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Dr Manouchehr Farajzadeh, Miss Zahra Kazemnezhad, Dr Reza Borna,
Volume 5, Issue 4 (3-2019)


Climate change in one area has severe impacts on water resources and, consequently, agriculture in that area. Therefore, studying the extent of the vulnerability of regions to adopting policies to reduce or adapt to new conditions is of particular importance. One of the methods for assessing the extent of damage to agricultural activities is the calculation of the vulnerability index. In this study, with the aim of assessing agricultural vulnerability to climate change, The CVI index was calculated for 16 cities in Guilan province.

The results showed that the cities of Rasht (61.58) and Talesh (55.21) had the highest vulnerability and, accordingly, had the least adaptive power to climate change compared to other cities. And Langrood County (29.51) has the lowest number of vulnerabilities. The average value of the calculated index is 40.42 in Guilan province. In component R, the most vulnerable were Talesh (99.66) and lowest for Lahijan (2.27), In component M, the highest vulnerability was for Rudbar (97.21) and the lowest for Talesh (24.30), In component A, the most vulnerable were Rasht (89.99) and the lowest for Anzali (2.21), In component C, the most vulnerable were Shaft (66.66) and lowest for Anzali (1.89), In component U, the most vulnerable were Rasht (67.55) and the lowest for Astara (28.92), In component E, the highest vulnerability was for Talesh (76.49) and lowest for Lahijan (22.69), In component G, the most vulnerable was reported to Rasht (53.05) and the lowest vulnerability was reported for Sunnelk (23.24).

Reza Reza Borna, Shahla Shahla Ghasemi, Farideh Farideh Asadian,
Volume 6, Issue 3 (9-2019)

Today, the impact of climate is considered on the life, health, comfort, activity and behavior in a form of the branch of science   such as human biology. Due to difference of frequency people with each other, the sensibility of every one from weather can be different from the other one that's why the climate can’t be totally undesirable or the climate can be totally desirable for all the people, so we can say that all of climatic elements are affected on human comfort but the effect of some of them is quite cleared and the effect of the others is mild and sometimes invisible. The greatest effect on comfort and discomfort can be included temperature, humidity and solar radiation. The aim of this research is to investigate and determine    the area risk of climatic comfort. For this purpose, the temperature, precipitation and humidity data have been extracted for Khuzestan province form Esfarazi database. In this approach, first different properties of the temperature, precipitation and humidity for the area with climatic discomfort   have discussed   based on the conditional probability distribution. This study has been identified the areas of climatic comfort in Khuestan province using multivariate analysis (Cluster analysis and Discriminant analysis) and spatial autocorrelation pattern (Hot Spot index and Moran index) with an emphasis on architecture. The results showed that the risk area of climate comfort is included mostly  of  the western parts of  Khuzestan province namely the border areas with Iraq and some parts of  southern  of  province .On the other hand ,trend analysis the  range of this area to climatic discomfort indicated that it has increased significantly  in  recent periods .The results also  showed that  the local distribution of   precipitation  in all periods in the areas of climatic discomfort  has  been   a high  the coefficient of  variations.
Mr Gholamreza Mohamadi, Dr Reza Borna, Dr Farideh Asadian,
Volume 7, Issue 3 (11-2020)

In the present study, the spatial-temporal analysis of the Arctic vortex and its role in the occurrence of heavy precipitation days in the Ghare-Su basin have been investigated. For this purpose, firstly, with the 95% percentile method, heavy precipitation days of the basin were extracted. Then, considering the pervasiveness condition, 79 days of heavy and pervasive precipitation days determined during the1979–2015. In the following considering the contour representative of the polar vortex in the geopotential height of 500 hPa maps, elevation maps of 500 hPa, the vortex position identified on each of the heavy precipitation days based on its maximum extent on the synoptic zone. Synoptic analysis of the temporal and spatial of Arctic vortex during the selection of heavy and pervasive precipitation days shows that the 4 patterns can be identified within 79 days of heavy precipitation days. The position and concentration of the vortex patterns in each season have changed. So that the least penetration of the vortex is seen during the autumn and the most penetration in the winter. In all cases of the days of heavy and pervasive precipitation due to the locating the trough of the arctic vortex over the study region, which coincides with the settlement of the huge Rex and Omega blockings on  Europe. The highest correlation between the latitude of the vortex and the precipitation intensity is seen in the third pattern ( the Red Sea to the west of the Persian Gulf), which has the most vortex penetration in the region. In each of the vortex spatial locations, the location, length, and depth of the trough have also changed in each location. So that the best position and the most impact of vortex occurred in the third and fourth patterns where the troughs from vortex have the most depth and extension on adjacent water resources.
Mohammad Javad Barati, Manuchehr Farajzadeh Asl, Reza Borna,
Volume 8, Issue 1 (5-2021)

Evaluation of SADFAT model performance in daily forecast of Land Surface Temperature in the city of Tehran
The high spatial and temporal limitations of TIR images for use in urban climatology have been identified as a current scientific challenge. Therefore, the use of Data Fusion Algorithms in Remote Sensing has been considered. In the old methods, two bands of one sensor were used for Data Fusion. In these methods, a panchromatic band was used to increase spatial accuracy, so only spatial resolution was increased. To solve this problem, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was used to integrate the images of two Landsat and Modis gauges to increase the spatial and temporal resolution of the reflection. but, this algorithm is designed for pixels and unmixing areas that are the same in Modis and Landsat pixels. The use of this model was not suitable for urban areas with a different of landuse. Therefore, the Enhanced STARFM model (ESTARFM) was developed. The ESTARFM model was improved in 2014 to predict thermal radiation and LST, taking into account the annual temperature cycle and the unevenness of the earth's surface, and the SADFAT model was introduced.
In this study, the performance of SADFAT model in the use of OLI spatial resolution and MODIS temporal resolution in LST forecast in urban areas was examined. The metropolis of Tehran has different surface covers and multiple microclimates. So if the algorithm works successfully, This model can be used in other cities to improve urban heat island studies. The inputs for the algorithm are thermal radiance of Modis and Landsat   images, the red and near infrared band of Landsat for daily production of LST in 2017 in the city of Tehran. The algorithm uses two pairs of Modis and Landsat images at the same time and sets of Modis images at the time of prediction and then calculate the conversion coefficient for relating the thermal radiance change of a mixed pixel at the coarse resolution to that of a fine resolution. In this way, LST is generated in areas with a variety of landuse.
All the estimated pixels were compared to the base image pixels in that range to evaluate the results of the model. The comparison results for the autumn days with the average correlation coefficient of 0.86 and RMSE equal to 0.122, showed that the model has the highest accuracy in this season and in other seasons with the average correlation coefficient of 0.76 and RMSE about 0.4, has provided good accuracy.
Visual interpretation of the results of SADFAT showed that this model is able to accurately predict the LST of the land cover in different surface coatings and even in areas where one or more urban land uses are mixed in one MODIS pixel.
However, the borders are well separated and the features are not combined. Although the boundaries are clearly defined, in some land uses, the predicted LST is somewhat higher than the observational image.
Landsat and Modis satellites pass through an area with a small time difference, so they are suitable for combining with each other. But in predicting reflectance with the SADFAT algorithm, there are systematic and variable errors that we need to be aware of in order to increase the output accuracy. One of the systematic and unavoidable errors is the instability of the Terra and Aqua satellites passing through at any point, ie at each satellite pass, the location of the study area in Swath and the size of the pixel changes. Due to the distance of the study area from the vertical center of measurement on the ground (Nadir), the amount of this error varies on different days and should be checked for each day. The preventable error is the sudden change in one or more images used (16 days of the same pass time interval for Landsat) is high for estimating surface reflectance with spatial and temporal resolution. These changes may be due to human factors such as air pollution or natural factors. Natural factors such as clouds and dust storms are the main sources of error in using the SADFAT model because they are sudden and temporary and cover a wide area. The occurrence of these two factors has a great impact on reflectance. Therefore, a sudden change in these factors, in one or more images, causes a large error in the calculations.
The study also found minor spatial errors in the prediction, so that even on days when the results were better, points were observed where the values ​​in the predicted LST images did not match exactly with the OLI sensor. The reason for this may be due to changes in vegetation. Although there are some systematic and variable errors in the images and the implementation of the algorithm The results of this study showed that the performance of this model is reliable for predicting the daily LST with a spatial resolution of 30 meters in Tehran.
This method is able to support urban planning activities related to climate change in cities, so it is recommended that its performance be examined separately for different land cover in the city and the efficiency of this algorithm be evaluated with other sensors such as Copernicus Sentinels.
Key words: Spatial and Temporal Data Fusion, SADFAT, Heat island, LST, Urban climatology
Rasool Nooriara, Seysd Jamalaldin Daryabari, Bohlol Alijani, Reza Borna,
Volume 9, Issue 3 (12-2022)

Synoptic analysis of the torrential on Day 21, 1398 (Case study: Zahedan and Qeshm)

Rainfall is the most important phenomenon or feature of the environment and so far many studies have been done about its causes. In any place, rainfall occurs when humid air and climbing cause are provided. Both of these conditions are provided by the circulation pattern. The study area is affected by some severe and sudden weather phenomena such as low annual rainfall, short rainfall period and rainfall in the form of heavy showers. Thus, it is possible that the limited and pervasive precipitation of the area is due to a different synoptic pattern. Because the relationship between circulation patterns and precipitation is significant, achieving acceptable results in the field of the relationship between these patterns with the limit and total rainfall of the studying area requires the analysis of synoptic maps. Therefore, the most important purpose of the present study is the synoptic analysis of heavy cloud rainfall of the studying area on Day 1398.
Two sets of data were required for this study: A: Daily precipitation data of study stations on the day of heavy cloud rainfall on 21 Day (January 11, 2020) along with daily precipitation data in the days before the flood (96 hours before the flood) which was received from the main Meteorological Organization of the country.
B: atmosphere data levels including: sea level (SLP), 850 and 500 hPa levels, vertical atmospheric velocity and wind flow levels of 1000, 850 and 500 hPa, specific humidity of 1000 and 700 hPa levels and 250 hPa surface flow winds for study days from the US National Center for Environmental Forecasting / National Atmospheric Research Center (NCEP/NCAR) were provided in the range of 0 to 60 degrees at north latitude and 0 to 80 degrees at east longitude, and finally, maps were drawn and prepared in Gardes software to provide the ability to interpret.
The synoptic analysis of sea level showed that: on the day of the heavy cloud, a low-height closed center with a central core of 1,010 hPa in the northeast-southwest direction covered the entire study area. Then, the high-height with a central core equal to 1030 hPa is located at northwest of Iran, northwest of Europe and on Tibet. According to the location of high-pressure dams around Iran and the location of low-pressure centers on the study area and water resources in the south, a strong pressure has been created. Subsequently, with height increasing, low-height with central core equal to 1440 geopotential meters is located at northeast-southwest direction of entire study area. And the low height of northern Russia extends to the Persian Gulf and provides the conditions for severe ascent and instability in a very large area. The rear dams of Nave transferred the cold air of the high latitudes into the bottom of the Nave located on the study area and have intensified the instability. Also, the geopotential height of 500 hPa level of deep descent is located at the northeast-southwest direction of Iran and core of the Nave covers the Persian Gulf completely, that is the study area in the best condition and in front of the Nave, which is diverged by hot and humid weather. This deepening of the rotation and the penetration of the Nave to the lower latitudes caused the cold air to fall. 
The analysis of the 250-hectopascal-level flow-wind shows that the flow-wind with a core speed of 65 meters per second has covered the entire study area by crossing above the Persian Gulf, and compared to the previous days, the flow-wind is completely meridional.
Synoptic analysis of the vertical velocity at the level of 1000 hPa shows that the maximum negative omega -0.2 to -0.15 Pascal per second in the northwest-southeast direction has covered the study area. The presence of negative omega index values ​​indicates the role of convection in intensifying precipitation in mentioned area and the dynamic ascent of air. The study map shows that compared to other countries in the study map, the maximum of negative omega is located on Iran, which is reduced along to the west of Iran. With increasing altitude, the maximum negative omega has increased to -0.3 Pascal per second and the core of the maximum negative omega is completely located on the study stations (Zahedan and Qeshm). Then, at the level of 500 hPa, the maximum negative omega has reached -0.6 Pascal per second and its value has doubled compared to the level of 850 hPa, which covers the northeast-southwest direction from Zahedan to the Strait of Hormuz. Cold air fall has increased with increasing of omega levels in the middle levels of the atmosphere.In other words, in the middle levels of the atmosphere, with increasing temperature difference between the earth's surface and the level of 500 hPa, the amount of precipitation has increased.
Synoptic analysis of specific moisture level of 1000 hPa shows that the most moisture deposition was from south water sources to the study area, and the amount of moisture equal to 14 grams per kilogram has entered the study area from the Oman Sea and then its amount has been reduced crossing to other regions of Iran. Furthermore, at the level of 700 hPa, the maximum advection of hot and humid air is in front of the upper atmosphere of Nave from the Red Sea over the study area. There is a moisture strip from the southeast to the whole area under analysis. These suitable humidity conditions with the depth of the western wave have been able to cause heavy cloud rainfall. The maximum amount of moisture in the study area is equal to 7 grams per kilogram, which is a large amount compared to heavy rainfalls.

Keywords: heavy rainfall, flood, synoptic, Zahedan, Qeshm

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