Climate Change and Climate Disaster

Abstract The main goal of this research is monitoring of the Miankale lagoon during a period of 42 years using RS & GIS. To achieve this goal, LANDSAT satellite images and field visits have been used. RS was used to analyse findings and GIS was used to draw maps. The results show that the water sea-level condition of the bay and Miankala lagoon is strongly affected by the fluctuations of the Caspian Sea-Level. Based on the findings of the research, it was found that from 1977-1987, about 123.2 square kilometers, from 1987-1996, 1.51 square kilometers were added to the area of the wetland, which indicates the sea-level rise and erosion in the shore. However, since 1996-2003, 15.6 square kilometers and since 2003-2015, 51.8 square kilometers of sedimentation has occurred. Also, during 2015-2019, 97.1 square kilometers of sedimentation and 0.11 square kilometers of erosion have taken place. Generally, from 1977 to 2019, the amount of aridification and erosion was 164.79 and 175.36 square kilometers, respectively.

Abstract Global land-use and land-cover pattern has greatly changed in the past years, which exerts considerable direct or indirect bearing on the climate change at both regional and global scales. The purpose of this study is to analyze the impacts of land-use changes on regional climate by linking them with temperature and precipitation trend using spatio-temporal analysis and statistical method. The relationships between the observed changes in land-use and temperature parameters in Khoy from 1987 to 2017 were examined. The results showed the following features: (1) The use of built-up areas in Khoy city has increased by 19328 hectares (20.74%) in a 30-year period. (2) The trend of changes in the two temperature parameters in the period 1987-2017 in Khoy is upward and increasing, but not very upward for the average temperature. (3) There is a positive correlation between minimum and maximum temperature ranges in this city with the increase in the number of built-up areas during the study period, but the correlation for the average temperature, was negative

Abstract Drought is considered one of the biggest natural disasters, the frequency of which is very high, especially in arid and semi-arid regions. Monitoring devices are necessary tools for drought management. It is with these systems that it is possible to know the intensity and spatial development of drought, which is usually done with drought indicators. In the present study, RAI, SPI, PN and DI indices were used to quantitatively express drought and its zoning in six meteorological stations in Bushehr province. First, the meteorological data of precipitation during the statistical period of 28 years (1989-2016) were collected from selected stations. Then, each of the indicators was calculated and the severity of drought was analyzed for the statistical period. R2 coefficient of determination was used to select the most appropriate profile and finally, in order to investigate droughts, zoning maps were prepared using kriging method. The results showed that in most of the stations, the pairs of profiles have a high correlation with each other. Also, the zoning results indicated that drought zoning in all indicators does not follow a regular trend during the studied period. According to zoning, the most severe droughts related to the years (1989-1999) have been observed in Dilam, Brazjan, Chahkotah and Bushehr stations. In all stations, PN and SPI indexes show droughts better than other stations, and RAI index also shows very severe droughts better.

Abstract Investigating the distribution of thermal radiation and its relationship with the existing uses is very important in understanding the microclimate of urban areas. The purpose of this study is to monitor land use changes and its relationship with the surface temperature using Landsat satellite images during a 20-year period (1998-2018) in Bandar-Abbas city. In this study, after applying processing on satellite images and then using thermal equations and Sabal algorithm, the surface temperature of the earth was calculated for the study periods. The results show a decreasing trend of vegetation cover from 1998 to 2008 and an increasing trend from 2008 to 2018. In 1998, the amount of vegetation between (0.2 and 1) was 130 hectares and in 2008 it reached 95 hectares and finally in 2018 it increased to 115 hectares. The temperature in the northern and northeastern regions has always been higher than other regions during the statistical period, and the lowest temperature is in the south due to the presence of water and in the center of the city due to the presence of vegetation. Temperatures increased by 5 degrees from 1998 to 2008, but decreased by 8 degrees from 2008 to 2018 in the center of the city and most parts.

Abstract The useful tools for recognition of behavior of this climatic element are the statistical techniques. In this regard, in this paper, in addition the statistical tools in the trend analysis, from‌ Rotated Factor Analysis to Maximum Likelihood method is used for identification of the dominate parameter on the monthly precipitation of synoptic station of Rasht. For purpose were used from the daily precipitation data of synoptic station of Rasht in during 1961 to 2005 years. The first to the identify a precipitation regime of Rasht extracted the number of days with precipitation equal and greater than R1, 5, 10, 20,30,40,50 and100mm for each month during the 45 years. The study of decadal trend precipitation with using Pearson, Spearman and Mann Kendal was evidence the signification negative trend in the third decade in July (Tir) and in the fourth decade in March (Esfand) and the signification positive trend in the third decade in January (Day) and in the first decade in February (Bahman). Also in seasonal scale, only in the second decade of the winter was revealed signification negative trend. The results showed that two effective factors on the number of the day's precipitation in July, October, January and February are the same act. So in these months the dominance of the heavy rain can infer as the controlling factor of the number of the days precipitation and this is indicating on the separate precipitation regime in this month. The ordibehesht (May) were identified as the separate regime.

Abstract The main goal of the current research is to estimate the spatial distribution of rainfall using satellite remote sensing in the geographical area of Iran. To achieve this goal, calibrated rainfall data of level 3 version 6 of GPM satellite with a spatial resolution of 0.1 x 0.1 degrees from January 2001 to December 2019 were used for the geographical area of Iran. The results showed that in terms of monthly spatial distribution, the heterogeneous distribution of precipitation was evident. Among the rainfall zones, the highest amount of rainfall is related to the rainfall zone of the Caspian Sea coast and then the central Zagros highlands in the west of Iran. The lowest amount of precipitation was also estimated in a wide area of Iran in the central and eastern regions. The seasonal distribution also indicates a significant difference in the distribution of precipitation in different seasons of the year, so that the highest amount of precipitation is related to the winter season and the lowest amount is estimated to be in the summer season. The average rainfall in Iran is 259 mm, which varies from 189 to 344 mm in different years. On the other hand, this small amount of rainfall does not have a homogeneous spatial distribution, so that its largest amount is concentrated in the coastal areas of the north and west, and the smallest amount is concentrated in large areas of central and eastern Iran.

Abstract Hail of the most dangerous natural phenomenon, which every year with the damage to crops is unsustainable cultivation practices. Therefore, the objective of this research is to comprehensively examine the temporal-spatial distribution and synoptic conditions of this destructive phenomenon for the sustainability of agriculture. For this purpose, the statistical data 18, 25 synoptic stations (1992-2009) in the plant growing season (April to September) and a selection of 10 cases of hail and heavy rainfall-data center NCEP / NCAR synoptic maps sea level, 850 and 500 hPa, cold wind, wet wind, omega, volubility and application environment Grads drawn on the job front. In addition of local factors such as topography of the study area, the results showed that hailing systems such as west winds have been effected the highest frequency of South-West, South and center of the study area. Located deep volatile due to extremely cold weather activities have latitude westerly winds North, Mediterranean and Black on the humidity, temperature difference between the surface (due to hot, humid Frarfthay at ground level) and high levels (with front cold) and ground-level air mass could have climbed the highest frequency of hail in the spring rainfall in April is the peak.

Abstract Despite the fact that the snow masses in the snow-bearing mountains provide vital water resources for ecosystems and society, but they are sensitive to climate warming. With the occurrence of climate change in recent years, the amount of snow storage in the snow-bearing areas has decreased significantly. Snow plays an essential role in providing the world's water resources, climate and biogeochemical processes on the earth's surface. he global importance of snowfall is undeniable. Snowfall causes the earth's surface to cool. On the other hand, water from melting snow supplies the amount of fresh water needed by one sixth of the world's population. Snow also attracts tourists and strengthens the tourism industry. Recreational activities, including the skiing industry, attract billions of dollars of income during the year. The reduction of water resources resulting from snow melting has affected the amount of agricultural and garden production, as well as the volume of environmental water in the rivers. In the current research, the amount and trend of changes in the snow mass in the snow catchment areas of the Alborz and Zagros mountain ranges during a period of 42 years were studied. Zoning maps of water equivalent to snowmelt were produced using MERRA2 satellite model data and in the geographic information system environment. The results showed that the highest amount of water equivalent to snowmelt in January (14.15 liters per square meter) is observed in the central Alborz region to the northwest of Iran (Alborz) and the Zardkoh Bakhtiari region .

Abstract The present study is concerned with probing the daily average temperature behavior of 64 synoptic stations at the north west of Iran using the regression method with a 32 year (1985-2016) statistical period. The obtained results indicate an increasing trend in the average temperature of a few areas in the studied region. A negative rate in the average temperature is found during January to March and October to December. Overall, the month of March exhibits the highest significance level. In the winter, a few northern and eastern areas show the highest positive rate of temperature variation. The southern areas of West Azerbaijan and a few northern areas of the Kurdistan demonstrate greater positive rates than other spots during spring. In the summer days, the negative values are merely observed during September. Moreover, only a few cases in central and western areas in the West Azerbaijan show a positive rate of average temperature. However, different negative rates are observed during November and December in a few parts of West Azerbaijan, East Azerbaijan and Kurdistan.

Abstract Snow cover represents the amounts of water accumulated in the mountainous area. therefore, spatial and temporal monitoring of areas with snowfall potential is of great importance for predicting snowmelt, runoff and forecasting. North Khorasan province is one of the most important snowy area of the country which plays a crucial role in the feeding surface currents. So, in this study, in order to determine the areas with maximum snowfall potential, optical satellite images were used to identify the snow line and snow cover in region

. For this purpose, we used the daily production of MODIS snowcover as MOD10A2 to determine the snowcover values during 2006-2015. The above information was obtained in HDF format via FTP from MODIS Satellite Data Retention and Distribution Center, Reverb. In the following, initial processes were performed and daily surface temperature extracted. To specify the zero-degree (3-degree) isometric line, areas with the surface temperature of zero or less than zero (with 3 or less than 3) Celsius degrees were identified. Results show that, Central and Eastern half of region are the major snow-prone areas for the all three winter months (December, January and February), With the highest average of snowfall potential in January with an average of 926 pixels (230,000km2), 728 (180,185km2) in December and 569 (141,000) in February, respectively. Also the zero-degree trend line reveals the decreasing trend for January and December, while for February doesn’t show much changes. also for three-degree isotherm, the trendline shows increasing values in snow pixels.

Abstract One of the research subject in climate is study and identification of frost and its temporal and spatial distribution in each geographic region which threaten agricultural products in different parts of the world. Maragheh is located at a mountainous area of the country and it has high altitude. So, frost damages crops and horticultural plants heavily each year. The economic reliance of the people of this region upon agriculture requires the careful study of features of this phenomenon. In this research, five agro climatic indices, i.e. first fall frost date, last spring frost date, growing season (frost free season), early fall frost date, late spring frost date were considered. First, using minimum temperature data in daily scale (1984-2015), frost indices were extracted. Then, using Matlab software, among 17 probability distribution, best distribution for each frost index was determined. Results showed that Logistic, Inverse Gaussian, Extreme Value, Log Logistic distribution were identified as the best fitted distributions for first frost, last frost, early fall frost and late spring frost, respectively. Weibull was selected as appropriate distribution for growing season. Afterwards, using selected distributions in different probability levels, probable dates of the studied indices in different probability levels and return period was calculated in Matlab. It was found that every 5 year, the date of first frost and last frost will be on 7 November and 28 March. Early fall frost and late spring frost will occur on 5 November and 17 April. The length of growing season will be 201 days.

Abstract Investigating heavy metals in falling dust has important information about air pollution and its possible risks for humans. Meanwhile, the investigation of the zinc metal is very important because of its effect on the metabolic actions of the body and the structure of brain enzymes. The current research aims to determine the concentration of zinc (Zn) in the dust of Tehran city, its spatial analysis, and the calculation of the Enrichment Factor (EF) to investigate the intensity of the influence of anthropogenic factors. For this purpose, falling dust was collected in 28 stations in Tehran using Marble Dust Collector (MDCO) in the spring of 2017. XRF analysis was used to identify and determine the concentration of heavy metals. Then, the kriging interpolation model was used to determine the spatial distribution of the heavy zinc metal in the falling dust. Also, the Enrichment Factor (EF) was used to determine its pollution level. The analysis of the results showed that the prevailing wind pattern and the topographical shape of Tehran are the reasons for more dust pollution with zinc metal in the eastern areas of Tehran compared to its western areas. The results of the Enrichment Factor (EF) showed the role of human factors in this problem.