نشریه نیوار
پیاپی 120-121 (بهار و تابستان 1402)

Identifying the local people's attitude towards climate change and the traditional and modern solutions they took to adapt can be very useful in managing the effects of climate change. The purpose of this research is to present the views and attitudes of the native rice farmers of Mazandaran with climate change and adaptation strategies to it. In order to do this, first, the opinions of the local people about climate change and the strategies to adapt to it were measured using a questionnaire method, and they were processed using statistical methods. After determining the adaptation strategies index (ASI), 19 presented strategies were ranked so that the results can be used for more effective policies to adapt to climate change and provide better services to the local rice farmers of Mazandaran. The results showed that more than 50% of the rice farmers in the region have felt and experienced climate change and its effects, and the most important consequences of climate change in the rice sector are the reduction of soil fertility, the use of more fertilizer and the increase of pests and diseases, early planting and This is followed by the damage of the late spring cold, the increase in the time the seedlings stay in the treasury and the decrease in drinking and agricultural water, and solutions such as public fight against pests, provision of subsidized fertilizers and poisons, management of irrigation time and sustainable water management are the solutions selected by local people .

Although the accuracy of wind-driven wave height simulation largely depends on the quality of the forced wind field, despite the production of high-quality wind products, the wind fields used for ocean waves modeling are more or less subject to bias. Minimizing the impact of wind errors on wave model output is not a long-term operational solution. A more common method is to calibrate the wave model, which is generally implemented by setting certain coefficients in these models. In the present study, the sensitivity of the simulations of the significant wave height to the terms of the wind input and whitecapping dissipation in a third generation wave model has been investigated. For this purpose, 36 different configurations of the wave model have been used. the results of this study allow us to see the response of the SWAN model as a function of physical parameters. Calibration of the SWAN model using the ERA5 forced wind field significantly improved the simulation accuracy in the Oman Sea. For the Oman Sea, it is recommended to use the expressions of wind input and whitecapping dissipation based on the Janssen formulation with the coefficient C_ds=4.0 in the simulation. Considering the error statistics, the same finding was obtained when the model results were compared with the measurements of the wave recorder buoy of the I.R. of Iran Meteorological Organization (IRIMO) in the northern part of the Oman Sea.

In recent years, dealing with the phenomenon of dust has become one of the most important environmental challenges in different regions of the world, and many studies have been conducted in connection with the identification of sources of dust and the areas affected by them, as well as ways to deal with it. Iran, as one of the countries located in the global dust belt, is affected by the dust phenomenon, and its different provinces are involved in this phenomenon in different seasons. Hormozgan province, located on the northern shores of the Persian Gulf, is affected by dust events due to weather patterns. In this article, using different observational data, remote sensing products and numerical modeling, dust springs in Hormozgan province have been identified and the areas affected by them have been identified. The results showed that dust springs with intense activity are located in the southeast of Jask city, the border of Bandar Abbas and Khmer cities, and also east of Bandar Lange. The highest amount of vertical dust flux is related to Jask, south of Bandar Abbas, Bandar Khem and east of Bandar Lange, which also include the highest potential of dust with wind speed of 20 meters per second and humidity of 5%.

In order to study the phenomenon of dust in the Middle East, using the reanalyzed data of ERA5 and the observation data of synoptic stations in the period 2009 to 2018, the temporal and spatial patterns of synoptics affecting the formation of dust have been analyzed. With the increase of temperature in spring, a low-pressure is formed in the southeast of Iran, which expands to its northeast in summer, and along with the penetration of a ridge in northeastern Iran, it causes to create pressure gradient and consequently an increase in wind speed. Eventually it causes dust emission. In autumn and winter, the polar jet blows stronger and expands to the south. In summer, however, it becomes weaker and the subtropical jet moves to higher latitudes. In other words, in the warm season of the year, dust storms are accompanied by a strengthening of the pressure gradient near the mean sea level and an increase in wind speed, which activates the sources and emits and transports dust. In the cold season of the year, the formation of the cold front, especially in Iraq, causes strong winds and eventually leads to the emission and transfer of dust.

Modeling extreme temperatures is one of the important challenges in predicting climate behavior. The aim of the current research is to introduce and evaluate a new Hamadi (weighted mean-correlation) in forecasting the extreme temperatures of the cold season of Iran using socio-economic scenarios. In this regard, the output of 5 models GFDL-ESM4, MPI-ESM1-2-HR, IPSL-CM6A-LR, MRI-ESM2 and UKESM1-0-LL and the data of 95 synoptic stations in two basic periods (1981-2019) and The forecast period (2021-2040) was used. First, the direct output of the models was corrected by the variance method, and then Taylor's diagram and statistical measures were used to check the efficiency of the models and the introduced Hamadi model (weighted average-correlation). Using the newly introduced Hamadi model, limit temperatures were predicted with two optimistic scenarios SSP126 and pessimistic SSP585. The results showed that the error rate of the used Hammadi model has been able to reduce the error of the models used in forecasting to an optimal extent. The estimated data for the minimum temperature are more similar to the actual data than the maximum temperature. The minimum temperature will increase significantly compared to the maximum temperature in the base period. The country's latitude will play a major role in the country's maximum temperature distribution, and the minimum temperature distribution will also be influenced by the country's major altitudes and latitude.

The study of soil temperature at different depths is important for climatology (especially at the micro-scale), agriculture and industry, and affects many soil processes. The method used is descriptive-analytical and its purpose is to determine the linear and non-linear relationships of air temperature and temperature depth of 5, 10, 20, 30, 50 and 100 cm during the statistical period of 1386 to 1390 in Jahrom station... Hourly statistics of air temperature and temperature of different soil depths were obtained from Fars Meteorology and linear and non-linear relationships were extracted for each soil depth using regression method. The results showed that based on the correlation coefficient and determination coefficient, linear regression has better results than non-linear relationships and in linear relationships, the correlation coefficient between air temperature and soil depth temperature for all seasons is significant at the 99% level. The highest correlation coefficient in all seasons was usually at the depth of the soil surface, especially at a depth of 5 cm at 18:30 and the lowest correlation coefficient in all seasons was at a depth of 1 meter at 6:30. As the depth increases, the correlation coefficient and determination coefficient have a decreasing trend. The highest range of temperature fluctuations in the soil occurred at 6:30 and at depths of 5 to 20 cm, and the increase in soil temperature compared to the increase in air temperature in spring and autumn is more than in other seasons.

The late spring frost damage has been one of the significant natural hazards. Spring frost is considered an important threat to agricultural products. The aim of this study is to find the answers to these questions. "How does a late spring frost affect agricultural crops?" and "What are the gaps in recent research?" Several articles were collected from Web of Science, Scopus, Science Direct, Pub Med, ResearchGate and Google Scholar search engine, SID, Iran Doc, Magiran, and Si explore the databases until November 2022. In order to find relevant publications, “Spring Frost”, “Late Frost” and “Late Spring Frost” were used as the keywords. After evaluating the articles, 45 articles were selected. Recent studies have shown that 42.22% of the articles were related to damage inflicted by late spring frost. 53.33% of that were published in Asia. Most articles were published in Iran and other parts of the world in 2014 and 2018, respectively. The words "Frost Damage", "Phenology", "Climate Change" and "Frost Spring" appeared as the most frequent keywords. In addition, the results showed that the damage caused by the LSFs (Late Spring Frosts) significantly affects vulnerable plant organs markedly affects. Late-spring frosts occurring after the germination of herbaceous plants and trees have an important impact on agriculture and forestry in regions of the world. This event has caused more economic losses to agriculture than any other climatic hazard in Asia, North America, and Europe. However, the severity of damage due to LSF may be amplified by climate change.

Preventing environmental damage from oil spills has always been considered a big challenge for marine communities. In the meantime, the first step in facing this problem is to reveal and identify the pollution as soon as possible in order to control its spread and adverse effects. Traditional methods that are based on field visits are costly and time-consuming due to the need for equipment and manpower. Therefore, the use of methods based on remote sensing technology and satellite images has been significantly developed recently. In this research, the capabilities of Synthetic Aperture Radar-SAR data, Google Earth Engine, and Geographic Information System environment were used in the form of an integrated framework to accelerate the process of identifying oil slicks. Based on the method of this research, first, the area of interest was determined and the SAR data of the Sentinel 1 satellite was selected in the Google Earth Engine environment. In the next step, oil slicks were revealed through filtering. In order to check the accuracy of the method, the results were compared with records of pollution events in the area of study. Comparing the obtained results with oil pollution events in the study area shows the appropriate efficiency of the proposed framework for detecting oil stains.

The pistachio nut is native to Iran and this country has the most favorable climate for cultivating pistachio trees. Generally, there were only five main pistachio producing-provinces in Iran including Kerman, Khorasan, Yazd, and Semnan. Temperature, specifically winter chill accumulation, is generally considered to be a decisive climatic factor in flowering and fruit sets. Pistachio trees require winter chilling to overcome their dormancy and initiate fruiting. If the winter chilling requirements are not met, the pistachio tree may not achieve the best yield the following year, or may not produce any fruit at all. The main goal of this work is to calculate the chilling requirements for breaking the dormancy of four pistachio cultivars, using the CH method. ERA5-Land reanalysis data of temperature have been used to delimit the potential spatial distribution of chill accumulation for these cultivars in Iran during 1981-2021. Moreover, the probability of satisfying the chilling requirements has been mapped to delineate the appropriate zones of the country where the chilling requirements can be met. The results showed the Kalle-Ghuchi cultivar could be potentially cultivated in almost every location of Iran, except coastal and mountainous areas where the chilling requirements would not be met. If a higher probability of satisfying the chilling requirements is desired (75% of the years, the requirements of winter chilling are achieved) around 0.2, 29, 47 and 66 percent of the area of Iran are potentially suitable for Akbari, Owhadi, Ahamd-Aghaei and Kalle-Ghuchi cultivars respectively. Kalle-Ghuchi can be grown with a high probability of chilling requirement satisfaction in wide areas of Iran. This information can be used to advise pistachio farmers about which cultivars are best suited to their area and which areas of our region are the most appropriate for pastiche production.

Considering that in automatic weather station systems, raw data is collected by sensors by AWSs, and these sensors themselves cannot process raw data. The data is sent to the CPS unsafely for processing, considering that the raw data in the wireless network is sent. No encryption operation or key exchange has been performed between the communication parties. At any moment, there is a possibility that a third party with an identity attack can be placed between AWS and CPS and listen to or manipulate the data sent. In this article, we have presented a new encryption method by combining the Jamal encryption system and the Diffie-Hellman key exchange algorithm, which, unlike the existing method, provides the ability to exchange keys for the sender and receiver from the public key so that there is no longer a need for encryption and key exchange from two algorithms. Be used differently. The simulation results of the proposed method against pervasive search attack show that the proposed method in the first scenario is 0.030141 seconds in the normal way and 1.241097 seconds in the parallel mode, and in the second scenario is, 5.112216 seconds in the normal manner and 6.724856 seconds in the parallel process compared to the ElGamal process against the attack. Comprehensive search resists.

The purpose of this research is to analyse the drought situation of Kerman city using standardized precipitation drought indices , normal precipitation percentage and Palmer drought intensity and the relationship between these indices with the vegetation of the region. For this purpose, 30yeard of temperature and precipitation data (1988-2017) were obtained from the Iran Meteorological website to determine the value of (SPI) and (PNPI). In order to check the severity of drought, SPDI index was used. In addition, the map and diagram of the vegetation trend were prepared using GIS software and Google Earth Engine. The results showed that the SPI index of Kerman was mostly around the axis of -1 to +1, which represents a mild drought, and the PNPI of Kerman recognized most of the years as normal with 43%, and the Palmer index also showed that the years (2008-2004) 2010) have experienced a very severe drought with an intensity of about 4.8. Finally, the NDVI index showed that the maps obtained from satellite images show a decrease in vegetation of about 15 km, and according to the time series chart of 2008 and 2012, they had the lowest vegetation cover with an area of about 3 to 4 km. Therefore, due to the fact that the drought indicators examined in this study show the increasing trend of the intensity and duration of the drought and the vegetation map of the region has seen a decrease in area and the NDVI trend has been decreasing,

The security of communication between Internet of Things devices is a big concern in this field, and with the increase in the number of devices and users, the current architecture and communication protocols cannot adequately respond to the system's needs, such as authentication and access authorization. One of the important solutions to this problem is using distributed and decentralized networks such as blockchain. So far, various blockchain-based authentication and key agreement protocols have been presented in the Internet of Things and similar environments. However, a secure authentication scheme has not been proposed for meteorological systems.This paper proposes a secure authentication scheme based on the blockchain network for meteorological systems resistant to various attacks. The Security of the proposed project against formal and informal attacks is evaluated, and the analysis results show that Securityrity of the proposed scheme resists active and passive attacks. In the following, the proposed scheme is evaluated in terms of computational costs, and the evaluation results show that the proposed scheme is increasing compared to similar schemes due to the focus on computational security.