Polar stratospheric cloud climatology based on CALIPSO spaceborne lidar measurements from 2006–2017

Pitts, Mıchael; Poole, L. R.; Gonzalez, Ryan

doi:10.5194/acp-2018-234

Cited by 22 publications

(85 citation statements)

References 48 publications

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“…Today, it is known that there is a variety of particles present at low temperatures in the polar vortices (e.g. Pitts et al, 2011Pitts et al, , 2018Spang et al, 2018), namely ice particles of different sizes and number densities, nitric acid trihydrate (NAT) particles, liquid supercooled ternary H 2 SO 4 / H 2 O / HNO 3 solution (STS) particles and cold binary sulfate aerosol. All of these particles can, in principle, facilitate the heterogeneous reactions that lead to activation of chlorine in the polar stratosphere (Peter, 1997;Solomon, 1999;Wegner et al, 2012;Drdla and Müller, 2012;Shi et al, 2001;Grooß et al, 2011).…”

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confidence: 99%

On the discrepancy of HCl processing in the core of the wintertime polar vortices

Grooß¹,

Müller²,

Spang³

et al. 2018

Atmos. Chem. Phys.

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Abstract. More than 3 decades after the discovery of the ozone hole, the processes involved in its formation are believed to be understood in great detail. Current state-of-the-art models can reproduce the observed chemical composition in the springtime polar stratosphere, especially regarding the quantification of halogen-catalysed ozone loss. However, we report here on a discrepancy between simulations and observations during the less-well-studied period of the onset of chlorine activation. During this period, which in the Antarctic is between May and July, model simulations significantly overestimate HCl, one of the key chemical species, inside the polar vortex during polar night. This HCl discrepancy is also observed in the Arctic. The discrepancy exists in different models to varying extents; here, we discuss three independent ones, the Chemical Lagrangian Model of the Stratosphere (CLaMS) as well as the Eulerian models SD-WACCM (the specified dynamics version of the Whole Atmosphere Community Climate Model) and TOMCAT/SLIMCAT. The HCl discrepancy points to some unknown process in the formulation of stratospheric chemistry that is currently not represented in the models. We characterise the HCl discrepancy in space and time for the Lagrangian chemistry–transport model CLaMS, in which HCl in the polar vortex core stays about constant from June to August in the Antarctic, while the observations indicate a continuous HCl decrease over this period. The somewhat smaller discrepancies in the Eulerian models SD-WACCM and TOMCAT/SLIMCAT are also presented. Numerical diffusion in the transport scheme of the Eulerian models is identified to be a likely cause for the inter-model differences. Although the missing process has not yet been identified, we investigate different hypotheses on the basis of the characteristics of the discrepancy. An underestimated HCl uptake into the polar stratospheric cloud (PSC) particles that consist mainly of H2O and HNO3 cannot explain it due to the temperature correlation of the discrepancy. Also, a direct photolysis of particulate HNO3 does not resolve the discrepancy since it would also cause changes in chlorine chemistry in late winter which are not observed. The ionisation caused by galactic cosmic rays provides an additional NOx and HOx source that can explain only about 20 % of the discrepancy. However, the model simulations show that a hypothetical decomposition of particulate HNO3 by some other process not dependent on the solar elevation, e.g. involving galactic cosmic rays, may be a possible mechanism to resolve the HCl discrepancy. Since the discrepancy reported here occurs during the beginning of the chlorine activation period, where the ozone loss rates are small, there is only a minor impact of about 2 % on the overall ozone column loss over the course of Antarctic winter and spring.

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confidence: 99%

On the discrepancy of HCl processing in the core of the wintertime polar vortices

Grooß¹,

Müller²,

Spang³

et al. 2018

Atmos. Chem. Phys.

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“…The Level 2 PSC Mask Product Version 1.0 (v1) is based on PSC detection and classification as described in Pitts et al (2011). Within this study, we make use of Version 2.0 (v2) of the PSC product, which has recently been introduced in Pitts et al (2018). PSCs are detected as statistical outliers relative ice particles as a function of wavelength (e.g.…”

Section: Caliopmentioning

confidence: 99%

“…The PSC areal coverage is estimated as the sum of the occurrence frequency multiplied by the total area. This approach has also been used by Spang et al (2018) and Pitts et al (2018) and bypasses the caveat of the irregular sampling density due to the orbit geometry. MIPAS observations and CLaMS simulations are only considered at latitudes < 82…”

Section: Mipasmentioning

confidence: 99%

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Lagrangian simulation of ice particles and resulting dehydration in the polar winter stratosphere

Tritscher¹,

Grooß²,

Spang³

et al. 2018

Preprint

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“…In V4, however, the operational CAD algorithm now distinguishes between clouds and aerosols in the stratosphere 20 , and stratospheric aerosols are further evaluated to determine aerosol type (Kim et al, 2018). For PSCs, the CALIPSO project also produces a dedicated PSC data product that reports PSC presence in 5 km horizontal by 180 m vertical bins and classifies each bin according to a composition classification scheme described by Pitts et al (2018). The compositions in the dedicated PSC product include water ice, supercooled ternary solutions (STS), and several mixtures of liquid droplets and nitric acid trihydrate (NAT).…”

Section: Fringesmentioning

confidence: 99%

Application of High-Dimensional Fuzzy K-means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination

Zeng¹,

Vaughan²,

Liu³

et al. 2018

Preprint

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Abstract. This study applies Fuzzy K-Means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products and compares the clustering results with cloud-aerosol discrimination (CAD) scores reported in the 10 version 4.1 release of the CALIPSO data products. The selection of samples, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameter analyses in feature type discrimination are discussed. Statistical results show that the FKM classification agrees with the CAD algorithm classification for more than 94% of the cases in troposphere. This is because the lidar-measured signatures of most clouds and aerosols are naturally different.Based on their different natures, objective methods can effectively separate clouds from aerosols in most cases. In addition to 15 validating the current CAD algorithm, the FKM clustering can also provide new insights and supplemental information to help better understand the driving parameters in the scene classification process.

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Polar stratospheric cloud climatology based on CALIPSO spaceborne lidar measurements from 2006–2017

Abstract: there has been no obvious long-term trend.

Cited by 22 publications

References 48 publications

On the discrepancy of HCl processing in the core of the wintertime polar vortices

On the discrepancy of HCl processing in the core of the wintertime polar vortices

Lagrangian simulation of ice particles and resulting dehydration in the polar winter stratosphere

Application of High-Dimensional Fuzzy K-means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination

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