Geographic Data
Zahra Heydari monfared; Seyed Hossein Mirmousavi; Hossein Asakereh; Koohzad Raisipour
Abstract
Extended Abstract
Introduction: Snow-cover changes and related phenomena (especially depth, snow water equivalent and snow density) have a fundamental role in mountainous environments and strongly affect water availability in downstream areas. In this way, the importance of correct and appropriate analysis ...
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Extended Abstract
Introduction: Snow-cover changes and related phenomena (especially depth, snow water equivalent and snow density) have a fundamental role in mountainous environments and strongly affect water availability in downstream areas. In this way, the importance of correct and appropriate analysis is more visible. Due to the fact that most of the rainfall falls in the form of snow in mountainous areas, the management of snow resources in these areas is very important, and knowing the different aspects of variability and geographical patterns governing the phenomenon of snow is a scientific and practical need. It is considered special in water resources and in the agricultural sector. Thus, in the current research, the spatio-temporal patterns governing the annual average of snow density in different decades and the difference of each of the decades compared to the entire time period have been estimated and analyzed using spatial statistics methods.
Materials & Methods: The studied area with an area of about 151,771.91 square kilometers is located between 34°44' to 39°25' north latitude from the equator and 44°3' to 49°52' east longitude from the Greenwich meridian. In order to investigate the spatial autocorrelation changes of the average snow density in northwest Iran during the years 1982-2022 from the data obtained from the database of the European Center for Medium-Range Atmospheric Forecasting ECMWF4/ ERA5 based on daily data, and to identify and understand the spatial patterns of density Barf, based on statistical and graphic models have been used in the geographic information system environment. In the study of temporal-spatial changes of the average snow density of the region in different time periods including 4 decades ((1982-1992), (1992-2002), (2002-2012), (2012-2022)) and the whole period of 41 years (2022) -1982)), general Moran's I and Getis-Ord Gi* statistics were used. Also, in the current research, in order to investigate the effect of changes in Extreme snow precipitation on the amount of snow density in the northwest region, it has been done to determine the snow threshold. In order to estimate snow drift, a threshold was defined. Since the station snowfall amount data has a high dispersion, values above the mean cannot be accurate for defining the threshold of freezing snow. In this way, the 99th percentile index has been used to determine the snow threshold.
Results & Discussion: The aim of the current research is to investigate the spatial autocorrelation changes of the annual mean snow density in the northwest of Iran. For this purpose, the annual snow density data during the statistical period of 1982-2022 was obtained from the ECMWF/EAR5 database with a resolution of 0.25 x 0.25 degrees, and then divided into four ten-year periods. In order to analyze spatial autocorrelation changes, global Moran indices and hot spot analysis (Gettys-RDJ) were used at the significance level of 90, 95 and 99%. Also, in order to investigate the effect of extreme precipitation on changes in the level of snow density, the 99th percentile statistical index was used, and based on this index, the freezing threshold of each synoptic station in the region was determined during the last decade (2012-2022) and the interval the entire statistical period (1982-2002) was carried out. The results of the present research showed that in the studied area, snow density has spatial autocorrelation and a strong cluster pattern. With a density threshold less than 0.10 kg/m3, from the first decade to the end of the fourth decade, the area (number of pixels) and the amount of snow density in the northwest have decreased. The results of the analysis of the changes in precipitation in the 99th percentile showed that the amount of this type of precipitation has increased significantly during the last decade of the study, and this has caused the snow density to increase relatively in the last decade compared to the first to third decades. However, in general, the amount of snow density in the entire northwest area has significantly decreased during the last four decades.
Conclusion: The evaluation of the temporal changes of snow density also strengthened the hypothesis of the occurrence of freezing snow precipitation leading to an increase in snow density in the months of cold seasons during the last decade. This point was confirmed by examining the statistical index of the 99th percentile of snowy days of each synoptic station in the region during the last decade (2009-2018) compared to the entire period of station statistics (2000-2018). The results of the analysis of the changes in precipitation in the 99th percentile showed that the amount of this type of precipitation has increased significantly in the last decade of the study and this has caused the snow density in the last decade to increase relatively compared to the first to third decades. However, in general, the amount of snow density in the entire northwest area has decreased significantly during the last four decades. Moran's statistic was used to explain the pattern governing snow density in northwest Iran. The results of Moran's index about the annual average of snow density showed that the values related to different time periods have a positive coefficient and are close to one, which indicates that the snow density data has spatial autocorrelation and has a cluster pattern. Also, the results of standard Z score and P-value confirmed the cluster significance of the spatial distribution of snow density in the northwest. Finally, the analysis of hot spots has been a clear confirmation of the continuation of concentration and clustering of snow density in northwest Iran in space with the increase of the time period, which mountainous areas have the first rank in the formation of hot clusters with a probability of 99%. have given.
Omid Reza Kefayat Motlagh; Mahmood Khosravi; Sayyed Abolfazl Masoodian
Abstract
1-Introduction The sun is the primary source of energy and life for Earth, and without solar radiation, there will be no atmospheric and climate processes on the Earth. Animal, human and plant life on the Earth depend on the energy received from the sun. Shortwave solar radiation is very important, due ...
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1-Introduction The sun is the primary source of energy and life for Earth, and without solar radiation, there will be no atmospheric and climate processes on the Earth. Animal, human and plant life on the Earth depend on the energy received from the sun. Shortwave solar radiation is very important, due to its role in biological processes, especially photosynthesis and human life. Outgoing Long Radiation (OLR), which is the result of heat reflection from the Earth’s surface, plays a vital role in the thermal balance of the Earth with regard to the presence of greenhouse gases. Part of the OLR goes out through atmospheric windows, but a large part of it is returned to the Earth by greenhouse gases, and plays an important role in the Earth’s thermal balance, especially during nights and in winters. Estimating Outgoing Long Radiation (OLR) is very difficult and remote sensing can be used to evaluate OLR on a planetary and regional scale. The purpose of this study is to examine long-term average of outgoing longwave radiation (OLR) over Iran using data received from the Iranian National Center for Oceanography and atmospheric science. Solar radiation is one of the most important parameters affecting the Earth atmosphere thermal balance (Isoman and Mayer, 2002). It also forms the basis for most of climate studies, because the process of evapotranspiration depends on the amount of available energy for evaporation (Alan et al, 1998). Since 99.8 percent of the energy at the Earth’s surface comes from the sun, the effect of solar radiation on evapotranspiration has been of great interest to researchers working in the field of agricultural science, especially irrigation sciences (De Souza et al, 2005). Some studies have used OLR trend to explore feedback and climate processes (Chu and Wang, 1997; Suuskind et al, 2012). Chuudi and Harrison studied El Niño’s impact on seasonal rainfall, temperature and atmospheric cycles’ anomalies in the U.S. using OLR. In another study, they have also estimated global seasonal rainfall anomalies related to El Niño and La niña using OLR (Chiody and Harrison, 2013, 2015). Knowing the amount of solar radiation in different locations is important for many practical issues such as estimating evapotranspiration, architectural design, agricultural products growth models, and etc. (Moradi, 2005; Alizadeh and Khalili, 2009; Mousavi Baygi et al, 2010). Considering the importance of climate change effects on the fluctuations of short wave and long wave radiations from the Earth surface and its relation with regional climate, research on this issue seems necessary. Since this issue has been underestimated in our country, and most researchers have only tried to find different coefficients and equations for estimating received solar radiation based on other meteorological parameters, making previous sporadic studies and researches on outgoing longwave radiation changes over Iran and other parts of the world applicable seems to be necessary. 2- Materials & Methods In this study, HIRS satellite data were used to analyze long-term average of OLR on planetary and regional scale. NOAA satellites were launched by the National Oceanic and Atmospheric Administration of the United States. The latest satellite in these series (version 19) was launched in February 2009. This polar-orbiting satellite circles the Earth from the North Pole to the South Pole 14 times a day. This allows NOAA-19 to observe the whole Earth twice every day (NOAA website). Since the purpose of the present study is to examine long-term average of outgoing longwave radiation over Iran based on data received from NOAA, daily OLR averages were retrieved from the CDR database with 1 arc degree resolution on a global scale for the period 1/1/1979 - 12/29/2016. Then, Iran long-term average of OLR and also its global average were calculated based on nearly 1 billion cells. The Gi* analysis method was also used to study the spatial distribution of outgoing long wave radiation over Iran. Since data received from outside Iranian territory were also included, we used “In polygon” function in MATLAB software to extract data specific to geographic borders of Iran. 3- Results & Discussion After calculating long-term average, results indicated that maximum OLR occurs between 30˚ north and south latitude, especially over the Middle East and North Africa, which is due to the radiation angle and ground cover. Results also showed that long-term average of the OLR was 222 W/m2. However, the mentioned areas have a reflection of more than 280 W/m2. Maximum OLR (289W/m2) occurs over Rub’ al-Khali desert and minimum OLR occurs over Antarctic glaciers (126 W/m2). These two points are one of the warmest and coldest areas on the Earth, respectively. They also have different ground cover. Therefore, it is natural to have a 173 W/m2 difference between the highest and lowest outgoing long-wave radiation over the Earth. Regional scale findings indicated that long-term average of OLR over Iran is 265 W/m2, which is 43 W/m2 (19 percent) higher than the global average. Results also showed that maximum OLR occurs to the west of Poshti region in Konnak city, Sistan and Baluchestan province (289 W/m2), and minimum OLR occurs over Ararat mountains in north-west Iran (approximately 235 W/m2). This 50 W/m2 difference is due to different latitude and altitude of these locations, which shows the significant role of temperature in the amount of outgoing long-wave radiation. 4-Conclusion Findings indicated that average global OLR is 222W/m2 and maximum reflection over the Earth surface occurs between 20˚ north and south latitude. This is because the average reflection between these latitudes reaches 270 W/m2, which can be attributed to the proximity of Tropic of Cancer and Tropic of Capricorn. Findings also showed that average long-wave radiation over Iran (264 W/m2) is %19 higher than the global long-term average. Although, maximum global OLR occurs in Rub’ al-Khali desert in Saudi Arabia (299W/m2), Iran is also considered to have a high level of OLR due to its geographic location and limited ground cover. With a reflection of more than 280 W/m2,vast regions in southern Iran are considered to have excessive energy and thus play an important role in environmental warming. Spatial analysis of hot and cold spots concentration patterns (above 90% level of confidence) showed that nearly 40 percent of Iran is considered to be hot spots, 17 percent neutral and 43 percent cold spots, the pattern of which is affected by difference in latitude and ground cover.