Assimilating aircraft-based measurements to improve forecast accuracy of volcanic ash transport

Fu, Guangliang; Lin, Hai; Heemink, A.W.; Segers, Arjo; Sha, Liqing; Palsson, Thorgeir

doi:10.1016/j.atmosenv.2015.05.061

Cited by 23 publications

(33 citation statements)

References 39 publications

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“…Van Loon et al, 2000;Hanea et al, 2004;Barbu et al, 2009;Van Velzen et al, 2010;Curier et al, 2012) as well as particulate matter (Denby et al, 2008 and Fig. 6) and volcanic ash (Fu et al, 2015). Besides in situ data, satellite tropospheric NO 2 column observations (OMI: Eskes et al, 2014) as well as aerosol optical depth (AOD) (SEVIRI: Segers et al, 2010) have been successfully assimilated in the LOTOS-EUROS model.…”

Section: Data Assimilation Systemmentioning

confidence: 99%

Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model

et al. 2017

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Abstract. The development and application of chemistry transport models has a long tradition. Within the Netherlands the LOTOS-EUROS model has been developed by a consortium of institutes, after combining its independently developed predecessors in 2005. Recently, version 2.0 of the model was released as an open-source version. This paper presents the curriculum vitae of the model system, describing the model's history, model philosophy, basic features and a validation with EMEP stations for the new benchmark year 2012, and presents cases with the model's most recent and key developments. By setting the model developments in context and providing an outlook for directions for further development, the paper goes beyond the common model description.With an origin in ozone and sulfur modelling for the models LOTOS and EUROS, the application areas were gradually extended with persistent organic pollutants, reactive nitrogen, and primary and secondary particulate matter. After the combination of the models to LOTOS-EUROS in 2005, the model was further developed to include new source parametrizations (e.g. road resuspension, desert dust, wildfires), applied for operational smog forecasts in the Netherlands and Europe, and has been used for emission scenarios, source apportionment, and long-term hindcast and climate change scenarios. LOTOS-EUROS has been a front-runner in data assimilation of ground-based and satellite observations and has participated in many model intercomparison studies. The model is no longer confined to applications over Europe but is also applied to other regions of the world, e.g. China. The increasing interaction with emission experts has also contributed to the improvement of the model's performance. The philosophy for model development has always been to use knowledge that is state of the art and proven, to keep a good balance in the level of detail of process description and accuracy of input and output, and to keep a good record on the effect of model changes using benchmarking and validation. The performance of v2.0 with respect to EMEP observations is good, with spatial correlations around 0.8 or higher for concentrations and wet deposition. Temporal correlations are around 0.5 or higher. Recent innovative applications include source apportionment and data assimilation, particle number modelling, and energy transition scenarios including corresponding land use changes as well as Saharan dust forecasting. Future developments would enable more flexibility with respect to model horizontal and vertical resolution and further detailing of model input data.Published by Copernicus Publications on behalf of the European Geosciences Union.

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Section: Data Assimilation Systemmentioning

confidence: 99%

Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model

et al. 2017

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“…One reason for this time decrease is that when the size of the matrix is reduced, the memory access cost also goes down (e.g., through better cache usages). Another possible reason is that the ash grid number actually decreases with time (not always taking 39.3 % of the total grid number), due to ash sedimentation and deposition processes (Fu et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

“…This case might not be general for all ash forecasts, as the computational cost for initialization and forecast greatly depends on the forecast model that is used. For the current development, it makes sense to use the LOTOS-EUROS model, because the model has been configured and evaluated in (Fu et al, 2015) by comparison with other famous models (e.g., NAME, Jones et al, 2007, andWRFChem, Webley et al, 2012) in simulating volcanic ash transport. However, if a more expensive ash forecasting model is used, then the bottleneck would be the forecast step.…”

Section: G Fu Et Al: a Mask-state Algorithmmentioning

confidence: 99%

Accelerating volcanic ash data assimilation using a mask-state algorithm based on an ensemble Kalman filter: a case study with the LOTOS-EUROS model (version 1.10)

Lin

Heemink

et al. 2017

Geosci. Model Dev.

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Abstract. In this study, we investigate a strategy to accelerate the data assimilation (DA) algorithm. Based on evaluations of the computational time, the analysis step of the assimilation turns out to be the most expensive part. After a study of the characteristics of the ensemble ash state, we propose a mask-state algorithm which records the sparsity information of the full ensemble state matrix and transforms the full matrix into a relatively small one. This will reduce the computational cost in the analysis step. Experimental results show the mask-state algorithm significantly speeds up the analysis step. Subsequently, the total amount of computing time for volcanic ash DA is reduced to an acceptable level. The mask-state algorithm is generic and thus can be embedded in any ensemble-based DA framework. Moreover, ensemble-based DA with the mask-state algorithm is promising and flexible, because it implements exactly the standard DA without any approximation and it realizes the satisfying performance without any change in the full model.

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“…Recently in the application of volcanic ash transport, the benefit of aircraft in situ observations in an ensemble Kalman filter (EnKF) system has been studied (Fu et al, 2015). It was shown using so-called twin experiments that ensemble-based data assimilation is in principle able to combine the aircraft in situ measurements with a volcanic ash transport and dispersion model (VATDM) to make improvements on volcanic ash estimation close to the eruption location.…”

Section: G Fu Et Al: Assimilating Aircraft In Situ Measurementsmentioning

confidence: 99%

“…Note that the term real-life aircraft measurements in this study refer to authentic measurements obtained by real aircrafts. This is to distinguish the artificial aircraft measurements as used in Fu et al (2015). Another term distal volcanic ash plume is used to clarify the study focuses on volcanic ash forecasts far from the volcano, i.e., continental Europe in this study.…”

Section: G Fu Et Al: Assimilating Aircraft In Situ Measurementsmentioning

confidence: 99%

Model-based aviation advice on distal volcanic ash clouds by assimilating aircraft in situ measurements

Heemink

Sha

et al. 2016

Atmos. Chem. Phys.

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Abstract. The forecast accuracy of distal volcanic ash clouds is important for providing valid aviation advice during volcanic ash eruption. However, because the distal part of volcanic ash plume is far from the volcano, the influence of eruption information on this part becomes rather indirect and uncertain, resulting in inaccurate volcanic ash forecasts in these distal areas. In our approach, we use real-life aircraft in situ observations, measured in the northwestern part of Germany during the 2010 Eyjafjallajökull eruption, in an ensemble-based data assimilation system combined with a volcanic ash transport model to investigate the potential improvement on the forecast accuracy with regard to the distal volcanic ash plume. We show that the error of the analyzed volcanic ash state can be significantly reduced through assimilating real-life in situ measurements. After a continuous assimilation, it is shown that the aviation advice for Germany, the Netherlands and Luxembourg can be significantly improved. We suggest that with suitable aircrafts measuring once per day across the distal volcanic ash plume, the description and prediction of volcanic ash clouds in these areas can be greatly improved.

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Assimilating aircraft-based measurements to improve forecast accuracy of volcanic ash transport

Cited by 23 publications

References 39 publications

Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model

Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model

Accelerating volcanic ash data assimilation using a mask-state algorithm based on an ensemble Kalman filter: a case study with the LOTOS-EUROS model (version 1.10)

Model-based aviation advice on distal volcanic ash clouds by assimilating aircraft in situ measurements

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