Input Data Requirements for Lagrangian Trajectory Models

Bowman, Kenneth P.; Lin, John C.; Stohl, Andreas; Draxler, Roland R.; Konopka, Paul; Andrews, A. E.; Brunner, Dominik

doi:10.1175/bams-d-12-00076.1

Cited by 74 publications

(99 citation statements)

References 58 publications

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“…Stohl et al (2001) suggest typical average errors of approximately 20% of the travel distance and accordingly to Bowman et al (2012) globally averaged error of around 350 km can be found in lagrangian methodologies considering 6-h wind sampling for 5 days forward trajectories. These errors are mainly associated with the temporal resolution of input data (Bowman et al, 2013). Moreover, there are numerical errors related with the temporal variation of the particles' moisture, which produces miscalculation on the moisture transport (Stohl and James, 2004), and important uncertainties can be found if the method does not properly close the water cycle Gimeno et al (2012).…”

Section: Methodsmentioning

confidence: 99%

Moisture transport from the Arctic: a characterization from a Lagrangian perspective

Vázquez

Nieto

Drumond

et al. 2018

CIG

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The Arctic Ocean has suffered extreme reductions in sea ice in recent decades, and these observed changes suggest implications in terms of moisture transport. The Arctic region is a net sink of moisture in terms of the total hydrological cycle, however, its role as a moisture source for specific regions has not been extensively studied. Our results show that 80% of the moisture supply from the Arctic contributes to precipitation over itself, representing about 8% of the global moisture supply to the Arctic, the remaining 20% is distributed in the surrounding. A reduction in the sea ice extent could make the Arctic Ocean a slightly higher source of moisture to itself or to the surrounding areas. The analysis of the areas affected by Arctic moisture transport is important for establishing those areas vulnerable to change in a framework of a growing sea ice decline. To this end, the Lagrangian model FLEXPART was used in this work to establish the main sinks for the Arctic Ocean, focusing on the moisture transport from this region. The results suggest that most of the moisture loss occurs locally over the Arctic Ocean itself, especially in summer. Some moisture contribution from the Arctic Ocean to continental areas in North America and Eurasia is also noted in autumn and winter especially from Central Arctic, the East Siberian Sea, the Laptev, Kara, Barents, East Greenland and Bering Seas, and the Sea of Okhotsk.

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Section: Methodsmentioning

confidence: 99%

Moisture transport from the Arctic: a characterization from a Lagrangian perspective

Vázquez

Nieto

Drumond

et al. 2018

CIG

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“…The sensitivity of back trajectories to the temporal and spatial resolution of meteorological data is discussed in Draxler (1987). The temporal resolution is likely to have had an impact on trajectories, but the necessary temporal resolution increases with the horizontal resolution (Bowman et al, 2013).…”

Section: The Weather Research and Forecasting Model (Wrf)mentioning

confidence: 99%

Particulate Pollution in the Sydney Region: Source Diagnostics and Synoptic Controls

Crawford

Griffiths

Cohen

et al. 2016

Aerosol Air Qual. Res.

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Airborne particulate matter (PM 2.5 ) was sampled at Richmond and Liverpool, located in the Sydney Basin, Australia, and ion beam analysis was used to obtain the elemental composition. Using self-organising maps to classify synoptic weather systems, it was found that high PM 2.5 concentrations were associated with high pressure systems located to the east of the sampling sites. The highest median sulfur was associated with weak synoptic conditions and high soil dust days were more often associated with frontal systems.To investigate the effect of local flows in the Sydney Basin, the Weather Research and Forecasting model (WRF) was used to generate meteorological data of 12 km resolution. A comparison was made between back trajectories generated using the higher-resolution WRF data, the 0.5° by 0.5° Climate Forecast System data and the 1° by 1° Global Data Assimilation System data. It was found that for high soil dust days, there were small differences between the different back trajectories. However, under weak synoptic conditions (high sulfur days), the back trajectories generated from higher resolution data showed larger variations over a 24 hr period. This was attributed to the meandering of local winds and seabreezes.Lower altitude back trajectories, generated from low resolution data, passed more often over the power stations located on the western side of the Great Dividing Range (while the sampling sites are on the east). This demonstrates the need for higher resolution meteorological data for generating low altitude back trajectories when the source and receptor are separated by hilly terrain.In estimating the number of high sulfur days for which a power station was crossed, there was up to 20% difference at Liverpool and up to 10% difference at Richmond, between back trajectories starting at different altitudes and generated from meteorological data of three different resolutions.

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“…It has been known since Brewer's seminal work on stratospheric circulation that tropical tropopause temperature is the main driver of stratospheric H 2 O concentration (Brewer, 1949). As parcels approach and pass through the cold-point tropopause -the altitude at which air temperature is the coldest -condensation occurs and ice falls out, thereby regulating the parcel's H 2 O concentration to the local saturation level (e.g., Fueglistaler et al, 2009, and references therein).…”

Section: Trajectory Model and Temperatures Usedmentioning

confidence: 99%

“…The trajectory model used here follows the details described in Schoeberl and Dessler (2011), with parcel positions integrated using the Bowman trajectory code (Bowman, 1993;Bowman et al, 2013). This model has been proven capable of simulating stratospheric H 2 O and its long-term variability (Schoeberl and Dessler, 2011;Schoeberl et al, 2012Schoeberl et al, , 2013Dessler et al, 2014), modeling chemical tracer transport in the lower stratosphere , and studying the stratospheric air age spectrum (Ray et al, 2014).…”

Section: Trajectory Modelmentioning

confidence: 99%

The impact of temperature vertical structure on trajectory modeling of stratospheric water vapor

et al. 2015

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Abstract. Lagrangian trajectories driven by reanalysis meteorological fields are frequently used to study water vapor (H 2 O) in the stratosphere, in which the tropical cold-point temperatures regulate the amount of H 2 O entering the stratosphere. Therefore, the accuracy of temperatures in the tropical tropopause layer (TTL) is of great importance for understanding stratospheric H 2 O abundances. Currently, most reanalyses, such as the NASA MERRA (Modern Era Retrospective -analysis for Research and Applications), only provide temperatures with ∼ 1.2 km vertical resolution in the TTL, which has been argued to miss finer vertical structure in the tropopause and therefore introduce uncertainties in our understanding of stratospheric H 2 O. In this paper, we quantify this uncertainty by comparing the Lagrangian trajectory prediction of H 2 O using MERRA temperatures on standard model levels (traj.MER-T) to those using GPS temperatures at finer vertical resolution (traj.GPS-T), and those using adjusted MERRA temperatures with finer vertical structures induced by waves (traj.MER-Twave). It turns out that by using temperatures with finer vertical structure in the tropopause, the trajectory model more realistically simulates the dehydration of air entering the stratosphere. But the effect on H 2 O abundances is relatively minor: compared with traj.MER-T, traj.GPS-T tends to dry air by ∼ 0.1 ppmv, while traj.MERTwave tends to dry air by 0.2-0.3 ppmv. Despite these differences in absolute values of predicted H 2 O and vertical dehydration patterns, there is virtually no difference in the interannual variability in different runs. Overall, we find that a tropopause temperature with finer vertical structure has limited impact on predicted stratospheric H 2 O.

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Input Data Requirements for Lagrangian Trajectory Models

Cited by 74 publications

References 58 publications

Moisture transport from the Arctic: a characterization from a Lagrangian perspective

Moisture transport from the Arctic: a characterization from a Lagrangian perspective

Particulate Pollution in the Sydney Region: Source Diagnostics and Synoptic Controls

The impact of temperature vertical structure on trajectory modeling of stratospheric water vapor

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