AIRS-Derived Turbulent Fluxes for the Northwater Polynya

MODIS image of extent of North Water Polynya in May 2015.

Data Description

The sensible heat flux (SHF) and latent heat flux (LHF) terms are given by:

    SHF = cp Sr [CSz,i IC (Ts,i - Tz) + CSz,w(1 - IC) (Ts,w - Tz)]

    LHF = ρ Sr [CEz,i Li IC (qs,i - qz) + CEz,w Lw (1 - IC) (qs,w - qz)]

where ρ is the air density, cp is the specific heat of air, Li (Lw) is the latent heat of sublimation (vaporization) over ice (water), CSz(CEz) is the sensible (latent) heat transfer coefficient over ice (i) and water (w), IC is the ice concentration, Sr is the effective wind speed at 10m (m s-1) [Andreas et al., 2010b], Ts (qs) is the temperature (specific humidity) of the surface either sea ice (i) or water(w), and Tz (qz) is the air temperature (specific humidity) at 2 meters.

SHF and LHF are calculated via the bulk method using the Monin Obukhov Similarity Theory. There were extensive in-situ measurements made over the Arctic sea ice during the Surface Heat Budget of the Arctic Ocean Project (SHEBA) campaign in 1997-1998, and Grachev et al. [2007] used these to create a highly accurate flux profile algorithm for stable conditions over the ice. This algorithm better fits the very stable boundary layer conditions in the Arctic and are used in our calculations over sea ice. Andreas et al. [2010a,b] used roughness lengths measured from the SHEBA campaign to create an algorithm over the sea ice in the winter when the ice is covered with compact, dry snow and in the summer when the ice is covered with wet snow, melt ponds and leads. As these are the most accurate estimates made for the sea ice in different seasons, these new roughness lengths are used in our model.

This updated algorithm from Launiainen and Vihma [1990] includes these changes, which improve the accuracy of the turbulent flux calculations over grid points that contain sea ice. This method also allows for the input parameters of temperature, humidity and wind speed to be taken at various heights above the surface and uses an iterative calculation that takes into account the stability of the boundary layer to calculate what the variables would be at a predetermined reference height (2 meters) [Launinien and Vihma, 1990]. For a full description of the model used to calculate the turbulent fluxes over the sea ice please reference Boisvert et al. [2013; 2015a]. These Arctic sea ice specific changes made to this algorithm have not been adapted in any other climate models or reanalysis products and are better suited to simulate turbulent fluxes from the Arctic Ocean. In fact, when compared with in situ data from the N-ICE2015 campaign, AIRS latent heat fluxes had an error of 0.74 W/m2 and sensible heat fluxes had an error of 5.32 W/m2 [Taylor et al., 2018]. Overall, these comparisons produce an error of ~20% in the AIRS-derived surface turbulent fluxes.

Specifically we use AIRS version 7, level 3 daily skin temperatures, 925-1000 hPa air temperatures, 925-1000 hPa relative humidity and 925-1000 hPa geopotential heights to calculate the sensible and latent heat flux.

10-m wind speeds come from MERRA-2, and ice concentrations come from passive microwave SSM/I.

 

References

Andreas, E. L., T. W. Horst, A. A. Grachev, P. O. G. Persson, C. W. Fairall, P. S. Guest, and R. E. Jordan (2010a), Parameterizing turbulent exchange over summer sea ice and the marginal ice zone, Q. J. R. Meteorol. Soc., 136,927-943, doi:10.1002/jq.618.

Andreas, E. L., P. O. G. Persson, R. E. Jordan, T. W. Horst, P. S. Guest, A. A. Grachev, and C. W. Fairall (2010b), Parameterizing Turbulent Exchange over Sea Ice in Winter, J. Hydrometeorology, 11, 87-104.

Grachev, A. A., E. L. Andreas, C. W. Fairall, P. S. Guest, and P. O. G. Persson (2007), SHEBA flux-profile relationships in the stable atmospheric boundary layer, Bound-Layer Meteor., 124, 315-333.

Launiainen, J., and T. Vihma (1990), Derivation of turbulent surface fluxes – An iterative flux-profile method allowing arbitrary observing heights, Environmental Software, 5, 113-124.

Taylor PC, Hegyi BM, Boeke RC, Boisvert LN. On the Increasing Importance of Air-Sea Exchanges in a Thawing Arctic: A Review. Atmosphere. 2018; 9(2):41. https://doi.org/10.3390/atmos9020041.

 

Contact

For additional information or questions, please contact Dr. Linette Boisvert: Linette.n.boisvert@nasa.gov

 


 

Data File Description/Formats

AIRS-Derived_LatentHeat_NorthWaterPolynya.zip / AIRS-Derived_SensibleHeat_NorthWaterPolynya.zip are zip files containing daily files of latent or sensible heat turbulent fluxes over the North Water Polynya & Baffin Bay. Data is gridded to a 25 sq km grid. Files are in binary, small-endian, floating-point data type, with a grid size of 51 x 51. Filename format is: "update_FF_YYYYddd", where FF is for either LH (latent heat flux) or SH (sensible heat flux), YYYY is the year and ddd the day-of-year.

lons.bin and lats.bin are files containing longitude and latitude (respectively) of grid point location centers. Similar to turbulent flux files, these files are in binary, small-endian, floating-point data type, with a grid size of 51 x 51.

region_mask.bin file contains a byte mask for region type. The file is a binary file, small-endian, byte data type, with a grid size of 51 x 51.
Byte values are as follows:
4: Gulf of St. Lawrence
6: Baffin Bay
14: Canadian Archipelago
20: Land
21: Coastlines

 

References that use the data

Boisvert, L. N., Markus, T., Parkinson, C. L., & Vihma, T. (2012). Moisture fluxes derived from EOS Aqua satellite data for the North Water polynya over 2003‐2009. Journal of Geophysical Research, 117, D06119. https://doi.org/10.1029/2011JD016949

Boisvert, L. N., T. Markus, and T. Vihma (2013), Moisture flux changes and trends for the entire Arctic in 2003-2011 derived from EOS Aqua data, J. Geophys. Res., 118, doi:10.1002/jgrc.20414.

Boisvert, L. N., D. L. Wu, T. Vihma, and J. Susskind (2015a), Verification of air / surface humidity differences from AIRS and ERA-Interim in support of turbulent flux estimation in the Arctic, J. Geophys. Res. Atmos., 120, doi:10.1002/2014JD021666.

Boisvert, L. N., D. L. Wu, and C.-L. Shie (2015b), Increasing evaporation amounts seen in the Arctic between 2003 and 2013 from AIRS data. J. Geophys. Res. Atmos., 120, 6865–6881, doi:10.1002/2015JD023258.

Boisvert, L. N., and J. C. Stroeve (2015), The Arctic is becoming warmer and wetter as revealed by the Atmospheric Infrared Sounder, Geophys. Res. Lett., doi:10.1002/2015GL063144.

Boisvert, L. N., A. A. Petty, and J. C. Stroeve (2016), The impact of the extreme winter 2015/16 Arctic cyclone on the Barents–Kara Seas, Mon. Wea. Rev., 144(11), 4279-4287, doi:10.1175/MWR-D-16-0234.1.

Taylor PC, Hegyi BM, Boeke RC, Boisvert LN. On the Increasing Importance of Air-Sea Exchanges in a Thawing Arctic: A Review. Atmosphere. 2018; 9(2):41. https://doi.org/10.3390/atmos9020041.

Monroe, E., P. C. Taylor and L. N. Boisvert (2021), Arctic cloud response to a Perturbation in Sea Ice Concentration: The North Water Polynya, Journal of Geophysical Research: Atmospheres.

Boisvert, L. N., R. Boeke, P. C. Taylor and C. L. Parker (in prep), Observational evidence of wintertime surface based Arctic Amplification related to surface turbulent fluxes’.

Taylor et al. (in prep), Process drivers, inter-model spread, and the path forward: A review of amplified Arctic warming

 


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