Vote for your favorite mineral in #MinCup25! - Carpathite vs. Tugtupite
Battle of mineralogical oddities as organic mineral #carpathite battles against vs #tugtupite, a mineral that looks like reindeer blood!
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Lindsay, R., Schweiger, A. (2015) Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations. The Cryosphere, 9 (1). 269-283 doi:10.5194/tc-9-269-2015

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleArctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations
JournalThe Cryosphere
AuthorsLindsay, R.Author
Schweiger, A.Author
Year2015 (February 10)Volume9
Issue1
PublisherCopernicus GmbH
DOIdoi:10.5194/tc-9-269-2015Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID9431135Long-form Identifiermindat:1:5:9431135:2
GUID0
Full ReferenceLindsay, R., Schweiger, A. (2015) Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations. The Cryosphere, 9 (1). 269-283 doi:10.5194/tc-9-269-2015
Plain TextLindsay, R., Schweiger, A. (2015) Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations. The Cryosphere, 9 (1). 269-283 doi:10.5194/tc-9-269-2015
In(2015, February) The Cryosphere Vol. 9 (1) Copernicus GmbH

See Also

These are possibly similar items as determined by title/reference text matching only.

Stroeve, J., Barrett, A., Serreze, M., Schweiger, A. (2015) Corrigendum to "Using records from submarine, aircraft and satellites to evaluate climate model simulations of Arctic sea ice thickness" published in The Cryosphere, 8, 1839–1854, 2014. The Cryosphere, 9 (1). 81 doi:10.5194/tc-9-81-2015
Melia, N., Haines, K., Hawkins, E. (2015) Improved Arctic sea ice thickness projections using bias-corrected CMIP5 simulations. The Cryosphere, 9 (6). 2237-2251 doi:10.5194/tc-9-2237-2015
Stroeve, J., Barrett, A., Serreze, M., Schweiger, A. (2014) Using records from submarine, aircraft and satellites to evaluate climate model simulations of Arctic sea ice thickness. The Cryosphere, 8 (5). 1839-1854 doi:10.5194/tc-8-1839-2014
Griewank, P. J., Notz, D. (2015) A 1-D modelling study of Arctic sea-ice salinity. The Cryosphere, 9 (1). 305-329 doi:10.5194/tc-9-305-2015
Horvat, C., Tziperman, E. (2015) A prognostic model of the sea-ice floe size and thickness distribution. The Cryosphere, 9 (6). 2119-2134 doi:10.5194/tc-9-2119-2015
Kaminski, T., Kauker, F., Eicken, H., Karcher, M. (2015) Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies. The Cryosphere, 9 (4). 1721-1733 doi:10.5194/tc-9-1721-2015
Wernecke, A., Kaleschke, L. (2015) Lead detection in Arctic sea ice from CryoSat-2: quality assessment, lead area fraction and width distribution. The Cryosphere, 9 (5). 1955-1968 doi:10.5194/tc-9-1955-2015
Bouillon, S., Rampal, P. (2015) On producing sea ice deformation data sets from SAR-derived sea ice motion. The Cryosphere, 9 (2). 663-673 doi:10.5194/tc-9-663-2015
Braakmann-Folgmann, Anne, Donlon, Craig (2019) Estimating snow depth on Arctic sea ice using satellite microwave radiometry and a neural network. The Cryosphere, 13 (9). 2421-2438 doi:10.5194/tc-13-2421-2019
Goelles, T., Bøggild, C. E., Greve, R. (2015) Ice sheet mass loss caused by dust and black carbon accumulation. The Cryosphere, 9 (5). 1845-1856 doi:10.5194/tc-9-1845-2015
Durand, G., Pattyn, F. (2015) Reducing uncertainties in projections of Antarctic ice mass loss. The Cryosphere, 9 (6). 2043-2055 doi:10.5194/tc-9-2043-2015
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: September 20, 2025 06:43:27
Go to top of page