Articles | Volume 14, issue 11
https://doi.org/10.5194/amt-14-7069-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-7069-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Ground mobile observation system for measuring multisurface microwave emissivity
Wenying He
CORRESPONDING AUTHOR
Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Hongbin Chen
CORRESPONDING AUTHOR
Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Yuejian Xuan
Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, China
Jun Li
Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, China
Minzheng Duan
Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Weidong Nan
Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, China
Xianghe Observatory of Whole Atmosphere, Institute of Atmospheric Physics, Chinese Academy of Sciences,Xianghe 065400, China
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Cited articles
Calvet, J. C., Wigneron, J. P., Chanzy, A., Raju, S., and Laguerre, L.:
Microwave dielectric proporeties of a silt-loam at high frequencies, IEEE T. Geosci. Remote., 33, 634–642, https://doi.org/10.1109/36.387579, 1995.
Fung, A. K.: Microwave Scattering and Emission Models and Their Applications, Artech House Publishers, Norwood, MA, ISBN 100890065233, 1994.
Hewison, T. J.: Airborne measurements of forest and agricultural land surface
emissivity at millimeter wavelengths, IEEE T. Geosci. Remote.,
39, 393–400, https://doi.org/10.1109/36.905247, 2001.
Hewison, T. J. and English S. J.: Airborne retrievals of snow and ice
surface emissivity at millimeter wavelengths, IEEE T. Geosci. Remote., 37, 1871–1887, https://doi.org/10.1109/36.774700, 1999.
Isaacs, R. G., Jin, Y. Q., Worsham, R. D., Deblonde, G., and Falcone, V. J.: The RADTRAN microwave surface emission models, IEEE T. Geosci. Remote., 27, 433–440, https://doi.org/10.1109/36.29563, 1989.
Jones, A. S. and Vonder Haar, T. H.: Retrieval of microwave surface emittance
over land using coincident microwave and infrared satellite
measurements, J. Geophys. Res., 102, 13609–13626, https://doi.org/10.1029/97JD00797, 1997.
Karbou, F., Aires, F., Prigent, C., and Eymard, L.: Potential of Advanced
Microwave Sounding Unit-A (AMSU-A) and AMSU-B measurements for atmospheric
temperature and humidity profiling over land, J. Geophys. Res., 110, D07109, https://doi.org/10.1029/2004JD005318, 2005.
Lemmetyinen, J., Derksen, C., Toose, P., Proksch, C., Pulliainen, J., Kontu,
A., Rautiainen, K., Seppänen, J., and Hallikainen, M.: Simulating seasonally and spatially varying snow cover brightness temperature using HUT snow emission model and retrieval of a microwave effective grain size, Remote
Sens. Environ., 156, 71–95, https://doi.org/10.1016/j.rse.2014.09.016, 2015.
Matzler, C.: Seasonal evolution of microwave radiation from an oat field,
Remote Sens. Environ., 31, 161–173, https://doi.org/10.1016/0034-4257(90)90086-2, 1990.
Matzler, C.: Passive microwave signatures of landscapes in winter, Meteorol.
Atmos. Phys., 54, 241–260, https://doi.org/10.1007/BF01030063, 1994.
McNally, A. P., Derber, J. C., Wu, W. S., and Katz, B. B.: The use of TOVS level-1B
radiances in the NCEP SSI analysis system, Q. J. Roy. Meteor. Soc., 126, 689–724, https://doi.org/10.1002/qj.49712656315, 2000.
Mo, T. and Schmugge, T. J.: A parameterization of the effect of surface
roughness on microwave emission, IEEE T. Geosci. Remote., 4, 481–486, https://doi.org/10.1109/TGRS.1987.289860, 1987.
Moncet, J. L., Liang, P., and Galantowicz, J. F.,: Land surface
microwave emissivities derived from AMSR-E and MODIS measurements with
advanced quality control, J. Geophys. Res., 116, D16104, https://doi.org/10.1029/2010JD015429, 2011.
Montpetit, B., Royer, A., Roy, A., and Langlois, A.: In-situ passive microwave
emission model parameterization of sub-arctic frozen organic soils, Remote
Sens. Environ., 205, 112–118, https://doi.org/10.1016/j.rse.2017.10.033, 2018.
Morland, J. C., Grimes, D. I. F., Dugdale, G., and Hewison, T. J.: The Estimation of
Land Surface Emissivities at 24 GHz to 157 GHz Using Remotely Sensed
Aircraft Data, Remote Sens. Environ., 73, 323–336,
https://doi.org/10.1016/S0034-4257(00)00108-5, 2000.
Morland, J. C., Metcalfe, J., and Walker, A.: Microwave remote sensing of soil
moisture in southern Ontario: Aircraft and satellite measurements at 19 and
37 GHz, Radio Sci., 38, 8073, https://doi.org/10.1029/2002RS002677, 2003.
Njoku, E. G. and O'Neill, P. E.: Multifrequency microwave radiometer
measurements of soil moisture, IEEE T. Geosci. Remote., 20, 468–475,
https://doi.org/10.1109/TGRS.1982.350412, 1982.
Prigent, C., Rossow, W. B., and Matthews, E.: Microwave land surface emissivities
estimated from SSM/I observations, J. Geophys. Res., 102, 21867–21890,
https://doi.org/10.1029/97JD01360, 1997.
Prigent, C., Rossow, W. B., Matthews, E., and Marticorena, B.: Microwave
radiometric signatures of different surface types in deserts, J. Geophys. Res., 104, 12147–12158, https://doi.org/10.1029/1999JD900153, 1999.
Prigent, C., Wigneron, J. P., Rossow, W. B., and Pardo-Carrionet, J. R.:
Frequency and angular variations of land surface microwave emissivities: Can
we estimate SSM/T and AMSU emissivities from SSM/I emissivities?, IEEE T. Geosci. Remote., 38, 2373–2386, https://doi.org/10.1109/36.868893, 2000.
Prigent, C., Aires, F., and Rossow, W. B.: Land surface microwave emissivities
over the globe for a decade, B. Am. Meteorol. Soc., 87, 1573–1584,
https://doi.org/10.1175/BAMS-87-11-1573, 2006.
Ruston, R. C. and Vonder Haar, T. H.: Characterization of summertime microwave
emissivity from the Special Sensor Microwave Imager over the conterminous
United States, J. Geophys. Res., 109, D19103, https://doi.org/10.1029/2004JD004890,
2004.
Schwartz, C. S., Liu, Z. Q., Chen, Y., and Huang, X. Y.: Impact of assimilating microwave radiances with a limited-area ensemble data assimilation system on
forecasts of Typhoon Morakot, Weather Forecast., 27, 424–437,
https://doi.org/10.1175/WAF-D-11-00033.1, 2012.
Ulaby, F. T., Moore, R. K., and Fung, A. K.: Microwave Remote Sensing Active and Passive-Volume III: From Theory to Applications, Artech House, Norwood, ISBN 0890061920, 1986.
Wang, J. R. and Schmugge, T. J. : An empirical model for the complex dielectric permittivity of soil as a function of water content, IEEE Trans. Geosci. Remote Sens., GE-18, 288–295, 1980.
Weng, F., Yan, B., and Grody, N. C.: A microwave land emissivity model, J.
Geophys. Res., 106, 20115–20123, https://doi.org/10.1029/2001JD900019,
2001.
Wigneron, J. P., Guyon, D., Calvet, J. C., Courrieer, G., and Bruguier, N.:
Monitoring coniferous forest characteristics using a multifrequency
microwave radiometry, Remote Sens. Environ., 60, 299–310,
https://doi.org/10.1016/S0034-4257(96)00212-X, 1997.
Xie, Y., Shi, J., Ji, D., Zhong, J., and Fan, S.: A Parameterized Microwave
Emissivity Model for Bare Soil Surfaces, Remote Sens.-Basel., 9, 155–170,
https://doi.org/10.3390/rs9020155, 2017.
Short summary
Large microwave surface emissivities (ε) cause difficulties in widely using satellite microwave data over land. Usually, ground-based radiometers are fixed to a scan field to obtain the temporal evolution of ε over a single land-cover area. To obtain the long-term temporal evolution of ε over different land-cover surfaces simultaneously, we developed a ground mobile observation system to enhance in situ ε observations and presented some preliminary results.
Large microwave surface emissivities (ε) cause difficulties in widely using satellite microwave...