• Amayenc, P., , Testud J. , , and Marzoug M. , 1993: Proposal for a spaceborne dual-beam rain radar with Doppler capability. J. Atmos. Oceanic Technol., 10, 262276, doi:10.1175/1520-0426(1993)010<0262:PFASDB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Apel, J. R., 1994: An improved model of the ocean surface wave vector spectrum and its effects on radar backscatter. J. Geophys. Res.,99, 16 269–16 291, doi:10.1029/94JC00846.

  • Battaglia, A., , and Simmer C. , 2008: How does multiple scattering affect the spaceborne W-band radar measurements at ranges close to and crossing the sea-surface range? IEEE Trans. Geosci. Remote Sens., 46, 16441651, doi:10.1109/TGRS.2008.916085.

    • Search Google Scholar
    • Export Citation
  • Battaglia, A., , and Tanelli S. , 2011: DOMUS: DOppler Multiple-Scattering Simulator. IEEE Trans. Geosci. Remote Sens., 49, 442450, doi:10.1109/TGRS.2010.2052818.

    • Search Google Scholar
    • Export Citation
  • Battaglia, A., , and Kollias P. , 2014: Using ice clouds for mitigating the EarthCARE Doppler radar mispointing. IEEE Trans. Geosci. Remote Sens., 53, 2079–2085, doi:10.1109/TGRS.2014.2353219.

    • Search Google Scholar
    • Export Citation
  • Battaglia, A., , Ajewole M. O. , , and Simmer C. , 2007: Evaluation of radar multiple scattering effects in CloudSat configuration. Atmos. Chem. Phys., 7, 17191730, doi:10.5194/acp-7-1719-2007.

    • Search Google Scholar
    • Export Citation
  • Battaglia, A., , Haynes J. M. , , L’Ecuyer T. , , and Simmer C. , 2008: Identifying multiple-scattering-affected profiles in CloudSat observations over the oceans. J. Geophys. Res., 113, D00A17, doi:10.1029/2008JD009960.

    • Search Google Scholar
    • Export Citation
  • Battaglia, A., , Tanelli S. , , Kobayashi S. , , Zrnić D. , , Hogan R. , , and Simmer C. , 2010: Multiple-scattering in radar systems: A review. J. Quant. Spectrosc. Radiat. Transfer, 111, 917947, doi:10.1016/j.jqsrt.2009.11.024.

    • Search Google Scholar
    • Export Citation
  • Battaglia, A., , Augustynek T. , , Tanelli S. , , and Kollias P. , 2011: Multiple scattering identification in spaceborne W-band radar measurements of deep convective cores. J. Geophys. Res., 116, D19201, doi:10.1029/2011JD016142.

    • Search Google Scholar
    • Export Citation
  • Battaglia, A., , Tanelli S. , , and Kollias P. , 2013: Polarization diversity for millimeter spaceborne Doppler radars: An answer for observing deep convection? J. Atmos. Oceanic Technol., 30, 27682787, doi:10.1175/JTECH-D-13-00085.1.

    • Search Google Scholar
    • Export Citation
  • Battaglia, A., , Tanelli S. , , Heymsfield G. , , and Tian L. , 2014: The dual wavelength ratio knee: A signature of multiple scattering in airborne Ku–Ka observations. J. Appl. Meteor. Climatol., 53, 17901808, doi:10.1175/JAMC-D-13-0341.1.

    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., , Weiss C. C. , , and Pazmany A. , 2004: The vertical structure of a tornado near Happy, Texas, on 5 May 2002: High-resolution, mobile, W-band, Doppler radar observations. Mon. Wea. Rev., 132, 23252337, doi:10.1175/1520-0493(2004)132<2325:TVSOAT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., and Coauthors, 2014: Radar in atmospheric sciences and related research: Current systems, emerging technology, and future needs. Bull. Amer. Meteor. Soc.,95, 1850–1861, doi:10.1175/BAMS-D-13-00079.1.

  • Doviak, R. J., , and Zrnić D. S. , 1984: Doppler Radar and Weather Observations. Academic Press, 458 pp.

  • ESA, 2006: Earthcare mission requirements document. EarthCARE Mission Advisory Group Tech. Rep. EC-RS-ESA-Sy-012, Issue 5, 73 pp. [Available online at http://esamultimedia.esa.int/docs/EarthObservation/EarthCARE_MRD_v5.pdf.]

  • Eyre, J., , Thepaut J.-N. , , Joiner J. , , Riishojgaard L. P. , , and Gerard F. , 2002: Requirements for observations for global NWP. EUMETSAT Position Paper, 25 pp.

  • Gao, J., , Xue M. , , Shapiro A. , , and Droegemeier K. K. , 1999: A variational method for the analysis of three-dimensional wind fields from two Doppler radars. Mon. Wea. Rev., 127, 21282142, doi:10.1175/1520-0493(1999)127<2128:AVMFTA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Guimond, S. R., , Tian L. , , Heymsfield G. M. , , and Frasier S. J. , 2014: Wind retrieval algorithms for the IWRAP and HIWRAP airborne Doppler radars with applications to hurricanes. J. Atmos. Oceanic Technol., 31, 11891215, doi:10.1175/JTECH-D-13-00140.1.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, G. M., and Coauthors, 1996: The EDOP radar system on the high-altitude NASA ER-2 aircraft. J. Atmos. Oceanic Technol., 13, 795809, doi:10.1175/1520-0426(1996)013<0795:TERSOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, G. M., , Halverson J. B. , , and Caylor I. J. , 1999: A wintertime Gulf Coast squall line observed by EDOP airborne Doppler radar. Mon. Wea. Rev., 127, 29282950, doi:10.1175/1520-0493(1999)127<2928:AWGCSL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, G. M., , Halverson J. B. , , Simpson J. , , Tian L. , , and Bui T. P. , 2001: ER-2 Doppler radar investigations of the eyewall of Hurricane Bonnie during the Convection and Moisture Experiment-3. J. Appl. Meteor., 40, 13101330, doi:10.1175/1520-0450(2001)040<1310:EDRIOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hou, A. Y., and Coauthors, 2014: The Global Precipitation Measurement Mission. Bull. Amer. Meteor. Soc.,95, 701–722, doi:10.1175/BAMS-D-13-00164.1.

  • Illingworth, A. J., and Coauthors, 2015: The EarthCARE satellite: The next step forward in global measurements of clouds, aerosols, precipitation, and radiation. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-12-00227.1, in press.

    • Search Google Scholar
    • Export Citation
  • Joe, P., and Coauthors, 2010: The Polar Precipitation Measurement Mission. Proc. Sixth European Conf. on Radar Meteorology and Hydrology, Sibiu, Romania, EUMETSAT, 18 pp. [Available online at http://www.erad2010.org/pdf/oral/tuesday/satellite/01_ERAD2010_Joe.pdf.]

  • Kobayashi, S., , Kumagai H. , , and Kuroiwa H. , 2002: A proposal of pulse-pair Doppler operation on a spaceborne cloud-profiling radar in the W band. J. Atmos. Oceanic Technol., 19, 12941306, doi:10.1175/1520-0426(2002)019<1294:APOPPD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kobayashi, S., , Kumagai H. , , and Iguchi T. , 2003: Accuracy evaluation of Doppler velocity on a spaceborne weather radar through a random signal simulation. J. Atmos. Oceanic Technol., 20, 944949, doi:10.1175/1520-0426(2003)020<0944:AEODVO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kollias, P., , Tanelli S. , , Battaglia A. , , and Tatarevic A. , 2014: Evaluation of EarthCARE Cloud Profiling Radar Doppler velocity measurements in particle sedimentation regimes. J. Atmos. Oceanic Technol., 31, 366386, doi:10.1175/JTECH-D-11-00202.1.

    • Search Google Scholar
    • Export Citation
  • Kummerow, C. D., , Barnes W. , , Kozu T. , , Shiue J. , , and Simpson J. , 1998: The Tropical Rainfall Measuring Mission (TRMM) sensor package. J. Atmos. Oceanic Technol., 15, 809817, doi:10.1175/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Mace, G. G., , Marchand R. , , Zhang Q. , , and Stephens G. , 2007: Global hydrometeor occurrence as observed by CloudSat: Initial observations from summer 2006. Geophys. Res. Lett., 34, L09808, doi:10.1029/2006GL029017.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S., 2005: Attenuation-based estimates of rainfall rates aloft with vertically pointing Ka-band radars. J. Atmos. Oceanic Technol., 22, 4354, doi:10.1175/JTECH-1677.1.

    • Search Google Scholar
    • Export Citation
  • Meneghini, R., , and Kozu T. , 1990: Spaceborne Weather Radar. Artech House Radar Library, Artech House, 199 pp.

  • Mitrescu, C., , Ecuyer T. L. , , Haynes J. , , Miller S. , , and Turk J. , 2010: CloudSat precipitation profiling algorithm—Model description. J. Appl. Meteor. Climatol., 49, 9911003, doi:10.1175/2009JAMC2181.1.

    • Search Google Scholar
    • Export Citation
  • Pazmany, A., , Galloway J. , , Mead J. , , Popstefanija I. , , McIntosh R. , , and Bluestein H. , 1999: Polarization diversity pulse-pair technique for millimeter-wave Doppler Radar measurements of severe storm features. J. Atmos. Oceanic Technol., 16, 19001910, doi:10.1175/1520-0426(1999)016<1900:PDPPTF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Romeiser, R., , Alpers W. , , and Wismann V. , 1997: An improved composite surface model for the radar backscattering cross section of the ocean surface: 1. Theory of the model and optimization/validation by scatterometer data. J. Geophys. Res.,102, 25 237–25 250, doi:10.1029/97JC00190.

  • Schutgens, N. A. J., 2008: Simulated Doppler radar observations of inhomogeneous clouds: Application to the EarthCARE space mission. J. Atmos. Oceanic Technol., 25, 15141528, doi:10.1175/2007JTECHA1026.1.

    • Search Google Scholar
    • Export Citation
  • Simpson, J., , Kummerow C. , , Tao W.-K. , , and Adler R. , 1996: On the Tropical Rainfall Measuring Mission (TRMM). Meteor. Atmos. Phys., 60, 1936, doi:10.1007/BF01029783.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., , and Klemp J. B. , 2008: A time-split nonhydrostatic atmospheric model for research and NWP applications. J. Comput. Phys., 227, 34653485, doi:10.1016/j.jcp.2007.01.037.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., , Klemp J. B. , , Dudhia J. , , Gill D. O. , , Barker D. M. , , Wang W. , , and Powers J. G. , 2005: A description of the advanced research WRF version 2. NCAR Tech Note NCAR/TN-468+STR, 88 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v2.pdf.]

  • Smith, E. A., and Coauthors, 2007: International Global Precipitation Measurement (GPM) program and mission: An overview. Measuring Precipitation from Space: EURAINSAT and the Future, V. Levizzani, P. Bauer, and F. J. Turk, Eds., Advances in Global Change Research, Vol. 28, Springer, 611–653.

    • Search Google Scholar
    • Export Citation
  • Snyder, C., , and Zhang F. , 2003: Assimilation of simulated Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 131, 16631677, doi:10.1175//2555.1.

    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., and Coauthors, 2002: The CloudSat mission and the A-Train. Bull. Amer. Meteor. Soc., 83, 17711790, doi:10.1175/BAMS-83-12-1771.

    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., and Coauthors, 2008: CloudSat mission: Performance and early science after the first year of operation. J. Geophys. Res., 113, D00A18, doi:10.1029/2008JD009982.

    • Search Google Scholar
    • Export Citation
  • Stoffelen, A., , Bonavita M. , , Eyre J. , , Goldberg M. , , Jarvinen H. , , Serio C. , , Thepaut J.-N. , , and Wulfmeyer V. , 2006: Post-EPS developments on atmospheric sounding and wind profiling. EUMETSAT Position Paper, 36 pp.

  • Sy, O., , Tanelli S. , , Takahashi N. , , Ohno Y. , , Horie H. , , and Kollias P. , 2013: Simulation of EarthCARE spaceborne Doppler radar products using ground-based and airborne data: Effects of aliasing and non-uniform beam-filling. IEEE Trans. Geosci. Remote Sens., 52, 1463–1479, doi:10.1109/TGRS.2013.2251639.

    • Search Google Scholar
    • Export Citation
  • Sy, O., , Tanelli S. , , Kollias P. , , and Ohno Y. , 2014: Application of matched statistical filters for EarthCARE cloud Doppler products. IEEE Trans. Geosci. Remote Sens., 52, 72977316, doi:10.1109/TGRS.2014.2311031.

    • Search Google Scholar
    • Export Citation
  • Tanelli, S., , Im E. , , Durden S. L. , , Facheris L. , , and Giuli D. , 2002: The effects of nonuniform beam filling on vertical rainfall velocity measurements with a spaceborne Doppler radar. J. Atmos. Oceanic Technol., 19, 10191034, doi:10.1175/1520-0426(2002)019<1019:TEONBF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Tanelli, S., , Im E. , , Durden S. L. , , Facheris L. , , Giuli D. , , and Smith E. , 2004: Rainfall Doppler velocity measurements from spaceborne radar: Overcoming nonuniform beam-filling effects. J. Atmos. Oceanic Technol., 21, 2744, doi:10.1175/1520-0426(2004)021<0027:RDVMFS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Tanelli, S., , Durden S. , , Im E. , , Pak K. , , Reinke D. , , Partain P. , , Haynes J. , , and Marchand R. , 2008: CloudSat’s Cloud Profiling Radar after 2 years in orbit: Performance, calibration, and processing. IEEE Trans. Geosci. Remote Sens., 46, 35603573, doi:10.1109/TGRS.2008.2002030.

    • Search Google Scholar
    • Export Citation
  • Tanelli, S., , Heymsfield G. M. , , Stephens G. S. , , Durden S. L. , , Im E. , , Racette P. , , Li L. , , and Sadowy G. , 2010: Decadal survey tier 2 mission study summative progress report: ACE radar. JPL/NASA Doc., 14 pp. [Available online at http://hdl.handle.net/2014/41978.]

  • Testud, J., , and Amayenc P. , 1989: Stereoradar meteorology: A promising technique for observation of precipitation from a mobile platform. J. Atmos. Oceanic Technol., 6, 89108, doi:10.1175/1520-0426(1989)006<0089:SMAPTF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Testud, J., , Amayenc P. , , and Marzoug M. , 1992: Rainfall-rate retrieval from a spaceborne radar: Comparison between single-frequency, dual-frequency, and dual-beam techniques. J. Atmos. Oceanic Technol., 9, 599623, doi:10.1175/1520-0426(1992)009<0599:RRRFAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ulaby, F. T., , Moore R. K. , , and Fung A. K. , 1986: Microwave Remote Sensing Fundamental and Radiometry. Vol. 1, Microwave Remote Sensing: Active and Passive, Artech House, 456 pp.

    • Search Google Scholar
    • Export Citation
  • Yuter, S. E., , and Houze R. A. , 1995: Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part II: Frequency distributions of vertical velocity, reflectivity, and differential reflectivity. Mon. Wea. Rev., 123, 19411963, doi:10.1175/1520-0493(1995)123<1941:TDKAME>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zhang, F., , Weng Y. , , Sippel J. A. , , Meng Z. , , and Bishop C. H. , 2009: Cloud-resolving hurricane initialization and prediction through assimilation of Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 137, 21052125, doi:10.1175/2009MWR2645.1.

    • Search Google Scholar
    • Export Citation
  • Zrnić, D. S., 1977: Spectral moment estimates from correlated pulse pairs. IEEE Trans. Aerosp. Electron. Syst., AES-13, 344354, doi:10.1109/TAES.1977.308467.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 19 19 11
PDF Downloads 18 18 11

Error Analysis of a Conceptual Cloud Doppler Stereoradar with Polarization Diversity for Better Understanding Space Applications

View More View Less
  • 1 Department of Physics and Astronomy, University of Leicester, Leicester, United Kingdom
  • 2 Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Canada
© Get Permissions
Restricted access

Abstract

An error budget analysis is performed for retrieval of along-track winds based on the design of a spaceborne Doppler radar using polarization diversity. The analysis is conducted within the framework of a case study of an Atlantic hurricane. The proposed concept consists of either a Ka-band or W-band stereoradar mounted on an LEO satellite equipped with both nadir- and forward-viewing beams and with an optional cross-scanning capability. Such a radar design is intended for observing the microphysical and dynamical structures of cloud systems, including disturbed mesoscale convective systems. Because of the high winds involved in such weather phenomena and because of the Doppler fading introduced by platform motion, polarization diversity is adopted. The simulation framework enables a breakdown of the Doppler velocity measurement error budget into its most important components, that is, nonuniform beamfilling, multiple scattering, and inherent signal noise. The impact of each of these error terms on the total error depends on the adopted integration length, the number of scanned tracks, and the specifics of the radar. This allows for optimally selecting an integration length suitable for minimizing the total rms velocity error. The analysis shows that the use of a large antenna could achieve impressive measurement accuracy of the along-line-of-sight wind velocities. Notably, this would be the case for integration lengths longer than 3 km, even when carrying out cross-track scanning for up to 17 separate tracks. Examples of retrieved along-track wind fields also reveal that the large antenna configurations are capable of identifying and quantifying the foremost dynamic features (e.g., vertical wind shear and convergence/divergence regions).

Corresponding author address: Alessandro Battaglia, Department of Physics and Astronomy, University of Leicester, University Road, Leicester LE1 7RH, United Kingdom. E-mail: ab474@le.ac.uk

Abstract

An error budget analysis is performed for retrieval of along-track winds based on the design of a spaceborne Doppler radar using polarization diversity. The analysis is conducted within the framework of a case study of an Atlantic hurricane. The proposed concept consists of either a Ka-band or W-band stereoradar mounted on an LEO satellite equipped with both nadir- and forward-viewing beams and with an optional cross-scanning capability. Such a radar design is intended for observing the microphysical and dynamical structures of cloud systems, including disturbed mesoscale convective systems. Because of the high winds involved in such weather phenomena and because of the Doppler fading introduced by platform motion, polarization diversity is adopted. The simulation framework enables a breakdown of the Doppler velocity measurement error budget into its most important components, that is, nonuniform beamfilling, multiple scattering, and inherent signal noise. The impact of each of these error terms on the total error depends on the adopted integration length, the number of scanned tracks, and the specifics of the radar. This allows for optimally selecting an integration length suitable for minimizing the total rms velocity error. The analysis shows that the use of a large antenna could achieve impressive measurement accuracy of the along-line-of-sight wind velocities. Notably, this would be the case for integration lengths longer than 3 km, even when carrying out cross-track scanning for up to 17 separate tracks. Examples of retrieved along-track wind fields also reveal that the large antenna configurations are capable of identifying and quantifying the foremost dynamic features (e.g., vertical wind shear and convergence/divergence regions).

Corresponding author address: Alessandro Battaglia, Department of Physics and Astronomy, University of Leicester, University Road, Leicester LE1 7RH, United Kingdom. E-mail: ab474@le.ac.uk
Save