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Summer air-mass transformation: feedback among physical processes
in advection of warm air over melting sea ice
Michael Tjernström ([email protected])Department of Meteorology &
Bolin Centre for Climate Research Stockholm University, Sweden
Ian Brooks1, Joseph Sedlar2, Matt Shupe3, Ola Persson3, John Prytherch1, Dominic Salisbury1, Peggy Achtert1, Barbara Brooks1, and Georgia Sotiropoulou4
1Leeds University, Leeds, UK2Swedish Meteorological and Hydrological Institute, Norrköping, Sweden3NOAA/PSD & CIRES, Boulder, Colorado US4Stockholm University, Stockholm Sweden
Part of the Swedish-Russian-US Arctic Ocean Investigation
of Climate-Crysophere-Carbon Interactions(SWERUS-C3)
Tromsö Barrow
5 juli till 19 augusti
Barrow Tromsö
21 augusti till 4 oktober
2017-11-2114th Conference on Polar Meteorology and Oceanography, Seattle
There and back again
Summer airmass transformationTransport in over sea ice
Tjernström et al. 2015
2017-11-21 Michael Tjernström, Stockholm University
Tjernström et al. 2015
2017-11-21 Michael Tjernström, Stockholm University
Temperature (ºC)
Specific humidity (g kg-1)
Surface inversions:
zi = z(T Tmax)
T0 <T(z < zi) <Tmax
2017-11-2114th Conference on Polar Meteorology and Oceanography, Seattle
Tjernström & Graversen 2009
SHEBA surface
inversions
2017-11-21 Michael Tjernström, Stockholm University
2017-11-21 Michael Tjernström, Stockholm University
Three cases:Ice cover >15% (51% of all)
• All cases with no surface
temperature inversions (62%)
• Surface temperature inversions with DQ
< 1 g kg-1 (“dry”; 13% or ~4 net days)
• Surface temperature inversions with DQ
> 1 g kg-1 (“moist”; 25% or ~8 net days)
Meridional displacement
No inversion
Dry inversion
Moist inversion
2017-11-21 Michael Tjernström, Stockholm University
From where does
the air come?
No surface inversion
Dry inversion
Moist inversion
Vertical displacement
2017-11-21 Michael Tjernström, Stockholm University
From where does
the air come?
2017-11-21 Michael Tjernström, Stockholm University
Lowest cloud base
Lowest
cloud top
Cloud
thickness
2017-11-21 Michael Tjernström, Stockholm University
Lowest cloud base
Lowest
cloud top
Cloud
thickness
2017-11-21 Michael Tjernström, Stockholm University
Lowest cloud base
Lowest
cloud top
Cloud
thickness
This much net solar radiation
(200 – 300 W m-2) could only
come from clear conditions.
Yet, the more cloudy “moist inversions”
have more net surface energy than the
less cloudy “dry inversions”
Is there a systematic sampling bias?
2017-11-21 Michael Tjernström, Stockholm University
The solar radiation problem
Calculated incoming
clear-sky radiation
Almost
the same!
Observed shortwave
radiation divided by TOA
Observed shortwave radiation
divided by clear-sky
2017-11-21 Michael Tjernström, Stockholm University
DoY 220 – 8 August
DoY 260 – 17 September
2017-11-21 Michael Tjernström, Stockholm University
About -20 Wm-2
About 0 Wm-2
Using the transmissivity and
surface albedo time series, but
setting solar conditions constant
for all days, but taken from
different days
But what happens at the top of
the atmosphere?
2017-11-21 Michael Tjernström, Stockholm University
Sedlar & Tjernström 2017
Using AIRS to find more episodes
2017-11-21 Michael Tjernström, Stockholm University
Stability index
Moisture index
Sedlar & Tjernström 2017
Take-home messages …
• Transport events lead to air-mass transformation
forcing feedbacks intimately coupled to the transport itself
• Moisture advection more important than heat advection?
• Hypothesis of an “extra-energy zone” for melting sea ice is
validated – sort of - but things are more complicated than
expected…
• Dry inversion contribute about – nothing in summer; loss of
clouds and therefore net longwave, radiation eats it all up…
• Moist inversions contribute about 10-20 W m-2 in summer
• Q: What is the atmospheric dynamics that determine the
inversion characteristics, and how can it be generalized? Is it
tied to the feedback on the feedback – on the height
anomalies?
Surface inversions:
zi = z(T Tmax)
T(z < zi) > T0
HatPro temperature error
2017-11-2114th Conference on Polar Meteorology and Oceanography, Seattle
HatPro humidity error