1. Clear-sky thermodynamic and radiative anomalies over a sea ice sensitive region of the Arctic Joseph Sedlar and Abhay Devasthale joseph.sedlar@smhi.se S wedish Meteorological and Hydrological Institute Norrköping, Sweden 1. Introduction 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 ERA- Interim 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. 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 1 st degree, constrained by reality. 2. Data 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 3a. Thermodynamic and radiative anomalies All anomalies are calculated relative to the monthly averages from 2003-2010 (which are referred to as climatology). 5. Conclusions 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). Fig. 4. a) Time series of monthly clear-sky greenhouse anomalies (W/m 2, contours); b) the GH anomalies contribution of holding T to climatology and c) the contribution holding WV to climatology. Seasonal cycle in clear-sky fraction (Fig. 2a) Positive co-variablity in T-WV anomalies below 600 hPa (Fig. 2 b,c) LWD flux anom closely follow atm. thermodynamic anom (Fig. 3 black) 0.45 W/m 2 /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. 3. Monthly clear-sky LWD anomalies (W/m 2 ) 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). 4. Clear-sky thermo. and radiative impact on 2007 evolution 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/m 2, blue). 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/m 2 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) 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. A11K-0193 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°E- 165°W). September ice area (a x 10 5 km 2 ) with the box for ice concentrations > 15% shown in bottom right of each panel. Fig. 5. a) Clear-sky GH effect (W/m 2 ) 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. Clear-sky greenhouse (GH) LWU(100 hPa)-LWU(1000 hPa) 2003-06 GH anom = -1.20 W/m 2 ; 2007-10 GH anom = +1.18 W/m 2 (Fig. 4) Double-sided t-test with null hypothesis that means are equal disproved at 99% 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 3b. Greenhouse anomalies  Increased SWN corresponds to decreased albedo [order 20-40 W/m 2 ] (Fig. 6 a,b)  LWN deficit slightly greater than climatology [order 15 W/m 2 ] (Fig. 6b) – surface temperature feedback; see large surface temperature anomalies from July through year’s end (Fig. 6d)  Result is 20-40 W/m 2 anomalous clear-sky surface radiation available for ice melt (Fig. 6c), but essentially only during summer when clear-sky fraction is small (Fig. 6a)  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 ( δ LW/ δ T = 4 σ T 3 ) Clear-sky radiative ice melt: (1) (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! 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/m 2, 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.