Synoptic analysis of the systems due to Sudan low during the historical process of May in the south and southwest of Iran
Fahimeh
Mohammadi
Shahid Beheshti University
author
Hassan
Lashkari
Associate Prof. Shahid Beheshti University
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text
article
2020
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Introduction The Sudan low pressure is regarded as a system influencing the rainfall during the cold season, in the South and Southwest of Iran. Often in the cold season these systems have crossed Ethiopia, Sudan, and the Red Sea and then on its way entered the country from the south and southwest of Iran and it is causing rain in these areas. According to El-Fandy (1948), the history of recognizing the Sudan low in the Middle East and the Red Sea region goes back to about 80 years ago when Ashbel (1938) first described the eastern Mediterranean rainfall. Ashbel concluded that the rainfall in the area was affected by a system which he called the “Red Sea low pressure”. Based on the evidence, Olfat (1968) was the first one who studied Sudan low in the context of Iran. Olfat refers to low pressures which are formed in northeastern Africa and the Red Sea and then pass Saudi Arabia and the Persian Gulf, and finally, enter Iran and cause rainfall. The purpose of this study is the Investigation of dynamic fluctuations of Sudan low In May rainfall performance over the course of 60 years. Materials and methods The study period is from1957 to 2017. May was considered as a symbol of the poor performance of the Sudan low in the south and southwest of Iran (Lashkari & Mohammadi, 2019). The study period with long-term variations was considered from 9.5 to 11 years based on solar cycle. In this regard, the daily precipitation data of 42 stations of the south and southwest of the country were prepared by the Meteorological Organization of Iran. Rainfall days were extracted in May using the daily rainfall data of 42 synoptic stations. For these days, sea level pressure (SLP) and geopotential (hgt) data at 1000 hPa with 2.5 × 2.5◦ spatial resolution were obtained from the dataset of NCEP/NCAR reanalysis project. Additionally, the frame of the reference was provided in 0-100◦ E and 10-55◦ N latitude belt in GrADS software. The visual analysis of high and low altitude cores and geopotential height at 1000 hPa pressure level (El-Fandy, 1950a; Lashkari, 1996; 2002) were considered based on the aim of the study. Accordingly, the approximate locations of activity centers, as well as the range of the formation and displacement of the Sudan system were initially identified based on the location of the formation of low and high-pressure cores. Then, the rainy days due to the Sudan system in May were separated from the precipitation of the other atmospheric systems (i.e., Sudan-Mediterranean and Mediterranean systems). For these days, SLP, hgt, specific humidity, zonal and meridional wind data at the levels of 1000, 850, 700, and 500 hPa with 2.5 × 2.5◦ spatial resolution were obtained from the NCEP/NCAR dataset. Using the GrADS software, the numerical values of these parameters were calculated at synoptic stations with the highest statistical data over six decades. In addition, for the sum of the days of Sudan low rainfall in each decade, the daily composites of the anomalies of these variables were provided from NCEP/NCAR dataset. Results and discussion Analysis of sea level pressure changes Examination of sea level pressure (SLP) revealed that during the first to sixth decades SLP has declined relative to its long-term average in southwestern of Iran (-1 to -3 hPa). But in the south of Iran during the first to second decades, the SLP decreased slightly and remained constant in the third decade and then increased during the fourth to sixth decades (+1 hPa). Analysis of Geopotential height Changes Examination of Geopotential height (hgt) changes over the level of 1000hpa to the 500hpa showed that the height of the Sudan low was reduced Compared to its long-term average, during the first decade to the sixth decade in southwest of Iran but the size of its hgt reduction, was reduced from the first decade (-70 m) to in the sixth decade (–30m). The height of the Sudan low was decreased from the first decade to the third decade in the southern part of Iran (-10m to -30m). But the height of the Sudan low was increased during the fourth to sixth decades (+10 to +15 meters). Analysis of specific humidity Changes Examine the specific humidity (Shum) values at 1000,850 and 700hpa showed that moisture change was reduced during the first to the second decade in southwestern Iran (about 2 gr/kg), and it was constant with a slight swing from the second decade to the sixth decade (4 gr/kg). In the south of Iran Shum status was accompanied by decreasing and increasing with a swing during the first decade to the third decade and it was almost fixed from the fourth through the sixth decades (2.5-3 gr/kg). Specific humidity values increased to some extent at 850 and 700hPa during the last decade. Analysis of vector wind and vorticity Changes Survey of vector wind and vorticity at 850hpa level showed that Sudan Cyclone deployed in northeast Saudi Arabia and the southern coast of the Persian Gulf and on other hands, Anticyclone (Arabian subtropical High Pressure) Stationed on southern Iran. So during the decades of climate, the Barotropic and Baroclinic Atmosphere is ruler on the south and southwest of Iran, respectively. Conclusion The purpose of this study was to investigate the performance of a compressive structure, humidity and other dynamic parameters of systems due to Sudan low in May of south and southwest of Iran. The climate decades were regulated by solar cycles over 60 years (1957-2017). The results made it clear that changing the dynamic parameters of Sudan low system has strengthened and weakened in the southwest and south of Iran respectively, over the decades. Also, Investigation of the average of decidedly precipitation rate due to Sudan low showed the values of rainfall in May, increasing in the south and southwest of Iran over the past decades until now in a long historical trend. Keywords: Sudan low- solar cycle-Anomaly-south and southwest of Iran.
Journal of Climate Research
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https://clima.irimo.ir/article_126016_dd12dbb5f3841ca9d25281a3c44dc1ff.pdf
Evaluation and comparison of the accuracy of the CORDEX database's summer precipitation network data with station data
(Case study: summer precipitation of South East of Iran)
Mohammad Reza
Salari Fanoodi
PhD student of Climatology, University of Sistan and Baluchestan, Daneshgah Ave., Zahedan, Iran
author
Mahmood
Khosravi
Professor, Climatology, Department of Physical Geography (Climatology); University of Sistan and Baluchestan
author
Taghi
Tavousi
Professor, Climatology, Department of Physical Geography (Climatology); University of Sistan and Baluchestan
author
Mohsen
Hamidian Pour
Assistant Professor, Climatology, Department of Physical Geography (Climatology); University of Sistan and Baluchestan
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text
article
2020
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Introduction
South East of Iran will yearly receive part of its water requirements from the summer precipitation, which is mostly due to the monsoon expansion. These precipitations are related to the temperature changes in the Indian Ocean level (Aramash et al., 2016: 2). Producing the accurate climate data is one of the main goals of the forecasting and modeling centers. Among the most important advantages of this data can mention the following: better estimation of the climatic variables in the regions which have no station, possibility to study the climate more appropriately and evaluate the fluctuations and changes of climate elements (Forsythe et al., 2015).
Data and Methods
In this research, we used daily precipitation data of 6 synoptic stations and the outputs of various CORDEX models in the South Asia during the statistical period of 30 years (2005-1976) in the studied region.
Results and Discussion
Evaluation of the accuracy of the global models' output on the basis of the downscaling of the studied regional model on a daily basis during the monsoon period (June, July, August and September) in (1976-2005) indicated that according to the different indicators the CanESM2, CSIRO and NorESM1 models have respectively more accurate estimation of precipitation values at most studied stations than other models. The correlation coefficient of none of the models has a good relationship. The observed and estimated precipitation values of the studied models in the form of the average activity months of the monsoon system showed the accuracy of the investigated models at each station is different but, in general, the three models CanESM2, CSIRO and NorESM1 are more appropriate in the estimation at the most stations than other models. A number of macro criteria must be considered to select the proper model; the 500 HPA Geo-potential height and the sea level pressure have been used in this research for this purpose. In fact, investigating the model's ability to simulate the 500 height as well as the earth is preferable over precipitation and temperature.
Conclusion
The results have suggested that the accuracy of the studied models at a variety of stations is different but, totally and at most of the stations, the three models CanESM2, CSIRO and NorESM1 have respectively better estimation of monsoon precipitation values than the other models. We cannot definitely prefer one model over the others according to the error estimation criteria as well as the comparison of different models with each other. We have shown in this research that the large scale variables such as Geo-potential height and pressure are more predictable than the precipitation and CanESM2, CSIRO-Mk, IPSL-CM2A-MR, MIROC2 and MPI ESM-LR models can be introduced as suitable models to simulate and predict climatic parameters of sea level pressure and 500 HPA Geo-potential in the monsoon system activity governing on the South East of Iran.
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https://clima.irimo.ir/article_126017_1bf6d34059eab1923dc5176edf4a1ddd.pdf
A review on the Mechanism and synoptic patterns of the Red Sea Trough (RST) and its effects on Iran's precipitations
Ghasem
Azizi
Associate Professor in Physical Geography(climatology),Faculty of Geography,University of Tehran
author
Elaheh
Ghasemi Karakani
Ph.D. Student, University of Tehran, Iran
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Naser
Ezadi
Ph.D. Student, University of Tehran, Iran
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text
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2020
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1- Introduction The RST is a large-scale subtropical–tropical thermal low-pressure and synoptic system regarded to an extension of the African monsoon trough, northward over the Red Sea region toward the Eastern Mediterranean (El-Fandy 1948; Vries et al, 2013). The RST is attributed to the local topography and thermal forcing factors (Krichak et al., 1997a). Synoptically, the position of the RST is strongly influenced by the Siberian and Azores high systems (Baseer et al., 2019). The RST is associated with hot and dry weather, resulting from an East-Southeasterly flow in the lower troposphere. Such conditions correspond to a ‘‘nonactive’’ RST (Kahana et al. 2002). In some cases, the RST is investigating to be accompanied by an upper-tropospheric trough extending from the north over the EM. These conditions are associated with unstable stratification, favoring the development of mesoscale convective systems. This kind of RST has been defined as an ‘‘active’’ RST (Tsvieli and Zangvil 2005). ARST events usually lead to reasonably intense precipitation over the eastern Mediterranean; in some rare situations, they are associated with heavy, torrential rains and devastating floods. It can occur in late autumn and to a lesser incidence in early winter and spring. The ARST is a rare climate phenomenon that is the main cause of floods in the arid and semi-arid region of eastern and southern of Mediterranean (Kahana et al. 2004; Krichak et al., 2012; Vries et al, 2013). Some researches show the ARST preference for autumn by coinciding favorable latitudinal positions of the African Monsoon and the subtropical jet (STJ) stream (Dayan et al. 2001). Based on Conceptual model of ARST and algorithm for its identification by Krichak et al., 2012, According to the new algorithm for ARSTs, the occurrence of ARST events is defined to have taken place when:The CAPE or PRWT exceed particular threshold values over a target area that covers the EM (28°–32°N, 32°–38°E). 1) A northward-oriented 1000-hPa trough (H1000) extends from northeastern Africa to the EM within a target area of (22.5°–32.5°N, 25°–45°E). 2) A mid-tropospheric 500hPa trough is detected over one of the following two target areas (25°–30°N,158–35°E or 30°–35°N, 25°–40°E). The ARST is associated with extreme precipitation, in the Middle East (ME) and some region in the west and southwest of Iran. Generally, it causes flood events in some years, many studies, focused on these cases and most of them explained western cyclones and RST are the main cause of them. On 25 November 2009, Jeddah (Saudi Arabia) was dramatically hit by heavy precipitation and consequent flash floods and on 21 November, 2011this event occurred in Lilac-Behbahan. In this research attempted extract difference between these two ARST synoptic patterns also, we review previous literature addressing ARST associated dynamics. Data and Methods We tried to investigate the extreme precipitation events over the Jeddah region on 25 November 2009, southwestern Iran (Lilac-Behbahan) on 21 November 2011. To perform this research, we used ERA-Interim reanalysis data and precipitation observations. 6-hourly gridded data from the multiyear dataset of the European Center for Medium-Range Weather Forecasts (ECMWF- ERA-Interim) are employed for 2009 and 2011. We utilize the daily mean and 6 hourly analysis and forecasted variables at pressure and surface levels, as well as vertically integrated quantities derived from pressure levels. The ERA-Interim data are available for the entire globe with 0.5˚ * 0.5˚ spatial resolution and 6-h temporal resolution. Precipitation observational data from stations of Iran are collected from Meteorological Organization and data of 30 stations of Saudi Arabia are available via http://www.meteomanz.com. We followed these ARST events by these dynamical factors (de Vries et al., 2013): 1) A low-level trough; the Red Sea Trough (RST). 2) An anticyclone over the Arabian Peninsula; the Arabian Anticyclone (AA). 3) A transient midlatitude upper trough. 4) An intensified subtropical jet stream. 5) Moisture transport pathways, and 6) Strong ascent resulting from tropospheric instability and the synoptic-scale dynamical forcing. 2- Result and Discussion The result shows the spatial extent of Arabian Anticyclone is one major reason for the distribution of precipitation in Saudi Arabia and the southwest of Iran. Also, the position of the axis of upper trough and its rotation is another reason and it's oriented to lower latitude, as whatever southward leading of upper trough to lower latitude is greater and wavelength of the trough is more, accordingly, the possibility of precipitation increased in Saudi Arabia. Moreover, the location of a stream jet can be effective on extreme precipitation. On the other hand, a streak of subtropical jet extended southeast of upper trough, and this status is so significant.
Journal of Climate Research
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https://clima.irimo.ir/article_126018_dab79740a179f2e186052a098642af16.pdf
The Representation of Climate Variability researches in Social Media: A Scientometric and Altmetric analysis
forough
rahimi
Regional information center for science and technology, Shiraz, Iran
author
Nosrat
Riahinia,
Prof. of Knowledge and Information Science, Kharazmi University, Tehran, Iran
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HamzehAli
Nourmohammadi
Department of Knowledge & Information Sciences, Shahed University, Tehran, Iran
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Hajar
Sotudeh
Department of Knowledge & Information Sciences, School of Education & Psychology, Shiraz University, Shiraz, Iran
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, Gholamabbas
Fallah
Geomorphology & Meteorology Department, Faculty of Geography & Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
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2020
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Introduction: Considering the development of social web, its capacities in publishing research findings, researchers’ tendency in utilizing social web to increase their visibility, beside the importance to answer the question of how to measure the research social impact, the present study attempts to provide new insights into the amount of scientific and social users' attention to climate variability articles and do co-occurrence analysis of the key terms. This is to provide scholars with a knowledge visualization in the field and help them identify central or neglected issues. Materials and methods: The current applied research was conducted through altmetrics method along with the use of co-word analysis. The climate variability articles analyzed using descriptive and analytic statistics in Excel, VoS viewer and SPSS version 20. Results and discussion: The results showed that a number of 2755 articles in the field received 89129 citations over the past 41 years. The most cited article published in 2000, received 1458 citations. The growth rate of the publications in the field was 2366 percent with the largest number of annual publications in 2017. The United States, China and Germany contributed the largest number of articles, respectively, while Iran ranked 43. From among 2556 articles with DOIs, a number of 1447 items were available from Altmetric explorer and received a total of 8832 social citations in 14 social Medias. Mendeley (92358 reads) and Twitter (6480 tweets) were the most used social media, respectively, followed by news outlet, blogs, and policy documents. The most active users of Twitter, Facebook, news media and policy documents are from the US. The altmetrics attention score of the most influential papers is 651 and for an Iranian paper was 82, published in 2016 and 2015 respectively. Spearman test showed that there was a significant though weak relationship between citation and altmetric score. The most productive, most socially and academic cited subject categories was multidisciplinary sciences. Visualizing climate variability articles revealed that sea surface temperature, global warming, southern oscillation, and El Niño were the most frequently used key terms in the articles. Conclusion: The value of this research lies in providing a picture of four decades of research in the field and in the clarification of the extent to which social network users pay attention to climate variability issues and how much is the power of altmetrics in showing the impact of science on society and research evaluation.
Journal of Climate Research
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https://clima.irimo.ir/article_126019_f91e4b4109204e1e3fd39f18c9b98748.pdf
Thunderstorm simulation using WRF model in Kermanshah Case Study: March 31, 2014
Ali mohammad
Khorshiddoust
Professor of Climatology- Department of Tabriz University
author
Mehdi
Asadi
Hakim Sabzevari University
author
Hassan
Hajmohammadi
Hakim
author
text
article
2020
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To study the atmospheric structure at the time of Thunder storm occurrence in Kermanshah province, were used the transmitted codes from synoptic stations of the province. To study the atmospheric structure, the sea level pressure parameters, geopotential heights, specific humidity, Uwnd and Vwnd were obtained from the NCEP / NCAR Web site, and Radio sonde data was used for intermediate studies. To illustrate this phenomenon, the WRF model was used with a resolution of 15 km. Finally, in order to evaluate the model output in the rainfall section, the estimated rainfall values of the TRMM sensor. The results showed that the cold weather and the formation of a deep cave on the west of Iran, the emergence of severe pressure gradient in the northwest and west of the country and the formation of a cold front in the region, were the main synoptic factors during the storm. Also, the role of the Arabian Sea, Red Sea and Persian Gulf can be mentioned in providing rain water resources. On the other hand, extreme climbs of the air have played a major role in the formation of bubble clouds and hailstones. The review and evaluation of the WRF model output (Estimated precipitation is 18 mm) and TRMM sensor (Estimated precipitation is 19 mm) compared to reported rainfall from stations (Estimated precipitation is 17 mm) showed that this model with RMSE=1 mm is suitable for exploring the structure of atmosphere in the region to dynamically visualize intermediate scale phenomena such as thunder storms. Keywords: Thunderstorm, Synoptic, WRF model, TRMM sensor, Kermanshah province. Introduction Thunder storm is one of the most important, most abundant and most severe atmospheric hazards that due to its combination with rainstorms, hail and lightning, its effective role in creating sudden floods, both in terms of agriculture and in terms of financial and life damage, this phenomenon has always been of interest to researchers. Hail from grains or pieces of ice with a diameter of 5 to 50 mm and sometimes more. Hail intensive growth is the result of intense and frequent vertical movements of the air in the clouds of the cumulonimbus, which causes hailstones to absorb water droplets around them and freeze them. Creating and hailing, the presence of hot and humid air at the bottom of the atmosphere and climbing clouds accumulated with high altitude and high temperature combined with the continuation of the conditions of maximum instability of the air. Because of the importance of the hail event, studies have been conducted on its formation and growth in different countries in order to anticipate them. This can be cited by Sterling (2003) Prosenjit et al. (2008) by Litta et al. (2012). Materials and methods WRF model The Advanced Modeling System (WRF) is an interdisciplinary and flexible model with many capabilities that can be used to simulate different atmospheric conditions. This model has been developing over the past few years, the model is available on a variety of computer systems, including a computer cluster, its range is very wide and covering a range between several meters to thousands of kilometers and by varying the different modes of physical parameters in the model, a wide range of performances can be achieved. In the course of this investigation and to simulate real thunderstorm was used from version 3.8 Medium scale WRF model. For this purpose, the network was considered with a horizontal resolution of 15 km with a moderate resolution in a network with dimensions of = 316x, = 451y. Also, FNL-type data were used with a one-degree separation as three hours. Discussion and results In Fig. 2, the arrangement of pressure patterns is such that a high pressure masses with a central pressure of 1016 hPa in the south of the Black Sea causes an hourly flow to occur in this region. On the other hand, in central Iran, a low-pressure cell with a central pressure of 1004 hPa has caused pressure gradient on the country. With an increase in the pressure gradient of about 12 hPa, a fracture in the pressure lines in the south of the Caspian region has occurred, which continues to the west of Iran. The formation of the fronts with extreme high currents has made it possible to provide conditions for incidental precipitation and thunderstorms in the region. On the other hand, in the middle of the atmosphere and on the west of Iran, the cold weather of the troposphere with the loss of geopotential has led to an ever-increasing upturn in air and instability. With 5450 geopotential meters placed on the area, a very powerful rotating core has affected all of the western and northwest regions of the country. This cold weather has caused the formation of a cold front in the region resulting in heavy rains and heavy storms along with hail in the area. Conclusion The results showed a high pressure masses with a central pressure of 1016 hpa in the south of the Black Sea, causing an hourly flow in this area. . On the other hand, in central Iran, a low-pressure cell with a central pressure of 1004 hPa has caused pressure gradient on the country. The model output also showed the highest positive vortices in the mid-range in the Iraq-Turkey region, which includes another core of the south-west. The existence of instabilities at all levels in the western regions has caused the conditions for storms in the region. The results of the total precipitation also showed that by eliminating the initial 6 hours of the output of the model, the maximum changes and the region's potentiality from the atmospheric systems referred to the east of Kermanshah province. Therefore, it is needed to demonstrate this phenomenon from the previous day and use more hours to explain the behavior and structure of the Thunder storm in the WRF model. On the other hand, it can be pointed out that simultaneous use of satellite data and dynamic model can be a good way to monitor and predicting thunderstorms with hail.
Journal of Climate Research
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https://clima.irimo.ir/article_126020_326aef9373e420394cb2f74ee5787828.pdf
Study and evaluation of dust emission scheme in WRF-Chem model of duststorm in the east and southeast of the Iran (Case study 11 to 13 August 2018)
Mohammad
Asghari
Department of Earth Sciences, Islamic Azad University, Science and Research Branch, Tehran, Iran
author
Amirhossein
Meshkatee
Professor of Islamic Azad University, Science and Research Branch
author
Abbas
Ranjbar
ASMERC
author
Mohammad
Moradi
Associate Prof. of Atmospheric Science and Meteorological Research (ASMERC), Tehran
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2020
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Since dust phenomenon has become one of the major problems in many parts of the world, a large number of models have been developed in order to predict the concentration of dust particles in the atmosphere. In the east and southeast of Iran, the occurrence of dust phenomenon causes severe financial, human and environmental losses every year. Therefore, accurate forecasting in order to provide the necessary warnings can reduce the damage as much as possible. From 11 to 13 August 2018 the report of the current weather code 07, 30, 31 and 32 in the synoptic stations of southeastern Iran, including Zabol, Zahedan, Nehbandan and Iranshahr, indicates the occurrence of storms and the horizontal visibility of the region during the storm occurred less than 1000 meters. In this study, ERA5 (ECMWF) reanalysis data set was used to obtain the required fields including sea level pressure, geopotential height, temperature and relative vorticity at 500 hPa, and geopotential height and temperature at the 850 hPa level. The vertical cross section of the wind speed from the ground level to the level of 400 hPa along with the vertical velocity are also plotted and analyzed for latitude 31 degrees north and longitude 53 to 63° E. Moreover, weather research and forecasting model coupled with chemistry (WRF-Chem) with three emission schemes, GOCART, AFWA and SHAO1,SHAO2,SHAO3, were used to simulate the dust load and amount of particulate matter (PM10) and its transportation over the studied region. The initial and lateral boundary conditions of the model simulations are provided by Global Forecast System (GFS) data with the horizontal resolution of 0.5°. Atmospheric pattern analysis shows that during the storm (120-day winds in warm season), with high pressure around the Caspian Sea and Turkmenistan and on the other hand intensified seasonal thermal low pressure on the southeast of Iran, India and Pakistan and cool air advection from the north and then strong gradients of temperature and pressure lead to strong winds. Storm simulations showed that the implementation of the model clearly showed the beginning of dust from the southeast and its emission to the east. In general, the output of the model in terms of scale and temporal variations gave a reasonable estimate of dust particles in the study area. The AFWA and GOCART emission schemes of the WRF-Chem model simulate very similar the emission source and dust storm concentration changes of 11 to 13 August 2018. However, the simulation results of SHAO schemas, especially SHAO1 and SHAO2, are completely different and have a significant error. Quantitative comparison of the model output for different emission schemas with the observational data of Zabol station shows that the AFWA scheme simulated the dust concentration more than the observations, but the trend of its changes is acceptable. The dust concentration predicted by the GOCART scheme is lower in quantity than observed. Simulation of hurricane dust particles in eastern Iran, Zabol region, Zahedan and southern regions of Kerman and Sistan and Baluchestan province (Kahnooj, Regan, Nikshahr and Qasrgand), Zahedan, Zabol (consecutive report weather code 07 of these stations) and east part of Hormozgan porivence (Jask and Minab) as the main source dust of the region. In terms of compliance at the time of the occurrence of severe dust, it has an acceptable compliance with the PM10 data of Zabol station. The simulated concentrations showed good validity of the temporal and spatial distribution of dust concentrations with respect to satellite RGB images and observation data. Synoptic analysis in the warm season indicates the presence and intensification of seasonal thermal low pressure in Pakistan, Afghanistan and east and southeast of Iran and on the other hand high pressure in Turkmenistan in the north of the Caspian Sea and in the cold season of Siberian high pressure and dynamic low pressure in eastern and southeastern part of Iran. The activity of low-level jets (severe northern currents) near Zabol region and alternating vertical motion are other effective factors in the instability of the region and the occurrence of dust storms and have provided favorable conditions for dust formation. The dry bed of Lake Hamoon, the low rainfall of recent decades, is also a very important factor in the occurrence of dust in east and southeast of Iran.
Journal of Climate Research
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https://clima.irimo.ir/article_126021_5cf050ab8ebc50adf71430c5d93ac09e.pdf
The PM2.5 estimations over Tehran Using Remotely Sensed Aerosol Optical Depths Data
Amir Houshang
Ehsani
School of engineering, College of Engineering, University of Tehran, Tehran
author
Mostafa
Bigdeli
School of Environment, College of Engineering, University of Tehran, Tehran, Iran
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text
article
2020
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Introduction One of the major air pollutants, in particular particulate matter (PM) with an aerodynamic diameter of less than 2.5 microns (PM2.5), remains as a pervasive problem in spite of outstanding efforts to reduce and control it. Satellite-based measurement is used in many studies. A commonly used satellite product to estimate the ground concentration of PM2.5 is aerosol optical depth (AOD). AOD is an optical measurement method that describes the frequency of aerosol and their extinction factors in an integrated column in the atmosphere, which is commonly obtained from satellites and ground instrumentation. Regression statistical methods such as simple linear regressions to complex multivariate regressions (including boundary height elevation, temperature, relative humidity and wind) have been used to establish a relationship between AOD and PM2.5 in literature. In particular, the Advanced Sensor MODIS is used to obtain aerosol optical depth on a global scale for long-term. Many studies have been using MODIS AOD products to achieve particulate matter concentrations. The purpose of this study is to estimate the annual mass concentrations of PM2.5 particles using regression and satellite data, investigate the seasonal variation trend of the aerosol optical depth on Tehran and the concentration of PM2.5 particles measured by the air quality monitoring station of the Air Quality Control Company during one year. Materials & Methods The amount of PM2.5 concentration in Tehran in recent years, especially in the late fall and early winter, is in many cases above the standard limit, which sometimes provoked a warning and even a dangerous situation. In this study, the MOD04_L2 product (Collection 6.1 level 2) of MODIS on the Terra satellite at 550 nm (https://worldview.earthdata.nasa.gov) with spatial resolution 3 × 3 km was used. AOD data were retrieved from 8:30 to 10:30 (corresponding to 12-14 local time) for a one-year period (from 22/6/2017 to 21/6/2018). By extracting the AOD values for Tehran (and also extracting the same latitude and longitude optical depths as well as each ground air pollution measurement station), the amount of daily optical depth of each station was determined. In this study, PM2.5 mass concentrations (in micrograms per cubic meter) were used which measured by the BAM device at the Air Quality Control Company (AQCC) stations for the one-year period. It should be noted that the 12 to 14 measured concentrations were used to correspond with the satellite's time from the study area. The rest of the monitoring stations of the air quality control company had not any data during the study period. Also, by using an Inverse Distance Weight (IDW) method at a 12 km radius around each air pollution monitoring station, the concentration of PM2.5 was predicted in other parts of Tehran without a station. AOD and PM2.5 daily data (during the one-year period) were used to determine regression relations for each station. In this method, which was applied independently to each of the stations, the data for one month were discarded from each station, and the regression equation was established between the remaining 11 months data. Then, the PM concentration values for the separated moon were predicted by the obtained regression relationship to determine the ability of the relationship to estimate the concentrations that were not used in the regression equation. Finally, the annual concentrations of each station were obtained by averaging the estimated daily values. This operation was repeated for all stations individually to predict the average annual concentration of particulate matters in all stations. It should be noted that for determining the regression equations for each month (at each station), the AOD and PM2.5 data were used when the two parameters had a value. Results and Discussion The annual AOD value of the total stations with average of 0.23 and standard deviation of 0.01 varied from 0.20 to 0.25, which was the highest average (0.24) for the autumn between all seasons. Also, the maximum and minimum values of AOD (0.29 and 0.06, respectively) were related to spring. The PM2.5 annual concentration of all stations with a mean of 27.09 μg/m3 and a standard deviation (SD) of 5.16 ranging from 20.10 to 36.14 μg/m3, which was the highest average among the seasons (34.95 μg/m3) in fall. The highest (71 μg/m3) and the lowest (4.33 μg/m3) PM2.5 measured concentration were for autumn and spring, respectively. The maximum average amount of AOD and PM2.5 data measured (among all stations) was related to fall. As stated above, the average annual PM2.5 concentration was predicted for areas in Tehran without a station using an IDW interpolation method at a 12 km radius around each air pollution monitoring station. Accordingly, the areas around the stations Aqdisiyeh, Municipality of District 2 and Golbarg with a concentration of up to 22 μg/m3, had the lowest concentrations (due to higher altitudes than other stations and the probability of having higher wind speed and precipitation rates) and the areas around the stations Shad Abad, Sharif University, Municipality of District 11 and Sadr Highway (up to 36.14 μg/m3), which may be due to the heavy traffic of vehicles from this highway or to carry out bridge repairs had the highest average annual concentration of PM2.5. As described before, regression equations were obtained between AOD and PM2.5 data for each month at each station. Then, by placing the AOD data in the equations, the PM2.5 concentrations were estimated. A good correlation was observed between the mean annual values of measured and estimated PM2.5 of stations with a high correlation coefficient (R2 = 0.99). Conclusions Considering the acceptable ability of the regression method to estimate the average annual concentration of particulate matters, it can be used for areas with similar topographical, climatic, stationary and moving pollutant sources (including desert, semi-desert areas and having heavy traffic) conditions. In order to accelerate the prediction (with acceptable accuracy) of the average concentration of PM2.5, the use of satellite remote sensing can be an economical and low cost alternative in comparison to ground pollution monitoring stations, which are usually dispersed and located far from each other.
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https://clima.irimo.ir/article_126022_c19533bbcfb05422309bf0b546aff877.pdf
Investigating the Effect of Climate Change on the Quality of White Seedless Grapes (Case Study: Golmakan Agricultural Weather Station)
Ahmad
Alizadeh
Environmental Sciences Department-Grape and Grape Research Institute-Malayer-Iran University / Expert-Pathologist of Northern Khorasan-Iran
author
Iman
Babaeian
پژوهشکده اقلیم شناسی
author
Hamid
Nouri
Faculty of Natural and Environmental Sciences, Malayer University; Iran
author
Mohammad Ali
Najatian
4- Scientific member of Agricultural and Natural Resources Research and Education Center of Qazvin Province, Iran
author
text
article
2020
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Iintroduction The purpose of this articleCheck it outThe effects are wider on temperature and rainfall parameters AlsoIf any of these islamic parameters qualifyGrapesWhite seed in Golmkan area of Khorasan Razavi. One of the major effects of climate change is its impact on the quality of agricultural products. Grapes are also one of the strategic agricultural horticultural products.And the semi-arid climate of Iran is highly vulnerable to future climate change, so it is an appropriate and low-cost alternative to this type of study to achieve grape crop responses to climate change by developing modeling techniques.Golmakan, a city of Golbahar section of Chenaran city in Razavi Khorasan province, 45 kilometers from Mashhad, covers an area of 2000 thousand hectares and is 1176 meters in height at 36, 29 and 59.17 meters in height. According to the Cold Desert dry climate, the climate is also classified as Cold Dry by climate. Materials andmethods Currently the customer is producing equipment for the three-phase circulation converter of the Air-Ocean Circuit.What are the rules (provided by mathematical relations).Headcm3 model, designed and studied in the country by Ngelis and the Hadley Center Institute.And 360 days suitable for RCP8.5 and RCP4.5 scenarios.Daily temperature and precipitation values based on Hadcm3 models in baseline and future under RCP4.5, RCP8.5 scenarios. in a more complete way, the DownscalingWith the use of the change factor approach for Golmakan region, were scaled And using station data, scaled Downscaling to baseline quality by Perceptron Neural Network in A2019 Content for the Future.Multilayer neural network approach was used in this study. Multilayer neural networks have three input, middle and output segments. The middle layer corresponds to constraints. The first layer is removed from the middle section, extra data or out of the dataset; in the second layer, the data is normalized using operational definition.After defining variables and intermediate layers, the quality data is input to the neural network through the input layer and after performing the middle layer corrections, using the function definition, they exit the neural network output layer.This output consists of two parts: the first part teaching (or learning) and the second part exam. In this study, 70% of the data were used in the training section and 30% in the default test section. Pearson correlation test and Spearman and Chi-square tests were used to assess the relationship between each of these variables.In both sections, there was a significant relationship between the quality variables and the quantitative variables.Therefore, descriptive tests were used to assess the relationship between each of these variables.These tests included the Pearson correlation test and Spearman and Chi-square tests.After knowing the positive relationship between grape quality variables and basic meteorological data, the simulation process continues. Results and Discussion Climate models increasing temperature and decreasing rainfIn the future under RCP4.5, RCP8.5 scenarios Shows the ratio to the baseline period.The maximum temperature increased by 3.9 and 4.7 ° C, respectively, while the minimum temperature increased by 3.8 and 4.4 ° C, respectively, and the rainfall decreased by 0.3 and 0.8%, respectively.Pearson test showed a significant relationship between the variables.That is, each of the independent variables included min, max temperature, and precipitation Each of the dependent variables represented tree age, sugar content, panicle weight, panicle size, fruit length, fruit width, acidity, pH and TSS. Both scenarios represented panicle weight, panicle size, fruit length, fruit width, sugar, HP, TSS, Brix, acidity and weight of berries. It is predicted to decrease.In RCP8.5, the change rate is greater than in RCP4.5. Features: Juice color, meat color, fruit flavor, warehousing, marketability and transportation are unchanged in two scenarios.T-test for most variables: pH, sugar, acidity, panicle weight, fruit length and panicle length were significant in two scenarios.In the variables of berry weight and fruit width in two scenarios 4.5 and 8.5, cluster size of scenario 8.5 and length in berry scenario 4.5 were not significant. Conclusion The results show that as a result of rising temperatures and decreasing rainfall in the future climate, some components of grape quality will change in the future.Such studies provide the opportunity for agricultural managers and practitioners in the relevant agencies to take appropriate measures, such as the proper location of gardens, to determine appropriate and appropriate future climate patterns to mitigate the potential adverse effects of new methods and practices. Provide adaptation to new and changing climate conditions Key words: Climate Change, Model HadCM3, RCP5,White Grape, Network Neural
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https://clima.irimo.ir/article_126023_004d0896aa458c65f3527c2432cb92b1.pdf
Impacts of Window Form on Natural Light in Classroom in BWk Climate
neda
marufi
دانشجوی دکتری گروه معماری، واحد سمنان، دانشگاه آزاداسلامی، سمنان
author
Mohammadjavad
Mahdavinejad
Department of Architecture, Tarbiat Modares University, Tehran, Iran
author
Hossein
Moradinasab
Department of Architecture, Semnan branch, Islamic Azad university, Semnan, Iran
author
text
article
2020
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Introduction The “window form” is a determining factor in the transmission of “daylight” into the interior of educational classrooms. Studies show that the use of daylight affects students' physical health and mental well-being. Therefore, in the design standards of educational spaces, the necessity of using daylight has been emphasized. On the other hand, increasing the brightness of the student's desk can cause glare. It is necessary for classroom to gain natural light and visual communication with outside as a matter of “visual comfort”. Literature review and recent major advances show that the most efficient window form in Khorramabad of classroom is “horizontal”. The current debates show that southern classroom needs a canopy to provide adequate daylight and to eliminate glare and reduce eyestrain. The significant gaps in the field might be the form of the window and the effect of daylight in the education classroom. The research hypothesis emphasize that horizontal-rectangular windows in classrooms do not satisfy “sense of beauty” of the students. It seems that the amount of light that enters the classroom through the horizontal-rectangular windows is suitable for the classroom. It is predicted that during the teaching hours, due to the high amount of light radiation and sometimes due to the lack of sufficient light in the classroom, students feel bored and drowsy. Materials and methods The main purpose of this study is to evaluate the effect of window form on the quality of light absorption of educational spaces in BWk climate. A sample classroom in Semnan is selected as the case study of the research to examine the impacts of the window form. The research question is: What is the relationship between the window form (including shape and dimension) and the quality of natural daylight (the brightness of the daylight factor)? According to the research methodology, the independent variables are "dimensions" and "window form"; and “brightness” and “pleasant atmosphere inside the classroom” are dependent variables of the research which might be estimated based on 1- the daylight glare probability (DGP), 2- The Annual Sun Exposure (ASE), 3- the spatial daylight autonomy (sDA), 4- The daylight factor (DF) and 5- The Useful Daylight Illuminance (UDI). The research is to consider window materials, floor height, window OKB from floor, interior wall type and window glass type as controlled variables. The research enjoys qualitative-quantitative approach. The simulated environment in this study is a classroom with windows facing south in the city of Semnan. The dimensions of the examined classroom, in terms of length, width and height, have been selected according to the criteria of the Organization for Development, Renovation and Equipping of Schools (DRES). In the next step, students and professors use a questionnaire to express their opinion about the quality of daylight. For analytical simulation, a three-dimensional model of a “sample classroom” is simulated in commercially available software. Analyzes of daylight and well-being have been simulated in the Ladybug and Honeybee-Plus Tools, and the questionnaires have been analyzed by the means of SPSS Statistics. Results and discussion It was DGP that shows challenging behavior in the case study of the research in spring, autumn, winter at 11 AM in the 15th day of each month. ASE examined in order to calculate how much of space gets direct sunlight more than standard levels which might be the case of glare (visual discomfort) or more energy consumption for cooling loads. ASE as a dynamic indicator shows risk of glare which is dependent on the window of the classroom dimensions directly. According to the dynamic indicator of sDA, the research is going to answer “is there enough daylight in the classroom and examines whether the classroom receives enough daylight during standard operating hours or not”? The results indicate that the model umber 4, is in the best condition and about 50% of the hypothetical points in the class absorb at least 300 Lux of sufficient natural light to provide light for other spaces. Those that absorb relatively less light require artificial light. DF analysis, which is a static indicator, according to the form of common windows in the country, the light absorption conditions in the cloudy sky are such that it has the desired light absorption in the middle part of the classroom and in the third part of the class. It has been concluded that the provision of lighting by artificial sources such as ceiling lamps, etc. is an integral element of the class, but it is recommended to provide energy for optimal use of artificial light. UDI is to be between 100 and 2000 Lux. The case study simulation shows that in the first, second and fourth samples of the space under the window, less than 10% of the daylight hours will receive useful daylight lighting. According to the results of the questionnaire provided to the students, 80% have felt drowsy because of the poor lighting conditions in the classroom. 66% of the pupils consider their priority to choose the light source and lighting to achieve a sense of comfort, the natural light entering the classroom through the windows along with the light supply through the lamp < br /> Conclusion The results concluded that the efficient height of the classroom window is 180 cm. Other dimensions might be result in glare and visual discomfort in BWk climate. Based on visual discomfort of direct sunlight, window overhangs might be great solution for the case as well as passive shading. The simulations endorse adoption of an awning or an overhang above the window of the classroom. The results emphasizes that the standard classroom which has been promoted by the Organization for Development, Renovation and Equipping of Schools (DRES) is not good enough to be used in BWk climate schools.
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https://clima.irimo.ir/article_126024_d66b58022b8f8bdf169f471f44771551.pdf
Investigation of Temporal-Spatial Characteristics of Precipitation Using Discrete Maximal Overlap Wavelet Transform (MODWT) and Spatial Clustering Tools
Kiyoumars
Roushangar
Professor, Faculty of Civil Engineering, University of Tabriz,Tabriz, Iran
author
Mohsen
Moghaddas
M.Sc, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
author
Roghayeh
Ghasempour
Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
author
text
article
2020
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Precipitation is one of the important climatic elements and is one of the factors affecting the hydrological cycle. Temporal-spatial variations of precipitation in a watershed can have numerous effects on the engineering, management and planning of water resources. Many researchers have been studied precipitation variations. Most hydrological time series are non-stationary, trendy, or with seasonal fluctuations. Wavelet analysis is one the commonly applied approaches by researchers. It has been utilized as a common tool to break down and excavate complex, periodic, and irregular hydrological and geophysical time series, especially in recent years. On the other hand, clustering techniques can be used to identify structure in an unlabeled precipitation data set by objectively organizing data into homogeneous groups where the within-group-object dissimilarity is minimized and the between-group-object dissimilarity is maximized. Clustering analysis is similar to the homogeneity test. Considering the dynamic characteristics and non-uniform distribution of precipitation data and due to the need for identifying of homogeneous precipitation regions in water resources management, a temporal-spatial model is proposed to investigate the characteristics of precipitation. The time series of the precipitation were decomposed using MODWT mothod and the energy of sub-series was culculated. MODWT is a mathematical technique which transforms a signal into multilevel wavelet and scaling coefficients. Maximal overlap discrete wavelet transform (MODWT) is similar to the discrete wavelet transform (DWT) in that low-pass and high-pass filters are applied to the input signal at each level. However, the MODWT does not decimate the coefficients and the number of wavelet and scaling coefficients is same as the number of sample observation at every level of the transform. In other words, MODWT coefficients consider the result of a simple changing in the pyramid algorithm used in computing DWT coefficients through not down sampling the output at each scale and inserting zeros among coefficients in the scaling and wavelet filters. Clustering is the process of partitioning or grouping a given set of patterns into disjoint clusters. This is done such that patterns in the same cluster are alike and patterns belonging to two different clusters are different. k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. RBF methods have their origins in techniques for performing the exact interpolation of a set of data points in a multi-dimensional space. RBF mappings provide an interpolating function which passes exactly through every data point. In the present study, the classical and proposed methods were used to investigate the monthly rainfall characteristics of 30 stations in the southeastern of United States during 1968- 2018. In the proposed method, the time series pre-processing method including MODWT discrete wavelet transform and K-means clustering were used. At first the monthly precipitation time series of the stations were districted into several sub-series using MODWT method and db mother wavelet. Then, the energy of sub-series was calculated and used as input for K-means and RBF methods. The optimum number of clusters for the stations in both classical and proposed methods was five clusters. In order to use the data as the input of the RBF method, the correlation of the data was evaluated by variogram and covariance graphs. Then Spline with Tension method was selected in RBF model and zoning maps were drawn. In order to evaluate the temporal-spatial characteristics of monthly rainfall of 30 selected stations, two classical and proposed methods were used. At first the monthly precipitation time series of the stations were districted into several sub-series using MODWT method and db mother wavelet. Then, the energy of sub-series was calculated and used as input for K-means and RBF methods. The optimum number of clusters for the stations in both classical and proposed methods was five clusters. In order to use the data as the input of the RBF method, the correlation of the data was evaluated by variagram and covariance graphs. Based on the results of clustering and in accordance with the latitude and longitude variations of the stations, it was found that with increasing the energy of the clusters, the amount of precipitation in the stations decreased and vice versa. Silhouette coefficient of clustering in classical method was 0.3 and in proposed method was 0.8, which indicates better clustering of studied stations in the proposed method.
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https://clima.irimo.ir/article_126025_0761d798663d2585fd0b7e6d9a54efff.pdf
Investigation of Climate Change Occurrence and its Impact on Rainfall Wheat Phenology in West and Northwest of Iran
Elham
Mohammadi
university esfhan
author
Saeed
Movahedi
Department of Physical Geography, Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran.
author
Reza
Mohammadi
Institute of Agricultural Research, Sararood, Kermanshah, Iran
author
Saber
Golgari
Dryland Agricultural Research Institute
author
text
article
2020
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ntroduction Climate change will affect all sectors of the economy to some extent, but the agricultural sector may be the most sensitive and most vulnerable part because agricultural products are highly dependent on climate resources, And according to scientific evidence, future climate change, especially the combined effects of elevated temperatures and elevated atmospheric CO2 concentrations, will have a significant impact on crops (droughts, floods, frosts) on crops( Chiottioud ,1995). The general effects of climate change on crop development vary depending on the plant and study area (Rawlins, 1991), and commenting on the response of different species to climate change requires case studies. Materials and Methods area of study The study area includes west and northwest of the country Uncovering Climate Change in Past Times Climatic data of maximum temperature, minimum temperature, 30-year historical rainfall (1988-2008) were obtained from 23 stations in the west and northwest of the country And Using two nonparametric tests Mann-Kendall and Estimator slop sen, the trend of precipitation and temperature changes was investigated in order to detect climate change phenomenon in the region. Generating climate scenarios in future periods To assess future climate change in the west and northwest of the country, the CCSM4 general circulation model under RCP4.5 scenario is one of a number of new RCP emission scenarios that the Climate Change Intervention Board will develop in its Fifth Assessment Report (AR5) as representative of the linesVarious concentrations of greenhouse gases have been used Predictive model of wheat phenology and yield unctional and phenological data for three years (90-93) with 40 climatic parameters (Table 2) from seven stations (Zanjan, Arak, Sararood, Maragheh, Ghamloo, Ardabil and Orumieh) containing performance and phenology data Was prepared Then, using these data, performance and phenology in the baseline and future period were predicted through simple linear regression, multiple regression. The results consisted of 20 regression models The best model was selected based on R-squard index using RMSE. Results and discussion February, March, September, and the year are at 99 percent confidence levels, while January, June, July and August are at 95 percent confidence levels. As well as total rainfall, both the upward and downward trends have a significant and decreasing trend at 95% confidence level only in January and March. Changes in temperature and rainfall in the coming period The results of climate change assessment at each of the stations in the future climate show that the mean maximum temperature in the future climate has increased at 14 stations compared to the previous climate and decreased at the other stations. The mean minimum temperature in the future climate has increased in all the stations except for Ghamloo and Sanandaj stations compared to the previous climate. Average temperature also increased at all stations except Ahar, Zarineh, Sarab and Ghomloo stations in all stations compared to past climates Average mean precipitation in all stations excluding sarpolzahab station in future climates It increases with the past climate Impact of Climate Change on Phenology nder the climate change, the length of the flowering stage of the wheat in the future climate will be shorter than in the previous climate, so that the flowering stage length in all the studied stations with the exception of Zarrineh station in the next period (2039-2018 ) Is shorter than the average long-term flowering stage of wheat. he mean flowering stage duration in the basal climate is 136 days, whereas the mean flowering stage duration in the future climate is 118 days, ie the average flowering stage duration in the future climate is 18 days short. Increasingly, the shortening of the flowering stage in future climates is due to the increase in average temperature in May and April and average maximum temperature in December. Impact of Climate Change on Performance Under climate change, wheat grain yields will increase in future climates than in the past, so that at all stations with the exception of Mahabad station, wheat grain yield is higher than the long-term average in the past. verage wheat yield in the past climate was 1863.3 kg / ha but in the future climate it would be 2529.9 kg / ha. Wheat yields are up 35 percent due to the favorable future climate in the region. Conclusion tudies show that precipitation in the west and northwest region of the country during the past period has been decreasing and the temperature is increasing in most months of the year. And in the coming period the temperature in all months of the year until the end of 2039 shows an increase of 2.5 to 3.5 ° C. The flowering period is also 136 days for the previous period but 118 days for the next period shortening of flowering stage of wheat plant is due to increase in average temperature in May and April and average maximum temperature in December as well as increase in precipitation in December and February. Comparison of wheat grain yields of the current and past periods showed that wheat grain yields will increase by 35% in the future, due to the increase in average March and April temperatures and average January and March minimum temperatures. It also saw an increase in the average precipitation of February and March in the next period compared to the previous period.
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https://clima.irimo.ir/article_126026_4190fe747a7500bc40ced4ef624a9a0e.pdf
Investigating the Conformity of Meymand Earthsheltered Buildings with Its Climatic in Thermal Comfort
Amirreza
Khaksar
Department of Architecture, Semnan Branch, Islamic Azad University, Semnan, Iran.
author
Seyed-Majid
Mofidi-Shemirani
Assistant Professor Iran University of Science & Technology, Faculty of Architecture and Urbanism.
author
Mahmoud
Nikkhah-Shahmirzadi
Civil Engineering Department ,Semnan Branch, Islamic Azad University, Semnan, Iran.
author
text
article
2020
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Climate is one of the most important issues related to architecture that having it pre-designed can help with thermal comfort. Knowing the climate of a place can play an important role in reducing fossil fuel consumption. Contemporary architecture, irrespective of the climatic and environmental features of a place, causes severe damage to the environment that cannot be reversed. also. Consequences of not paying attention to climate in architecture are inadequate buildings in terms of thermal comfort where fossil fuels should be used. . In the present study, the research and construction of a region's climate through software and the degree of integration of its architecture and climate is a research concern. Therefore, the study of the degree of adaptation of Meymand Earthsheltered buildings was considered as the main issue of the paper. Also, identifying the most influential climatic variables on the formation of thermal comfort in Meymand village was selected as the main objective of the study. To achieve this goal, case study method based on field measurements was used and specialized software was used as data collection method. The village of Meymand is selected as a case study. Meymand village climate was first constructed in the meteonorm software during the period 1991-2019 in EPW format. The output is then obtained in the Claimate Consultant software, and for the validity and accuracy of the meteonorm software data, the data obtained from the software are in conjunction with the general data of the Babak City Synoptic Station as well as the output data. The data logger is compared and controlled. The temperature and relative humidity data of Meymand village on 11, 12 and 13 August 1398 are measured by field recorders using a data logger. The data from the data logger is controlled with the data from the Babak Synoptic Station and after the accuracy of the data logger, the software output is finally compared with the data logger. The results confirm the accuracy of the software and, after the meteonorm climatic output accuracy, the Meymand village climate EPW file is entered into the Climate consultant software for analysis and analysis. Be. Charts were also used as data analysis software. The results showed that the most influential climatic variable on the formation of Meymand EarthSheltered structures is the temperature component. And the thermal mass was the ratio of the opening to the wall, the thickness of the walls and the shades of the shapes. The least attention was paid to the orientation of the buildings towards sunlight, probably due to the natural texture of the village. Also, buildings with simultaneous south or southeast orientation with respect to sunlight, topographic midline elevation, planar square shaft and maximum soil penetration depth were selected as the most climate-friendly buildings in terms of thermal comfort. It was found that the climatic element of temperature was considered to be the most influential component on the formation of Meymand Earthsheltered structures. Therefore, after reviewing the architecture of the village of Meymand, it was found that most of the buildings in Meymand are in accordance with the climatic conditions of using heat mass to delay heat and cold at different times of the year, the square shape of the plan and finally the cubic fit. As it creates compact forms and helps to accelerate cold and warming of the space, the extruder shells make the extruder easy to contact, with a good ratio of the opening to the wall surface which minimizes It is possible and plays an important role in the thermal stability of the interior, the thickness of the walls, sometimes the walls between the two buildings. Considering the climate variables of temperature, radiation, precipitation, wind and relative humidity, it can be said that most architecture corresponds to climate with buildings with south-eastern and southern orientation towards sunlight, mid-level alignment. Topographies, with dense square shapes and cubic proportions, and ultimately with soil penetration depth, are most likely to result in thermal comfort at different times of the year. In summary, it can be said that the rate of compliance of the Earthsheltered structures of the village of Meymand with its climate is acceptable and this has caused that despite its thousands of years of construction, it is still stable and thermally desirable.
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https://clima.irimo.ir/article_126027_8852547c8d3eb38ae530df216e6d0b48.pdf