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.

scholarly journals Atmospheric rivers moisture transport from a Lagrangian perspective

2015 ◽  
Vol 6 (2) ◽  
pp. 2617-2643
Author(s):  
A. M. Ramos ◽  
R. Nieto ◽  
R. Tomé ◽  
L. Gimeno ◽  
R. M. Trigo ◽  
...  
Keyword(s):  
North Atlantic ◽  
Western Europe ◽  
North Atlantic Ocean ◽  
Local Maximum ◽  
Detection Algorithm ◽  
Ocean Basin ◽  
Lagrangian Analysis ◽  
Atmospheric Rivers ◽  
The North ◽  
The North Atlantic

Abstract. An automated atmospheric rivers (ARs) detection algorithm is used for the North Atlantic Ocean Basin allowing the identification of the major ARs that affected western European coasts between 1979 and 2014 over the winter half-year (October to March). The entire west 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 sources of moisture that reach each domain. The Lagrangian dataset used was obtained from the FLEXPART model global simulation from 1979 to 2012, where the atmosphere was divided into approximately 2.0 million parcels, and it was forced by ERA-Interim reanalysis on a 1° latitude–longitude grid. Results show that, in general, for all regions considered, the major climatological source of moisture extends 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 of evaporation. In addition, during the AR events, the Atlantic subtropical source is reinforced and displaced, with a slight northward movement of the moisture sources is found when the sink region is positioned at higher latitudes. In conclusion, the results confirm the advection of moisture linked to ARs from subtropical ocean areas, but also the existence of a tropical one, and the mid-latitude sources further the analysed longitude along the North Atlantic is located eastward.

scholarly journals Moisture Sources for the Explosive Cyclogenesis of Extratropical Cyclone Miguel (2019) through a Lagrangian Approach

2021 ◽  
Vol 8 (1) ◽  
pp. 19
Author(s):  
Patricia Coll-Hidalgo ◽  
Albenis Pérez-Alarcón ◽  
José Carlos Fernández-Alvarez ◽  
Raquel Nieto ◽  
Luis Gimeno
Keyword(s):  
Atlantic Ocean ◽  
North Atlantic ◽  
North Atlantic Ocean ◽  
Dispersion Model ◽  
Particle Dispersion ◽  
Eastern Coast ◽  
Moisture Uptake ◽  
Moisture Sources ◽  
The North ◽  
Uptake Pattern

In this study, the moisture sources for the explosive cyclogenesis Miguel that occurred during 4–9 June 2019 in the North Atlantic were investigated. To determine the moisture sources, the Lagrangian FLEXPART particle dispersion model was used. The moisture uptake pattern revealed the western North Atlantic Ocean extending to north-western North America, the south-eastern coast of Greenland, and the central North Atlantic Ocean around 45° N and 50°–20° W as the main moisture sources for Miguel explosive cyclogenesis. Furthermore, the moisture uptake from these regions was higher than the climatology. During the intensification of Miguel, the moisture contribution from oceanic sources was higher than terrestrial sources. Although the total amount of atmospheric moisture achieved during the explosive intensification was similar to that absorbed the 24 h prior, they changed in intensity geographically, being more intense the local support over central and northern North Atlantic basin.

scholarly journals North Atlantic Ocean–Atmosphere Driven Variations in Aerosol Evolution along Lagrangian Cold-Air Outbreak Trajectories

2021 ◽  
Author(s):  
Kevin J. Sanchez ◽  
Bo Zhang ◽  
Hongyu Liu ◽  
Matthew D. Brown ◽  
Ewan C. Crosbie ◽  
...  
Keyword(s):  
North Atlantic ◽  
Dispersion Model ◽  
Temporal Variations ◽  
Particle Dispersion ◽  
Rate Of Change ◽  
Data Set ◽  
Cold Air ◽  
Accumulation Mode ◽  
Cloud Properties ◽  
Cold Air Outbreak

Abstract. Atmospheric marine particle concentrations impact cloud properties, which strongly impact the amount of solar radiation reflected back into space or absorbed by the ocean surface. While satellites can provide a snapshot of current conditions at the overpass time, models are necessary to simulate temporal variations in both particle and cloud properties. However, poor model accuracy limits the reliability with which these tools can be used to predict future climate. Here, we leverage the comprehensive ocean ecosystem and atmospheric aerosol-cloud data set obtained during the third deployment of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES3). Airborne and ship-based measurements were collected in and around a cold-air outbreak during a three-day intensive operations period from September 17–19, 2017. Cold-air outbreaks are of keen interest for model validation because they are challenging to accurately simulate, which is due, in part, to the numerous feedbacks and sub-grid scale processes that influence aerosol and cloud evolution. The NAAMES observations are particularly valuable because the flight plans were tailored to lie along Lagrangian trajectories, making it possible to spatiotemporally connect upwind and downwind measurements with the state-of-the-art FLEXible PARTicle (FLEXPART) Lagrangian particle dispersion model and then calculate a rate of change in particle properties. Initial aerosol conditions spanning an east-west, closed-cell cloudy to clear air transition region of the cold-air outbreak indicate similar particle concentrations and properties. However, despite the similarities in the aerosol fields, the cloud properties downwind of each region evolved quite differently. One trajectory carried particles through a cold-air outbreak, resulting in a decrease in accumulation mode particle concentration (−42 %) and cloud droplet concentrations, while the other remained outside of the cold-air outbreak and experienced an increase in accumulation mode particle concentrations (+62 %). The variable meteorological conditions between these two adjacent trajectories result from differences in the local sea surface temperature altering stability of the marine atmospheric boundary layer because of the location of the Labrador Current. Further comparisons of historical satellite observations indicate that the observed pattern occurs annually in the region, making it an ideal location for future airborne Lagrangian studies tracking the evolution of aerosols and clouds over time under cold air outbreak conditions.

scholarly journals Current model capabilities for simulating black carbon and sulfate concentrations in the Arctic atmosphere: a multi-model evaluation using a comprehensive measurement data set

2015 ◽  
Vol 15 (16) ◽  
pp. 9413-9433 ◽  
Author(s):  
S. Eckhardt ◽  
B. Quennehen ◽  
D. J. L. Olivié ◽  
T. K. Berntsen ◽  
R. Cherian ◽  
...  
Keyword(s):  
Black Carbon ◽  
Atmospheric Chemistry ◽  
Emission Inventory ◽  
Dispersion Model ◽  
Measurement Data ◽  
Particle Dispersion ◽  
The Arctic ◽  
Late Winter ◽  
Data Set ◽  
Arctic Haze

Abstract. The concentrations of sulfate, black carbon (BC) and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality and especially the high concentrations associated with Arctic Haze. In this study, we evaluate sulfate and BC concentrations from eleven different models driven with the same emission inventory against a comprehensive pan-Arctic measurement data set over a time period of 2 years (2008–2009). The set of models consisted of one Lagrangian particle dispersion model, four chemistry transport models (CTMs), one atmospheric chemistry-weather forecast model and five chemistry climate models (CCMs), of which two were nudged to meteorological analyses and three were running freely. The measurement data set consisted of surface measurements of equivalent BC (eBC) from five stations (Alert, Barrow, Pallas, Tiksi and Zeppelin), elemental carbon (EC) from Station Nord and Alert and aircraft measurements of refractory BC (rBC) from six different campaigns. We find that the models generally captured the measured eBC or rBC and sulfate concentrations quite well, compared to previous comparisons. However, the aerosol seasonality at the surface is still too weak in most models. Concentrations of eBC and sulfate averaged over three surface sites are underestimated in winter/spring in all but one model (model means for January–March underestimated by 59 and 37 % for BC and sulfate, respectively), whereas concentrations in summer are overestimated in the model mean (by 88 and 44 % for July–September), but with overestimates as well as underestimates present in individual models. The most pronounced eBC underestimates, not included in the above multi-site average, are found for the station Tiksi in Siberia where the measured annual mean eBC concentration is 3 times higher than the average annual mean for all other stations. This suggests an underestimate of BC sources in Russia in the emission inventory used. Based on the campaign data, biomass burning was identified as another cause of the modeling problems. For sulfate, very large differences were found in the model ensemble, with an apparent anti-correlation between modeled surface concentrations and total atmospheric columns. There is a strong correlation between observed sulfate and eBC concentrations with consistent sulfate/eBC slopes found for all Arctic stations, indicating that the sources contributing to sulfate and BC are similar throughout the Arctic and that the aerosols are internally mixed and undergo similar removal. However, only three models reproduced this finding, whereas sulfate and BC are weakly correlated in the other models. Overall, no class of models (e.g., CTMs, CCMs) performed better than the others and differences are independent of model resolution.

scholarly journals Current model capabilities for simulating black carbon and sulfate concentrations in the Arctic atmosphere: a multi-model evaluation using a comprehensive measurement data set

2015 ◽  
Vol 15 (7) ◽  
pp. 10425-10477 ◽  
Author(s):  
S. Eckhardt ◽  
B. Quennehen ◽  
D. J. L. Olivié ◽  
T. K. Berntsen ◽  
R. Cherian ◽  
...  
Keyword(s):  
Black Carbon ◽  
Atmospheric Chemistry ◽  
Emission Inventory ◽  
Dispersion Model ◽  
Measurement Data ◽  
Particle Dispersion ◽  
The Arctic ◽  
Late Winter ◽  
Data Set ◽  
Arctic Haze

Abstract. The concentrations of sulfate, black carbon (BC) and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality and especially the high concentrations associated with Arctic Haze. In this study, we evaluate sulfate and BC concentrations from eleven different models driven with the same emission inventory against a comprehensive pan-Arctic measurement data set over a time period of two years (2008–2009). The set of models consisted of one Lagrangian particle dispersion model, four chemistry-transport models (CTMs), one atmospheric chemistry-weather forecast model and five chemistry-climate models (CCMs), of which two were nudged to meteorological analyses and three were running freely. The measurement data set consisted of surface measurements of equivalent BC (eBC) from five stations (Alert, Barrow, Pallas, Tiksi and Zeppelin), elemental carbon (EC) from Station Nord and Alert and aircraft measurements of refractory BC (rBC) from six different campaigns. We find that the models generally captured the measured eBC/rBC and sulfate concentrations quite well, compared to past comparisons. However, the aerosol seasonality at the surface is still too weak in most models. Concentrations of eBC and sulfate averaged over three surface sites are underestimated in winter/spring in all but one model (model means for January-March underestimated by 59 and 37% for BC and sulfate, respectively), whereas concentrations in summer are overestimated in the model mean (by 88 and 44% for July–September), but with over- as well as underestimates present in individual models. The most pronounced eBC underestimates, not included in the above multi-site average, are found for the station Tiksi in Siberia where the measured annual mean eBC concentration is three times higher than the average annual mean for all other stations. This suggests an underestimate of BC sources in Russia in the emission inventory used. Based on the campaign data, biomass burning was identified as another cause of the modelling problems. For sulfate, very large differences were found in the model ensemble, with an apparent anti-correlation between modeled surface concentrations and total atmospheric columns. There is a strong correlation between observed sulfate and eBC concentrations with consistent sulfate/eBC slopes found for all Arctic stations, indicating that the sources contributing to sulfate and BC are similar throughout the Arctic and that the aerosols are internally mixed and undergo similar removal. However, only three models reproduced this finding, whereas sulfate and BC are weakly correlated in the other models. Overall, no class of models (e.g., CTMs, CCMs) performed better than the others and differences are independent of model resolution.

scholarly journals The A-LIFE field experiment in the Eastern Mediterranean - Overview and selected highlights 

2021 ◽  
Author(s):  
Bernadett Weinzierl ◽  
Keyword(s):  
Field Experiment ◽  
Field Experiments ◽  
Dispersion Model ◽  
Eastern Mediterranean ◽  
Particle Dispersion ◽  
Saharan Dust ◽  
Aerosol Layer ◽  
Particle Removal ◽  
Data Set ◽  
Coarse Mode

<p>In April 2017, the A-LIFE aircraft field experiment (Absorbing aerosol layers in a changing climate: aging, lifetime and dynamics; (www.a-life.at) was carried out in the Eastern Mediterranean. The overall goal of the ERC-funded A-LIFE project is to investigate the properties of mixtures of absorbing aerosols (in particular mineral dust and black carbon) during their atmospheric lifetime to gather a new data set of key parameters of absorbing aerosol mixtures, to investigate their microphysical and optical properties, and to study potential links between the presence of absorbing particles, aerosol layer lifetime and particle removal.</p><p>In 22 research flights (~80 flight hours), several outbreaks of Saharan and Arabian dust, as well as pollution, biomass burning, and dust-impacted clouds were studied, and a unique aerosol and cloud data set was collected. During a number of flights, coordinated observations including overflights of the ground-based sites in Cyprus (Limassol, Paphos, Agia Marina), Crete (Finokalia), and over Austria (Vienna, Sonnblick Observatory) were performed. The A-LIFE campaign was carried out in close coordination with the 18-month field observations conducted in the framework of CyCARE (October 2016 – March 2018) organized by the Leibniz Institute for Tropospheric Research, and with the PreTECT initiative of the National Observatory of Athens.</p><p>To perform source apportionment, the Lagrangian transport and dispersion model FLEXPART (FLEXible PARTicle dispersion model) version 8.2 was used. Based on FLEXPART model results and aerosol measurements, the observations were classified into 12 aerosol types including background aerosol, clean and polluted mixtures without coarse mode aerosol as well as three sub-classes (clean, moderately-polluted and polluted) for Saharan dust, Arabian dust and mixtures with coarse mode. For each of the 12 aerosol classes, microphysical and optical aerosol properties were derived. One surprising finding of A-LIFE is that scattering properties of polluted dust aerosol do not show the typical dust signature, but rather show a wavelength-dependency of the scattering coefficient.</p><p>We will give an overview of the A-LIFE field experiment and available data sets, compare the properties of the different aerosol mixtures, and discuss the question which aerosol component (natural vs. anthropogenic) dominates the properties in mixed aerosols. We will also compare the A-LIFE dust observations with results from other field experiments (SAMUM, SALTRACE, ATom).</p><p> </p><p>Acknowledgements: This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 640458 (A-LIFE). Two EUFAR projects clustered with A-LIFE provided funding for 16 additional flight hours. We would also like to thank the University of Vienna, LMU and DLR for a significant amount of funding for instrumentation, aircraft certification costs, extra flight hours and aircraft allocation days.</p>

scholarly journals Temporally delineated sources of major chemical species in high Arctic snow

2018 ◽  
Vol 18 (5) ◽  
pp. 3485-3503 ◽  
Author(s):  
Katrina M. Macdonald ◽  
Sangeeta Sharma ◽  
Desiree Toom ◽  
Alina Chivulescu ◽  
Andrew Platt ◽  
...  
Keyword(s):  
Black Carbon ◽  
Carboxylic Acids ◽  
Major Ions ◽  
Dispersion Model ◽  
High Arctic ◽  
Particle Dispersion ◽  
Photochemical Reactions ◽  
Sea Salt ◽  
The Arctic ◽  
Data Set

Abstract. Long-range transport of aerosol from lower latitudes to the high Arctic may be a significant contributor to climate forcing in the Arctic. To identify the sources of key contaminants entering the Canadian High Arctic an intensive campaign of snow sampling was completed at Alert, Nunavut, from September 2014 to June 2015. Fresh snow samples collected every few days were analyzed for black carbon, major ions, and metals, and this rich data set provided an opportunity for a temporally refined source apportionment of snow composition via positive matrix factorization (PMF) in conjunction with FLEXPART (FLEXible PARTicle dispersion model) potential emission sensitivity analysis. Seven source factors were identified: sea salt, crustal metals, black carbon, carboxylic acids, nitrate, non-crustal metals, and sulfate. The sea salt and crustal factors showed good agreement with expected composition and primarily northern sources. High loadings of V and Se onto Factor 2, crustal metals, was consistent with expected elemental ratios, implying these metals were not primarily anthropogenic in origin. Factor 3, black carbon, was an acidic factor dominated by black carbon but with some sulfate contribution over the winter-haze season. The lack of K+ associated with this factor, a Eurasian source, and limited known forest fire events coincident with this factor's peak suggested a predominantly anthropogenic combustion source. Factor 4, carboxylic acids, was dominated by formate and acetate with a moderate correlation to available sunlight and an oceanic and North American source. A robust identification of this factor was not possible; however, atmospheric photochemical reactions, ocean microlayer reaction, and biomass burning were explored as potential contributors. Factor 5, nitrate, was an acidic factor dominated by NO3−, with a likely Eurasian source and mid-winter peak. The isolation of NO3− on a separate factor may reflect its complex atmospheric processing, though the associated source region suggests possibly anthropogenic precursors. Factor 6, non-crustal metals, showed heightened loadings of Sb, Pb, and As, and correlation with other metals traditionally associated with industrial activities. Similar to Factor 3 and 5, this factor appeared to be largely Eurasian in origin. Factor 7, sulfate, was dominated by SO42− and MS with a fall peak and high acidity. Coincident volcanic activity and northern source regions may suggest a processed SO2 source of this factor.

Monthly satellite-derived phytoplankton pigment distribution for the North Atlantic Ocean basin

Eos ◽  
1986 ◽  
Vol 67 (44) ◽  
pp. 835 ◽  
Author(s):  
W. E. Esaias ◽  
G. C. Feldman ◽  
C. R. McClain ◽  
J. A. Elrod
Keyword(s):  
Atlantic Ocean ◽  
North Atlantic ◽  
North Atlantic Ocean ◽  
Ocean Basin ◽  
Phytoplankton Pigment ◽  
The North ◽  
Pigment Distribution ◽  
The North Atlantic

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 Pedestrian detection algorithm in traffic scene based on weakly supervised hierarchical deep model

2016 ◽  
Vol 14 (1) ◽  
pp. 172988141769231 ◽  
Author(s):  
Yingfeng Cai ◽  
Youguo He ◽  
Hai Wang ◽  
Xiaoqiang Sun ◽  
Long Chen ◽  
...  
Keyword(s):  
Deep Learning ◽  
Pedestrian Detection ◽  
Recognition Rate ◽  
Detection Algorithm ◽  
Training Methods ◽  
Two Dimensional ◽  
Data Set ◽  
Deep Model ◽  
Unsupervised Training ◽  
Weakly Supervised

The emergence and development of deep learning theory in machine learning field provide new method for visual-based pedestrian recognition technology. To achieve better performance in this application, an improved weakly supervised hierarchical deep learning pedestrian recognition algorithm with two-dimensional deep belief networks is proposed. The improvements are made by taking into consideration the weaknesses of structure and training methods of existing classifiers. First, traditional one-dimensional deep belief network is expanded to two-dimensional that allows image matrix to be loaded directly to preserve more information of a sample space. Then, a determination regularization term with small weight is added to the traditional unsupervised training objective function. By this modification, original unsupervised training is transformed to weakly supervised training. Subsequently, that gives the extracted features discrimination ability. Multiple sets of comparative experiments show that the performance of the proposed algorithm is better than other deep learning algorithms in recognition rate and outperforms most of the existing state-of-the-art methods in non-occlusion pedestrian data set while performs fair in weakly and heavily occlusion data set.

Sign in / Sign up

Export Citation Format

Share Document