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Robertson, Lennart
Publications (10 of 47) Show all publications
Plu, M., Scherllin-Pirscher, B., Arnold Arias, D., Baro, R., Bigeard, G., Bugliaro, L., . . . Zopp, R. (2021). An ensemble of state-of-the-art ash dispersion models: towards probabilistic forecasts to increase the resilience of air traffic against volcanic eruptions. Natural hazards and earth system sciences, 21(10), 2973-2992
Open this publication in new window or tab >>An ensemble of state-of-the-art ash dispersion models: towards probabilistic forecasts to increase the resilience of air traffic against volcanic eruptions
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2021 (English)In: Natural hazards and earth system sciences, ISSN 1561-8633, E-ISSN 1684-9981, Vol. 21, no 10, p. 2973-2992Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-6178 (URN)10.5194/nhess-21-2973-2021 (DOI)000706528100001 ()
Available from: 2021-10-26 Created: 2021-10-26 Last updated: 2021-10-26Bibliographically approved
Barre, J., Petetin, H., Colette, A., Guevara, M., Peuch, V.-H., Rouil, L., . . . Kouznetsov, R. (2021). Estimating lockdown-induced European NO2 changes using satellite and surface observations and air quality models. Atmospheric Chemistry And Physics, 21(9), 7373-7394
Open this publication in new window or tab >>Estimating lockdown-induced European NO2 changes using satellite and surface observations and air quality models
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2021 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 21, no 9, p. 7373-7394Article in journal (Refereed) Published
Abstract [en]

This study provides a comprehensive assessment of NO2 changes across the main European urban areas induced by COVID-19 lockdowns using satellite retrievals from the Tropospheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5p satellite, surface site measurements, and simulations from the Copernicus Atmosphere Monitoring Service (CAMS) regional ensemble of air quality models. Some recent TROPOMI-based estimates of changes in atmospheric NO2 concentrations have neglected the influence of weather variability between the reference and lockdown periods. Here we provide weather-normalized estimates based on a machine learning method (gradient boosting) along with an assessment of the biases that can be expected from methods that omit the influence of weather. We also compare the weather-normalized satellite-estimated NO2 column changes with weather-normalized surface NO2 concentration changes and the CAMS regional ensemble, composed of 11 models, using recently published estimates of emission reductions induced by the lockdown. All estimates show similar NO2 reductions. Locations where the lockdown measures were stricter show stronger reductions, and, conversely, locations where softer measures were implemented show milder reductions in NO2 pollution levels. Average reduction estimates based on either satellite observations (-23 %), surface stations (-43 %), or models (-32 %) are presented, showing the importance of vertical sampling but also the horizontal representativeness. Surface station estimates are significantly changed when sampled to the TROPOMI overpasses (-37 %), pointing out the importance of the variability in time of such estimates. Observation-based machine learning estimates show a stronger temporal variability than model-based estimates.

National Category
Meteorology and Atmospheric Sciences
Research subject
Environment
Identifiers
urn:nbn:se:smhi:diva-6119 (URN)10.5194/acp-21-7373-2021 (DOI)000653523100002 ()
Available from: 2021-06-16 Created: 2021-06-16 Last updated: 2021-06-16Bibliographically approved
Brenot, H., Theys, N., Clarisse, L., van Gent, J., Hurtmans, D. R., Vandenbussche, S., . . . Wotawa, G. (2021). EUNADICS-AV early warning system dedicated to supporting aviation in the case of a crisis from natural airborne hazards and radionuclide clouds. Natural hazards and earth system sciences, 21(11), 3367-3405
Open this publication in new window or tab >>EUNADICS-AV early warning system dedicated to supporting aviation in the case of a crisis from natural airborne hazards and radionuclide clouds
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2021 (English)In: Natural hazards and earth system sciences, ISSN 1561-8633, E-ISSN 1684-9981, Vol. 21, no 11, p. 3367-3405Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-6193 (URN)10.5194/nhess-21-3367-2021 (DOI)000716716200001 ()
Available from: 2021-11-23 Created: 2021-11-23 Last updated: 2021-12-01Bibliographically approved
Hirtl, M., Arnold, D., Baro, R., Brenot, H., Coltelli, M., Eschbacher, K., . . . Zopp, R. (2020). A volcanic-hazard demonstration exercise to assess and mitigate the impacts of volcanic ash clouds on civil and military aviation. Natural hazards and earth system sciences, 20(6), 1719-1739
Open this publication in new window or tab >>A volcanic-hazard demonstration exercise to assess and mitigate the impacts of volcanic ash clouds on civil and military aviation
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2020 (English)In: Natural hazards and earth system sciences, ISSN 1561-8633, E-ISSN 1684-9981, Vol. 20, no 6, p. 1719-1739Article in journal (Refereed) Published
National Category
Environmental Sciences
Research subject
Environment
Identifiers
urn:nbn:se:smhi:diva-5764 (URN)10.5194/nhess-20-1719-2020 (DOI)000541724700001 ()
Available from: 2020-08-17 Created: 2020-08-17 Last updated: 2020-08-17Bibliographically approved
Sofiev, M., Ritenberga, O., Albertini, R., Arteta, J., Belmonte, J., Bernstein, C. G., . . . Vokou, D. (2017). Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook. Atmospheric Chemistry And Physics, 17(20), 12341-12360
Open this publication in new window or tab >>Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook
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2017 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 17, no 20, p. 12341-12360Article in journal (Refereed) Published
National Category
Environmental Sciences
Research subject
Environment
Identifiers
urn:nbn:se:smhi:diva-4306 (URN)10.5194/acp-17-12341-2017 (DOI)000413112300002 ()
Available from: 2017-11-13 Created: 2017-11-13 Last updated: 2017-11-13Bibliographically approved
Andersson, C., Alpfjord, H., Robertson, L., Karlsson, P. E. & Engardt, M. (2017). Reanalysis of and attribution to near-surface ozone concentrations in Sweden during 1990-2013. Atmospheric Chemistry And Physics, 17(22)
Open this publication in new window or tab >>Reanalysis of and attribution to near-surface ozone concentrations in Sweden during 1990-2013
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2017 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 17, no 22Article in journal (Refereed) Published
National Category
Earth and Related Environmental Sciences
Research subject
Environment
Identifiers
urn:nbn:se:smhi:diva-4452 (URN)10.5194/acp-17-13869-2017 (DOI)000416001700001 ()
Available from: 2017-12-12 Created: 2017-12-12 Last updated: 2020-05-04Bibliographically approved
Thomas, M., Brannstrom, N., Persson, C., Grahn, H., von Schoenberg, P. & Robertson, L. (2017). Surface air quality implications of volcanic injection heights. Atmospheric Environment, 166, 510-518
Open this publication in new window or tab >>Surface air quality implications of volcanic injection heights
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2017 (English)In: Atmospheric Environment, ISSN 1352-2310, E-ISSN 1873-2844, Vol. 166, p. 510-518Article in journal (Refereed) Published
National Category
Environmental Sciences
Research subject
Environment
Identifiers
urn:nbn:se:smhi:diva-4316 (URN)10.1016/j.atmosenv.2017.07.045 (DOI)000411298800046 ()
Available from: 2017-11-13 Created: 2017-11-13 Last updated: 2020-05-05Bibliographically approved
Silver, J. D., Christensen, J. H., Kahnert, M., Robertson, L., Rayner, P. J. & Brandt, J. (2016). Multi-species chemical data assimilation with the Danish Eulerian hemispheric model: system description and verification. Journal of Atmospheric Chemistry, 73(3), 261-302
Open this publication in new window or tab >>Multi-species chemical data assimilation with the Danish Eulerian hemispheric model: system description and verification
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2016 (English)In: Journal of Atmospheric Chemistry, ISSN 0167-7764, E-ISSN 1573-0662, Vol. 73, no 3, p. 261-302Article in journal (Refereed) Published
National Category
Environmental Sciences
Research subject
Environment
Identifiers
urn:nbn:se:smhi:diva-3036 (URN)10.1007/s10874-015-9326-0 (DOI)000380265800003 ()
External cooperation:
Available from: 2016-09-01 Created: 2016-09-01 Last updated: 2017-11-21Bibliographically approved
Marecal, V., Peuch, V.-H. -., Andersson, C., Andersson, S., Arteta, J., Beekmann, M., . . . Ung, A. (2015). A regional air quality forecasting system over Europe: the MACC-II daily ensemble production. Geoscientific Model Development, 8(9), 2777-2813
Open this publication in new window or tab >>A regional air quality forecasting system over Europe: the MACC-II daily ensemble production
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2015 (English)In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 8, no 9, p. 2777-2813Article in journal (Refereed) Published
Abstract [en]

This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The paper gives an overall picture of its status at the end of MACCII (summer 2014) and analyses the performance of the multi-model ensemble. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O-3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs (non-methane volatile organic compounds) and PAN + PAN precursors) over eight vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performance of the system is assessed daily, weekly and every 3 months (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the ensemble median to forecast regional ozone pollution events. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10. The statistical indicators for ozone in summer 2014 show that the ensemble median gives on average the best performances compared to the seven models. There is very little degradation of the scores with the forecast day but there is a marked diurnal cycle, similarly to the individual models, that can be related partly to the prescribed diurnal variations of anthropogenic emissions in the models. During summer 2014, the diurnal ozone maximum is underestimated by the ensemble median by about 4 mu g m(-3) on average. Locally, during the studied ozone episodes, the maxima from the ensemble median are often lower than observations by 30-50 mu g m(-3). Overall, ozone scores are generally good with average values for the normalised indicators of 0.14 for the modified normalised mean bias and of 0.30 for the fractional gross error. Tests have also shown that the ensemble median is robust to reduction of ensemble size by one, that is, if predictions are unavailable from one model. Scores are also discussed for PM10 for winter 2013-1014. There is an underestimation of most models leading the ensemble median to a mean bias of 4.5 mu g m(-3). The ensemble median fractional gross error is larger for PM10 (similar to 0.52) than for ozone and the correlation is lower (similar to 0.35 for PM10 and similar to 0.54 for ozone). This is related to a larger spread of the seven model scores for PM10 than for ozone linked to different levels of complexity of aerosol representation in the individual models. In parallel, a scientific analysis of the results of the seven models and of the ensemble is also done over the Mediterranean area because of the specificity of its meteorology and emissions. The system is robust in terms of the production availability. Major efforts have been done in MACC-II towards the operationalisation of all its components. Foreseen developments and research for improving its performances are discussed in the conclusion.

National Category
Environmental Sciences
Research subject
Environment
Identifiers
urn:nbn:se:smhi:diva-1943 (URN)10.5194/gmd-8-2777-2015 (DOI)000364325700005 ()
Available from: 2016-04-29 Created: 2016-03-03 Last updated: 2017-11-30Bibliographically approved
Sofiev, M., Berger, U., Prank, M., Vira, J., Arteta, J., Belmonte, J., . . . Peuch, V.-H. -. (2015). MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe. Atmospheric Chemistry And Physics, 15(14), 8115-8130
Open this publication in new window or tab >>MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe
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2015 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 15, no 14, p. 8115-8130Article in journal (Refereed) Published
Abstract [en]

This paper presents the first ensemble modelling experiment in relation to birch pollen in Europe. The seven-model European ensemble of MACC-ENS, tested in trial simulations over the flowering season of 2010, was run through the flowering season of 2013. The simulations have been compared with observations in 11 countries, all members of the European Aeroallergen Network, for both individual models and the ensemble mean and median. It is shown that the models successfully reproduced the timing of the very late season of 2013, generally within a couple of days from the observed start of the season. The end of the season was generally predicted later than observed, by 5 days or more, which is a known feature of the source term used in the study. Absolute pollen concentrations during the season were somewhat underestimated in the southern part of the birch habitat. In the northern part of Europe, a record-low pollen season was strongly overestimated by all models. The median of the multi-model ensemble demonstrated robust performance, successfully eliminating the impact of outliers, which was particularly useful since for most models this was the first experience of pollen forecasting.

National Category
Environmental Sciences
Research subject
Environment
Identifiers
urn:nbn:se:smhi:diva-1964 (URN)10.5194/acp-15-8115-2015 (DOI)000358799000023 ()
Available from: 2016-04-27 Created: 2016-03-03 Last updated: 2017-11-30Bibliographically approved
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