{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:30:39Z","timestamp":1760236239366,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T00:00:00Z","timestamp":1635897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The European Organisation for the Exploitation of Meteorological Satellites-Ocean and Sea Ice Satellite Application Facility\u2013European Space Agency-Climate Change Initiative (EUMETSAT-OSISAF\u2013ESA-CCI) Level-4 sea-ice concentration (SIC) climate data records (CDRs), named SICCI-25km, SICCI-50km and OSI-450, provide gridded SIC error estimates in addition to SIC. These error estimates, called total error henceforth, comprise a random, uncorrelated error contribution from retrieval and sensor noise, aka the algorithm standard error, and a locally-to-regionally correlated contribution from gridding and averaging Level-2 SIC into the Level-4 SIC CDRs, aka the representativity error. However, these CDRs do not yet provide an error covariance matrix. Therefore, correlation scales of these error contributions and the total error in particular are unknown. In addition, larger-scale SIC errors due to, e.g., unaccounted weather influence or mismatch between the actual ice type and the algorithm setup are neither well represented by the total error, nor are their correlation scales known for these CDRs. In this study, I attempt to contribute to filling this knowledge gap by deriving spatial correlation length scales for the total error and the large-scale SIC error for high-concentration pack ice. For every grid cell with &gt;90% SIC, I derive circular one-point correlation maps of 1000 km radius by computing the cross-correlation between the central 31-day time series of the errors and all other 31-day error time series within that circular area (disc) with 1000 km radius. I approximate the observed decrease in the correlation away from the disc\u2019s center with an exponential function that best fits this decrease and thereby obtain the correlation length scale L sought. With this approach, I derive L separately for the total error and the large-scale SIC error for every high-concentration grid cell, and map, present and discuss these for the Arctic and the Southern Ocean for the year 2010 for the above-mentioned products. I find correlation length scales are substantially smaller for the total error, mostly below ~200 km, than the SIC error, ~200 km to ~700 km, in both hemispheres. I observe considerable spatiotemporal variability of the SIC error correlation length scales in both hemispheres and provide first directions to explain these. For SICCI-50km, I present the first evidence of the method\u2019s robustness for other years and time series of L for 2003\u20132010.<\/jats:p>","DOI":"10.3390\/rs13214421","type":"journal-article","created":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T21:57:49Z","timestamp":1635976669000},"page":"4421","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Spatial Correlation Length Scales of Sea-Ice Concentration Errors for High-Concentration Pack Ice"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7281-3746","authenticated-orcid":false,"given":"Stefan","family":"Kern","sequence":"first","affiliation":[{"name":"Integrated Climate Data Center (ICDC), Center for Earth System Research and Sustainability (CEN), University of Hamburg, 20144 Hamburg, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1002\/2013RG000431","article-title":"Arctic sea ice in transformation: A review of recent observed changes and impacts on biology and human activity","volume":"51","author":"Meier","year":"2014","journal-title":"Rev. Geophys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.rse.2016.05.020","article-title":"New visualizations highlight new information on the contrasting Arctic and Antarctic sea-ice trends since the late 1970s","volume":"183","author":"Parkinson","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"103001","DOI":"10.1088\/1748-9326\/aade56","article-title":"Changing state of Arctic sea ice across all seasons","volume":"13","author":"Stroeve","year":"2018","journal-title":"Environ. Res. Lett."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"6883","DOI":"10.1002\/2017JC012768","article-title":"Variability and trends in the Arctic Sea ice cover: Results from different techniques","volume":"122","author":"Comiso","year":"2017","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2251","DOI":"10.1175\/JCLI-D-16-0408.1","article-title":"Positive trends in the Antarctic sea ice cover and associated changes in surface temperature","volume":"30","author":"Comiso","year":"2017","journal-title":"J. Clim."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"14414","DOI":"10.1073\/pnas.1906556116","article-title":"A 40-y record reveals gradual Antarctic sea ice increases followed by decreases at rates far exceeding the rates seen in the Arctic","volume":"116","author":"Parkinson","year":"2019","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"21004","DOI":"10.3402\/polar.v33.21004","article-title":"Verification of a new NOAA\/NSIDC passive microwave sea-ice concentration climate record","volume":"33","author":"Meier","year":"2014","journal-title":"Polar Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1797","DOI":"10.5194\/tc-9-1797-2015","article-title":"Inter-comparison and evaluation of sea ice algorithms: Towards further identification of challenges and optimal approach using passive microwave observations","volume":"9","author":"Ivanova","year":"2015","journal-title":"Cryosphere"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"49","DOI":"10.5194\/tc-13-49-2019","article-title":"Version 2 of the EUMETSAT OSI SAF and ESA-CCI sea-ice concentration climate data records","volume":"13","author":"Lavergne","year":"2019","journal-title":"Cryosphere"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3261","DOI":"10.5194\/tc-13-3261-2019","article-title":"Satellite passive microwave sea-ice concentration data set intercomparison: Closed ice and ship-based observations","volume":"13","author":"Kern","year":"2019","journal-title":"Cryosphere"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2469","DOI":"10.5194\/tc-14-2469-2020","article-title":"Satellite passive microwave sea-ice concentration data set intercomparison for Arctic summer conditions","volume":"14","author":"Kern","year":"2020","journal-title":"Cryosphere"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"311","DOI":"10.5194\/essd-5-311-2013","article-title":"A long-term and reproducible passive microwave sea ice concentration data record for climate studies and monitoring","volume":"5","author":"Peng","year":"2013","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2275","DOI":"10.5194\/tc-10-2275-2016","article-title":"The EUMETSAT sea ice concentration climate data record","volume":"10","author":"Tonboe","year":"2016","journal-title":"Cryosphere"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2387","DOI":"10.5194\/tc-14-2387-2020","article-title":"The Arctic Ocean observation operator for 6.9 GHz (ARC3O)\u2014Part 2: Development and evaluation","volume":"14","author":"Burgard","year":"2020","journal-title":"Cryosphere"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2051","DOI":"10.5194\/tc-12-2051-2018","article-title":"Thin Arctic sea ice in L-band observations and an ocean reanalysis","volume":"12","author":"Tietsche","year":"2018","journal-title":"Cryosphere"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2265","DOI":"10.5194\/tc-11-2265-2017","article-title":"Sea ice assimilation into a coupled ocean-sea ice model using its adjoint","volume":"11","author":"Koldunov","year":"2017","journal-title":"Cryosphere"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"761","DOI":"10.5194\/tc-10-761-2016","article-title":"The challenge and benefit of using sea ice concentration satellite data products with uncertainty estimates in summer sea ice data assimilation","volume":"10","author":"Yang","year":"2016","journal-title":"Cryosphere"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"511","DOI":"10.5194\/essd-9-511-2017","article-title":"Uncertainty information in climate data records from Earth observation","volume":"9","author":"Merchant","year":"2017","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1038\/s41597-019-0236-x","article-title":"Satellite-based time-series of sea-surface temperature since 1981 for climate applications","volume":"6","author":"Merchant","year":"2019","journal-title":"Sci. Data"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"521","DOI":"10.5194\/tc-13-521-2019","article-title":"On the timescales and length scales of the Arctic sea ice thickness anomalies: A study based on 14 reanalyes","volume":"13","author":"Ponsoni","year":"2019","journal-title":"Cryosphere"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1029\/JC091iC01p00975","article-title":"Characteristics of arctic winter sea ice from satellite multispectral microwave observations","volume":"91","author":"Comiso","year":"1986","journal-title":"J. Geophys. Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"C02S07","DOI":"10.1029\/2007JC004257","article-title":"Trends in the sea ice cover using enhanced and compatible AMSR-E, SSM\/I, and SMMR data","volume":"113","author":"Comiso","year":"2008","journal-title":"J. Geophys. Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/S0034-4257(96)00220-9","article-title":"Passive microwave algorithms for sea ice concentration: A comparison of two techniques","volume":"60","author":"Comiso","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1109\/TGRS.2002.808317","article-title":"Sea ice concentration, ice temperature, and snow depth, using AMSR-E data","volume":"41","author":"Comiso","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","unstructured":"Smith, D.M., and Barrett, E.C. (1994). Satellite Mapping and Monitoring of Sea Ice, University of Bristol. Report. CB\/RAE\/9\/2\/4\/2034\/113\/ARE, RSU."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2625","DOI":"10.1080\/01431169608949096","article-title":"Extraction of winter total sea ice concentration in the Greenland and Barents Seas from SSM\/I data","volume":"17","author":"Smith","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"32","DOI":"10.3390\/ijgi1010032","article-title":"EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets","volume":"1","author":"Brodzik","year":"2012","journal-title":"ISPRS Int. Geo-Inf."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"32","DOI":"10.3390\/ijgi1010032","article-title":"Correction: Brodzik, M.J. et al. EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets","volume":"1","author":"Brodzik","year":"2012","journal-title":"ISPRS Int. Geo-Inf."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.rse.2010.10.017","article-title":"The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system","volume":"116","author":"Donlon","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.rse.2017.06.034","article-title":"Uncertainty propagation in observational references to climate model scales","volume":"203","author":"Bellprat","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"8244","DOI":"10.1175\/JCLI-D-14-00345.1","article-title":"Characteristics of Arctic sea-ice thickness variability in GCMs","volume":"27","author":"Bitz","year":"2014","journal-title":"J. Clim."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"35","DOI":"10.3402\/polar.v22i1.6441","article-title":"Improving sea ice type discrimination by the simultaneous use of SSM\/I and scatterometer data","volume":"22","author":"Voss","year":"2003","journal-title":"Polar Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3897","DOI":"10.5194\/tc-15-3897-2021","article-title":"MOSAiC drift expedition from October 2019 to July 2020: Sea ice conditions from space and comparison with previous years","volume":"15","author":"Krumpen","year":"2021","journal-title":"Cryosphere"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"29","DOI":"10.3189\/2015AoG69A615","article-title":"Pan-Arctic lead detection from MODIS thermal infrared imagery","volume":"56","author":"Willmes","year":"2015","journal-title":"Ann. Glaciol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1957","DOI":"10.3390\/rs12121957","article-title":"A new algorithm for daily sea ice lead identification in the Arctic and Antarctic winter from thermal-infrared satellite imagery","volume":"12","author":"Reiser","year":"2020","journal-title":"Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4421\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:25:27Z","timestamp":1760167527000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/21\/4421"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,3]]},"references-count":35,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13214421"],"URL":"https:\/\/doi.org\/10.3390\/rs13214421","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,11,3]]}}}