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(a) 1000 hPa height (contours), vorticity (5×10S−1−5) (shaded), and wind flow (m/s) (vectors). (b) 850 hPa height, vorticity (5×10S−1−5), and wind flow (m/s). (c) 700 hPa height (hPa), vorticity (5×10S−1−5), and wind flow (m/s). (d) 500 hPa height, vorticity (5×10S−1−5), and wind flow (m/s).
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In this study, precipitation data for 483 synoptic stations, and the U&V component of wind and HGT data for 4 atmospheric levels were respectively obtained from IRIMO and NCEP/NCAR databases (1961–2013). The precipitation threshold of 1 mm and a minimum prevalence of 50% were the criteria based on which the prevalent precipitation of Iran was ident...
Citations
... By capturing moisture dynamics at different depths, stationary measurements offer insights into vertical water movement, root zone moisture distribution, and soil moisture variability across various landscapes (Kafarski et al., 2019). However, at the present time drought and flood monitoring is often based on remote sensing rainfall images provided by satellites as a viable substitute for conventional measurements and meteorological data (Gupta et al., 2020;Rousta et al., 2018). ...
... In cluster analysis, data are grouped based on the distance or similarity between them. Several methods exist to measure the distance between data, with the Euclidean distance [71,72] being one of the most widely used. In this study, Ward's method was employed for clustering and the Euclidean distance method was used to measure the similarity and distance between the data. ...
The accurate recognition of atmospheric circulation patterns is vital for understanding the intricate relationships among various climatic elements. Therefore, the main goal of this study is to comprehensively identify circulation patterns during the occurrence of the summertime Extended Area Precipitation Event (EAPE) in southeastern Iran. The data used in this study encompass precipitation rates from synoptic and rain gauge stations, Geopotential Height (GPH), omega (upward motion speed), u-wind (east-west), and v-wind (north-south) components at different atmospheric levels, along with satellite images from the visible spectrum. In this research, both subjective and objective clustering methods have been utilized to identify synoptic circulation patterns based on 500-hPa GPH data. Summer precipitation was chosen for analysis because its characteristics and relationships with large-scale circulation patterns are less understood compared to those of winter precipitation. Examination of the 500-hPa GPH data for sixty-two identified cases of EAPE over southeast Iran revealed that the causative factors for these events are comprised of five recurring patterns (referred to here for convenience as AP, BP, CP, DP, and EP). Three of these patterns (AP, BP, and DP) significantly contributed to 71% of all EAPE cases. It was evident that the five patterns responsible for creating the EAPE in southeastern Iran had distinct directions.
... In mid-latitudes at the synoptic scale, the important dynamic properties are those which are related to rotation (Soltani et al. 2014). Precipitation analyses have been done worldwide focusing on the role of vorticity and the circulations within pressure systems that produce severe storms (Jenkinson and Collison1977;Rousta et al. 2018). Since convergence leads to upward movement, some studies have investigated vorticity advection, divergence, and vertical motions in association with upper-level jet streams as triggers for the development of surface low-pressure systems (Jones et al. 1993;Conway and Jones 1998;Trigo and Dacamara 2000). ...
This study is aimed at investigating and identifying dominant flood-inducing mechanisms in western and southwestern Iran. For this purpose, the data of dynamic-synoptic components 11–14 April 2016, including total rainfall, sea level pressure, geopotential heights, the jet stream, potential vorticity at 250 hPa, the Omega index at 500 hPa, moisture flux convergence (MFC) at 1000 hPa, Convective Available Potential Energy (CAPE), were used for revealing the mechanisms of heavy rainfall events. On the other hand, Meteosat-7 satellite images were used to identify cloud type in the study area. The results showed that the main cause of the heavy rainfall was the formation of Mediterranean low and high pressure on the Aral Lake in the sea level and the presence of an upper-level cut-off low core over the northeastern Mediterranean and the study area. Moreover, analysis of MFC indicated that heavy rainfall moisture sources had been supplied from the Mediterranean, Red, and Arabian seas, respectively. Based on CAPE maps, the core of the maximum potential of convective energy is drawn as a line along the southwest-northeast from the Red Sea to the west of Iran. Meteosat-7 satellite images indicated that cumulonimbus clouds covered the study area during 11–14 April 2016. These results highlight that the intrusion of the southern polar vortex and its flux over the eastern Mediterranean and the Red Sea provides the conditions for cyclogenesis. The results of this study could serve as a guideline for monitoring and predicting heavy rainfall.
... Each unit is composed of 8 cars, offering a large capacity currently being are in operation94 stations on seven lines, with a total route of 273 kilometers in its railway network. Its lines connect 23 cities of Greater São Paulo transporting daily about 2.9 million passengers [19]. ...
The Regiotram de Occidente It has been one of the largest innovations and development projects for the department of Cundinamarca in Colombia, since over the years and due to the great growth of the population in the area of influence of this sector of the country, transport of the inhabitants has caused great conflict, that is why this book chapter will demonstrate how the environmental impact assessment is related and its direct relationship with the sustainable development objectives (SDG) in the execution and construction of high impact for the environment in this sector of the country (Colombia), planting the relationship that this has with Latin American trains.
... At 06 UTC 21 January 2013, the southern and central Yellow Sea, which was in front of the trough on the 850 hPa level, was controlled by the warm advection. Warm advection can bring abundant water vapor to a region [36]. The Bohai Sea and northern Yellow Sea were located behind the trough. ...
Sea fog is one of the main types of dangerous weather affecting offshore operations. The sea surface temperature (SST) has an important influence on the water vapor content and intensity of sea fog. In order to study the impact of SST on local relative humidity and atmospheric visibility, a sea fog episode that occurred over the Yellow Sea and Bohai Sea on 21 January 2013 was investigated through observational data, reanalysis data, and Weather Research and Forecasting (WRF) simulation. The results show that the influence of SST on the distribution of sea fog with different properties is inconsistent. Based on the time-varying equation of relative humidity, the changes in the advection, radiation, and turbulence effects on the relative humidity with respect to SST are explored through control and sensitivity experiments. The results show that the advection effect plays a decisive role in the generation and dissipation stages of sea fog. The increase (decrease) in SST weakens (strengthens) the radiative cooling and relative humidity. The contribution magnitude of advection effect to relative humidity is 10−5, while those of radiation and turbulence are 10−6 and 10−7, respectively. The atmospheric visibilities in the Bohai Sea and northern Yellow Sea decrease with increasing SST, which are mainly affected by the positive turbulence effect; whereas the atmospheric visibility in the central and southern Yellow Sea increases with SST, which is mainly influenced by the combined effects of U-direction advection, radiation, and turbulence. The stability related to boundary layer height plays an important role in water vapor condensation.
... The water that falls to the ground as hail, sleet, rain, mist, or snow is referred to as precipitation (Driscoll et al., 2003;Li et al., 2021). It is an important climate parameter that's been used to investigate the trend and variability of hydrometeorological occurrences (DasGupta and Shaw, 2015;Rousta et al., 2017;Rousta et al., 2018). Variability in precipitation is defined as a variation in the amount of precipitation that falls naturally in a certain area. ...
The Climate Hazard Group InfraRed Precipitation with Stations (CHIRPS) dataset was examined for its variability and performance in explaining precipitation variations, forecasting, and drought monitoring in Southeast Asia (SEA) for the period of 1981–2020. By using time-series analysis, the Standardized Precipitation Index (SPI), and the Autoregressive Integrated Moving Average (ARIMA) model this study established a data-driven approach for estimating the future trends of precipitation. The ARIMA model is based on the Box Jenkins approach, which removes seasonality and keeps the data stationary while forecasting future patterns. Depending on the series, ARIMA model annual estimates can be read as a blend of recent observations and long-term historical trend. Methods for determining 95 percent confidence intervals for several SEA countries and simulating future annual and seasonal precipitation were developed. The results illustrates that Bangladesh and Sri Lanka were chosen as the countries with the greatest inaccuracies. On an annual basis, Afghanistan has the lowest Mean Absolute Error (MAE) values at 33.285 mm, while Pakistan has the highest at 35.149 mm. It was predicted that these two countries would receive more precipitation in the future as compared to previous years.
... The convectional rainfall of the monsoon adds up to the relief rainfall caused due to existence of the Himalayas in the North (Bookhagen and Burbank 2010). Also, atmospheric blockings affect the rainfall anomalies, climate variability, and land surface temperature significantly (Rousta et al. 2014(Rousta et al. , 2018) that may trigger inundation and waterlogging conditions. Optical satellite remote-sensing technology usually fails to capture imageries of monsoon in Asia due to dense cloud cover and an overcast situation in the atmosphere (Qadir and Mondal 2020). ...
... The convectional rainfall of the monsoon adds up to the relief rainfall caused due to existence of the Himalayas in the North (Bookhagen and Burbank 2010). Also, atmospheric blockings affect the rainfall anomalies, climate variability, and land surface temperature significantly (Rousta et al. 2014(Rousta et al. , 2018) that may trigger inundation and waterlogging conditions. Optical satellite remote-sensing technology usually fails to capture imageries of monsoon in Asia due to dense cloud cover and an overcast situation in the atmosphere (Qadir and Mondal 2020). ...
Delineating a flood map is critical to perceive the potential risks of the event at diverse communities living both in urban and rural settings in Bangladesh. A timely generated flood map can help determine the losses of properties, calculate payment options from insurances, and set up mitigation measures when required. Application of satellite remote sensing (RS) and geographic information systems (GIS) are common these days to determine inundated areas, and to calculate possible losses of economies at scale. However, challenges remain while considering the available options for collecting satellite imageries obtained during the monsoon season with more than 70% cloud coverages found in the data. As a result, active synthetic aperture radar (SAR) sensors are a better choice to utilize the data in delineating the inundated areas. In doing so, this scientific paper sets up a few objectives to (1) prepare a flood map of Bangladesh using SAR remote-sensing data available from Sentinel-1 satellite; and (2) generate the inundated maps using cloud-based product, i.e., Google Earth Engine (GEE) in categorizing flood-affected districts of Bangladesh in 2020. Results have demonstrated that approximately 11% area of Bangladesh has been affected by the 2020 flood mainly located in the north-central and north-eastern part of the country. Moreover, the old Brahmaputra floodplain, Tista floodplain, lower Ganges-River floodplain, and Karataya-Bangali floodplain have been severely affected by the flood. Note that, the GEE-based automated processing systems adopted in this study have enhanced the computational time while obtaining freely available satellite data to generate mitigation strategies for the betterment of the communities suffered by the flood event.
... On the other hand, the simultaneous occurrence of a cyclonic circulation to the north and a convergent flow of humidity in the southern parts of Iraq, Kuwait, and part of Saudi Arabia led to the formation of the cold front ( Figure 7) and deep convections in the study area, which in turn may be a cause for the formation of a squall line longer than 100 km ( Figure 5 (top)). It was already shown that when the mid-level winds are close to geostrophic and show strong vorticity, ideal conditions for frontogenesis formation occurs [34][35][36]. ...
... On the other hand, the simultaneous occurrence of a cyclonic circulation to the north and a convergent flow of humidity in the southern parts of Iraq, Kuwait, and part of Saudi Arabia led to the formation of the cold front ( Figure 7) and deep convections in the study area, which in turn may be a cause for the formation of a squall line longer than 100 km ( Figure 5 (top)). It was already shown that when the midlevel winds are close to geostrophic and show strong vorticity, ideal conditions for frontogenesis formation occurs [34][35][36]. The radar images (top panel of Figure 5) show that the thickness of the cumulonimbus clouds in the huge convection cell was approximately 15 km and their base was about 1 km a.s.l. ...
Severe thunderstorms are often accompanied by strong vertical air currents, temporary wind gusts, and heavy rainfall. The development of this atmospheric phenomenon over tropical shallow water zones, such as bays, can lead to intensification of atmospheric disturbances and produce a small-scale storm surge. Here, the storm surge that occurred on 19 March 2017 in the Persian Gulf coastal area has been investigated. Air temperature, precipitation, mean sea level pressure, wave height, wind direction, wind speed, geopotential height, zonal components, meridional winds, vertical velocity, relative humidity, and specific humidity obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Global Forecast System (FNL) were used to implement the Weather Research and Forecasting (WRF) model. The results showed that the main cause of the storm surge was the occurrence of a supercell thunderstorm over the Persian Gulf. The formation of this destructive phenomenon resulted from a downburst under Cumulonimbus cloud and high-velocity air subsidence, after collision with the sea surface coinciding with the high tide. This caused a severe, yet temporary, gust, which in turn caused the creation of the four waves of 3.1 m height along the coast of Bandar Dayyer.
... On the other hand, the simultaneous occurrence of a cyclonic circulation to the north and a convergent flow of humidity in the southern parts of Iraq, Kuwait, and part of Saudi Arabia led to the formation of the cold front (Fig. 7a) and deep convections in the study area, which in turn may be a cause for the formation of squall line longer than 100 km (Fig. 5a). It was already shown that when the mid-level winds are close to geostrophic and show strong vorticity, the best condition of frontogenesis formation occurs [34][35][36]. From the radar images (top panel of Fig 5) it results that the thickness of Cumulonimbus clouds in the huge convection cell was approximately 15 km and their base was about 1 km a.s.l. The severe subsidence of cold air under clouds (downburst) and its collision with warm air near the ground caused the creation of a gusty front. ...
Severe thunderstorms are often accompanied by strong vertical air currents, temporary wind gusts, and heavy rainfall. The development of this atmospheric phenomenon over tropical shallow water zones, such as bays, can lead to intensification of atmospheric disturbances and produce a small-scale storm surge. Here, the storm surge that occurred on 19 March 2017 in the Persian Gulf coastal area has been investigated. Air temperature, precipitation, mean sea level pressure, wave height, wind direction, wind speed, geopotential height, zonal components, meridional winds, vertical velocity, relative humidity, and specific humidity obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF (and Global Forecast System (FNL) were used to implement the Weather Research and Forecasting (WRF) model. The results showed that the main cause of the storm surge was the occurrence of a supercell thunderstorm over the Persian Gulf. The formation of this destructive phenomenon resulted from a downburst under Cumulonimbus cloud and high-velocity air subsidence, after collision with the sea surface coinciding with the high tide. This caused a severe, yet temporary, gust, which in turn caused the creation of the four waves of 3.1 m height along the coast of Bandar Dayyer.
... The northern and western parts of the study area are located in the pathway of the westerlies (anti-trades, that is, steady prevailing winds that blow from the west toward the east and overlie the trade winds) [117,118]. The main factors affecting the atmospheric dynamics are westerlies and the large water bodies (Black, Mediterranean, and Caspian seas), which supply the water vapor; therefore, these areas contain the densest vegetation in the ME [119][120][121][122]. ...
The spatiotemporal variability of vegetation in the Middle East was investigated for the period 2001–2019 using the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day/500 m composites of the Normalized Difference Vegetation Index (NDVI; MOD13A1). The results reveal a strong increase in the NDVI coverage in the Middle East during the study period (R = 0.75, p-value = 0.05). In Egypt, the annual coverage exhibits the strongest positive trend (R = 0.99, p-value = 0.05). In Turkey, both the vegetation coverage and density increased from 2001 to 2019, which can be attributed to the construction of some of the biggest dams in the Middle East, such as the Atatürk and Ilisu dams. Significant increases in the annual coverage and maximum and average NDVI in Saudi Arabia are due to farming in the northern part of the country for which groundwater and desalinated seawater are used. The results of this study suggest that the main factors affecting the vegetation coverage in the Middle East are governmental policies. These policies can have a positive effect on the vegetation coverage in some countries such as Egypt, Saudi Arabia, Qatar, Kuwait, Iran, and Turkey.
