Editorial Type:
Article
Article Type:
Research Article

Atlantic Tropical Cyclone Monitoring with AMSU-A: Estimation of Maximum Sustained Wind Speeds

Roy W. Spencer NASA Marshall Space Flight Center, Global Hydrology and Climate Center, Huntsville, Alabama

Search for other papers by Roy W. Spencer in
Current site
Google Scholar
PubMed Close
and
William D. Braswell Computer Sciences Corporation, Global Hydrology and Climate Center, Huntsville, Alabama

Search for other papers by William D. Braswell in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Jun 2001
DOI:
https://doi.org/10.1175/1520-0493(2001)129<1518:ATCMWA>2.0.CO;2
Page(s):
1518–1532
Restricted access

Abstract

The first Advanced Microwave Sounding Unit temperature sounder (AMSU-A) was launched on the NOAA-15 satellite on 13 May 1998. The AMSU-A’s higher spatial and radiometric resolutions provide more useful information on the strength of the middle- and upper-tropospheric warm cores associated with tropical cyclones than have previous microwave temperature sounders. The gradient wind relationship suggests that the temperature gradient near the core of tropical cyclones increases nonlinearly with wind speed. The gradient wind equation is recast to include AMSU-A-derived variables. Stepwise regression is used to determine which of these variables is most closely related to maximum sustained winds (Vmax). The satellite variables investigated include the radially averaged gradients at two spatial resolutions of AMSU-A channels 1–10 Tb data (δrTb), the squares of these gradients, a channel-15-based scattering index (SI89), and area-averaged Tb. Calculations of Tb and δrTb from mesoscale model simulations of Andrew (1992) reveal the effects of the AMSU spatial sampling on the cyclone warm core presentation. Stepwise regression of 66 AMSU-A terms against National Hurricane Center Vmax estimates from the 1998 and 1999 Atlantic hurricane season confirms the existence of a nonlinear relationship between wind speed and radially averaged temperature gradients near the cyclone warm core. Of six regression terms, four are dominated by temperature information, and two are interpreted as correcting for hydrometeor contamination. Jackknifed regressions were performed to estimate the algorithm performance on independent data. For the 82 cases that had in situ measurements of Vmax, the average error standard deviation was 4.7 m s−1. For 108 cases without in situ wind data, the average error standard deviation was 7.5 m s−1. Operational considerations, including the detection of weak cyclones and false alarm reduction, are also discussed.

Corresponding author address: Roy W. Spencer, NASA Marshall Space Flight Center, Global Hydrology and Climate Center, 320 Sparkman Drive, Huntsville, AL 35805.

Abstract

The first Advanced Microwave Sounding Unit temperature sounder (AMSU-A) was launched on the NOAA-15 satellite on 13 May 1998. The AMSU-A’s higher spatial and radiometric resolutions provide more useful information on the strength of the middle- and upper-tropospheric warm cores associated with tropical cyclones than have previous microwave temperature sounders. The gradient wind relationship suggests that the temperature gradient near the core of tropical cyclones increases nonlinearly with wind speed. The gradient wind equation is recast to include AMSU-A-derived variables. Stepwise regression is used to determine which of these variables is most closely related to maximum sustained winds (Vmax). The satellite variables investigated include the radially averaged gradients at two spatial resolutions of AMSU-A channels 1–10 Tb data (δrTb), the squares of these gradients, a channel-15-based scattering index (SI89), and area-averaged Tb. Calculations of Tb and δrTb from mesoscale model simulations of Andrew (1992) reveal the effects of the AMSU spatial sampling on the cyclone warm core presentation. Stepwise regression of 66 AMSU-A terms against National Hurricane Center Vmax estimates from the 1998 and 1999 Atlantic hurricane season confirms the existence of a nonlinear relationship between wind speed and radially averaged temperature gradients near the cyclone warm core. Of six regression terms, four are dominated by temperature information, and two are interpreted as correcting for hydrometeor contamination. Jackknifed regressions were performed to estimate the algorithm performance on independent data. For the 82 cases that had in situ measurements of Vmax, the average error standard deviation was 4.7 m s−1. For 108 cases without in situ wind data, the average error standard deviation was 7.5 m s−1. Operational considerations, including the detection of weak cyclones and false alarm reduction, are also discussed.

Corresponding author address: Roy W. Spencer, NASA Marshall Space Flight Center, Global Hydrology and Climate Center, 320 Sparkman Drive, Huntsville, AL 35805.

Save
Cover Monthly Weather Review
Monthly Weather Review

  • Chedin, A., N. A. Scott, C. Wahiche, and P. Moulinier, 1985: The improved initialization inversion method: A high resolution physical method for temperature retrievals from satellites of the TIROS-N series. J. Climate Appl. Meteor.,24, 128–143.

  • Dvorak, V. F., 1984: Tropical cyclone intensity analysis using satellite data. NOAA Tech. Rep. NESDIS 11, NOAA, U.S. Department of Commerce.

  • Elsner, J. B., and C. P. Schmertmann, 1994: Assessing forecast skill through cross validation. Wea. Forecasting,9, 619–624.

  • Franklin, J. L., M. L. Black, and K. Valde, 2000: Eyewall wind profiles in hurricanes determined by GPS dropwindsondes. Preprints, 24th Conf. on Hurricane and Tropical Meteorology, Fort Lauderdale, FL, Amer. Meteor. Soc., 446–447.

  • Grody, N. C., C. M. Hayden, C. C. Shen, P. W. Rosenkranz, and D. H. Staelin, 1979: Typhoon June winds estimated from scanning microwave spectrometer measurements at 55.45 GHz. J. Geophys. Res.,84, 3689–3695.

  • ——, F. Weng, and R. Ferraro, 2000: Application of AMSU for obtaining hydrological parameters, Microwave Radiometry and Remote Sensing of the Earth’s Surface and Atmosphere, P. Pampaloni and S. Paloscia, Eds., VSP, 339–351.

  • Hawkins, H. F., and S. M. Imbembo, 1976: The structure of a small, intense hurricane—Inez 1966. Mon. Wea. Rev.,104, 419–442.

  • Hirschberg, P. A., and A. M. Fritsch, 1993: On understanding height tendency. Mon. Wea. Rev.,121, 2646–2661.

  • Jarvinen, B. R., C. J. Neumann, and M. A. S. Davis, 1984: A tropical cyclone data tape for the North Atlantic Basin, 1886–1983. NOAA Tech. Memo. NWS NHC 22, 21 pp.

  • Kidder, S. Q., W. M. Gray, and T. H. VonderHaar, 1978: Estimating tropical cyclone central pressure and outer winds from satellite microwave data. Mon. Wea. Rev.,106, 1458–1464.

  • ——, ——, and ——, 1980: Tropical cyclone surface winds derived from satellite microwave sounder data. Mon. Wea. Rev.,108, 144–152.

  • Klein, J. A., and C. T. Swift, 1977: An improved model for the dielectric constant of sea water at microwave frequencies. IEEE J. Oceanic Eng.,OE-2, 104–111.

  • Liu, Y., D.-L. Zhang, and M. K. Yau, 1997: A multiscale numerical study of Hurricane Andrew (1992). Part I: Explicit simulation and verification. Mon. Wea. Rev.,125, 3073–3093.

  • Merrill, R. T., 1995: Simulations of physical retrieval of tropical cyclone thermal structure using 55-GHz band passive microwave observations from polar-orbiting satellites. J. Appl. Meteor.,34, 773–787.

  • Mo, T., 1996: Prelaunch calibration of the Advanced Microwave Sounding Unit-A for NOAA-K. IEEE Trans. Microwave Theory Techniques,44, 1460–1469.

  • Nunez, E., and W. M. Gray, 1977: A comparison between West Indies hurricanes and Pacific typhoons. Postprints, 11th Tech. Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 528–534.

  • Poe, G. A., 1990: Optimum interpolation of imaging microwave radiometer data. IEEE Trans. Geosci. Remote Sensing,GE-28, 800–810.

  • Smith, E. A., and Coauthors, 1998: Results of the WetNet PIP-2 project. J. Atmos. Sci.,55, 1483–1536.

  • Spencer, R. W., W. S. Olson, W. Rongzhang, D. W. Martin, J. A. Weinman, and D. A. Santek, 1983: Heavy thunderstorms observed over land by the Nimbus-7 Scanning Multichannel Microwave Radiometer. J. Climate Appl. Meteor.,22, 1041–1046.

  • ——, W. M. Lapenta, and F. R. Robertson, 1995: Vorticity and vertical motions diagnosed from satellite deep layer temperatures. Mon. Wea. Rev.,123, 1800–1810.

  • Velden, C. S., 1989: Observational analyses of North Atlantic tropical cyclones from NOAA polar-orbiting satellite microwave data. J. Appl. Meteor.,28, 59–70.

  • ——, 1992: Satellite-based microwave observations of tropopause-level thermal anomalies: Qualitative applications in extratropical cyclone events. Wea. Forecasting,7, 669–682.

  • ——, and W. L. Smith, 1983: Monitoring tropical cyclone evolution with NOAA satellite microwave observations. J. Climate Appl. Meteor.,22, 714–724.

  • ——, B. M. Goodman, and R. T. Merrill, 1991: Western North Pacific tropical cyclone intensity estimation from NOAA polar-orbiting satellite microwave data. Mon. Wea. Rev.,119, 159–168.

  • Wilheit, T. T., and Coauthors, 1982: Microwave radiometric observation near 19.35, 92, and 183 GHz of precipitation in Tropical Storm Cora. J. Appl. Meteor.,21, 1137–1145.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1908 1639 196
PDF Downloads 235 57 4