Annual Volume and Area Variations in Tropical Cyclone Rainfall Over the Eastern United States

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Annual Volume and Area Variations in Tropical Cyclone Rainfall over the Eastern United States

RICARDO C. NOGUEIRA AND BARRY D. KEIM Louisiana Ofﬁce of State Climatology, Department of Geography and Anthropology, Louisiana State University, Baton Rouge, Louisiana

(Manuscript received 22 September 2009, in ﬁnal form 1 April 2010)

ABSTRACT

This paper examines tropical cyclone (TC) rainfall in the eastern United States from the perspective of documenting accumulated annual water volumes and areas of the precipitation. Volume is a value that merges both rainfall depth and rainfall area into a single metric for each year that can be directly compared between individual years. Area represents the total land area affected by tropical rains. These TC rainfall metrics were then compared to the ENSO and the Atlantic multidecadal oscillation (AMO). Time series of annual TC water volumes show an annual average of 107 km3. The maximum volume was produced in 1985 with 405.8 km3, driven by Hurricanes Bob, Claudette, Danny, Elena, Gloria, Henri, Juan, and Kate as well as by Tropical Storms Henri and Isabel. The lowest TC volume occurred in 1978 with 8.9 km3. ENSO phases did not show any statistical correlation with TC frequency in the eastern United States. However, AMO showed a signiﬁcant correlation with volume and the number of storms affecting the region. TC rainfall volume and area in the eastern United States showed a strong correlation. However, there are exceptions, whereby 1985 stands out as an exceptional volume year though the area affected is not as impressive. In contrast, 1979 is an example when TCs covered a large area with a corresponding small rainfall volume, in part because of the rapid forward movement of the storms, for example, Hurricanes David and Frederic. Since 1995, TCs have become more numerous, producing larger volumes and affecting larger areas.

1. Introduction flooding (e.g., Tropical Storm Allison in Houston, Texas, in 2001), and drought-mitigating rains (e.g., Hurricanes Tropical cyclones (TCs) affecting the eastern United Katrina and Rita across Texas, Louisiana, and Mississippi States are responsible for causing economic losses and in 2005). As a result, this paper will address the effects loss of human life (Blake et al. 2007). These events are of Atlantic TC rainfall (including storms in the Gulf of generally thought of as storms with coastal effects with Mexico and Mexico) in the eastern United States. high winds and surge, but they can also produce heavy Tropical cyclone activity in the North Atlantic expe- rainfall along the coast, as well as much farther inland. riences great variability from the intra-annual (e.g., Keim As a result, they can be an important contributor to and Robbins 2006), interannual (e.g., Bove et al. 1998), monthly and seasonal rainfall totals during hurricane and interdecadal (Gray 2007; Landsea et al. 1999) time season. Indeed, this was the case from June to Novem- scales. Clearly, no two hurricane seasons are identical, ber in the eastern United States as documented by Cry but there is some long-term predictability to tropical (1967), Knight and Davis (2007), and Nogueira and Keim activity in the North Atlantic basin that stems from (2010). However, the total volume of water and total area atmospheric teleconnections. For example, Landsea et al. affected by Atlantic TC rainfall in the eastern United (1999) point out that the overall TC activity is associated States has never been determined. Implications of TC with North Atlantic sea surface temperatures (SSTs)— rainfall input over land include river basin flooding (e.g., termed the Atlantic Multidecadal Oscillation (AMO)— from Hurricane Camille in Virginia in 1969), urban flash combined with other modulating environmental factors such as El Ninõ–Southern Oscillation (ENSO). An em- Corresponding author address: Ricardo Nogueira, Louisiana pirical relationship between Atlantic SSTs and TC activity State University, E348 Howe-Russell, Baton Rouge, LA 70803. was identified, whereby warmer Atlantic SSTs enhance E-mail: [email protected] the development of TCs (Shapiro and Goldenberg 1998;

DOI: 10.1175/2010JCLI3443.1

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Molinari and Mestas-Nun˜ ez 2003) and landfalls in the Larson et al. (2005) found this to be reasonable. Rainfall eastern United States (Keim et al. 2007). Furthermore, totals, however, tend to be larger on the right side of the El Nin˜ o events have been shown to reduce TC activity track because of the onshore flow of moisture (Jones through enhanced upper-tropospheric westerly wind 1987; Powell 1987) and smaller on the left side because shear over the Caribbean Basin and the equatorial At- of the entrainment of drier air from the continent. How- lantic, while La Ninã events increase activity (Gray 1984; ever, when TCs begin interacting with extratropical Bove et al. 1998). Hence, the interaction between AMO weather systems, rainfall patterns get increasingly asym- and ENSO looms particularly large regarding the tropical metric (Larson et al. 2005). The 500-km criterion is an storm and hurricane effects in the eastern United States. operational definition to reduce the influences of these Therefore, the objectives of this study are as follows: systems. TC-related precipitation was considered as any pre- 1) to determine the annual volume of rain produced cipitation produced by landfalling tropical storms and by tropical storms and hurricanes over the eastern hurricanes as well as for those storms that tracked within United States; an offshore distance of 500 km (determined by the Arc- 2) to determine the total area that received tropical- Map buffer), whereas land lies within the tropical cyclone storm- and hurricane-induced precipitation in the rain swath. The 6-hourly data available through the Na- eastern United States each year; and tional Hurricane Center (NHC) in the Atlantic basin 3) to determine if teleconnections (AMO and ENSO) Hurricane Database (HURDAT; Jarvinen et al. 1984) are associated with the annual volumes of rain as well was used to determine the timing and location of the as the annual area sizes of the eastern United States storm to properly appropriate the rainfall. If a storm was that are affected by the tropical cyclones. denoted in this database as either subtropical, extratropical, or as a tropical depression, then the associated rainfall with those systems was no longer included in this 2. Data and methods analysis. Remnant lows can in some instances produce Separating rainfall into tropical and nontropical cy- very high rainfall totals (i.e., remnants of Tropical Storm clone components is a challenging task, as TCs can pro- Amelia in 1978 or Tropical Storm Erin in 2007); however, duce rainfall for hundreds of kilometers from their centers these systems often interact with extratropical weather (Larson et al. 2005). However, previous research provides systems as well and thus were not included in this anal- guidance regarding the size of the rainfall swath produced ysis. Compared to other studies that include remnants by TCs. For example, Cry (1967) considered rainfall to be of tropical storms (i.e., Knight and Davis 2007), these tropical within the limits of the TC circulation ranging methods would underestimate rainfall totals. We also from less than 100 to more than 800 km, depending on note that prior to 1968, there is no designation of sub- each storm’s rainfall characteristics. Rao and Macarthur tropical storms in HURDAT, and a small percentage of (1994) gridded each storm’s rainfall swath and deter- events that would now be subtropical are designated as mined the rainfall within each grid cell. Gleason (2006) tropical (Landsea et al. 2008). As performed by Cry used a simple partition method, classifying any rainfall (1967), rainfall data were divided into two subsets: one #600 km from the center of the storm as ‘‘tropical.’’ called tropical rainfall (TR), which includes the accu- Englehart and Douglas (2001) found that in 90% of cases, mulated TC daily rainfall for each site for each month, TC rainfall occurs within 600 km from the center. In the and the other called nontropical rainfall (NTR), which is end, they used a 550-km radius from the center of each derived as the difference between TR and U.S. Histor- storm to assign surface weather stations as receiving TC- ical Climatology Network (USHCN) monthly precipita- derived rainfall data. Knight and Davis (2007) included tion totals at each site. all rainfall data associated with the tropical storm, even Rainfall data from 1960 to 2007 were extracted from after becoming extratropical or associating with a fron- monthly rainfall observations from the USHCN monthly tal system. This approach yields a relatively high con- precipitation and temperature data (Williams et al. 2007). tribution of TC rainfall in monthly totals. This dataset contains 1221 high-quality stations from the In this study, a conservative approach was used in U.S. Cooperative Observer Network within the 48 con- considering tropical rainfall related to the distance of the tiguous United States, and it has undergone extensive center of TC. Using guidance from these previous efforts, quality assurance checks and includes only the most re- a500-km(;310 miles) radius centered on each storm was liable and unbiased long-term records. Of the 1221 sta- used to delineate the area affected by tropical precipita- tions, monthly precipitation data were obtained from tion. The TC rain shield was assumed symmetric around a subset of these data totaling 717 stations in the eastern the storm center, and sensitivity analysis performed by United States (Fig. 1). TC rainfall contributions are less

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FIG. 1. Study region and USHCN stations. than 1% west of Minnesota and Iowa, and north of Kansas for all stations regardless of the time of observation, since (Cry 1967; Knight and Davis 2007); hence, these areas the vast majority of stations have morning observation were not considered in this study. Daily precipitation times. Basically, the choice was either to be inclusive or data were obtained for the same 717 stations through exclusive of the tropical rainfall in this circumstance, and the Southern Regional Climate Center (SRCC) Applied we chose to be inclusive. Our decision was based on the Climate Information System (ACIS; see Hubbard et al. findings that the transition declaration by the National 2004; ACIS 2009) to update the USHCN dataset to 2007 Hurricane Center is a subjective decision and that there for the delineated region. The source for both datasets is considerable uncertainty in the accuracy of the specific (UNHCN and ACIS) is National Oceanic and Atmo- point in time when this transition occurs (Hart and Evans spheric Administration (NOAA)’s National Climatic 2001), hence including the entire observational day of Data Center. A sample of stations was cross-checked from rainfall when this occurred seemed reasonable. both networks, and very few differences between the Environmental Systems Research Institute, Inc. (ESRI)’s datasets were found. When differences arose in our pe- ArcMap 9.2 was used to plot and display all weather sta- rusal, it was because there were missing data in the ACIS tions by year, subset those stations by each storm’s buffer dataset. In such cases, USHCN made efforts to fill in short region, and perform spatial analyses (Johnston et al. 2001). periods of missing data using nearby stations. This was accomplished by importing hurricane track One incongruity we addressed is that the HURDAT shapefiles from NOAA’s Coastal Services Center. These dataset provides data in 6-hourly intervals, yet the rainfall data are generated from the NHC’s HURDAT dataset. data are provided daily. Most National Weather Service For each storm track, a 500-km buffer was produced. A cooperative stations take observations in the morning, simple kriging quartile tool was then used to create an near 1200 UTC, thereby representing an observational interpolated TC rainfall surface (Chapman and Thornes day of 1200 UTC from the previous day to 1200 UTC on 2003). Kriging is a stochastic technique—similar to in- the day of the observation. When a storm transitions to verse distance weighting (IDW)—that uses linear com- extratropical, or is downgraded to a depression within binations of weight at known points to estimate values to this 24-h ‘‘observational day’’ window of time, the entire unknown points. Kriging has been used effectively to daily rainfall logged at the end of the observational day interpolate rainfall data (Earls and Dixon 2007; Mira´s- was included in this analysis. This practice was consistent Avalos et al. 2007).

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The Lambert equal-area conic projection was used noted that during the cold phase ENSO (La Ninã) events, to minimize errors in calculating the rainfall areas and the United States experiences a larger number of TCs and volumes of TCs. The first step in this endeavor selected more damage compared to the warm ENSO (El Nin˜ o) all USHCN stations in the study area that fell within phases. 500 km of the center of each storm’s position and then The ENSO monthly SST anomalies used in this study computed the accumulated rainfall total related to TCs were obtained from the Nin˜ o-3.4 region (58N–58S, 1708– at each station. The second step interpolated a rainfall 1208W) from NOAA’s Climate Prediction Center (CPC), pattern using simple kriging, which is then converted to based on a threshold of 0.38C, as suggested by Trenberth a raster format (cell size 5 2km3 2 km). Lastly, the (1997). The ENSO index is identified using 6-month raster pattern over the buffer area is used to calculate (June–November) averages of SST anomalies. El Nin˜ o volume by implementing the following formula: was defined as when the SST anomaly average was greater than 0.38CandaLaNinã as when the SST anomaly av- annual rainfall volume (km3) 5 annual pixel average erage was at least 0.38C below average. Figure 2 shows TC rainfall (km) 3 annual number of pixels 3 total buffer area by year (km2). theENSO-3.4SSTanomalytimeseriesandtheENSO phases (cold, warm, and neutral). After interpolating the rainfall pattern over land in the eastern United States, the depth and area of rainfall for 2) AMO each hurricane season is converted into the total TC- AMO is defined by the SST between warm and cold induced volume of water. Volume, therefore, is a value phases within a 65–80-yr cycle (Kerr 2000). AMO showed that merges both rainfall depth and rainfall area into warm phases from periods 1860–80 and 1940–60 and cold a single metric for each year that can be directly com- phases from periods 1905–25 and 1970–94. A new AMO pared between individual years. It is presented in units warm phase started circa 1995 (Enfield et al. 2001) and of cubic kilometers. continued through the end of the study period in 2007. Teleconnections The relationship between TC frequencies and decadal- scale SSTs has been well documented (Knight et al. 2005; TC rainfall is characterized by interannual and inter- Kerr 2000; Landsea et al. 1999; Shapiro and Goldenberg decadal variability. Those variations may be related to 1998; Rao and Macarthur 1994). climate teleconnections such as ENSO and AMO. In AMO was named by Kerr (2000), and it is an index of this paper, effects of ENSO and AMO in the TC rainfall North Atlantic sea surface temperatures between 08 and over the eastern United States are examined. Listed 608N latitude and 7.58 and 758W longitude. The AMO next are seven variables related to TC rainfalls chosen to phase affects weather patterns, such as rainfall and river test for correlations with ENSO and AMO: Month_tot flow, over the continental United States (Enfield et al. represents all rainfall during hurricane season extending 2001) and is linked to Atlantic hurricane activity (Landsea from June–November rainfall, including both tropical et al. 1999; Goldenberg et al. 2001; Gray 2007). The AMO and nontropical rainfall; TC_tot is the total amount of dataset was obtained from the NOAA Earth System Re- rain by month and season produced by TCs only; Non_tc search Laboratory’s Physical Sciences Division laboratory. tot is the total rainfall produced by nontropical systems NotethatAMOdatawereaveragedbythe12-month and is derived by subtracting TC_tot from Month_tot; (January–December) anomaly values. These values are Percentage_tc is the percentage of total rainfall pro- plotted as a time series in Fig. 3. duced by TCs; Number of Storms is the number of storms by year affecting the eastern United States; VOLUME represents the total rainfall volume produced by TCs; 3. Results and discussion AREA is the area in square kilometers affected by the The study period showed an average of 313 (of a total TC rain shield (based on the 500-km buffer). of 717) stations were affected by TC rainfall per year (Fig. 4a). Note that a station can be counted more than 1) ENSO once in the same year, if more than one storm affects the Henderson-Sellers et al. (1998) pointed out that El Ninõ site. Also, the number of stations is constant over time events are related to the seasonal frequency and inter- over the study area at 717. The year 1990 had the lowest annual variations of tropical cyclone activity. Further- number of stations affected at 52 and 1985 had the highest more, several studies relate ENSO with tropical cyclone at 936, demonstrating the double—or even triple— activity (Landsea et al. 1996; Bove et al. 1998; Landsea counting (or more) of some stations in a single year. The et al. 1999; Pielke and Landsea 1999; Tonkin et al. 1997; number of affected stations showed a slight positive trend, Enfield et al. 2001; Gray 2007). Pielke and Landsea (1999) but it was not statistically significant based on the Kendall

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FIG. 2. Pacific Nin˜ o-3.4 region SST anomalies and the Japan Meteorological Agency (JMA) ENSO phases (gray for positive; white for negative; and black for neutral, based on 0.38C thresholds). A more detailed description of the Nin˜ o-3.4 index can be found at online (at http://www.cpc.ncep.noaa.gov/data/indices/). tau-b correlation test. Instead, it shows a multidecadal and a positive trend after 1995. The number of stations oscillation, with affected stations above average from affected by TC rainfall per year is directly related to the the 1960s to the mid-1970s and after the mid-1990s, and number of storms. However, averaging the number of affected stations below average from the late 1970s to stations affected by the number of TC per year shows the early 1990s. The number of affected stations showed a different result (Fig. 4b). This time series serves as an a high correlation with the AMO phase, significant at the index of the annual average spatial extent of the storms 99% confidence level using Student’s t test. The 5-yr that occurred each year. The greater the value, one can moving average shows two periods with a lower number assume that the storms of that year affected larger areas of stations affected by TC rainfall: 1971–82 and 1987–94, than if this value was smaller. However, this is not an

FIG. 3. The 5-yr-averaged AMO temperature anomalies (June–November). The AMO dataset can be downloaded from the NOAA Web site (available online at http://www.cdc.noaa.gov/ Timeseries/AMO/).

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FIG. 4. (a) Number of TC-affected stations by year (stations can be double counted, if there is more than one TC in a year) in the eastern United States (bars), 48-yr average (dashed line), and 5-yr moving average (bold line). (b) Total number of affected stations averaged by the number of storms per year (bars), 48-yr average (dashed line), and the 5-yr moving average (bold line). Vertical dashed lines represent change of AMO phases (warm, cold, warm). index for the number of storms or the total area affected (a # 0.05)andsimilartoKarlandKnight(1998)and each year, but rather the average area affected per storm as described in the Intergovernmental Panel on Cli- event. The average number of affected stations per storm mate Change (IPCC) special report on climate change shows less interannual variability when compared with (Houghton et al. 1996, chapter 8). the total number of affected stations per year. Figure 5c is the TC-accumulated total rainfall by year, Total rainfall (TC and non-TC rainfall) accumulated summed for all USHCN stations in the eastern United for all 717 stations from June to November in the study States. There is some bias introduced in this figure be- period is shown in Fig. 5a. Figure 5b represents the cause of geographically varying station densities. The TC anomalies from average, in units of standard deviations rainfall component accumulated each year is influenced (std devs) from the mean. Overall, total rainfall exhibits by the number of storms (based on the 500-km thresh- great interannual variation (2.5 3 standard deviations). old), the duration of each storm, the station density most The time series presents a drier period in the first decade affected, and most likely the storm’s forward velocity. (1960–70) that is likely related to the positive phase of Results are nevertheless intriguing. The time series shows AMO (see Fig. 3), as described by Enfield et al. (2001). large interannual variability of TC rainfall over land in Rainfall after 1970 was characterized by high interan- the eastern United States (Figs. 5c,d), perhaps with some nual variability, and from 1992–96, there was a sequence relationship to known patterns of AMO. During the of 5 yr with values higher than average followed by 5 yr AMO negative phase, from 1970 to the mid-1990s, annual (1997–2001) with values lower than average. Total rain- TC rainfall sums were predominantly below average and fall has a slight overall positive trend, and the Kendall then mostly above average after 1995 (see Fig. 3). The tau-b test indicates this trend is statistically significant year 1985 had the largest total (3.6 standard deviations

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FIG. 5. Time series of seasonal (June–November) rainfall from 1960 to 2007 and AMO phases (vertical dashed lines). (a) Total rainfall and total 5-yr rainfall moving average (line). (b) Total rainfall anomalies from average (bars) (average 5 40 257 cm, std dev 5 3779 cm). (c) TC rainfall accumulated by year (bars) and 5-yr moving average (line). (d) TC rainfall anomaly accumulated by year (average 5 1931 cm, std dev 5 1731 cm). (e) TC rainfall percentage of the total rainfall (bars) and 5-yr moving average (line).

Unauthenticated | Downloaded 09/25/21 02:59 AM UTC 4370 JOURNAL OF CLIMATE VOLUME 23 from the mean) and 1978 had the smallest. The moving depression status (Hurricanes Danny and Elena). In average showed a positive trend after the mid-1990s, and these latter cases, the heavy coastal rains are tropical, but the overall time series shows a slight positive trend; how- rains farther inland induced by storm remnants were not ever, it was not statistically significant. Subsequent analysis included as tropical. In some years TCs traveled greater using kriging largely eliminates the varying station density distances, thereby covering larger areas, increasing the problem. potential for rainfall. In other years even with many The TC rainfall contribution to total rainfall (total storms covering a large area, the total volume of rainfall found in Fig. 5a) presents a high yearly variation, from was relatively low. The year 1979 is an example when 2.5% in 1978 to 16% in 1985 (Fig. 5e). The time series TCs covered a large area with a corresponding small shows a negative trend during the first half of the study rainfall volume, in part because of the rapid forward period (1960–84) and a positive trend during the second movement of the storms over the eastern United States, half (1985–2007). Overall, the TC rainfall contribution for example, Hurricanes David and Frederic. After 1995, has a slight positive trend; however, it is not statistically TCs have become more numerous, producing larger significant. volumes and affecting larger areas. Figure 6 displays a time series of the annual TC rain- a. ENSO fall volume for the eastern United States. These annual values are derived by interpolating the spatial patterns The Levene (1960) test for equality of variances and of annual TC rainfall through kriging. The time series the t test were used to compare ENSO warm and cold shows an annual average of 107 km3 of water volume. phases with TC variables (Table 1). Levene’s test is used Although the data show an increasing TC rainfall vol- to test if k samples have equal variances, with no re- ume rate of 1.5 km3 yr21, especially evident after 1995, quirement of a normal distribution. Equal variances the Kendall test for trend indicates that it is not sta- across samples are called homogeneity of variance, and tistically significant. The TC rainfall consists of inter- Levene’s test can be used to verify that assumption. The decadal and interannual variations, also found by Ren test for equality of variances show that only the per- et al. (2007). The volume distribution shows 16 yr with centage of TC rainfall to total rainfall (Percentage_tc) values above average and 32 yr with values below aver- was statistically significant (at the 95% confidence level); age, indicating a right skew to the distribution (Fig. 6b). hence, the null hypothesis of equal variance between However, 65% of those years with positive values oc- La Nin˜ a and El Nin˜ o is rejected. However, the t- test for curred after 1984, indicating that TCs are producing more Percentage_tc under either positive or negative ENSO volume of rainfall in the latter portion of the time series. conditions is insignificant. The variable Number of Storms The maximum of 405.8 km3 (3.6 standard deviations shows a value significant at a 5 0.095, suggesting some- in Fig. 6b) occurred in 1985, driven by Hurricanes Bob, what different storm frequencies during La Nin˜ aevents Claudette, Danny, Elena, Gloria, Henri, Juan, and Kate, when compared to El Nin˜ o. Gray (1984) pointed out and Tropical Storms Henri and Isabel. The second that differences in TC frequency between ENSO phases highest value occurred in 2004 with 313.7 km3 (2.6 3 is related to the storm track, whereby during non– standard deviations on Fig. 6b), driven by Hurricanes El Nin˜ o years, TCs cross the Caribbean more frequently. Cindy, Dennis, Emily, Katrina, Ophelia, Rita, and Wilma, However, despite this result, there is no ENSO effect and Tropical Storms Arlene and Tammy. The lowest with the amount of TC rainfall over the eastern United TC volume occurred in 1978 with 8.9 km3 with only States. Tropical Storms Amelia, Debra, and Hope making any b. AMO contributions. The block of years from 1973 to 1984, with the exception of 1979, was a protracted period with Wendland (1977) noted that the frequency and in- anomalously low input of TC rainfall in the eastern United tensity of TCs are associated with the magnitude and States. distribution of SSTs. Furthermore, Nyberg et al. (2007) Comparing TC area (Figs. 6c,d) with TC rainfall vol- found that the increase in hurricane activity since 1995 ume (Figs. 6a,b) shows a strong correlation (Kendall could be considered a return to normal TC activity when tau-b correlation 5 0.674, p , 0.001). However, there are compared with other periods. some interesting exceptions in the data, whereby 1985 The AMO phases were tested against the suite of var- stands out as an exceptional volume year though the area iables. Levene’s test for equality of variances shows that affected is not as impressive. Storms that year tracked all variables are insignificant; hence, the variances in TC close to the coast (e.g., Hurricane Juan that persisted rainfall do not differ significantly between warm and along Louisiana’s coast for four days) and those that cold SST phases. Using a t test, Month_tot, TC_tot, penetrated inland were quickly downgraded to tropical VOLUME, and Percentage_tc are not significant at

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FIG. 6. Volume and area of TC rainfall from 1960 to 2007. (a) TC rainfall volume (bars) and total 5-yr rainfall moving average (bold line; average 5 103 km3, std dev 5 89 km3). (b) TC rainfall volume (bars). (c) Area of TC rainfall anomaly accumulated by year and 5-yr moving average (average 5 106 km2, std dev 5 4.4 3 105 km2). (d) Area of TC rainfall anomalies accumulated by year.

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TABLE 1. Kendall tau-b test of correlation results: correlations between AMO phase and all variables. Bold numbers represent statically significant (Sig.) correlations at 99% confidence level. Italics indicate numbers that are not statistically significant at the 0.05 level, but are significant at the 0.1 level.

Correlations AMO (January–December) Kendall tau-b Month_tot Correlation coefficient 20.138 Sig. (two tailed) 0.166 TC_tot Correlation coefficient 0.186 Sig. (two tailed) 0.062 Non_tc tot Correlation coefficient 20.193 Sig. (two tailed) 0.053 Percentage_tc Correlation coefficient 0.183 Sig. (two tailed) 0.067 Number of Storms Correlation coefficient 0.310** Sig. (two tailed) 0.004 AREA Correlation coefficient 0.261** Sig. (two tailed) 0.009 VOLUME Coefficient 0.261** Sig. (two tailed) 0.009

* Correlation is significant at the 0.05 level (two tailed). ** Correlation is significant at the 0.01 level (two tailed). a # 0.05. However, VOLUME was significant at a 5 4. Summary 0.054. Nontropical, AREA, and Number of Storms are found to have significantly different mean values between This study represents a first effort to examine TC AMO phases at the 95% confident interval. There are rainfall in the eastern United States from the perspec- significant differences in the values related to the AMO tive of documenting accumulated annual water volumes phase that cannot be attributed to variability alone. The and areas of the precipitation. These TC rainfall metrics North Atlantic SST works as fuel to power TC by pro- were then compared to ENSO and AMO. Time series viding moist enthalpy and instability (Elsner et al. 2008). of annual TC water volumes show an annual average of This suggests that the AMO positive phase could in- 107 km3. The single year with the maximum volume of crease the seasonal number of storms and the large area TC-induced precipitation was in 1985 with 405.8 km3 covered by those storms, and affect nontropical rainfall. driven by Hurricanes Bob, Claudette, Danny, Elena, The Kendall tau-b test was used to determine the pos- Gloria, Henri, Juan, and Kate, and Tropical Storms Henri sible correlations (Table 3). AMO is shown to have a and Isabel. The second highest value occurred in 2004 high correlation with almost all variables. Month_tot with 313.7 km3. The lowest TC volume occurred in 1978 showed a negative correlation with AMO; however, it with 8.9 km3 with only Tropical Storms Amelia, Debra, was not statistically significant. TC_tot and Percentage_tc and Hope making any contributions. The years 1973–84, showed a positive correlation with AMO, significant at with the exception of 1979, was a protracted period with a levels of 0.062 and 0.067, respectively. The variables anomalously low input of TC rainfall in the eastern United related to TC rainfall: VOLUME, Number of Storms, States. and AREA have positive correlations with AMO at In the Atlantic basin in total, TC frequency is related a 5,.01. to ENSO phases, where the warm phase (El Nin˜ o) has In conclusion, ENSO and AMO phases play different fewer storms and the cold phase (La Nin˜ a) has more roles in relation to their influence on TC rainfall in the storms. However, ENSO phases did not show any statis- United States. ENSO has a strong signal in relation to tical correlation with TC frequency in the eastern United the number of storms; however, there is an insignificant States. AMO showed a significant correlation with vol- relationship to the amount of TC rainfall, explained by ume produced by TC rainfall and the number of storms. El Ninõ increasing the upper-atmosphere wind shear over The AMO phases have a negative correlation with non- the Caribbean Sea and tropical Atlantic (Gray 1984). On tropical rainfall; however, monthly rainfall is not statis- other hand, AMO has a statistically significant correlation tically significant. with all variables related to TC rainfall in the eastern When comparing TC area in the eastern United States United States. Warmer SST clearly leads to increases in with TC rainfall volume, a strong correlation was found. TC frequency, resulting in increased inland TC rainfall. However, there are some interesting exceptions in the

Unauthenticated | Downloaded 09/25/21 02:59 AM UTC 15 AUGUST 2010 N OGUEIRA AND KEIM 4373 data, whereby 1985 stands out as an exceptional vol- and Tropical Meteorology, Monterey, CA, Amer. Meteor. ume year though the area affected is not as impressive. Soc., 16C.6. [Available online at http://ams.confex.com/ams/ In that year, storms that tracked close to the coast (e.g., 27Hurricanes/techprogram/paper_108735.htm.] Goldenberg, S. B., C. W. Landsea, A. M. Mestas-Nun˜ ez, and Hurricane Juan persisted along Louisiana’s coast for W. M. Gray, 2001: The recent increase in Atlantic hurricane four days) and those that penetrated inland were quickly activity: Causes and implications. Science, 293, 474–479. downgraded to tropical depression status (Hurricanes Gray, W. M., 1984: Atlantic seasonal hurricane frequency. Part I: Danny and Elena) and were then no longer included in El Nin˜ o and 30 mb quasi-biennial oscillation influences. Mon. the analysis. 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