Journal article Open Access

Supercooled liquid water cloud observed, analysed, and modelled at the top of the planetary boundary layer above Dome C, Antarctica

P. Ricaud; M. Del Guasta; E. Bazile; N. Azouz; A. Lupi; P. Durand; J.-L. Attié; D. Veron; V. Guidard; P. Grigioni

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    <subfield code="a">Supercooled liquid water cloud observed, analysed, and modelled at the top of the planetary boundary layer above Dome C, Antarctica</subfield>
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    <subfield code="a">Atmospheric Science</subfield>
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    <subfield code="a">10.5194/acp-20-4167-2020</subfield>
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    <subfield code="a">Abstract. A comprehensive analysis of the water budget over the Dome C (Concordia,
Antarctica) station has been performed during the austral summer 2018–2019
as part of the Year of Polar Prediction (YOPP) international campaign. Thin
(∼100 m deep) supercooled liquid water (SLW) clouds have been
detected and analysed using remotely sensed observations at the station
(tropospheric depolarization lidar, the H2O Antarctica Microwave Stratospheric and Tropospheric
Radiometer (HAMSTRAD), net
surface radiation from the Baseline Surface Radiation Network (BSRN)), radiosondes, and satellite observations (CALIOP, Cloud-Aerosol LIdar with Orthogonal Polarization/CALIPSO, Cloud Aerosol Lidar and Infrared
Pathfinder Satellite Observations) combined with a specific
configuration of the numerical weather prediction model: ARPEGE-SH (Action
de Recherche Petite Echelle Grande Echelle – Southern Hemisphere). The
analysis shows that SLW clouds were present from November to March, with the
greatest frequency occurring in December and January when ∼50 % of the days in summer time exhibited SLW clouds for at least 1 h. Two case studies are used to illustrate this phenomenon. On 24 December 2018, the atmospheric planetary boundary layer (PBL) evolved
following a typical diurnal variation, which is to say with a warm and dry
mixing layer at local noon thicker than the cold and dry stable layer at
local midnight. Our study showed that the SLW clouds were observed at Dome C
within the entrainment and the capping inversion zones at the top of the
PBL. ARPEGE-SH was not able to correctly estimate the ratio between liquid
and solid water inside the clouds with the liquid water path (LWP) strongly
underestimated by a factor of 1000 compared to observations. The lack of
simulated SLW in the model impacted the net surface radiation that was 20–30 W m−2 higher in the BSRN observations than in the ARPEGE-SH
calculations, mainly attributable to the BSRN longwave downward surface
radiation being 50 W m−2 greater than that of ARPEGE-SH. The second
case study took place on 20 December 2018, when a warm and wet episode
impacted the PBL with no clear diurnal cycle of the PBL top. SLW cloud
appearance within the entrainment and capping inversion zones coincided with
the warm and wet event. The amount of liquid water measured by HAMSTRAD was
∼20 times greater in this perturbed PBL than in the typical
PBL. Since ARPEGE-SH was not able to accurately reproduce these SLW clouds,
the discrepancy between the observed and calculated net surface radiation
was even greater than in the typical PBL case, reaching +50 W m−2,
mainly attributable to the downwelling longwave surface radiation from BSRN
being 100 W m−2 greater than that of ARPEGE-SH. The model was then run
with a new partition function favouring liquid water for temperatures below
−20 down to −40 ∘C. In this test mode, ARPEGE-SH has
been able to generate SLW clouds with modelled LWP and net surface radiation
consistent with observations during the typical case, whereas, during the
perturbed case, the modelled LWP was 10 times less than the observations and
the modelled net surface radiation remained lower than the observations by
∼50 W m−2. Accurately modelling the presence of SLW
clouds appears crucial to correctly simulate the surface energy budget over
the Antarctic Plateau.</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">M. Del Guasta</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">E. Bazile</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">N. Azouz</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">A. Lupi</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">P. Durand</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">J.-L. Attié</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">D. Veron</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">V. Guidard</subfield>
  <datafield tag="700" ind1=" " ind2=" ">
    <subfield code="a">P. Grigioni</subfield>
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