نشریه نیوار
پیاپی 88-89 (بهار و تابستان 1394)

The heavy snow that occurred in the February of 2014 in Gilan province was an extreme individual phenomena that caused high economic losses and disrupted the daily life of people who were living there. In order to find large and synoptic scale structures of this phenomena, first the dates of heavy snow have been extracted in Gilan in the period of 1964-2014, using data produced by Rasht synoptic meteorological station and also reanalysis data from National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR).
This climatological research has been conducted thorough two steps. First, averaged values of meteorological parameters have been computed during 1981-2010 years. Then the calculated anomalies have been analyzed. For this aim, two meteorological parameters including mean sea level pressure and geopotential heights at 10 and 500 hpa levels have been considered.
The results show that in recent years heavy snowfall over Gilan province has been intensified. Although there was not sudden stratospheric warming and weakness of polar vortex in the mentioned years. However, a blocking pattern in 500 hpa, especially with coupled type, have been detected for all of distinguished phenomena. In addition, sea level pressure patterns show a development of Siberian or Balkan high pressure. Also in some cases the combination of these two high pressures, has been extended to the Caspian Sea region and has caused instability and humidity transfer to the Northern coast of Iran.

Today,climate change reasonse of these changes, forecasting and recognizing the effect of these variations on the other elements and phenomenon on the earth is very important. In this study used of 28 stations in Central Plateau Basin, Iran, during 1969-2008 for modling and surveying the minimum temperature trend. Normal distribution of the annual temperature series were valuated with using Joiner test and Normal probability plot. The obtained results show that the minimum temperature of 7stations in Central Plateau Basin has abnormal distribution.which were surveyed with Daniels nonparametric test and other stations with normal distribution were surveyed with Tr parametric test.The result show 17 station have tendency change or trend amang 28 station. Tendency changes or trend are increase in all stations except Fassa. analyzing and forecasting temperature of the stations whith trend using least square and Quadratic model show that minimum temperature trend in the stations of Hamedan, Dargzin, Sabzevar, Tehran and Semnan is decreasing and for other stations, the obtained forecast show the increasing trend continues in the next year.

The main objective of this study was to evaluate potential vorticity on isentropic surfaces, and its relationship with precipitation over Iran by using of a numerical mesoscale model (MM5). The model runs were initiated at 00:00 UTC, 24 and 26 December 2004 to provide 48-h simulations of the cases and 6-hour precipitation data from the synoptic stations of Iran meteorological organization were used.
Potential vorticity (PV) is an important dynamical variable due to its conservative property in the absence of diabatic heating and friction and to its invertibility principle. Therefore PV analysis has been used in a wide range (from mesoscale to of planetary scales) of atmospheric circulations. On the synoptic-scale, isentropic potential vorticity anomalies evolve through a combination of translation (motion/advection), rotation, and deformation by the synoptic-scale wind field (Horinouchi, 2014). For these processes, isentropic potential vorticity is conserved following the motion. This study provides an overall understanding of relationship between isentropic PV and surface precipitation over Iran. The upper tropospheric disturbances are characterized by the folding of PV on the 330 K isentropic surfaces.
The findings have the following major implications. (1) Application of the dynamic tropopause patterns appears to be useful for prediction of precipitation over Iran. (2) In many areas where mean daily PV values were predicted between 1.5PVU and 3PVU, surface precipitations, also have been occurred. (3) Additional research efforts are required for a deeper investigation of the role of PV on precipitation over Iran.

Today, dust phenomenon is a new problem that affects on human life. However, the weather conditions in major planning decisions are common. Although dust in North KHorasan is a occasionally phenomenon, but it can lead to more attention. Therefore, it should be considered for the recognition and management. In this study, synoptic data of Bojnord, maps of different levels, climate data and SODAR output directed to investigate the dust phenomenon occurred in Bojnord. Studies demonstrate that pressure patterns play an important role in this area in the formation of dust. The convergence due to pressure gradient and low pressure make a strong wind near the ground. This causes dust spread in different layer and environment that the result is reduced visibility and air quality.

The main purpose of modeling time series of observations of a particular order is dependent on time according to their predictions to be made for the future. The main purpose of the analysis of time series and forecasting by the model changes. Study to predict future climate change, maximum temperature of Shiraz for the period (2011-2020) is using the box and Jenkize model. At the beginning of the study to avoid bias the polls and the final of the series a decade to predict and verify the model was abandoned. Mean and variance of the series of static tests was to restore order in the series, the series are not static. Conduct an annual series of high-pass filter (the difference) was removed and graphics ACF and identify the model was based on the difference PACF series ARIMA model = (3, 2, 1) were chosen. The adjusted model was chosen and finally go through the analysis of residues was examined and its validity was confirmed. Finally, after several steps and a more complete model are mounted to the minimum mean squared error, the model predictions were tested and the prototype that has been set aside to test the predictions. Correlation between actual and predicted values was complete. This change was predicted in the series.

In this study, four statistical methods including diurnal cycle forecast correction (DRL), linear least-square corrected forecast (LLS), mean and variance corrected forecast (MAV) and average of the three previous methods (AVG), were used to postprocess the WRF mesoscale model output for wind speed at 10-m above ground level over 85 synoptic stations located in north and northwest of Iran. For this purpose, the WRF model with a horizontal resolution of 15 km was run to prepare 3, 15, 27, 39, 51, 63, 75, 87, 99 and 111hour forecasts from the beginning of November 2011 until 30th of April 2012. By varying the number of days used for training and calculating the mean absolute error (MAE), an optimum number of days were selected as training period separately for each method. The results show that the mean error over all stations dropped to zero or close to zero for all four methods, indicating the removal of the systematic error of WRF direct model output for the wind speed. In general, LLS has a better performance in reducing the systematic error when compared to other methods and improves the MAE of the direct model output between 26 to 42 percent, for different forecast ranges So that in this way, has been reduced the mean absolute error of about 36 percent for all predictions in all studied stations. The highest amount of decrease in MAE was around 65 percent and was obtained for Qazvin, Baladeh and Alasht stations while least improvement of 1 percent was observed for Ardebil, Nir and Khodabande stations.

Precipitation in rain fed wheat agriculture is of the main factors and is considered as the only source of water. Therefore precipitation variability can greatly affect production and may be regarded as one of the most important crop production risk .This paper focuses on analysis and investigating the rain risk .For this purpose, precipitation data and production yield of rain fed wheat of Mashhad, Bojnord and Birjand is used during years 1362 to 1383. First by using the Just and Pope stochastic production function; the economic effect of the rainfall on average and variance of production, has been studied. Then expected value of loss function as the proxy of risk has been estimated. The result showed that 1 percentage increase in cumulative rainfall may affect production variance more than production average. In addition, estimation results of expected loss value base on strike level of rainfall, is 36/3 mm in Mashhad, 20/4 mm in Bojnord and 53/9 mm in Birjand. In all of three cases cultivation rain fed wheat has high risk and rain risk in Birjand is the highest than the other cases of study. This important result is applicable to designing risk management tools especially insurance programs.