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  • View in gallery

    Scatter diagrams of OCS vs R17 over the (a) WNP and (b) NA. Lines indicate the regression lines.

  • View in gallery

    Percentage frequency distributions of size over the WNP and NA.

  • View in gallery

    Monthly mean sizes over the (a) WNP and (b) NA during 1999–2009. Vertical bars represent the 95% confidence intervals in the t distribution. Numbers above the x axis indicate the number of cases.

  • View in gallery

    Monthly percentage frequencies of small (S), medium (M), and large (L) TCs over the (a) WNP and (b) NA in JASO.

  • View in gallery

    Monthly mean sizes and lifetimes over the WNP. Vertical bars represent the 95% confidence intervals of TC lifetime in the t distribution. Numbers above the x axis indicate the number of R17 cases and number of TCs (with parentheses). The results for the months with fewer than eight TCs are not shown.

  • View in gallery

    Homogeneous monthly means of GEOS-5 ROCI, ROCIs from the operation centers, and sizes (R17), over the (a) WNP and (b) NA. Numbers above the x axis indicate the number of cases. The results for the months with fewer than two cases are not shown.

  • View in gallery

    Scatter diagrams of GEOS-5 ROCI vs size over the (a) WNP and (b) NA. Lines indicate the regression lines.

  • View in gallery

    Percentage frequencies of large TCs over the (a) WNP and (b) NA as a function of latitude in JASO.

  • View in gallery

    Percentage frequencies of small TCs over the NA as a function of latitude in JASO.

  • View in gallery

    As in Fig. 8, but as a function of longitude.

  • View in gallery

    Climatology of streamlines (solid lines with arrows) and isotachs (dashed lines in m s−1) at 500 hPa during (a) July, (b) August, (c) September, and (d) October over the WNP during 1999–2009.

  • View in gallery

    As in Fig. 11, but over the NA.

  • View in gallery

    Distributions of (a) large- and (b) small-sized TCs between 1999 and 2009 over the WNP. Numbers denoted in the square bracket are number of cases, TCs, and mean TC size.

  • View in gallery

    As in Fig. 13, but over the NA.

  • View in gallery

    (a) Annual means of size and ENSO index (JASO average) over the WNP. Vertical bars represent the 95% confidence intervals of TC size in the t distribution. Numbers above the x axis indicate the number of cases. (b) The corresponding scatter diagram of ENSO index (JASO average) vs size over the WNP. The straight line indicates the regression line.

  • View in gallery

    (a) Annual mean sizes and lifetimes over the WNP. Vertical bars represent the 95% confidence intervals of TC lifetime in the t distribution. Numbers above the x axis indicate the number of R17 cases and number of TCs (with parentheses). (b) The corresponding scatter diagram of TC lifetime vs size over the WNP. The line indicates the regression line.

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Size and Strength of Tropical Cyclones as Inferred from QuikSCAT Data

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  • 1 School of Energy and Environment, City University of Hong Kong, Hong Kong, China
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Abstract

A comprehensive statistical climatology of the size and strength of the tropical cyclones (TCs) occurring over the western North Pacific (WNP; including the South China Sea) and the North Atlantic (NA; including the Gulf of Mexico and the Caribbean Sea) between 1999 and 2009 is constructed based on Quick Scatterometer (QuikSCAT) data. The size and strength of a TC are defined, respectively, as the azimuthally averaged radius of 17 m s−1 of ocean-surface winds (R17) and the azimuthally averaged tangential wind within 1°–2.5°-latitude radius from the TC center (outer-core wind strength, OCS).

The mean TC size and strength are found to be 2.13° latitude and 19.6 m s−1, respectively, in the WNP, and 1.83° latitude and 18.7 m s−1 in the NA. While the correlation between size and strength is strong (r ≈ 0.9), that between intensity and either size or strength is weak.

Seasonally, midsummer (July) and late-season (October) TCs are significantly larger in the WNP, while the mean size is largest in September in the NA. The percentage frequency of TCs having large size or high strength is also found to vary spatially and seasonally. In addition, the interannual variation of TC size and strength in the WNP correlate significantly with the TC lifetimes and the effect of El Niño over the WNP. TC lifetime and seasonal subtropical ridge activities are shown to be potential factors that affect TC size and strength.

Corresponding author address: Prof. Johnny Chan, School of Energy and Environment, City University of Hong Kong, Tat Chee Ave., Kowloon, Hong Kong, China. E-mail: johnny.chan@cityu.edu.hk

Abstract

A comprehensive statistical climatology of the size and strength of the tropical cyclones (TCs) occurring over the western North Pacific (WNP; including the South China Sea) and the North Atlantic (NA; including the Gulf of Mexico and the Caribbean Sea) between 1999 and 2009 is constructed based on Quick Scatterometer (QuikSCAT) data. The size and strength of a TC are defined, respectively, as the azimuthally averaged radius of 17 m s−1 of ocean-surface winds (R17) and the azimuthally averaged tangential wind within 1°–2.5°-latitude radius from the TC center (outer-core wind strength, OCS).

The mean TC size and strength are found to be 2.13° latitude and 19.6 m s−1, respectively, in the WNP, and 1.83° latitude and 18.7 m s−1 in the NA. While the correlation between size and strength is strong (r ≈ 0.9), that between intensity and either size or strength is weak.

Seasonally, midsummer (July) and late-season (October) TCs are significantly larger in the WNP, while the mean size is largest in September in the NA. The percentage frequency of TCs having large size or high strength is also found to vary spatially and seasonally. In addition, the interannual variation of TC size and strength in the WNP correlate significantly with the TC lifetimes and the effect of El Niño over the WNP. TC lifetime and seasonal subtropical ridge activities are shown to be potential factors that affect TC size and strength.

Corresponding author address: Prof. Johnny Chan, School of Energy and Environment, City University of Hong Kong, Tat Chee Ave., Kowloon, Hong Kong, China. E-mail: johnny.chan@cityu.edu.hk

1. Introduction

In all operational tropical cyclone (TC) forecasts, the intensity, expressed as either the maximum sustained winds (MSWs) or the minimum sea level pressure (MSLP), and the track of the TC are always predicted to provide estimates of the potential wind destruction near the TC center. Because of their importance in forecasting, many researchers and forecasters in the past have tried to identify the physical processes responsible for TC intensity and track changes (see, e.g., Chan and Kepert 2010). However, with the dynamic structure of a TC resembling that of a Rankine vortex, the MSW or MSLP alone cannot provide a unique description of the TC structure. Outside the radius of maximum wind (RMW), the rate of decrease in tangential winds with increasing radius can vary with time in different TCs. Two more parameters—size and strength—have therefore been proposed to give a more complete description of the dynamical structure of a TC (Merrill 1984).

The average radius of the outermost-closed isobar (ROCI) and that of 15 or 17 m s−1 of surface winds (R15 or R17, respectively) are two common definitions of TC size. Frank and Gray (1980) composited rawinsonde data around TCs and found that R15 has a large variation but bears little relationship with MSW. Merrill (1984) found that ROCI varies seasonally and regionally and is again only weakly correlated with TC intensity.

Merrill (1984) defined TC strength as the average wind speed in the cyclonic circulation (e.g., the region from RMW to the radius of gale-force wind). Weatherford and Gray (1988a,b) further defined the mean tangential wind velocity within a 1°–2.5°-latitude radius from the center of the TC as the outer-core wind strength (OCS). They used aircraft reconnaissance data to estimate OCS and found that TCs with similar MSWs can have very different values of OCS.

Due to the scarcity of data over the open oceans, very few studies on these two parameters were made prior to the availability of satellite-derived winds. Liu and Chan (1999) studied TC size over the western North Pacific (WNP) and the North Atlantic (NA) using satellite-derived ocean-surface winds from the European Research Satellites-1 and -2 (ERS-1 and -2), and obtained results similar to those of Merrill (1984). The wider swath and higher horizontal resolution availability of Quick Scatterometer (QuikSCAT) satellite-derived winds allowed Chan and Yip (2003) to conduct a preliminary investigation (4 yr of data, 1999–2002) on the interannual variations of TC size. They found that TC size tends to be larger during El Niño years because of their formation locations. Chavas and Emanuel (2010) used QuikSCAT data (1999–2008) to examine further the global climatology of TC size, which is defined as the radius of vanishing winds. In terms of TC size maintenance, Lee et al. (2010) found that TCs that intensified to typhoon intensity during their lifetimes tend to stay in the same size (defined as R15) category during intensification over the WNP based on QuikSCAT data (2000–05).

With the accumulation of ocean-surface wind data from QuikSCAT (until its demise in 2009), a much larger sample of TCs can be extracted. A more comprehensive climatology of TC size and the strength of TCs over the WNP (including the South China Sea) and the NA (including the Caribbean Sea and the Gulf of Mexico) can therefore be made, which is the main objective of this study. As will be seen in section 3, after the quality check of the QuikSCAT data and based on the similar TC size definition (R15 or R17), the sample size in this study for both the WNP and NA is the largest compared with all previous studies based on the remote sensing techniques so that the climatology obtained should be much more robust.

Following most previous studies, R17 is chosen to be the definition of TC size in this study. Although Chavas and Emanuel (2010) also examined the QuikSCAT data, their definition of TC size makes comparisons with previous studies difficult. Further, with 11 yr of data, it is possible to have a more robust examination of the interannual variation of TC size and its relation with El Niño. In addition, by comparing with the results from previous studies (Merrill 1984; Liu and Chan 1999; Kimball and Mulekar 2004; Yuan et al. 2007; Lee et al. 2010), it is possible to have some estimate of the possible interdecadal variations in TC size.

The definition of TC strength follows that of Weatherford and Gray (1988a,b), that is, the OCS. Strength is examined in this study because it can possibly provide us with an additional important measure (other than intensity and size) of how the outer-core winds are distributed. It should also be pointed out that a thorough search through the literature yields only the Weatherford and Gray (1988a,b) study as having its focus on TC strength. This study should therefore provide some additional insights into how important or useful TC strength is in describing the dynamical structure of a TC, and how size and strength are related.

Section 2 describes the datasets used in this study. The methods of data selection, definitions of the parameters, and classification of TCs are presented in section 3. Section 4 presents the relation between size and strength while section 5 discusses the climatologies and the comparisons of size in different aspects between the two basins. Finally, section 6 concludes with a summary and a discussion.

2. Data

a. Scatterometer data

The SeaWinds microwave scatterometer was launched on the QuickBird satellite in June 1999 and its mission ended in November 2009. Hereafter, this entire set of instruments is referred to as QuikSCAT. QuikSCAT transmitted microwave pulses (a continuous swath of 1800 km) down to the earth’s surface and then received the backscattered power that is related to surface roughness, which is highly correlated with the near-surface wind speed and direction on water surfaces. Hence, both wind speed and direction at the height of 10 m over the ocean surface can be estimated.

In this study, the postprocessed 0.25° latitude × longitude gridded QuikSCAT data from the Remote Sensing Systems (RSS) database are used. These data are produced by RSS and sponsored by the National Aeronautics and Space Administration Ocean Vector Winds Science Team. Data are available online (www.remss.com). RSS postprocessed the QuikSCAT L2A data from the Jet Propulsion Laboratory, which reprocessed the data in 2006 using the Ku-2001 geophysical model function and passed them through quality checks by comparing with the first-guess field of a numerical weather prediction (NWP) model so that the data are largely acceptable. Rain-free QuikSCAT winds below 20 m s−1 agree extremely well with the buoy results (Ebuchi et al. 2002). Using extremely limited validation data, those from 20 to 40 m s−1 are roughly verified to be within 10 m s−1 under rain-free conditions. It is well known that rain affects QuikSCAT and results in overestimated low winds or underestimated high winds when heavy rain is present. In TCs with winds weaker than 15 m s−1, the QuikSCAT winds in the presence of rain are often overestimated due to surface roughening and signal scattering. QuikSCAT winds within TCs above 20–30 m s−1 are often lower than actual storm speeds as the rain attenuates the radar signal (Atlas et al. 2001; Stiles and Yueh 2002; Brennan et al. 2009). Data selection is therefore important and will be discussed in detail in section 3.

The data between July 1999 and November 2009 from the QuikSCAT satellite are the main data for defining the size and strength of TCs over the WNP and the NA. Details of the definitions of these parameters will be given in sections 3c and 3d.

b. Best-track datasets

The 6-hourly best-track data (including TC center position, MSW, MSLP, ROCI, and lifetime) of TCs with at least tropical storm intensity between July 1999 and November 2009 over the WNP and the NA are extracted and evaluated from the Joint Typhoon Warning Center (JTWC) and the National Hurricane Center (NHC) web sites (http://www.usno.navy.mil/JTWC and http://www.nhc.noaa.gov, respectively). MSWs provided in these best-track datasets will be mainly used as the TC intensity in this study.

c. GEOS-5 data

Because not all the ROCIs from the JTWC and the NHC are available within the study period, and the methods of defining the ROCI between them are different (see Fig. 6), sea level pressure (SLP) data from the Goddard Earth Observing System Model version 5 (GEOS-5) database (http://goldsmr2.sci.gsfc.nasa.gov/dods/MAT1NXSLV.info) around TCs with at least tropical storm intensity are extracted to estimate the ROCI over the WNP and the NA. GEOS-5 is a system of models integrated using the Earth System Modeling Framework. The latitude, longitude, and time resolutions of this dataset are 0.5° in latitude, 0.667° in longitude, and hourly, respectively. The method of defining ROCI from GEOS-5 data will be presented in section 3e. It is emphasized that the GEOS-5 ROCIs are used to provide additional reference but are not used to define TC size in this study.

d. NCEP–NCAR reanalysis data

Climatology of the midlevel (500 hPa) synoptic flow is generated from the 6-hourly National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis data (Kalnay et al. 1996) with 2.5° latitude × 2.5° longitude global grid resolutions that contain meteorological parameters such as zonal and meridional winds on 17 pressure levels. These resolutions should be adequate for studying large-scale synoptic systems such as the subtropical ridge.

e. ENSO index

The El Niño–Southern Oscillation (ENSO) indices from the National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Center Web site (http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml) are used to investigate further the relationship between ENSO and the interannual variations of size and strength. The 3-month running-average sea surface temperature (SST) anomalies in the Niño-3.4 region (5°N–5°S, 120°–170°W), with 1971–2000 as the base climatology, are used as ENSO indices in this study.

3. Methodology

a. Criteria for the selection of QuikSCAT data

As QuikSCAT is a polar-orbiting satellite, its swath might not cover the entire circulation of a particular TC at a particular time. In addition, in order to minimize noise and uncertainty, only data satisfying all of the following criteria are used:

  1. TC must be at tropical storm (TS) intensity or above (MSW ≥ 17 m s−1),
  2. the TC center must be covered by the swath,
  3. the distance between the TC center and the edge of the swaths must be >1° latitude,
  4. more than 50% of the TC circulation is covered by the swath,
  5. the TC circulation should have no extensive wind-discontinuity problem,
  6. azimuthally averaged wind speed profiles must reach 17 m s−1 or above after filtering all rain-flagged data (see section 3c),
  7. R17 is not close to any landmass, and
  8. rain-flagged data are excluded.

After passing this strict quality check, the sample size of this study is the largest among all of the previous studies based on remote sensing techniques and similar TC size definitions (R15 or R17). While some of these criteria might be somewhat subjective, such an approach minimizes the potential for large errors in the estimations of size and strength.

b. Estimation of TC center

Because rain-flagged data are found most of the time and some TCs were only partly covered by the swath, estimating the TC center position by calculating the maximum relative vorticity can be difficult at times. Therefore, for simplicity, the TC center is estimated by the linear interpolation method using the best-track data according to the time at which the QuikSCAT swath was over the TC. The case is eliminated (<1% in total) if the interpolated TC center is found to deviate from the QuikSCAT TC center by >1° latitude. Although the center estimated in this way may not be consistent with the wind data, such a deviation should be considered acceptable.

c. Estimation of TC size

In this study, the size of a TC is defined as the average radial extent of gale-force surface winds (17 m s−1; R17), similar to the method of Chan and Yip (2003). Azimuthally averaged winds between 0.25° and 6.25° latitude from the center at intervals of 0.25° latitude are obtained by averaging the winds within each 0.25°-latitude-wide ring belt (0.125° ≤ r < 0.375° latitude radial area for the first ring belt). The intent behind using an azimuthal average is in the removal of most of the asymmetry associated with TC motion (Shea and Gray 1973). To make sure that a reasonable value of the azimuthally averaged wind in each ring belt can be obtained, the following criteria are also set. A missing value is set for any case failing any of the following criteria:

  1. The number of available (not rain flagged) data points in each ring belt must be >5 without considering the wind directions.
  2. The fraction of available data points to total data points in each ring belt must be ≥0.5.

It is assumed that a TC behaves like a Rankine vortex outside the maximum winds; that is,
e1
where υθ is the tangential wind speed, r is the radial distance from the TC center, and C and b are constants for a given profile. As the values of the tangential winds and total winds are similar, especially at radii far away from the radius of maximum winds (Shea and Gray 1973), the total winds are assumed to be the same as the tangential winds. Six valid azimuthally averaged winds with wind speeds closest to 17 m s−1 are then used to fit the vortex profile in (1) after taking the logarithm. The choice of six values (~1.5° latitude) is considered to be adequate and reasonable to estimate R17. It should also be noted that the value of R17 from (1) is only considered to be acceptable if the innermost valid azimuthally averaged wind is ≥17 m s−1. In other words, no extrapolation of TC size is allowed.

d. Estimation of TC strength

As RMW is nearly always <1° latitude from the TC center and rain generally affects the quality and availability of QuikSCAT data near the eyewall of TCs (also likely <1° latitude from the TC center), estimating TC strength by averaging wind speed between RMW and R17 (Merrill 1984) may not be appropriate. Instead, the definition of strength in this study follows that proposed by Weatherford and Gray (1988a,b), that is, the OCS, which is the mean tangential surface wind velocity within 1°–2.5°-latitude radius from the TC center. Such a definition of strength basically removes much of the rain contamination of QuikSCAT data. Using the same definition also allows for a direct comparison of the results between this study and theirs. Again, because the values of the tangential winds υθ and total winds υ are similar, OCS can be estimated using (2). It should be reemphasized that the strength defined here is not a measure of the TC intensity (MSW and MSLP) but, rather, that of the outer-core TC circulation.

Given the fulfillment of the prerequisite that R17 of a particular case is valid, OCS is then calculated as
e2

The denominator 7 represents the number of values of υ to be averaged as these values are at 0.25° latitude intervals. Due to the rain contamination or partial coverage of a swath, a maximum of two missing values of υ are allowed within 1°–2.5°-latitude radius from the TC center. Although the RMWs of some cases lie within or even outside of this region, the impact on the overall result should not be substantial because they only account for 3% or less of the total cases.

e. Estimation of GEOS-5 ROCI

The method of defining ROCI using GEOS-5 data is similar to that of Merrill (1984). Given that R17 is valid, SLP data from GEOS-5 are plotted at 2-hPa contour intervals. GEOS-5 ROCI is then defined as the average of the distances to the north, east, south, and west from the TC center to the highest-valued closed isobar. If the outermost-closed isobar is strongly elongated or distorted, the next isobar of a lower value is used. This might be subjective to a certain extent. However, such an approach ensures that the main circulation of the TC is considered.

f. Classifications of size and strength

As there is no absolute definition of the classifications of size and strength of a TC, the classifications of size (small or large) and strength (low or high) are defined in this study using the 25th and 75th percentiles (Table 1). For comparison, the size categories of other researchers or meteorological centers over the WNP and the NA are summarized in Tables 2 and 3, respectively. The different definitions of TC size are likely the reason for the values of the size category boundaries in this study being smaller than those of previous studies. Again, as mentioned in the introduction, based on remote sensing techniques and our data selection criteria, the sample size of this study is the largest among all the previous studies.

Table 1.

Statistical attributes of TC size and strength for the WNP and the NA TCs in this study.

Table 1.
Table 2.

Size categories over the WNP used by different researchers and meteorological centers. Units are degrees latitude.

Table 2.
Table 3.

Size categories over the NA used by different researchers. Units are degrees latitude.

Table 3.

4. Relation between size and strength

In both the WNP and the NA, a strong relationship between R17 and OCS (r ≈ 0.9) is found (Fig. 1). This 11-yr comprehensive study confirms the preliminary results of Weatherford and Gray (1988b) based on 3 yr of aircraft reconnaissance data. Given the fact that most of the radial decaying wind factors are similar, such high correlation is reasonable because R17 is a quantity describing the distance that the wind decays to gale force (17 m s−1) from the TC center. Thus, the larger the R17, the higher the wind speeds that can be captured (within 1°–2.5° latitude), and vice versa.

Fig. 1.
Fig. 1.

Scatter diagrams of OCS vs R17 over the (a) WNP and (b) NA. Lines indicate the regression lines.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

Due to such a high correlation between R17 and OCS, most of the climatological features of OCS are found to be similar to those of R17 (not shown). Therefore, for succinctness and to avoid redundancy, only the climatology of R17 will be discussed for the rest of the paper and will be used to generalize the climatology of OCS in this study as well. In other words, the climatologies of large, medium, and small TCs are applicable to high-, average-, and low strength TCs, respectively. The statistical attributes of TC size and strength for the WNP and the NA TCs are shown in Table 1.

5. Climatology of TC size

a. Overall distributions

Cases fulfilling all of the data selection criteria in section 3 represent around 37% and 27% of the total possible cases over the WNP and the NA, respectively (Table 1), with the latter being counted by the number of times during which TCs had MSW ≥ 40 kt (from best-track datasets) (1 kt = 0.5144 m s−1) every 12 h.1 Such percentages are considered to be reasonable because a large number of cases are ignored or filtered due to large swath gaps (~500–1000 km) in the tropics and subtropics, rain contamination, and proximity to landmass.

The percentage frequency distributions of the sizes of TCs over the WNP and the NA in the period of study show that TCs over the WNP have a broader spectrum of sizes (Fig. 2), which is consistent with the results of Liu and Chan (1999). The mean size of WNP TCs is larger by 0.3° latitude (~16%) than those over the NA (Table 1), which means that, on average, the area enclosed by WNP TCs is about 1.35 times larger than that of the NA TCs. This difference in mean TC sizes between the two basins is statistically significant at the 99.9% confidence level based on a Student’s t test. This result also suggests that WNP TCs have a slower radial decaying wind profile than those with the same intensity and are therefore likely to be more destructive. The means and the medians of TC size in both basins in this study are comparable to those of Chavas and Emanuel (2010), though their definition of size is different. In addition, the standard deviation of size over the WNP is also found to be significantly (99.9% confidence level based on an F test) larger than that over the NA, which suggests that WNP TCs have a larger size variation than NA TCs. Such results are consistent with those of previous studies although their definitions of TC size are different (Table 4). In terms of ROCI, the mean GEOS-5 ROCIs are found to be 4.2° and 3.3° latitude over the WNP and the NA, respectively, which are also similar to those from Merrill (1984).

Fig. 2.
Fig. 2.

Percentage frequency distributions of size over the WNP and NA.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

Table 4.

Summary of the mean and standard deviation of TC sizes of previous and current studies. Units are degrees latitude.

Table 4.

The correlation coefficients between MSW and TC size over the WNP and the NA are found to be 0.29 and 0.35, respectively, which are consistent with those from Merrill (1984) and Chavas and Emanuel (2010).

b. Monthly variations

The monthly means of TC size during the study period over the WNP and NA (Fig. 3) give two R17 peaks in both the WNP (July and October) and the NA (September and November). Over the WNP, the mean TC sizes in July and October are larger (statistically significant at the 90% confidence level based on the Student’s t test) than those of their neighboring months. On the other hand, the mean NA TC sizes in September and November are larger than those of their neighboring months at the 99% and 74% confidence levels, respectively, which suggests that the mean R17 peak in November may not be genuine or significant, probably because of the small number of cases. However, these two peaks are consistent with the results of Kimball and Mulekar (2004), who studied the 15-yr climatology of TC size parameters over the NA using an extended best-track dataset (1988–2002). They also found two mean R17 peaks in September and November. Nevertheless, the peak found in November should be treated with caution.

Fig. 3.
Fig. 3.

Monthly mean sizes over the (a) WNP and (b) NA during 1999–2009. Vertical bars represent the 95% confidence intervals in the t distribution. Numbers above the x axis indicate the number of cases.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

These monthly mean size peaks are consistent with the monthly percentage frequencies of large TCs during July–October (JASO) (Fig. 4). Troughs in August and September over the WNP are also consistent with more small TC cases found. JASO is chosen because most TCs occur during these 4 months. Larger percentage frequencies are found in July and October over the WNP, and in September over the NA within JASO.

Fig. 4.
Fig. 4.

Monthly percentage frequencies of small (S), medium (M), and large (L) TCs over the (a) WNP and (b) NA in JASO.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

Even if the value of R17 in November over the NA is not considered, such results (Fig. 3) are still different from those of Merrill (1984) and Liu and Chan (1999), who found a peak in the mean TC size in October in both basins. This may be due to sampling problems and the differing definitions of TC size in different studies (Table 4). However, the two seasonal mean TC size peaks found over the WNP in this study are similar to the results based on 2000–05 QuikSCAT data from Lee et al. (2010), who defined R15 as TC size and found two mean TC size peaks in August and October. It is suggested that these two seasonal mean TC size peaks found over the WNP may be genuine. Besides, the peak found in September over the NA is consistent with the results of Kimball and Mulekar (2004). Thus, an interdecadal variation in seasonal TC size may actually exist. In addition, it is remarkable that the monthly mean TC lifetimes [estimated by the time interval starting from MSW = 34 kt (in genesis or deepening stages) to MSW = 34 kt (in decaying stage) from best-track data] match quite well with the monthly mean TC sizes (Fig. 5). The monthly mean TC lifetimes peaks in July and October are longer than those of their neighboring months at the 80% and 75% confidence levels, respectively. In other words, it is suggested that TCs having longer lifetimes may have more time to intensify and grow (e.g., angular momentum transports, moisture convergences, upper-level divergences, etc.). To summarize, within the study period (1999–2009), the mean sizes of both midsummer (July) and late-season (October) TCs are relatively large over the WNP and TCs occurring in the late season (September) tend to be larger over the NA.

Fig. 5.
Fig. 5.

Monthly mean sizes and lifetimes over the WNP. Vertical bars represent the 95% confidence intervals of TC lifetime in the t distribution. Numbers above the x axis indicate the number of R17 cases and number of TCs (with parentheses). The results for the months with fewer than eight TCs are not shown.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

The monthly mean distributions of GEOS-5 ROCI and ROCIs from the operational centers are different from that of R17 (Fig. 6) although GEOS-5 ROCI and R17 are significantly correlated (Fig. 7), with correlation coefficients of ~0.49–0.54 (statistically significant at the 99% confidence level based on the Student’s t test). It is notable that Fig. 6 also shows there should be a difference between the approaches of finding ROCI between JTWC and NHC in which the JTWC ROCI seems to have a systematic smaller value than that of the GEOS-5 ROCI while the NHC ROCI matches well with the GEOS-5 ROCI. This is the reason why the GEOS-5 ROCI is chosen in order to present a fair comparison and consistency in this study. The month with the maximum mean GEOS-5 ROCI over the WNP is October, which is consistent with results from previous studies (Brand 1972; Merrill 1984; Liu and Chan 1999). Note, however, that the peak over the NA is again in November.

Fig. 6.
Fig. 6.

Homogeneous monthly means of GEOS-5 ROCI, ROCIs from the operation centers, and sizes (R17), over the (a) WNP and (b) NA. Numbers above the x axis indicate the number of cases. The results for the months with fewer than two cases are not shown.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

Fig. 7.
Fig. 7.

Scatter diagrams of GEOS-5 ROCI vs size over the (a) WNP and (b) NA. Lines indicate the regression lines.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

Over the NA, the month having the maximum mean ROCI estimated from both the GEOS-5 data (17 cases) and the NHC best-track data (134 cases) is found to be November (Fig. 6b), which differs from the findings in Merrill’s (1984) study that the maximum is in October. The mean TC sizes obtained from the GEOS-5 data and the NHC best-track data in November are significantly (based on the Student’s t test) larger than those of their neighboring months at the 95% and 99% confidence levels, respectively. Again, this difference gives additional evidence to support the hypothesis that there could be an interdecadal variation in seasonal TC size (R17 and ROCI).

c. Spatial variations

No large TC is found in the regions south of 10°N or north of 40°N over the WNP (Fig. 8a). The percentage frequency of large WNP TCs [calculated by the fraction of the number of large TCs cases to the number of all possible cases (including large, medium, and small TCs cases) within the particular month and region] at 30°–40°N increases from August to October. Note that the peaks in the percentage frequencies of large TCs over the WNP shift from 20°–30°N in July and August to 30°–40°N in September and October. This suggests that large TCs in the WNP are likely to occur at lower latitudes in midsummer but higher latitudes in the late season.

Fig. 8.
Fig. 8.

Percentage frequencies of large TCs over the (a) WNP and (b) NA as a function of latitude in JASO.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

Over the NA, no large TC is found south of 10°N or north of 50°N in JASO (Fig. 8b). The percentage frequencies of large TCs increase from July to September. TCs tend to be small if they are located within 10°–20°N (Fig. 9). No clear latitudinal distribution of small TCs can be found over the WNP (not shown).

Fig. 9.
Fig. 9.

Percentage frequencies of small TCs over the NA as a function of latitude in JASO.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

In addition, the percentage frequencies of large TCs as a function of longitude for JASO over the WNP show a higher large TC occurrence percentage shifting from west (120°–140°E) in July and August to east (140°–150°E) in September and October (Fig. 10a). Over the NA, TCs occurring over the eastern Gulf of Mexico (80°–90°W) are likely to be large TCs (Fig. 10b).

Fig. 10.
Fig. 10.

As in Fig. 8, but as a function of longitude.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

These observations can likely be explained by the seasonal migration of the subtropical ridge (STR). Over the WNP, the STR moves poleward and extends westward from the central Pacific to eastern China (Figs. 11a and 11b) in midsummer. As a result, more TCs form at higher latitudes and are forced to move westward so that they seldom reach too far north. During the late season, the STR moves equatorward and retreats eastward. TCs are therefore more likely to form at lower latitudes. The eastward retreat of STR together with the southward penetration of midlatitude troughs often lead to a col region between the Asian continental anticyclone associated with the Asian winter monsoon and the STR (Figs. 11c and 11d), which would favor the TCs recurvature. Late-season TCs therefore tend to have a longer life span and thus have more time to develop into larger TCs, which is consistent with the results in Fig. 5. Similarly, in the NA, the STR moves equatorward from midsummer to late season (Fig. 12), which also suggests that TCs will have a higher chance to recurve into the westerlies before weakening so that they may continue to grow in size.

Fig. 11.
Fig. 11.

Climatology of streamlines (solid lines with arrows) and isotachs (dashed lines in m s−1) at 500 hPa during (a) July, (b) August, (c) September, and (d) October over the WNP during 1999–2009.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

Fig. 12.
Fig. 12.

As in Fig. 11, but over the NA.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

In terms of the total frequency within the study period, more large WNP TC cases are found in the region 15°–30°N and 122°–150°E (small, 100; large, 145) where recurvature often occurs (Fig. 13a). Small WNP TCs are more likely to appear in the southeastern region (5°–20°N, 150°–170°E) (small, 25; large, 5), south of 15°N (small, 48; large, 25), and in the South China Sea (small, 32; large, 12) (Fig. 13b). In the NA (Fig. 14), more large TCs cases are found (small, 7; large, 20) in the northeastern region (30°–50°N, 30°–55°W) and eastern Gulf of Mexico (small, 0; large, 9) while more small TCs cases are found (small, 22; large, 9) in the southeastern region (10°–30°N, 30°–55°W) and western Gulf of Mexico (small, 7; large, 0).

Fig. 13.
Fig. 13.

Distributions of (a) large- and (b) small-sized TCs between 1999 and 2009 over the WNP. Numbers denoted in the square bracket are number of cases, TCs, and mean TC size.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

Fig. 14.
Fig. 14.

As in Fig. 13, but over the NA.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

d. Interannual variations

The annual mean WNP TC size correlates strongly with the ENSO index (JASO average), with r ≈ 0.76 (Fig. 15). In addition, an even higher correlation (r ≈ 0.95) is found between the annual mean TC lifetime and TC size over the WNP (Fig. 16), which further reinforces the conclusions discussed in relation to Fig. 5. Both correlations are significant at the 99% confidence level based on a Student’s t test. The interannual variation of TC size (Fig. 15a) shows the mean TC size over the WNP in the strong La Niña year of 1999 is especially small, which agrees with the findings of Chan and Yip (2003). During strong La Niña years, the STR position and TC formations shift westward across the western Pacific (Wang and Chan 2002; Wu et al. 2004). The westward shift in TC formations is related to the reduced overwater tracks prior to landfall, thus reducing the TC lifetime. Over the NA, no such correlations are found because the strict data selection criteria used in this study result in an annual average of 6.6 TCs over the NA, which unfortunately is not large enough to identify interannual variations.

Fig. 15.
Fig. 15.

(a) Annual means of size and ENSO index (JASO average) over the WNP. Vertical bars represent the 95% confidence intervals of TC size in the t distribution. Numbers above the x axis indicate the number of cases. (b) The corresponding scatter diagram of ENSO index (JASO average) vs size over the WNP. The straight line indicates the regression line.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

Fig. 16.
Fig. 16.

(a) Annual mean sizes and lifetimes over the WNP. Vertical bars represent the 95% confidence intervals of TC lifetime in the t distribution. Numbers above the x axis indicate the number of R17 cases and number of TCs (with parentheses). (b) The corresponding scatter diagram of TC lifetime vs size over the WNP. The line indicates the regression line.

Citation: Monthly Weather Review 140, 3; 10.1175/MWR-D-10-05062.1

6. Summary and discussion

Weatherford and Gray (1988a,b) studied the tropical cyclone (TC) structure using 3 yr (1980–82) of aircraft reconnaissance data over the western North Pacific (WNP). They were the first to introduce the concept of outer-core strength (OCS) for describing the outer structure of TCs. In this comprehensive statistical study, an 11-yr (1999–2009) climatology of both TC size (azimuthally averaged radius of 17 m s−1 ocean-surface winds, R17) and strength (azimuthally averaged total surface wind speed within 1° and 2.5°-latitude radius from TC center, OCS) over the WNP (including the South China Sea) and the North Atlantic (NA, including the Gulf of Mexico and the Caribbean Sea) is further made using QuikSCAT satellite data. Based on the strict data selection criteria, the sample size is the largest among all of the investigations that are based on remote sensing techniques (cf. Weatherford and Gray 1988a,b; Liu and Chan 1999; Chavas and Emanuel 2010; Lee et al. 2010). This study therefore provides more robust results compared with those of previous studies. As the statistical results found in strength are similar to those found in size, the climatology of large, medium, and small TCs is likely to be applicable to TCs with high, average, and low strength, respectively.

In addition to results that are consistent with previous results, this study identifies seasonal, interannual, and spatial variations of each category of TC size. Such climatological attributes are explained in terms of TC tracks, lifetimes, and subtropical ridge (STR) activity. By comparing the results from different studies, this study further hypothesizes the possible existence of an interdecadal variation in TC size.

a. Summary

The mean and standard deviation of TC sizes are found to be 2.13° and 0.98° latitude for the WNP TCs, and 1.83° and 0.75° latitude for the NA TCs. The corresponding values for TC strength are 19.6 and 5.0 m s−1 over the WNP, and 18.7 and 5.0 m s−1 over the NA. These results suggest that compared to the NA TCs, WNP TCs are 0.3° latitude larger in size and 1 m s−1 higher in strength on the average. These may probably be due to the Asian winter monsoon and southwesterly summer monsoon enhancements (Liu and Chan 2002) and the much larger warm pool area over the WNP so that TCs there are under more favorable conditions to grow and strengthen than those in the NA. A strong correlation (r ≈ 0.9) is found between size and strength, which is consistent with the 3-yr aircraft reconnaissance study conducted by Weatherford and Gray (1988b). This is an important result that suggests using three parameters (size, strength, and intensity) to describe the structure of a TC may be superfluous; in other words, only size and intensity would be sufficient.

The mean TC sizes and lifetimes are found to vary seasonally in both basins. The midsummer (July) and late-season (October) TC sizes and lifetimes are significantly larger and longer over the WNP. Meanwhile, over the NA, the highest value of the monthly mean sizes of TCs is found in September.

The percentage frequency of large TCs is found to vary spatially and seasonally. The WNP large TCs are likely to occur farther west (120°–140°E) and south (20°–30°N) in midsummer (July and August) but farther east (140°–150°E) and north (30°–40°N) in the late season (September and October). Over the NA, TCs occurring at high latitudes (>40°N) in the late season (September) tend to be large. TCs occurring over the eastern Gulf of Mexico (80°–90°W) are also likely to be large. However, NA TCs tend to be small if they are located within 10°–20°N. These spatial distributions of different categories of TC size are probably due to the seasonal migration of the STR, which affects the tracks and lifetimes of TCs.

In terms of interannual variation, the annual means of the WNP TC size are strongly related to the effect of El Niño–Southern Oscillation (ENSO), with more large size and high strength in warm events (El Niño) and vice versa in cold events (La Niña). This comprehensive study verifies the preliminary results of Chan and Yip (2003) using 4 yr of data. Similar results are found between TC lifetime and size, which suggests that the longer the lifetime, the larger would be the TC.

All these results are useful in both the understanding of the dynamical structure of TCs and the operational forecasting of the radius of gale-force winds. The climatology presented here represents the most comprehensive study to date and the results should therefore be robust.

b. Discussion

Two seasonal TC size (based on R17) peaks (July and October) are found over the WNP, a result different from previous studies (Brand 1972; Merrill 1984; Liu and Chan 1999), which show only one seasonal size (based on ROCI or relative vorticity) peak (in October). In addition, the seasonal maximum ROCI over the NA (from both the GEOS-5 data and the NHC best-track data) is found to be in November, which differs from Merrill (1984)’s result that the seasonal maximum ROCI (1957–77 average) occurs in October. These differences may be due to the sampling problems (e.g., number of cases, study periods, dataset, etc.) or the different definitions of TC sizes of different studies. It is also plausible that TC sizes over the two basins vary on interdecadal time scales, which could be related to the findings of the interdecadal variations of TC activities from previous studies (Yumoto and Matsuura 2001; Matsuura et al. 2003; Chan 2005; Liu and Chan 2008). For instance, Yumoto and Matsuura (2001) identified a high-frequency period (HFP) when TC activity is enhanced, and a low-frequency period (LFP) when TC activity is reduced. Their study showed that the area of TC genesis in HFPs extends more to the east than that in LFP. In other words, TC lifetime may also vary in a similar manner so that TCs in HFPs have a longer lifetime (and hence can be larger) and a shorter lifetime (and hence tend to be smaller) in LFPs. However, the veracity of this preliminary hypothesis and the underlying mechanisms need to be further investigated.

Moreover, Merrill (1984) suggested the angular momentum transports between large and small TCs are different while Liu and Chan (2002) suggested the size of a TC depends on the synoptic flow patterns nearby. Hill and Lackmann (2009) modeled environmental relative humidity as one factor controlling TC size. Therefore, as over 10 yr of QuikSCAT data are available, more comprehensive investigation into such factors as size and strength of TCs, as well as the physics behind these factors, can also be conducted, which will be the next step of the present study.

Acknowledgments

This study is from part of the first author’s Ph.D. work, which is supported by the Research Studentship from City University of Hong Kong and the Hong Kong Research Grants Council Grant CityU 100209. The authors thank Deborah Smith for her support of the RSS QuikSCAT data description. They would also like to offer their thanks to the editor, Professor Pat Harr, and two anonymous reviewers for their comments, which led to improvements in the manuscript.

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1

A threshold of 40 kt (rather than 34 kt) and a time period of 12 h (rather than every 6 h or 1 day) are set here because the best-track datasets only give 1-min MSW, which is not consistent with the QuikSCAT mean surface wind (~8–10 min) and QuikSCAT is a polar-orbiting satellite that generally has swaths twice per day (~12 h in between) over a given geographic region. Therefore, in order to have a fair count of the total possible cases, an increment in the wind speed and the matched time period should be made.

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