect changes in the composition and configuration of landscape in RASHT township between 1989 and 2011. It has been conducted applying SYNOPTIC analysis. Hence, landscape maps have been generated from three TM satellite images at 1987, 1999 and 2011 applying hybrid classification method. Some composition and configuration-based metrics including NP, PD, LSI, LPI, SHDI, CONTAG, ED and PLAND were then calculated at two class and landscape levels and their changes is detected. The results indicated that, in general, the landscape has been more fragmented, more complex and irregular in shape, more disconnected in continuity of patches and more diversified in the term of land use/ land cover types. It was in spite of the differences between trend and gradient of changes in RASHT county landscape at two period of time (1987- 1999 and 1999- 2011). Moreover, the results revealed that sprawl of the manmade areas have caused increase in fragmentation, irregularity and complexity of agriculture patches and decrease in total area of agriculture class. Hence, an intense degradation of ecosystems might be resulted if the current trend continues in future in the study area.

One of the consequences of the rapid growth of the cities is the heat islands, where the air temperature of the cities rises sharply in relation to the surrounding areas. Anzali station SYNOPTIC statistics were used to detect and detect changes in the RASHT elemental elements over the period 1956 to 2017. The time intervals included mean temperature, mean and maximum temperature, precipitation, humidity, evaporation, sunshine and mean wind speed. the effect The heat island intensity of RASHT city was selected from the atmospheric SYNOPTIC models and its effect on climate elements, 6 days of 2010, and ground conditions were investigated with the Jumvord scale. Sunshine and evaporation have had the highest increasing trend at different months of the year as well as the annual trend. During the high-altitude system due to the stability and stability of the island, the intensity of the heat island increases, and this occurs during the low-altitude system and the instability of the air. After comparing climate elements RASHT During the reign of high altitude and low altitude systems in this city, it was found that the climate elements were strongly influenced by these patterns. So that the difference of more than 11.5 ° C in the maximum air temperature between August 5, 2010 and August 22, 2010 Also, the difference of about 29% of humidity on the same day indicates the intensity of RASHT heat island on August 5, 2010 This system is dominated by low altitude.

Prediction and evaluation of meteorological data in effect of climate change is very important especially in water resources management. LARS is a model that generates weather data and predicts weather parameters by downscaling global circulation models (GCM). In this study, in order to evaluate 15 GCM models performance in simulating the minimum and maximum temperature, radiation and precipitation in RASHT SYNOPTIC station (2011-2012), statistical downscaling of each model was performed by LARS model. Then, the mentioned data were predicted on the basis selected GCM models for 2013-2042 and 2043-2072 periods. The results showed that the highest increase in annual average of minimum and maximum temperature will occur during the 2043-2072 periods with 1.3 and 2.0oC, under A2 scenario, respectively. The amounts of radiation will decrease in future periods for all seasons. The highest decrease (143.4 MJ m-2) of radiation will occur in 2013-2042 periods in winter under A2 scenario. The seasonal precipitation will often increase in future periods. The highest increase of seasonal precipitation (55.5 mm) will occur under B1 scenario in 2043-2072 periods for autumn.

Drought is considered broad rang of deleterious meteorological phenomena which have a significant role in reducing plant production. Temporal analyzing phenomenon is from several days to years changing. Its normally starts with the fall of precipitation below the long-term average which itself is recognized as a meteorological drought. Intensity, duration and geographical broad of this phenomenon is indicative of the extent of this phenomenon. Understanding this relationship can be an effective step in prediction and forecast for the efficient use of water for cultivators. In this study, temperature, geopotential height, relative humidity and pressure for RASHT station for a thirty year time span starting at 1974 and ending at 2004, the website of NOAA, has been collected. The use of soft ware DIP «Effective Drought Index» (EDI) and the mean time periods of drought indices were calculated. The relationship between drought index and SYNOPTIC phenomena of shows with The SAS software. There were high correlation between the estimated data and real ones, and were meaningless. That’s it; this showman is high accuracy in daily drought estimating. Therefore, with this multilateral regression model, it can estimate the site drought position carefully.

One of the most reliable methods for assessing the effects of climate change is the use of climate variables simulated by general atmospheric circulation (GCM) models, but these simulations have uncertainties. Avoiding the uncertainties associated with climate change in research will reduce the credibility of the results and result in unrealistic and unrealistic results. In this study, the data of temperature, precipitation and radiation simulated by 5 models HADCM3, NCCCSM, NCCCSM, INCM3, GFCM21 and MPEH5 at the SYNOPTIC Station of RASHT based on A1B, A2 and B1 emission scenarios were statistically analyzed. Also, the uncertainty of each of the general atmospheric circulation models and diffusion scenarios was investigated by weighting method. The results of the test of the calculated statistics for each model were presented individually. The INCM3 model in the A1B scenario for simulating rainfall, the NCCCSM model in the A1B scenario for radiation simulation and GFCM21 under B1 scenario for simulating minimum temperature and HADCM3 model in the A1B scenario for maximum temperature simulation. The results of ensemble performance of the models also showed that in the future planning, the group composition of the models can be simulated with less uncertainty and more accurately the climatic parameters. In order to select the best scenario based on the group implementation of the models, the best match is the simulated rainfall data with real data based on B1 scenario, for A1B scenario data and minimum and maximum temperature based on scenario B1.

Introduction: Evapotranspiration is a key principle of water balance and an important element of energy balance. Therefore, forecasting and estimation of evapotranspiration in agricultural water management, forecasting and monitoring drought, and the development and exploitation of effective water resources might be valuable and practical. The purpose of this study was to model the Reference Evapotranspiration time series (ET0) at RASHT SYNOPTIC Station with two SARIMA and GRNN models during 1956-2017 and its forecast for 2018-2027. Material and methods: RASHT is located in the temperate and humid parts of northern Iran and in the southern strip of the Caspian Sea. In this study, the Adjusted ThornthWaite method (ATW) was used to estimate ET0, the credibility of which was previously confirmed by researchers for estimation of reference evapotranspiration rate in RASHT. Evapotranspiration values were estimated for the time period of 1956-2017. Two models were selected for modeling and validation of the ET0 series. The SARIMA model is based on seasonal stochastic models, and the GRNN model is based on artificial intelligence. The models’ inputs were selected on the basis of three previous monthly and yearly. The target-input matrices were divided into calibration (75%) and validation (25%) sections. Autocorrelation Function (ACF) indicated a seasonal trend in the ET0 monthly series, with a return period of 12. Four times seasonal differentiation, revealed that the best degree of SARIMA’ s seasonal integrated degree was the first-order. Other SARIMA operators, including seasonal and non-seasonal autoregressive, and average seasonal and non-seasonal moving, were selected by trial and error. Optimization of the GRNN model was accomplished by trying and error of the spread parameter. In this study, criteria such as RMSE, NS, and R were used to check the error and correlate the outputs of the model. Results and discussion: The best model of SARIMA pattern was SARIMA (0, 0, 1) (0, 1, 1)12 which has RMSE and NS values of 8. 89 mm and 0. 97, respectively. The GRNN model had its best performance by applying the total inputs. The RMSE and NS values were 9. 22 and 0. 96, respectively, for GRNN’ s best output. The difference between the two models was reported in predicting the year’ s minima (January-February), which showed SARIMA’ s better performance. To compare these two models, the Taylor diagram was also used, which showed that the accuracy of SARIMA not only in error but also in the correlation and estimation of the true deviation of the real values was slightly more accurate than GRNN. After evaluating the models and assessing their acceptable performances, best extracted models from both SARIMA & GRNN were used for ET0’ s long-term forecasting up to the next ten years (for the period of 2018-2027). Conclusion: The results of the forecasts for RASHT’ s future showed a sharp ascending trend in the rate of evapotranspiration in the years 2018-2027 (compared to the period of 1956-2017). This is a warning of a rapid increase in the evapotranspiration rate in the years ahead, in the wet area of RASHT. This issue is very important for the surface water and groundwater resources planning, agricultural uses, and will be a serious warning to farmers and water managers in this area.

Homogeneity analysis is one of the important challenges of trend detection in the climate data series. However, the ability of homogeneity tests in detecting heterogeneity differs depending to the parameters or types of changes. RASHT SYNOPTIC Station has long-term climate data which according to the recorded metadata and documents has undergone several location changes. In this study, homogeneous tests including cumulative deviations, Worsley, Normal Standard, Pettit and Bishand were used to test the homogeneity of daily average temperature, air pressure and rainfall data of RASHT station during the period from 1961 to 2018. The results showed that none of the tests were able to reveal any jump in precipitation data. In temperature and pressure parameters, Both Bishand and Pettit tests had more success in discovering the sharpest heterogeneities in accordance to changes in the metadata. However, simultaneous use of multiple test results will lead to more reliable results for identifying heterogeneity. Also, although these tests give a definite date as a jump date, it should be noted that the given dates represent the range of heterogeneity occurring in the least-estimated two years around the real time of the jump. Awareness of the time period of the change of metadata can be useful in choosing the appropriate test. If it is known that potential changes have occurred around the midpoints of the series, Pettit and Bisahnd methods provide a more accurate estimate of the time of the jump occurrence.

In this study, effective SYNOPTIC anomalies in the occurrence of early heat of Andimeshk SYNOPTIC station during the statistical period 1390-1360 with an environmental approach to rotation were investigated and from altitude data related to 500 and 700 hPa and ground level pressure in the geographical area 0 to 90 degrees East longitude and 0 to 60 degrees north latitude were used and related maps were drawn in Grads software environment. Data from the National Center for Environmental Prediction Analysis and the National Center for Meteorological Research (NCEP / NCAR) as a 6-hour observation with a spatial resolution of 2.5 2 2.5 degrees showed that the high-altitude subtropical system played a major role. Is in charge. During the warm period of the year, a tongue of high pressure from the subtropical Azores that forms in the Atlantic Ocean settles on Iran. The range of operation of this tab extends from the level of 700 to 100 millibars. In this system, lines of the same height are formed parallel to each other. In contrast, sea level is associated with negative anomalies.