ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-16-15219-2016Interannual variations of early winter Antarctic polar stratospheric cloud formation and nitric acid observed by CALIOP and MLSLambertAlynalyn.lambert@jpl.nasa.govSanteeMichelle L.LiveseyNathaniel J.Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, California, USAAlyn Lambert (alyn.lambert@jpl.nasa.gov)8December20161623152191524619May201613June201617November201621November2016This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/16/15219/2016/acp-16-15219-2016.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/16/15219/2016/acp-16-15219-2016.pdf
We use satellite-borne measurements collected over the last decade
(2006–2015) from the Aura Microwave Limb Sounder (MLS) and the Cloud-Aerosol
Lidar with Orthogonal Polarization (CALIOP) to investigate the nitric acid
distribution and the properties of polar stratospheric clouds (PSCs) in the
early winter Antarctic vortex. Frequently, at the very start of the winter,
we find that synoptic-scale depletion of HNO3 can be detected in the
inner vortex before the first lidar detection of geophysically associated
PSCs. The generation of “sub-visible” PSCs can be explained as arising from
the development of a solid particle population with low number densities and
large particle sizes. Assumed to be composed of nitric acid trihydrate (NAT),
the sub-visible PSCs form at ambient temperatures well above the ice frost
point, but also above the temperature at which supercooled ternary solution
(STS) grows out of the background supercooled binary solution (SBS)
distribution. The temperature regime of their formation, inferred from the
simultaneous uptake of ambient HNO3 into NAT and their Lagrangian
temperature histories, is at a depression of a few
kelvin with respect to the NAT
existence threshold, TNAT. Therefore, their nucleation requires
a considerable supersaturation of HNO3 over NAT, and is consistent
with a recently described heterogeneous nucleation process on solid foreign
nuclei immersed in liquid aerosol. We make a detailed investigation of the
comparative limits of detection of PSCs and the resulting sequestration of
HNO3 imposed by lidar, mid-infrared, and microwave techniques. We
find that the temperature history of air parcels, in addition to the local
ambient temperature, is an important factor in the relative frequency of
formation of liquid/solid PSCs. We conclude that the initiation of NAT
nucleation and the subsequent development of large NAT particles capable of
sedimentation and denitrification in the early winter do not emanate from an
ice-seeding process. Finally, we investigate the patterns of interannual
variability and compare the relative formation frequency of liquid and solid
PSCs in the Antarctic lower polar stratosphere using the results of a cluster
analysis to synthesize the combined CALIOP and MLS measurements into a
relatively small number of interrelated categories.
Introduction
In we reported on the formation of polar
stratospheric clouds (PSCs) and the initial stages of denitrification in the
early 2008 Antarctic PSC season. The first appearance of PSCs was observed
through the uptake of gas-phase HNO3 by MLS and by patchy lidar
backscatter detection by CALIOP. Although the uptake of HNO3 was
substantial, the low lidar backscatter and ambient temperatures indicated a
nitric acid trihydrate (NAT) composition rather than supercooled ternary
solution (STS). An inference of large particle sizes with radii
≥ 5–7 µm and low NAT number density
(< 1 × 10-3 cm-3) was made from the combination of the
temperature, HNO3, and backscatter data, further confirmed by the
timescale of the appearance of an enhanced HNO3 layer at 68 hPa,
caused by sedimentation of NAT from above and evaporation back into the gas
phase. We also determined that in 2008 a NAT polar freezing belt
, generated by gravity-wave
induced ice-seeding, occurred after the first appearance of large particle
NAT clouds; i.e., the latter were not causally linked to the mountain wave
seeding events. In and , we
studied the uptake of HNO3 by different types of PSCs classified by
CALIOP as a function of temperature. We showed that the distributions of
gas-phase HNO3 vs. temperature combined with the independent CALIOP
PSC classification provide valuable insights into the
PSC formation process. Liquid STS particles exhibit well-defined equilibrium
properties, whereas the liquid/solid particle STS/NAT mixtures exhibit
non-equilibrium properties resulting from kinetically limited growth. In this
paper we expand our previous investigations to include the distribution of
the lidar backscatter of different PSC types as a function of temperature and
HNO3 uptake. We also report on the interannual variability in the
Antarctic PSC seasons from 2006 to 2015.
The discrimination between different PSC types at temperatures above the ice
frost point, TICE, stemming either from the growth of STS on
the background liquid supercooled binary solution (SBS) or the nucleation of
NAT, provides critical observations enabling validation of theoretical PSC
formation pathways. In the case of NAT, the nucleation processes are still
not understood in detail. Whether homogeneous or heterogeneous nucleation is
in force, it is the nucleated NAT number density that provides the key to the
subsequent microphysical development of the NAT clouds, since rapid
nucleation at high supersaturations leads to higher NAT number densities with
small particle radii, whereas slow nucleation at low supersaturations
produces low NAT number densities and allows the particles to grow to much
larger sizes . The homogeneous nucleation of NAT from
STS and the production of large-size NAT in the 2010/2011 Arctic winter has
been simulated in the SD-WACCM/CARMA PSC model (Whole-Atmosphere Community
Climate Model with Specified Dynamics with the Community Aerosol and
Radiation Model for Atmospheres) as described by . In
this model, homogeneous nucleation rates were determined using the nucleation
equations derived from laboratory experiments by
, with the free energy tuned by less than
10 %. The same nucleation rates were found by to
reproduce the observed timing of PSC formation during the Antarctic winter of
2011. In contrast, used an extension of the Zurich
Optical and Microphysical box Model (ZOMM) to include
a new pathway of heterogeneous formation of ice and NAT on solid foreign
nuclei inclusions, originating from meteoritic dust, that are assumed to be
present in at least 50 % of all aerosol drops .
determined that NAT can form heterogeneously at some
considerable vapor supersaturation, at temperatures well above the ice frost
point, on the solid foreign nuclei immersed in STS. Only a limited number of
surface inhomogeneities on the foreign nuclei provide favorable active sites
such that the NAT nucleation barrier is depressed sufficiently for nucleation
to occur. Once the most efficient active sites have caused nucleation at a
particular supersaturation, the remaining population of STS/foreign particles
have lower quality active sites that require either a higher supersaturation
to increase the nucleation rate or waiting for a longer period of time for
nucleation at the same supersaturation to occur. Three tuning parameters are
used to control the heterogeneous nucleation rate in the ZOMM model:
nucleation barrier, nucleation strength, and compatibility factor. These were
adjusted with consideration of the detection thresholds applied to the model
results , to replicate successfully
the CALIOP backscatter observations for a representative orbit. The tuned
model was then used to facilitate intercomparisons with the CALIOP
observations during December 2009 and to verify the model results for a few
case studies in the Arctic . However,
the low visibility of the NAT PSCs, as we indicated in
, poses a detection challenge for lidar backscatter
techniques, even though the accompanying HNO3 sequestration in NAT
can be substantial and detectable by other instruments as a decrease in the
gas-phase HNO3.
In situ measurements of NAT particles on a synoptic scale, with a large
particle mode of around 15 µm diameter, from the Forward Scattering
Spectrometer Probe (FSSP) , and observations of
their attendant denitrification , were reported
during the Arctic RECONCILE (reconciliation of essential process parameters
for an enhanced predictability of Arctic stratospheric ozone) campaign
. In order to resolve discrepancies involving
implied condensed HNO3 above that available from the gas phase
(including additional HNO3 brought down by renitrification) and
growth/sedimentation rates that are not commensurate with back-trajectories,
those authors hypothesized that the particles are non-compact or highly
aspherical or NAT-coated ice. coupled a
saturation-dependent parameterization of the ZOMM heterogeneous NAT scheme
with the Chemical Lagrangian Model of the Stratosphere (CLaMS) and determined
that derived PSC properties were in better agreement with CALIOP data than
for simulations using a constant rate NAT nucleation, thus confirming the
results of . Furthermore,
compared their simulations to the Arctic in situ aerosol size distributions
from FSSP in January 2010 and found that the observed large NAT particles
(exceeding 15 µm in diameter) were not present in the co-located
simulations. However, the CLaMS simulations did develop particle
distributions with median NAT diameters of up to 20 µm at other
times in the 2009/2010 Arctic winter. Hence, the new ZOMM nucleation scheme
is quite capable of producing large-size NAT, and
speculate that the presence of a highly
non-spherical NAT component coupled with the orientation of the particles
within the FSSP sample volume may lead to an overestimation of their actual
size. also found that particles with diameters of
20 µm were produced with their homogeneous nucleation scheme, which
does not require that there are special nuclei only available under certain
conditions.
PSC formation processes at play in the Arctic are clearly applicable to the
Antarctic, and the recent observations from RECONCILE add support to the
conclusions of our previous work , which highlighted
the appearance of synoptic-scale large particle NAT in the early Antarctic
winter of 2008. Obviously, the hypotheses concerning the origin and
microphysical characteristics of these so-called “NAT rocks” will be a
challenge to validate without further in situ observations. However, the
decade-long record of overlapping spaceborne CALIOP and MLS measurements
presents an opportunity to develop improved algorithms for the extraction of
information on PSCs and to apply new-found knowledge to the understanding of
their current and future role in ozone depletion.
In Sect. we review the satellite instruments and
atmospheric measurements used in our analyses. The temperature history of an
air parcel and the relation to heterogeneous nucleation of NAT is explored.
We introduce a compact alternative visualization to the standard graphical
representation of satellite orbit plots that enables easier comprehension of
several parameters plotted at multiple atmospheric levels and spanning many
days of observations. In Sect. we investigate the
limits of detection of equilibrium STS and STS/NAT mixtures separately for
lidar backscatter, mid-infrared extinction, and uptake of HNO3 from
the gas phase. We also investigate STS and NAT PSCs in terms of the
distributions in a three-parameter space of HNO3,
backscatter, and temperature. We
compare these with the CALIOP PSC classification scheme, which uses fixed
regions within a two-parameter discrimination domain (depolarization vs.
total backscatter). In Sect. we show orbit
transects and time series of co-located CALIOP and MLS data. These are used
to investigate the relative formation of liquid/solid PSCs and the resulting
denitrification and renitrification. In Sect. the
early stages of formation of Antarctic PSCs at 68–21 hPa in 2009 are
examined using CALIOP PSC types and Lagrangian temperature history, with the
inference of an initial population of sub-visible solid-particle NAT clouds
superseded by a predominantly liquid STS composition over a period of about a
week. Finally, the interannual variability of the early Antarctic PSC seasons
from 2006 to 2015 is discussed in Sect. .
Datasets and methodology
The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) dual-wavelength
elastic backscatter lidar flies on the Cloud-Aerosol
Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite
launched in April 2006. The Microwave Limb Sounder (MLS) is onboard the Aura
spacecraft launched in July 2004. CALIPSO and Aura are part of the NASA/ESA
afternoon “A-train” satellite constellation at 705 km nominal altitude and
98∘ inclination, with daily global coverage attained in 14.5 orbits.
The initial A-train configuration of the CALIPSO and Aura spacecraft from
April 2006 to April 2008 resulted in an across-track orbit offset of
∼ 200 km, with the MLS tangent point leading the CALIOP nadir view by
about 7.5 min. Since April 2008 Aura and CALIPSO have been operated to
maintain positioning within tightly constrained control boxes, such that the
MLS tangent point and the CALIOP nadir view are co-located to better than
about 10–20 km and about 30 s.
We derive co-located meteorological data from the Goddard Earth Observing
System Data Assimilation System (GEOS-5 DAS). The 6-hourly synoptic gridded
data products of temperatures and winds are supplied on a
540 by 361 longitude–latitude grid. The GEOS-5 data are interpolated in
location and time to the MLS along-track data. Parcel temperature histories
are obtained from the MLS Lagrangian Trajectory Diagnostic (LTD) dataset
, which consists of 15-day forward and reverse
trajectories launched from a curtain of points along the Aura MLS observation
track. The advection calculations are based on ,
with wind fields and diabatic heating rates taken from the 3-hourly
Modern-Era Retrospective Analysis for Research and Applications (MERRA-2)
dataset . Advances in both the GEOS-5 model and the
assimilation system, including GPS Radio Occultation datasets, are included
in MERRA-2. The integration uses a fourth-order Runge–Kutta scheme with a
5 min time step, and saved trajectory locations and temperatures are output
every 30 min. The MLS derived meteorological products (DMPs)
are used where necessary to identify measurement
locations that lie within the Antarctic vortex based on the potential
vorticity field, sPV<-1.4, scaled in “vorticity units”
.
CALIOP PSC data
We use the CALIOP Level-1b v3 standard data product to extract information on
PSCs (as documented in ) at a 50 km horizontal by
0.5 km vertical resolution. We also use a recently released Level-2
operational dataset – L2PSCMask (v1 Polar Stratospheric Cloud Mask Product)
– produced by the CALIPSO science team. The Level-2 operational data consist
of nighttime-only data and contain profiles of PSC presence, composition,
optical properties, and meteorological information along the CALIPSO orbit
tracks at 5 km horizontal by 180 m vertical resolution.
We have determined that the v1 L2PSCMask operational product has an incorrect
separation of the MIX1 and MIX2 classifications and does
not follow the boundary specification given by since
it failed to include in MIX1 those observations with a total
scattering ratio of less than 1.25. Separation of PSCs into the MIX1
and MIX2 classes is somewhat arbitrary, but provides useful
information on the NAT number densities .
The following three-step algorithm (using the Scientific Data Set variable
names supplied with the CALIPSO Hierarchical Data Files (HDF) files) has been
applied to generate the correct MIX1 and MIX2 classes:
INVBR=1.-1./TOTAL_SCATTERING_RATIO_532MIX1=PSC_CompositionEQ 2OR(PSC_CompositionEQ 3AND(INVBRLE 0.2))MIX2=PSC_CompositionEQ 3AND(INVBRGT 0.2)
MLS gas-phase constituents
The Microwave Limb Sounder measures thermal emission at millimeter and
sub-millimeter wavelengths from the Earth's limb
along the forward direction of the Aura spacecraft flight track, with a
vertical scan from the surface to 90 km every 24.7 s. Each orbit consists
of 240 scans spaced at 1.5∘ (165 km) along-track, with a total of
almost 3500 profiles per day and a latitudinal coverage of 82∘ S to
82∘ N. The Level-1 limb radiance measurements are inverted using 2-D
optimal estimation to produce Level-2 profiles of
atmospheric temperature and composition. Validation of the MLS H2O
and HNO3 data products and error estimations are discussed in detail
by , , and
. Here we use the MLS version 4 (v4) data
with single-profile precisions (accuracies) of
4–15 % (4–7 %) for H2O and 0.6 ppbv (1–2 ppbv) for
HNO3.
Temperature history and relation to NAT nucleation and growth processes
In this work we frequently apply a convenient temperature coordinate
transformation, T-TICE, by using MLS H2O to calculate
the ice frost point, in order to remove height-related variations due to
changes in the H2O partial pressure
. As in we
quantify the duration of exposure of an air parcel to low temperatures by
defining the temperature threshold exposure (TTE) as the total integrated
time the air parcel is subject to synoptic-scale temperatures below the
chosen threshold. We use a threshold of TICE+4 K
(approximately TNAT-3.5 K) to demonstrate empirically the
correlation of TTE with the uptake of HNO3 by NAT PSCs. The
temperature history follows a diabatic back-trajectory for up to 15 days
obtained from the MLS LTD dataset . The TTE is the
total time (in days) that an air parcel has been exposed to temperatures
below TICE+4 K since the last time the temperature fell
below TNAT and remained below TNAT consistently;
i.e., any number of episodes of cooling below TICE+4 K are
accumulated provided that the air parcel has remained consistently below
TNAT. The HNO3 and H2O values (for estimating
TNAT and TICE) are assumed to be constant from
the start point of the back-trajectories. For typical lower stratospheric
polar conditions (5 ppmv H2O, 10 ppbv HNO3, and 46 hPa),
values for TICE and TNAT are 188 and 195 K,
respectively. Both TICE and TNAT are lowered
(raised) by about 2 K at 32 hPa (68 hPa). Under denitrified conditions
(5 ppbv HNO3), TNAT is lowered by about 1 K, and
under dehydrated conditions (3 ppmv H2O), TICE is
lowered by about 3 K. In denitrified and dehydrated conditions,
TNAT is also lowered by about 3 K. TTE is a remarkably good
indicator of the geographical extent of the HNO3 depletion in the
vortex . Here, we explore the correspondence of TTE
to NAT nucleation and growth processes.
According to the development of NAT along a sample trajectory shown by
in their Fig. 1, substantial nucleation begins only
for temperatures below TNAT-4 K. We investigate the
temperature–time domain of the nucleation process in Fig. ,
for both (a) early season unperturbed and (b) late season denitrified
atmospheres, and calculate the resulting NAT number densities using the
heterogeneous nucleation scheme given in . The figure
serves to illustrate the general properties of NAT cloud formation, but in
reality the temperature–time path is important for the modeling of specific
clouds. The nucleation rate is a strong function of temperature, and the
nucleated NAT shows an almost step-like transition over a narrow temperature
range. In contrast, the variation of NAT density with exposure time is more
gradual because the nucleation rate at a fixed temperature (i.e., fixed
supersaturation) depends only on the integration over time. Exposure to
temperatures of TNAT-2.2 K and above produces negligible NAT
densities (<10-6 cm-3), even for time durations exceeding a
month, whereas exposures of ∼ 1 day to temperatures near
TNAT-4 K produce NAT densities 3 orders of magnitude greater
(∼10-3 cm-3). At lower temperatures, the NAT saturation ratio
is limited by uptake of HNO3 from the gas phase by STS
, causing the curvature of the NAT density contours
below TNAT-4.5 K. Denitrification has little effect on the
sharp temperature transition, but at lower temperatures where STS forms there
is a visible decrease in the NAT number density generated for the same time
duration. At nucleation, the NAT particle sizes are small and no larger than
the progenitor aerosol particle (SBS or STS). Hence, considerable growth of
the NAT particles is required before they can be detected using remote
sensing techniques. TTE can be viewed as a proxy for the time elapsed since
nucleation occurred, i.e., as a measure of the effective growth time of the
NAT particles. The NAT volume density increases gradually through
sequestration of HNO3 from the ambient gas phase, and the particles
may not achieve their much larger equilibrium size until several days
following nucleation.
(a) Calculated NAT number densities (colored shading and
labeled contour lines) resulting from varying temperature exposure durations
in an unperturbed atmosphere with 15 ppbv total HNO3. Horizontal
dashed lines highlight exposures of between 1 min and 1 month. An air parcel
(containing the requisite background aerosol embedded with foreign nuclei)
exposed to a temperature of T-TNAT=-4 K for 1 day will
generate 0.0012 cm-3 of nucleated NAT particles. (b) As for
(a) except for a denitrified atmosphere with 5 ppbv total
HNO3.
(a) Polar stereographic projection of the MLS measurement
locations for all orbits over the Antarctic on 2009d146 (26 May 2009). Each
orbit is numbered sequentially. The square symbols denote the latitude and
longitude locations of the MLS vertical profiles. The size of the squares is
not representative of the along-track or across-track resolutions. The
HNO3 volume mixing ratio at 32 hPa is given by the color bar.
(c) The same data points are shown as a temporal raster plot. The
ordinate is the time of day in hours (UT) and the abscissa is the geodetic
along-track angle. The squares denote the time of day of the MLS measurement
and the measurement location with respect to the closest approach of the
orbit track to the South Pole. Each orbit is numbered along the right
ordinate. Also shown are the along-track distance, the latitude, and the
solar zenith angle. The size of the squares is not representative of the MLS
integration time or the along-track resolution. (b, d) As
for (a, c), except for 2009d156 (5 June 2009).
Visual representation of satellite orbital data
Figure a shows typical orbit tracks of the MLS
HNO3 distribution mapped onto a polar stereographic projection for
ascending and descending orbits at 32 hPa. Each colored square is centered
at the corresponding MLS profile latitude–longitude retrieval location. The
along-track spacing is 1.5∘ (distance between centers of the
squares). Note that the dimensions of the squares are not related to the MLS
along-track (several hundred kilometers for HNO3) or across-track
(about 10 km) resolutions. Orbit numbering (0 is the day of start orbit) is
shown around the 60∘ S latitude circle. The color scheme indicates
contrasting colors either side of 10 ppbv. Over the 10-day period (26 May to
5 June 2009, Fig. a and b), the HNO3 values
decrease and the area with values < 10 ppbv is seen to increase and move
eastward. Such “satellite data orbit plots” are commonly used, but they do
not scale up easily for viewing multiple quantities and pressure levels over
periods of the order of a month; e.g., tracking the evolution of four
parameters over 20 days at four distinct atmospheric levels requires the
digestion of 320 images.
We present an alternative scheme, designed to improve the data visualization,
with some similarities to the familiar Hovmöller diagram, but with the
abscissa following selected sections of the satellite orbit track rather than
running along a zonal or meridional circle. Figure c
shows the same data as in Fig. a, but replotted as a
time-ordered sequence of the along-track points. The MLS orbit tracks are
unfolded along the abscissa as a function of the along-track angle
(1.5∘ is the angular spacing), where the along-track angle of
30∘ corresponds to the closest approach of the orbit to the South
Pole (at about latitude 82∘ S). Also shown for convenience are the
along-track distances (in kilometers) and the corresponding latitudes and
solar zenith angles. The MLS measurement time (hours since start of day at
00:00 UT) is on the ordinate. The orbit numbers are given next to the
right-hand ordinate. Again, the dimensions of the squares are not related to
the MLS orbital track spacing or the MLS measurement time (each complete
vertical atmospheric profile is accumulated over about 25 s). The main
purpose of this compact visual representation (i.e., a sparse “raster”
image) is that it enables the “raw” daily observations to be stacked into a
longer time series without involving gridding onto a map projection. Note
that there is a geographical data void (within 8∘ of the pole; see
Fig. a and b) that is not apparent in the raster
representation. MLS looks forward in the along-track direction, so it never
actually looks into the 8∘ polar cap; nor does CALIOP with its nadir
view. While the low HNO3 in the vortex rotates eastward in the orbit
track plot, this motion translates into a time displacement in the raster
plot. The ascending/descending tracks do not intersect in the raster plot and
the terminator is always on the rightmost side (a feature that could be
potentially useful for examining diurnal species such as ClO).
Detection and classification of PSCs
Improvements in modeling capabilities drive a commensurate need for a
thorough evaluation of the observational aspects of PSC research, such as
biases in temperature analyses, derived air parcel temperature histories
along trajectories and instrument measurement biases and uncertainties. This
is highlighted in a specific example shown by in the
Arctic on 26 December 2009 (their Fig. 7, orbit 26_04), where they indicate
that the ZOMM model predicts a secondary area of NAT clouds between
longitudes 12 and 53∘, whereas the CALIOP observations do not show a
corresponding lidar detection. noted the prolonged
exposure time (80 h) resulting in sedimentation of NAT as a potential cause
of the lack of a coincident lidar signal from CALIOP in the L2PSCMask
product. However, we have determined that smoothing of the CALIOP L2PSCMask
data using a 5×5 median filter to improve signal-to-noise does in
fact indicate the presence of PSCs. In Fig. , we compare the
along-track cross sections of the MLS HNO3, CALIOP L2PSCMask, and the
smoothed total and perpendicular backscatter ratios. Additionally, inspection
of the MLS gas-phase HNO3 identifies a coincident decrease also
consistent with the location of the CALIOP PSCs (note that the ZOMM model
HNO3 is not shown by ).
Comparison of along-track data for the partial orbit shown by
(note that the x axis is reversed here from their
figure). (a) MLS HNO3 showing sequestration at 12 and
-27∘ longitude. (b) CALIOP PSC Mask does not show
detection of PSCs at 12∘ longitude. (c) Smoothed CALIOP
total backscatter ratio. (d) Smoothed CALIOP perpendicular
backscatter ratio. Solid thick white contours are the MLS HNO3
isolines for 7 and 12 ppbv HNO3. Solid thin white vertical lines are
the longitude markers shown by . The detection of PSCs
near 12∘ longitude is evident in the smoothed CALIOP perpendicular
backscatter ratio along with the corresponding HNO3 sequestration
measured by MLS in (a).
Modeled uptake of HNO3, lidar backscatter, and
infrared extinction in PSCs
We model the microphysics of representative STS and NAT particle
distributions according to the methodology given in
and . For the lidar scattering calculations, Mie
theory is used for liquid spherical particles and the T-matrix
for solid NAT particles. As we noted in
, the NAT particle shape is an open issue, and we
continue here to use a range of spheroidal shapes to illustrate the lidar
sensitivity to NAT. Real refractive indices at 532 nm were assumed to be
1.43 for STS and 1.50 for NAT, with zero imaginary refractive indices for
both particle types. For the mid-infrared region, complex refractive indices
were obtained from the tabulations given by for STS
and for NAT.
Existence temperatures of the PSC types are calculated using equilibrium
thermodynamics and are dependent on the ambient partial pressures of
H2O in the case of the ice frost point, TICE, and also HNO3 for TNAT and STS
. Errors in the calculations of these
reference temperatures arising from uncertainties in the MLS H2O and
HNO3 data are estimated to be ≤ 0.5 K for TICE
and ≤ 0.7 K for TNAT in the pressure range 70–20 hPa.
SBS particles grow by condensation on cooling, first by uptake of H2O
from the gas phase and, then, at sufficiently low temperatures, uptake of
HNO3 occurs, forming STS at a few kelvin below the NAT point close to
TSTS∼TNAT-3.5 K
. In the polar stratosphere, NAT
is thermodynamically stable at temperatures below
TNAT∼TICE+7 K, although the NAT
nucleation process is still not understood in detail.
Comparison of limb sounder and lidar sampling volumes.
The PSC detection limits for lidar backscatter and infrared extinction are
dependent on the background aerosol loading in addition to measurement noise.
Under conditions of high quiescent background aerosol loadings (e.g., at
times perturbed by volcanic aerosol), a higher threshold is required to
discriminate PSCs from the background. The thresholds also depend on vertical
and horizontal averaging both along-track and across-track. In the case of
MLS, the across-track averaging (i.e., the 240 GHz antenna beam width at the
tangent point) is around 8 km, the vertical field of view for HNO3
is a few kilometers and the along-track sampling is over several hundred
kilometers. We have investigated coarser averaging of the lidar data in the
along-track and vertical directions to achieve better signal-to-noise.
However, the across-track averaging of CALIOP is only about 0.09 km, and as
a result the sampling volumes of limb sounding instruments are 3 or more
orders of magnitude larger. The nominal sampling volumes that demonstrate the
much larger limb sounder sampling are shown in Table .
For illustration, here we use typical threshold levels appropriate for the
CALIOP Level-1b v3 lidar data gridded with a 50 km by 0.5 km resolution
: total backscatter ratio, RT=1.25 (STS
type threshold), and perpendicular backscatter, β⟂=2.5×10-6 km-1 sr-1 (MIX type threshold). For a mid-infrared limb
sounder operating in the window region near 12 µm at 46 hPa, we
use an extinction threshold, kext=5×10-5 km-1.
This value is based on measurements by the Improved Stratosphere and
Mesosphere Sounder poleward of 70∘ N taken
during late 1991, before the meridional transport of volcanic aerosol
impacted polar background levels. We also found a similar extinction
threshold by examining the characteristics of the polar aerosol extinction
measured by the High Resolution Dynamics Limb Sounder (HIRDLS)
during 2005–2007. For both ISAMS and HIRDLS the
distribution of the background aerosol extinction is modeled adequately by a
log-normal distribution, with the stated threshold being at least 3 standard
deviations higher than the mean of the extinction distribution. For the
Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument,
determined a cloud-index (CI) parameter with a
threshold for PSC detection of CI<4.5, and
indicated that this corresponds to a volume density
detection limit of 0.2–0.4 µm3 cm-3. Finally, the
threshold level for detection of the gas-phase removal resulting from the
ambient HNO3 uptake in STS is taken to be 1 ppbv, slightly higher
than the 0.6 ppbv MLS measurement uncertainty.
Equilibrium STS
Figure a shows the temperature variation of the
modeled equilibrium thermodynamic properties of STS based on the
parameterization and the calculated lidar
backscatter and 12 µm infrared extinction assuming Mie theory. The
calculations assume a pressure of 46 hPa, 5 ppmv H2O, and 12 ppbv
total HNO3. In situ observations of the STS aerosol volume are well
modeled , as is the uptake of HNO3 from the
gas phase . Uptake of HNO3 from the gas
phase varies rapidly (50, 10, 1 %) over a narrow temperature range (T-TICE=2.3, 3.1, 3.9 K), and the maximum temperature derivative
(-6.7 ppbv K-1) is at T-TICE=2.9 K. The
theoretical residual gas-phase HNO3, accounting for the uptake in
STS, is shown in Fig. b as a function of the
total backscatter and 12 µm infrared extinction. In a scatter plot,
the observations of HNO3 and backscatter (or extinction) in the
presence of STS are expected to lie beneath the theoretical curve, and this
is investigated in Sect. .
Figure c shows that the infrared extinction is
marginally more sensitive to STS than the lidar backscatter, since the
corresponding threshold equivalent condensed HNO3 contents of STS are
0.65 and 0.84 ppbv for the two measurement approaches, respectively.
(a) Temperature variation relative to the frost point of
the uptake of HNO3 in STS (red), the calculated 532 nm lidar total
backscatter ratio, RT, (blue), and the 12 µm infrared
extinction (orange). (b) Gas-phase HNO3 vs. 532 nm total
backscatter ratio (blue) and 12 µm infrared extinction (orange).
(c) STS detection limits for lidar backscatter ratio (blue diamond)
and infrared limb extinction (orange diamond) and correspondence to the
uptake of HNO3 in STS.
STS/NAT mixtures
The morphology of NAT particles is still an open question, as is the
compactness of the particles . Light scattering studies have repeatedly shown that
detailed particle morphology cannot be deduced from the depolarization; e.g.,
investigated simple and complex shapes with size
parameters (ratio of the particle circumference to the wavelength) in the
range 2–12 and real refractive indices in the range 1.55–1.603
representative of silicate particles, and noted similar depolarization ranges
for the fifteen different shapes (regular and irregular) that were
analyzed. Therefore, by analogy, the
selection of a few aspect ratios for a simple spheroidal shape is sufficient
to demonstrate the variations in lidar backscatter properties and to
highlight the challenges for lidar measurements to detect low number density
large particle radii NAT. The NAT particles are modeled as spheroids with
diameter-to-lengths (aspect ratios), ϵ, both oblate (1.2) and
prolate (0.8, 0.9, 0.95) using T-matrix calculations assuming a power-law NAT
size distribution; otherwise, the STS/NAT mixtures are modeled as in
and . Previous
investigations have noted that larger depolarizations (over 60 %)
result from the more nearly spherical particles in the aspect ratio range
ϵ=0.90–1.10. Recent analyses of the CALIOP data
have used ϵ=0.90 for NAT to
improve modeling of the observed CALIOP depolarization range. Note that
although the total backscatter is often dominated by STS, the use of a
perpendicular backscatter threshold , rather than an aerosol depolarization threshold, reduces
the possibility of the STS signal to mask the NAT signal in STS/NAT mixtures
.
(a) Temperature variation relative to the frost point of
the uptake of HNO3 in an STS/NAT mixture (red) for a NAT number
density of 0.001 cm-3 and an effective radius of 6.5 µm, the calculated
lidar backscatter ratio for four different particle shape aspect
ratios (purple–blue), and the 12 µm infrared extinction (orange).
(b) Condensed HNO3 in NAT (red line)
at T-TICE=5 K as a function of NAT number density.
(c) NAT detection limits for lidar total backscatter
ratio (blue–purple diamonds) and infrared limb
extinction (orange diamond) and correspondence to
the NAT number density. (d) As (c), except for the lidar
perpendicular backscatter coefficient only.
The large particle example shown in
Fig. a is for a NAT particle
distribution with a number density NNAT=0.001 cm-3 and
effective radius Reff=6.5µm. Note that in this
example the uptake of HNO3 follows the NAT equilibrium curve until
the saturation point is reached and the condensed HNO3 equals the
volume in the assumed NAT particle distribution (plateau region with 4 ppbv
condensed HNO3). No further uptake of HNO3 occurs until the
temperature decreases sufficiently to allow growth of STS. This example is a
crude, but not unrealistic, snapshot of a possible STS/NAT mixture at a
particular time because the growth of NAT is kinetically limited
. A high number density of NAT nuclei would ultimately
lead to a NAT distribution with smaller particle sizes than a low number
density since the available HNO3 is spread over a large number of
particles . Once nucleated, a NAT particle will
continue to grow, provided there is sufficient HNO3 and H2O
available and T<TNAT such that the HNO3 vapor
pressure over NAT is supersaturated, until it attains its equilibrium size
(reaching a radius of tens of microns). Gravitational sedimentation may cause
the NAT particles to descend into a region of lower HNO3 and/or
rising temperature, causing evaporation rather than growth. The
Wegener–Bergeron–Findeisen process will cause sequestration of HNO3
by NAT in a mixed-phase STS/NAT cloud at the expense of the HNO3 in
the liquid STS . However, if the STS forms quickly by
rapid cooling, then the uptake of ambient HNO3 can be predominantly
into STS rather than into NAT. Growth of NAT is therefore retarded at these
low temperatures of a few K above the frost point .
The lidar detection of NAT (backscattering in the visible spectrum) is
sensitive to the asphericity parameter, whereas the infrared extinction
(dependent mainly on emission and therefore particle volume) is not. Hence,
there are four lidar total backscatter curves corresponding to each aspect
ratio in Fig. a, but only a single
infrared extinction curve is plotted that is representative of all four.
Likewise, the inferred uptake of HNO3 by STS/NAT as measured by
microwave observations is also insensitive to particle shape (in addition,
the aerosol emission is negligible in the microwave region and has no effect
on the gas measurements). In the absence of an actual PSC detection, the
observed reduction in gas-phase HNO3 is an indirect detection method
of PSC activity , since either the HNO3 is
condensed into NAT PSCs below the detection threshold of the lidar or the NAT
particles were so large that they sedimented and the missing gas-phase
HNO3 is the result of permanent denitrification.
The theoretical condensed HNO3 in NAT at a fixed temperature of T-TICE=5 K is shown in
Fig. b as a function of the NAT number
density. At this temperature, the STS contribution to the backscatter,
infrared extinction, and HNO3 uptake is negligible (see
Fig. ) and we may safely concentrate on the
properties of the NAT particles alone. The temperature is about 2.5 K below
the NAT existence temperature and about 2 K above the temperature at which
substantial uptake of HNO3 into STS occurs. The red diamond symbol
marks the detection threshold for 1 ppbv of HNO3 condensed in NAT
(or equivalently a 1 ppbv uptake of HNO3 from the gas phase) and
corresponds to a NAT number density of 2.45×10-4 cm-3. In
Fig. c we show the total lidar
backscatter and infrared extinction as a function of the NAT number density.
The total backscatter detection threshold (1.25) for the four particle aspect
ratios corresponds to NAT number densities ranging from 4.9 to 8.4×10-4 cm-3 compared to 1.4×10-4 cm-3 for the
infrared extinction threshold (kext=5×10-5 km-1).
For this large particle radius example, uptake of HNO3 and infrared
detections are more sensitive than the lidar total backscatter. The
perpendicular backscatter coefficient
(Fig. d) is more sensitive than the
total backscatter to the presence of non-spherical NAT, resulting in the
detection of lower number densities ranging from 1.2 to 3.6×10-4 cm-3, except for the 0.8 aspect ratio, which shows less
sensitivity. Hence, operation of a lidar with an orthogonal polarization
channel can substantially improve the detection threshold for non-spherical
NAT for some aspect ratios. The infrared detection is shown to be more
sensitive for the large particle range, except for an aspect ratio of 0.95
for which the sensitivities are comparable.
Intercomparison of the sensitivity of various PSC detection
techniques to a range of NAT number densities and effective radii at a
temperature of T-TICE=5 K, for an ambient pressure of 46 hPa,
5 ppmv H2O, and 12 ppbv total HNO3. The purple–blue lines
indicate the limits of detection for lidar with total backscatter (solid) and
orthogonal channel (dashed) for a range of aspect ratios (EPS). The red
(green) line indicates the sensitivity of an in situ sampling instrument to
1 ppb of condensed HNO3 in NAT (aerosol density,
0.2 µm3 cm-3) or the equivalent uptake from the gas phase
(e.g., by a microwave limb sounder). Yellow/orange lines indicate the
sensitivities in the mid-infrared for a limb sounder at two wavelengths. NAT
PSCs with particle distribution characteristics lying within the gray shaded
region are undetectable by any of the above techniques, with the assumed
horizontal and vertical averaging scales given in the text.
Intercomparisons of PSC detection techniques
The sensitivity of different techniques employed to detect PSCs over a wide
range of number densities and effective radii is illustrated with
Fig. . Selected detection limits for CALIOP
lidar, infrared limb emission, and inferred detection by the measured uptake
of HNO3 from the gas phase or the in situ aerosol detection of
condensed HNO3 in NAT are shown. Again, the calculations are for a
temperature T-TICE=5 K, since the purpose of the
comparison is to show the potentially large variation in lidar backscatter
response to NAT PSCs of differing asphericities. The lines in
Fig. mark the detection limits for the
various techniques and indicate the lowest NAT number density
(NNAT) that can be detected for a given NAT effective radius
(Reff); i.e., any combination of (NNAT,Reff) lying below a given line is below the detection limit for
that particular technique. The gray shading indicates the region that is
below the detection threshold for any of the techniques assuming the given
variation in NAT aspect ratio. The solid (dashed) purple–blue lines
correspond to the detection thresholds for total backscatter (perpendicular
backscatter) for different aspect ratios. As expected from the previous
section, the perpendicular backscatter is in general more sensitive to the
presence of low number density NAT than is the total backscatter ratio.
However, there is substantial variation in the sensitivity to the particle
aspect ratio, ϵ. The sensitivity curves for infrared extinction
(yellow) and lidar perpendicular backscatter are similar for the
ϵ=0.95 case for Reff≥4, whereas for ϵ=0.8
the lidar is much less sensitive. For low number density/large particle NAT
(bottom right of Fig. ), the uptake of
HNO3 from the gas phase (red) can still be quite substantial
(1 ppbv) and is independent of the particle asphericity. The extremes of the
lidar sensitivity to small NAT (Reff<1µm) (ranging
over an order of magnitude in particle number density) are seen to be
reversed for large NAT (Reff>5µm); i.e., the lidar
technique is more sensitive to small NAT with an aspect ratio of 0.80 than
0.95 and vice versa for large NAT. Except for the aspect ratio of 0.95, the
detection limits for infrared emission and the uptake of 1 ppbv HNO3
from the gas phase become more sensitive than the lidar limit for large NAT
with Reff>2.5 and Reff>5µm,
respectively. The near coincidence of the green dashed line and red solid
line shows that a NAT volume density of 0.2 µm3 cm-3
(limit of detection for MIPAS given by ) is
approximately equivalent to 1 ppbv of condensed HNO3. This threshold
is consistent with a previous study by that showed that
large particle, small number density NAT can be detected by MIPAS. The
specific case studied was for a particle distribution with a 7 µm
mode radius and number density 2.9×10-4 cm-3, which we
estimate to be equivalent to a 12 µm extinction of 1.9×10-4 km-1 (practically independent of the particle aspect ratio in
the infrared region).
CALIOP PSC type classifications and their corresponding 2-D
cross-section pairs derived from the 3-D coordinate space of temperature
T-TICE, HNO3, and total backscatter, RT, for
10 May to 25 October 2009. The six columns are the CALIOP PSC types
identified in the text. Blue (green) lines are theoretical calculations for
total HNO3 from 2 to 24 ppbv in 2 ppbv steps for STS (NAT)
equilibrium. Red–black dashed lines are theoretical calculations for
equilibrium NAT with number densities 0.001 cm-3 (bottom curve) and
0.01 cm-3 (top curve) and 14 ppbv total HNO3. The lower limit
of detection, given by the black–white dashed line, is described in the
text.
Separation of PSC types using backscatter, HNO3, and temperature
In this section we investigate the lidar PSC classification by exploring the
2-D cross sections resulting from projections of the 3-D coordinate space of
temperature, HNO3, and total backscatter. Here we use the CALIOP
Level-1b v3 data with coincident MLS data processed as detailed in
for the period 10 May to 25 October 2009 in the
Antarctic at 46–21 hPa. In Fig. we show
probability density functions (PDFs) classified according to the CALIOP PSC
scheme , with modifications discussed in
and , in six columns
(ALL, LIQ, MIX1, MIX2, ICE, and None) and four rows
(described below). The ALL class is the sum of the individually
classified PSC components LIQ, MIX1, MIX2, and ICE. The
None class represents all cases below the CALIOP detection
threshold. The four rows for each column show the depolarization vs.
normalized backscatter and the corresponding PDFs for the three possible
combinations of pairings from the temperature, HNO3, and total
backscatter coordinates in the PSC classification. Nitric acid vs.
temperature has been shown previously by and
(and is included for completeness), but backscatter
vs. temperature and HNO3 vs. backscatter are shown for the first time
here.
Row 1: depolarization (δ) vs. normalized backscatter
(1-1/RT)
CALIOP data analysis, detection, and classification are discussed in
and . The PSC classes are
shown in the CALIOP depolarization vs. backscatter classification diagram in
the first row. Black solid lines indicate the main PSC types. Class
boundaries for MIX2-enh and wave ice (RT>50) are shown
as black dashed lines, but are not differentiated here from the MIX2
and ICE main classes. The classification boundaries were originally
chosen to distinguish STS (depolarization less than
3 %), STS/NAT mixtures (significant depolarization indicating a solid
component), and ice. Note that the LIQ/MIX1 class boundary is fuzzy,
and depolarization values (the ratio of the perpendicular to parallel
backscatter) can exceed 3 % for LIQ because of measurement noise
even though the perpendicular backscatter component indicates below-threshold
response. Similarly, the None class boundary is fuzzy because of
measurement noise. The black–white dashed line shows the theoretical lower
limit of detection as a locus of points (δ, 1-1/RT) for
the chosen perpendicular backscatter threshold, β⟂=2.5×10-6 km-1 sr-1, calculated for a typical polar atmosphere
from the expression
RT(δ)=1+1δ(β⟂-βm⟂)+βmT1βmT,
where the molecular depolarization δm is 0.0036, the molecular
perpendicular backscatter component βm⟂ is βmTδm1+δm, the
total Rayleigh scattering (both polarizations) is βmT,
and the fractional depolarization range is δ=0…1. This low
detection limit is not strictly attained in practice because of additional
spatial coherence constraints that are imposed to reduce false positives to
less than 0.1 % . The coherence constraint
results in the distribution of points in the None class appearing to
the right side of the black–white dashed line. All the other imposed class
boundaries are sharp, although this does not imply that the distinction
between these PSC types is definitive. For example, as noted in
, the ICE “arm” close to the LIQ
class (normalized backscatter 0.7–0.85) is intersected by the
MIX2/ICE boundary. Better separation between the MIX2 and
ICE classes based on allowing for the seasonal variation in the
location of the ice “arm” associated with denitrification was discussed in
. Overall, the classification using the 2-D regions of
the depolarization vs. normalized backscatter provides very good
discrimination between STS and solid-particle PSCs.
Row 2: Gas-phase HNO3 vs. T-TICE
In and , we demonstrated
that the uptake of HNO3 vs. temperature, classified according to
CALIOP PSC types, is in good agreement with expected temperature existence
regimes for STS, NAT, and ice, except for an apparent ∼ 1 K bias with
respect to the GEOS-5 temperatures. This is consistent with comparisons (not
shown) of coincident independent temperatures obtained from the Constellation
Observing System for Meteorology, Ionosphere, and Climate (COSMIC) GPS Radio
Occultation data, which indicate a cold bias in GEOS-5 of up to 0.7 K in the
2009 Antarctic lower stratosphere. The LIQ class follows the
theoretical equilibrium uptake of HNO3 by STS (blue lines from 2 to
24 ppbv in 2 ppbv steps), and the MIX1 and MIX2 classes
show significant non-equilibrium behavior,
along with two discernible branches following the STS and the NAT (green
line) equilibrium curves. The ICE class is a compact and roughly
symmetric distribution, located at the lowest temperatures and lowest
HNO3 gas-phase amounts. The leading edge of the HNO3
gas-phase distribution for the None class follows the STS uptake
curve. Also visible is a separate highly denitrified branch
(HNO3< 5 ppbv) extending to beyond 10 K above the ice frost
point.
Row 3: total backscatter (RT) vs. T-TICE
This row shows the temperature domains corresponding to the various CALIOP
PSC classes (the region of highest backscatter, RT>10, is not
shown). The blue lines indicate the theoretical STS backscatter vs. T-TICE for gas-phase HNO3 increasing from 2 to 24 ppbv in
2 ppbv steps. Note that the current depolarization/backscatter
classification scheme does not use temperature as a discriminant. Backscatter
vs. temperature is only used in the CALIOP classification scheme to determine
daily detection thresholds . The LIQ class
shows a rapid increase in total backscatter near T-TICE=3.5 K (i.e., TSTS is located at the point the blue curves
join the abscissa). There is a thin tail which does not reach out as far as
TNAT (located at the intersection of the two red–black dashed
curves). The envelope of the theoretical STS curves (bounded by total
HNO3 values of 16–18 pbbv) is a reasonable description of the
distribution, but at the lowest temperatures and highest expected backscatter
(> 6) the region is unpopulated. This may be because such conditions are
favorable for freezing of STS to form ice . The
MIX1 class shows a tail with very low backscatter extending from
TSTS out to beyond TNAT and is consistent with
NNAT≤0.001 cm-3. At temperatures below
TSTS the backscatter increases, but remains below values of
about 3, and the distribution is consistent with NNAT≤0.01 cm-3. The MIX2 class also shows a tail beyond
TNAT and is consistent with the largest NNAT
ranging up to slightly above 0.01 cm-3, except at the lowest
temperatures below T-TICE=1 K, where the backscatter
increases rapidly. The demarcation between the MIX2 and ICE
classes at RT=5 is somewhat arbitrary and leads to NAT/ice
misclassification in this transition region. This effect is ameliorated by
the use of a successive averaging scheme , since ice
can generally be detected at a higher spatial resolution than is shown here.
At the highest backscatter values there is an apparent trend in the
ICE class towards higher minimum temperatures. The None
class shows a narrow distribution consistent with the chosen total
backscatter threshold of 1.25.
Row 4: Gas-phase HNO3 vs. total backscatter
(RT)
The blue lines indicate the theoretical STS HNO3 vs. backscatter
curves. These show an almost linear decrease in HNO3 with increasing
backscatter. For the LIQ class the regions RT<2 with high
HNO3 and RT>6 with low HNO3 are not fully
populated when compared to the theoretical curves. For low backscatter this
is likely to indicate STS containing less than 0.8 ppbv of HNO3,
which cannot be detected. For high backscatter this may suggest the result of
freezing of STS to ice (see Row 3 discussion). The LIQ class also
shows a bulge in the PDF around RT=4 to 6 that reaches the
theoretical curve for total HNO3= 22 ppbv. Since the
None class indicates that the maximum HNO3 is 18.5 ppbv,
the ∼ 3.5 ppbv excess HNO3 in the LIQ PDF may have
arisen from the formation of additional HNO3 produced from
heterogeneous reactions occurring on the liquid particles and released into
the gas phase or by renitrification from evaporation of sedimenting NAT
clouds (see Sect. ). The None class also
indicates totally denitrified regions (consistent with the noise floor of the
MLS measurements) with insufficient HNO3 to form any kind of non-ice
PSCs. Note that the data in this row are independent of the suspected GEOS-5
temperature bias.
Evaluation of CALIOP and MLS co-located measurements
Although simultaneous co-located measurements of PSCs and gas constituents
are obviously to be preferred over spatially and temporally decorrelated
measurements, the availability of such measurements from MLS and CALIOP
cannot be expected to provide full closure to the questions of PSC formation.
Careful consideration of the details of PSC formation is required to
reconcile the pieces of information garnered from the different measurement
techniques. In this regard the ultimate aim would seem to be Lagrangian
measurements following the full life-cycle of PSC evolution. However, further
unresolved issues have emerged from the long-duration stratospheric balloon
flights by , who describe measurements of the NAT
nucleation rate that show much larger spatial inhomogeneities in NAT
occurrence than anticipated.
Co-located MLS and CALIOP orbit transects for
selected orbits showing in six rows: (a) MLS HNO3. (b) Ambient temperature,
T-TICE. (c) Temperature threshold exposure, TTE (days).
(d) Fifteen-day reverse trajectory temperature history,
T-TICE,
ending at the 31 hPa pressure level. Minimum temperature encountered along the trajectory
is inset at the top left.
(e) CALIOP L2PSCMask
PSC classification. (f)LS_index. MLS pressure
levels are shown as labeled black or white contours. Blue
(green) contours indicate TICE+2 K (TNAT). Red
contours indicate TTE values ≥3 days. The MLS 12 ppbv
HNO3 contours are indicated in yellow. Gray shading in (e, f) indicates that
the CALIOP observations are in daylight.
MLS and CALIOP orbit transects
We have selected some views from the combined MLS and CALIOP data record to
illustrate how the interpretation of the morphology of PSCs and gas-phase
HNO3 in along-track transects is governed not only by the local
ambient temperature, but also by the underlying temperature histories. Here
we use the CALIOP Level-2 v1 PSC Mask dataset and also apply post-processing
to generate coarser horizontal/vertical bins for a better comparison at the
scale of the MLS along-track and vertical resolution. Each averaging bin is
the size of the MLS along-track separation (165 km) and the height between
the mid-points of the pressure levels (2.1 km) for the MLS HNO3 data
product. Note that in this section we use the L2PSCMask data class name
STS instead of LIQ.
In Fig. we present along-track orbit transects in
the 2009 Antarctic early winter. The four columns show a sample of orbit
tracks over an 11-day period (day number/orbit number): 2009d136/11,
2009d145/6, 2009d145/13, 2009d147/9. The data in each row are (a) MLS
HNO3, (b) T-TICE, (c) temperature history (TTE),
(d) temperatures following the Lagrangian back-trajectories, (e) L2PSCMask
CALIOP PSC classification, and (f) the post-processed
Liquid/Solid index, LS_index=(L-S)/(L+S),
where L is the number of observations in the STS classification
and S is any other PSC (solid) detection. The LS_index is the
ratio of the number of CALIOP classifications occurring within the
corresponding MLS along-track extent, with the extreme values of -1
indicating only solid class and +1 only liquid class detections. The
LS_index represents the dominant PSC classification in a sample
volume similar in size to the MLS gas species resolution. The pixel size is
much larger than that in the L2PSCMask composition plot, and the composition
speckle can be seen as “blocky” regions in the LS_index.
Several contour lines are superposed on the orbit transects: the black–white
quasi-horizontal labeled contours show a sample of the MLS pressure levels
(HNO3 is retrieved at a six-level/decade change in pressure). The
green and blue contours represent temperatures corresponding to the
TNAT threshold (using GEOS-5 and MLS HNO3, H2O)
and TICE+2 K, respectively. The blue temperature contour
encompasses an expected HNO3 uptake of about 50 % from the gas
phase into STS (see Fig. a). The yellow contour
is the HNO3 12 ppbv contour, and the red contour encloses the area
with TTE ≥ 3 days.
Case 1: 16 May 2009/2009d136/11: MLS HNO3 shows an extent of
a few hundred kilometers with HNO3 uptake from the gas phase, which
is offset from the region of the lowest local temperatures
(Fig. b), but more closely located with peak values
of TTE (Fig. c) (which are still below 3 days).
CALIOP detects some pixels of MIX1 and fewer of MIX2
(Fig. e). Another orbit track (9, not shown) on the
same day shows smaller HNO3 uptake with no coincident PSC detections.
Case 2: 25 May 2009/2009d145/6: MLS HNO3 shows a substantial
region of HNO3 uptake over 1500 km and suggests a combination of
uptake in two separate regions, one located centrally within the local
temperature minimum (blue contour, TICE+2 K) and another
offset extending to the right edge of the TNAT contour (green).
The temperature history (red contour) is the key to this rather apparent
asymmetry of the HNO3 distribution with respect to the
TNAT contour, since the TTE clearly has larger values outside
of the central local temperature minimum and is associated with the region of
HNO3 uptake on the right. The L2PSCMask
(Fig. e) shows a substantial STS cloud with
some composition speckle, mainly coincident with the central local
temperature minimum. The LS_index (Fig. f)
shows predominantly liquid detections, with more solid detections at the top
and lower-right edge of the cloud. The STS class
(Fig. e) does not completely fill the local
temperature contour on the right-hand side, which overlaps with the largest
TTE values (red contour).
Case 3: 25 May 2009/2009d145/13: MLS HNO3 shows significant
uptake coincident with the peak temperature exposure history. The L2PSCMask
(Fig. e) shows some MIX1/MIX2 class, but is
not coincident with the largest HNO3 uptake. A very small area of
local temperature minimum (blue contour), near the along-track distance
coordinate at -1000 km and on the 32 hPa level, shows little HNO3
uptake and some STS class pixels.
Case 4: 27 May 2009/2009d147/9: MLS HNO3 indicates
substantial HNO3 uptake (Fig. a) coincident
with the local temperature minimum (blue contour), but also extending to the
left edge of the TNAT region (green contour). The greatest
exposure to low temperatures (red contour) is associated with the left region
of HNO3 uptake. The L2PSCMask (Fig. e) shows
a substantial STS class (with multi-class speckle), but only in the
right half of the minimum local temperature region. The left half is the area
with the largest TTE values (red contour). The L2PSC_Mask shows
MIX1/MIX2 class pixels below and to the left of the large
STS cloud and also in the regions outside of the TTE and
TNAT contours. We also note that although the minimum
temperatures along a number of the back trajectories passed below the frost
point within 2 days of the MLS/CALIOP observations, no ice PSCs were
detected.
Comparison of along-track data for a partial orbit on 27 May 2009:
(a) MLS HNO3 showing sequestration and the central region of
total denitrification. (b) CALIOP PSC Mask does not show a
corresponding large-scale detection of MIX1 clouds.
(c) Smoothed CALIOP total backscatter ratio.
(d) Smoothed CALIOP perpendicular backscatter ratio.
Solid thick white contours are the MLS HNO3 isolines
for 7 and 12 ppbv HNO3. Red contours indicate TTE values ≥3 days.
The detection of solid particle PSCs is evident in the smoothed
CALIOP perpendicular backscatter ratio and extends below the TTE contour by 2–4 km.
Examination of the overlaps between the high TTE values (red contour) and
local temperature minima (blue contour) in the cases discussed above reveals
a correspondence to HNO3 uptake but a frequent lack of coincident PSC
detections. The local temperatures are just as low (and sufficient for STS
formation) as in the areas outside the overlaps, but the STS class
is not seen at all, whereas the TTE increases substantially. The
corresponding detailed time histories of the temperatures at 32 hPa are
shown in Fig. d and reveal that the remarkable
asymmetries in the along-track location of HNO3 uptake with respect
to the local temperature minimum distribution can be understood in terms of
the different rates of cooling of particular air parcels. This indicates that
in the regions where slow cooling forms NAT first (marked by long white
arrows in cases 2 and 4), HNO3 is sequestered into NAT, and therefore
STS cannot grow. In contrast, there are regions where fast cooling occurs and
STS forms without prior NAT formation (marked by short white arrows in
cases 2 and 4). The NAT exists as large particle/low number density clouds
(sedimenting, sub-visible MIX1) that contain enough condensed
HNO3 to be detectable through MLS gas-phase depletion, but have low
lidar backscatter and are invisible to CALIOP. Alternatively, it could be
argued that the NAT particles grew so large further upstream that they were
effectively removed to lower altitudes through sedimentation at the time of
the orbit crossing observations, leaving behind a permanently denitrified air
mass detected by MLS but without coincident CALIOP PSC detections. However,
further averaging of CALIOP backscatter (as discussed in
Sect. ) on 27 May, shown in Fig. , does
indicate a considerably larger area of solid particle detections
(MIX1 class), associated with the high TTE region, and so it appears
that we are dealing with the limit of the L2PSCMask detection range.
Sedimentation of large NAT is suggested by the 2–4 km region of solid
particle detections lying below the high TTE region.
Denitrification and renitrification
The Antarctic gas-phase HNO3 distribution shown in
Fig. provides a record of the effects of the formation and
dissipation of PSCs and is displayed as the daily areal coverage for
equivalent latitudes less than 60∘ S, for isentropic levels from 340
to 500 K. The white solid lines indicate low, median, and high values of the
HNO3 probability density function. The minimum HNO3 mixing
ratios (i.e., the colored region below the 10th percentile white line)
indicate that PSCs can lead to a complete removal of the available ambient
HNO3 from the gas phase. As shown in , the
spread of HNO3 mixing ratios in totally denitrified regions is
compatible with the MLS precision. The temperature decrease starts from the
upper levels of the vortex and descends over time, resulting in PSCs and
HNO3 uptake developing later at the lower levels. The maximum
HNO3 mixing ratios (i.e., the colored region above the 90th
percentile white line) indicate episodes of renitrification at the lower
levels arising from the sedimentation of PSCs. As the NAT particles fall
through lower levels, they may pass into regions where they are less
thermodynamically stable. In these cases the evaporative release of
HNO3 from the condensed phase increases the gas-phase values, and
this is detected as a rise in the HNO3 measured by MLS at the lower
levels. The process is seen quite clearly in the increasing time lag between
the appearance of anomalously large HNO3 values above the 90th
percentile at 420 K (mid-May) compared to 340 K (mid-June). This process
acts to raise the NAT temperature existence threshold at the lower levels
because of the enhanced gas-phase HNO3 and therefore increases the
likelihood of occurrence of NAT. Heterogeneous chemical reactions on the PSC
particles involving ClONO2 and N2O5 produce additional
HNO3, which remains in the condensed phase until the PSC dissipates
. Therefore, an increase in gas-phase HNO3 at
a given level may arise from the evaporation either of sedimenting PSCs from
above or from extant PSCs that release the excess HNO3 formed as a
product of heterogeneous reactions. As the Antarctic winter progresses and
the temperatures at the lower levels decrease, the redistributed HNO3
is itself subject to further uptake into STS/NAT, resulting in potential
further denitrification and consequent removal of HNO3 from a larger
vertical range of the lower stratosphere.
Time series of the distribution of MLS HNO3 in the
Antarctic from May to October 2009,
for equivalent latitudes less than 60∘ S, and for isentropic
levels from 340 to 500 K. Major tick marks indicate the beginning of the month.
The color scale indicates the areal
coverage. White solid lines indicate the 10th,
20th, 50th (i.e., median), 80th, and 90th percentiles of the
HNO3 probability density function.
Twenty-day time series of Antarctic raster plots at 68, 46, 32, and
21 hPa in 2009 from day number 132 (12 May) to 151 (31 May). Gray shading
indicates no observations; olive-green shading indicates observations but no
detections.
(a) MLS HNO3. Numbers on the right axis indicate the
median HNO3 for the region where TTE > 2 days (in ppbv) for each day at 32 hPa.
(b) Temperature history. A set of three numbers on the right axis for each day at
32 hPa indicates in ascending order (i) maximum TTE in days, (ii) minimum local temperature,
T-TICE in K, (iii) minimum temperature encountered along the
back-trajectory, and T-TICE in K.
(c) CALIOP LS_index.
(d) CALIOP PSC fraction. Numbers on the right axis indicate the
maximum PSC fraction (ratio of the number of PSC detections to the number of
observations) for each day at 32 hPa.
Time series of PSC formation and Lagrangian temperature history
In this section we examine the formation of PSCs and the Lagrangian
temperature history during the early 2009 Antarctic PSC season.
Figure shows a time series of data taken over the
20 days from 2009d132 to 2009d151 (12–31 May) of HNO3, TTE
(temperature history), LS_index, and PSC fraction. Averaging bins
are as described in Sect. . There are four columns in
each panel corresponding to four pressure levels at 68, 46, 32, and 21 hPa.
Each “mini-plot” (e.g., identified by HNO3 2009d132 68 hPa) is a
raster image with the axes shown in Fig. (the reduction
in plot size merges together the square pixels; there is no longer any
visible white space between the measurement locations). The first column
(68 hPa) for HNO3 consists of 20 such images, one for each day
stacked one above the other. The second column is plotted adjacent and
corresponds to HNO3 at 46 hPa and so on for the third (32 hPa) and
fourth (21 hPa) columns. TTE is the Lagrangian temperature threshold
exposure as discussed in connection with Fig. . The
LS_index is as described before for each averaging bin (gray
shading indicates no data, e.g., instrument off or daytime CALIOP
observations; olive-green shading indicates operations but no detections).
PSC fraction is the ratio of the number of PSC detections to the total number
of observations in each averaging bin.
Significant TTE first appears on the 32 hPa level close to the South Pole on
2009d134/2009d135 (14–15 May), gradually increases in area, and expands in
vertical extent rapidly to the 46 hPa level and eventually to the 68 and
21 hPa levels with a delay of about a week. Note the lack of corresponding
areal coverage of PSCs, especially on the 32 hPa level (only a few PSC
detections are scattered about; see the PSC fraction panel). The PSC
LS_index indicates some predominantly solid class PSC detections at
68 and 46 hPa before 2009d141 (21 May), but there are fewer detections at
32 hPa. However, MLS indicates HNO3 uptake on the 32 hPa level
starting earlier from 2009d135 (15 May) that is as widespread as that on the
46 hPa level and similar in areal extent to the TTE. At 68 hPa there is
evidence for an increase in HNO3 following 2009d139 (19 May),
presumably due to renitrification from evaporating NAT PSCs that have
sedimented from a higher level. The combined data at 32 hPa indicate that,
in the early period, the CALIOP L2PSCMask is not detecting PSCs, since there
is a persistent area of daily HNO3 depletion that is not matched by
corresponding PSC detections but is consistent with the temperature history.
We use the term sub-visible PSCs to refer to these cases (i.e., significant
depletion of gas-phase HNO3, but without detection by CALIOP).
MLS HNO3 on the 32 hPa pressure level over the 10-day
period from 15 to 24 May 2009 (days 135–144) in
the Antarctic polar vortex. Data are selected only if there
are no coincident PSC detections by CALIOP.
(a) Scatter plot of
individual HNO3 values vs. TTE. The colored dots
indicate the measurement day number (given in the inset
color bar). The two colored curves are from a calculation
of the gas-phase HNO3, assuming growth of NAT at a
constant temperature of TICE+4 K
for NAT number densities and initial total HNO3 values of 5×10-5 cm-3
and 18 ppbv, respectively, for the upper curve and 5×10-4 cm-3
and 14 ppbv for the lower curve. The top color
bar indicates the NAT radius. (b) As in (a) except plotted
as a 2-D histogram of the density of points, with the inset color bar giving the
number of samples per bin. Only bins accumulating two or more data
points are shown.
Thirty-day time series of Antarctic raster plots at 32 hPa for
2006–2015. Diamond symbols indicate the last day before the start of
detectable HNO3 depletion. Gray shading indicates no observations;
olive-green shading indicates observations but no detections. Day number is
shown on the vertical axis. (a) MLS gas-phase HNO3.
(b) CALIOP LS_index.
We examine the variation of MLS HNO3 with TTE for sub-visible PSCs in
the period 2009d135–2009d144 (15–24 May) in more detail in
Fig. . The scatter plot of the gas-phase
HNO3 values shows a range of ∼ 4 ppbv (from ∼ 14 to
∼ 18 ppbv) for low TTE, and as TTE increases beyond ∼ 1 day, the
HNO3 decreases. A highly simplified microphysical model has been used
to calculate the uptake of HNO3 from the gas phase. Growth of NAT by
vapor deposition has been calculated in the manner outlined by
and following the simplifications introduced by
. Here, we ignore sedimentation and calculate the
growth of monodisperse NAT in a constant temperature atmosphere
(TICE+4 K) for two different initial NAT densities (5×10-4 and 5×10-5 cm-3) and two initial total
HNO3 values that encompass the observed range (14 and 18 ppbv). The
NAT growth model is initialized with a 0.1 µm radius at the
nucleation time (TTE = 0), and the subsequent time evolution of the
gas-phase HNO3 is plotted as colored curves indicating the NAT
particle radius. These two curves practically bound the MLS observations of
the distribution of gas-phase HNO3 as a function of TTE. As is well
known, low NAT number densities produce large NAT particles
, which take several days to reach thermodynamic
equilibrium (the uptake curves bottom out after 15 days or more). Backscatter
calculations for NAT with characteristics of the upper curve (assuming
ϵ=0.9) show that the backscatter (perpendicular or total) is below
the CALIOP threshold of detection along the entire time evolution. For the
lower curve, the higher NAT number density limits the particle growth to a
much smaller radius, and backscatter calculations suggest that the NAT
particles should be detectable after 0.8 days following nucleation for the
perpendicular backscatter threshold and after 1.3 days for the total
backscatter threshold. The details of the scattering calculations depend on
assumptions about the underlying particle characteristics, for which we lack
definitive knowledge. However, observationally we repeatedly see large
depletions of HNO3 without accompanying particle detections, which
can be accounted for qualitatively by a NAT population characterized by low
number densities/large radii.
Thirty-day time series of Antarctic raster plots at 32 hPa for
2006–2015. Day number is shown on the vertical axis. (a) TTE
(days). (b)T-TICE (K).
Interannual variations in the early Antarctic PSC season
In this section we investigate the interannual variability of Antarctic PSCs
and HNO3 over the past decade and again make use of the geolocated
raster plot format discussed in Sect. .
Figure shows the MLS
HNO3 and CALIOP LS_index at 32 hPa for 30 days from day
number 132 to 161 (12 May to 10 June) for the years 2006–2015. The
corresponding time series for TTE and T-TICE are shown in
Fig. . Additionally, in
Fig. , we present a complementary
side-by-side comparison of the same observations by plotting the MLS
HNO3 as a time series with each observation colored according to the
TTE (Fig. a) or the CALIOP LS_index
(Fig. b). The evolution of the Antarctic
dataset of HNO3, LS_index, and the corresponding TTE and T-TICE can then be followed as a function of time by reference
to the above figures. In this analysis we have not treated ice PSCs
separately and they are counted as part of the solid PSC population. However,
in general, the number of PSCs classified as ice types in the time period
considered here is low and constitutes less than 2 % of the total PSC
detections, except for the years 2007 and 2011, in which ice is 6 % of
the total and accompanying dehydration is observed about a week before the
end of the time period. The extent to which the polar vortex distorts and
wanders around the South Pole can be assessed by a dynamical diagnostic such
as the vortex–temperature concentricity (VTC). This hybrid
temperature–vortex diagnostic see their Eq. 1 and
Fig. 16 indicates that, for the Southern Hemisphere, the
cold pool temperatures and the polar vortex are highly concentric. We have
also investigated the daily scatter of temperature vs. vorticity in the
ERA-Interim reanalysis data (not shown here), and find that the annular
region 60 to 82∘ S (visible to Aura and CALIOP) describes adequately
the state of the region poleward of 82∘ S (not sampled by Aura or
CALIOP).
The start of the PSC season appears to display two modes (see
Figs. b and
b), with some years having larger coverage of
solid PSCs (2007, 2011, and 2014) than others, which show larger coverage of
liquid PSCs (2008, 2009, 2010, and 2015). We identify the presence of
sub-visible PSCs by a delay between the onset of gas-phase HNO3
depletion (see Figs. a and
a) and the geophysically associated detection
of PSCs (see Figs. b and
b). Table lists
the day number of the initial onset of HNO3 depletion, the first day
of detection of PSCs by CALIOP, the presence of sub-visible PSCs, and the
predominant PSC class (solid or liquid) for the first few days following
detection. Sub-visible clouds are present in 5 out of the 7 years with MLS
and CALIOP overlap during the critical time period when uptake of gas-phase
HNO3 is first detected. The time lag between the observed depletion
of gas-phase HNO3 and the detection of PSCs varies and is largest in
2009 and 2014. We infer that the sub-visible PSCs are composed of NAT because
the expected uptake of HNO3 is negligible for STS at the associated
ambient temperatures (see
Fig. b). In 2015 there is a
notable period of several days (148–153) without many PSC detections (see
Figs. b and
b), although HNO3 is still
consistently low (see Fig. a),
probably indicating sedimentation of NAT and permanent denitrification.
However, since have reported the presence of
NAT with larger apparent sizes compared to compact spherical particles and
with concomitant reduced settling rates, we must also consider the
possibility that the NAT radius grew larger and subsequently evolved into
sub-visible NAT.
Comparison of times of occurrence of HNO3 depletion and
detection of PSCs at the start of each PSC season.
YearOnset day of HNO3 depletionFirst day of PSC detectionSub-visible PSCsDominant PSC class2006148***2007137137NoSOL2008145147YesLIQ2009135141YesLIQ2010140141YesLIQ2011140141YesSOL2012139***2013138***2014133139YesSOL2015139139NoLIQ
* indicates no MLS and CALIOP
overlap.
Time series for the Antarctic for associated HNO3 and PSCs
during 2006–2015 at 32 hPa. (a) MLS HNO3 vs. day number.
The color scale shows the TTE. Only data for TTE > 0.1 day are plotted.
The inset pie charts indicate the relative proportions of measurements in six
categories (red–yellow sectors are solid PSCs; purple–blue sectors are
liquid PSCs) as defined in the text and in Fig. .
(b) CALIOP LS_index vs. day number. The color scale shows
the LS_index. Gray shading indicates no measurements. Light green
shading in (b) indicates the envelope of MLS HNO3
observations in (a).
Results of the K=6 cluster analysis of the combined MLS and
CALIOP data for the Antarctic for the years 2006–2015 at 32 hPa.
Thermodynamic diagrams indicate for reference the theoretical HNO3
uptake by STS (blue–black dashed line) and by NAT (green–black dashed
line). The scatter plots show the MLS HNO3 vs. temperature relative
to the ice frost point colored by the corresponding LS_index
obtained from CALIOP. Column a (b) shows the data in three
groups a1–a3 (b1–b3), which are seen to
be predominantly liquid (solid) PSC detections according to the
LS_index. The colored contours (a1 – purple, a2
– dark blue, a3 – light blue, b1 – red, b2 –
orange, b3 – yellow) contain 95 % of the corresponding cluster
members. The maps show the geographic distribution of the members of each of
the clusters and are color-coded by the LS_index (inset color bar).
A 2-D view (HNO3 vs. TTE) is provided of the cluster densities
(purple–yellow shading indicates low to high density) and the accompanying
colored solid lines represent the normalized 1-D histogram of the TTE values.
The cluster densities are also displayed as a 2-D view of LS_index
vs. day number.
and presented
intercomparisons of CALIOP vs. MIPAS PSC detections and statistics on the
frequency of type classifications that are relevant here. During May,
considerably more MIPAS-only PSC detections (i.e., without corresponding
matching detections by CALIOP) were found by , and
even with longer-term averaging, over the entire May–October period,
concluded that MIPAS has higher sensitivity to PSCs
since, for the cases where CALIOP detects no cloud, about 60 % correspond
to cloudy scenes for MIPAS. Therefore, these MIPAS/CALIOP comparisons support
our conclusion that CALIOP is not sensitive to low number density and large
particle NAT.
Results of the K=6 cluster analysis for 2006–2015: the number
of members assigned to each group, the mean and standard deviation of the
relative number of observations, and the centroids in the four-variable data
space are given.
The goal of describing the interannual variability of PSC seasons within the
context of a decadal climatology can be met by synthesizing the CALIOP and
MLS observations, consisting of the four-variable dataset (HNO3, TTE,
T-TICE and LS_index), into a number of
characteristic groups or clusters and thereby capturing the major
characteristics of PSC formation. Simple partitioning obtained by setting a
single threshold boundary on each of the four variables would result in 16
different PSC groups (some of which may be empty). Such a large number of
groupings would complicate interpretation, and so a more parsimonious scheme
is desirable to enforce a reduction in the number of groups. Cluster analysis
(CA) is a well-established tool for unsupervised exploration of a dataset
. Ideally members of the same cluster (identified by their
proximity to the cluster centroid) will naturally exhibit similar intrinsic
properties and display low within-cluster variance, whereas the differences
amongst the members of one cluster to another will display high
between-cluster variance. We used a K means centroid algorithm with a
Euclidian distance metric to partition the four-variable dataset after
performing zero mean and unit variance normalization. K means analyses were
performed for a varying number of imposed clusters (K=2 to K=20), and the
gap statistic was used to assess the optimal
number of clusters by comparison with uniformly random data and an
uncorrelated dataset obtained by randomly reordering the measurement
times of the four variables. A steep rise in the gap statistic was observed
over the range K=2 to K=7, followed by a flattened plateau region out to
K=20 (not shown). The clusterings obtained for K=6 are shown in
Table and Fig. for all the
years 2006–2015. The K=6 case was chosen because the clusters fell
practically into two sets (a, b) of three groups, corresponding to
predominantly liquid (Fig. a,
LS_index> 0) and predominantly solid
(Fig. b, LS_index< 0) PSCs. No
particular improvement was observed for the K=7 case. The
LS_index vs. day number scatter plot indicates that there is some
cross-over of liquid/solid PSCs present in both the a1 and a2 groups. The
groups are presented superposed as a scatter plot on the thermodynamic
HNO3 vs. T-TICE diagram and show clearly that the two
sets (a, b) are associated with the STS and NAT equilibrium branches. As in
previous analyses, the NAT population exhibits considerable non-equilibrium
effects , with the temperature
distribution extending to temperatures as low as the STS branch. No
correction has been made for the suspected temperature bias in the
meteorological temperature data (Sect. ).
The stereographic map projections in Fig. show
the PSC groups with higher temperatures (a3, b2, b3) extending to lower
latitudes, reflecting the general outward radial increase in the polar
temperature distribution. However, in particular, group b3 displays
similarities to a circumpolar NAT belt , although it is notable that this group also includes
CALIOP detections at temperatures apparently higher than the NAT existence
threshold TNAT=TICE+7 K. The b3 group
temperature history (HNO3 vs. TTE) also shows little exposure to low
temperatures. These may result from the inability of the gridded synoptic
reanalysis data to capture accurately the local temperature minima. Another
possibility is that the NAT particles may survive for a time before fully
melting as they are advected downstream away from
their gravity-wave sites of origin.
Compelling evidence of the differences in the formation of liquid and solid
PSCs can be deduced from comparisons of the temperature history of the
groups. For the case of moderate gas-phase HNO3 depletion, the
occurrence of liquid PSCs (a3) shows a steep fall-off in the TTE distribution
beyond ∼ 1 day. In contrast, the occurrence of solid PSCs (b2) extends
to TTE ∼ several days and also shows a trend of declining HNO3
with increasing TTE that can be explained by reference to the NAT growth
curves modeled in Fig. . For the case of large
gas-phase HNO3 depletion, the b1 group shows a peak around
TTE = 6 days, and very few of these solid PSCs formed at
TTE < 2 days. This is also a consequence of the microphysics of NAT
growth since it requires ∼ days for the NAT particles to grow sufficiently to substantially
deplete the gas-phase HNO3. Permanent denitrification caused by
sedimentation of large NAT is the likely cause of the fall-off in the
occurrence of PSCs in the b1 group at large TTE. In contrast, there exists a
substantial occurrence of liquid PSCs at all values of TTE in groups a1 and
a2, as expected since the growth/evaporation of STS is a faster process
dependent on the instantaneous temperature.
The total number of coincident MLS and CALIOP observations over the 10-year
time span is ∼ 2 × 104, and the mean (standard deviation)
of the relative number of observations (in percent) for group a is 55 (8),
and for group b it is 45 (11). Therefore liquid PSCs (group a) are the
dominant form and solid PSCs (group b) have slightly more variability. The
corresponding breakdown of the mean and standard deviation for the individual
groups is given in Table .
The observations in each cluster obtained from the decadal climatology were
sub-divided to produce data for the individual PSC seasons. The results are
shown in the pie charts in Fig. to provide a
convenient summary of the interannual variations. Note that the year 2006
cannot be compared to the others because the sampling consists of only 3 days
at the end of the season. The pie charts show that the years 2009 and 2010
stand out as the ones with the highest occurrence of liquid PSCs
(purple–blue sectors) (77 and 83 %, respectively) in the 10-year record.
The remaining years fall into two broadly related categories with a slightly
larger proportion of liquid PSCs in 2007 (52 %), 2008 (54 %), 2013
(58 %), and 2015 (53 %) and a slightly larger proportion of solid
PSCs (red–yellow sectors) in 2011 (63 %), 2012 (58 %), and 2014
(57 %).
Conclusions
A decade of MLS and CALIOP satellite measurements from 2006 to 2015 over the
Antarctic polar vortex were used to investigate the early season development
of PSCs and the gas-phase HNO3 distribution in the lower
stratosphere. We developed a compact visual representation of the daily orbit
tracks that allows a time series to be constructed from the montage of a few
hundred separate daily images, consisting of a combination of different
days/pressure levels/species, and displayed on a single page.
Lidar properties were calculated for the STS and NAT components of PSCs. We
reviewed the capabilities of spaceborne instruments (lidar, mid-infrared,
microwave) applied to the detection of PSCs and uptake of HNO3 and
used the results to investigate the generation of large particle/low number
density NAT at temperatures above the ice frost point, which results in
sub-visible PSCs that can be detected through the gas-phase uptake of
HNO3. The presence of sub-visible PSCs was found in over half of the
years examined.
In this work we have demonstrated that the early initiation of NAT nucleation
in the Antarctic vortex takes place frequently at temperatures above the ice
frost point and often before cooling produces liquid PSCs. A consistent
picture emerges, with HNO3 depletion occurring in the inner vortex,
usually before any associated PSC development is detected by CALIOP. We
conclude that an ice-seeding process is not essential for the initiation of
NAT nucleation or subsequent development of large-scale NAT growth in the
early winter.
We used detailed measurements in the CALIOP and MLS along-track transects to
illustrate that the formation of PSCs is not only governed by the local
ambient temperature, but is also shaped in large measure by the underlying
temperature histories.
A cluster analysis method was used to organize the combined CALIOP and MLS
data into a manageable form to guide an investigation of the decadal
climatology and facilitate ready comparison of the patterns of interannual
variability. The temperature distribution of the groups was used to compare
the relative frequency of formation of liquid and solid PSCs in the Antarctic
lower polar stratosphere.
Data availability
MLS data are archived at the NASA Goddard Earth Sciences Data
Information and Services Center (; ).
CALIOP data were obtained from the NASA Langley Research Center
Atmospheric Science Data Center ().
GEOS5.9.1 data were obtained from the Goddard Earth Sciences Data and
Information Services Center ().
MERRA-2 data were obtained from the Goddard Earth Sciences Data and
Information Services Center ().
IDL software for calculation of PSC thermodynamic properties provided by
M. E. Hervig was obtained from the GATS Scientific Software 95 website
(http://gwest.gats-inc.com/software/software_page.html). Fortran
software for T-matrix calculations provided by M. I. Mishchenko was obtained
from the NASA GISS website
(http://www.giss.nasa.gov/staff/mmishchenko/t_matrix.html).
Acknowledgements
We gratefully acknowledge members of the teams associated with the CALIOP and
MLS instruments, and the GEOS-5 meteorological analyses. Work at the Jet
Propulsion Laboratory, California Institute of Technology, was carried out
under a contract with the National Aeronautics and Space Administration. We
acknowledge the scientific guidance and sponsorship of the World Climate
Research Programme, coordinated in the framework of the SPARC
(Stratosphere-troposphere Processes And their Role in Climate) Polar
Stratospheric Clouds activity. We acknowledge the
International Space Science Institute (ISSI), Bern, Switzerland, for their
support of the Polar Stratospheric Cloud initiative. We thank the anonymous
reviewers for their careful reading of the manuscript and their comments and
suggestions. Edited by: F.
Khosrawi Reviewed by: two anonymous referees
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