Forecasts and assimilation experiments of the Antarctic ozone hole 2008

Flemming, Johannes; Inness, Antje; Jones, Luke; Eskes, Henk; Huijnen, Vincent; Schultz, Martin; Stein, Olaf; Cariolle, D.; Kinnison, Douglas E.; Brasseur, Guy

doi:10.5194/acp-11-1961-2011

Cited by 36 publications

(38 citation statements)

References 64 publications

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“…These results are similar to those found with IFS-MOZART by Flemming et al (2011). In the case of the BASCOE CTM, this is due to the absence of tropospheric processes and surface emissions, which prevents proper exchanges with the troposphere; and to the parameterisation of PSC surface area density, which lacks any memory of the coldness experienced by polar air masses.…”

Section: Bascoesupporting

confidence: 77%

“…This indicates that IFS-MOZART has problems with a correct simulation of the ozone depletion. This is a known problem of the underlying MOZART CTM in the MACC configuration, which cannot be completely fixed by the data assimilation (Flemming et al, 2011;Inness et al, 2013), especially because the assimilated profile only gives information down to 68 hPa. MOZART performs better with WACCM meteorology (Kinnison et al, 2007), which indicates that the chemical parameterisations are sensitive to the meteorological fields that are used to drive transport in the models.…”

Section: Antarctic -Neumayermentioning

confidence: 99%

“…Thanks to their gridded and instantaneous description of the atmospheric composition, chemical analyses enable short-range to middle-range forecasts (Flemming et al, 2011) and are much easier to use and to interpret than satellite observations. The resulting "snapshot" maps show stratospheric composition at a specific time and are routinely used to monitor the evolution of the ozone layer, e.g.…”

Section: Introductionmentioning

confidence: 99%

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Copernicus stratospheric ozone service, 2009–2012: validation, system intercomparison and roles of input data sets

et al. 2015

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Abstract. This paper evaluates and discusses the quality of the stratospheric ozone analyses delivered in near real time by the MACC (Monitoring Atmospheric Composition and Climate) project during the 3-year period between September 2009 and September 2012. Ozone analyses produced by four different chemical data assimilation (CDA) systems are examined and compared: the Integrated Forecast System coupled to the Model for OZone And Related chemical Tracers (IFS-MOZART); the Belgian Assimilation System for Chemical ObsErvations (BASCOE); the Synoptic Analysis of Chemical Constituents by Advanced Data Assimilation (SACADA); and the Data Assimilation Model based on Transport Model version 3 (TM3DAM). The assimilated satellite ozone retrievals differed for each system; SACADA and TM3DAM assimilated only total ozone observations, BASCOE assimilated profiles for ozone and some related species, while IFS-MOZART assimilated both types of ozone observations. All analyses deliver total column values that agree well with ground-based observations (biases < 5 %) and have a realistic seasonal cycle, except for BASCOE analyses, which underestimate total ozone in the tropics all year long by 7 to 10 %, and SACADA analyses, which overestimate total ozone in polar night regions by up to 30 %. The validation of the vertical distribution is based on independent observations from ozonesondes and the ACE-FTS (Atmospheric Chemistry Experiment -Fourier Transform Spectrometer) satellite instrument. It cannot be performed with TM3DAM, which is designed only to deliver analyses of total ozone columns. Vertically alternating positive and negative biases are found in the IFS-MOZART analyses as well as an overestimation of 30 to 60 % in the polar lower stratosphere during polar ozone depletion events. SACADA underestimates lower stratospheric ozone by up to 50 % during these events above the South Pole and overestimates it by approximately the same amount in the tropics. The three-dimensional (3-D) analyses delivered by BASCOE are found to have the best quality among the three systems resolving the vertical dimension, with biases not exceeding 10 % all year long, at all stratospheric levels and in all latitude bands, except in the tropical lowermost stratosphere.The northern spring 2011 period is studied in more detail to evaluate the ability of the analyses to represent the exceptional ozone depletion event, which happened above the Arctic in March 2011. Offline sensitivity tests are performed during this month and indicate that the differences between the forward models or the assimilation algorithms are much less important than the characteristics of the assimilated data sets. They also show that IFS-MOZART is able to deliver realistic analyses of ozone both in the troposphere and in the stratoPublished by Copernicus Publications on behalf of the European Geosciences Union. sphere, but this requires the assimilation of observations from nadir-looking instruments as well as the assimilation of profiles, which are well resolved vertically an...

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Section: Bascoesupporting

confidence: 77%

Section: Antarctic -Neumayermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Copernicus stratospheric ozone service, 2009–2012: validation, system intercomparison and roles of input data sets

et al. 2015

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“…For example, O 3 profile retrievals from MLS were assimilated together with O 3 total column retrievals from OMI, SBUV-2 and SCIAMACHY to exploit synergies of different instruments (Flemming et al, 2011). To reduce detrimental effects of inter-instrument biases, the variational bias correction scheme (Dee and Uppala, 2009) developed for the meteorological assimilation was adapted to correct multiple atmospheric composition retrievals.…”

Section: Case Study From Ecmwf: Macc Re-analysis Of Atmospheric Compomentioning

confidence: 99%

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

et al. 2015

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Abstract. Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of three-dimensional chemical (including aerosol) concentrations and perform inverse modeling of input variables or model parameters (e.g., emissions). Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. They offer the possibility to assimilate both meteorological and chemical data; however, because CCMM are fairly recent, data assimilation in CCMM has been limited to date. We review here the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data assimilation in CCMM. We first review the methods available for data assimilation in atmospheric models, including variational methods, ensemble Kalman filters, and hybrid methods. Next, we review past applications that have included chemical data assimilation in chemical transport models

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“…Advanced data assimilation allows the propagation of observational information in time and space and from a limited number of observed species to a wide range of chemical components and provides global fields that are physically and chemically consistent and in agreement with individual observations (Sandu and Chai, 2011;Bocquet et al, 2015). Various studies have demonstrated the capability of data assimilation techniques in the analysis of chemical species in the troposphere and stratosphere (e.g., Stajner and Wargan, 2004;Jackson, 2007;Parrington et al, 2009;Kiesewetter et al, 2010;Flemming et al, 2011;Coman et al, 2012;Inness et al, 2013;Emili et al, 2014;Miyazaki et al, 2012aMiyazaki et al, , b, 2014Miyazaki et al, , 2015Miyazaki et al, , 2017Miyazaki and Eskes, 2013;van der A et al, 2015;Gaubert et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis

Miyazaki

Bowman

2017

Atmos. Chem. Phys.

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Abstract. The Atmospheric Chemistry Climate Model Intercomparison Project (ACCMIP) ensemble ozone simulations for the present day from the 2000 decade simulation results are evaluated by a state-of-the-art multi-constituent atmospheric chemical reanalysis that ingests multiple satellite data including the Tropospheric Emission Spectrometer (TES), the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), and the Measurement of Pollution in the Troposphere (MOPITT) for [2005][2006][2007][2008][2009]. Validation of the chemical reanalysis against global ozonesondes shows good agreement throughout the free troposphere and lower stratosphere for both seasonal and year-to-year variations, with an annual mean bias of less than 0.9 ppb in the middle and upper troposphere at the tropics and midlatitudes. The reanalysis provides comprehensive spatiotemporal evaluation of chemistry-model performance that compliments direct ozonesonde comparisons, which are shown to suffer from significant sampling bias. The reanalysis reveals that the ACCMIP ensemble mean overestimates ozone in the northern extratropics by 6-11 ppb while underestimating by up to 18 ppb in the southern tropics over the Atlantic in the lower troposphere. Most models underestimate the spatial variability of the annual mean lower tropospheric concentrations in the extratropics of both hemispheres by up to 70 %. The ensemble mean also overestimates the seasonal amplitude by 25-70 % in the northern extratropics and overestimates the inter-hemispheric gradient by about 30 % in the lower and middle troposphere. A part of the discrepancies can be attributed to the 5-year reanalysis data for the decadal model simulations. However, these differences are less evident with the current sonde network. To estimate ozonesonde sampling biases, we computed model bias separately for global coverage and the ozonesonde network. The ozonesonde sampling bias in the evaluated model bias for the seasonal mean concentration relative to global coverage is 40-50 % over the western Pacific and east Indian Ocean and reaches 110 % over the equatorial Americas and up to 80 % for the global tropics. In contrast, the ozonesonde sampling bias is typically smaller than 30 % for the Arctic regions in the lower and middle troposphere. These systematic biases have implications for ozone radiative forcing and the response of chemistry to climate that can be further quantified as the satellite observational record extends to multiple decades.

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Forecasts and assimilation experiments of the Antarctic ozone hole 2008

Cited by 36 publications

References 64 publications

Copernicus stratospheric ozone service, 2009–2012: validation, system intercomparison and roles of input data sets

Copernicus stratospheric ozone service, 2009–2012: validation, system intercomparison and roles of input data sets

Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis

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