Implementing growth and sedimentation of NAT particles in a global Eulerian model

Broek, M. van den; Williams, J. E.; Bregman, Ahron

doi:10.5194/acp-4-1869-2004

Cited by 17 publications

(9 citation statements)

References 44 publications

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“…The long period of temperatures below the ice formation threshold led to much greater dehydration than previously seen in the Arctic (Manney and Lawrence, 2016). Large areas of ice PSC throughout January were observed with CALIPSO that also were the greatest observed in the Arctic in the 8 years of the CALIPSO data record (Voigt et al, 2016). In the EMAC simulation, large areas of ice PSCs are simulated throughout January (Fig.…”

Section: Dehydrationmentioning

confidence: 72%

“…Satellite observations indicate that sedimentation of PSC particles led to denitrification as well as dehydration of stratospheric layers (Manney and Lawrence, 2016). Widespread persistent ice PSC layers were observed by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) (Voigt et al, 2016). Ozone destruction was strong, but not as strong as in 2010/2011, since a major final sudden stratospheric warming ended the 2015/2016 Arctic winter by early March (Manney and Lawrence, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Denitrification, dehydration and ozone loss during the Arctic winter 2015/2016

Khosrawi¹,

Kirner²,

Sinnhuber³

et al. 2017

Preprint

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Abstract. The Arctic winter 2015/2016 was one of the coldest stratospheric winters in recent years. A stable vortex formed by early December and the early winter was exceptionally cold. Cold pool temperatures dropped below the Nitric Acid Trihydrate (NAT) existence temperature of about 195 K, thus allowing Polar Stratospheric Clouds (PSCs) to form. The low temperatures in the polar stratosphere persisted until early March allowing chlorine activation and catalytic ozone destruction. Satellite observations indicate that sedimentation of PSC particles led to denitrification as well as dehydration of stratospheric layers. Model simulations of the Arctic winter 2015/2016 nudged toward European Center for Medium-Range Weather Forecasts (ECMWF) analyses data were performed with the atmospheric chemistry&#8211;climate model ECHAM5/MESSy Atmospheric Chemistry (EMAC) for the Polar Stratosphere in a Changing Climate (POLSTRACC) campaign. POLSTRACC is a High Altitude and LOng Range Research Aircraft (HALO) mission aimed at the investigation of the structure, composition and evolution of the Arctic Upper Troposphere and Lower Stratosphere (UTLS). The chemical and physical processes involved in Arctic stratospheric ozone depletion, transport and mixing processes in the UTLS at high latitudes, polar stratospheric clouds as well as cirrus clouds are investigated. In this study an overview of the chemistry and dynamics of the Arctic winter 2015/2016 as simulated with EMAC is given. Further, chemical-dynamical processes such as denitrification, dehydration and ozone loss during the Arctic winter 2015/2016 are investigated. Comparisons to satellite observations by the Aura Microwave Limb Sounder (Aura/MLS) as well as to airborne measurements with the Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) performed on board of HALO during the POLSTRACC campaign show that the EMAC simulations are in fairly good agreement with observations. We derive a maximum polar stratospheric O3 loss of ~&#8201;2&#8201;ppmv or 100&#8201;DU in terms of column in mid March. The stratosphere was denitrified by about 8&#8201;ppbv HNO3 and dehydrated by about 1&#8201;ppmv H2O in mid to end of February. While ozone loss was quite strong, but not as strong as in 2010/2011, denitrification and dehydration were so far the strongest observed in the Arctic stratosphere in the at least past 10 years.

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Section: Dehydrationmentioning

confidence: 72%

Section: Introductionmentioning

confidence: 99%

Denitrification, dehydration and ozone loss during the Arctic winter 2015/2016

Khosrawi¹,

Kirner²,

Sinnhuber³

et al. 2017

Preprint

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“…3.2.1) implemented in the submodel. A new parameterisation for NAT particles based on the efficient growth and sedimentation algorithm of van den Broek et al (2004) and Carslaw et al (2002) has been implemented (described in Sect. 3.2.2) and is available since EMAC version 1.9 (released 2010).…”

Section: The Submodel Pscmentioning

confidence: 99%

“…In the kinetic growth NAT parameterisation of the submodel PSC consequently a separation into eight size bins is implemented (see Table 2). These are based on a PSC algorithm in the chemistry transport model (CTM) TM5 described by van den Broek et al (2004). For every size bin a minimum, a maximum and a mean radius (r NAT(bin) in µm) exist, as well as a maximum number density (in particles cm −3 ).…”

Section: Growth Of Nat Particles Over Size Binsmentioning

confidence: 99%

Simulation of polar stratospheric clouds in the chemistry-climate-model EMAC via the submodel PSC

et al. 2011

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Abstract. The submodel PSC of the ECHAM5/MESSy Atmospheric Chemistry model (EMAC) has been developed to simulate the main types of polar stratospheric clouds (PSC). The parameterisation of the supercooled ternary solutions (STS, type 1b PSC) in the submodel is based on Carslaw et al. (1995b), the thermodynamic approach to simulate ice particles (type 2 PSC) on Marti and Mauersberger (1993). For the formation of nitric acid trihydrate (NAT) particles (type 1a PSC) two different parameterisations exist. The first is based on an instantaneous thermodynamic approach from Hanson and Mauersberger (1988), the second is new implemented and considers the growth of the NAT particles with the aid of a surface growth factor based on Carslaw et al. (2002). It is possible to choose one of this NAT parameterisation in the submodel. This publication explains the background of the submodel PSC and the use of the submodel with the goal of simulating realistic PSC in EMAC.

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“…The TM5 model has been developed at the Institute of Marine and Atmospheric research Utrecht (IMAU) in cooperation with the Royal Dutch Meteorological Institute (KNMI) and the Dutch center for Mathematics and Computer Science (CWI). The TM5 model has been used to study stratospheric chemistry and transport [ Bregman et al , 2003; van den Broek et al , 2003, 2004]. A detailed description of the TM5 model is given in work by Krol et al [2005].…”

Section: Model and Measurementsmentioning

confidence: 99%

Validation of Global Ozone Monitoring Experiment ozone profiles and evaluation of stratospheric transport in a global chemistry transport model

et al. 2007

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[1] This paper presents a validation of Global Ozone Monitoring Experiment (GOME) ozone (O 3 ) profiles which are used to evaluate stratospheric transport in the chemistry transport model (CTM) Tracer Model version 5 (TM5) using a linearized stratospheric O 3 chemistry scheme. A comparison of GOME O 3 profile measurements with independent O 3 sonde measurements at midlatitudes shows an excellent agreement. Differences are smaller than 5%, well within the uncertainty of the O 3 sonde measurements. Within the tropics, the GOME O 3 profile differences are larger, with a clear lower stratospheric negative O 3 bias with compensating positive biases in the troposphere and higher stratosphere. The TM5 model with linearized O 3 chemistry simulates realistic lower and middle stratospheric spatial and temporal O 3 variations on both short (daily) and long (seasonal) timescales. Model stratospheric O 3 is significantly overestimated in the extratropics and slightly underestimated in the tropics, as is also shown in a comparison with Total Ozone Mapping Spectrometer total O 3 column measurements. This model bias predominantly occurs in the lower stratosphere and is present throughout the year, albeit with seasonal variations: The bias is larger during local winter compared with local summer. The particular spatial and seasonal variations of the model bias suggest a too fast meridional stratospheric transport in TM5, which agrees with earlier found shortcomings of using winds from data assimilation systems. The model results are very sensitive to the data assimilation method in the numerical weather prediction that provides the model wind fields. A large reduction (up to 50% of the bias) in modeled lower stratospheric midlatitude O 3 was found when winds from four-dimensional instead of three-dimensional data assimilation were used. Previous work has shown that using different forecast periods was important for improving the age of air. Model results differed with different forecast periods (up to 3 days), although the effect was mainly confined to high-latitude lower stratospheric O 3 . Apparently, using different forecast periods is more important for age-of-air calculations than for stratospheric O 3 calculations. A positive bias in the extratropical lower stratosphere of about 20% remained, possibly related to the lack of heterogeneous polar stratospheric O 3 destruction in TM5.

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Implementing growth and sedimentation of NAT particles in a global Eulerian model

Cited by 17 publications

References 44 publications

Denitrification, dehydration and ozone loss during the Arctic winter 2015/2016

Denitrification, dehydration and ozone loss during the Arctic winter 2015/2016

Simulation of polar stratospheric clouds in the chemistry-climate-model EMAC via the submodel PSC

Validation of Global Ozone Monitoring Experiment ozone profiles and evaluation of stratospheric transport in a global chemistry transport model

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