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The Tropical Rainfall Potential (Trap) Technique. Part I: Description and Examples Ϩ STANLEY Q

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The Tropical Rainfall Potential (Trap) Technique. Part I: Description and Examples Ϩ STANLEY Q 456 WEATHER AND FORECASTING VOLUME 20 The Tropical Rainfall Potential (TRaP) Technique. Part I: Description and Examples ϩ STANLEY Q. KIDDER,* SHELDON J. KUSSELSON, JOHN A. KNAFF,* RALPH R. FERRARO,#,@ ϩ ROBERT J. KULIGOWSKI,# AND MICHAEL TURK *Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado ϩNOAA/NESDIS/OSDPD/Satellite Services Division, Camp Springs, Maryland #NOAA/NESDIS/Center for Satellite Applications and Research, Camp Springs, Maryland @Cooperative Institute for Climate Studies, University of Maryland, College Park, College Park, Maryland (Manuscript received 16 February 2004, in final form 9 August 2004) ABSTRACT Inland flooding caused by heavy rainfall from landfalling tropical cyclones is a significant threat to life and property. The tropical rainfall potential (TRaP) technique, which couples satellite estimates of rain rate in tropical cyclones with track forecasts to produce a forecast of 24-h rainfall from a storm, was developed to better estimate the magnitude of this threat. This paper outlines the history of the TRaP technique, details its current algorithms, and offers examples of its use in forecasting. Part II of this paper covers verification of the technique. 1. Introduction accurate rainfall forecasts can be made is beyond the state of the art. Radar observations of storm rain rate For centuries, the wind and waves caused by tropical and rain area are valuable, particularly for short-term cyclones have menaced mariners and coastal dwellers. (ϳ1 h) forecasting of urban flash flooding and land- Enormous resources have been invested in observing slides, but only when the storm is within radar range of and forecasting these killers. Today, largely because of the coast. Twenty-four hours before landfall, when weather satellites, no tropical cyclone anywhere on warnings and evacuation orders need to be issued, earth goes undetected or evades the eyes of forecasters. tropical cyclones typically are beyond radar range. As the storm approaches, most people are able to es- Weather satellite observations, and in particular micro- cape the storm’s fury by moving inland. Consequently, wave observations, have, therefore, become the chief attention has shifted to a different threat from tropical source of data in forecasting tropical rainfall potential cyclones. Rappaport (2000) found that in the contigu- (TRaP), or the amount of rain to fall from a tropical ous United States during the period 1970–99, freshwa- cyclone in a (usually) 24-h period. ter floods accounted for more than half of the 600 This paper details the TRaP technique. Section 2 deaths directly associated with tropical cyclones. Else- summarizes the history of the TRaP technique, with the where in the world the toll can be much higher. Thus, current approach presented in section 3. The perfor- forecasting the rainfall potential of tropical cyclones mance of the current technique is illustrated in section has taken on new importance in our struggle to protect 4 via several examples, followed by discussion in sec- life and property. tion 5. The second part of this paper (Ferraro et al. One would like to rely on numerical weather predic- 2005, hereafter Part II) describes verification of the tion models to make such forecasts, but while the storm TRaP technique. is offshore, few observations are available, and initial- izing models with sufficient details of the storm so that 2. TRaP history Corresponding author address: Stanley Q. Kidder, CIRA, Col- Because of the importance and danger of flooding orado State University, Fort Collins, CO 80523-1375. caused by tropical cyclones, TRaP has a long history, E-mail: [email protected] which is summarized in this section. WAF860 AUGUST 2005 K I D D E R E T A L . 457 a. Rule of thumb creased approximately exponentially with distance from the center, but were found to be a function of Perhaps the first method for estimating rainfall from intensity and geographic location. Maximum values, tropical cyclones was the “rule of thumb” [attributed to which were reported to agree well with rain gauge data, R. H. Kraft by Pfost (2000)] that 100 divided by the were close to 13 mm hϪ1 near the center of very strong speed of the storm in knots yields an estimate of the tropical cyclones (maximum winds Ͼ49 m sϪ1) and 24-h rainfall in inches. This rule takes into account the close to 3 mm hϪ1 near the center of tropical-storm- fact that faster-moving storms reside over a point for strength (Ͼ17 m sϪ1) tropical cyclones. In addition to less time than slower-moving storms, and therefore, the mean rain rates found in this study, large systematic rainfall at a point should be inversely related to storm asymmetries were found in composites that were func- speed. This rule, however, makes no allowance for tions of geographical location, intensity, and forward storm size or rain rate, both of which can vary consid- speed. erably from storm to storm. b. Observational studies c. Spayd and Scofield Spayd and Scofield (1984) realized that the expected Several survey studies have been conducted to deter- duration of rainfall at a point as a tropical cyclone mine the average rainfall associated with tropical cy- passes overhead is approximately DVϪ1, where D is the clones. Riehl and Malkus (1961) and Simpson and distance across the storm (measured in the direction of Riehl (1981) reported that rainfall decreased exponen- motion), and V is its speed. The total rainfall, then, tially with distance from the cyclone center. Within 20 would be R DVϪ1, where R is the average rain rate n mi (37 km) of the center, rain rates averaged about avg avg Ϫ1 Ϫ1 of the storm. The rule of thumb discussed above, then, 1.3 in. h (33 mm h ). In successive 20 n mi annuli, Ϫ R D. the rain rates averaged 0.66, 0.33, and 0.16 in. h 1 (16.8, uses 100-in. knots as the “average” value of avg 18.4, and 4.1 mm hϪ1). Using these findings, a relation- Spayd and Scofield used infrared satellite imagery to identify storm features or cloud types, and then as- ship for the maximum 24-h rainfall (R24) as a function of the speed of translation of storm (V) was developed: signed a rain rate to each cloud type. They defined the tropical rainfall potential as ϭ ͑ V͒ ͑ ͒ R24 a b , 1 ϭ Ϫ1 ͑ ͒ TRaP V ͚ RiDi, 2 where a ϭ 31.1 in. (790 mm) and b ϭ 0.915 for V in i miles per hour (or b ϭ 0.926 for V in knots, or b ϭ 0.946 where D is the distance (in the direction of storm mo- for V in kilometers per hour). This constituted the first i tion) across cloud type i, and R is the rain rate assigned operational tropical cyclone rainfall estimation method i to cloud type i. The four cloud types used were central (Pfost 2000). While this technique is an improvement dense overcast (CDO), wall cloud (WC), embedded on Kraft’s rule of thumb, rain rates are highly variable cold convective tops (ECT), and outer banding (OBA). from storm to storm. Following Scofield and Oliver (1977), an analyst as- Using a similar compositing approach Goodyear signed a rain rate to each cloud type depending on the (1968) examined 46 tropical storms and hurricanes cloud-top temperature and its trend in the infrared sat- making landfall on the Gulf Coast of the United States ellite imagery. The rain-rate ranges were 0.01 to 2.00 in. to produce a 48-h rainfall pattern with respect to the hϪ1 (0.3–50 mm hϪ1) for CDO, 1.00 to 3.00 in. hϪ1 tropical cyclone center. His study showed that the av- (25–75 mm hϪ1) for WC, 0.10 to 2.00 in. hϪ1 (3–50 mm erage maximum rainfall of 6 in. (150 mm) occurs hϪ1) for OBA, and 0.05 to 4.00 in. hϪ1 (1–100 mm hϪ1) roughly 25 to 50 miles (40 to 80 km) inland and 25 to 50 for ECT. Results of the Spayd and Scofield technique miles (40 to 80 km) to the right of the storm track. compare well with rain gauge data, but the technique is Again, much variability was found from storm to storm. labor intensive. However this method is still used to assess potential risks of flooding (Pfost 2000). d. NESDIS/SSD TRaP Lonfat et al. (2004), in the most comprehensive study of tropical cyclone rain rates to date, used rain-rate With the arrival of cloud-penetrating microwave ob- information derived from the National Aeronautics and servations of tropical cyclones, the rain rate could be Space Administration (NASA) Tropical Rainfall Mea- more directly estimated, and cloud typing could be suring Mission (TRMM) to composite rain rates of eliminated. Since 1992, the Satellite Services Division global tropical cyclones for a 3-yr period to produce (SSD, which encompasses the Satellite Analysis Branch) climatological rain rates. These rain rates again de- of the National Environmental Satellite, Data, and In- 458 WEATHER AND FORECASTING VOLUME 20 formation Service (NESDIS) has experimentally used the operational Special Sensor Microwave Imager (SSM/I) rain-rate data from the Defense Meteorologi- cal Satellite Program (DMSP) satellites to produce a rainfall potential for tropical disturbances expected to make landfall within 24 h to at most 36 h. The launch in 1998 of the first Advanced Microwave Sounding Unit (AMSU) on the National Oceanic and Atmospheric Administration (NOAA) satellites and the 2001 addi- tion of the NASA TRMM Microwave Imager (TMI) data brought additional microwave-based estimates of rain rate. (The TRMM satellite was launched in 1997; the TMI data became available at SSD in 2001.) The NESDIS/SSD technique was summarized in Kidder et al.
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