A Method to Speed up a Lagrangian Stochastic Particle Dispersion Model

2000 ◽  
pp. 509-517 ◽  
Author(s):  
Mathias W. Rotach ◽  
Stefan Schwere
Keyword(s):  
Dispersion Model ◽  
Particle Dispersion ◽  
Speed Up ◽  
Stochastic Particle

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.

scholarly journals A regional CO2 observing system simulation experiment for the ASCENDS satellite mission

2014 ◽  
Vol 14 (23) ◽  
pp. 12897-12914 ◽  
Author(s):  
J. S. Wang ◽  
S. R. Kawa ◽  
J. Eluszkiewicz ◽  
D. F. Baker ◽  
M. Mountain ◽  
...  
Keyword(s):  
Measurement Errors ◽  
Dispersion Model ◽  
A Priori ◽  
Wrf Model ◽  
Particle Dispersion ◽  
Instrument Design ◽  
Satellite Mission ◽  
Model Framework ◽  
Satellite Systems ◽  
Novel Approach

Abstract. Top–down estimates of the spatiotemporal variations in emissions and uptake of CO2 will benefit from the increasing measurement density brought by recent and future additions to the suite of in situ and remote CO2 measurement platforms. In particular, the planned NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) satellite mission will provide greater coverage in cloudy regions, at high latitudes, and at night than passive satellite systems, as well as high precision and accuracy. In a novel approach to quantifying the ability of satellite column measurements to constrain CO2 fluxes, we use a portable library of footprints (surface influence functions) generated by the Stochastic Time-Inverted Lagrangian Transport (STILT) model in combination with the Weather Research and Forecasting (WRF) model in a regional Bayesian synthesis inversion. The regional Lagrangian particle dispersion model framework is well suited to make use of ASCENDS observations to constrain weekly fluxes in North America at a high resolution, in this case at 1° latitude × 1° longitude. We consider random measurement errors only, modeled as a function of the mission and instrument design specifications along with realistic atmospheric and surface conditions. We find that the ASCENDS observations could potentially reduce flux uncertainties substantially at biome and finer scales. At the grid scale and weekly resolution, the largest uncertainty reductions, on the order of 50%, occur where and when there is good coverage by observations with low measurement errors and the a priori uncertainties are large. Uncertainty reductions are smaller for a 1.57 μm candidate wavelength than for a 2.05 μm wavelength, and are smaller for the higher of the two measurement error levels that we consider (1.0 ppm vs. 0.5 ppm clear-sky error at Railroad Valley, Nevada). Uncertainty reductions at the annual biome scale range from ~40% to ~75% across our four instrument design cases and from ~65% to ~85% for the continent as a whole. Tests suggest that the quantitative results are moderately sensitive to assumptions regarding a priori uncertainties and boundary conditions. The a posteriori flux uncertainties we obtain, ranging from 0.01 to 0.06 Pg C yr−1 across the biomes, would meet requirements for improved understanding of long-term carbon sinks suggested by a previous study.

scholarly journals A new Lagrangian in-time particle simulation module (Itpas v1) for atmospheric particle dispersion

2021 ◽  
Vol 14 (4) ◽  
pp. 2205-2220
Author(s):  
Matthias Faust ◽  
Ralf Wolke ◽  
Steffen Münch ◽  
Roger Funk ◽  
Kerstin Schepanski
Keyword(s):  
Boundary Layer ◽  
Particle Transport ◽  
Dispersion Model ◽  
Weather Forecast ◽  
Forecast Model ◽  
Particle Dispersion ◽  
Particle Simulation ◽  
High Temporal Resolution ◽  
Atmospheric Particle ◽  
Trajectory Models

Abstract. Trajectory models are intuitive tools for airflow studies. But in general, they are limited to non-turbulent, i.e. laminar flow, conditions. Therefore, trajectory models are not particularly suitable for investigating airflow within the turbulent atmospheric boundary layer. To overcome this, a common approach is handling the turbulent uncertainty as a random deviation from a mean path in order to create a statistic of possible solutions which envelops the mean path. This is well known as the Lagrangian particle dispersion model (LPDM). However, the decisive factor is the representation of turbulence in the model, for which widely used models such as FLEXPART and HYSPLIT use an approximation. A conceivable improvement could be the use of a turbulence parameterisation approach based on the turbulent kinetic energy (TKE) at high temporal resolution. Here, we elaborated this approach and developed the LPDM Itpas, which is coupled online to the German Weather Service's mesoscale weather forecast model COSMO. It benefits from the prognostically calculated TKE as well as from the high-frequency wind information. We demonstrate the model's applicability for a case study on agricultural particle emission in eastern Germany. The results obtained are discussed with regard to the model's ability to describe particle transport within a turbulent boundary layer. Ultimately, the simulations performed suggest that the newly introduced method based on prognostic TKE sufficiently represents the particle transport.

scholarly journals Arctic smoke – record high air pollution levels in the European Arctic due to agricultural fires in Eastern Europe

2006 ◽  
Vol 6 (5) ◽  
pp. 9655-9722 ◽  
Author(s):  
A. Stohl ◽  
T. Berg ◽  
J. F. Burkhart ◽  
A. M. Fjæraa ◽  
C. Forster ◽  
...  
Keyword(s):  
Air Pollution ◽  
Eastern Europe ◽  
Dispersion Model ◽  
Spatial Scales ◽  
Agricultural Waste ◽  
Particle Dispersion ◽  
The Arctic ◽  
Aerosol Size Distribution ◽  
Radiative Processes ◽  
European Arctic

Abstract. In spring 2006, the European Arctic was abnormally warm, setting new historical temperature records. During this warm period, smoke from agricultural fires in Eastern Europe intruded into the European Arctic and caused the most severe air pollution episodes ever recorded there. This paper confirms that biomass burning (BB) was indeed the source of the observed air pollution, studies the transport of the smoke into the Arctic, and presents an overview of the observations taken during the episode. Fire detections from the MODIS instruments aboard the Aqua and Terra satellites were used to estimate the BB emissions. The FLEXPART particle dispersion model was used to show that the smoke was transported to Spitsbergen and Iceland, which was confirmed by MODIS retrievals of the aerosol optical depth (AOD) and AIRS retrievals of carbon monoxide (CO) total columns. Concentrations of halocarbons, carbon dioxide and CO, as well as levoglucosan and potassium, measured at Zeppelin mountain near Ny Ålesund, were used to further corroborate the BB source of the smoke at Spitsbergen. The ozone (O3) and CO concentrations were the highest ever observed at the Zeppelin station, and gaseous elemental mercury was also enhanced. A new O3 record was also set at a station on Iceland. The smoke was strongly absorbing – black carbon concentrations were the highest ever recorded at Zeppelin –, and strongly perturbed the radiation transmission in the atmosphere: aerosol optical depths were the highest ever measured at Ny Ålesund. We furthermore discuss the aerosol chemical composition, obtained from filter samples, as well as the aerosol size distribution during the smoke event. Photographs show that the snow at a glacier on Spitsbergen became discolored during the episode and, thus, the snow albedo was reduced. Samples of this polluted snow contained strongly enhanced levels of potassium, sulphate, nitrate and ammonium ions, thus relating the discoloration to the deposition of the smoke aerosols. This paper shows that, to date, BB has been underestimated as a source of aerosol and air pollution for the Arctic, relative to emissions from fossil fuel combustion. Given its significant impact on air quality over large spatial scales and on radiative processes, the practice of agricultural waste burning should be banned in the future.

scholarly journals An extended Kalman-filter for regional scale inverse emission estimation

2011 ◽  
Vol 11 (10) ◽  
pp. 29195-29249 ◽  
Author(s):  
D. Brunner ◽  
S. Henne ◽  
C. A. Keller ◽  
S. Reimann ◽  
M. K. Vollmer ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Dispersion Model ◽  
Regional Scale ◽  
Estimation Method ◽  
Particle Dispersion ◽  
Montreal Protocol ◽  
Correlated Noise ◽  
Temporal Correlations ◽  
Emission Estimation ◽  
Hfc 152A

Abstract. A Kalman-filter based inverse emission estimation method for long-lived trace gases is presented for use in conjunction with a Lagrangian particle dispersion model like FLEXPART. The sequential nature of the approach allows tracing slow seasonal and interannual changes rather than estimating a single period-mean emission field. Other important features include the estimation of a slowly varying concentration background at each measurement station, the possibility to constrain the solution to non-negative emissions, the quantification of uncertainties, the consideration of temporal correlations in the residuals, and the applicability to potentially large inversion problems. The method is first demonstrated for a set of synthetic observations created from a prescribed emission field with different levels of (correlated) noise, which closely mimics true observations. It is then applied to real observations of the three halocarbons HFC-125, HFC-152a and HCFC-141b at the remote research stations Jungfraujoch and Mace Head for the quantification of emissions in Western European countries from 2006 to 2010. Estimated HFC-125 emissions are mostly consistent with national totals reported to the Kyoto protocol and show a generally increasing trend over the considered period. Results for HFC-152a are much more variable with estimated emissions being both higher and lower in different countries. The highest emissions of the order of 1000 Mg yr−1 are estimated for Italy which so far does not report HFC-152a emissions. Emissions of HCFC-141b show a continuing strong decrease as expected due to its ban under the Montreal Protocol. Emissions from France, however, were still rather large (near 1000 Mg yr−1) in the years 2006 and 2007 but strongly declined thereafter.

scholarly journals Identification of Aerosol Sources in Siberia and Study of Aerosol Transport at Regional Scale by Airborne and Space-Borne Lidar Measurement

2020 ◽  
Vol 237 ◽  
pp. 02014
Author(s):  
Antonin Zabukovec ◽  
Gérard Ancellet ◽  
Jacques Pelon ◽  
J.D. Paris ◽  
Iogannes E. Penner ◽  
...  
Keyword(s):  
Forest Fires ◽  
Dispersion Model ◽  
Regional Scale ◽  
Particle Dispersion ◽  
Airborne Lidar ◽  
Orthogonal Polarization ◽  
Lidar Measurement ◽  
Imaging Spectrometer ◽  
Modis Aod ◽  
Moderate Resolution

Airborne lidar measurements were carried out over Siberia in July 2013 and June 2017. Aerosol optical properties are derived using the Lagrangian FLEXible PARTicle dispersion model (FLEXPART) simulations and Moderate Resolution Imaging Spectrometer (MODIS) AOD. Comparison with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol products is used to validate the CALIOP aerosol type identification above Siberia. Two case studies are discussed : a mixture of dust and pollution from Northern Kazakhstan and smoke plumes from forest fires. Comparisons with the CALIOP backscatter ratio show that CALIOP algorithm may overestimate the LR for a dusty mixture if not constrained by an independent AOD measurement.

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