Synoptic analysis of Iran’s northwest dust storms
faramarz
khosh akhlagh
Associate Professor of Climatology, Department of Natural Geography, Faculty of Geography, University of Tehran
author
farshad
pazhoh
Department of Natural Geography, Faculty of Geographical Sciences, Kharazmi University of Tehran
author
farzaneh
jafari
PhD student climatology, Department natural geography, University shahid Beheshti Tehran
author
sanam
kohi
PhD Student in climatoology, Department of Natural Geography, Faculty of Geography and Environmental Planning, Sistan and Baluchestan University
author
text
article
2020
per
Synoptic analysis of Iran’s northwest dust storms This study was conducted to identify the effective synoptic patterns in creating dust storms using hourly visibility data and considering the meteorological codes related to the dust phenomenon in 8 meteorological stations located in East and West Azerbaijan for a period of 14 years (1996-2010). Then, using the network data of the US Center for Atmospheric and Oceanic Forecasting, the scan-synoptic characteristics of each dust storm were analyzed. The determination of the main sources of dust for each of the selected storms was performed using the Lagrangian model of dust particle tracking and using the regression tracking method. The results show that most dust storms in the northwest of the country occur in spring and May. Also, 2008 and 2009 had the highest frequency of dusty days. The synoptic view found that the pervasiveness, durability, and intensity of dust storms were consistent with the location of low-pressure surface systems located in western and southwestern Asia. In the synoptic study of the association of dust storms, 3 sea level pressure patterns with different arrangements were identified as the main patterns at the time of the storms. The results show a strong pressure gradient due to the expansion of warm low pressures from southern latitudes and cold high pressures from high latitudes to the west and southwest of Asia and the rise of dust particles from the ground and dust currents blowing towards the research area with The southwest-northeast direction is by low depth trough based on dust sources in Syria, Iraq and Saudi Arabia in the middle levels of the troposphere. Key words: Dust storm, Low pressure, LAGRANGIAN particle tracing model, low depth trough, North West of Iran Key words: Dust storm, Low pressure, LAGRANGIAN particle tracing model, low depth trough, North West of Iran
Journal of Meteorology and Atmospheric Science
Iran Meteorology Society (IMS)
2645-7261
2
v.
4
no.
2020
272
286
https://www.ims-jmas.net/article_128174_6faa2108a3bf5e2cbd99d06ae9f7148b.pdf
Evaluation of M5P Algorithm for Estimation of Potential Evapotranspiration, Minimum and Maximum Temperature (Case study: Sari Weather Station)
SeyedHassan
Mirhashemi
Graduated ph.d, Dept. of Water Engineering, Faculty of Water and Soil, University of Zabol. Iran
author
Mehdi
Panahi
Assistant Professor, Dept. of Water Engineering, Faculty of Agriculture, University of Zanjan, Iran
author
Leila
Zareei
Master student of water resources engineering,Imam khomeini internatinal university, Iran
author
text
article
2020
per
In this study, we evaluated the performance of M5P tree model in estimating three parameters of potential evapotranspiration, minimum and maximum temperature. The used data of monthly mean of Sari Synoptic Weather Station during the 30 year period from 1989 to 2019 were performed. According to the results of M5P model with correlation coefficient of 0.92, RMSE of 0.25 and MAE of 0.12, has better performance in predicting potential transpiration evaporation than prediction of minimum and maximum temperature. . According to sensitivity analysis of M5P algorithm with average temperature inputs, sunshine hours, air humidity percentage, dew point temperature and saturation vapor pressure deficiency had the highest and with sunny hour inputs and wind speed had the least correct performance in predicting potential transpiration evaporation. It was also found that the wind velocity parameter had a negative effect on the prediction performance of the M5P model in the amount of transpiration evaporation. In this study, we evaluated the performance of M5P tree model in estimating three parameters of potential evapotranspiration, minimum and maximum temperature. The used data of monthly mean of Sari Synoptic Weather Station during the 30 year period from 1989 to 2019 were performed. According to the results of M5P model with correlation coefficient of 0.92, RMSE of 0.25 and MAE of 0.12, has better performance in predicting potential transpiration evaporation than prediction of minimum and maximum temperature. . According to sensitivity analysis of M5P algorithm with average temperature inputs, sunshine hours, air humidity percentage, dew point temperature and saturation vapor pressure deficiency had the highest and with sunny hour inputs and wind speed had the least correct performance in predicting potential transpiration evaporation. It was also found that the wind velocity parameter had a negative effect on the prediction performance of the M5P model in the amount of transpiration evaporation.
Journal of Meteorology and Atmospheric Science
Iran Meteorology Society (IMS)
2645-7261
2
v.
4
no.
2020
287
295
https://www.ims-jmas.net/article_128176_247cb3df6f0b4a8a03149c343c66f545.pdf
Sensitivity and uncertainty analysis of the different parameterization schemes in regional climate model RegCM4.5 for simulation of air temperature and precipitation over North and West of Iran
Fatemeh
Khayatian Yazdi
Department of Earth Science, Science and Research Branch, Islamic Azad University
author
Gholamali
Kamali
Department of Earth Science, Science and Research Branch, Islamic Azad University, Tehran, Iran
author
Seyed Majid
MirRokni
Yazd Unversity, Yazd, IRAN
author
Mohammad Hossein
Memarian
Division of space physics, Department of physics, physics faculty, Yazd university.
author
text
article
2020
per
In this study, the performance of the Regional Climate Model version 4 (RegCM4.5) with different parameterization schemes was evaluated to simulating the seasonal 2-m temperature and precipitation over the north and west of Iran in the period of 1986-2015.. For this purpose, the NNRP2 reanalysis data were used as initial and boundary conditions of the RegCM4.5 climate model as well as six different parameterization schemes for simulation. The results demonstrated that the RegCM4.5 model has good potential for simulating precipitation and surface temperature in the north and west of Iran. The model bias for 2- temperature in different regions of Iran using parameterization schemes is different. Magnitude of the model bias for land surface temperature over different regions of Iran varies by convection parameterization schemes. In most cases, the root mean square error between post-processed simulated seasonal average temperature and observation value was less than 1°C and their correlation coefficient was more than 0.9. In general, according to the surface temperature simulations, using the model data after post-processing with Holtslag-Grell and Holtslag-Kuo schemas, compared to other simulations, achieved better performance on the study area. So, for the average seasonal precipitation, the Emanuel scheme is suggested along with the two Holtslag and UW PBL schemas with a correlation between 0.55-0.75 and a standard deviation close to 1. Also, this research intends to investigate the performance of model in simulating 2-m temperature and precipitation by developing a multi-physics ensemble for RegCM4.5 model over north and west of Iran. The investigation on RegCM4.5 model uncertainty in the ensemble prediction of temperature and precipitation by combining physical schemas, shows that the amplitude of the model uncertainty can be reduced and more reliable predictions of temperature and precipitation can be achieved. So that UW PBL-Grell and Holtslag PBL-Emanuel schemes had a good performance for ensemble prediction of temperature and Holtslag PBL-Emanuel had a good performance for ensemble prediction of precipitation.
Journal of Meteorology and Atmospheric Science
Iran Meteorology Society (IMS)
2645-7261
2
v.
4
no.
2020
296
318
https://www.ims-jmas.net/article_128177_350843db8d454ad004ece7d6f947bc5c.pdf
Modification of Crop Pattern for Optimal Use of Water Derived from Heavy Precipitation Simulated by RegCM4 Model in South Khorasan Province
Motahhareh
Zargari
Department of Climatology and Geomorphology, Hakim Sabzevari University, Sabzevar, Iran
author
alireza
entezari
Department of Climatology and Geomorphology, Hakim Sabzevari University, Sabzevar, Iran
author
Abbas
Mofidi
Department of Geography, Ferdowsi University of Mashhad, Mashhad, Iran
author
Mohammad
Baaghideh
Department of Climatology and Geomorphology, Hakim Sabzevari University, Sabzevar, Iran
author
text
article
2020
per
The application of the RegCM4 dynamic model has enabled the study of mesoscale and regional scale atmospheric phenomena in different regions. Heavy precipitation is one of the essential atmospheric phenomena critical for agriculture in arid regions. Optimal use of rainwater increases water resources in the arid region. One of the solutions for optimal use of water in arid climate is to utilize crop pattern. The crop pattern means the share of cropping and selection of crops in an area, employing the optimal cropping pattern as one of the important solutions to water efficiency in agriculture. In this research, various data including rainfall data, NCEP/NCAR, TRMM satellite model, RegCM4 regional climate model, Aphrodite, and finally, agricultural data were used to change the cropping pattern for optimum use of water. Then, 5% precipitation threshold method was used to investigate heavy rainfall and selected as a representative of heavy rainfall in the study area on March 14th. The seasonal rainfall percentile chart, heavy rainfall maps and rainfall zones and performance of crops were then prepared and analyzed. The results indicate that the percentage of seasonal precipitation is in ascending and descending order in spring and winter, respectively. According to the regression model, Birjand, Nehbandan, and Ghayen stations are suitable in spring, and Ferdows and Boshrouyeh stations in winter. Moreover, the intensity of atmospheric streams in NCEP/NCAR and TRMM model maps gradually in northeast and east areas especially south Khorasan has led to heavy rainfall that RegCM4 model has been able to significantly simulate it and this rainfall has considerable values. Humidity values have increased on CAPE and thermodynamic graphs. Furthermore, in the zoning maps in the output of the observation map on Birjand station, Birjand, Ghayen, and Nehabandan, with the highest rainfall show better agricultural performance, while Boshrouyeh and Ferdows stations have the lowest performance. Therefore, since crop performance is directly related to rainfall, heavy rainfall can improve in agricultural in South Khorasan as a dry climate province. One way to deal with low-water resources in arid climates is to use crops such as Jujube, Barberry, and Saffron that are less water-intensive in agriculture and more adaptable to climate and regional conditions than other crops. Therefore, with proper use of rainwater during heavy rainfall in low-lying areas, the performance of agricultural products will greatly improve in South Khorasan province.
Journal of Meteorology and Atmospheric Science
Iran Meteorology Society (IMS)
2645-7261
2
v.
4
no.
2020
319
334
https://www.ims-jmas.net/article_128179_2e204d49a4bd66fe7ef319191bb04725.pdf
Feasibility study of solar energy utilization with emphasized on plains of Iran
Sohaila
Javanmard
Faculty member of physical meteorology and weather modification, Atmospheric Science and Meteorological research Center,
author
Elham
Yarahmadi
Lorestan University
author
Leili
Khazanedari
Climate research Institute
author
text
article
2020
per
Solar energy is a free, accessible and pollution-free resource which can be used as an alternative to fossil fuels in the current climate of Iran. The purpose of this study is to estimate the spatial and temporal distribution of solar energy with emphasis on plains of Iran. For this purpose, cloud cover amount and sunny hours during the period of 30 (1985-2014), 20 (1995-2014) and 10 years (2005-2014) for 51, 146 and 218 synoptic stations of I. R. of Iranian Meteorological Organization have been derived respectively. Then the day light hours for 403 stations were estimated monthly and annually and were zoned using GIS. Both of monthly average of cloud cover amount and sunny hours have been derived during warm seasons (March to August) and cold seasons (September to February). The cloud amount have been classified in the following three classes; clear to partly cloudy (0-2 Octa), semi cloudy (3-6 Octa), and total cloudy (7-8 Octa). The results showed only clear and partly cloudy during May through September and Semi-cloudy region were shown during October through February mostly occurred over Northern regions, Caspian coast, and North West of Iran. The Maximum of monthly sunny hours has been occurred in Mashad station with 15.7 days in June and the minimum in Anzali station with 3.8 days during 30 years. The results of the study of the three average parameters of amount of cloud cover, sunny hours and day light hours show that the greatest potential for solar energy utilization is in the summer and then in the spring. Spatially, this potential is observed in the plains of semi-southeastern and eastern, central and southwestern regions of Iran, respectively. In addition, all temporal and spatial changes of these three parameters are directly related to the climate systems of Iran and the position of the sun.
Journal of Meteorology and Atmospheric Science
Iran Meteorology Society (IMS)
2645-7261
2
v.
4
no.
2020
335
354
https://www.ims-jmas.net/article_128181_67828f5d83b1b3a2dbb0733272a6a890.pdf
Investigation of coincident temperature and relative humidity in Bushehr coastal for air conditions design
Mohammad
Moradi
Associate Prof. of Atmospheric Science and Meteorological Research (ASMERC), Tehran
author
parviz
rezazadeh
I.R. of Iran Meteorological Organization
author
text
article
2020
per
In this study, the data of coincident temperature and relative humidity in Bushehr coastal station (1993-2017) were discussed to estimate the corresponding values with probabilities of 95% and 99%. This value in the design of large structures for determining the method of calculating air conditioning are used. For this job, graphical and numerical methods were used. The graphical method is based on the empirical cumulative function and the basis of the numerical or statistical methods is the fit of the best probability cumulative function. In numerical methods, data from the hot month, hot season and all months of the year were used. To determine the coincident relative humidity at the same time as the estimated dry temperature, the average relative humidity amongst the data was used. The results showed that the statistical method used to determine the dry temperature corresponding to different probabilities for all data of the year is more appropriate than the method that uses season and hot month data, but obtains higher values than the graphical method. This difference occurred due to the placement of maximum data at the top of the fitted curve in the statistical method and the use of observation data in the graphical method. In addition, at the Bushehr coastal station, the average annual dry temperature and the temperature corresponding to different probabilities, has a significant upward trend. Therefore, it is recommended that in the design of structures with a life span of 50 years on the coasts of Bushehr, the specified dry temperature corresponding to probabilities of 95 and 99 present is 1.7 and 1.8 degrees Celsius, respectively, should be considered higher than estimated values. Therefore, while recommending the use of the generalized graphic method of this paper, it is suggested that at Bushehr coastal station, the dry temperature corresponding to probabilities of 95% and 99% is estimated to be 37.1 and 39.2 degrees Celsius, respectively, and the relative humidity is 55% and 52% respectively.
Journal of Meteorology and Atmospheric Science
Iran Meteorology Society (IMS)
2645-7261
2
v.
4
no.
2020
355
366
https://www.ims-jmas.net/article_128184_427a4c1cfdd6838b642d16ced858f2ed.pdf