Dehydration and sedimentation of ice particles in the Arctic stratospheric vortex

Vömel, H.; Rummukainen, Markku; Kivi, Rigel; Karhu, Juha; Turunen, T.; Kyrö, E.; Rosen, James M.; Kjome, Norman T.; Oltmans, S. J.

doi:10.1029/97gl00668

Cited by 50 publications

(35 citation statements)

References 16 publications

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“…If ice clouds had occurred prior to the lidar measurements, the water vapour content could have decreased significantly. Measurements at Sodankylä on 23 January at 00:00 UTC indicated that H 2 O dropped under 3 ppmv between 22 and 24 km (Vömel et al, 1997). Therefore, lower H 2 O could have been considered.…”

Section: Refractive Indexmentioning

confidence: 99%

Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements

et al. 2008

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Abstract.A method for estimating the stratospheric particle size distribution from multiwavelength lidar measurements is presented. It is based on matching measured and modelsimulated backscatter coefficients. The lidar backscatter coefficients measured at the three commonly used wavelengths 355, 532 and 1064 nm are compared to a precomputed lookup table of model-calculated values. The optical model assumes that particles are spherical and that their size distribution is unimodal. This inverse problem is not trivial because the optical model is highly non-linear with a strong sensitivity to the size distribution parameters in some cases. The errors in the lidar backscatter coefficients are explicitly taken into account in the estimation. The method takes advantage of the statistical properties of the possible solution cluster to identify the most probable size distribution parameters. In order to discard model-simulated outliers resulting from the strong non-linearity of the model, solutions farther than one standard deviation of the median values of the solution cluster are filtered out, because the most probable solution is expected to be in the densest part of the cluster. Within the filtered solution cluster, the estimation algorithm minimizes a cost function of the misfit between measurements and model simulations.Two validation cases are presented on Polar Stratospheric Cloud (PSC) events detected above the ALOMAR observatory (69 • N -Norway). A first validation is performed against optical particle counter measurements carried out in January 1996. In non-depolarizing regions of the cloud (i.e. spherical particles), the parameters of an unimodal size distribution and those of the optically dominant mode of a bimodal size distribution are quite successfully retrieved, especially for the median radius and the geometrical standard deviation. As expected, the algorithm performs poorly when Correspondence to: J. Jumelet (julien.jumelet@aero.jussieu.fr) solid particles drive the backscatter coefficient. A small bias is identified in modelling the refractive index when compared to previous works that inferred PSC type Ib refractive indices. The accuracy of the size distribution retrieval is improved when the refractive index is set to the value inferred in the reference paper.Our results are then compared to values retrieved with another similar method that does not account for the effect of the measurements errors and the non-linearity of the optical model on the likelihood of the solution. The case considered is a liquid PSC observed over northern Scandinavia on January 2005. An excellent agreement is found between the two methods when our algorithm is applied without any statistical filtering of the solution cluster. However, the solution for the geometrical standard deviation appears to be rather unlikely with a value close to unity (σ ≈1.04). When our algorithm is applied with solution filtering, a more realistic value of the standard deviation (σ ≈1.27) is found. This highlights the importance of taking int...

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Section: Refractive Indexmentioning

confidence: 99%

Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements

et al. 2008

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“…It has been shown that the nucleation of NAT on ice is quite efficient (e.g. Fueglistaler et al, 2002;Hoyle et al, 2013). The sedimentation of large HNO 3 containing ice PSC particles can lead to greater denitrification than the sedimentation of (typically smaller) NAT or liquid PSC particles alone (Lowe and MacKenzie, 2008;Wohltmann et al, 2013;Manney and Lawrence, 2016).…”

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“…Kelly et al, 1989;Vömel et al, 1995;Nedoluha et al, 2000) but only rarely in the Arctic (e.g. Fahey et al, 1990;Vömel et al, 1997;Pan et al, 2002;Schiller et al, 2002;Khaykin et al, 2013).…”

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

et al. 2017

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“…During cold Arctic winters dehydration has been observed in the Arctic (e.g. Fahey et al, 1990;Ovarlez and Ovarlez, 1994;Vömel et al, 1997;Jimenez et al, 2006), thus making the process of ice formation on NAT particles and subsequent sedimentation that causes denitrification possible during such winters. Further, in a recent study by Pitts et al (2011) analysing CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) observations for the Arctic winter 2009/2010 an increase of ice observations with a coincident decrease in NAT mixtures under a synopticscale cooling event was observed, suggesting that under these conditions heterogeneous nucleation on NAT particles may be an important process for ice PSC formation.…”

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Denitrification and polar stratospheric cloud formation during the Arctic winter 2009/2010

et al. 2011

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Abstract. The sedimentation of HNO 3 containing Polar Stratospheric Cloud (PSC) particles leads to a permanent removal of HNO 3 and thus to a denitrification of the stratosphere, an effect which plays an important role in stratospheric ozone depletion. The polar vortex in the Arctic winter 2009/2010 was very cold and stable between end of December and end of January. Strong denitrification between 475 to 525 K was observed in the Arctic in mid of January by the Odin Sub Millimetre Radiometer (Odin/SMR). This was the strongest denitrification that had been observed in the entire Odin/SMR measuring period (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010). Lidar measurements of PSCs were performed in the area of Kiruna, Northern Sweden with the IRF (Institutet för Rymdfysik) lidar and with the Esrange lidar in January 2010. The measurements show that PSCs were present over the area of Kiruna during the entire period of observations. The formation of PSCs during the Arctic winter 2009/2010 is investigated using a microphysical box model. Box model simulations are performed along air parcel trajectories calculated six days backward according to the PSC measurements with the ground-based lidar in the Kiruna area. From the temperature history of the backward trajectories and the box model simulations we find two PSC regions, one over Kiruna according to the measurements made in Kiruna and one north of Scandinavia which is much colder, reaching also temperatures below T ice . Using the box model simulations along backward Correspondence to: F. Khosrawi (farah@misu.su.se) trajectories together with the observations of Odin/SMR, Aura/MLS (Microwave Limb Sounder), CALIPSO (CloudAerosol Lidar and Infrared Pathfinder Satellite Observations) and the ground-based lidar we investigate how and by which type of PSC particles the denitrification that was observed during the Arctic winter 2009/2010 was caused. From our analysis we find that due to an unusually strong synoptic cooling event in mid January, ice particle formation on NAT may be a possible formation mechanism during that particular winter that may have caused the denitrification observed in mid January. In contrast, the denitrification that was observed in the beginning of January could have been caused by the sedimentation of NAT particles that formed on mountain wave ice clouds.

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Dehydration and sedimentation of ice particles in the Arctic stratospheric vortex

Cited by 50 publications

References 16 publications

Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements

Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements

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

Denitrification and polar stratospheric cloud formation during the Arctic winter 2009/2010

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