سامان مرتضی پور

In the warm seasons of the year, some storms occur that are difficult and complicated to predict. These strong winds that are usually accompanied by dust are known as Haboob in some countries. In the last decade, some of the storms that have occurred over Tehran area, which have caused numerous damages, have included the mechanism of the Haboob event. In this study, a method is introduced for the feasibility of predicting the potential of storms with a down burst structure, that provides defined warning levels for this phenomenon. In the this method, by using a post-processing on the output of a numerical weather prediction model, according to the dynamics and thermodynamic conditions of the weather, a level of warnings is issued for the potential of storm events with down burst mechanism. In the present work, an ensemble forecasting system developed for the WRF model, is used to provide short term predictions of such storms over Tehran area. Five different thermodynamic indices were calculated for the grid points and the process of calculating the potential of a storm event with a down burst structure was carried out by considering the temperature near the earth's surface, the thermodynamic conditions of the atmosphere, the vertical profile of relative humidity, and also checking the presence of dynamic conditions for air ascent. If the thermodynamic conditions and the instabilities of the atmosphere identified by the relevant indicators are conducive and the temperature of the earth's surface and the vertical profile of the relative humidity are appropriate, then the potential of a storm with a down burst structure can be considered probable. The humidity conditions were considered in such a way that the lower levels of the atmosphere have low relative humidity and the higher levels have more relative humidity so that the probability of evaporation of rain before it reaches the earth's surface is high. By combining these conditions for the output of the numerical model, in all of the time steps, three warning levels of the model output for the potential of a storm with a down burst mechanism were presented in the form of yellow, orange and red color zones. Four cases of strong winds and storm, as well as the famous storm that occurred on June the second, 2014, were investigated for the city of Tehran. Various forecasting maps of the output of model run include the mean sea level pressure, the thickness of the layer between the levels of 500 and 1000 hPa, wind speed, the relative vorticity of the level of 500 hPa, geopotential heights of some levels, thermodynamic indices, relative humidity in some pressure levels and the skew-T diagram was prepared at the grid points to analyze the dynamics, thermodynamic and synoptic conditions of the atmosphere. According to the information of the Meteorological Organization of Iran, winds with speeds between 80 to 120 kilometers per hour have been recorded in the meteorological stations of Tehran on these dates. In all these cases, the recorded wind speeds is significantly higher than the direct prediction of numerical weather forecasting models. In fact, it could not be recognized and predicted only by the output of these models. The maps for forecasting the warning level of the feasibility of a storm with a down burst mechanism in all cases investigated in this work during the calculations related to the probability of the occurrence are presented in this study. It seems that the presented method is able to predict the potential of the occurrence of strong winds and storms with down burst structure for the city and province of Tehran.

Calculating the Q vector and preparing its output products can be very effective for meteorology and weather forecasting. The vector and its convergence determine the upward motions of the atmosphere, so maps involving the vector and its convergence at different pressure levels, along with other meteorological maps, for weather forecasts and related warnings, increases the accuracy of this process. In order for the omega equation to have a more appropriate description and analysis, and also to combine sentences in the equation that neutralize each other to some extent, the Q vector has been defined and replaced in the equation. Thus, convergence and divergence for the Q vector show the ascending and descending motions of the atmosphere, respectively. In this study, Q vector values and their convergence were calculated at different pressure levels and the accuracy of the results was studied for two incoming meteorological systems with heavy rainfall. A period of time includes February 25 and 26, 2020, during which regions in the west of the Iran and the southern slopes of the Alborz mountain range received significant rainfall. The second period is July 13 and 14, 2020, with relatively heavy rainfall in parts of the north of the Iran.To perform the calculation, global GFS model output data with a horizontal resolution of 0.5 degrees and 3-hour forecast time step, temperature values and geopotential height at grid points were extracted. the Q vector and its convergence were calculated using the central second-order finite difference method and the numerical noise arising from high spatial resolution was reduced using a discrete spatial filter. Convergence maps of the Q vector representing the upward motion were analyzed by the accumulated precipitation, ground surface information, satellite images, and synoptic maps. The results of vector calculation and its convergence had considerable accuracy and consistency with the time and place of heavy rainfall leading to flooding in the two cases studied. In the first case, the precipitation system was imported from the west of the Iran with a dynamic active trough, and there was a good humidity flux from lower altitudes, which caused heavy rainfall, especially in Ilam province and areas of the southern slopes of the Alborz mountain range, including Tehran province. Studying of synoptic maps, cumulative precipitation and analyzes performed and their comparison with the results of Q vector calculation and its convergence in different forecasting hours, shows the appropriate accuracy of the Q vector calculation. The convergence of Q vector, corresponds to the hours and areas of heavy rainfall in the west of the country and the southern slopes of the Alborz mountain range. In the second case, the existing conditions from the analysis of synoptic maps indicate that the influence of the high pressure system from the north to the shores of the Caspian Sea, which is a common cause of mechanically ascending due to precipitation in this region, does not have a strong presence and being located at the cold output of the jet, the presence of the trough in the middle of the atmosphere in the northwest of the Iran and the flux of moisture from the eastern Mediterranean have caused instability and precipitation. These rains caused floods and damage in areas of the northern slopes of the Alborz mountain range, especially in the western and eastern heights of Gilan province. Despite the differences in precipitation forecasts by GFS and ARPEGE models for this time period, the studies show a significant temporal and spatial agreement between the results of Q vector calculation and its convergence with the analysis of synoptic maps and land surface information.The results showed that the Q vector results for the western regions and along the Zagros mountain range at the level of 500 hPa, for the southern areas of the Alborz mountain range at the level of 700 hPa and for Gilan province and the southern shores of the Caspian Sea at the level of 850 hPa, was more consistent with the cumulative precipitation measurements and synoptic analyzes. Considering more cases continuously and operationally, can provide the better estimate the conditions of forecasting by Q vector and its accuracy, according to the specific conditions of each region, such as altitude, moisture resources, location of roughness and mountain ranges and other factors.

Precise forecast of meteorological quantities has always been an important challenge. Direct model outputs (DMO) of Numerical weather prediction models always contain random and systematic errors that reduce the accuracy of predictions. By using post-processing methods on raw output, models can reduce the systematic errors and improve the accuracy of predictions. It has been proven that by using statistical post-processing methods, the skills of the forecasts are mainly improved by reducing systematic errors. In fact, post-processing process, should reduce the systematic error between model predictions and observational values in future by using the statistical relationships between the output of the model and the observations in the past. In this study, the output of the WRF model for the Meteorological Station of Rasht Airport in the period of 8 months for temperature, dew point temperature, maximum temperature and minimum temperature was applied post-processing by the moving average method (MA) and verified. Continuous value verification showed improvement in all quantities, Continuous verification showed improvement in all quantities, and the recovery rate is based on ME from 81% to 110% and based on RSME from 4% to 12%. By defining threshold values, improvements were also observed in most categorical verification values.

Climate change is a statistically significant change in the average time series of long-term data (decades and more) related to climate in the region. Significance of the climate change, looking at its impact on the process and cycle of ecosystems and climate patterns on a regional and global scale, the occurrence of phenomena such as severe floods, droughts, global warming, severe heat and colds, changes in atmospheric synoptic and dynamic patterns and so on are evident. These impacts have implications in many areas of life including economics, agriculture, tourism, water resources, urban life, health and many more. For this reason, a regional study of this subject seems necessary and is one of the most important global issues of concern to politicians, economists, researchers, and other relevant individuals and institutions. In this study, using 30-year meteorological data of five stations in Guilan province and calculation of potential evapotranspiration, climate change in the region for a number of parameters, as well as the precipitation climate indices investigated. Trend analysis results with methods statistical and graphical Mann-Kendall tests, simple linear regression and climate indices were in agreement with each other. Significant levels of 0.1, 1, 5 and 10 percent used in the analysis of the results. The results showed that there is climate change in the region due to wind speed and potential evapotranspiration whit significant increasing trend and due to variable relative humidity whit significant decreasing trend. For example, the city of Rasht had increasing trend of 0.27 meters per second in the decade for the wind speed, 33 mm per decade for total potential evapotranspiration per year, as well as, a decreasing trend of -0.45 mm per decade for daily average humidity, over the 30-year period studied. Precipitation variables and indices do not have sufficient significant levels for climate change. The overall results indicate that these climate changes are the most dependent in summer and the least dependent in autumn.

Temperature is one of the main climatic parameters and its changes have a great impact on many natural processes, on the other hand, climatic indices which are based on temperature are considered as the main indicators of climate change in related researches. In this study, daily temperature data of 30-year temperature of the five synoptic stations in Guilan province were used for assessing climatic changes of the temperature parameters as well as the climatic indexes of the temperature extreme events in the region. In analyzing the results, significance levels of 0.1, 1, 5 and 10% were considered. Trend analysis was examined using the Man-Kendall statistical and graphical trend tests, single-variable regression, and extreme climate indexes. The results show that temperature parameters maintain an increasing trend in the region with meaningful level of confidence. The arithmetic mean of the increase in temperature at all of the stations was 0.5 and, as examples for the average temperature, the city of Rasht had an increasing decadal trend of 0.46 degrees Celsius, which consequently causes 1.38 degrees Celsius increase in the whole study period. Other extreme temperature indicators were also showing significant increasing trends in the region, as the proofs of climate change occurrence. In seasonal term, Temperature indices have the highest seasonal dependency in summer and the lowest dependence in autumn.

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 we obtained the maximum height of the mixed layer for each day in the time period 1998 to 2017 by using the radiosonde zero Greenwich data of Mehrabad airport station in Tehran and also using the maximum temperature measured at 12 GMT at the same station. The mean value of the depth of the mixed layer whit monthly time separation during the studied time period as well as the maximum, minimum and average height of the mixed layer for January, December, July and August were calculated as the representative of the two cold and two warm months. In the following the selected samples were analyzed by the SKEW-T chart. The results showed that the average maximum height of the mixed layer in warm seasons was between 3 to 4 km and in cold seasons between 1 and 2.5 km. The purpose of this research is to provide a method that predicts the depth of the mixed layer by using the upper air data of the zero GTM and also using the predicted maximum temperature. The predicted results can be used in suitable time range for practical, scientific and prognosis purposes.

Precise forecast of meteorological quantities has always been an important challenge. Direct model outputs (DMO) of Numerical weather prediction models always contain random and systematic errors that reduce the accuracy of predictions. By using post-processing methods on raw output, models can reduce the systematic errors and improve the accuracy of predictions. It has been proven that by using statistical post-processing methods, the skills of the forecasts are mainly improved by reducing systematic errors. In fact, post-processing process, should reduce the systematic error between model predictions and observational values in future by using the statistical relationships between the output of the model and the observations in the past. In this study, the output of the WRF model for the Meteorological Station of Rasht Airport in the period of 8 months for temperature, dew point temperature, maximum temperature and minimum temperature was applied post-processing by the moving average method (MA) and verified. Continuous value verification showed improvement in all quantities, Continuous verification showed improvement in all quantities, and the recovery rate is based on ME from 81% to 110% and based on RSME from 4% to 12%. By defining threshold values, improvements were also observed in most categorical verification values.

With regard to the importance of the Mediterranean region as a highly active region in the Northern Hemisphere winter, many studies have been devoted to the weather and climate of this region in general and the impact it receives from the North Atlantic storm track in particular. In 2014, Ahmadi-Givi et al. studied the interaction between the North Atlantic and Mediterranean storm tracks in winter 2005–2004 from the perspective of Rossby-wave propagation and introduced two different kinds of interaction which are referred to as the first and second kind of interaction in what follows. In this paper, based on the latter two kinds of interaction, we aim to identify and better understand the mechanisms of the impact of the North Atlantic storm track by investigating the way Rossby wave-packets are transferred to the Mediterranean region in the extended winter of 2012–2011. To this end, the Hovmoller diagrams, the wave envelope detection, wave activity diagnostics and the energetics are employed. For this extended winter, in total, five marked cases of wave-packet propagation from the North Atlantic to the Mediterranean region are detected. Results show that these five cases can be put into three categories. In the first category, there are two cases in which the wave packets reach Europe, in the upstream of the Mediterranean storm track and penetrate to lower latitudes and the southern branch mentioned in the work by Lee in 2000 and the first track mentioned in the work by Hoskins and Hodges in 2002. Therefore, these cases behave in the same manner of the first kind of interaction. In the second category, there are two cases in which the wave packets pass through the northern part of Europe, then propagate southeastward and join the southern branch along the second track introduced by Hoskins and Hodges in 2002, farther downstream from the first category. Therefore, the cases of the second category behave in the same manner of the second kind of interaction. In the third category, there is only one case in which the wave packet enters the upstream of the Mediterranean storm track and the southern branch in the west of Mediterranean region. However, wave activity diagnostics show that most of the wave activity propagates eastward in the Northern Europe along the second track with little penetration to the lower latitudes. Having signatures of both the first and second kind of interaction, the third category thus exhibits a mixed behavior. Detailed diagnostics are presented for two cases, one from each of the first and second categories. Overall, the fact that four of five cases are compatible with the two kinds of interaction adds to the credibility of this classification. It is also significant that on average, there is monthly one case of wave-packet propagation from the North Atlantic to the Mediterranean region. Finally, it is hoped that this work can be applied to the long-term data sets available, like that of NCEP/NCAR, in order to determine the statistical behavior of the wave packets and the interaction of the two storm tracks.