Iraqi Meteorological Organization Research Articles

A Coda-Duration Magnitude Scale for the Mesopotamian Seismological Network in Iraq

One of the routine tasks of local, regional, and global seismic networks is to calculate the earthquake magnitude using one or more scales. This study aims to derive a duration magnitude equation using the earthquake data recorded by the local Mesopotamian Seismological Network (MPSN) in Iraq. The seismic waveform data were collected from 13 broadband seismic stations of the local MPSN for the period June 2014 to October 2023 years. The source parameters of these earthquakes were extracted from the International Seismological Centre (ISC). To establish a coda duration magnitude scale, 476 events were used and 100 events were employed to test the derived equation. Coda-duration magnitude equations were derived using linear regression analysis. To ensure the applicability of the magnitude equation for the network, the station correction coefficient (Sc) was estimated. The established coda duration magnitude scales are as follows: (4 ≤ ML ≤ 6) (4 ≤ ML ≤ 5) There is a good agreement between the MD values calculated using the above equation with those estimated for the same events using coda-duration magnitude equation derived in previous study from data of the Iraqi Meteorological Organization and Seismology (IMOS). The significant strong scaling relationships derived between MD–ML, MD–mb, MD–Ms, and MD–MW can be used quickly and reliably in MD calculation for earthquakes recorded by the MPNS stations and vice versa.

Evolution the Relationship Between Physiologically Equivalent Temperature and Some Meteorological Parameters for Basra City, Iraq

Background: Physiologically equivalent temperatures (PET) is highly efficient in evaluating the thermal component of any given microclimate as a single thermal index. The assist stakeholders in understanding and interpreting existing bioclimatic, allowing them to make any required modifications and become more robust to predicted climate change. Objective: This study assesses the relationship between Physiologically equivalent temperatures (PET) and some Meteorological Parameters. Methods: The data for this study includes observed mean monthly air temperature values, relative humidity, and wind speed for the period (2001-2020). The data was acquired from “Iraqi Meteorological Organization and Seismology (IMOS)” stations for Basra city. The radiation and Human Bioclimatic (RayMan) model were used to simulate bioclimatic indices (SET, UTCI, PET, PMV). Results: The findings revealed that the greatest mean values for PMV (4.3), SET (36.3), PET (45.5), and UTCI (42.1) were seen in July and August. The measurements have a nice thermal sensation of PMV (-0.5 - 1.9), SET (19.2- 29), PET (18.1- 31.8), and UTCI (15.9 - 28.7) is most noticeable in the months of (March, April, and October). The results showed the PET values (cool) and (Slightly cool) between (9- 18.3) for January, February, March, and December. The value of UTCI was between (5.9- 8.5) within classes (Slight cold stress), the values of PMV (-2.6- (-2.1)) within classes (strong cold stress) and (Slight cold stress) and the value of SET was (10.2- 12.4) within classes (Slight cold stress). Conclusions: Correlations between PET and air temperature (0.99), indicating good agreement between PET and air temperature, and relative humidity (0.96). PET and wind speed (R2=0.56). The scattering pattern of PET and other thermal indices shows that all indexes have a significant correlation coefficient, between PET and UTCI (R2=0.99), between PET and SET (R2=0.98), and (R2=0.99) between PET and PMV.

Intelligent Dust Monitoring System Based on IoT

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system train and test part was applied to dust phenomena historical data. Its data has been collected through the Iraqi Meteorological Organization and Seismology (IMOS) raw dataset with 170237 of 17023 rows and 10 columns. The LSTM model achieved small time, computationally complexity of, and layers number while being effective and accurate for dust prediction. The simulation results reveal that the model's mean square error test reaches 0.12877 and Mean Absolute Error (MAE) test is 0.07411 at the same rates of learning and exact features values of vector in the dense layer, representing a neural network layer deeply is connected to the LSTM training proposed model. Finally, the model suggested enhances monitoring performance.

The Relationship of CLWC and Rainfall to the Synoptic Cases of Two Case Studies Over Iraq

Climate change and the improvement of the environment is one of the most important topics that preoccupied the world, and the main factor for it is precipitation. To understand how to improve the environment, precipitation must be increased by understanding the mechanisms of cloud formation and benefiting from the water content of the liquid cloud, which is the basic building block of precipitation. There is no precipitation without liquid water content. This study examined the effect of depressions on rain and liquid cloud water content, in addition to studying the relationship of liquid water content and precipitation, and classifying clouds according to liquid water content over Iraq. We found that the liquid water content and the amount of precipitation are affected by depressions. Hourly data has been taken cloud liquid water content were used for four primary times, (00, 06, 12, and 18 UTC), at all pressure levels from (1000 to 175 hpa) for the study Selected days in Winter 2019 Taken from the generation of European Center for Medium-Range Weather Forecasting (ECMWF) from ERA5 it is the fifth generation ECMWF atmospheric reanalysis of the global climate covering the period from January 1950 to present. ERA5 is produced by the Copernicus Climate Change Service at ECMWF, sea level pressure maps and geopotential height maps were taken from ECMWF ERA5 Reanalysis. And low, medium, and high clouds and the amount of precipitation were taken from the (Iraqi Meteorological Organization and Seismic Monitoring). Two programs (Matlab) and (Origin) were used to analyze and plot the data.

Intelligence framework dust forecasting using regression algorithms models

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, comes in second place with a gross ratio of 91%. Furthermore, Bayesian ridge (BR), linear regressor (LR), and stochastic gradient descent (SGD), with mean square error and with accuracy ratios of 84.365%, 84.363%, and 79%. As a result, the performance precision of these regression models yields. The interaction framework was designed to be a straightforward tool for working with this paradigm. This model is a valuable tool for establishing strategies to counter the swiftness of climate change in the area under study.</span>

Application of the Empirical Mode Decomposition Method to Noise Reduction Using Seismic Event Data Recorded at Kirkuk Seismological Station.

This study aims to use the Empirical Mode Decomposition for reducing the noise of passive seismic signals recorded across seismic event recorded at Kirkuk station which is one of the Iraqi Meteorological Organization and Seismology data, where human activities in Iraq's populous cities significantly impact the seismic recordings at Iraqi Meteorological Organization and Seismology stations sites. In this paper, we present an algorithm based on the Empirical Mode Decomposition. It is a data driven method used as a propelling tool for analyzing and decomposing non-stationary and non-linear data without any previous assumptions. Empirical Mode Decomposition generates a finite and often small number of Intrinsic Mode Functions. The decomposition is based on the direct extraction of the energy related to various intrinsic time scales, an important parameter of the system. Empirical Mode Decomposition technique is applied to the available seismic records to reduce the noise level in the records, which helps in the interpretation of the records.

Determining Attenuation Q-Factor Values for Selected Seismic Stations in Iraq

The coda wave decay (CWD) method was used to estimate the quality factor from the coda wave amplitude decay rate for the broadband seismic stations (IBDR, MSL, and NSR4) using a single backscattering model. This research aims to calculate the attenuation coefficient and the frequency-dependent coefficient (α) for three stations and compare them to comprehend the details of Earth's crust structure in those stations. Then, to test if they are homogenous or not. Also, investigate how sensitive extracted values to tectonic differences in study stations. The attenuation properties are important for providing information about the medium that seismic waves pass through and can also be applied to areas with seismic activity as initial disaster mitigation. The study used data from the Mesopotamian Network (MP) and the Iraqi Meteorological Organization and Seismology (IMOS) from 2011 to 2021. The selected earthquakes have less than < 100 km epicentral distances, and magnitudes ranging from 3.5 to 5.6. Forty-six earthquakes were recorded by three stations (IBDR, MSL, and NSR4). These earthquakes were analyzed at eight center frequencies (1, 2, 3.5, 6, 8, 10, 12, and 16 Hz) and a 30-sec length window by using the SEISAN Earthquake Analysis Software. The QC values are computed by the frequency-dependent relationship QC= Q0 f α, where Q0 is QC at 1Hz and α denotes frequency dependence degree. The attenuation relationship of the station IBDR is obtained as QC =98 f 1.07, QC = 99 f 1.09 in the MSL station, and QC = 77 f 0.98 in the NSR4 station. The results showed that low Q0 corresponds to high attenuation. The comparison of the estimated QC for these three stations indicates that attenuation is highest at NSR4, followed by other stations.

Obtaining an Empirical Earthquakes Duration Magnitude Formula from the Data of the Iraqi Meteorological Organization and seismology (IMOS)

This paper calculated the Duration Magnitude (MD) equation using data from the Iraqi Meteorological Organization and seismology (IMOS). It is an empirically determined equation and expressed as: The epicentral distance and local geological conditions affect the duration of the coda. The data is obtained from 7 seismic stations in the network. The new proposed duration magnitude equation results from applying linear regression analysis to the data of a seismic signal duration with correlation coefficient R2=0.76; and a standard deviation value of 0.049. Station corrections indicated by Sc are also specified for the seismic stations that range from -0.024 to + 0.02.

Verification of Some Weather Elements Forecasts from BSC-DREAM8b V2 Model

Abstract The aim of this study is to verify 2-meter temperature and mean sea level pressure forecasts from BSC-DREAM8B V2.0 model, which is a short-term numerical forecasting model against observed data from the Iraqi Meteorological Organization & Seismology constitution and modelled data (ERA-Interim) reanalysis from the European Centre for Medium Range Weather Forecasts (ECMWF) for the period 1-3 June 2012 for four selected stations in Iraq, they are Mosul, Baghdad, Rutba and Basra which represent northern, central, western and southern of Iraq respectively by using some statistical methods including Mean Absolute Error (MAE), Bias Error (BE) and Correlation Coefficient (R). The results showed that the BSC-DREAM8B V2.0 model worked well in representing the daily temperature variation and with relatively good compatibility with the ERA-I modelled data, however, the latter showed lower absolute error rates. The two modelled data showed the highest absolute error rate for Baghdad station whereas BSC showed lower values for Basra station and different values for Rutba and Mosul, and the predicted values were overestimated for all stations and for both models except for Rutba station where ERA-I data showed underestimated value. As for the surface pressure at mean sea level, the BSC-DREAM8B V2.0 model showed its ability to simulate the daily change of pressure and worked in a good consistency with ERA-I modelled data with few hetopascal as mean absolute error. Both modelled data showed underestimated values for all stations, and thus, BSC modelled data is better for simulating temperature and mean sea level pressure in low elevated regions compared to ERA-Interim data and vice versa.

Assessing the Groundwater Recharge with Water Balance in Ameriat Al-Falluja City, Al-Anbar Governorate, Western Iraq

This study aims to figure out how to calculate water recharge using the soil conservation service method, one of the most widely used methods for calculating runoff volume following rainfall. The research is being conducted in Ameriat Al-Falluja City, Al-Anbar Governorate. The Iraqi meteorological organization's Baghdad Airport and Al-Ramadi stations provided data on the research area from 1989 to 2020 as total annual rainfall (123.1 mm), the RH% (43%), the mean monthly T (23.6 °C), total evaporation (3169.61 mm), the wind speed (3.1 m/s), and the sunshine duration (9 h/day). The climate of the study area is described as arid. The total evapotranspiration value quantity is 1137.38 mm for the 32-year comparison period, while the total amount of correct evapotranspiration was 992.3 mm. Water surplus is 36.7% of total rainfall, which equals 45.2 mm. Groundwater recharge is 45.2 mm, with a rate of 36.7%, showing the groundwater recharge (%) from total rainfall. The value of groundwater recharge throughout a year is about equivalent to 23.6848* 105 m3/year.

Estimation of Coda Q Wave Attenuation Factors for Northern Iraq

The coda wave decay method was used to estimate the quality factor from the coda wave amplitude decay rate for the broadband seismic stations in northern Iraq using a single back-scattering model. The study aims to calculate the attenuation factor to comprehend the details of the structure of the earth's crust in the study area. The study was conducted using data from the Mesopotamian Network and the Iraqi Meteorological Organization and Seismology from 2007 to 2021. The selected earthquakes have magnitudes ranging from 4 to 6.1 ML and epicentral distances of less than < 100 km. Seventy seven earthquakes were recorded by three stations (SLY1, DHK1, and IKRK). These earthquakes were analyzed at eight center frequencies (1, 2, 3.5, 6, 8, 10, 12, and 16 Hz) and a 30-sec length window by using the Seisan package. The Qc values are computed by the frequency-dependent relationship QC= Q0 f α, where Q0 is QC at 1 Hz and α denotes the degree of frequency dependence. The attenuation relationship of station SLY1 is obtained as QC =88 f 1.02, QC = 90 f 0.97 in the DHK1 station, and QC = 91 f 1.04 in the IKRK station. The comparison of these three stations indicates that attenuation is highest in Sulaymaniyah, followed by Duhok, and then Kirkuk.

The Effects Of Different Weather Conditions On 5G Millimeter Waves Propagations at 38 GHz and 73 GHz For Kut-City in Iraq

It is critical to utilize a good model for predicting acceptable and optimum frequencies while designing and planning for the future generation wireless communications system's channel. This paper explains how the weather conditions affect the strength of the transmitted signal in various environments and circumstances, as well as how the mmWave behaves as it passes through free space and the atmosphere. An NYUSIM simulator package is used for predicting the performance of the channel for two months (January and July). Two frequencies were used, 38 GHz and 73 GHz to test the channel performance and which frequency is the best suited for the Kut city environment. The simulation results shown that an agreement with the 38 GHz for its lower path loss and acceptable received power. The weather database was real and actual obtained from the Iraqi meteorological organization and seismology reports consist of (rain, fog and temperature). The result for both directional and omnidirectional power delay profile showed a great agreement at 38 GHz for the two months (January and July), where the path loss and received power at 38 GHz for January is 127 dB and -47.2 dBm respectively, where for 73 GHz the path loss is 135.4 dB and with a received power of -55.7 dBm. At July the path loss and received power for 38 GHz and 73 GHz is (123 dB, -43.2 dBm) and (130 dB, -43.2 dBm) respectively.

Trend Analysis of Annual Surface Air Temperature for Some Stations over Iraq

Surface Air Temperature (SAT) is an important weather element affecting the climate and its nature, as it greatly affects the nature of the atmosphere prevailing in the city of Baghdad, as well as the main influence on the pressure systems affecting Iraq and thus the city of Baghdad. In this study, the annual SAT for three aspects of temperatures (mean, maximum, and minimum) for Baghdad city of approved 11 years had studied, analyzed and discussed. The sources of data came from two sources. First, Iraqi Meteorological Organization and Seismology (IMOS), which represented the arithmetic average annually of the SAT, maximum and minimum temperature for the period (2009 – 2019). Second source of data was from Mustansiriyah University, atmospheric sciences department of Atmospheric Sciences - college of Science, the data are supported as monthly average for SAT for Baghdad. Results shown Basrah was high annual of SAT than four selective cities in Iraq. The variation of annual SAT was in the end study period where reach to 7 oC in mean of SAT for Basrah city. The trend of SAT for Baghdad city was positive for Mean and maximum, while negative for minimum case. Mustansiriyah station was high than IMOS station by 2 oC for mean of SAT, and 5 oC for maximum SAT.

Processing ambient noise using wavelet analysis tools: the Iraqi Seismological broadband Network Data at Iraqi Meteorological Organization and seismology (IMOS)

The purpose of this study is to reduce the noise of passive seismic signals recorded across the Iraqi Seismological Network Data at Iraqi Meteorological Organization and seismology (IMOS). The seismic records from six broadband stations of IMOS are largely affected by human activities in the populated cities of Iraq. We utilized several well-developed amplitude power spectrum and wavelet analysis techniques to improve signal-to-noise ratio. The results obtained from this comparison show that continuous wavelet transform can largely improve signal with minimal changes in the waveform shape of interest, even in presence of high noise levels. In addition, has overwhelmingly strong vitality and gains substantial development in the field of signal processing. Several mother wavelets were tested and Morlet and Coiflet selected as the optimum waves based on the signal characteristics and the noise reduction objective (maximizing SNR or reducing errors). Hence, the quality of the final seismic signal is crucial for the moment tensor analysis. However, traditional filters including discrete wavelet packet transform and 1-D wavelet analysis methods can be affective to reduce distortion in the signal.

The effect of Urban Heat Island mitigation strategies on outdoor human thermal comfort in the city of Baghdad

Todays, most Iraqi cities suffer from extremely hot-dry climate for long periods throughout the year. However, most urban patterns that exist inside these cities are not suitable for this harsh conditions and lead to an increase in the value of the Urban Heat Island (UHI) index. Consequently, this will increase outdoor human thermal discomfort as well as energy consumption and air pollution in cities. This study attempts to evaluate the effect of UHI mitigation strategies on outdoor human thermal comfort in three different common types of urban patterns in the biggest and most populated city in Iraq, Baghdad. Three different mitigation strategies are used here – vegetation, cool materials, and urban geometry – to build 18 different scenarios. Three-dimensional numerical software ENVI-met 4.2 is utilised to analyse and assess the studied parameters. The input data for simulations process are based on two meteorological stations in Baghdad: Iraqi Meteorological Organization & Seismology, and Iraqi Agrometeorological Network. All measurements are taken in a pedestrian walkway. The results of different scenarios are compared based on their effect on human thermal comfort. Outdoor thermal comfort is assessed according to Predicted Mean Vote index, as mentioned in ISO 7730 standard. This study provides a better understanding of the role of UHI mitigation strategies on human thermal comfort in the outdoor spaces of Baghdad's residential neighbourhoods. This can help generate guidelines of urban design and planning practices for better thermal performance in hot and dry cities.

Approaching of May maximum surface air temperature to characteristic summer season for Baghdad city

Seasonal variability is the complex non-linear response of the physical climate system. There are two types of natural variability: those external and internal to the climate system. In any given season, natural variability may cause the climate to be different than its long-term average. This study examines with the seasonal variation of the maximum temperatures during the summer season. In addition, the maximum temperatures in May become close to the characteristics of the summer season. The monthly data for maximum temperature of May, June and July were used from Iraqi Meteorological Organization and Seismology (IMOS) for 47 years from 1970 to 2017 for Baghdad city. This period was long enough to estimate the range of approaching maximum temperature (Tmax) May to summer. Results revealed a significant Tmax for Baghdad during the second period (1992–2017) and ?shown similar behavior of Tmax in May to June and July; on the contrary that first period (1970–1991). In second period, two phases have been found out, positive phase and negative phase. The positive phase were happened in 1995, 1999, and 2006, and the negative phase was four cases (1992, 2004, 2013, and 2016), while a few cases recorded in first period. The amplitudes of monthly variability had same distance of leaner correlation especially in 1999 and 2013 that represent coherent wave with summer seasons. The variance difference for Tmax between May and June approximately was 2°C for second study’s period, while exceed this range in first period. This variance change to 7.5°C when found difference between July and May.

Predicted the Cumulative Annual Rainfall in Iraq Using SDSM Modal

Rain is deemed one of the most important climate elements. It must be given special attention for being the basis without which no kind of life in the world can be there. the aim of the study is to use Statistical models Downscaling (SDSM) where it is a universal model used to converting large scale output into a small scale that can be used to study impact at the local scale (Iraq)' to Forecasting cumulative annual rainfall for the next years where there are a few studies used this model in Iraq. Daily rainfall data from the Iraqi Meteorological Organization and Seismology (IMOS) (2007-2016) for the study areas (Baghdad, Karbala, Al-Hay, Mosul, Kirkuk, Khanaqin, Basra, Nasiriya, Diwaniya, and Rutba) is used to estimate the amount of rainfall by using SDSM. The model was used to estimate the rain values and then the results were compared with the actual values, the results were very close to each other. Also, the model used to predict the cumulative annual rainfall from (2017-2021), The result shows that the bigger amount of rainfall in the north region with (3821) mm and the lowest amount in the west region (665) mm, while middle region (1848) mm and south region (1828) mm.

Study the Effect of the Amount of Clouds on the Number of Actual Hours of Sunshine at Selected Stations in Iraq

This research aims to study the effect of the amount of clouds on the number of actual hours of Sunshine in selected stations in Iraq, namely (Mosul Station, Baghdad Station, Basra Station), using data (the amount of clouds and the number of actual hours of Sunshine) for a period of (31 years) for the period extending from (1980 - 2010), which were obtained by data available in the Iraqi Meteorological organization and Seismology. In this research, the effect of the amount of clouds on the number of actual hours of Sunshine was clarified by studying the monthly and seasonal change of the two variables, in addition to clarifying the nature of the relationship between them by calculating the correlation coefficient using Microsoft Excel (2010). The results indicated that there is a strong inverse correlation between both variables in The three study stations, where the values ​​of correlation coefficients ranged between (-0.92) – (-0.87) in the study sites, and this indicates that with the increase in the amount of clouds the number of hours of actual hours of Sunshine decreases, and vice versa.

Identify Months of Comfort and Discomfort Using the Temperature-Humidity Index at Selected Stations in Iraq

In this research, the months of comfort and discomfort were identified using the Temperature-Humidity Index in selected stations in Iraq (Mosul, Baghdad, Basra) using data of the temperature and relative humidity values of the period (1983-2019) obtained from the Iraqi Meteorological organization and Seismology. The results showed that the months of discomfort in the three study stations were (January, July, August, December), while the months of comfort in the three study stations were both (April, September), while the months (February, March, June, September, November) alternated between comfort and discomfort in the three study stations. This research also clarified the effect of both temperature and relative humidity on the values of the Temperature-Humidity Index by clarifying the nature of the relationship between them by calculating the coefficient of correlation using Microsoft Excel (2010), where the results showed a linear strong correlation between temperature and Temperature-Humidity Index values, where the values ​​of correlation coefficients ranged between (0.996) – (0.997), while the correlation was inversely strong between relative humidity and Temperature-Humidity Index values where the values ​​of correlation coefficients ranged between (-0.985) – (-0.959) in the study stations, this indicates that the increase in the value of temperature and decrease relative humidity leads to an increase in the values of the Temperature-Humidity Index, and vice versa.

Decadal Surface Temperature Trends in Iraq using NOAA/ESRL Gridded High Resolution Data

Global warming has major impacts on world environment and human activities and it has been of increasing concern by scientific community, governmental agencies, and public. Iraq as one of the Middle East countries is vulnerable to global warming. Recent research works indicated that Iraq is facing an increasing heat waves and more aridity. The aim of this work is to analyze long-term temperature (1900-2017) to determine the warming and cooling phases at Mosul (north), Baghdad (center), Rutba (desert), and Basra (south). Gridded high-resolution monthly means of temperature were obtained from NOAA/ESRL. 30 years (1981-2010) available data from Iraqi Meteorological Organization were used to verify The NOAA/ESRL data. Results of comparisons of the two sets of data indicated that they are highly correlated. Time series analysis showed that the most effect of global warming on Iraq occurred on the decades of 2000’s and 2010’s during summer months (Jun, July, and Aug). The most affected cities were Baghdad and Basra. The less affected city was Rutba. Rutba is less populated town located on the desert near the borders with Jordan. Analysis of temperature decadal anomalies showed that from 1900’s to 1980’s temperature was cooling with anomalies between 0 and -0.5°C (except during 1960’s anomalies were less than +0.25). The results also indicated that during the last three decades (1990’s to 2010’s) temperature was warming and the highest warming (about +1.5 °C) occurred during last eight years (2010-2017) in all four cities.