• Ackinson, G. D., and C. R. Holiday, 1977: Tropical cyclone minimum sea level pressure/maximum sustained wind relationship for the western North Pacific. Mon. Wea. Rev.,105, 421–471.

  • Baik, J.-J., S.-M. Lee, and C. H. Cho, 1993: Examination of convective process representation and inertial stability in a tropical cyclone model J. Korean Meteor.,28, 308–323.

  • Black, P. G., and L. K. Shay, 1998: Observations of tropical cyclone intensity change due to air–sea interaction processes. Preprints, Symp. on Tropical Cyclone Intensity Change, Phoenix, AZ, Amer. Meteor. Soc., 161–168.

  • Burgett, W. S., and G. H. Trapp, 1999: Eye structure of Typhoon Paka as viewed by the Kwajalein Doppler Radar. Preprints, 23d Conf. on Hurricanes and Tropical Meteorology, Vol. 1, Dallas, TX, Amer. Meteor. Soc., 448–450.

  • Cecil, D. J., and E. J. Zipser, 1999: Relationships between tropical cyclone intensity and satellite-based indicators of inner core convection: 85-GHz ice-scattering signature and lightning. Mon. Wea. Rev.,127, 103–123.

  • Challa, M., and R. Pfeffer, 1980: Effects of eddy flux of angular momentum on model hurricane development. J. Atmos. Sci.,37, 1603–1618.

  • Charney, J. G., and A. Eliassen, 1964: On the growth of the hurricane depression. J. Atmos. Sci.,21, 68–75.

  • Chen, L., and W. M. Gray, 1985: Global view of the upper level outflow patterns associated with tropical cyclone intensity changes during FGGE. Colorado State University, Atmospheric Science Paper 392, 1216 pp. [Available from Colorado State University, Fort Collins, CO 80523.].

  • Christian, H. J., R. J. Blakeslee, and S. J. Goodman, 1992: Lightning imaging sensor (LIS) for the earth observing system. NASA TM-4350, 44 pp. [Available from Center for Aerospace Information, P.O. Box 8757, International Airport, Baltimore, MD 21240.].

  • DeMaria, M., and J. Kaplan, 1994: A Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic basin. Wea. Forecasting,9, 209–220.

  • ——, ——, and M. M. Huber, 1998: The effect of vertical shear on tropical cyclone intensity change: An historical perspective. Preprints, Symp. on Tropical Cyclone Intensity Change, Phoenix, AZ, Amer. Meteor. Soc., 22–29.

  • ——, ——, J.-J. Baik, and J. Kaplan, 1993: Upper-level eddy angular momentum fluxes and tropical cyclone intensity change. J. Atmos. Sci.,50, 1183–1147.

  • Des Jardins, M., K. Brill, and S. Schots, 1991: Use of GEMPAK on Unix Workstations. Preprints, Seventh Int. Conf. on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, New Orleans, LA, Amer. Meteor. Soc., 449–451.

  • Dvorak, V. F., 1975: Tropical cyclone intensity analyses and forecasting from satellite imagery. Mon. Wea. Rev.,103, 420–430.

  • Emanuel, K. A., 1986: An air–sea interaction theory for tropical cyclones. Part I: Steady-state maintenance. J. Atmos. Sci.,43, 585–604.

  • Fishman, J., and J. C. Larsen, 1987: Distribution of total ozone and stratospheric ozone in the tropics. Implication for the distribution of tropospheric ozone. J. Geophys. Res.,92, 6627–6634.

  • Fitzpatrick, P. J., 1996: Understanding and forecasting tropical cyclone intensity change. Colorado State University, Atmospheric Science Paper 598, 346 pp. [Available from Colorado State University, Fort Collins, CO 80523.].

  • Frank, W. M., 1977: The structure and energetics of the tropical cyclone. Part I: Storm structure. Mon. Wea. Rev.,105, 1119–1135.

  • Gaby, D. C., J. B. Sushine, R. M. Mayfield, S. C. Pearce, and F. E. Torres, 1980: Satellite classification of Atlantic tropical and subtropical cyclones: A review of eight years of classification at Miami. Mon. Wea. Rev.,108, 587–595.

  • Gray, W. M., 1979: Hurricanes: Their formation, structure, and likely role in the tropical circulation. Meteorology over the Tropical Oceans, D. B. Shaw, Ed., Roy. Meteor. Soc., 155–218.

  • Hollinger, J. O., 1991: DMSP Special Sensor Microwave/Imager calibration/validation. Final Report Vol. 11, 1225 pp. [Available from J. O. Hollinger, Naval Research Laboratory, Washington, DC 20375].

  • Kummerow, C., W. S. Olson, and L. Giglio, 1996: A simplified scheme for obtaining precipitation and vertical hydrometeor profiles from passive microwave sensors. IEEE Trans. Geosci. Remote Sens.,34, 1213–1232.

  • ——, W. Barnes, T. Kozu, J. Shine, and J. Simpson, 1998: The Tropical Rainfall Measuring Mission (TRMM) sensor package. J. Atmos. Oceanic Technol.,15, 809–817.

  • Lee, C. S., 1986: An observational study of tropical cloud cluster evolution and cyclogenesis in the western North Pacific. Colorado State University, Atmospheric Science Paper 403, 250 pp. [Available from Colorado State University, Fort Collins, CO 80523.].

  • Lyons, W. A., and C. S. Keen, 1994: Observations of lightning in convective supercells within tropical storms and hurricanes. Mon. Wea. Rev.,122, 1897–1916.

  • Marks, F. D., 1985: Evolution of the structure of precipitation in Hurricane Allen (1980). Mon. Wea. Rev.,113, 909–930.

  • ——, and R. A. Houze, 1987: Inner-core structure of Hurricane Alicia from airborne Doppler radar observations. J. Atmos. Sci.,44, 1296–1317.

  • McPeters, R. D., S. M. Hollandsworth, L. E. Flynn, J. R. Herman, and C. J. Seltor, 1996: Long-term ozone trends derived from the 16-year combined Nimbus-7/Meteosat-3 TOMS version 7 record. Geophys. Res. Lett.,23, 3099–3702.

  • Merrill, R. T., 1988: Environmental influence on hurricane intensification. J. Atmos. Sci.,45, 1678–1687.

  • Molinari, J., and S. Skubis, 1985: Evolution of the surface wind field in an intensifying tropical cyclone. J. Atmos. Sci.,42, 2865–2879.

  • ——, and D. Vollaro, 1989: External influences on hurricane intensity. Part I: Outflow layer eddy momentum fluxes. J. Atmos. Sci.,46, 1093–1105.

  • ——, ——, ——, R. W. Henderson, and A. B. Saljoughy, 1994: Cloud-to-ground lightning in Hurricane Andrew. J. Geophys. Res.,99, 16 665–16 676.

  • Moller, J. D., and M. T. Montgomery, 1999: Vortex Rossby waves and hurricane intensification in a barotropic model. J. Atmos. Sci.,56, 1674–1687.

  • Morales, C. A., J. S. Kriz, E. B. Rodgers, and J. A. Weinman, 1997:The evolution of sferics around Hurricane Lilli-1996. Preprints, 22d Conf. on Hurricanes and Tropical Meteorology, Fort Collins, CO, Amer. Meteor. Soc., 127–128.

  • Mundell, D. B., 1991: Tropical cyclone intensification. Preprints, 19th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 511–515.

  • Olson, W. S., C. D. Kummerow, G. M. Heymsfield, and L. Giglio, 1996: A method for combined passive–active microwave retrievals of cloud and precipitation profiles. J. Appl. Meteor.,35, 1763–1789.

  • ——, ——, Y. Hong, and W.-K. Tao, 1999: Atmospheric latent heating distributions in the Tropics derived from satellite passive microwave radiometer measurements. J. Appl. Meteor.,38, 633–664.

  • Ooyama, K. V., 1964: A dynamical model for the study of tropical cyclone development. Geifus. Int.,4, 187–198.

  • Orville, R. E., R. A. Weisman, R. B. Pyle, R. W. Henderson, and R. E. Orville, 1987: Cloud-to-ground lightning flashes characteristics from June 1994 through May 1995. J. Geophys. Res.92 (D5), 5640–6544.

  • Petty, G. W., and K. B. Katsaros, 1990: New geophysical algorithms for the Special Sensor Microwave Imager. Preprints, Fifth Int. Conf. on Satellite Meteorology and Oceanography, London, United Kingdom, Amer. Meteor. Soc., 247–251.

  • Reed, R. J., A. Hollingsworth, W. A. Heckley, and F. Delsol, 1988: An evaluation of the performance of the ECMWF operational system in analyzing and forecasting easterly wave disturbances over Africa and the tropical Atlantic. Mon. Wea. Rev.,116, 824–865.

  • Reuter, G. W., and M. K. Yau, 1986: Numerical modeling of cloud development in a shear environment. Beitr. Phys. Atmos.,66, 65–80.

  • Rodgers, E. B., and H. F. Pierce, 1995: Environmental influence on Typhoon Bobbie’s precipitation distribution. J. Appl. Meteor.,34, 2515–2532.

  • ——, J. Stout, J. Steranka, and S. Chang, 1990: Tropical cyclone–upper atmospheric interaction as inferred from satellite total ozone observations. J. Appl. Meteor.,29, 934–954.

  • ——, S. W. Chang, J. Stout, J. Steranka, and J.-J. Shi, 1991: Satellite observations of variations in tropical cyclone convection caused by upper-tropospheric troughs. J. Appl. Meteor.,30, 1163–1184.

  • ——, ——, and H. F. Pierce, 1994a: A satellite observational and numerical study of the precipitation characteristics in western North Atlantic tropical cyclones. J. Appl. Meteor.,33, 129–139.

  • ——, J.-J. Baik, and H. F. Pierce, 1994b: The environmental influence on tropical cyclone precipitation. J. Appl. Meteor.,33, 573–593.

  • ——, W. S. Olson, V. M. Karyampudi, and H. F. Pierce, 1998: Satellite-derived latent heating distribution and environmental influences in Hurricane Opal (1995). Mon. Wea. Rev.,126, 1229–1247.

  • Shaw, D. B., P. Lonnberg, A. Hollingsworth, and P. Unden, 1987: Data assimilation: The 1984/1985 revisions of the ECMWF mass and wind analysis. Quart. J. Roy. Meteor. Soc.,113, 533–566.

  • Shay, L. K., O. G. Black, A. J. Mariano, J. D. Hawkins, and R. L. Exlberry, 1992: Upper ocean response to hurricane Gilbert. J. Geophy. Res.,97, 20 227–20  248.

  • Shi, J.-J., S. W. Chang, and S. Raman, 1990: A numerical study of the outflow layer of tropical cyclones. Mon. Wea. Rev.,118, 2042–2055.

  • Simpson, J., Ed., 1988: Report of the Science Steering Group for a Tropical Rainfall Measurement Mission (TRMM). U.S. Government Printing Office, 94 pp.

  • ——, C. Kummerow, W.-K. Tao, and R. F. Adler, 1996: On the Tropical Rainfall Measurement Mission (TRMM). Meteor. Atmos. Phys.,60, 19–36.

  • Weatherford, C., 1987: Typhoon structural evolution. Preprints, 17th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 337–340.

  • Willoughby, H. E., 1988: The dynamics of the tropical cyclone core. Aust. Meteor. Mag.,36, 183–191.

  • ——, 1990: Temporal changes of the primary circulation in tropical cyclones. J. Atmos. Sci.,47, 242–264.

  • ——, J. A. Clox, and M. G. Shoreibah, 1982: Concentric eye-walls, secondary wind maxima, and the evolution of the hurricane vortex. J. Atmos. Sci.,39, 395–411.

  • Wu, C.-C., and H.-J. Chang, 1999: An observational study of environmental influences on the intensity changes of Typhoons Flow (1990) and Gene (1990). Mon. Wea. Rev.,127, 3003–3031.

  • View in gallery

    Best-track location and intensity (see legend) for Tropical Cyclone Paka between 8 and 22 Dec 1997

  • View in gallery

    Paka’s intensity (dashed line, m s−1) and SSM/I (open circle) and TMI-derived (×) mean total (i.e., combined stratified and convectively generated rain rates) inner-core (within 111 km of the center) rain rates (solid line, mm h−1) for the period between 9 and 21 Dec 1997

  • View in gallery

    Paka’s SSM/I–TMI-derived mean total inner-core rain rates (solid line, mm h−1) interpolated for every 6 h and the size of the eye (dashed line, km) determined from GMS IR data for the period between 9 and 21 Dec 1997

  • View in gallery

    Plan views of the SSM/I horizontal-polarized 85-GHz TB of Paka during 15–16 Dec 1997. The coldest TBs represent the greatest scattering caused by ice. Adapted from the Naval Research Laboratory

  • View in gallery

    Paka’s SSM/I–TMI-derived mean total inner-core rain rates (solid line, mm h−1) interpolated for every 6 h and the mean inner-core cloud-top TBB (K) determined from GMS IR data for the period between 9 and 21 Dec 1997

  • View in gallery

    Paka’s SSM/I–TMI-derived inner-core mean total (solid line, mm h−1) and convective generated rain rates (dashed lines, mm h−1) interpolated for a 6-h interval during the period between 9 and 21 Dec 1997

  • View in gallery

    Time–radius view of Paka’s azimuthally averaged SSM/I–TMI-derived convective generated rain rates (contours of rain rate are shown: mm h−1) interpolated for every 6 h and 6-h maximum winds (m s−1) for the period between 9 and 21 Dec 1997. Rain rates were azimuthally averaged for annuli 55 km in width extending 444 km outward from the center. The greatest rain rates are delineated by the warmest colors

  • View in gallery

    Plan view of Paka’s convectively generated rain rates (mm h−1) from the SSM/I and TMI observations at 0509 UTC on 13 Dec, 0831 UTC on 14 Dec, 0817 and 2149 UTC on 15 Dec, and 1435 and 2243 UTC on 16 Dec 1997 during Paka’s CRB cycle. Gray background is nonraining SSM/I–TMI observations, and the colors indicated rain rates of different intensities (see color bar). Radial rings are 1° latitude interval centered on Paka’s center

  • View in gallery

    A radial–height display of the azimuthally averaged SSM/I–TMI-derived total LHR (W m−3) for the same CRB cycle seen in Fig. 8. Latent heating was azimuthally averaged for annuli 55 km in width extending 333 km outward from the center. Noncolored regions (i.e., regions of negative latent heating) indicate a loss of latent heat due to evaporation. Contour interval is given in the figure. The darker the colors, the greater the latent heating

  • View in gallery

    A plan view of Paka’s CDO regions (Paka’s eye delineated by a darker shade point within the CDO) obtained from a GMS IR image at 1832 UTC on 12 Dec 1997 superimposed upon the OTD (white background cross) and LIS (no background cross) observed lightning strokes during 12 Dec

  • View in gallery

    Paka’s SSM/I–TMI-derived total (solid line) inner-core rain rates (mm h−1) interpolated for every 6 h and the 12-h interval SSTs (°C) for the period between 9 and 21 Dec 1997

  • View in gallery

    Paka’s SSM/I–TMI-derived total (solid line) inner-core rain rates (mm h−1) interpolated for every 6 h and the 12-h interval vertical wind shear (m s−1) for the period between 9 and 21 Dec 1997

  • View in gallery

    The SSM/I-observed (left) total precipitable water (TPW, mm) and the ECMWF-derived (right) TPW and 850-hPa winds for the environment surrounding Paka at approximately 2200 UTC on 16 Dec 1997. The white dot designates Paka’s center. Contour intervals of TPW are given by color bar. Black in the SSM/I observations denotes the raining areas where TPW cannot be observed from this sensor

  • View in gallery

    A time–azimuthal display of Paka’s outer core (i.e., greater than 333 km from the center) ECMWF-derived 850-hPa HMF (g kg−1 m s−1) for 8–21 Dec 1997. Contours of HMF are given in the figure. The darker shades delineate the larger HMF values

  • View in gallery

    Paka’s SSM/I–TMI-derived azimuthally averaged total (solid line) outer-core rain rates (mm h−1) interpolated for a 6-h interval and the 12-h interval total (integrated between 1000 and 400 hPa) moisture flux (HMF, 105 kg s−1) at the radius of 333 km from Paka’s center for the period between 9 and 21 Dec 1997. Rain rates were averaged over an annulus whose outer and inner radius are 333 and 265 km, respectively. Shaded regions delineate negative HMF values

  • View in gallery

    Time–latitude distance view of the 150-hPa geopotential heights (m) that Paka traversed during the period of 9–21 Dec 1997. Distance perpendicular to best-track path of Paka (delineated by thick black line) are in positive and negative degrees of latitude depending, respectively, on whether one moves to the right or left of Paka direction of motion. Contours are given in figure. Darker shades designate higher geopotential heights

  • View in gallery

    Time–latitude distance view of the 100–200-hPa potential vorticity (PV × 10−7 hPa s−1) that Paka traversed during the period of 9–21 Dec 1997. Distance perpendicular to best-track path of Paka (delineated by thick black line) are in positive and negative degrees of latitude depending, respectively, whether one moves to the right or left of Paka direction of motion. Contours are given in figure. Darker shades designate higher PV values

  • View in gallery

    Paka’s SSM/I–TMI-derived total (solid line) inner-core rain rates (mm h−1) interpolated every 6 h and the 12-h interval azimuthally averaged 200-hPa eddy-relative angular momentum flux convergence (ERFC, m s−1 day−1) for the period between 9 and 21 Dec 1997. ERFC was azimuthally averaged over annuli whose outer and inner radii are, respectively, 1000 and 600 km from the center of Paka. Shaded regions delineate regions of eddy relative angular momentum flux divergence

  • View in gallery

    Time–distance view of the azimuthally averaged 200-hPa ERFC (m s−1 day−1) for the period between 9 and 21 Dec 1997. ERFC is azimuthally averaged over annuli whose widths are 100 km that extend outward from Paka’s center from 100 to 1000 km. Contours are given in figure. Darker shades designate higher ERFC values

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 112 112 8
PDF Downloads 18 18 6

Environmental Forcing of Supertyphoon Paka’s (1997) Latent Heat Structure

View More View Less
  • 1 Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland
  • | 2 Joint Center for Earth Systems Technology, University of Maryland, Baltimore County, Baltimore, Maryland, and NASA Goddard Space Flight Center, Greenbelt, Maryland
  • | 3 Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland
  • | 4 Science and Systems Applications, Inc., Lanham, Maryland
© Get Permissions
Full access

Abstract

The distribution and intensity of total (i.e., combined stratified and convective processes) rain rate/latent heat release (LHR) were derived for Tropical Cyclone Paka during the period 9–21 December 1997 from the F-10, F-11, F-13, and F-14 Defense Meteorological Satellite Special Sensor Microwave Imager and the Tropical Rainfall Measuring Mission Microwave Imager observations. These observations were frequent enough to capture three episodes of inner-core convective bursts and a convective rainband cycle that preceded periods of rapid intensification. During these periods of convective bursts, satellite sensors revealed that the rain rates/LHR 1) increased within the inner-core region, 2) were mainly convectively generated (nearly a 65% contribution), 3) propagated inward, 4) extended upward within the mid- and upper troposphere, and 5) became electrically charged. These factors may have increased the areal mean ascending motion in the mid- and upper-troposphere eyewall region, creating greater cyclonic angular momentum, and, thereby, warming the center and intensifying the system.

Radiosonde measurements from Kwajalein Atoll and Guam, sea surface temperature observations, and the European Centre for Medium-Range Forecasts analyses were used to examine the necessary and sufficient conditions for initiating and maintaining these inner-core convective bursts. For example, the necessary conditions such as the atmospheric thermodynamics [i.e., cold tropopause temperatures, moist troposphere, and warm SSTs (>26°C)] fulfill the necessary conditions and suggested that the atmosphere was ideally suited for Paka’s maximum potential intensity to approach supertyphoon strength. Further, Paka encountered moderate vertical wind shear (<15 m s−1) before interacting with the westerlies on 21 December. The sufficient conditions that include horizontal moisture and the upper-tropospheric eddy relative angular momentum fluxes, on the other hand, appeared to have some influence on Paka’s convective burst. However, the horizontal moisture flux convergence values in the outer core were weaker than some of the previously examined tropical cyclones. Also, the upper-tropospheric outflow generation of eddy relative angular momentum flux convergence was much less than that found during moderate tropical cyclone–trough interaction. These results indicated how important the external necessary condition and the internal forcing (i.e., convective rainband cycle) were in generating Paka’s convective bursts as compared with the external sufficient forcing mechanisms found in higher-latitude tropical cyclones. Later, as Paka began to interact with the westerlies, both the necessary (i.e., strong vertical wind shear and colder SSTs) and sufficient (i.e., dry air intrusion) external forcing mechanisms helped to decrease Paka’s rain rate.

* Deceased.

Corresponding author address: Dr. Joanne Simpson, Chief Scientist for Meteorology, Earth Science Directorate, Code 912, Bldg. 33, Rm. C407, NASA Goddard Space Flight Center, Greenbelt, MD 20771.

simpson@agnes.gsfc.nasa.gov

Abstract

The distribution and intensity of total (i.e., combined stratified and convective processes) rain rate/latent heat release (LHR) were derived for Tropical Cyclone Paka during the period 9–21 December 1997 from the F-10, F-11, F-13, and F-14 Defense Meteorological Satellite Special Sensor Microwave Imager and the Tropical Rainfall Measuring Mission Microwave Imager observations. These observations were frequent enough to capture three episodes of inner-core convective bursts and a convective rainband cycle that preceded periods of rapid intensification. During these periods of convective bursts, satellite sensors revealed that the rain rates/LHR 1) increased within the inner-core region, 2) were mainly convectively generated (nearly a 65% contribution), 3) propagated inward, 4) extended upward within the mid- and upper troposphere, and 5) became electrically charged. These factors may have increased the areal mean ascending motion in the mid- and upper-troposphere eyewall region, creating greater cyclonic angular momentum, and, thereby, warming the center and intensifying the system.

Radiosonde measurements from Kwajalein Atoll and Guam, sea surface temperature observations, and the European Centre for Medium-Range Forecasts analyses were used to examine the necessary and sufficient conditions for initiating and maintaining these inner-core convective bursts. For example, the necessary conditions such as the atmospheric thermodynamics [i.e., cold tropopause temperatures, moist troposphere, and warm SSTs (>26°C)] fulfill the necessary conditions and suggested that the atmosphere was ideally suited for Paka’s maximum potential intensity to approach supertyphoon strength. Further, Paka encountered moderate vertical wind shear (<15 m s−1) before interacting with the westerlies on 21 December. The sufficient conditions that include horizontal moisture and the upper-tropospheric eddy relative angular momentum fluxes, on the other hand, appeared to have some influence on Paka’s convective burst. However, the horizontal moisture flux convergence values in the outer core were weaker than some of the previously examined tropical cyclones. Also, the upper-tropospheric outflow generation of eddy relative angular momentum flux convergence was much less than that found during moderate tropical cyclone–trough interaction. These results indicated how important the external necessary condition and the internal forcing (i.e., convective rainband cycle) were in generating Paka’s convective bursts as compared with the external sufficient forcing mechanisms found in higher-latitude tropical cyclones. Later, as Paka began to interact with the westerlies, both the necessary (i.e., strong vertical wind shear and colder SSTs) and sufficient (i.e., dry air intrusion) external forcing mechanisms helped to decrease Paka’s rain rate.

* Deceased.

Corresponding author address: Dr. Joanne Simpson, Chief Scientist for Meteorology, Earth Science Directorate, Code 912, Bldg. 33, Rm. C407, NASA Goddard Space Flight Center, Greenbelt, MD 20771.

simpson@agnes.gsfc.nasa.gov

Introduction

Tropical cyclone case studies of Hurricane Opal (Rodgers et al. 1998); Typhoon Bobbie (Rodgers and Pierce 1995); and Hurricanes Dean, Gabrielle, and Hugo (Rodgers et al. 1994a,b) that used the F-10, F-11, F-13, and the F-14 Defense Meteorological Satellite Program’s (DMSP) Special Sensor Microwave Imager (SSM/I) helped to estimate cloud microphysics of these systems, while the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses were used to derive tropical cyclone environmental forcing mechanisms. Results from these studies suggested the following.

First, the increase of the eyewall/inner core [within 111-km radius of tropical cyclone center (Weatherford 1987)] latent heat appeared to be enhanced by the inward propagation of the convective rainband (CRB) cycles (Willoughby 1988, 1990; Willoughby et al. 1982) cycles and/or by the generation of convective bursts. A convective burst is defined in this and previous papers as a mesoscale (i.e., 100 km by hours) system consisting of a cluster of high cumulonimbus towers within the inner-core region that approaches or reaches the tropopause with nearly undiluted cores.

Second, in ocean regions where sea surface temperatures (SSTs) were warmer than 26°C, the tropospheric conditions were uniformly moist, the vertical wind shear was less than 10 m s−1, and the inner-core convective bursts and CRB cycles appeared to be initiated by lower-tropospheric horizontal moisture flux convergence and/or by the gradient wind adjustment processes associated with the thermally direct circulation in the entrance regions of the upper-tropospheric outflow channel (Challa and Pfeffer 1980; Merrill 1988; Chen and Gray 1985; Molinari and Vollaro 1989; Shi et al. 1990; Rodgers et al. 1991; DeMaria et al. 1993).

Last, the presence of either multiple inner-core convective bursts or CRB cycles may initiate a period of intensification depending on the strength of its low- to mid-tropospheric inertial stability. The mechanism of how enhanced latent heat release (LHR) near the center of circulation intensifies these tropical cyclones is not well understood, but there have been some interesting hypotheses. One theory that appears to be applicable for this study states that the wind adjusts to the mass, as documented by Fitzpatrick (1996). His theory suggests that the increased eyewall areal mean ascending motion created by the excess latent heating in the inertially stable inner-core vortex could help to compensate for the loss of eyewall cyclonic angular momentum due to surface friction and upper-tropospheric outward transport. The upward transport of cyclonic angular momentum could increase the cyclonic tangential circulation aloft and thereby warm the upper-tropospheric eye through the thermal wind balance and geostrophic adjustment processes or by forced eye subsidence. The induced warming in the upper-tropospheric eye, in turn, could hydrostatically lower the surface pressure, enhance the mid- and lower-tropospheric cyclonic vortex, increase the momentum and moisture influx, and intensify the system.

However, the Opal analyses (Rodgers et al. 1998) was the only case study for which there were a sufficient number of SSM/I observations to resolve the large-scale rain-rate oscillations. Furthermore, the majority of the previous studies did not incorporate other remotely sensed data that helped validate the hypotheses concerning cloud microphysics and sparse upper-tropospheric circulation observations.

This case study differs from previous ones by employing the following additional satellite-borne sensors. First, the monitoring of the evolution of Paka’s spatial distribution of rain rate and LHR profiles by SSM/Is will be improved by adding the Tropical Rainfall Measuring Mission’s (TRMM) Microwave Imager (TMI) observations. Second, lightning data obtained from the optical transient detector (OTD) sensor and the TRMM Lightning Imaging Sensor (LIS) will help assess the electrically active convective regions of Paka. Finally, the Earth Probe Total Ozone Mapping Spectrometer (TOMS) and the Geostationary Meteorological Satellite (GMS)–derived upper-tropospheric water vapor and water vapor winds will help to substantiate the ECMWF analyses of the upper-tropospheric circulation.

In this paper, section 2 describes the satellites and their sensors, the satellite-observed parameters, and how these parameters are obtained. Section 3 includes a description of the environmental forcing parameters obtained from the Goddard Data Assimilation Office (DAO) and the ECMWF analyses. A brief narration of the time history of Tropical Cyclone Paka is presented in section 4, while section 5 details the evolution of the distribution of Paka’s total rain rate/LHR and lightning and its relationship to intensity change. Section 6 identifies possible environmental parameters that favor Paka’s rain rate/latent heat production and its subsequent intensification. Last, a summary and discussion of the Paka case study is presented in section 7.

Satellite-observed parameters

Table 1 lists the satellites, the sensors, and the satellite-derived parameters that are utilized in this study. The SSM/I is employed to estimate rain rate, LHR, and total precipitable water (TPW), while the TMI is used to only estimate rain rate and LHR. The OTD and LIS monitor Paka’s electric activity. These satellite observations also help to qualitatively assess the ascending motion of the convective regions of Paka. The SSM/I-derived TPW is employed to justify the ECMWF-derived moisture distribution. The rapid observations from the GMS-observed infrared (11.5-μm window channel) blackbody temperatures (TBB) are utilized to estimate Paka’s lower- and upper-tropospheric winds, intensity [using the Dvorak technique (Dvorak 1975)], eye size, and to qualitatively verify whether SSM/I and TMI observations are capturing the major temporal changes of Paka’s mean rain rate. Finally, the GMS-observed upper-tropospheric water vapor and derived water vapor winds as well as the Earth Probe TOMS-estimated total ozone help to qualitatively verify the ECMWF-derived upper-tropospheric environmental circulation. Further information concerning the OTD, LIS, TOMS, and GMS sensors and their derived parameters can be found in appendix A.

SSM/I-estimated rain rate and LHR parameters

The F-11, F-13, and F-14 DMSP SSM/Is

The SSM/Is aboard DMSP F-11, F-13, and F-14 satellites that were launched, respectively, in November 1992, May 1995, and April 1997 measure scattered and emitted microwave radiation at frequencies of 19.35, 22.25, 37.0, and 85.5 GHz. All channels except the 22.2-GHz channel are dual polarized. The SSM/Is complete 14.1 revolutions per day along a nearly sun-synchronous polar orbit at an altitude of 833 km. The approximate times that the ascending branches of the DMSP F-11, F-13, and F-14 orbits pass over the equator at 165°E (i.e., the approximate location of Tropical Cyclone Paka during 9–22 December 1997) are, respectively, 0800, 0700, 0900 UTC, while the descending branches occur 12 h later. The SSM/Is scan conically at a constant 45° angle from nadir and have an observational swath width of nearly 1400 km at the earth’s surface. Further information concerning the SSM/I sensor and measurements may be found in Hollinger (1991).

SSM/I-estimated rain rates, convective rain fraction, and latent heating profiles

The surface rain rate, convective rain fraction, and latent heating profiles are retrieved from all the SSM/I channels by employing the Goddard Profiling Algorithm (GPROF). This algorithm uses the estimated expected value, or “Bayesian” method described by Kummerow et al. (1996) and Olson et al. (1996, 1999). All three parameters are retrieved at a horizontal resolution of 12.5 km × 12.5 km. The surface rain rates are defined as the average rain rate over the 12.5 km × 12.5 km area centered on the SSM/I observation.

The convective rain fraction is the fraction of the surface rain rate associated with significant cloud updrafts and downdrafts (|W| > 1 m s−1). The LHR at a given level is the net energy release per unit volume of air due to hydrometeor phase changes (i.e., condensation/evaporation, deposition/sublimation, and freezing/melting), averaged over the same 12.5 km × 12.5 km area. Further description of the retrieval method and supporting numerical atmospheric model simulations are found in the appendix of Rodgers et al. (1998) and Olson et al. (1999).

SSM/I-estimated total precipitable water (TPW)

The SSM/I-estimated TPW over ocean regions is derived from all algorithm developed by Petty and Katsaros (1990). The algorithm is based upon a logarithmic regression equation relating rawindsonde-observed TPW to the SSM/Is dual-polarized 19.35-GHz channel and vertically polarized 23.25-GHz channel. The SSM/I algorithm cannot retrieve TPW over land and in raining ocean areas.

TMI-estimated rain rate and LHR parameters

The TRMM TMI

The TRMM-based TMI was launched in November 1997 and measures scattered and emitted microwave radiation at frequencies of 10.7, 19.4, 21.3, 37.0, and 85.5 GHz. All channels, except the 21.3-GHz channel, are dual polarized. The TRMM satellite has a circular orbit with an altitude of 350 km, an inclination of 35° to the equator, and observes a swath width of 790 km at the earth’s surface. Diffraction effects and the fixed antenna size of the TMI cause the instantaneous field of view (IFOV) to increase with decreasing channel frequency. For example, the 85.5-GHz channel IFOV is 4.4 km, while IFOV of the 10.7-GHz channel is 40 km. The satellite completes 16 orbits per day, and the TRMM orbit precesses such that Paka’s overpass times vary during the study period. Further information concerning the TMI sensor and measurements may be found in Simpson et al. (1996); Simpson (1988), and Kummerow et al. (1998).

TMI-estimated rain rates, convective rain fraction, and latent heating profiles

The TMI-derived surface rain rate, convective rain fraction, and latent heating rate profile are retrieved using the same SSM/I algorithm (i.e., GPROF). However, the surface rain rates are averaged over a 10.0 km × 10.0 km area centered on the TMI observation. Other TMI observational differences are the improved IFOV and the employment of the 10.7-GHz channel in its algorithm. Further description of the SSM/I retrieval method and supporting numerical atmospheric model simulations are found in the appendix of Rodgers et al. (1998) and in Olson et al. (1999).

Model-derived and archived environmental and tropical cyclone parameters

Table 2 lists the parameters that are estimated and derived, respectively, from the Goddard Center Analyses Office (DAO) archives and the ECMWF analyses. A brief description of these parameters is as follows.

Sea surface temperature

To determine whether the SSTs are warm enough (i.e., SST > 26°C) to allow for sufficient moist static energy flux to support convection in Tropical Cyclone Paka, mean weekly SSTs within the regions that Paka traversed are examined. The weekly mean SSTs on a 1.0° latitude × 1.0° longitude grid are obtained from National Centers for Environmental Prediction analyses that are archived at Goddard’s DAO. The SSTs that Paka traversed are estimated for a given location by interpolating the SSTs near the center of Paka at a 12-h interval from the given weekly SSTs. To eliminate discontinuities in the SSTs between the weeks, the SSTs at each 12-h interval are time weighted between the weekly means.

ECMWF-derived environmental parameters

The upper- and lower-tropospheric external environmental forcing mechanisms are also examined for their role in initiating, maintaining, and inhibiting Paka’s total rain rate/LHR. The forcing mechanisms analyzed in this study are the vertical wind shear, the lower-tropospheric horizontal moisture flux, and the upper-tropospheric gradient wind adjustment processes associated with Paka’s outflow jet-induced eddy-relative angular momentum flux convergence (ERFC). These external forcing parameters are similar to those used in the National Oceanic and Atmospheric Administration’s (NOAA) Statistical Hurricane Intensity Prediction Scheme (DeMaria and Kaplan 1994), except for the horizontal tropospheric moisture flux.

The upper- and lower-tropospheric parameters are obtained from the ECMWF (Shaw et al. 1987) diagnostic program. The ECMWF analyses are archived on a 2.5° latitude × 2.5° longitude grid and the environmental parameters are calculated every 12 h (i.e., at 0000 and 1200 UTC) by using the GEMPAK 5.1 (Des Jardins et al. 1991).

The preference of ECMWF analyses is based on the fact that the wind, height, and moisture fields are less noisy in data-void North Pacific regions and that the model employs NOAA, GMS, and Television and Infrared Observational Satellite (TIROS-N) Operational Vertical Sounder–observed temperature, thickness, and wind data in their analyses. It has also been shown that the model generates more accurate analyses of tropical systems over data-void eastern North Atlantic Ocean regions (Reed et al. 1988). However, because of the poor spatial resolution of the ECMWF analyses and the lack of observations, finer-scale features surrounding Paka’s central dense overcast (CDO) are not always captured. Nevertheless, the ECMWF analyses of the upper-tropospheric wind and lower-tropospheric TPW within Paka’s environment may be improved by using, respectively, the GMS-derived water vapor winds and TOMS-derived total ozone anomalies and the SSM/I-derived TPW. The ECMWF grid analyses at finer time and space resolution were not readily available for this study. A more detailed description of the parameters that are employed in this study can be found in appendix B.

Tropical Cyclone Paka

A region of organized convection that was associated with an equatorial westerly wind burst was first observed in late November during the strong El Niño of 1997 approximately 2000 km southwest of the Hawaiian Islands. The dual-cyclonic vorticity regions associated with the westerly wind burst led to the formation of twin tropical cyclones, one in the Southern Hemisphere named Pam and the other in the Northern Hemisphere named Paka. During the first week in December, Tropical Cyclone Paka, the system of concern, reached tropical storm stage as it moved rapidly west-northwestward over the open north-central Pacific at relatively low latitudes. The system reached typhoon stage on 10 December, supertyphoon stages on 15 and again on 18 December, and then quickly dissipated on 21 December. Typhoon Paka’s west-northwest movement across the central and western North Pacific during 9–21 December brought the system just south of the Majuro and Kwajalein Atolls between 10 and 12 December and just north of Guam on 16 December. A plan view of Paka’s location and intensity status during this time is shown in Fig. 1. Information concerning the intensity and position of Tropical Cyclone Paka can be found at the National Climate Data Center.

Time history of Paka’s rain rate, latent heating, and lightning distribution

Inner-core total rain rate versus intensity

To estimate the evolution of Paka’s inner-core mean-total rain rate, the SSM/I and TMI-derived rain rates are azimuthally averaged over the inner-core area. Figure 2 shows a time series of Paka’s maximum surface wind speeds every 6 h and the SSM/I (open circles) and TMI-derived (×) inner-core averaged rain rates. Between 9 and 21 December there were 9 SSM/I and 9 TMI observations, with at least one rain-rate observation during each day, except on 20 December.

It is seen in Fig. 2 that there are three episodes when the long-term trend in the inner-core areal mean-total rain rates increase significantly. These episodes occur approximately 10–12, 13–14, and 16–17 December. During the first episode, rain rates increased by more than 3 mm h−1, while during the second and third episodes they increased, respectively, by approximately 2 and 4 mm h−1. These three periods appear to precede the times of maximum surface winds. The figure also suggests that as Paka became more intense, the response time between enhanced rain rates and increased surface winds decreased. This increased response time has been suggested by Baik et al. (1993) to be related to the increase of the mid- and lower-tropospheric inner-core inertial stability, which is a function of tangential winds and Coriolis force.

Paka’s eye

By comparing the GMS infrared (IR) observed eye with the inner-core rain rates that have been interpolated (using a spline fit) over a 6-h interval (Fig. 3), the IR observations of Paka were used to detect the presence of an eye continuously at rapid intervals. The IR observations were able to detect an eye on 11, 14–15, and 17–18 December. It is seen from the figure that Paka’s eye was present during and preceding large increases of inner-core rain rates. The presence of an eye suggests that the areal mean ascending motion within the eyewall is strong enough to generate the horizontal convergence and subsidence necessary to warm the upper-tropospheric region of the eye and intensify the tropical cyclone.

However, due to the slant angle view of the eye from the GMS IR sensor, the strong sensitivity of the IR frequency to opaque cirrus, and the fact that the upper-tropospheric eyes of mature tropical cyclone sometimes slope inward with decreasing heights, the IR sensor cannot always accurately assess the size of an eye. For example, the Kwajalein Doppler radar (Burgett and Trapp 1999) indicated that Paka’s eye on 11 December was between 14- and 18-km radius, far larger than that observed in Fig. 3. It is also seen from the figure that the radius of the eye became progressively larger (i.e., 5 km on 11 December to 20 km on 17–18 December) as Paka intensified. During the later stages of development (17–18 December) when Paka’s maximum winds peaked, the eye radius reached its maximum radius. This finding is contrary to earlier observations.

A more accurate view of Paka’s eye size can be obtained from the SSM/I horizontal polarized 85-GHz TB observations. These observations allow one to measure a deeper layer of Paka’s upper-cloud microphysics, since cirrus is transparent at this frequency. An example of these images for Paka between 15 and 16 December is shown in Fig. 4. The figure shows that the eye was constricting, rather than expanding during intensification, as delineated by Fig. 3. These results are consistent with earlier studies.

The relationship between areal mean estimated rain rate and areal mean CDO TBB

Examining the SSM/I and TMI observations, it is not obvious that these observations are frequent enough to accurately delineate the large-scale oscillations in Paka’s inner-core averaged rain rates. If it is assumed that the increased ascending motion in the inner-core regions corresponds to colder mean CDO TBB and greater rain rates, it may be possible to qualitatively verify the large-scale relative change of Paka’s SSM/I and TMI-derived rain rates with the more frequently observed GMS IR-derived mean inner-core CDO TBB.

To qualitatively verify whether the SSM/I and TMI observations are capturing the major temporal changes of Paka’s inner-core mean rain rate, the 10% smoothed hourly observed GMS infrared (11.0 μm) mean TBB averaged over the inner-core region is compared to the evolution of the 6-h interval SSM/I and TMI-derived mean rain rate (Fig. 5). Considering the facts 1) that sampling the eye may overestimate the mean CDO TBB;2) that thick cirrus debris left by the initial convection may mask future lower active convective cells and, therefore, cause the minimum mean CDO TBB to precede the time of maximum mean rain rates; and 3) that the convective cells dissipate from the bottom upward, which causes the minimum mean CDO TBB to follow the time of maximum inner-core rain rate, there is reasonable consistency between these parameters. Except for the third episode of increasing rain rates on 17 December when the sampling of the infrared delineated large eye caused an overestimation of the CDO TBB, the trend in the GMS mean inner-core CDO TBB appears to capture the major changes in Paka’s inner-core mean rain rate. This mean inner-core CDO TBB curve in Fig. 5 suggests that there are frequent enough SSM/I and TMI observations to define the majority of the large timescale temporal changes in Paka’s inner-core rain-rate cycle.

Percent of convectively generated LHR in Paka’s inner core

It is seen in Fig. 6 that the trend of the rain rate generated by convective processes, although less, approximately mirrors the trend of total rain rate. The greatest percent of contribution was approximately 65%, which occurs during episodes of maximum total rain rate. These values were slightly less than that found with Tropical Cyclone Opal’s episodes of maximum total LHR (Rodgers et al. 1998), but consistent with those derived from airborne radar in earlier hurricane case studies (Marks 1985; Marks and Houze 1987). Since the greatest contribution of total rain rate was from convective processes during episodes of maximum total rain rates, these episodes will be referred to as convective bursts, as defined in the introduction and in the remainder of the text.

Radial–time distribution of Paka’s convective rain rate

To examine the temporal change of Paka’s horizontal distribution of convective rain rates during the period of 8–21 December 1997, all available SSM/I- and TMI-derived convective rain rates of Paka are azimuthally averaged over 16 annuli, each 27.5 km in width, extending outward from Paka’s center to 444-km radius. The averaged convective rain-rate values in each annulus are, again, interpolated to 6-h intervals using a spline fit and are presented in a time–radius format in Fig. 7. Also plotted with these azimuthally averaged rain rates are Paka’s 6-h interval maximum surface winds.

Although the convective rain rates are averaged over large annular areas, the evolution of the three periods of convective bursts is clearly delineated. Similar to what was seen in Fig. 2, Fig. 7 indicates that the periods of increasing inner-core rain rate precede the time of maximum surface winds. This inner-core rain-rate cycle and intensity relationship were also revealed in SSM/I observational studies of four 1989 western North Atlantic hurricanes (Rodgers et al. 1994a), western North Pacific Typhoon Bobbie (1992, Rodgers and Pierce 1995), and the Gulf of Mexico Hurricane Opal (1995; Rodgers et al. 1998). However, the poor spatial and temporal presentation of the rain rate data did make it difficult to ascertain the CRB cycles from this figure.

Plan views of Paka’s convective rain-rate distribution

To obtain clearer evidence that the second inner-core convective burst on 14 December exists and that the proposed CRB cycle on 15–16 December Fig. 8 is shown. The figure shows six plan views of the distribution of Paka’s convective rain rates during the period 13–16 December that was derived from SSM/I and TMI observations. The figure illustrates the following series of events. During the period between 0509 UTC on 13 December to 0831 UTC on 14 December, a crescent-shaped eyewall (rain rates > 20 mm h−1) expands and intensifies. Approximately 24 h later at 0817 UTC on 15 December, evidence of an outer-convective rainband (rain rates > 2 mm h−1) is seen on the outer edge (i.e., ∼165 km from the center of circulation) of the convective rain shield. During this time, the rain rates in the eyewall decrease in intensity. At 2149 UTC on 15 December, the outer-convective rainband appears to grows in area and propagates inward causing the rain rates in the eyewall to rapidly decrease. At 1425 UTC on 16 December, the new eyewall is formed as the outer CRB propagates inward toward the center where the reduction of the Rossby radius is great enough so that the latent heating is able to warm the upper troposphere. The new inner-core rainband, in turn, generates a well-developed eyewall with an open eye. Finally, at 2243 UTC on 16 December (the time of the third convective burst), rain rates in the eyewall rapidly intensify; however, the eyewall becomes more asymmetric and the eye rapidly decreases in size. These events, if they are actually occurring, are similar to those observed during CRB cycles described by Willoughby (1988, 1990) and Willoughby et al. (1982).

The clearest evidence that a CRB was present during the 15–16 of December is observed from the plan views of the evolution of the large convective ice amounts (darkest shade), as seen in Fig. 4. The plan views show an eyewall displacement at 0843 UTC on 15 December that dissipates and is replaced by a constricting outer-core convective rainband. As noted earlier, this rainband continues to propagate inward eventually forming the new eyewall.

The plan views of Paka’s convective rain distribution seen in Figs. 4 and 8 also show the symmetry of its eyewall. The figures clearly show that as the new eyewall formed during the CRB cycle late on 16 December, it became more symmetric. By 2243 UTC on 16 December the eyewall convective rain rates began to increase more rapidly, but the new eyewall, once again, lost its symmetry as it continued to constrict. The lack of eyewall symmetry has sometimes been associated with the presence of convective bursts. Numerical studies by Moller and Montgomery (1999) have also suggested that these convective bursts can introduce asymmetries in the cyclonic vortex. In most tropical cyclones, the presence of a more symmetric eyewall usually indicates that there is a greater concentration of subsidence-induced warming at the center, and a greater likelihood that the system will intensify.

Vertical distribution of latent heating in Paka’s inner core

To estimate the mean ascending motion in the second inner-core convective burst on 14 December and the proposed CRB cycle on 15–16 December, the SSM/I and TMI vertical distributions of the azimuthally averaged total (i.e., combined stratified and convective) latent heating for the six observation periods described in Fig. 8, are shown in Fig. 9. Evidence of the second convective burst is delineated by the latent heat profiles seen at 0509 UTC on 13 December and at 0831 UTC on 14 December. These figures suggest that the large net latent heating of 1 W m−3 that is observed at the altitude of 4 km during 0509 UTC on 13 December extends upward to 10 km at 0831 UTC on 14 December. These maximum latent heating values (greater than 3 W m−3), located in the lower troposphere (<3 km), at this time were mainly generated by convective processes (65%, as seen in Fig. 6) with little loss of latent heat near the surface due to evaporation. On the other hand, in the upper troposphere above the freezing level, cloud ice microphysical processes generated large amounts of stratiform and convectively induced latent heat on 14 December. These figures also suggested that the deep layer maximum net latent heating is located within 25 km of the center of circulation where the reduction of the Rossby radius is great enough so that the latent heating can warm the upper troposphere. This helped to concentrate and increase the mass, moisture, and momentum nearer to the center of circulation and thereby enhanced the intensity of the system.

First evidence of an outer-convective rainband can be seen at 0817 UTC on 15 December outside the eyewall and within the inner core that appeared to propagate inward at 2149 UTC on 15 December. Between 0817 and 2149 UTC on 15 December the eyewall latent heating decreased (i.e., ∼2 W m−3) leaving a limited vertical region of maximum latent heat of 1 W m−3 near the center at the altitude of less than 4 km, while the latent heating in the outer-convective rainband expanded in volume and increased to values greater than 1 W m−3. Between 1425 and 2243 UTC on 16 December, the outer rainband that initiated the third convective burst appeared to propagate inward to within 25 km of the center of circulation, dissipating the original eyewall and increasing the latent heat, volume, and vertical extent. The distribution and net latent heating in the new eyewall appear to be similar to that of the original eyewall. If this CRB cycle that generated the last two convective bursts does exist, it appears that it greatly influenced Paka’s eyewall mean ascending motion and its subsequent intensification by generating intense deep-layer latent heating near the center of circulation. The importance of enhanced areal mean ascending motion in the eyewall region may be related to a theory presented by Fitzpatrick (1996), which was discussed earlier in the introduction.

Lightning distribution

The monitoring of electrical discharge in clouds from satellites can provide substantial information about the distribution of the convective system’s LHR, precipitation, cloud microphysics, and localized ascending motion. This information, in turn, can be used to assess the severity of the weather that the convective system could produce. However, in measuring the electrical discharge in Typhoon Paka (as well as most tropical cyclones) from both OTD and LIS two major problems arise.

The first, and most obvious problem, is the infrequent visit time of the OTD and LIS sensors. Because of the different orbital geometry of the satellites and the different IFOVs of the sensors, the approximate number of times each sensor could observe Paka would be at least once a day, and there would be no fixed observational time difference between the sensors.

The second problem is that the mean ascending motion in the eyewall region (i.e., the region that dictates the intensity of the tropical cyclone) in the majority of the tropical cyclones is less than approximately 10.0 m s−1. This is the minimum ascending motion required to generate the cloud microphysical properties necessary for the production of electrical discharges (Molinari et al. 1994; Lyons and Keen 1994). The upward vertical velocities in the outer-core regions are usually greater. Therefore, using lightning discharge observations to assess the relative mean ascending motion of the eyewall region of a tropical cyclone may be questionable. However, by employing land-based sensors that can frequently measure electrical discharge directly in tropical cyclones near the U.S. coast [National Lightning Detection Network (Orville et al. 1987)] or indirectly over some of the data-void oceans [sferics measurements (Morales et al. 1997)], the inward-propagating convection and/or the CRB cycle can be easily monitored if the outer-core convection is highly electrically charged. Unfortunately, Paka was over the western North Pacific, far removed from any ground-based sensors.

Nevertheless, the infrequent observations of lightning discharge in Paka from the LIS and OTD sensors did suggest that the greatest number of lightning discharges occurred on 12 (Fig. 10) and 13 December in the southeastern rainbands (greater than 444 km from the center). These lightning strokes, most likely, had little influence on Paka’s intensity (Molinari et al. 1994). This result is not surprising, since these outer-core rainbands often have stronger ascending motion than the eyewall regions. However, at approximately 1800 UTC on 12 December, lightning discharges were observed within Paka’s inner core [i.e., approximately 50 km north of Paka center (see Fig. 10)] indicating that the ascending motion in the inner core was greater than the critical value needed to produce lighting, thereby, generating greater latent heating/rain rate and helping Paka to rapidly intensify. It can be seen in Fig. 2 that indeed the inner-core lightning discharge occurred prior to the second convective burst on 13 December. After 13 December, the LIS and OTD sensors failed to observe any other lightning discharges in Paka.

Time history of the environmental influences on Paka’s rain rates and LHR

There are three specific periods of interest during Paka’s evolution: 1) the episodes of inner-core convective bursts that occurred between 10–11 and 13–14 December, 2) the initiation of the proposed CRB cycle that was observed between 15 and 17 December; and 3) the rapid dissipation of the inner- and outer-core convection that occurred after 19 December. In order to determine what influence the large-scale external forcing mechanisms had in enhancing, maintaining, and dissipating the inner- and outer-core convective bursts and CRB cycle, both the necessary and possible sufficient forcing conditions are explored. The necessary conditions involve the magnitudes of tropopause temperature, SSTs, and vertical wind shear, and have been shown from many earlier studies to affect a tropical cyclone’s intensity, maximum potential intensity (MPI), and convection, are first examined. Then the possible significant sufficient conditions that may have led to the initiation or dissipation of these convective episodes will be examined. The first possible sufficient environmental forcing condition that will be examined is the lower-tropospheric moisture flux convergence, which has been observed to initiate and decay the outer-core convective rainbands. The upper-tropospheric circulation will then be examined as it pertains to trough–tropical cyclone interaction, the generation of diffluent outflow channels, and the creation of an inward surge of eddy relative angular momentum.

Because of the poor spatial and temporal resolution of the ECMWF analyses and the lack of data, no attempt will be made to rigorously connect these sufficient forcing conditions to the distribution and intensity of cloud microphysical properties. Instead the justification for choosing these forcing conditions will be based on previous research. The forcing conditions will be involved only to suggest processes that may have changed the distribution and intensity of Paka’s cloud microphysical properties.

Necessary conditions that may have initiated and maintained the inner- and outer-core convective burst or CRB cycle

Sea surface temperature

The evolution of SSTs that Paka traversed between 0000 UTC on 9 December to 0000 UTC on 21 December and Paka’s inner-core mean rain rate are seen in Fig. 11. Paka encountered SSTs above 28°C that are greater than the critical temperatures required to support convective growth [i.e., approximately 26°C (Gray 1979)] throughout the period. However, these SSTs were less than those that Opal (1995) traversed in the Gulf of Mexico during its lifetime (Rodgers et al. 1998; Black and Shay 1998; Shay et al. 1992). The figure also indicates an increase in the SSTs of nearly 1.0°C between 9 and 11 December as the system moves westward into an eddy of warm SSTs. Between 11 and 19 December, the SSTs initially decreased and then remained near 28.0°C. After 19 December, Paka entered a region of rapidly decreasing SSTs as it moved into the cooler ocean regions of the western North Pacific. Although SSTs were warm enough to maintain convective growth throughout the majority of the period, it is obvious that the extreme increase and decrease of SSTs, respectively, between 9 and 11 December and after 19 December had a profound effect on Paka’s intensity.

Maximum potential intensity

To estimate the average environmental tropopause temperature that Paka encountered during its typhoon and supertyphoon stages, the Kwajalein Atoll and Guam radiosonde data are used. As Paka moved to within 2° latitude south of the Kwajalein Atoll on 11 December, the mean tropopause temperature was approximately 197 K. This temperature was nearly 2 K lower than the tropical mean tropopause temperatures and 1 K lower than the mean tropopause temperature at 2° latitude radius from the center of a mean western Pacific typhoon (Frank 1977). On 15 December, when Paka approached to within 6° latitude east of Guam and prior to radiosonde failure, the mean tropopause temperature was approximately 192 K. This temperature was nearly 7 K lower than the tropical mean tropopause temperatures and 2 K lower than the mean tropopause temperature at 6° latitude radius from the center of a mean western Pacific typhoon.

Assuming that the SSTs were approximately 28°C at both locations, and that the surface air temperatures were 1°–2°C less than the SSTs, Paka’s minimum potential central pressure using Emanuel’s (1986) technique at Kwajalein Atoll and Guam was, respectively, between 924–935 and 918–930 hPa. On the other hand, Paka’s minimum central pressure near Kwajalein Atoll and Guam from the Dvorak (1975) technique and the maximum wind–minimum central pressure relationship (Ackinson and Holliday 1977), were, respectively, 965 and 900 hPa. Although Emanuel’s minimum potential central pressures are subject to errors due to assumptions in his technique and the uncertainties in the measured mean SSTs and tropopause temperatures that Paka encountered, these results suggest that Paka was approaching its potential intensity as it passed Guam.

Vertical wind shear

The evolution of Paka’s vertical wind shear and inner-core mean rain rates seen in Fig. 12 suggests that the vertical wind shear that Paka encountered before 20 December was moderate in strength (i.e., mean value of 10.7 m s−1), but varied little (i.e., standard deviation of 2.1 m s−1). However, on 13 December when Paka passed an upper-tropospheric trough, the vertical wind shear abruptly increased from 7 to 12 m s−1 during a 12-h period. Nevertheless maximum vertical wind shear never reached values greater than 15.0 m s−1 prior to 20 December. Plan views of the vertical wind shear upstream of Paka (figure not shown) also indicates that the maximum vertical wind shear that Paka would have confronted 12 h later was no greater than 12 m s−1. Although these mean vertical wind shear values are larger than the threshold values of 8.5 m s−1 that are needed to inhibit tropical cyclone intensification (Fitzpatrick 1996), it appears from the figure that Paka’s vertical wind shear had little adverse effect on its inner-core rain rates during the majority of the time prior to 20 December. After 20 December, however, Paka’s vertical wind shear increased to values greater than 15 m s−1 and this appeared to have helped reduce its mean inner-core rain rates.

Possible sufficient conditions that may have initiated and maintained convective burst

Lower-tropospheric environmental forcing

The availability of moist air is an external forcing condition that may have helped to maintain and initiate the outer-core (>333-km radius from a tropical cyclone’s center) convective rainbands in Paka. To examine the response of Paka’s outer-core rain rates to the availability of moist air, the distribution of the TPW derived from SSM/I and estimated from the ECMWF analyses at 2009 UTC on 16 December and 0000 UTC on 17 December, respectively, are shown in Fig. 13. These times roughly coincide with Paka’s third convective burst.

There are two distinct results that are noted from this figure. First, it is clearly seen in the figure that the SSM/I-derived and the ECMWF-analyzed synoptic-scale TPW fields are generally similar in areal extent and magnitude. However, there are small-scale differences caused either by the differences in time and spatial resolution of the products, the lack of moisture and wind measurements used in the ECMWF analyses, and/or the inability of the SSM/I to supply TPW over land and in raining areas. Nevertheless, the ECMWF-analyzed TPW is consistent with the large-scale synoptic features observed by the SSM/Is, the plan view of the ECMWF-measured TPW fields, and the mean tropospheric (i.e., 1000–400-hPa layer) and 850-hPa horizontal moisture flux (HMF). Therefore, the data can be used to determine the effect of the distribution of TPW on the initiation and maintenance of Paka’s outer-core convective burst and CRB cycle. Second, the TPW and 850-hPa streamline analyses in Fig. 13 reveal an intrusion of moist and dry lower-tropospheric air into, respectively, the northeastern quarter and southern half of Paka’s outer core.

The evolution of Paka’s outer-core time–azimuthal analysis of the 850-hPa HMF (Fig. 14) indicates a large influx of water vapor that first occurred at 0600 UTC on 9 December in the northeastern quadrant of Paka. This moisture influx maintained a maximum between 10 and 15 December. The influx of moisture then shifted toward the southeastern quadrant and reintensified. This enhanced moisture influx may have been influenced by both the increased availability of moisture east and south of Paka as well as Paka’s strengthening inward radial inflow during intensification.

The figure also suggests that there was a lack of moist air in Paka’s southeast quadrant prior to 11 December that later shifted to Paka’s northwest quadrant. The loss of moisture in the southeast and northwest quadrants appears to have been related to the dry subsiding air downstream of Paka as the typhoon’s outflow converged with the basic current. After 17 December, when Paka turned more northward and began to interact with the subtropical jet, cross-sectional analyses of the vertical motion and equivalent potential temperature (figure not shown) indicate that Paka’s outflow converged with the westerlies, subsided, and was entrained into the western region of the tropical cyclone’s outer core by the lower-tropospheric circulation (see Fig. 13). This subsiding air caused dry air to penetrate the western periphery of Paka’s outer core.

To ascertain whether the tropospheric (i.e., 1000–400-hPa layer) HMF has any influence in initiating, enhancing, or maintaining Paka’s outer-core rain rates, the evolution of the azimuthally averaged tropospheric HMF is compared to that of the outer-core mean rain rates (Fig. 15). The figure suggest that there was an approximate 2-day cycle in the enhancement of Paka’s outer-core rain rate throughout the 12-day period. This appeared to be preceded one day earlier by an inward surge of moisture into Paka’s outer core. These cycles in the outer-core rain rates are particularly evident on 11, 13, 15, and 17 December 1997. The figure suggests that on 10 and 12 December, the inward surge of moisture could have initiated the first two episodes of increasing outer-core rain rates. Then, on 14 December, the inward surge of moisture appeared to have aided in the formation of the outer-core convective rainband that led to the initiation of the proposed CRB cycle, while the inward surge of moisture on 16 December appeared to enhance and maintain this outer-core convective rainband.

Another period of interest that occurred between 17 and 19 December is the rapid decrease in the inward surge of moisture. The reduction of moisture flux led to dramatically decreased moisture in the outer core and eventually in the inner-core rain rates. As described earlier, the decreasing values of HMF at this time reflects strong upper-tropospheric convergence and subsidence as Paka began to interact with the westerlies (see Fig. 13). After 19 December, inward surges of moisture reoccurred (i.e., 20 December). Once again, this led to the reenhancement of Paka’s outer-core rain rates, but these outer bands had little influence on the system’s inner-core rain rates and intensification due to the increased vertical wind shear and decreasing SSTs.

Upper-tropospheric environmental forcing

The time–latitude distance of 150-hPa geopotential heights (Fig. 16) indicates that between 1200 UTC on 9 December and 1200 UTC on 12 December an upper-tropospheric trough with heights less than 14 300 m propagated southeastward and interacted with Paka. Further, the time–latitude distance of 100–200-hPa potential vorticity (PV) field (Fig. 17) within Paka’s environment suggests that the tropical cyclone encountered a region of PV-poor ascending air east of the trough axis between 0000 UTC on 11 December and 0000 UTC on 12 December. During this time, a strong diffluent outflow channel west of Paka was generated (figure not shown) that appears to have helped initiate the first convective burst (Fig. 2).

After passing west of the trough axis on 12 December, Paka entered into the confluent region of the upper-tropospheric trough that contained increasing PV-rich subsiding air (Fig. 17) and vertical wind shear (Fig. 12). These adverse conditions may have caused the rain rates in the inner-core region to become steady state.

As Paka continued its west-northwestward movement, the system encountered a mid-Pacific anticyclonic vortex. Plan views of the upper-tropospheric geopotential heights and streamlines (figure not shown) indicated that the ridge located to the east of Paka on 13 December built to the north and eventually west of the system, thereby subjecting Paka, once again, to a diffluent westerly anticyclonic outflow. The presence of the ridge helped to create favorable conditions for maintaining the inner-core rain rates.

Although the geopotential heights of the upper-tropospheric mid-Pacific ridge that Paka encountered remained persistently high (i.e., between 14 320 and 14 340 m) from the 0000 UTC on 14 December to 1800 UTC on 17 December, PV values suggested that Paka encountered the axes of two weak upper-tropospheric troughs. Paka encountered the second trough axis at 0000 UTC on 15 December and the third trough axis at 0000 UTC on 18 December. During the time, Paka entered into a region of PV-poor ascending upper-tropospheric air east of the trough axis at 0000 UTC 14 December, passed through the trough axis at 0000 UTC 15 December, and emerged into a region of PV-rich descending upper-tropospheric air west of the trough axis at 0000 UTC 16 December. It appears that when Paka encountered the ascending region of the trough, it helped to enhance and maintain the second convective burst.

At 0000 UTC on 16 December, Paka, once again, encountered the upper-tropospheric PV-poor ascending air east of the third upper-tropospheric trough (Fig. 17). This region of the upper-tropospheric trough appeared to help enhance the third convective burst. After passing this weak second trough, Paka, once again, emerged into the favorable influence of the mid-Pacific anticyclone. As Paka continued west-northwestward, it finally began to move into juxtaposition with the westerly subtropical jet on 19 December. The decreasing upper-tropospheric geopotential height fields (Fig. 16) that Paka encountered indicates that Paka was moving out of the influence of the supporting mid-Pacific ridge and into the hostile westerlies.

Figure 18, which depicts the evolution of Paka’s upper-tropospheric eddy relative angular momentum flux that was azimuthally averaged for an annulus 600–1000 km from Paka’s center and mean inner-core rain rate, suggests that during the majority of the time the upper-tropospheric outflow surrounding the system had a negative influence on Paka’s growth by diverging relative angular momentum away from the system. The only times when ERFC was observed was on 9 December and during the time when Paka interacted with the second (15 December) upper-tropospheric trough. However, the maximum magnitudes of the ERFC were no greater than 5 m s−1 day−1, considerably less than the critical value of 10 m s−1 day−1 that is observed for moderate environment–tropical cyclone interaction (DeMaria et al. 1993).

However, in examining the time–radial view of the azimuthally mean 200-hPa ERFC surrounding Paka (Fig. 19), it is clearly seen that during the periods prior to the first and second inner-core convective bursts there is an inward surge of upper-tropospheric eddy relative angular momentum originating from Paka’s environment (<444-km radius from the center). During the interaction with the first upper-tropospheric trough on 12 December, the inward surge of eddy relative angular momentum approached the inner core, while during the interaction with the weaker second trough on 15 December, the inward surge of eddy relative angular momentum only reached to within 500 km of the center. Thus, the figure suggests that the influx of eddy relative angular momentum into the inner core during the interaction with the first upper-tropospheric trough, although negative within the larger annular area, may have had greater influence in enhancing the rain rates in the inner-core eyewall region than it had during the interaction with the second trough. This result is consistent with the studies of Wu and Chang (1999).

Summary and discussion

It has been demonstrated that between 9 and 21 December, the large oscillations in tropical cyclone Paka’s rain rate/LRH caused by three long-lasting inner-core convective bursts and one CRB cycle have been sufficiently captured using the combination of SSM/I and TMI sensor data. The analyses also indicate that the convective burst prior to and particularly during the CRB had a profound effect on Paka’s intensification.

For example, the first episode of inner-core convective burst that occurred between 10 and 12 December helped to intensify Paka to typhoon status, where Paka’s maximum winds increased from 22 to 58 m s−1 in a 2-day period (see Fig. 2). The second convective burst occurred between 13 and 14 December after a slight decrease in rain rates and appeared, once again, to help reintensify Paka. On 15 December, the data suggested that an outer-convective rainband formed, propagated inward, and increased in rain rate. Similar to the earlier results described by Willoughby (1988, 1990) and Willoughby et al. (1982), an outer rainband dissipated the original eyewall by decreasing its water vapor influx and subjected the system to increasing upper-tropospheric subsidence. This caused a momentary weakening of the system. By 16 December, the new outer-convective rainband helped reintensify Paka’s maximum winds. After the new inner-core eyewall reached its minimum radius and maximum rain rates on 18 December, the third convective burst reintensified Paka to a maximum strength of nearly 80 m s−1. Finally, as Paka moved farther into the westerlies, its rain rates and intensity decreased under the influence of increasing vertical wind shear, the intrusion of dry air, and decreasing SSTs.

During these inner-core convective bursts cycles, the satellite-derived rain rates/LHR observations suggest the following: 1) the rain rates increased, 2) the convective processes dominated in the generation of latent heat, 3) large net latent heating penetrated deeper layers of the troposphere, 4) the eyewall propagated closer to the center of circulation, 5) the eyewall became more symmetric, and 6) the eyewall became more electrically charged. Because of these convective bursts, the distribution and intensity of latent heating may have helped intensify tropical cyclone Paka by generating enough upward motion to compensate for the loss of the eyewall cyclonic angular momentum due to surface friction and upper-tropospheric outward transport. Due to deep layer latent heating, the eyewall cyclonic angular momentum (i.e., a function of eyewall radius and symmetry) was able to concentrate the upper-troposphere warming nearer to the center of circulation. Further, if one considers the reduction of atmospheric density with height, the higher the warming occurs, the lower the surface pressure could be reduced hydrostatically at the center of Paka’s circulation, and the more intense the tropical cyclone could become.

Because Paka occurred over the data-void ocean regions of the central and western North Pacific, the poor spatial and temporal resolution of the ECMWF analyses, and the noncoincidence of model analyses and satellite observations made it difficult to assess the cause and effect relationship between actual internal forcing mechanisms and those estimated from the satellite data. Nevertheless, if one only emphasizes the significant forcing mechanisms, the results of this study suggest that convective bursts were mainly supported by the ideal necessary conditions, and to a lesser extent initiated by the sufficient conditions for convective growth.

For example, in examining the necessary conditions for convective growth the results indicate that 1) Paka’s environmental thermodynamic conditions were ideal for the system to reach its maximum potential intensity (MPI) during the later stages of its evolution. These favorable conditions were dictated by the high SSTs, the elevated height and cold temperatures of the tropopause, and the abundance of available moisture. 2) The vertical wind shear during 9–19 December was slightly greater than the critical values of 8.5 m s−1 that have been shown to be adverse for convective growth. 3) The SSTs were consistently 2.0°C above the threshold of value 26°C during this period, a criterion that has been shown to be necessary for the extraction of enough surface heat flux to provide for convective growth. The warm SSTs were particularly favorable for generating the first convective burst on 10–11 December, when Paka encountered a warm eddy of SSTs that was 2.5°C warmer than the threshold value.

The apparent sufficient conditions, on the other hand, suggest that 1) prior to the first convective burst, Paka traversed the diffluent region of a minor upper-tropospheric trough on 10–11 December as it encountered the warm pool of SSTs. Although the diffluent outflow was observed, the outflow-generated ERFC that reached the inner core was less than what was needed for moderate tropical cyclone–trough interaction. However, the combination of the warm ocean eddy and the weak influx of eddy relative angular momentum may have been sufficiently strong to help initiate and maintain the first convective burst. 2) During the second convective burst, as Paka emerged from the confluent region of the upper-tropospheric trough and into mid-Pacific ridge, the inner-core rain rates increased slowly, reaching steady state on 12 December. This convective burst appeared to initiate a second period of intensification. 3) From 13 to 18 December, as Paka entered the CRB cycle that helped initiate the third convective burst on 17 December, the tropical cyclone remained under the influence of the mid-Pacific ridge. 4) After 20 December, stronger vertical wind shear, lower SSTs, and greater intrusion of dry air began to erode the new inner-core eyewall and eventually weakened Paka (see Fig 2). 5) Finally, the inward surge of moisture that occurred in the southeastern quadrant and the loss of moisture that occurred in the southwestern quadrant of Paka’s outer-core regions may have, respectively, helped to initiate and dissipate these convective bursts and CRB cycle.

As in Hurricane Opal (Rodgers et al. 1998), Paka’s latent heat distribution and intensity greatly influenced its intensity. However, the sufficient environmental forcing conditions that helped initiate and maintain Paka’s convective burst were not as strong as those found in Opal. Paka was generally more intense than Opal, but Paka’s lower-tropospheric HMF convergence values were only about half as large as Opal’s and the values of upper-tropospheric ERFC were less than the critical value of 10 m s−1 day−1 and were considerably less than those observed during Opal’s mature stage. Paka’s weaker sufficient environmental forcing conditions were most likely due the system’s low-latitudinal development within the mid-Pacific ridge that protected the system from most upper-tropospheric troughs. The results also suggest that Paka’s necessary conditions were ideal for intensification and that the periods of convective burst were more internally forced (i.e., CRB cycles) in contrast to external forcing that is usually found in higher-latitude systems. As suggested in the Opal case and more strongly emphasized in this case, the distribution and intensity of inner-core latent heating needs to be monitored more often in order to better forecast tropical cyclone intensity changes. This might be accomplished by assimilating remotely sensed latent heat data into a three-dimensional mesoscale numerical weather prediction models.

Acknowledgments

The authors wish to thank Stacy Stewart of NOAA Tropical Prediction Center for his contribution in the synoptic analyses, Christopher Velden of the Space Science and Engineering Center at the University of Wisconsin for supplying the GMS infrared observations, and Dr. Robert Adler of Code 912 NASA Goddard Space Flight Center for his support and critique of this paper. The study was supported by NASA Headquarters Dynamics and Thermodynamic Research Program headed by Dr. Ramesh Kakar.

REFERENCES

  • Ackinson, G. D., and C. R. Holiday, 1977: Tropical cyclone minimum sea level pressure/maximum sustained wind relationship for the western North Pacific. Mon. Wea. Rev.,105, 421–471.

  • Baik, J.-J., S.-M. Lee, and C. H. Cho, 1993: Examination of convective process representation and inertial stability in a tropical cyclone model J. Korean Meteor.,28, 308–323.

  • Black, P. G., and L. K. Shay, 1998: Observations of tropical cyclone intensity change due to air–sea interaction processes. Preprints, Symp. on Tropical Cyclone Intensity Change, Phoenix, AZ, Amer. Meteor. Soc., 161–168.

  • Burgett, W. S., and G. H. Trapp, 1999: Eye structure of Typhoon Paka as viewed by the Kwajalein Doppler Radar. Preprints, 23d Conf. on Hurricanes and Tropical Meteorology, Vol. 1, Dallas, TX, Amer. Meteor. Soc., 448–450.

  • Cecil, D. J., and E. J. Zipser, 1999: Relationships between tropical cyclone intensity and satellite-based indicators of inner core convection: 85-GHz ice-scattering signature and lightning. Mon. Wea. Rev.,127, 103–123.

  • Challa, M., and R. Pfeffer, 1980: Effects of eddy flux of angular momentum on model hurricane development. J. Atmos. Sci.,37, 1603–1618.

  • Charney, J. G., and A. Eliassen, 1964: On the growth of the hurricane depression. J. Atmos. Sci.,21, 68–75.

  • Chen, L., and W. M. Gray, 1985: Global view of the upper level outflow patterns associated with tropical cyclone intensity changes during FGGE. Colorado State University, Atmospheric Science Paper 392, 1216 pp. [Available from Colorado State University, Fort Collins, CO 80523.].

  • Christian, H. J., R. J. Blakeslee, and S. J. Goodman, 1992: Lightning imaging sensor (LIS) for the earth observing system. NASA TM-4350, 44 pp. [Available from Center for Aerospace Information, P.O. Box 8757, International Airport, Baltimore, MD 21240.].

  • DeMaria, M., and J. Kaplan, 1994: A Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic basin. Wea. Forecasting,9, 209–220.

  • ——, ——, and M. M. Huber, 1998: The effect of vertical shear on tropical cyclone intensity change: An historical perspective. Preprints, Symp. on Tropical Cyclone Intensity Change, Phoenix, AZ, Amer. Meteor. Soc., 22–29.

  • ——, ——, J.-J. Baik, and J. Kaplan, 1993: Upper-level eddy angular momentum fluxes and tropical cyclone intensity change. J. Atmos. Sci.,50, 1183–1147.

  • Des Jardins, M., K. Brill, and S. Schots, 1991: Use of GEMPAK on Unix Workstations. Preprints, Seventh Int. Conf. on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, New Orleans, LA, Amer. Meteor. Soc., 449–451.

  • Dvorak, V. F., 1975: Tropical cyclone intensity analyses and forecasting from satellite imagery. Mon. Wea. Rev.,103, 420–430.

  • Emanuel, K. A., 1986: An air–sea interaction theory for tropical cyclones. Part I: Steady-state maintenance. J. Atmos. Sci.,43, 585–604.

  • Fishman, J., and J. C. Larsen, 1987: Distribution of total ozone and stratospheric ozone in the tropics. Implication for the distribution of tropospheric ozone. J. Geophys. Res.,92, 6627–6634.

  • Fitzpatrick, P. J., 1996: Understanding and forecasting tropical cyclone intensity change. Colorado State University, Atmospheric Science Paper 598, 346 pp. [Available from Colorado State University, Fort Collins, CO 80523.].

  • Frank, W. M., 1977: The structure and energetics of the tropical cyclone. Part I: Storm structure. Mon. Wea. Rev.,105, 1119–1135.

  • Gaby, D. C., J. B. Sushine, R. M. Mayfield, S. C. Pearce, and F. E. Torres, 1980: Satellite classification of Atlantic tropical and subtropical cyclones: A review of eight years of classification at Miami. Mon. Wea. Rev.,108, 587–595.

  • Gray, W. M., 1979: Hurricanes: Their formation, structure, and likely role in the tropical circulation. Meteorology over the Tropical Oceans, D. B. Shaw, Ed., Roy. Meteor. Soc., 155–218.

  • Hollinger, J. O., 1991: DMSP Special Sensor Microwave/Imager calibration/validation. Final Report Vol. 11, 1225 pp. [Available from J. O. Hollinger, Naval Research Laboratory, Washington, DC 20375].

  • Kummerow, C., W. S. Olson, and L. Giglio, 1996: A simplified scheme for obtaining precipitation and vertical hydrometeor profiles from passive microwave sensors. IEEE Trans. Geosci. Remote Sens.,34, 1213–1232.

  • ——, W. Barnes, T. Kozu, J. Shine, and J. Simpson, 1998: The Tropical Rainfall Measuring Mission (TRMM) sensor package. J. Atmos. Oceanic Technol.,15, 809–817.

  • Lee, C. S., 1986: An observational study of tropical cloud cluster evolution and cyclogenesis in the western North Pacific. Colorado State University, Atmospheric Science Paper 403, 250 pp. [Available from Colorado State University, Fort Collins, CO 80523.].

  • Lyons, W. A., and C. S. Keen, 1994: Observations of lightning in convective supercells within tropical storms and hurricanes. Mon. Wea. Rev.,122, 1897–1916.

  • Marks, F. D., 1985: Evolution of the structure of precipitation in Hurricane Allen (1980). Mon. Wea. Rev.,113, 909–930.

  • ——, and R. A. Houze, 1987: Inner-core structure of Hurricane Alicia from airborne Doppler radar observations. J. Atmos. Sci.,44, 1296–1317.

  • McPeters, R. D., S. M. Hollandsworth, L. E. Flynn, J. R. Herman, and C. J. Seltor, 1996: Long-term ozone trends derived from the 16-year combined Nimbus-7/Meteosat-3 TOMS version 7 record. Geophys. Res. Lett.,23, 3099–3702.

  • Merrill, R. T., 1988: Environmental influence on hurricane intensification. J. Atmos. Sci.,45, 1678–1687.

  • Molinari, J., and S. Skubis, 1985: Evolution of the surface wind field in an intensifying tropical cyclone. J. Atmos. Sci.,42, 2865–2879.

  • ——, and D. Vollaro, 1989: External influences on hurricane intensity. Part I: Outflow layer eddy momentum fluxes. J. Atmos. Sci.,46, 1093–1105.

  • ——, ——, ——, R. W. Henderson, and A. B. Saljoughy, 1994: Cloud-to-ground lightning in Hurricane Andrew. J. Geophys. Res.,99, 16 665–16 676.

  • Moller, J. D., and M. T. Montgomery, 1999: Vortex Rossby waves and hurricane intensification in a barotropic model. J. Atmos. Sci.,56, 1674–1687.

  • Morales, C. A., J. S. Kriz, E. B. Rodgers, and J. A. Weinman, 1997:The evolution of sferics around Hurricane Lilli-1996. Preprints, 22d Conf. on Hurricanes and Tropical Meteorology, Fort Collins, CO, Amer. Meteor. Soc., 127–128.

  • Mundell, D. B., 1991: Tropical cyclone intensification. Preprints, 19th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 511–515.

  • Olson, W. S., C. D. Kummerow, G. M. Heymsfield, and L. Giglio, 1996: A method for combined passive–active microwave retrievals of cloud and precipitation profiles. J. Appl. Meteor.,35, 1763–1789.

  • ——, ——, Y. Hong, and W.-K. Tao, 1999: Atmospheric latent heating distributions in the Tropics derived from satellite passive microwave radiometer measurements. J. Appl. Meteor.,38, 633–664.

  • Ooyama, K. V., 1964: A dynamical model for the study of tropical cyclone development. Geifus. Int.,4, 187–198.

  • Orville, R. E., R. A. Weisman, R. B. Pyle, R. W. Henderson, and R. E. Orville, 1987: Cloud-to-ground lightning flashes characteristics from June 1994 through May 1995. J. Geophys. Res.92 (D5), 5640–6544.

  • Petty, G. W., and K. B. Katsaros, 1990: New geophysical algorithms for the Special Sensor Microwave Imager. Preprints, Fifth Int. Conf. on Satellite Meteorology and Oceanography, London, United Kingdom, Amer. Meteor. Soc., 247–251.

  • Reed, R. J., A. Hollingsworth, W. A. Heckley, and F. Delsol, 1988: An evaluation of the performance of the ECMWF operational system in analyzing and forecasting easterly wave disturbances over Africa and the tropical Atlantic. Mon. Wea. Rev.,116, 824–865.

  • Reuter, G. W., and M. K. Yau, 1986: Numerical modeling of cloud development in a shear environment. Beitr. Phys. Atmos.,66, 65–80.

  • Rodgers, E. B., and H. F. Pierce, 1995: Environmental influence on Typhoon Bobbie’s precipitation distribution. J. Appl. Meteor.,34, 2515–2532.

  • ——, J. Stout, J. Steranka, and S. Chang, 1990: Tropical cyclone–upper atmospheric interaction as inferred from satellite total ozone observations. J. Appl. Meteor.,29, 934–954.

  • ——, S. W. Chang, J. Stout, J. Steranka, and J.-J. Shi, 1991: Satellite observations of variations in tropical cyclone convection caused by upper-tropospheric troughs. J. Appl. Meteor.,30, 1163–1184.

  • ——, ——, and H. F. Pierce, 1994a: A satellite observational and numerical study of the precipitation characteristics in western North Atlantic tropical cyclones. J. Appl. Meteor.,33, 129–139.

  • ——, J.-J. Baik, and H. F. Pierce, 1994b: The environmental influence on tropical cyclone precipitation. J. Appl. Meteor.,33, 573–593.

  • ——, W. S. Olson, V. M. Karyampudi, and H. F. Pierce, 1998: Satellite-derived latent heating distribution and environmental influences in Hurricane Opal (1995). Mon. Wea. Rev.,126, 1229–1247.

  • Shaw, D. B., P. Lonnberg, A. Hollingsworth, and P. Unden, 1987: Data assimilation: The 1984/1985 revisions of the ECMWF mass and wind analysis. Quart. J. Roy. Meteor. Soc.,113, 533–566.

  • Shay, L. K., O. G. Black, A. J. Mariano, J. D. Hawkins, and R. L. Exlberry, 1992: Upper ocean response to hurricane Gilbert. J. Geophy. Res.,97, 20 227–20  248.

  • Shi, J.-J., S. W. Chang, and S. Raman, 1990: A numerical study of the outflow layer of tropical cyclones. Mon. Wea. Rev.,118, 2042–2055.

  • Simpson, J., Ed., 1988: Report of the Science Steering Group for a Tropical Rainfall Measurement Mission (TRMM). U.S. Government Printing Office, 94 pp.

  • ——, C. Kummerow, W.-K. Tao, and R. F. Adler, 1996: On the Tropical Rainfall Measurement Mission (TRMM). Meteor. Atmos. Phys.,60, 19–36.

  • Weatherford, C., 1987: Typhoon structural evolution. Preprints, 17th Conf. on Hurricanes and Tropical Meteorology, Miami, FL, Amer. Meteor. Soc., 337–340.

  • Willoughby, H. E., 1988: The dynamics of the tropical cyclone core. Aust. Meteor. Mag.,36, 183–191.

  • ——, 1990: Temporal changes of the primary circulation in tropical cyclones. J. Atmos. Sci.,47, 242–264.

  • ——, J. A. Clox, and M. G. Shoreibah, 1982: Concentric eye-walls, secondary wind maxima, and the evolution of the hurricane vortex. J. Atmos. Sci.,39, 395–411.

  • Wu, C.-C., and H.-J. Chang, 1999: An observational study of environmental influences on the intensity changes of Typhoons Flow (1990) and Gene (1990). Mon. Wea. Rev.,127, 3003–3031.

APPENDIX A

A List of the Satellites, Sensors, and Satellite-Derived Parameters

Geostationary Meteorological Satellite (GMS)

Because there are no reconnaissance flights, Paka’s best-track intensity measurements (maximum sustained surface wind speeds and minimum central surface pressure) are estimated from the 11.5-μm channel of the Japanese geostationary satellite GMS infrared sensor by employing the Dvorak (1975) scheme. However, Gaby et al. (1980) determined that the Dvorak technique tended to underestimate the tropical cyclone maximum winds by approximately 5 kt in the mid mid–North Atlantic as compared to the Hurricane Data (HURDAT) file. The HURDAT file primarily uses reconnaissance flight data in the region of the mid–North Atlantic. Another problem with the Dvorak scheme was that it constrains the 24-h pressure falls by approximately 50 hPa, which sometimes makes the tropical cyclone intensity spinup and spindown time inaccurate. Nevertheless, since this study is more interested in intensity change, rather than absolute intensity, the weakness of the Dvorak scheme should have little impact in this study.

The study also uses the GMS infrared window and water vapor channels. The window channel is used to estimate Typhoon Paka’s inner-core mean CDO TBB for the purpose of qualitatively verifying whether SSM/I and TMI observations are frequent enough to capture the major temporal changes in Paka’s mean rain rates and to monitor the presence of Paka’s eye. The water vapor (6.7 μm) channel of the GMS infrared sensor is used to monitor qualitatively the propagation of the mid- and upper-tropospheric waves, while the water vapor–derived winds are employed to help derive a more accurate upper-tropospheric wind analyses around Paka.

Earth Probe Total Ozone Mapping Spectrometer (TOMS)

The Earth Probe TOMS was launched July 1996 and provided daily total ozone information for Paka from 14 to 21 December 1997. TOMS uses the solar backscatter of six ultraviolet wavelengths from 312.5 to 380.0 nm to separate the effects of cloud and ground reflection, scattering, and ozone absorption, thereby determining total ozone in a vertical column. TOMS measures total ozone at local noon with a nadir IFOV of approximately 50 km. Total ozone is measured in Dobson units (DU), where 1000 DU equals 1 atm cm. In cloudy regions, where ozone below the clouds is not observed, total ozone measurements are corrected by adding a climatological profile of tropospheric ozone below a cloud at a given height. The fraction of cloud cover is obtained from the TOMS ultraviolet reflectivity measurements (i.e., 380.0-nm radiance), and the cloud height is based on climatology [i.e., the International Satellite Cloud Climatology Project (ISCCP) dataset]. The ISCCP data was averaged monthly over a 0.5° latitude × 0.5° longitude grid (McPeters et al. 1996).

Over deep clouds that are associated with tropical cyclones, the underestimation of cloud height may cause a 2% underestimation in the TOMS-observed total ozone amount. However, these deep convective clouds are also highly reflective, which enables the TOMS to observe more backscattering ultraviolet radiation as compared to the low-reflective ocean surfaces (Fishman and Larsen 1987). The high reflectivity of the clouds would cause TOMS to observe more total ozone and thereby possibly compensate for the loss of total ozone caused by the underestimation of the cloud height. Therefore, clouds should not bias the estimation of the relative spatial distribution of TOMS-derived total ozone observation.

To eliminate the longitudinal and particularly the latitudinal total ozone gradients, the TOMS total ozone anomaly measurements are used. Total ozone anomalies are obtained from the Earth Probe TOMS data by subtracting the Nimbus-7 TOMS-derived climatology values of total ozone for a given day and location (based on 15 yr of Nimbus-7 TOMS measurements) from the observed Earth Probe TOMS data.

These measurements are used to help monitor and justify the upper-tropospheric circulation surrounding Tropical Cyclone Paka. By examining the mutual adjustment between upper-tropospheric waves and tropical cyclone outflow (Rodgers et al. 1990), it has been demonstrated that the distribution of total ozone reflects the distortion of the tropopause and PV fields caused by strong three-dimensional transport processes that are associated with upper-tropospheric waves, the secondary circulation induced by subtropical and tropical cyclone outflow jets, and the eye regions in tropical cyclones.

Lightning Derived from Optical Transient Detector (OTD) Satellite

The OTD is used to examine the evolution of the distribution of lightning in Tropical Cyclone Paka and to help identify convectively active regions. The OTD observes an area 1300 km × 1300 km twice a day with a viewing time of 189 s and a spatial resolution of 15 km × 15 km area. However, there can be a location error as high as 30 km due to navigation errors. The OTD monitors an oxygen emission line at 777.4 μm to detect intracloud and cloud-to-ground lightning. It detaches the optical pulses associated with the dissociation and excitation of oxygen due to lightning. The day and night flash detection efficiency is estimated to be roughly 50%. Approximately, 10% of the flashes detached by OTD is false due to radiation, electronic noise, or solar glint.

Due to detection efficiency, short view time, and the navigational errors, there is a limit of the OTD’s ability to monitor low flash rates that are common in tropical cyclones (Cecil and Zipser 1999). Nevertheless, the OTD observation will be used to augment the TRMM LIS lightning detection.

TRMM Lightning Imaging Sensor (LIS)

The TRMM LIS instrument is an optical staring telescope and filter imaging system. It monitors the distribution and variability of both cloud-to-cloud and cloud-to-ground lightning. LIS also measures at the frequency 0.777 μm and has a spatial resolution of approximately 4–7 km over a 600 km × 600 km swath of the earth’s surface. Due to the TRMM orbit, LIS can observe a cloud region for almost 90 s as it passes overhead, which is long enough to estimate the flashing rate of most electrical storms. The instrument records the time of occurrence, measures the radiant energy, and determines the location of lightning events within its IFOV. More information concerning the LIS sensor and measurements may be found in Christian et al. (1992).

APPENDIX B

A List of the Parameters that are Estimated and Derived from the DAO and ECMWF Analyses

Upper-tropospheric environmental parameters and cross-sectional analyses

The 150-hPa geopotential heights (m), horizontal divergence fields (s−1), and streamlines and the 100- and 200-hPa layer PV (10−7 hPa s−1) analyses are derived for the purpose of examining Paka’s upper-tropospheric environmental circulation. Northwest–southeast cross-sectional analyses through Paka are also constructed in order to examine the vertical distribution of the total wind flow and the potential temperatures within Paka and its environment. Tropopause temperatures, on the other hand, are obtained from Kwajalein Atoll and Guam prior to and during Paka and combined with the mean SSTs to qualitatively derive the system’s MPI.

Vertical wind shear

Vertical wind shear is considered for its ability to hinder convective growth (Gray 1979; Rueter and Yau 1986; Mundell 1991). It has been shown (DeMaria and Huber 1998) that vertical wind shear can negatively affect tropical cyclone structure and intensity through either ventilation caused by differential advection of heat, by the generation of a secondary circulation caused by the movement of a vertically coherent vortex, or by tilting and stabilization of its vortex caused by the thermal adjustments that are required to maintain balance as the PV vortex becomes tilted.

The vertical wind shear (m s−1) is derived from the 850- and 200-hPa ECMWF wind analyses. Horizontal winds at the 850- and 200-hPa level are averaged over a 500-km2 circular domain centered on the tropical cyclone. The tropical cyclone vortex is not removed. The large domain is used to ensure a more accurate vertical wind shear analyses over the relatively data-void central and western North Pacific region where Paka occurred. The vertical wind shear is then estimated from the magnitude of the difference between the mean horizontal wind vectors at 850 and 200 hPa. The vertical wind shear is also generated upstream of Paka for the purpose of estimating the magnitude of the vertical wind shear that the tropical cyclone would encounter 12–24 h later.

Upper-tropospheric horizontal eddy relative angular momentum flux convergence (ERFC)

In order to monitor the influence at which the gradient wind adjustment process that is associated with Paka’s outflow alters the system’s inner-core LHR; Paka’s upper-tropospheric horizontal ERFC (m s−1 day−1) is examined. The upper-tropospheric horizontal ERFC was calculated in Lagrangian cylindrical coordinates (Molinari and Vollaro 1989; DeMaria et al. 1993) using the following equation:
i1520-0450-39-12-1983-EB1
where r is the radius from the tropical cyclone center, Vr is the radial wind, and Vθ is the tangential wind. The overbar represents an azimuthal average and the prime denotes the deviation from the azimuthal average (e.g., eddy term). The radial and tangential winds in Lagrangian coordinates are obtained from the 200-hPa ECMWF wind analyses. The ERFC values are azimuthally averaged within an annulus whose inner and outer radii are, respectively, 600 and 1000 km from Paka’s center. To delineate the inward surge of eddy relative angular momentum into Paka, the upper-tropospheric ERFC is also calculated for annuli whose widths are 50 km that extend 100–900 km from Paka’s center. The data are presented as time–radius analyses.

Mean tropospheric horizontal moisture flux (HMF)

Some of the physical processes that have allowed the lower-tropospheric to influence tropical cyclone Paka’s rain rate/LHR have been documented to be the surface evaporation (Frank 1977) and the strong horizontal surges of low-level water vapor convergence (Ooyama 1964; Charney and Eliassen 1964; Molinari and Scubis 1985; Lee 1986). For this study, the mean tropospheric horizontal moisture flux (HMF) is examined in Lagrangian cylindrical coordinates in order to ascertain what effects the inward surges of water vapor has on altering the precipitation rates within Paka’s inner- and outer-core regions.

The mean tropospheric HMF (108 kg s−1) was again calculated in Lagrangian cylindrical coordinates (Frank 1977) by using the following equation:
i1520-0450-39-12-1983-EB2
where r is the radius from the tropical cyclone center, q is the mixing ratio, Vr is the radial wind velocity, g is gravity, dP is a vertical pressure increment, and P is the pressure level of integration. The overbar represents an azimuthal average. The radial winds and mixing ratio are obtained from the ECMWF analyses at mandatory levels up to 300 hPa. The mean tropospheric moisture flux is calculated for a cylindrical volume whose radius is 333 km from Paka’s center of circulation and between the pressure levels of 1000 and 300 hPa. The cylindrical radius of 333 km is chosen for the following reasons. 1) The analysis is comparable to the resolution of the ECMWF analyses. 2) The lower- and mid-tropospheric wind and water vapor observations are more abundant outside of the central dense overcast region. 3) Earlier water vapor budget studies indicated that the water vapor flux contributed more to the total precipitation within this circular area than surface evaporation (Frank 1977). Because of the uncertainties of measuring sea surface evaporation and the fact that not all water vapor convergence contributes to precipitation production, there is no attempt to relate the changes in the water vapor budget to variations in the inner-core LHR. The evolution of the azimuthal distribution of the 850-hPa water vapor flux (the level at which maximum water vapor flux is usually found) is also calculated from the ECMWF analyses in order to determine the asymmetry of the influx of water vapor with time.

Fig. 1.
Fig. 1.

Best-track location and intensity (see legend) for Tropical Cyclone Paka between 8 and 22 Dec 1997

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 2.
Fig. 2.

Paka’s intensity (dashed line, m s−1) and SSM/I (open circle) and TMI-derived (×) mean total (i.e., combined stratified and convectively generated rain rates) inner-core (within 111 km of the center) rain rates (solid line, mm h−1) for the period between 9 and 21 Dec 1997

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 3.
Fig. 3.

Paka’s SSM/I–TMI-derived mean total inner-core rain rates (solid line, mm h−1) interpolated for every 6 h and the size of the eye (dashed line, km) determined from GMS IR data for the period between 9 and 21 Dec 1997

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 4.
Fig. 4.

Plan views of the SSM/I horizontal-polarized 85-GHz TB of Paka during 15–16 Dec 1997. The coldest TBs represent the greatest scattering caused by ice. Adapted from the Naval Research Laboratory

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 5.
Fig. 5.

Paka’s SSM/I–TMI-derived mean total inner-core rain rates (solid line, mm h−1) interpolated for every 6 h and the mean inner-core cloud-top TBB (K) determined from GMS IR data for the period between 9 and 21 Dec 1997

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 6.
Fig. 6.

Paka’s SSM/I–TMI-derived inner-core mean total (solid line, mm h−1) and convective generated rain rates (dashed lines, mm h−1) interpolated for a 6-h interval during the period between 9 and 21 Dec 1997

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 7.
Fig. 7.

Time–radius view of Paka’s azimuthally averaged SSM/I–TMI-derived convective generated rain rates (contours of rain rate are shown: mm h−1) interpolated for every 6 h and 6-h maximum winds (m s−1) for the period between 9 and 21 Dec 1997. Rain rates were azimuthally averaged for annuli 55 km in width extending 444 km outward from the center. The greatest rain rates are delineated by the warmest colors

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 8.
Fig. 8.

Plan view of Paka’s convectively generated rain rates (mm h−1) from the SSM/I and TMI observations at 0509 UTC on 13 Dec, 0831 UTC on 14 Dec, 0817 and 2149 UTC on 15 Dec, and 1435 and 2243 UTC on 16 Dec 1997 during Paka’s CRB cycle. Gray background is nonraining SSM/I–TMI observations, and the colors indicated rain rates of different intensities (see color bar). Radial rings are 1° latitude interval centered on Paka’s center

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 9.
Fig. 9.

A radial–height display of the azimuthally averaged SSM/I–TMI-derived total LHR (W m−3) for the same CRB cycle seen in Fig. 8. Latent heating was azimuthally averaged for annuli 55 km in width extending 333 km outward from the center. Noncolored regions (i.e., regions of negative latent heating) indicate a loss of latent heat due to evaporation. Contour interval is given in the figure. The darker the colors, the greater the latent heating

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 10.
Fig. 10.

A plan view of Paka’s CDO regions (Paka’s eye delineated by a darker shade point within the CDO) obtained from a GMS IR image at 1832 UTC on 12 Dec 1997 superimposed upon the OTD (white background cross) and LIS (no background cross) observed lightning strokes during 12 Dec

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 11.
Fig. 11.

Paka’s SSM/I–TMI-derived total (solid line) inner-core rain rates (mm h−1) interpolated for every 6 h and the 12-h interval SSTs (°C) for the period between 9 and 21 Dec 1997

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 12.
Fig. 12.

Paka’s SSM/I–TMI-derived total (solid line) inner-core rain rates (mm h−1) interpolated for every 6 h and the 12-h interval vertical wind shear (m s−1) for the period between 9 and 21 Dec 1997

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 13.
Fig. 13.

The SSM/I-observed (left) total precipitable water (TPW, mm) and the ECMWF-derived (right) TPW and 850-hPa winds for the environment surrounding Paka at approximately 2200 UTC on 16 Dec 1997. The white dot designates Paka’s center. Contour intervals of TPW are given by color bar. Black in the SSM/I observations denotes the raining areas where TPW cannot be observed from this sensor

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 14.
Fig. 14.

A time–azimuthal display of Paka’s outer core (i.e., greater than 333 km from the center) ECMWF-derived 850-hPa HMF (g kg−1 m s−1) for 8–21 Dec 1997. Contours of HMF are given in the figure. The darker shades delineate the larger HMF values

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 15.
Fig. 15.

Paka’s SSM/I–TMI-derived azimuthally averaged total (solid line) outer-core rain rates (mm h−1) interpolated for a 6-h interval and the 12-h interval total (integrated between 1000 and 400 hPa) moisture flux (HMF, 105 kg s−1) at the radius of 333 km from Paka’s center for the period between 9 and 21 Dec 1997. Rain rates were averaged over an annulus whose outer and inner radius are 333 and 265 km, respectively. Shaded regions delineate negative HMF values

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 16.
Fig. 16.

Time–latitude distance view of the 150-hPa geopotential heights (m) that Paka traversed during the period of 9–21 Dec 1997. Distance perpendicular to best-track path of Paka (delineated by thick black line) are in positive and negative degrees of latitude depending, respectively, on whether one moves to the right or left of Paka direction of motion. Contours are given in figure. Darker shades designate higher geopotential heights

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 17.
Fig. 17.

Time–latitude distance view of the 100–200-hPa potential vorticity (PV × 10−7 hPa s−1) that Paka traversed during the period of 9–21 Dec 1997. Distance perpendicular to best-track path of Paka (delineated by thick black line) are in positive and negative degrees of latitude depending, respectively, whether one moves to the right or left of Paka direction of motion. Contours are given in figure. Darker shades designate higher PV values

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 18.
Fig. 18.

Paka’s SSM/I–TMI-derived total (solid line) inner-core rain rates (mm h−1) interpolated every 6 h and the 12-h interval azimuthally averaged 200-hPa eddy-relative angular momentum flux convergence (ERFC, m s−1 day−1) for the period between 9 and 21 Dec 1997. ERFC was azimuthally averaged over annuli whose outer and inner radii are, respectively, 1000 and 600 km from the center of Paka. Shaded regions delineate regions of eddy relative angular momentum flux divergence

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Fig. 19.
Fig. 19.

Time–distance view of the azimuthally averaged 200-hPa ERFC (m s−1 day−1) for the period between 9 and 21 Dec 1997. ERFC is azimuthally averaged over annuli whose widths are 100 km that extend outward from Paka’s center from 100 to 1000 km. Contours are given in figure. Darker shades designate higher ERFC values

Citation: Journal of Applied Meteorology 39, 12; 10.1175/1520-0450(2001)040<1983:EFOSPS>2.0.CO;2

Table 1.

List of satellites, sensors, and satellite-derived parameters used in this study

Table 1.
Table 2.

List of DAO-estimated and ECMWF analysis–derived parameters

Table 2.
Save