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Publications (10 of 24) Show all publications
Whaley, C. H., Law, K. S., Hjorth, J. L., Skov, H., Arnold, S. R., Langner, J., . . . Tarasick, D. W. (2023). Arctic tropospheric ozone: assessment of current knowledge and modelperformance. Atmospheric Chemistry And Physics, 23(1), 637-661
Open this publication in new window or tab >>Arctic tropospheric ozone: assessment of current knowledge and modelperformance
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2023 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 23, no 1, p. 637-661Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-6405 (URN)10.5194/acp-23-637-2023 (DOI)000918577900001 ()
Available from: 2023-02-14 Created: 2023-02-14 Last updated: 2023-02-14Bibliographically approved
Thomas, M., Devasthale, A. & Kahnert, M. (2022). Marine aerosol properties over the Southern Ocean in relation to the wintertime meteorological conditions. Atmospheric Chemistry And Physics, 22(1), 119-137
Open this publication in new window or tab >>Marine aerosol properties over the Southern Ocean in relation to the wintertime meteorological conditions
2022 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 22, no 1, p. 119-137Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-6219 (URN)10.5194/acp-22-119-2022 (DOI)000739364900001 ()
Available from: 2022-01-18 Created: 2022-01-18 Last updated: 2022-01-24Bibliographically approved
Thomas, M., Devasthale, A. & Nygard, T. (2021). Influence of springtime atmospheric circulation types on the distribution of air pollutants in the Arctic. Atmospheric Chemistry And Physics, 21(21), 16593-16608
Open this publication in new window or tab >>Influence of springtime atmospheric circulation types on the distribution of air pollutants in the Arctic
2021 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 21, no 21, p. 16593-16608Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing; Environment
Identifiers
urn:nbn:se:smhi:diva-6194 (URN)10.5194/acp-21-16593-2021 (DOI)000720121500001 ()
Available from: 2021-12-02 Created: 2021-12-02 Last updated: 2021-12-02Bibliographically approved
Im, U., Tsigaridis, K., Faluvegi, G., Langen, P. L., French, J. P., Mahmood, R., . . . Brandt, J. (2021). Present and future aerosol impacts on Arctic climate change in the GISS-E2.1 Earth system model. Atmospheric Chemistry And Physics, 21(13), 10413-10438
Open this publication in new window or tab >>Present and future aerosol impacts on Arctic climate change in the GISS-E2.1 Earth system model
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2021 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 21, no 13, p. 10413-10438Article in journal (Refereed) Published
Abstract [en]

The Arctic is warming 2 to 3 times faster than the global average, partly due to changes in short-lived climate forcers (SLCFs) including aerosols. In order to study the effects of atmospheric aerosols in this warming, recent past (1990-2014) and future (2015-2050) simulations have been carried out using the GISS-E2.1 Earth system model to study the aerosol burdens and their radiative and climate impacts over the Arctic (> 60 degrees N), using anthropogenic emissions from the Eclipse V6b and the Coupled Model Inter-comparison Project Phase 6 (CMIP6) databases, while global annual mean greenhouse gas concentrations were prescribed and kept fixed in all simulations. Results showed that the simulations have underestimated observed surface aerosol levels, in particular black carbon (BC) and sulfate (SO42-), by more than 50 %, with the smallest biases calculated for the atmosphere-only simulations, where winds are nudged to reanalysis data. CMIP6 simulations performed slightly better in reproducing the observed surface aerosol concentrations and climate parameters, compared to the Eclipse simulations. In addition, simulations where atmosphere and ocean are fully coupled had slightly smaller biases in aerosol levels compared to atmosphere-only simulations without nudging. Arctic BC, organic aerosol (OA), and SO(4)(2-)burdens decrease significantly in all simulations by 10 %-60% following the reductions of 7 %-78% in emission projections, with the Eclipse ensemble showing larger reductions in Arctic aerosol burdens compared to the CMIP6 ensemble. For the 2030-2050 period, the Eclipse ensemble simulated a radiative forcing due to aerosol-radiation interactions (RFARI) of -0.39 +/- 0.01Wm(-2), which is -0.08Wm(-2) larger than the 1990-2010 mean forcing (-0.32Wm(-2)), of which -0.24 +/- 0.01Wm(-2) was attributed to the anthropogenic aerosols. The CMIP6 ensemble simulated a RFARI of --0.35 to -0.40Wm(-2) for the same period, which is -0.01 to -0.06Wm(-2) larger than the 1990-2010 mean forcing of 0.35Wm(-2). The scenarios with little to no mitigation (worst-case scenarios) led to very small changes in the RFARI, while scenarios with medium to large emission mitigations led to increases in the negative RFARI, mainly due to the decrease in the positive BC forcing and the decrease in the negative SO42- forcing. The anthropogenic aerosols accounted for -0.24 to -0.26Wm(-2) of the net RFARI in 2030-2050 period, in Eclipse and CMIP6 ensembles, respectively. Finally, all simulations showed an increase in the Arctic surface air temperatures throughout the simulation period. By 2050, surface air temperatures are projected to increase by 2.4 to 2.6 degrees C in the Eclipse ensemble and 1.9 to 2.6 degrees C in the CMIP6 ensemble, compared to the 1990-2010 mean. Overall, results show that even the scenarios with largest emission reductions leads to similar impact on the future Arctic surface air temperatures and sea-ice extent compared to scenarios with smaller emission reductions, implying reductions of greenhouse emissions are still necessary to mitigate climate change.

National Category
Meteorology and Atmospheric Sciences
Research subject
Climate
Identifiers
urn:nbn:se:smhi:diva-6136 (URN)10.5194/acp-21-10413-2021 (DOI)000672721000004 ()
Available from: 2021-08-03 Created: 2021-08-03 Last updated: 2021-08-03Bibliographically approved
Thomas, M., Devasthale, A., Koenigk, T., Wyser, K., Roberts, M., Roberts, C. & Lohmann, K. (2019). A statistical and process-oriented evaluation of cloud radiative effects in high-resolution global models. Geoscientific Model Development, 12(4), 1679-1702
Open this publication in new window or tab >>A statistical and process-oriented evaluation of cloud radiative effects in high-resolution global models
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2019 (English)In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 12, no 4, p. 1679-1702Article in journal (Refereed) Published
National Category
Climate Research
Research subject
Climate
Identifiers
urn:nbn:se:smhi:diva-5201 (URN)10.5194/gmd-12-1679-2019 (DOI)000466174100001 ()
Available from: 2019-05-07 Created: 2019-05-07 Last updated: 2020-05-05Bibliographically approved
Thomas, M., Devasthale, A., L'Ecuyer, T., Wang, S., Koenigk, T. & Wyser, K. (2019). Snowfall distribution and its response to the Arctic Oscillation: an evaluation of HighResMIP models in the Arctic using CPR/CloudSat observations. Geoscientific Model Development, 12(8), 3759-3772
Open this publication in new window or tab >>Snowfall distribution and its response to the Arctic Oscillation: an evaluation of HighResMIP models in the Arctic using CPR/CloudSat observations
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2019 (English)In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 12, no 8, p. 3759-3772Article in journal (Refereed) Published
National Category
Climate Research
Research subject
Climate
Identifiers
urn:nbn:se:smhi:diva-5414 (URN)10.5194/gmd-12-3759-2019 (DOI)000483069400001 ()
Available from: 2019-09-18 Created: 2019-09-18 Last updated: 2020-05-05Bibliographically approved
Thomas, M., Devasthale, A., Tjernstrom, M. & Ekman, A. M. L. (2019). The Relation Between Aerosol Vertical Distribution and Temperature Inversions in the Arctic in Winter and Spring. Geophysical Research Letters, 46(5), 2836-2845
Open this publication in new window or tab >>The Relation Between Aerosol Vertical Distribution and Temperature Inversions in the Arctic in Winter and Spring
2019 (English)In: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 46, no 5, p. 2836-2845Article in journal (Refereed) Published
National Category
Climate Research
Research subject
Climate
Identifiers
urn:nbn:se:smhi:diva-5180 (URN)10.1029/2018GL081624 (DOI)000462612900056 ()
Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2020-05-05
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
Thomas, M. & Devasthale, A. (2017). Typical meteorological conditions associated with extreme nitrogen dioxide (NO2) pollution events over Scandinavia. Atmospheric Chemistry And Physics, 17(19), 12071-12080
Open this publication in new window or tab >>Typical meteorological conditions associated with extreme nitrogen dioxide (NO2) pollution events over Scandinavia
2017 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 17, no 19, p. 12071-12080Article in journal (Refereed) Published
National Category
Environmental Sciences
Research subject
Environment
Identifiers
urn:nbn:se:smhi:diva-4307 (URN)10.5194/acp-17-12071-2017 (DOI)000412824300001 ()
Available from: 2017-11-13 Created: 2017-11-13 Last updated: 2020-05-05Bibliographically 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
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ORCID iD: ORCID iD iconorcid.org/0000-0002-5709-7507

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