Not logged in
PANGAEA.
Data Publisher for Earth & Environmental Science

Mchedlishvili, Alexander; Lüpkes, Christof; Petty, Alek; Tsamados, Michel; Spreen, Gunnar (2023): Gridded pan-Arctic total neutral atmospheric 10-m drag coefficient estimates derived from ICESat-2 ATL07 sea ice height data (Version 2) [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.959728

Always quote citation above when using data! You can download the citation in several formats below.

RIS CitationBibTeX CitationShow MapGoogle Earth

Abstract:
This data-set contains average drag coefficient estimates for the whole of the Arctic (resampled onto a 25 km polar stereographic grid) for each month from 11.2018 to 06.2022. The total drag coefficients are referenced to a height of 10 meters and a neutrally stratified atmosphere is assumed. The total drag is the sum of open water drag scaled with (1-A) where A is sea ice concentration (Spreen et al., 2008), drag due to floe edges incorporated via a constant derived from parameterization (Lüpkes et al., 2012) and scaled with A(1-A), sea ice skin drag scaled with A, and sea ice form drag due to obstacles (e.g. ridges) computed from sea ice feature averages (Garbrecht et al., 2002) derived from ICESat-2 ATL07 sea ice heights (for all 25 km grid cells filled by ICESat-2 ATL07 data) (Kwok et al., 2021). Each individual component is also given as a separate variable in the data-set. In addition, the sea ice feature averages (10-km average obstacle height and obstacle spacing) used to derive form drag due to obstacles is also gridded and included in the data files. Obstacles below a threshold value of 20 cm and those that do not fulfill the Rayleigh Criterion (wherein if the trough between two peaks is smaller than the higher of two crests, only the higher one is considered) are omitted. Lastly, we scale up the ICESat-2 ATL07-derived form drag coefficients via a regression derived from comparing them to drag coefficients derived from topographic data collected during the 04.2019 NASA airborne Operation IceBridge ICESat-2 under-flights (Studinger, 2013). This is to deal with the sampling issues associated with resolution differences.
The current updated version corrects for unrealistic negative ICESat-2 ATL07-derived obstacle form drag coefficients by fixing the y-intercept of the regression used to scale up the values to zero.
Keyword(s):
Arctic; Drag Coefficient; Sea ice; sea ice-atmosphere interactions
Supplement to:
Mchedlishvili, Alexander; Lüpkes, Christof; Petty, Alek; Tsamados, Michel; Spreen, Gunnar (2023): New estimates of pan-Arctic sea ice–atmosphere neutral drag coefficients from ICESat-2 elevation data. The Cryosphere, 17(9), 4103-4131, https://doi.org/10.5194/tc-17-4103-2023
Related to:
Garbrecht, Thomas; Lüpkes, Christof; Hartmann, Jörg; Wolff, Mareile (2002): Atmospheric drag coefficients over sea ice - validation of a parameterisation concept. Tellus Series A-Dynamic Meteorology and Oceanography, 54(2), 205, https://doi.org/10.3402/tellusa.v54i2.12129
Kwok, Ronald; Petty, Alek; Cunningham, G; Markus, T; Hancock, D; Ivanoff, A; Wimert, J; Bagnardi, M; Kurtz, Nathan; et al. (2021): ATLAS/ICESat-2 L3A Sea Ice Height, version 5. NASA National Snow and Ice Data Center DAAC, https://doi.org/10.5067/ATLAS/ATL07.005
Lüpkes, Christof; Gryanik, V M; Hartmann, Jörg; Andreas, Edgar L (2012): A parametrization, based on sea ice morphology, of the neutral atmospheric drag coefficients for weather prediction and climate models. Journal of Geophysical Research: Atmospheres, 117(D13), https://doi.org/10.1029/2012JD017630
Petty, Alek; Tsamados, Michel; Kurtz, Nathan (2017): Atmospheric form drag coefficients over Arctic sea ice using remotely sensed ice topography data, spring 2009–2015. Journal of Geophysical Research-Earth Surface, 122(8), 1472-1490, https://doi.org/10.1002/2017JF004209
Spreen, Gunnar; Kaleschke, Lars; Heygster, Georg (2008): Sea ice remote sensing using AMSR-E 89-GHz channels. Journal of Geophysical Research, 113(C2), https://doi.org/10.1029/2005JC003384
Studinger, Michael (2013): IceBridge ATM L1B Elevation and Return Strength, Version 2. NASA National Snow and Ice Data Center DAAC, https://doi.org/10.5067/19SIM5TXKPGT
Original version:
Mchedlishvili, Alexander; Spreen, Gunnar; Lüpkes, Christof; Tsamados, Michel; Petty, Alek (2022): Gridded pan-Arctic total neutral atmospheric 10-m drag coefficient estimates derived from ICESat-2 ATL07 sea ice height data. PANGAEA, https://doi.org/10.1594/PANGAEA.951333
Project(s):
Funding:
German Research Foundation (DFG), grant/award no. 268020496: TRR 172: ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms
Horizon 2020 (H2020), grant/award no. 101003826: Climate Relevant interactions and feedbacks: the key role of sea ice and Snow in the polar and global climate system
Coverage:
Latitude: 90.000000 * Longitude: 0.000000
Date/Time Start: 2018-11-01T00:00:00 * Date/Time End: 2022-06-30T00:00:00
Event(s):
pan-Arctic * Latitude: 90.000000 * Longitude: 0.000000 * Location: Arctic
Comment:
The data files are in NetCDF4 format and contain drag coefficients from obstacles derived from ICESat-2 ATL07 (drag_IS2), drag coefficients due to open water (draw_ow), drag coefficients from floe edges (drag_fe), sea ice skin drag coefficients (drag_s) and total drag coefficients (drag_TOT; the sum of the previous 4). It also contains the data distribution (data_dist), longitude (lon), latitude (lat), average obstacle heights (H_e) and obstacle spacings (x_e). All data variables are gridded onto a 25 km polar stereographic grid and are thus stored as matrices. Longitude and latitude matrices contain one extra row and column for python pcolormesh(shading='flat') compatibility.
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethod/DeviceComment
1DATE/TIMEDate/TimeMchedlishvili, AlexanderGeocode
2netCDF filenetCDFMchedlishvili, Alexander
3netCDF file (File Size)netCDF (Size)BytesMchedlishvili, Alexander
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
44 data points

Download Data

Download dataset as tab-delimited text — use the following character encoding:

View dataset as HTML