Evaluating the Quality of Ground-Based Microwave Radiometer Measurements and Retrievals Using Detrended Fluctuation and Spectral Analysis Methods

K. Ivanova Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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E. E. Clothiaux Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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H. N. Shirer Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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T. P. Ackerman Pacific Northwest National Laboratory, Richland, Washington

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J. C. Liljegren Environmental Research Division, Argonne National Laboratory, Argonne, Illinois

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M. Ausloos SUPRAS and GRASP, Institute of Physics, University of Liège, Liège, Belgium

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Abstract

Time series both of microwave radiometer brightness temperature measurements at 23.8 and 31.4 GHz and of retrievals of water vapor and liquid water path from these brightness temperatures are evaluated using the detrended fluctuation analysis method. As quantified by the parameter α, this method (i) enables identification of the timescales over which noise dominates the time series and (ii) characterizes the temporal range of correlations in the time series. The more common spectral analysis method is also used to assess the data, and its results are compared with those from the detrended fluctuation analysis method. The assumption that measurements should have certain scaling properties allows the quality of the measurements to be characterized. The additional assumption that the scaling properties of the measurements of an atmospheric quantity are preserved in a useful retrieval provides a means for evaluating the retrieval itself. Applying these two assumptions to microwave radiometer measurements and retrievals demonstrates three points. First, the retrieved water vapor path during cloudy-sky periods can be dominated by noise on shorter-than-30-min timescales (α exponent = 0.1) and exhibits no scaling behavior at longer timescales. However, correlations in the brightness temperatures and liquid water path retrievals are found to be consistent with a power-law behavior for timescales up to 3 h with an α exponent equal to approximately 0.3, as in other geophysical phenomena. Second, clear-sky, moist atmospheres show the expected scaling for both measurements and retrievals of the water vapor path. Third, during clear-sky, dry atmospheric days, instrument noise from the 31.4-GHz channel compromises the quality of the water vapor path retrieval. The detrended fluctuation analysis method is thus proposed as means for assessing the quality of both the instrument data and the retrieved parameters obtained from these data.

Corresponding author address: Kristinka Ivanova, Department of Meteorology, The Pennsylvania State University, 503 Walker Building, University Park, PA 16802. kristy@essc.psu.edu

Abstract

Time series both of microwave radiometer brightness temperature measurements at 23.8 and 31.4 GHz and of retrievals of water vapor and liquid water path from these brightness temperatures are evaluated using the detrended fluctuation analysis method. As quantified by the parameter α, this method (i) enables identification of the timescales over which noise dominates the time series and (ii) characterizes the temporal range of correlations in the time series. The more common spectral analysis method is also used to assess the data, and its results are compared with those from the detrended fluctuation analysis method. The assumption that measurements should have certain scaling properties allows the quality of the measurements to be characterized. The additional assumption that the scaling properties of the measurements of an atmospheric quantity are preserved in a useful retrieval provides a means for evaluating the retrieval itself. Applying these two assumptions to microwave radiometer measurements and retrievals demonstrates three points. First, the retrieved water vapor path during cloudy-sky periods can be dominated by noise on shorter-than-30-min timescales (α exponent = 0.1) and exhibits no scaling behavior at longer timescales. However, correlations in the brightness temperatures and liquid water path retrievals are found to be consistent with a power-law behavior for timescales up to 3 h with an α exponent equal to approximately 0.3, as in other geophysical phenomena. Second, clear-sky, moist atmospheres show the expected scaling for both measurements and retrievals of the water vapor path. Third, during clear-sky, dry atmospheric days, instrument noise from the 31.4-GHz channel compromises the quality of the water vapor path retrieval. The detrended fluctuation analysis method is thus proposed as means for assessing the quality of both the instrument data and the retrieved parameters obtained from these data.

Corresponding author address: Kristinka Ivanova, Department of Meteorology, The Pennsylvania State University, 503 Walker Building, University Park, PA 16802. kristy@essc.psu.edu

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  • Addison, P. S. 1997. Fractals and Chaos: An Illustrated Course. Institute of Physics, 250 pp.

  • Ausloos, M. and K. Ivanova. 1999. Precise (m, k)-Zipf diagram analysis of mathematical and financial time series when m = 6 and k = 2. Physica A 270:526542.

    • Search Google Scholar
    • Export Citation
  • Ausloos, M. and K. Ivanova. 2001. Power law correlations in the Southern Oscillation index fluctuations characterizing El Niño. Phys. Rev. E 64. 047201.

    • Search Google Scholar
    • Export Citation
  • Ausloos, M., N. Vandewalle, Ph Boveroux, A. Minguet, and K. Ivanova. 1999. Applications of statistical physics to economic and financial topics. Physica A 274:229240.

    • Search Google Scholar
    • Export Citation
  • Ausloos, M., N. Vandewalle, and K. Ivanova. 2000. Time is money. Noise, Oscillators and Algebraic Randomness, M. Planat, Ed., Noise in Communication Systems to Number Theory, Vol. 550, Springer, 156–171.

    • Search Google Scholar
    • Export Citation
  • Bak, P., K. Chen, and M. Creutz. 1989. Self-organized criticality in the “game of life.”. Nature 342:780783.

  • Blum, E. K. 1972. Numerical Analysis and Computation Theory and Practice. Addison-Wesley, 612 pp.

  • Davis, A., A. Marshak, W. Wiscombe, and R. Cahalan. 1994. Multifractal characterization of nonstationarity and intermittency in geophysical fields: Observed, retrieved or simulated. J. Geophys. Res 99:(D4),. 80558072.

    • Search Google Scholar
    • Export Citation
  • Davis, A., A. Marshak, W. Wiscombe, and R. Cahalan. 1996. Scale invariance in liquid water distributions in marine stratocumulus. Part I: Spectral properties and stationary issues. J. Atmos. Sci 53:15381558.

    • Search Google Scholar
    • Export Citation
  • Frisch, U. and A. N. Kolmogorov. 1995. Turbulence: The Legacy of A. N. Kolmogorov. Cambridge University Press, 296 pp.

  • Hausdorff, J. M., C-K. Peng, Z. Ladin, J. Y. Wei, and A. L. Goldberger. 1995. Is walking a random walk? Evidence for long-range correlations in the stride interval of human gait. J. Appl. Physiol 78:349358.

    • Search Google Scholar
    • Export Citation
  • Heneghan, C. and G. McDarby. 2000. Establishing the relation between detrended fluctuations analysis and power spectral density analysis for stochastic processes. Phys. Rev. E 62:61036110.

    • Search Google Scholar
    • Export Citation
  • Hurst, H. E., B. P. Black, and Y. M. Simaika. 1965. Long-Term storage: An Experimental Study. Constable.

  • Ivanova, K. and T. Ackerman. 1999. Multifractal characterization of liquid water in clouds. Phys. Rev. E 59:27782782.

  • Ivanova, K. and M. Ausloos. 1999a. Application of the Detrended Fluctuation Analysis (DFA) method for describing cloud breaking. Physica A 274:349354.

    • Search Google Scholar
    • Export Citation
  • Ivanova, K. and T. Ackerman. 1999b. Low q-moment multifractal analysis of gold price, Dow Jones Industrial Average and BGL-USD exchange rate. Eur. Phys. J. B 8:665669.

    • Search Google Scholar
    • Export Citation
  • Ivanova, K., T. Ackerman, E. E. Clothiaux, and T. P. Ackerman. 2000. Break-up of stratus cloud structure predicted from non-Brownian motion liquid water and brightness temperature fluctuations. Europhys. Lett 52:4046.

    • Search Google Scholar
    • Export Citation
  • Kiely, G. and K. Ivanova. 1999. Multifractal analysis of hourly precipitation. Phys. Chem. Earth 24:781786.

  • Liljegren, J. C. 1994. Two-channel microwave radiometer for observations of total column precipitable water vapor and cloud liquid water path. Preprints, Fifth Symp. on Global Change Studies, Nashville, TN, Amer. Meteor. Soc., 262–269.

    • Search Google Scholar
    • Export Citation
  • Liljegren, J. C. 1999. Automatic self-calibration of ARM microwave radiometers. Microwave Radiometry and Remote Sensing of the Earth's Surface and Atmosphere, P. Pampaloni and S. Paloscia, Eds., VSP Press, 433–443.

    • Search Google Scholar
    • Export Citation
  • Liljegren, J. C. and B. M. Lesht. 1996. Measurements of integrated water vapor and cloud liquid water from microwave radiometers at the DOE ARM cloud and radiation testbed in the U.S. Southern Great Plains. IEEE Int. Geosci. Remote Sens. Symp 3:16751677.

    • Search Google Scholar
    • Export Citation
  • Liljegren, J. C., E. E. Clothiaux, G. G. Mace, S. Kato, and X. Dong. 2001. Retrieval of cloud liquid water path using microwave radiometer measurements. J. Geophys. Res 106:1448514500.

    • Search Google Scholar
    • Export Citation
  • Lovejoy, S., M. R. Duncan, and D. Schertzer. 1996. Scalar multifractal radar observer's problem. J. Geophys. Res 101:2647926491.

  • Marshak, A., A. Davis, W. Wiscombe, and R. Cahalan. 1997. Scale invariance in liquid water distributions in marine stratocumulus. Part II: Multifractal properties and intermittency issues. J. Atmos. Sci 54:14231444.

    • Search Google Scholar
    • Export Citation
  • McFarlane, S. A., K. F. Evans, E. J. Mlawer, and E. E. Clothiaux. 2000. Shortwave flux closure experiments at Nauru. Proc. 10th ARM Science Team Meeting, San Antonio, TX, U.S. Dept. of Energy, 1;nd7.

    • Search Google Scholar
    • Export Citation
  • Monin, A. S. and A. M. Yaglom. 1975. Statistical Fluid Mechanics. Vol. 2. MIT Press, 683 pp.

  • Panter, P. F. 1965. Modulation, Noise, and Spectral Analysis. McGraw-Hill, 759 pp.

  • Pelletier, J. D. 1997. Kardar-Parisi-Zhang scaling of the height of the convective boundary layer and fractal structure of cumulus cloud fields. Phys. Rev. Lett 78:26722675.

    • Search Google Scholar
    • Export Citation
  • Peng, C-K., S. V. Buldyrev, A. L. Goldberger, S. Havlin, F. Sciortino, M. Simmons, and H-E. Stanley. 1992. Long-range correlations in nucleotide sequences. Nature 356:168170.

    • Search Google Scholar
    • Export Citation
  • Peng, C-K., S. V. Buldyrev, S. Havlin, M. Simmons, H-E. Stanley, and A. L. Goldberger. 1994. On the mosaic organization of DNA sequences. Phys. Rev. E 49:16851689.

    • Search Google Scholar
    • Export Citation
  • Percival, D. B. and A. T. Walden. 1994. Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques. Cambridge University Press, 583 pp.

    • Search Google Scholar
    • Export Citation
  • Priestley, M. B. 1981. Spectral Analysis and Time Series. Academic Press, 890 pp.

  • Schroeder, J. A. and E. R. Westwater. 1991. User's guide to WPL microwave radiative transfer software. NOAA Tech. Memo. ERL WPL-213, 37 pp.

    • Search Google Scholar
    • Export Citation
  • Schroeder, M. 1991. Fractals, Chaos, Power Laws. W. H. Freeman and Co., 429 pp.

  • Stanley, H. E., S. V. Buldyrev, A. L. Goldberger, S. Havlin, C-K. Peng, and M. Simons. 1993. Long-range power-law correlations in condensed matter physics and biophysics. Physica A 200:424.

    • Search Google Scholar
    • Export Citation
  • Stokes, G. M. and S. E. Schwartz. 1994. The Atmospheric Radiation Measurement (ARM) program: Programmatic background and design of the cloud and radiation test bed. Bull. Amer. Meteor. Soc 75:12011221.

    • Search Google Scholar
    • Export Citation
  • Tessier, Y., S. Lovejoy, and D. Schertzer. 1993. Universal multifractals: Theory and observations for rain and clouds. J. Appl. Meteor 32:223250.

    • Search Google Scholar
    • Export Citation
  • Turcotte, D. L. 1997. Fractals and Chaos in Geology and Geophysics. Cambridge University Press, 398 pp.

  • Vandewalle, N. and M. Ausloos. 1997. Coherent and random sequences in financial fluctuations. Physica A 246:454459.

  • Vandewalle, N. and M. Ausloos. 1998. Extended detrended fluctuation analysis for financial data. Int. J. Comput. Anticipat. Syst 1:342349.

    • Search Google Scholar
    • Export Citation
  • Westwater, E. R. 1978. The accuracy of water vapor and cloud liquid water determination by dual-frequency ground-based microwave radiometry. Radio Sci 13:677685.

    • Search Google Scholar
    • Export Citation
  • Westwater, E. R. 1993. Ground-based microwave remote sensing of meteorological variables. Atmospheric Remote Sensing by Microwave Radiometry. M. A. Janssen, Ed., John Wiley and Sons, 145–213.

    • Search Google Scholar
    • Export Citation
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