scholarly journals Moisture Transport and Sources of the Extreme Precipitation Over Northern and Southern Xinjiang in the Summer Half-Year During 1979–2018

2021 ◽  
Vol 9 ◽  
Author(s):  
Qin Hu ◽  
Yong Zhao ◽  
Anning Huang ◽  
Pan Ma ◽  
Jing Ming
Keyword(s):  
Central Asia ◽  
Extreme Precipitation ◽  
Arabian Sea ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Source Areas ◽  
Northern Xinjiang ◽  
Moisture Source ◽  
Summer Half ◽  
Southern Xinjiang

Based on the output data from the Lagrangian flexible particle dispersion model (FLEXPART), we analyze the pathways of moisture to identify the moisture source areas for extreme precipitation in the summer half-year (April–September) over northern and southern Xinjiang, respectively. For both northern and southern Xinjiang, the local evaporation plays a decisive role for extreme precipitation in the summer half-year, of which contribution ratio accounts for 24.5% to northern Xinjiang and 30.2% to southern Xinjiang of all identified source areas. In addition, central Asia and northwestern Asia are the major moisture source areas as well and contribute similarly to extreme precipitation relative to local evaporation. For northern Xinjiang, central Asia surpasses northwestern Asia, and each of them contributes 24.1 and 18.8%, whereas northwestern Asia is somewhat more crucial than central Asia for southern Xinjiang, accounting 22.1 and 19.1%, respectively. Note that the three top-ranked moisture source areas make up a large proportion of total sources. Regarding the remaining source areas that also provide moisture, the contributions are entirely different for southern and northern Xinjiang. Originating from the North Atlantic Ocean, Europe, and the Mediterranean Sea, some water vapor enters northern Xinjiang and converge to precipitate, while this process is barely detectable for extreme precipitation over southern Xinjiang, which is affected by the westerly flow. On the contrary, the Arabian Sea, the Arabian Peninsula, and the Indian Peninsula contribute, even though slightly, to extreme precipitation over southern Xinjiang, which indicates that the meridional transport pathways from the Arabian Sea can carry moisture to this inland region.

scholarly journals An Analysis of Moisture Sources of Torrential Rainfall Events over Xinjiang, China

2019 ◽  
Vol 20 (10) ◽  
pp. 2109-2122 ◽  
Author(s):  
Yu-shu Zhou ◽  
Ze-ming Xie ◽  
Xin Liu
Keyword(s):  
Water Vapor ◽  
Central Asia ◽  
Dispersion Model ◽  
Source Area ◽  
Particle Dispersion ◽  
Rainfall Events ◽  
Moisture Source ◽  
Moisture Sources ◽  
North Asia ◽  
Torrential Rainfall

Abstract Water vapor is a primary rainfall source for the development of torrential rainfall events. By using a Lagrangian flexible particle dispersion model (FLEXPART), the water vapor transports associated with torrential rainfall over Xinjiang, China, during April–September of 2008–15 are examined in this study. The results show that water vapor related to torrential rainfall events is mostly transported by westerly winds. The moisture sources for the development of torrential rainfall over four areas (Altay, Ili Valley, Hami, and Aksu-Kashgar) are mainly from Xinjiang and central Asia. The north Asia area and the Mediterranean/Black/Caspian Sea region are also important contributors to moisture source over the Altay area. Over Ili Valley, both the central Asia area and Xinjiang contribute 40% of water vapor to rainfall sources. Over the Hami area, 70% of the moisture source is from the Xinjiang. Over the Aksu-Kashgar area, the central Asia region is the most important moisture source area.

Moisture sources of heavy precipitation in Xinjiang characterized by meteorological patterns

2021 ◽  
Author(s):  
Shibo Yao ◽  
Dabang Jiang ◽  
Zhongshi Zhang
Keyword(s):  
Central Asia ◽  
Dispersion Model ◽  
Source Region ◽  
Heavy Precipitation ◽  
Particle Dispersion ◽  
Tianshan Mountains ◽  
Wet Season ◽  
Moisture Source ◽  
Kunlun Mountains ◽  
South Central

AbstractIn this study, the FLEXible PARTicle dispersion model (FLEXPART) is applied to determine the moisture source of heavy precipitation in Xinjiang in the wet season (April–September) from 1979 to 2018. This is investigated for different meteorological patterns of heavy precipitation categories based on the self-organizing maps (SOM) method. The SOM results suggest that there are four main meteorological patterns (N1, N2, N3 and N4) for heavy precipitation in Xinjiang. These match the strength and position of geopotential height anomalies at middle-high levels over Central Asia and indicate the anomalous activities of the Central Asia trough and vortex. Further analysis shows that the heavy precipitation is centered at the Tianshan Mountains and the Kunlun Mountains in the N1 and N3 patterns and around the Tianshan Mountains in the N2 and N4 patterns. There are four moisture source regions that contribute to each of the four meteorological patterns for heavy precipitation in Xinjiang, which are listed in descending order of their contribution rates: southern Xinjiang (29–37%), North–Central Asia (19–27%), northern Xinjiang (14–19%), and South–Central Asia (13–16%). The contribution of each source to the heavy precipitation in Xinjiang varies with the meteorological pattern. Additionally, the contribution rates of each source region match well with the precipitation-related particle aggregation before heavy precipitation days. These results help us better understand the moisture source of the heavy precipitation in Xinjiang.

scholarly journals Identification of Long-Range Transport Pathways and Potential Source Regions of PM2.5 and PM10 at Akedala Station, Central Asia

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1183
Author(s):  
Hanlin Li ◽  
Qing He ◽  
Xinchun Liu
Keyword(s):  
Central Asia ◽  
Transport Pathways ◽  
Air Masses ◽  
Source Areas ◽  
Northern Xinjiang ◽  
Source Regions ◽  
Potential Source ◽  
Western Mongolia ◽  
Pm2.5 And Pm10 ◽  
Eastern Kazakhstan

Cluster analyses, potential source contribution function (PSCF) and concentration-weight trajectory (CWT) were used to identify the main transport pathways and potential source regions with hourly PM2.5 and PM10 concentrations in different seasons from January 2017 to December 2019 at Akedala Station, located in northwest China (Central Asia). The annual mean concentrations of PM2.5 and PM10 were 11.63 ± 9.31 and 19.99 ± 14.39 µg/m3, respectively. The air pollution was most polluted in winter, and the dominant part of PM10 (between 54 to 76%) constituted PM2.5 aerosols in Akedala. Particulate pollution in Akedala can be traced back to eastern Kazakhstan, northern Xinjiang, and western Mongolia. The cluster analyses showed that the Akedala atmosphere was mainly affected by air masses transported from the northwest. The PM2.5 and PM10 mainly came with air masses from the central and eastern regions of Kazakhstan, which are characterized by highly industrialized and semi-arid desert areas. In addition, the analyses of the pressure profile of back-trajectories showed that air mass distribution were mainly distributed above 840 hPa. This indicates that PM2.5 and PM10 concentrations were strongly affected by high altitude air masses. According to the results of the PSCF and CWT methods, the main potential source areas of PM2.5 were very similar to those of PM10. In winter and autumn, the main potential source areas with high weighted PSCF values were located in the eastern regions of Kazakhstan, northern Xinjiang, and western Mongolia. These areas contributed the highest PM2.5 concentrations from 25 to 40 µg/m3 and PM10 concentrations from 30 to 60 µg/m3 in these seasons. In spring and summer, the potential source areas with the high weighted PSCF values were distributed in eastern Kazakhstan, northern Xinjiang, the border between northeast Kazakhstan, and southern Russia. These areas contributed the highest PM2.5 concentrations from 10 to 20 µg/m3 and PM10 concentrations from 20 to 60 µg/m3 in these seasons.

scholarly journals The Identification of Iran’s Moisture Sources Using a Lagrangian Particle Dispersion Model

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 408 ◽  
Author(s):  
Mojtaba Heydarizad ◽  
Ezzat Raeisi ◽  
Rogert Sori ◽  
Luis Gimeno
Keyword(s):  
Mediterranean Sea ◽  
Persian Gulf ◽  
Arabian Sea ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Dry Season ◽  
Wet Season ◽  
Moisture Sources ◽  
The Mediterranean ◽  
The Persian Gulf

Iran has faced many water shortage crises in the past. Iran’s moisture sources for precipitation were identified by Lagrangian approach using the FLEXible PARTicle dispersion model (FLEXPART) v9.0 model. The results demonstrate that Iran receives its moisture from both continental and oceanic sources. During the wet season, moisture uptake from the Arabian Sea, the Persian Gulf, and the Mediterranean Sea is dominant, while during the dry season, the role of the Red Sea, the Caspian Sea, and the Persian Gulf is intensified. Studying drought conditions by comparing 1-month, 6-month, and 12-month standardized precipitation index (SPI) with (E-P) values of oceanic and continental moisture sources (E stands for the evaporation and P the precipitation) using multiregression model demonstrates that among oceanic sources the Arabian Sea, the Persian Gulf, the Mediterranean Sea, and the Indian Ocean affect SPI values and among continental sources, moisture from bare grounds and cultivated lands influences SPI values during wet season. However, no correlation exists between oceanic and continental (E-P) and SPI values during the dry season. The results obtained by this study can be used by meteorologists and hydrology scientists for future water management programmes in Iran.

scholarly journals Large-Scale Atmospheric Dispersal Simulations Identify Likely Airborne Incursion Routes of Wheat Stem Rust Into Ethiopia

2017 ◽  
Vol 107 (10) ◽  
pp. 1175-1186 ◽  
Author(s):  
M. Meyer ◽  
L. Burgin ◽  
M. C. Hort ◽  
D. P. Hodson ◽  
C. A. Gilligan
Keyword(s):  
Stem Rust ◽  
Large Scale ◽  
Dispersion Model ◽  
Fungal Spores ◽  
Disease Outbreaks ◽  
Particle Dispersion ◽  
East African ◽  
Wheat Stem Rust ◽  
Sub Saharan ◽  
African Rift

In recent years, severe wheat stem rust epidemics hit Ethiopia, sub-Saharan Africa’s largest wheat-producing country. These were caused by race TKTTF (Digalu race) of the pathogen Puccinia graminis f. sp. tritici, which, in Ethiopia, was first detected at the beginning of August 2012. We use the incursion of this new pathogen race as a case study to determine likely airborne origins of fungal spores on regional and continental scales by means of a Lagrangian particle dispersion model (LPDM). Two different techniques, LPDM simulations forward and backward in time, are compared. The effects of release altitudes in time-backward simulations and P. graminis f. sp. tritici urediniospore viability functions in time-forward simulations are analyzed. Results suggest Yemen as the most likely origin but, also, point to other possible sources in the Middle East and the East African Rift Valley. This is plausible in light of available field surveys and phylogenetic data on TKTTF isolates from Ethiopia and other countries. Independent of the case involving TKTTF, we assess long-term dispersal trends (>10 years) to obtain quantitative estimates of the risk of exotic P. graminis f. sp. tritici spore transport (of any race) into Ethiopia for different ‘what-if’ scenarios of disease outbreaks in potential source countries in different months of the wheat season.

scholarly journals Atmospheric rivers moisture sources from a Lagrangian perspective

2016 ◽  
Vol 7 (2) ◽  
pp. 371-384 ◽  
Author(s):  
Alexandre M. Ramos ◽  
Raquel Nieto ◽  
Ricardo Tomé ◽  
Luis Gimeno ◽  
Ricardo M. Trigo ◽  
...  
Keyword(s):  
North Atlantic ◽  
Dispersion Model ◽  
Local Maximum ◽  
Detection Algorithm ◽  
Ocean Basin ◽  
Particle Dispersion ◽  
Western Coast ◽  
Moisture Uptake ◽  
Lagrangian Analysis ◽  
Data Set

Abstract. An automated atmospheric river (AR) detection algorithm is used for the North Atlantic Ocean basin, allowing the identification of the major ARs affecting western European coasts between 1979 and 2012 over the winter half-year (October to March). The entire western coast of Europe was divided into five domains, namely the Iberian Peninsula (9.75° W, 36–43.75° N), France (4.5° W, 43.75–50° N), UK (4.5° W, 50–59° N), southern Scandinavia and the Netherlands (5.25° E, 50–59° N), and northern Scandinavia (5.25° E, 59–70° N). Following the identification of the main ARs that made landfall in western Europe, a Lagrangian analysis was then applied in order to identify the main areas where the moisture uptake was anomalous and contributed to the ARs reaching each domain. The Lagrangian data set used was obtained from the FLEXPART (FLEXible PARTicle dispersion) model global simulation from 1979 to 2012 and was forced by ERA-Interim reanalysis on a 1° latitude–longitude grid. The results show that, in general, for all regions considered, the major climatological areas for the anomalous moisture uptake extend along the subtropical North Atlantic, from the Florida Peninsula (northward of 20° N) to each sink region, with the nearest coast to each sink region always appearing as a local maximum. In addition, during AR events the Atlantic subtropical source is reinforced and displaced, with a slight northward movement of the sources found when the sink region is positioned at higher latitudes. In conclusion, the results confirm not only the anomalous advection of moisture linked to ARs from subtropical ocean areas but also the existence of a tropical source, together with midlatitude anomaly sources at some locations closer to AR landfalls.

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