A11K-0193
Clear-sky thermodynamic and radiative anomalies over
a sea ice sensitive region of the Arctic
Fig. 1. 2003-2010 September mean sea-ice concentation
(fraction) from AMSR-E (Spreen et al. 2008). The Laptev Sea
and East Siberian Sea region where temporal and spatial
averages are examined is shown in black (74-82°N, 135°E165°W). September ice area (a x 105 km2) with the box for
ice concentrations > 15% shown in bottom right of each
panel.
Joseph Sedlar and Abhay Devasthale
joseph.sedlar@smhi.se
Swedish Meteorological and Hydrological Institute
Norrköping, Sweden
1. Introduction
2. Data
Rapid Arctic sea ice decline over the past decade has drawn community-wide awareness to extreme warming of the Arctic region. Prior to
2012, Arctic sea-ice reached a record minimum in September 2007. Since then, a number of studies have emerged identifying potential
mechanisms in atmospheric circulation, ocean heating and mixing, cloud and latent heat anomalies, and associated feedbacks that may have
contributed to the record ice loss of 2007. Recently, Graversen et al. (2011) examined thermodynamic advection anomalies from ERAInterim over the Laptev and East Siberian Seas (Fig. 1), where they find anomalously large heat and moisture advection and cloud longwave
radiation could explain the large ice loss over that region.
• AIRS (Atmospheric Infrared Sounder) Aqua:
Daily Level3 1°x1° Version 5 Standard Product (ascending+descending overpasses)
Vertically-resolved temperature and water vapor mixing ratio
• RRTM-LW/SW radiative transfer calculations (monthly mean SZA from hourly estimates for mean box latitude)
• ERA-Interim monthly-averaged forecast surface albedo
• MODIS Level3 monthly-averaged cloud fraction
In this study, we quantify the monthly-averaged vertical contribution of atmospheric thermodynamics on radiative fluxes over the box region
in Fig. 1, the same region as Graversen et al. (2011), however we use clear-sky profile observations from the AIRS sounder onboard the Aqua
satellite. Radiative fluxes are estimated from AIRS thermodynamic profiles and radiative transfer. This allows a quantification of the clear-sky
radiative forcing over the Arctic and also provides an observational complement to studies that rely on model or reanalysis data. Since cloud
fields are prognostic and not directly assimilated into reanalyses, modeled clear- and cloudy fractions are not, to a 1st degree, constrained by
reality.
4. Clear-sky thermo. and radiative impact on 2007 evolution
 Increased SWN corresponds to decreased albedo [order 20-40
W/m2] (Fig. 6 a,b)
3a. Thermodynamic and radiative anomalies
 LWN deficit slightly greater than climatology [order 15 W/m2] (Fig.
6b) – surface temperature feedback; see large surface temperature
anomalies from July through year’s end (Fig. 6d)
All anomalies are calculated relative to the monthly averages from 2003-2010 (which are referred to as climatology).
• Seasonal cycle in clear-sky fraction (Fig. 2a)
 Result is 20-40 W/m2 anomalous clear-sky surface radiation available
for ice melt (Fig. 6c), but essentially only during summer when clear-sky
fraction is small (Fig. 6a)
• Positive co-variablity in T-WV anomalies
below 600 hPa (Fig. 2 b,c)
 Surface temperature anomalies positively correlated (r = 0.92) with
clear-sky LWD anomalies (Fig. 7); for Jan-May 2007, anomalous clear-sky
LWD enough to account for > 80% of temperature anomalies (δLW/δT
= 4σT3)
• LWD flux anom closely follow atm.
thermodynamic anom (Fig. 3 black)
• 0.45 W/m2/yr trend for 3-mon running
mean clear-sky LWD anom (signif. at 99%)
• Temperature contribution to LWD anom >
WV contribution (Fig. 3 blue, red)
Fig. 2. a) Monthly climatology of clear-sky fraction, and
time-pressure anomalies of b) temperature [K] and c)
water-vapor mixing ratio (g/kg).
3b. Greenhouse anomalies
Clear-sky greenhouse (GH)
LWU(100 hPa)-LWU(1000 hPa)
• 2003-06 GH anom = -1.20
W/m2 ; 2007-10 GH anom =
+1.18 W/m2 (Fig. 4)
• Double-sided t-test with null
hypothesis that means are equal
disproved at 99%
Fig. 4. a) Time series of monthly clear-sky greenhouse anomalies (W/m2,
contours); b) the GH anomalies contribution of holding T to climatology
and c) the contribution holding WV to climatology.
• Monthly PW anom < +/- 1 mm,
leads to linear GH anom
response (Fig. 5)
• Monthly WV averaging reduces
shorter time scale WV advection
events – Clausius-Clapyeron
controlled WV increases by
already large T anomalies
Fig. 3. Monthly clear-sky LWD anomalies (W/m2)
where the black line represent the total LWD anomaly,
the blue line represents LWD anomaly contribution
when holding the T profile to monthly climatology while
allow WV to vary as observed, the red line is the LWD
anomaly contribution of holding the WV profile to
monthly climatology while allow T to vary as observed.
The gray line is the monthly precipitable water (mm).
Fig. 6. Monthly 2007 evolution (solid lines) and climatology (dashed) of a)
cloud fraction (back) and surface albedo (blue); b) net SW (red), LW (blue)
and NET (black) surface radiation; c) anomalous NET radiation; d) surface
temperature; e) ice melt (positive) or freeze (negative) thickness anomalies
due to anomalous clear-sky surface radiation. CLIM refers to the
climatological surface LWU or surface temperature, respectively.
Fig. 7. Monthly clear-sky temperature anomalies (K,
black) and clear-sky LWD (W/m2, blue).
5. Conclusions
1. AIRS clear-sky profiles indicate substantial variability in thermodynamic advection over the East
Siberian and Laptev Sea regions
2. Monthly downwelling LW estimates show a clear response to thermodynamic anomalies, some as
large as +/- 12 W/m2
3. The change from negative to positive greenhouse anomalies agrees with the 3-mon running mean
linear trend of LWD anomalies – suggesting the shift in GH anomaly is at least partially manifested on
the surface downwelling fluxes
4. Rather than contributing to anomalous ice melt during the summer, the increased clear-sky radiative
flux anomalies are shown to be significant during the winter, spring and late autumn seasons –
atmospheric preconditioning of sea ice for the following melt season highlighted!
5. We find a clear-sky anomalous retardation of ice growth of 0.3 m, on top of 0.7 m climatological ice
melt – in an region where ice thickness generally ranges 0.5-2 m – clear-sky melt contribution is
significant!
6. Fig. 8 below shows a non-linear metric for ice melt/freeze potential as a function of cloud fraction,
surface albedo and radiative fluxes, which can be adapted to regions with similar solar and surface
properties (see Sedlar and Devasthale 2012)
Fig. 8. Temporal evolution of monthly clear-sky ice
melt (positive contours) and freeze (negative
contours) anomalies for hypothetical cloud
fraction (ordinate) and surface albedo (abscissa)
anomalies. Contour anomalies are shown for
LWD anomaly of + 9 W/m2, the mean LWD
anomaly for the same months of 2007. Solid lines
represent cloud fraction and albedo anomaly
relationships needed for zero change in ice melt
(freeze) relative to climatology for the respective
LWD anomalies.
Fig. 5. a) Clear-sky GH effect (W/m2) as a function of precipitable water
(PW, mm) for all months (black dots) and climatological monthly means
(red dots); b) Clear-sky GH anomalies as function of PW anomalies.
References
Graversen, R.G., T. Mauritsen, S. Drijfhout, M. Tjernström and S. Mårtensson (2011), Warm winds from the Pacific cuased extensive Arctic sea-ice melt in summer 2007, Clim. Dyn., 36, 2103-2112, doi: 10.1007/s00382-010-0809-z.
Kwok, R. and D.A. Rothrock (2009), Decline in Arctic sea ice thickness from submarine and ICESat records: 1958-2008, Geophys. Res. Lett., 36, L15501, doi:10.1029/2009GL039035.
Sedlar, J. and A. Devasthale (2012), Clear-sky thermodynamic and radiative anomalies over a sea ice sensitive region of the Arctic, J. Geophys. Res., 117, D19111, doi: 10.1029/2012JD017754.
Clear-sky radiative ice melt:
𝐹𝑐𝑠
𝑀=
1−𝑓
𝐿𝑠 ∙ 𝜌𝑖
(1)
𝐹𝑐𝑠 = 𝑆𝑊𝐷 1 − 𝛼𝑠 + 𝐿𝑊𝑁
(2)
 Total clear-sky ice melt for May-August 2007 (0.713 m) approximately identical to
climatology (0.706 m) (Table 1)
 Regional mean ice thickness: 1-2 m during spring; 0.5-1 m at end of melt season
(Kwok and Rothrock 2009) – clear sky melt is significant!
 Anomalous LWD fluxes from warm and moist air masses important for
retardation of ice growth (~0.3 m) during winter, spring and late autumn –
atmospheric preconditioning!