Reference Publications and Documentation

CIMR references and technical information (CIMR-REFS)

 

  1. Publications about or mentioning CIMR

 

Kilic, L., Prigent, C., Aires, F., Boutin, J., Heygster, G., Tonboe, R. T., Roquet, H., Jimenez, C.,  and C. Donlon (2018), Expected performances of the Copernicus Imaging Microwave Radiometer (CIMR) for an all‐weather and high spatial resolution estimation of ocean and sea ice parameters. Journal of Geophysical Research: Oceans, 123. https://doi.org/10.1029/2018JC014408

Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49-78, https://doi.org/10.5194/tc-13-49-2019, 2019.

  1. Reference Documents

 

Albergel, C. C. Rüdiger, T. Pellarin, J. C. Calvet, N. Fritz, F. Froissard, D.  Suquia, A. Petitpa, B. Piguet, E. Martin, (2008), From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations. Hydrol. Earth Syst. Sci., vol.12, 1323-1337.

Andersen, S., R. Tonboe, L. Kaleschke, G. Heygster, and L. T. Pedersen (2006), Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice, J. Geophys. Res., 112, C08004, doi:10.1029/2006JC003543.

Ashcroft, P. and F. J. Wentz, (2000), Algorithm Theoretical Basis Document for AMSR-E Level2A Algorithm. Revised Nov. 3, 2000, Santa Rosa, CA, Remote Sensing Systems, available from https://nsidc.org/sites/nsidc.org/files/technical-references/amsr_atbd_l...

Bertino, L., Breivik, L.A., Dinessen, F., Faugere, Y., Garric, G., Hackett, B., Johannessen, J.A., Lavergne, T., Le traon, P.-Y., Pedersen, L.-T., Rampal, P., Sandven S., Schyberg H. (2016). Copernicus Marine Environment Monitoring Service Position paper: Polar and snow cover applications User Requirements Workshop [a] 

Buongiorno Nardelli, B. (2012). A novel approach for the high-resolution interpolation of in situ sea surface salinity. J. Atmos. Ocean. Technol. 29, 867–879. doi: 10.1175/JTECH-D-11-00099.1

Buongiorno Nardelli, B., Droghei, R., and Santoleri, R. (2016). Multi- dimensional interpolation of SMOS sea surface salinity with surface temperature and in situ salinity data. Remote Sens. Environ. 180, 392–402. doi: 10.1016/j.rse.2015.12.052

Chelton, D. B. and F. J. Wentz, (2005), Global microwave satellite observations of sea surface temperature for numerical weather prediction and climate research, Amer. Meteorol. Soc., vol. 86, no. 8, pp. 1097–1115, Aug. 2005.

Cho, E.; Tuttle, S.E.; Jacobs, J.M. (2017), Evaluating Consistency of Snow Water Equivalent Retrievals from Passive Microwave Sensors over the North Central U. S.: SSM/I vs. SSMIS and AMSR-E vs. AMSR2, Remote Sens., 9, 465.

Comiso, J., D. Cavalieri, and T. Markus, (2003), Sea ice concentration, ice temperature and snow depth using AMSR-E data,” IEEE Trans. Geosci. Remote Sens., vol. 43, no. 2, pp. 243–252.

Comiso, J., D. Cavalieri, and T. Markus, (2003), Sea ice concentration, ice temperature and snow depth using AMSR-E data, IEEE Trans. Geosci. Remote Sens., vol. 43, no. 2, pp. 243–252.

Comiso, J. C., and R. Kwok (1996), Surface and radiative characteristics of the summer Arctic sea ice cover from multisensor satellite observations, J. Geophys. Res., 101(C12), 28397–28416, doi:10.1029/96JC02816.

Donlon, C. J., K. S. Casey, I. S. Robinson, C. L. Gentemann, R. W. Reynolds, I. Barton, O. Arino, J Stark, N. Rayner, P. LeBorgne, D. Poulter, J. Vazquez-Cuervo, E. Armstrong, H. Beggs, D. Llewellyn Jones, P. J. Minnett, C. J. Merchant, R. Evans, (20090, The GODAE High Resolution Sea Surface Temperature Pilot Project (GHRSST-PP), Oceanography, Volume 22, Number 3, 34-45.

Donlon, C. J., M. Martin, J. D. Stark, J. Roberts-Jones, E. Fiedler and W. Wimmer, (2012), The Operational Sea Surface Temperature and Sea Ice analysis (OSTIA), Remote Sensing of the Environment, 116, 140-158, doi: 10.1016/j.rse.2010.10.017.

Dorigo, W et al, (2017), ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions, Rem. Sens. of Env., 203,  185–215

Droghei, R. B. Buongiorno-Nardelli and R. Santolieri, (2018), A New Global Sea Surface Salinity and Density Dataset From Multivariate Observations (1993–2016), Front. Mar. Sci., 27,  https://doi.org/10.3389/fmars.2018.00084

Droghei, R., Nardelli, B. B., and Santoleri, R. (2016). Combining in situ and satellite observations to retrieve salinity and density at the ocean surface. J. Atmos. Ocean. Technol. 33, 1211–1223. doi: 10.1175/JTECH-D-15-0194.1

Drüe, C. and G. Heinemann, (2004), High-resolution maps of the sea-ice concentration from MODIS satellite data,” Geophys. Res. Lett., vol. 31, no. 20, pp. L20403-1–L20403.  

Du, J., J. S. Kimball and L. A. Jones, (2015), Satellite Microwave Retrieval of Total Precipitable Water Vapor and Surface Air Temperature Over Land From AMSR2, in IEEE Transactions on Geoscience and Remote Sensing, vol. 53, no. 5, pp. 2520-2531, doi: 10.1109/TGRS.2014.2361344

Duchossois G., P. Strobl, V. Toumazou, S. Antunes, A. Bartsch, T. Diehl, F. Dinessen, P. Eriksson, G. Garric, M-N. Houssais, M. Jindrova, J. Muñoz-Sabater, T. Nagler, O. Nordbeck, User Requirements for a Copernicus Polar Mission - Phase 1 Report, EUR 29144 EN , Publications Office of the European Union, Luxembourg, 2018, ISBN 978-92-79-80961-3, doi:10.2760/22832, JRC111067[b]

Duchossois G., P. Strobl, V. Toumazou, S. Antunes, A. Bartsch, T. Diehl, F. Dinessen, P. Eriksson, G. Garric, K. Holmlund, M-N. Houssais, M. Jindrova, M. Kern, J. Muñoz-Sabater, T. Nagler, O. Nordbeck, E. de Witte, User Requirements for a Copernicus Polar Mission - Phase 2 Report, EUR 29144 EN , Publications Office of the European Union, Luxembourg, 2018, ISBN 978-92-79-80960-6, doi:10.2760/44170, JRC111068[c]

European Commission, An integrated Europe Union policy for the Arctic, Joint Communication to the European Union and the Council, 2016, available at https://cimr.eu/sites/cimr.met.no/files/documents/160427_joint-communica...

Emery, W. J., Fowler, C. W. & Maslanik, J. A. (1997) Satellite-derived maps of Arctic and Antarctic sea ice motion: 1988–1994. Geophys. Res. Lett. 24, 897–900.

Entekhabi, D. et al., (2008), The Soil Moisture Active/Passive Mission (SMAP), IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, Boston, MA, 2008, pp. III - 1-III - 4. doi: 10.1109/IGARSS.2008.4779267

Eppler, D.; Farmer, L.; Lohanick, A.; Anderson, M.; Cavalieri, D.; Comiso, J.; Glorsen, P.; Garrity, C.;  Grenfell, T.; Hallikainen, M.; et al. (1992), Passive microwave signatures of sea ice. In Microwave Remote Sensing of Sea  Ice, in Carsey, F.D., Ed.; American Geophysical Union: Washington, DC, USA, 1992; doi:10.1029/GM068p0047.

European Commision, An integrated European Union policy for the Arctic, Joint Communication to the European Parliament and the Council, available at https://cimr.eu/sites/cimr.met.no/files/documents/160427_joint-communica...

Freitas, S. C., I. Trigo, J.  Macedo, C. Barroso, R. Silva, and R Perdigao, (2013), Land Surface Temperature from multiple geostationary satellites. Int. J. Rem. Sens., Vol 34, 3051-3068.

Gaiser, P. W. et al., (2004), The WindSat spaceborne polarimetric microwave radiometer: sensor description and early orbit performance, in IEEE Transactions on Geoscience and Remote Sensing, vol. 42, no. 11, pp. 2347-2361, Nov. 2004. doi: 10.1109/TGRS.2004.836867

Garcia-Eidell, C., J. C. Comiso, E. Dinnat, and L. Brucker (2017), Satellite observed salinity distributions at high latitudes in the Northern Hemisphere: A comparison of four products, J. Geophys. Res. Oceans, 122, 7717–7736, doi:10.1002/2017JC013184.

Gentemann, C. L. ,T. Meissner, and F. J. Wentz, (2010), Accuracy of satellite sea surface temperatures at 7 and 11 GHz,” IEEE Trans. Geosci. Remote Sens., vol. 48, no. 3, pp. 1009–1018.

Girard-Ardhuin, F.; Ezraty, R. (2012), Enhanced Arctic Sea Ice Drift Estimation Merging Radiometer and Scatterometer Data. IEEE Trans. Geosci. Remote Sens., 50, 2639–2648.  

Grenfell, T. C., Barber, D. G., Fung, A. K., Gow, A. J., Jezek, K. C., Knapp, E. J., Nghiem, S. V., Onstott, R. G., Perovich, D. K., Roesler, C. S., Swift, C. T., and Tanis, F., (1998), Evolution of electromagnetic signatures of sea ice from initial formation to the establishment of thick first year ice, IEEE T. Geosci. Remote, 36, 1642–1654, 1998.

Grenfell, T. C., Cavalieri, D. J., Comiso, J. C., Drinkwater, M. R., Onstott, R. G., Rubinstein, I., Steffen, K., and Winebrenner, D. P., (1992), Considerations for microwave remote sensing of thin sea ice, in: Microwave Remote Sensing of Sea Ice, edited by: Carsey, F. D., American Geophysical Union, Washington, D.C., doi:10.1029/GM068p0291.

Grenfell, T. C., Cavalieri, D. J., Comiso, J. C., Drinkwater, M. R., Onstott, R. G., Rubinstein, I., Steffen, K., and Winebrenner, D. P.(1992), Considerations for microwave remote sensing of thin sea ice, in: Microwave Remote Sensing of Sea Ice, edited by: Carsey, F. D., American Geophysical Union, Washington, D.C., doi:10.1029/GM068p0291.

Guerreiro, K., Fleury, S., Zakharova, E., Kouraev, A., Rémy, F., and Maisongrande, P.,(2017), Comparison of CryoSat-2 and ENVISAT radar freeboard over Arctic sea ice: toward an improved Envisat freeboard retrieval, The Cryosphere, 11, 2059-2073, https://doi.org/10.5194/tc-11-2059-2017, 2017.

Gu, H and A. W. England, (2007), AMSR-E data resampling with near circular synthesized footprint shape and noise/reduction trade-off study, IEEE Tras. GeoSci and Rem. Sens, 45(10), pp. 3193-3203

Hallikainen, M., and P. Jolma (1992), Comparison of algorithms for retrieval of snow water equivalent from Nimbus-7 SMMR data in Finland, IEEE Trans. Geosci. Remote Sens., 30(1), 124–131, doi:10.1109/36.124222.

Heil, P., Fowler, C. W. & Lake, S. E. (2006), Antarctic sea-ice velocity as derived from SSM/I imagery. Ann. Glaciol. Ser. 44, 361–366.

Heygster, G., Huntemann, M., Ivanova, N., Saldo, R., and Pedersen, L. T. (2014), Response of passive microwave sea ice concentration algorithms to thin ice, Proceedings Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International, 13–18 July, Quebec City, QC, 3618–3621, doi:10.1109/IGARSS.2014.6947266.

Hilburton, H and F. J. Wentz, (2008), Inter-calibrated Passive Microwave Rain Products from the Unified Microwave Ocean Retrieval Algorithm (UMORA), J. Applied Met. And Climatology, 778-794, DOI: 10.1175/2007JAMC1635.1

Ivanova, N., Johannessen, O. M., Pedersen, L. T., and Tonboe, R. T., (2014), Retrieval of Arctic sea ice parameters by satellite passive microwave sensors: a comparison of eleven sea ice algorithms, IEEE T. Geosci. Remote, 52, 7233–7246, 2014.

Ivanova, N., Pedersen, L. T., Tonboe, R. T., Kern, S., Heygster, G., Lavergne, T., Sørensen, A., Saldo, R., Dybkjær, G., Brucker, L., and Shokr, M., (2015), Inter-comparison and evaluation of sea ice algorithms: towards further identification of challenges and optimal approach using passive microwave observations, The Cryosphere, 9, 1797-1817, https://doi.org/10.5194/tc-9-1797-2015.

JAXA, Japan Aerospace Exploration Agency (2005), AMSR-E Data Users Hand- book, 3rd ed., Saitama, Japan.

Kaefer, L. S and R. F. Harrington (1983), Radiometer Requirements for Earth-Observation Systems Using Large Space Antennas, NASA reference publication, NASA-RP-1101 19830020139, available from         https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19830020139.pdf

Kaleschke, L., Maaß, N., Haas, C., Hendricks, S., Heygster, G., and Tonboe, R. T., (2010), A sea-ice thickness retrieval model for 1.4 GHz radiometry and application to airborne measurements over low salinity sea-ice, The Cryosphere, 4, 583–592, doi:10.5194/tc-4- 583-2010, 2010.

Kaleschke, L., X. Tian-Kunze, N. Maaß, A. Beitsch, A. Wernecke, M. Miernecki, Gerd Müller, B. H. Fock, A. M.U. Gierisch, K. H. Schlünzen, T. Pohlmann, M. Dobrynin, S. Hendricks, J. Asseng, R. Gerdes, P. Jochmann, N. Reimer, J. Holfort, C. Melsheimer, G. Heygster, G. Spreen, S. Gerland, J. King, N. Skou, S. Schmidl Søbjærg, C. Haas, F. Richter, and T. Casal, (2016), SMOS sea ice product: Operational application and validation in the Barents Sea marginal ice zone, Rem. Sen. of Env., 180, 264-273, https://doi.org/10.1016/j.rse.2016.03.009.

Karvonen, J., (2014), Baltic Sea ice concentration estimation based on C-band dual-polarized SAR data, IEEE Trans. Geosci. Remote Sens., vol. 52, no. 9, pp. 5558–5566, doi: 10.1109/TGRS.2013.2290331.

Karvonen, J., (2017), Baltic Sea Ice Concentration Estimation Using SENTINEL-1 SAR and AMSR2 Microwave Radiometer Data, in IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 5, pp. 2871-2883.
doi: 10.1109/TGRS.2017.2655567

Kazumori, M., (2012), A retrieval algorithm of atmospheric water vapor and cloud liquid water for AMSR-E, Eur. J. Remote Sens., vol. 45 pp. 63–74, doi: 10.5721/EuJRS20124507.

Kern, S., Khvorostovsky, K., Skourup, H., Rinne, E., Parsakhoo, Z. S., Djepa, V., Wadhams, P., and Sandven, S., (2015), The impact of snow depth, snow density and ice density on sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise, The Cryosphere, 9, 37–52, doi:10.5194/tc-9-37-2015.

Kurtz, N.T., Farrell, S.L., Studinger, M., Galin, N., Harbeck, J.P., Lindsay, R., Onana, V.D., Panzer, B., Sonntag, J.G. (2013), Sea ice thickness, freeboard, and snow depth products from Operation IceBridge airborne data. Cryosphere 7:1035–1056. http://dx.doi.org/ 10.5194/tc-7-1035-2013.

Kwok, R., Schweiger, A., Rothrock, D. A., Pang, S. & Kottmeier, C. (1998), Sea ice motion from satellite passive microwave imagery assessed with ERS SAR and buoy motions. J. Geophys. Res. 103, 8191–8214.

Lavergne, T., (2016a), Low Resolution Sea Ice Drift Product User’s Manual, Ocean & Sea Ice SAF GBL LR SID — OSI-405-c, Version 1.8 — July 2016  available from http://osisaf.met.no/docs/

Lavergne, T., (2016b), Ocean & Sea Ice SAF Algorithm Theoretical Basis Document for the OSI SAF Low Resolution Sea Ice Drift Product GBL LR SID — OSI-405-c Version 1.3 — May 2016

Lavergne, T.; Eastwood, S.; Teffah, Z.; Schyberg, H.; Breivik, L.A. (2010), Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic. J. Geophys. Res. Oceans, doi:10.1029/2009JC005958.

Laxon, S.W.; Giles, K.A.; Ridout, A.L.; Wingham, D.J.; Willatt, R.; Cullen, R.; Kwok, R.; Schweiger, A.; Zhang, J.; Haas, C.; Hendricks, S.; Krishfield, R.; Kurtz, N.; Farrell S.; Davidson, M. (2013), CryoSat-2 estimates of Arctic sea ice thickness and volume. Geophys. Res. Lett., 40, 1-6. doi:10.1002/grl.50193

Long, D. G., (2017), Polar Applications of Spaceborne Scatterometers, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 5, pp. 2307-2320. doi: 10.1109/JSTARS.2016.2629418

Liu, Y and P. Minnett, (2016), Sampling errors in satellite-derived infrared sea-surface temperatures Part I: Global and Regional MODIS fields, Rem. Sens. Env., 177, 48-64, http://dx.doi.org/10.1016/j.rse.2016.02.026

Maass, N., Kaleschke, L., Tian-Kunze, X., Tonboe, R.T., (2015). Snow thickness retrieval from L-band brightness temperatures: a model comparison. Ann. Glaciol. 56 (69), 9–17.

Maeda, K., A. Shibata and K. Imaoka, (2011), Protection of 6–7 GHz band spaceborne microwave radiometer from interferences to derive sea surface temperature and others, IEEE International Geoscience and Remote Sensing Symposium, Vancouver, BC, 2011, pp. 4217-4220. doi: 10.1109/IGARSS.2011.6050161

Maeda, K., Y. Taniguchi and K. Imaoka, (2016), GCOM-W1 AMSR2 Level 1R Product: Dataset of Brightness Temperature Modified Using the Antenna Pattern Matching Technique, IEEE Transactions on Geoscience and Remote Sensing, VOL. 54, NO. 2.

Maekynen, M., Cheng, B., and Similae, M. (2013), On the accuracy of thin-ice thickness retrieval using MODIS thermal imagery over Arctic first-year ice, Ann. Glaciol., 62, 87–96, doi:10.3189/2013AoG62A166.

Markus, T., D. Cavalieri, A. Gasiewski, M. Klein, J. Maslanik, D. Powell, B. Stankov, J. Stroeve and M. Sturm (2006). Microwave Signatures of Snow on Sea Ice: Observations. IEEE Trans. Geosci. Remote Sens., 44, 3081-3090. doi:10.1109/TGRS.2006.883134

Meissner, T. and F. J. Wentz, (2012), The emissivity of the ocean surface between 6 and 90 GHz over a large range of wind speeds and earth incidence angles,” IEEE Trans. Geosci. Remote Sens., vol. 50, no. 8, pp. 3004–3026.

Meissner, T. and F. J. Wentz, (2016), Remote Sensing Systems SMAP Ocean Surface Salinities [Level 2C, Level 3 Running 8-day, Level 3 Monthly], Version 2.0 validated release. Remote Sensing Systems, Santa Rosa, CA, USA. Available online at www.remss.com/missions/smap

Meissner, T. and Wentz, F. J. (2012), The emissivity of the ocean surface between 6–90 GHz over a large range of wind speeds and Earth incidence angles, IEEE T. Geosci. Remote, 50, 3004–3026.

Meissner, T., F. J. Wentz, and D. Draper, (2011), GMI calibration algorithm and analysis theoretical basis document, version F,” Remote Sens. Syst., Santa Rosa, CA, USA, Tech. Rep. 111311.  

Meissner, T.. and F. Wentz, (2002), An updated analysis of the ocean surface wind direction signal in passive microwave brightness temperatures, IEEE Trans. Geosci. Remote Sens., vol. 40, no. 6, pp. 1230–1240.  

Meissner, T., L. Ricciardulli, and F.J. Wentz, (2017), Capability of the SMAP Mission to Measure Ocean Surface Winds in Storms. Bull. Amer. Meteor. Soc., 98, 1660–1677,https://doi.org/10.1175/BAMS-D-16-0052.1 

Meier, W. N., J. S. Stewart, Y. Liu, J. Key and J. A. Miller, (2017), Operational Implementation of Sea Ice Concentration Estimates From the AMSR2 Sensor," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 9, pp. 3904-3911. doi: 10.1109/JSTARS.2017.2693120

Mohammed, P. N., M. Aksoy, J. R. Piepmeier, J. T. Johnson and A. Bringer, (2016), SMAP L-Band Microwave Radiometer: RFI Mitigation Prelaunch Analysis and First Year On-Orbit Observations, in IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 10, pp. 6035-6047. doi: 10.1109/TGRS.2016.2580459

NASA, (2014), SMAP Handbook Soil Moisture Active Passive, Mapping Soil Moisture and freeze/Thaw from space, available from https://smap.jpl.nasa.gov/mission/description/ 

Naoki, K., Ukita, J., Nishio, F., Nakayama, M., Comiso, J. C., and Gasiewski, A., (2008), Thin sea ice thickness as inferred from passive microwave and in situ observations, J. Geophys. Res., 113, C02S16, doi:10.1029/2007JC004270.

Nielsen-Englyst, P. L., J.  Høyer, L. Toudal Pedersen, C. Gentemann, E. Alerskans, T. Block, C. Donlon, (2018) Optimal Estimation of Sea Surface Temperature from AMSR-E., Remote Sens., 10, 229.

Njoku, E. G., T. J. Jackson, V. Lakshmi, T. K. Chan and S. V. Nghiem, (2003), Soil moisture retrieval from AMSR-E, in IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 2, pp. 215-229, doi: 10.1109/TGRS.2002.808243

Olmedo, E., I. Taupier-Letage, A.  Turiel, and A. Alvera-Azcárate, (2018), Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis. Remote Sens., 10, 485.

Olmedo, E., J. Martínez, A. Turiel, J. Ballabrera-Poy, M. Portabella, (2017), Debiased non-Bayesian retrieval: A novel approach to SMOS Sea Surface Salinity, In Remote Sensing of Environment, Volume 193, 2017, Pages 103-126, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.02.023.

OSI-SAF, (2017), Improving the effective temperature estimation over sea ice using low frequency microwave radiometer data and Arctic buoys.

Pațilea, C., Heygster, G., Huntemann, M., and Spreen, G.: Combined SMAP/SMOS Thin Sea Ice Thickness Retrieval, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-168, in review, 2017.

Pearson, K. J., C. J. Merchant, O. Embury and C. Donlon, (2018), The Role of Advanced Microwave Scanning Radiometer 2 Channels Within an Optimal Estimation Scheme for Climate Data Records of Sea Surface Temperature, Remote Sens. 2018, 10, 90; doi:10.3390/rs10010090

Pedersen, L. T., R. Saldo, (2016), Sea Ice Concentration (SIC) Round Robin Data Package. Sea ice climate change initiative phase 2. Doc Ref: SICCI-RRDP-07-16, v. 1.4, May 07, available from http://www.esa-seaice-cci.org/.

Pulliainen, J. and M. Hallikainen, (2001), Retrieval of Regional Snow Water Equivalent from Space-Borne Passive Microwave Observations, In Remote Sensing of Environment, Volume 75, Issue 1, Pages 76-85, ISSN 0034-4257, https://doi.org/10.1016/S0034-4257(00)00157-7.

Rasmussen, E., and J. Turner, Eds., 2003: Polar Lows. Cambridge University Press, 612 pp.

Reul, N., J. Tenerelli, J. Boutin, B. Chapron, F. Paul, E. Brion, F. Gaillard, and O. Archer (2012a), Overview of the first SMOS sea surface salinity products. Part I: Quality assessment for the second half of 2010, IEEE Trans. Geosci. Remote Sens., 50(5), 1636–1647, doi:10.1109/ TGRS.2012.2188408.

Reul, N., B. Chapron, E. Zabolotskikh, C. Donlon, Y. Quilfen, S. Guimbard, and J. F. Piolle, (2016), A revised L-band radio-brightness sensitivity to extreme winds under tropical cyclones: The five year SMOS-storm database. Remote Sens. Environ., 180, 274–291, doi:https://doi.org/10.1016/j.rse.2016.03.011.

Reul, N., J. Tenerelli, B. Chapron, D. Vandemark, Y. Quilfen, and Y. Kerr (2012b), SMOS satellite L-band radiometer: A new capability for ocean surface remote sensing in hurricanes, J. Geophys. Res., 117, C02006, doi:10.1029/2011JC007474.

Reul, N., B. Chapron, E. Zabolotskikh, C. Donlon, A. Mouche, J. Tenerelli, F. Collard, J.F. Piolle, A. Fore, S. Yueh, J. Cotton, P. Francis, Y. Quilfen, and V. Kudryavtsev, 2017:A New Generation of Tropical Cyclone Size Measurements from Space. Bull. Amer. Meteor. Soc., 98, 2367–2385, https://doi.org/10.1175/BAMS-D-15-00291.1 

Richter, F., M. Drusch, L. Kaleschke, N. Maaß, X. Tian-Kunze, and S. Mecklenburg, (2018), Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models, The Cryosphere, 12, 921-933, https://doi.org/10.5194/tc-12-921-2018.

Sakov, P., Counillon, F., Bertino, L., Lisæter, K. A., Oke, P. R., and Korablev, A. (2012), TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic, Ocean Sci., 8, 633-656, https://doi.org/10.5194/os-8-633-2012.

Scott, K. A. , E. Li and A. Wong, (2014), Sea Ice Surface Temperature Estimation Using MODIS and AMSR-E Data Within a Guided Variational Model Along the Labrador Coast," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 9, pp. 3685-3694, doi: 10.1109/JSTARS.2013.2292795

Smirnova, J.E., Zabolotskikh, E.V., Bobylev, L.P. et al. (2016), Statistical characteristics of polar lows over the Nordic Seas based on satellite passive microwave data, Izv. Atmos. Ocean. Phys. 52: 1128. https://doi.org/10.1134/S0001433816090255

Spreen, G., L. Kaleschke, and G. Heygster (2008), Sea ice remote sensing using AMSR-E 89-GHz channels, J. Geophys. Res., 113, C02S03, doi:10.1029/2005JC003384.

Soldo, Y. , D. M. Le Vine, P. de Matthaeis and P. Richaume, (2017), L-Band RFI Detected by SMOS and Aquarius, in IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 7, pp. 4220-4235, July 2017. doi: 10.1109/TGRS.2017.2690406

Svendsen, E., Matzler, C., and Grenfell, Th. (1987), A model for retrieving total sea ice concentration from a spaceborne dual-polarized passive microwave instrument operating near 90 GHz, Int. J. Remote Sens., 8, 1479–1487.

Svendsen, E., K. Kloster, B. Farrelly, O. M. Johannessen, J. A. Johannessen, W. J. Campbell, P. Gloersen, D. Cavalieri, and C. Matzler (1983), Norwegian remote sensing experiment: Evaluation of the NIMBUS 7 Scanning Multichannel Microwave Radiometer for sea ice research, J. Geophys. Res., 88(C5), 2781 – 2791.

Tsutsui, H.; Maeda, T. (2017), Possibility of Estimating Seasonal Snow Depth Based Solely on Passive Microwave Remote Sensing on the Greenland Ice Sheet in Spring. Remote Sens., 9, 523.

UNESCO, (1985),  The international system of units (SI) in oceanography, UNESCO Technical Papers No. 45, IAPSO Pub. Sci. No. 32, Paris, France.

Vihma, T., (2014), Effects of Arctic sea ice decline on weather and climate: A review, Surveys Geophys., vol. 35, no. 5, pp. 1175–1214.  

Wagner, W. G. Lemoine, and H. Rott, (1999), A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data. Rem. Sens. of Env., vol.70, 191-207.

Walker, N.; Partington, K.; Van Woert, M.; Street, T. (2006), Arctic sea ice type and concentration mapping using  passive and active microwave sensors. IEEE Trans. Geosci. Remote Sens. 44, 3574–3584.  

Warren, S. G., Rigor, I. G., Untersteiner, N., Radionov, V. F., Bryazgin, N. N., Aleksandrov, Y. I., and Colony, R. (1999), Snow depth on Arctic sea ice, J. Climate, 12, 1814–1829.

Wentz , F. J. and T. Meissner, (2000), Algorithm theoretical basis document (ATBD) version 2 AMSR ocean algorithm, Remote Sens. Syst., Santa Rosa, CA, USA, Tech. Rep. 121599A-1.  

Wentz F. J. and T. Meissner, (2016), Atmospheric absorption model for dry air and water vapor at microwave frequencies below 100 GHz derived from spaceborne radiometer observations, Radio Sci., vol. 51, no. 5, pp. 381–391.  

Wentz F. J. and T. Meissner, (2007), Supplement 1: Algorithm theoretical basis document for AMSR-E ocean algorithms, Remote Sens. Syst., Santa Rosa, CA, USA, Tech. Rep. 051707.  

Wentz, F. J., (1997), A well-calibrated ocean algorithm for special sensor microwave/imager, J. Geophys. Res., vol. 102, no. C4, pp. 8703–8718.  

Wentz, F. J., C. Gentemann, D. Smith, and D. Chelton, (2000), Satellite measurements of sea surface temperature through clouds, Science, vol. 288, no. 5467, pp. 847–850, May 2000.

Wiebe, H., G. Heygster and          L. Meyer-Lerbs 2008: Geolocation of AMSR-E Data. IEEE Trans. Geosci. and          Remote Sensing 46(10), p. 3098-3103, doi:10.1109/TGRS.2008.919272.

  • Wilheit, T.T. and A. T. C. Chang, (1980), An algorithm for retrieval of ocean surface and atmospheric parameters from the observations of the scanning multichannel microwave radiometer. Radio Sci. 15, 525–544.  

WMO, (2017), Sea-Ice Information Services in the World, Edition 2017 (last revision 2017-08-02), WMO-No. 574 available from http://www.jcomm.info/index.php?option=com_oe&task=viewDocumentRecord&docID=9607 

Xie, J., Counillon, F., Bertino, L., Tian-Kunze, X., and Kaleschke, L. (2016), Benefits of assimilating thin sea ice thickness from SMOS into the TOPAZ system, The Cryosphere, 10, 2745-2761, https://doi.org/10.5194/tc-10-2745-2016, 2016.

Ye, Y., M. Shokr, G. Heygster, and G. Spreen, (2016),Improving Multiyear Sea Ice Concentration Estimates with Sea Ice Drift. Remote Sens. 2016, 8, 397.

Ye Y. and G. Heygster, (2015), Arctic Multiyear Ice Concentration Retrieval from SSM/I Data Using the NASA Team Algorithm with Dynamic Tie Points. In: Lohmann G., Meggers H., Unnithan V., Wolf-Gladrow D., Notholt J., Bracher A. (eds) Towards an Interdisciplinary Approach in Earth System Science. Springer Earth System Sciences. Springer, Cham., https://doi.org/10.1007/978-3-319-13865-7_12

Yueh, S. H., R. West, W. J. Wilson, F. K. Li, E. G. Njoku and Y. Rahmat-Samii, (2001), Error sources and feasibility for microwave remote sensing of ocean surface salinity, in IEEE Transactions on Geoscience and Remote Sensing, vol. 39, no. 5, pp. 1049-1060,. doi: 10.1109/36.921423

Yueh, S., W. Tang, A. Fore, A. Hayashi, Y. T. Song, and G. Lagerloef (2014), Aquarius geophysical model function and combined active passive algorithm for ocean surface salinity and wind retrieval, J. Geophys. Res. Oceans, 119, 5360–5379, doi:10.1002/2014JC009939.

Zabolotskikh, E., G. Irina, A. Myasoedov and B. Chapron, (2016), Detection and study of the polar lows over the arctic sea ice edge, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, 2016, pp. 7705-7707.
doi: 10.1109/IGARSS.2016.7731009

Zabolotskikh, E. and B. Chapron, (2017), Improvements in Atmospheric Water Vapor Content Retrievals Over Open Oceans From Satellite Passive Microwave Radiometers, in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 7, pp. 3125-3133. doi: 10.1109/JSTARS.2017.2671920

Zheng, J., T. Geldsetzer, and J. Yackel, (2017), Snow thickness estimation on first-year sea ice using microwave and optical remote sensing with melt modelling, In Remote Sensing of Environment, Volume 199, 2017, Pages 321-332, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.06.038.

Zhao, E. C. Gao, X. Jiang, and Z. Liu, (2017), Land surface temperature retrieval from AMSR-E passive microwave data, Opt. Express, 25, A940-A952.

 

 

[a]This is [CMEMS-1] from the MRD

[b]This is [PEG-1] from the MRD

[c]This is [PEG-2] from the MRD