Articles | Volume 6, issue 1
https://doi.org/10.5194/gi-6-39-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gi-6-39-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
01 Feb 2017
Research article |
| 01 Feb 2017
Radio-frequency interference mitigating hyperspectral L-band radiometer
Climate Research Division, Environment and Climate Change Canada,
Toronto, Ontario, M3H 5T4, Canada
Alexandre Roy
Centre d'Applications et de Recherches en
Télédétection, Université de Sherbrooke, Sherbrooke,
Québec, J1K 2R1, Canada
Frederick Solheim
Dakota Ridge Research and Development, Boulder, Colorado, 80303,
USA
Chris Derksen
Climate Research Division, Environment and Climate Change Canada,
Toronto, Ontario, M3H 5T4, Canada
Tom Watts
Department of Geography, Northumbria University, Newcastle upon
Tyne, NE1 8ST, UK
Alain Royer
Centre d'Applications et de Recherches en
Télédétection, Université de Sherbrooke, Sherbrooke,
Québec, J1K 2R1, Canada
Anne Walker
Climate Research Division, Environment and Climate Change Canada,
Toronto, Ontario, M3H 5T4, Canada
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Victoria R. Dutch, Nick Rutter, Leanne Wake, Melody Sandells, Chris Derksen, Branden Walker, Gabriel Hould Gosselin, Oliver Sonnentag, Richard Essery, Richard Kelly, Phillip Marsh, Joshua King, and Julia Boike
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Leung Tsang, Michael Durand, Chris Derksen, Ana P. Barros, Do-Hyuk Kang, Hans Lievens, Hans-Peter Marshall, Jiyue Zhu, Joel Johnson, Joshua King, Juha Lemmetyinen, Melody Sandells, Nick Rutter, Paul Siqueira, Anne Nolin, Batu Osmanoglu, Carrie Vuyovich, Edward Kim, Drew Taylor, Ioanna Merkouriadi, Ludovic Brucker, Mahdi Navari, Marie Dumont, Richard Kelly, Rhae Sung Kim, Tien-Hao Liao, Firoz Borah, and Xiaolan Xu
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Physical measurements of snow on sea ice are sparse, making it difficulty to evaluate satellite estimates or model representations. Here, we introduce new measurements of snow properties on sea ice to better understand variability at distances less than 200 m. Our work shows that similarities in the snow structure are found at longer distances on younger ice than older ice.
Lawrence Mudryk, María Santolaria-Otín, Gerhard Krinner, Martin Ménégoz, Chris Derksen, Claire Brutel-Vuilmet, Mike Brady, and Richard Essery
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Existing stand-alone passive microwave SWE products have markedly different climatological SWE patterns compared to reanalysis-based datasets. The AMSR-E SWE has low spatial and temporal correlations with the four reanalysis-based products evaluated and GlobSnow and perform poorly in comparisons with snow transect data from Finland, Russia, and Canada. There is better agreement with in situ data when multiple SWE products, excluding the stand-alone passive microwave SWE products, are combined.
Nick Rutter, Melody J. Sandells, Chris Derksen, Joshua King, Peter Toose, Leanne Wake, Tom Watts, Richard Essery, Alexandre Roy, Alain Royer, Philip Marsh, Chris Larsen, and Matthew Sturm
The Cryosphere, 13, 3045–3059, https://doi.org/10.5194/tc-13-3045-2019, https://doi.org/10.5194/tc-13-3045-2019, 2019
Short summary
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Impact of natural variability in Arctic tundra snow microstructural characteristics on the capacity to estimate snow water equivalent (SWE) from Ku-band radar was assessed. Median values of metrics quantifying snow microstructure adequately characterise differences between snowpack layers. Optimal estimates of SWE required microstructural values slightly less than the measured median but tolerated natural variability for accurate estimation of SWE in shallow snowpacks.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
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This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the EASE-Grid 2.0 with a resolution of 36 km. To evaluate the product, we compared it with the resampled 37 GHz FT Earth Science Data Record during the overlapping period between 2011 and 2014. The FT-AP ensures, with the SMAP mission that is still in operation, an L-band passive FT monitoring continuum with NASA’s space-borne radiometers, for a period beginning in August 2011.
Fanny Larue, Alain Royer, Danielle De Sève, Alexandre Roy, and Emmanuel Cosme
Hydrol. Earth Syst. Sci., 22, 5711–5734, https://doi.org/10.5194/hess-22-5711-2018, https://doi.org/10.5194/hess-22-5711-2018, 2018
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A data assimilation scheme was developed to improve snow water equivalent (SWE) simulations by updating meteorological forcings and snowpack states using passive microwave satellite observations. A chain of models was first calibrated to simulate satellite observations over northeastern Canada. The assimilation was then validated over 12 stations where daily SWE measurements were acquired during 4 winters (2012–2016). The overall SWE bias is reduced by 68 % compared to original SWE simulations.
Alex Mavrovic, Alexandre Roy, Alain Royer, Bilal Filali, François Boone, Christoforos Pappas, and Oliver Sonnentag
Geosci. Instrum. Method. Data Syst., 7, 195–208, https://doi.org/10.5194/gi-7-195-2018, https://doi.org/10.5194/gi-7-195-2018, 2018
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To improve microwave satellite and airborne observation products in forest environments, a precise and reliable estimation of the permittivity of trees is required. We developed a probe suitable to measure the permittivity of tree trunks at L band in the field. The system is easily transportable in the field, low energy consuming, operational at low temperatures and weatherproof. The permittivity of seven tree species in both frozen and thawed states was measured, showing important contrast.
Paul J. Kushner, Lawrence R. Mudryk, William Merryfield, Jaison T. Ambadan, Aaron Berg, Adéline Bichet, Ross Brown, Chris Derksen, Stephen J. Déry, Arlan Dirkson, Greg Flato, Christopher G. Fletcher, John C. Fyfe, Nathan Gillett, Christian Haas, Stephen Howell, Frédéric Laliberté, Kelly McCusker, Michael Sigmond, Reinel Sospedra-Alfonso, Neil F. Tandon, Chad Thackeray, Bruno Tremblay, and Francis W. Zwiers
The Cryosphere, 12, 1137–1156, https://doi.org/10.5194/tc-12-1137-2018, https://doi.org/10.5194/tc-12-1137-2018, 2018
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Here, the Canadian research network CanSISE uses state-of-the-art observations of snow and sea ice to assess how Canada's climate model and climate prediction systems capture variability in snow, sea ice, and related climate parameters. We find that the system performs well, accounting for observational uncertainty (especially for snow), model uncertainty, and chaotic climate variability. Even for variables like sea ice, where improvement is needed, useful prediction tools can be developed.
Lawrence R. Mudryk, Chris Derksen, Stephen Howell, Fred Laliberté, Chad Thackeray, Reinel Sospedra-Alfonso, Vincent Vionnet, Paul J. Kushner, and Ross Brown
The Cryosphere, 12, 1157–1176, https://doi.org/10.5194/tc-12-1157-2018, https://doi.org/10.5194/tc-12-1157-2018, 2018
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This paper presents changes in both snow and sea ice that have occurred over Canada during the recent past and shows climate model estimates for future changes expected to occur by the year 2050. The historical changes of snow and sea ice are generally coherent and consistent with the regional history of temperature and precipitation changes. It is expected that snow and sea ice will continue to decrease in the future, declining by an additional 15–30 % from present day values by the year 2050.
Yann Blanchard, Alain Royer, Norman T. O'Neill, David D. Turner, and Edwin W. Eloranta
Atmos. Meas. Tech., 10, 2129–2147, https://doi.org/10.5194/amt-10-2129-2017, https://doi.org/10.5194/amt-10-2129-2017, 2017
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Multiband thermal measurements of zenith sky radiance were used in a retrieval algorithm, to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. The retrieval technique was validated using a synergy lidar and radar data. Inversions were performed across three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of thin ice clouds.
Libo Wang, Peter Toose, Ross Brown, and Chris Derksen
The Cryosphere, 10, 2589–2602, https://doi.org/10.5194/tc-10-2589-2016, https://doi.org/10.5194/tc-10-2589-2016, 2016
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The conventional wisdom is that Arctic warming will result in an increase in the frequency of winter melt events. However, results in this study show little evidence of trends in winter melt frequency over 1988–2013 period. The frequency of winter melt events is strongly influenced by the selection of the start and end dates of winter period, and a fixed-window method for analyzing winter melt events is observed to generate false increasing trends from a shift in the timing of snow cover season.
Tom Watts, Nick Rutter, Peter Toose, Chris Derksen, Melody Sandells, and John Woodward
The Cryosphere, 10, 2069–2074, https://doi.org/10.5194/tc-10-2069-2016, https://doi.org/10.5194/tc-10-2069-2016, 2016
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Ice layers in snowpacks introduce uncertainty in satellite-derived estimates of snow water equivalent, have ecological impacts on plants and animals, and change the thermal and vapour transport properties of the snowpack. Here we present a new field method for measuring the density of ice layers. The method was used in the Arctic and mid-latitudes; the mean measured ice layer density was significantly higher than values typically used in the literature.
Bart van den Hurk, Hyungjun Kim, Gerhard Krinner, Sonia I. Seneviratne, Chris Derksen, Taikan Oki, Hervé Douville, Jeanne Colin, Agnès Ducharne, Frederique Cheruy, Nicholas Viovy, Michael J. Puma, Yoshihide Wada, Weiping Li, Binghao Jia, Andrea Alessandri, Dave M. Lawrence, Graham P. Weedon, Richard Ellis, Stefan Hagemann, Jiafu Mao, Mark G. Flanner, Matteo Zampieri, Stefano Materia, Rachel M. Law, and Justin Sheffield
Geosci. Model Dev., 9, 2809–2832, https://doi.org/10.5194/gmd-9-2809-2016, https://doi.org/10.5194/gmd-9-2809-2016, 2016
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This manuscript describes the setup of the CMIP6 project Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).
Henna-Reetta Hannula, Juha Lemmetyinen, Anna Kontu, Chris Derksen, and Jouni Pulliainen
Geosci. Instrum. Method. Data Syst., 5, 347–363, https://doi.org/10.5194/gi-5-347-2016, https://doi.org/10.5194/gi-5-347-2016, 2016
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The paper described an extensive in situ data set of bulk snow depth, snow water equivalent, and snow density collected as a support of SnowSAR-2 airborne campaign in northern Finland. The spatial and temporal variability of these snow properties was analyzed in different land cover types. The success of the chosen measurement protocol to provide an accurate reference for the simultaneous SAR data products was analyzed in the context of spatial scale, sample size, and uncertainty.
Stephen E. L. Howell, Frédéric Laliberté, Ron Kwok, Chris Derksen, and Joshua King
The Cryosphere, 10, 1463–1475, https://doi.org/10.5194/tc-10-1463-2016, https://doi.org/10.5194/tc-10-1463-2016, 2016
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The Canadian Ice Service record of observed landfast ice and snow thickness represents one of the longest in the Arctic that spans over 5 decades. We analyze this record to report on long-term trends and variability of ice and snow thickness within the Canadian Arctic Archipelago (CAA). Results indicate a thinning of ice at several sites in the CAA. State-of-the-art climate models still have difficultly capturing observed ice thickness values in the CAA and should be used with caution.
Alexandre Roy, Alain Royer, Olivier St-Jean-Rondeau, Benoit Montpetit, Ghislain Picard, Alex Mavrovic, Nicolas Marchand, and Alexandre Langlois
The Cryosphere, 10, 623–638, https://doi.org/10.5194/tc-10-623-2016, https://doi.org/10.5194/tc-10-623-2016, 2016
C. Papasodoro, E. Berthier, A. Royer, C. Zdanowicz, and A. Langlois
The Cryosphere, 9, 1535–1550, https://doi.org/10.5194/tc-9-1535-2015, https://doi.org/10.5194/tc-9-1535-2015, 2015
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Located at the far south (~62.5° N) of the Canadian Arctic, Grinnell and Terra Nivea Ice Caps are good climate proxies in this scarce data region. Multiple data sets (in situ, airborne and spaceborne) reveal changes in area, elevation and mass over the past 62 years. Ice wastage sharply accelerated during the last decade for both ice caps, as illustrated by the strongly negative mass balance of Terra Nivea over 2007-2014 (-1.77 ± 0.36 m a-1 w.e.). Possible climatic drivers are also discussed.
G. Picard, A. Royer, L. Arnaud, and M. Fily
The Cryosphere, 8, 1105–1119, https://doi.org/10.5194/tc-8-1105-2014, https://doi.org/10.5194/tc-8-1105-2014, 2014
S. E. L. Howell, T. Wohlleben, A. Komarov, L. Pizzolato, and C. Derksen
The Cryosphere, 7, 1753–1768, https://doi.org/10.5194/tc-7-1753-2013, https://doi.org/10.5194/tc-7-1753-2013, 2013
G. Picard, L. Brucker, A. Roy, F. Dupont, M. Fily, A. Royer, and C. Harlow
Geosci. Model Dev., 6, 1061–1078, https://doi.org/10.5194/gmd-6-1061-2013, https://doi.org/10.5194/gmd-6-1061-2013, 2013
A. Roy, A. Royer, B. Montpetit, P. A. Bartlett, and A. Langlois
The Cryosphere, 7, 961–975, https://doi.org/10.5194/tc-7-961-2013, https://doi.org/10.5194/tc-7-961-2013, 2013
Related subject area
Microwave
Dielectric characterization of vegetation at L band using an open-ended coaxial probe
Time series analysis of ground-based microwave measurements at K- and V-bands to detect temporal changes in water vapor and temperature profiles
Application of ground-penetrating radar technique to evaluate the waterfront location in hardened concrete
Alex Mavrovic, Alexandre Roy, Alain Royer, Bilal Filali, François Boone, Christoforos Pappas, and Oliver Sonnentag
Geosci. Instrum. Method. Data Syst., 7, 195–208, https://doi.org/10.5194/gi-7-195-2018, https://doi.org/10.5194/gi-7-195-2018, 2018
Short summary
Short summary
To improve microwave satellite and airborne observation products in forest environments, a precise and reliable estimation of the permittivity of trees is required. We developed a probe suitable to measure the permittivity of tree trunks at L band in the field. The system is easily transportable in the field, low energy consuming, operational at low temperatures and weatherproof. The permittivity of seven tree species in both frozen and thawed states was measured, showing important contrast.
Sibananda Panda, Swaroop Sahoo, and Govindan Pandithurai
Geosci. Instrum. Method. Data Syst., 6, 15–26, https://doi.org/10.5194/gi-6-15-2017, https://doi.org/10.5194/gi-6-15-2017, 2017
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The focus of the paper is estimating profiles of water vapor and temperature with high accuracy from microwave radiometer measurements, performed for the month of August 2011 as part of the Integrated Ground Campaign during the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX-IGOC). To improve the accuracy of retrieved profiles Bayesian optimal estimation has been used along with optimized background data set.
Isabel Rodríguez-Abad, Gilles Klysz, Rosa Martínez-Sala, Jean Paul Balayssac, and Jesús Mené-Aparicio
Geosci. Instrum. Method. Data Syst., 5, 567–574, https://doi.org/10.5194/gi-5-567-2016, https://doi.org/10.5194/gi-5-567-2016, 2016
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When assessing concrete structures durability, the study of the water penetration is critical, because almost all deterioration reactions require the presence of water. Due to the nondestructive nature of ground-penetrating radar (GPR) technique, the objective of this study is, firstly, to assess water penetration depths in concrete from GPR wave parameters. Secondly, a procedure was developed to be able to determine, from GPR signals, the location of waterfront depths.
Cited articles
Anterrieu, E. and Khazâal, A.: One year of RFI detection and quantification with L1a signals provided by SMOS reference radiometers, Int. Geosci. Remote Sens., 2245–2248, 2011.
Aksoy, M. and Johnson, J. T.: A study of SMOS RFI over North America, Int. Geosci. Remote Sens., 10, 515–519, 2013.
Delwart, S. Bouzinac, C., Wursteisen, P., Berger, M., Drinkwater, M., Martin-Neira, M., and Kerr, Y.: SMOS Validation and the COSMOS campaigns, Int. Geosci. Remote Sens., 46, 695–704, 2008.
Delahaye, J.-Y., Golé, P., and Waldteufel, P.: Calibration error of L-band sky-looking ground-based radiometers, Radio Sci., 37, 11-1–11-11, 2002.
Entekhabi, D., Yueh, S., O'Neill, P. E., Wood, E. F., Njoku, E. G., Entin, J. K., and Kellogg, K. H.: The NASA Soil Moisture Active Passive (SMAP) Mission Status and Early Results, Geophys. Res. Abstr., EGU2015-5973, EGU General Assembly 2015, Vienna, Austria, 2015.
Fanise, P., Pardé, M., Zribi, M., Dechambre, M., and Caudoux, C.: Analysis of RFI identification and mitigation in CAROLS radiometer data using a hardware spectrum analyser, Sensors, 11, 3037–3050. 2011.
Forte, G. F., Tarongi, J. M., and Camps, A.: Hardware implementation of a wavelet-based radio frequency interference mitigation algorithm for microwave radiometers, Int. Geosci. Remote Sens., 2241–2244, 2011.
Hallikainen, M., Kainulainen, J., Seppanen, J., Hakkarainen, A., and Rautiainen, K.: Studies of radio frequency interference at L-band using an airborne 2-D interferometric radiometer, Int. Geosci. Remote Sen., 2490–2491, 2010.
Guner, B., Johnson, J. T., and Niamsuwan, N.: Time and frequency blanking for radio-frequency interference mitigation in microwave radiometry, IEEE T. Geosci. Remote, 45, 3672–3679, 2007.
ITU: No. 5.340 of Radio Regulations (RR) of the International Telecommunications Union – Radiocommunications sector (ITU-R), Article 5, Radio Regulations, Vol. 1, Edition of 2012, available at: https://www.itu.int/pub/R-REG-RR-2012 (last access: 11 October 2016), 2012.
Kaleschke, L., Tian-Kunze, X., Maaß, N., Mäkynen, M., and Drusch, M.: Sea ice thickness retrieval from SMOS brightness temperatures during the Arctic freeze-up period, Geophys. Res. Lett., 39, L05501, https://doi.org/10.1029/2012GL050916, 2012.
Kaleschke, L., Tian-Kunze, X., Maaß, N., Beitsch, A., Wernecke, A., Miernecki, M., Müller, G., Fock, B. H., Gierisch, A. M., Schlünzen, K. H., and Pohlmann, T.: SMOS sea ice product: Operational application and validation in the Barents Sea marginal ice zone, Remote Sens. Environ., 180, 264–273, 2016.
Kerr, Y. H., Waldteufel, P., Wigneron, J. P., Delwart, S., Cabot, F. O., Boutin, J., Escorihuela, M. J., Font, J., Reul, N., Gruhier, C., and Juglea, S. E.: The SMOS mission: New tool for monitoring key elements of the global water cycle, IEEE Proc., 98, 666–687, 2010.
Khazâal, A., Cabot, F., Anterrieu, E., and Soldo, Y.: A kurtosis-based approach to detect RFI in SMOS image reconstruction data processor, IEEE T. Geosci. Remote Sens., 52, 7038–7047, 2014.
Lagerloef, G., de Charon, A., and Lindstrom, E.: Ocean salinity and the Aquarius/SAC-D mission: A new frontier in ocean remote sensing, Mar. Technol. Soc. J., 47, 26–30, 2013.
Lemmetyinen, J., Schwank, M., Rautiainen, K., Parkkinen, T., Mätzler, C., Wiesmann, A., Wegmüller, U., Derksen, C., Toose, P., Roy, A., and Pulliainen, J.: Snow density and ground permittivity retrieved from L-Band radiometry: application to experimental data, Remote Sens. Environ., 180, 377–391, 2016.
Le Vine, D. M.: ESTAR experience with RFI at L-band and implications for future passive microwave remote sensing from space, Int. Geosci. Remote Sens., 2, 847–849, 2002.
Le Vine, D. M., Abraham, S., Kerr, Y., Wilson, W. J., and Skou, N.: Comparison of Model Prediction With Measurements of Galactic Background Noise at L-Band, IEEE T. Geosci. Remote, 43, 2018–2023, 2005.
Le Vine, D. M., de Matthaeis, P., Ruf, C. S., and Chen, D. D.: Aquarius RFI detection and mitigation algorithm: Assessment and examples, IEEE T. Geosci. Remote, 52, 4574–4584, 2014.
Misra, S., Mohammed, P. N., Güner, B., Ruf, C. S., Piepmeier, J. R., and Johnson, J. T.: Microwave radiometer radio-frequency interference detection algorithms: A comparative study, IEEE T. Geosci. Remote, 47, 3742–3754, 2009.
Misra, S., Johnson, J., Aksoy, M., Peng, J., Bradley, D., O'Dwyer, I., Padmanabhan, S., Dawson, D., Chazanoff, S., Latham, B., and Gaier, T.: SMAP RFI mitigation algorithm performance characterization using airborne high-rate direct-sampled SMAPVEX 2012 data, Int. Geosci. Remote Sens., 41–44, 2013.
O'Haver, T.: Software for peak finding and measurement, in: A Pragmatic Introduction to Signal Processing with application in scientific measurement, 1–142, available at: https://terpconnect.umd.edu/~toh/spectrum/IntroToSignalProcessing.pdf (last access: 3 November 2016), 2016.
Oliva, R., Daganzo, E., Richaume, P., Kerr, Y., Cabot, F., Soldo, Y., Anterrieu, E., Reul, N., Gutierrez, A., Barbosa, J., and Lopes, G.: Status of Radio Frequency Interference (RFI) in the 1400–1427 MHz passive band based on six years of SMOS mission, Remote Sens. Environ., 180, 64–75, 2016
Pardé, M., Zribi, M., Fanise, P., and Dechambre, M.: Analysis of RFI issue using the CAROLS L-band experiment, IEEE T. Geosci. Remote, 49, 1063–1070, 2011.
Pellarin, T., Mialon, A., Biron, R., Coulaud, C., Gibon, F., Ferr, Y., Lafaysse, M., Mercier, B., Morin, S., Redor, I., Schwank, M., and Völksch, I.: Three years of L-band brightness temperature measurements in a mountainous area: Topography, vegetation and snowmelt issues, Remote Sens. Environ., 180, 85–98, 2016.
Piepmeier, J. R., Johnson, J. T., Mohammed, P. N., Bradley, D., Ruf, C., Aksoy, M., Garcia, R., Hudson, D., Miles, L., and Wong, M.: Radio-frequency interference mitigation for the soil moisture active passive microwave radiometer, IEEE T. Geosci. Remote, 52, 761–775, 2014.
Rautiainen, K., Kainulainen, J., Auer, T., Pihlflyckt, J., Kettunen, J., and Hallikainen, M. T.: Helsinki University of Technology L-band airborne synthetic aperture radiometer, IEEE T. Geosci. Remote, 46, 717–726, 2008.
Rautiainen, K., Lemmetyinen, J., Schwank, M., Kontu, A., Ménard, C. B., Mätzler, C., Drusch, M., Wiesmann, A., Ikonen, J., and Pulliainen, J.: Detection of soil freezing from L-band passive microwave observations, Remote Sens. Environ., 147, 206–218, 2014.
Rautiainen, K., Parkkinen, T., Lemmetyinen, J., Schwank, M., Wiesmann, A., Ikonen, J., Derksen, C., Davydov, S., Davydova, A., Boike, J., and Langer, M.: SMOS prototype algorithm for detecting autumn soil freezing, Remote Sens. Environ., 180, 346–360, 2016.
Roy, A., Royer, A., Derksen, C., Brucker, L., Langlois, A., Mialon, A., and Kerr, Y. H.: Evaluation of Spaceborne L-Band Radiometer Measurements for Terrestrial Freeze/Thaw Retrievals in Canada, IEEE J. Sel. Top. Appl., 8, 4442–4459, 2015.
Roy, A., Toose, P., Williamson, M., Rowlandson, T., Derksen, C., Royer, A., Berg, A., Lemmetyinen, J., and Arnold, L.: Response of L-Band brightness temperature to freeze/thaw and snow dynamics in a prairie environment, Remote Sens. Environ., 191, 67–80, 2017.
Schwank, M., Mätzler, C., Wiesmann, A., Wegmüller, U., Pulliainen, J., Lemmetyinen, J., and Drusch, M.: Snow density and ground permittivity retrieved from L-band radiometry: A synthetic analysis, IEEE J. Sel. Top. Appl., 8, 3833–3845, 2015.
Skou, N., Misra, S., Balling, J. E., Kristensen, S. S., and Sobjaerg, S. S.: L-band RFI as experienced during airborne campaigns in preparation for SMOS, IEEE T. Geosci. Remote, 48, 1398–1407, 2010.
Short summary
Radio-frequency interference (RFI) can significantly contaminate the measured radiometric signal of current spaceborne L-band passive microwave radiometers used for monitoring essential climate variables. A 385-channel hyperspectral L-band radiometer system was designed with the means to quantify the strength and type of RFI. The compact design makes it ideal for mounting on both surface and airborne platforms to be used for calibrating and validating measurement from spaceborne sensors.
Radio-frequency interference (RFI) can significantly contaminate the measured radiometric signal...
