1. Introduction
Precipitation is one of the most difficult parameters to simulate in GCMs. Indeed, the inability of GCMs to adequately simulate the hydrological cycle is a major source of uncertainty in climate prediction (see, e.g., Webster 1994). One of the primary reasons is the inability to specify realistic diabatic heating rates in the models. While a global problem, the effect is greatest in the Tropics, where much of the global rainfall occurs in mesoscale convective systems that are not resolved by GCMs. Most tropical rainfall occurs in two major categories. Convective rainfall is characterized by relatively brief, intense, and localized rain, while stratiform rain tends to be lighter, of longer duration, and more uniformly distributed over spatial domains of the order of tens to hundreds of kilometers. Because the vertical distribution of heating rates is quite different for convective and stratiform rain (Hartmann et al. 1984; Houze 1989), it is imperative to be able to distinguish accurately between the two. Furthermore, there are other possible types of rain regimes that can be identified when high vertical resolution observations of precipitating cloud systems are available. The specification of diabatic heating is made more difficult by the lack of detailed knowledge of the morphology of convective systems over the vast Tropics. Indeed, precipitation measurement at the surface over the vast oceans remains a challenging problem (Morrissey et al. 1994; McCollum and Krajewski 1997). Clearly, global observations are needed to determine the temporal and areal distribution of precipitation and the four-dimensional distribution of diabatic heating (Simpson et al. 1988; Tao et al. 1990).
Radar wind profilers operating at several different frequencies are now used routinely as research tools to profile atmospheric winds in field campaigns and to monitor winds in support of operational missions. The ability of these profilers to measure the radar reflectivity and observe the motion of hydrometeors directly above the profilers means that the profilers can be used to measure and classify precipitation. Beginning in 1992, 915-MHz wind profilers were deployed in the tropical Pacific as part of the Integrated Sounding Systems (ISS) used in support of the Tropical Ocean–Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). While the primary mission of these profilers was to measure lower tropospheric winds, they also provided a wealth of information on the vertical structure of precipitating cloud systems in the Tropics. Subsequent to TOGA COARE, the National Oceanic and Atmospheric Administration (NOAA) established a network of stand-alone 915-MHz profilers in the tropical Pacific that operate routinely to obtain long-term observations of the tropical atmosphere.
The NOAA/Aeronomy Laboratory (AL) modified a standard 915-MHz profiler for use as a precipitation profiler in support of Tropical Rainfall Measuring Mission (TRMM) Ground Validation field campaigns. This profiler was modified to look vertically with a fixed antenna. In addition, a low-powered 2835-MHz precipitation profiler was developed similar to the 2835-MHz profiler described in Ecklund et al. (1999). The two profilers were operated during all of the TRMM Ground Validation field campaigns except for the South China Sea Monsoon Experiment (SCSMEX): the Texas Florida Underflights (TEFLUN A and B), the TRMM Large-Scale Biosphere–Atmosphere Experiment (TRMM-LBA), and the Kwajalein Experiment (KWAJEX). Collocated with the profiler was a Distromet RD-69 Joss–Waldvogel disdrometer, which can be used to calibrate the profilers at the lowest range gates. At higher altitudes, the calibrated profiler reflectivities can be compared to observations made by scanning radars such as the Weather Surveillance Radar-1998 Doppler (WSR-88D) in Dickinson, Texas, and Melbourne, Florida, and the S-band Dual-Polarization Doppler Radar (S-Pol) in Florida, as presented in Gage et al. (2000).
The TRMM satellite contains a 14-GHz precipitation radar (PR) and a passive microwave radiometer [the TRMM Microwave Imager (TMI)], as well as several other instruments (Kummerow et al. 1998). The PR serves to validate the precipitation estimates from the passive microwave radiometer, although it is unclear what the true precipitation is. The quality of the rainfall estimates for both the PR and TMI invariably rests with the adequacy of the algorithms used for rainfall retrieval and the physical assumptions upon which they are based (Iguchi et al. 2000; Kummerow et al. 2000). The TRMM satellite mission has made major strides toward the goal of an improved representation of tropical precipitation and related quantities (Adler et al. 2000; Kummerow et al. 2000; Petersen and Rutledge 2001; Short and Nakamura 2000). Indeed, several recent studies have shown that assimilation of the TRMM observables leads to impressive improvements in global forecasts (Hou et al. 2001 and Krishnamurti et al. 2000).
The Ground Validation Program (Thiele 1992) is an important component of the TRMM mission. It was designed to provide rainfall products primarily derived from scanning radars to compare with the TRMM rainfall estimates. Primary ground validation sites for TRMM include south Texas and central Florida; Kwajalein, Republic of the Marshall Islands; Guam; and Darwin, Australia. The Ground Validation field campaigns for the most part took place as intensive field campaigns involving aircraft, polarization-diversity scanning radars, and a suite of ground-based instruments. Profilers augmented these instruments at the Ground Validation sites for a limited period of time. Since the TRMM satellite was launched in November 1997, the major campaigns planned for the first 2 yr of the original 3-yr mission were scheduled for 1998 and 1999. TEFLUN A (south Texas), SCSMEX, and TEFLUN B (central Florida) took place in 1998, and TRMM-LBA (Rondonia Province, Brazil) and KWAJEX (Kwajalein, Republic of the Marshall Islands) took place in 1999. Profiler observations presented here are from TEFLUN A and B, TRMM-LBA, and KWAJEX.
The objective of this paper is to present an overview of the contribution of profilers to the TRMM Ground Validation field campaigns. The paper is organized as follows. The instrumentation is presented in section 2, within the context of the field campaigns. Profiler observations from the field campaigns are summarized in section 3. Calibration of the profilers by the disdrometer is considered in section 4. The use of profilers to calibrate scanning radars is briefly considered in section 5, and the retrieval of drop size distributions is highlighted in section 6. A synthesis of the observations and discussion of several issues is contained in section 7, and concluding remarks are contained in section 8.
2. Profiler instruments used in TRMM field campaigns
The NOAA AL developed UHF wind profiler technology for tropical dynamics and climate research (Carter et al. 1995). The UHF profilers, originally developed by the AL for the measurement of lower tropospheric winds in the Tropics, have been applied to precipitation research (Rogers et al. 1993; Gage et al. 1994, 1996; Ecklund et al. 1995; Williams et al. 1995). The UHF profilers are sensitive to hydrometeors and provide a highly resolved time–height cross section of precipitating cloud systems in the Tropics. During 1997–99, with support from TRMM, the NOAA AL developed and deployed a pair of vertically directed precipitation profilers that operate at 915 MHz (UHF) and 2835 MHz (S band) for the TRMM field campaigns (Gage et al. 1999a). In each campaign the profiler pairs collected a unique dataset that is now being intercompared with observations from other instrument platforms used in the TRMM field campaigns, such as scanning radars and the ER-2 Doppler radar (EDOP) flown on the National Aeronautics and Space Administration (NASA) Earth Resources-2 aircraft (ER-2) (Heymsfield et al. 1996, 2000). Direct comparisons with the TRMM PR are difficult to achieve in a 2-month field campaign since it is unlikely that the TRMM satellite will pass directly over the profiler when it is raining.
Measuring precipitation with a vertically pointing scanning Doppler radar was reported by Atlas et al. (1973). The technique has not been routinely performed because of the need to dedicate scanning Doppler radars to the observation of mesoscale systems over a large area. However, the operating modes of Doppler wind profilers are well suited to the routine observation of hydrometeors in the vertical profiler beam. Beginning in the 1980s, VHF profilers, which are more sensitive to “clear air” than UHF profilers, have been used to retrieve the vertical air motion patterns, partition precipitation, and infer diabatic heating rates in tropical convective systems (Wakasugi et al. 1986; Cifelli and Rutledge 1994, 1998; May and Rajopadhyaya 1996). More recently, UHF and VHF profilers have been used in combination to separate vertical air motions from hydrometeor fall velocities and retrieve precipitation parameters (Currier et al. 1992; Rajopadhyaya et al. 1998; Cifelli et al. 2000). Substantial progress has been made in the past five years in the separation of returns from hydrometeors (Rayleigh scatter) and air motions (Bragg scatter) from UHF profiler observations, as presented in Williams et al. (2000a). The dual-wavelength measurements employed by the Aeronomy Laboratory in the Maritime Continent Thunderstorm Experiment (MCTEX) enable the unambiguous separation of Rayleigh scatter and Bragg scatter in profiler observations (Gage et al. 1999b).
a. 915-MHz profiler
For TRMM, two collocated profilers were operated at 915 and 2835 MHz. Typical operating parameters are listed in Table 1. The 915-MHz profiler was a modified version of the 915-MHz wind profiler described in Carter et al. (1995). The major difference is that the precipitation profiler used a fixed antenna constraining observations to the vertical direction rather than a steerable microstrip antenna. During TEFLUN A, the 915-MHz profiler had a nominal 100-m pulse length to provide high-resolution observations with a dwell time of 30 s. In later field campaigns, the 915-MHz profiler was operated in a dual mode to provide more information on vertical air motions. It operated with nominal 100-m pulse length, alternating with a nominal 250-m vertical pulse length.
The minimum detectable signal for the 105-m pulse mode of the 915-MHz profiler used in these campaigns is approximately 3 dBZ at 5 km and 9 dBZ at 10 km. The minimum detectable signal for the 250-m pulse mode is approximately −5 dBZ at 5 km and 1 dBZ at 10 km.
b. 2835-MHz precipitation profiler
The 2835-MHz precipitation profiler was developed especially for TRMM to provide a sensitive low-powered instrument with relatively little sensitivity to Bragg scatter that could profile precipitation parameters. The 2835-MHz system is similar to the 915-MHz profiler and uses an identical control system developed in house for the 915-MHz profiler (Carter et al. 1995). Again, a vertically pointing fixed antenna is used. Its size is chosen to approximate the same observing volume as the 915-MHz profiler. The two profilers were first synchronized to observe simultaneously using the nominal 100-m pulse length. In later campaigns the 2835-MHz profiler operated in a dual mode with a nominal 60-m pulse length and a nominal 100-m pulse length. Table 1 provides more configuration details.
c. Deployment of the profilers in Texas and Florida
During TEFLUN A, the 2835-MHz antenna was covered with a fiberglass dome. It was noticed that the 2835-MHz system showed lower reflectivities than the 915-MHz profiler under heavy precipitation. The decreased reflectivity seen by the S-band system could be replicated by wetting the dome with a garden hose. During TEFLUN B and subsequent campaigns the dome was removed from the 2835-MHz antenna.
During TEFLUN A and B, the Aeronomy Laboratory profilers were collocated 25–40 km from at least one scanning radar. The location of the two profilers relative to the scanning radars is shown in Fig. 1. In TEFLUN A the profilers were located in south Houston. The site is 33 km west-northwest (WNW) of the WSR-88D in Dickinson, Texas. In TEFLUN B the profilers were located east of Holopaw, Florida, on the south side of U.S. Route 192 at the Triple N Ranch. This site is 35 km west of the Melbourne WSR-88D and 38 km northwest of the National Center for Atmospheric Research (NCAR) S-Pol radar. For TRMM Ground Validation field campaigns the two profilers have been collocated with disdrometers and rain gauges to provide calibration for scanning radars, which in turn are used to calibrate the TRMM PR measurements. A photo of the profilers and disdrometers at the Triple N Ranch site in Florida is reproduced in Fig. 2. For these field campaigns a Distromet RD-69 disdrometer, also known as a Joss–Waldvogel disdrometer (JWD) (Joss and Waldvogel 1967) was utilized to provide a calibration for the profiler reflectivity. For the TEFLUN campaign we integrated the datastream from the JWD into the AL profiler datastream in order to guarantee that the timing of the profiler and disdrometer measurements was coincident. In TEFLUN B, TRMM-LBA, and KWAJEX, a two-dimensional video disdrometer (2DVD) was also collocated with the profiler, providing additional opportunities for intercomparisons with the JWD.
d. Deployment of the profilers in Brazil and Kwajalein
The installations of the profilers were similar for TRMM-LBA and for KWAJEX. For TRMM-LBA the profilers were located at Ji Parana, Rondonia Province, Brazil, as shown in Fig. 3. They were situated at the Ji Parana municipal airport under the northeastern dual-Doppler lobe formed by the TOGA radar and the S-Pol radar. The Ji Parana municipal airport was located about 10 km east of Ji Parana. A JWD was mounted on a tripod as in TEFLUN B. NASA also operated a 2DVD at this location, but it was in operation only intermittently.
For KWAJEX, the AL profilers were located on Legan (Fig. 4a), about 35 km northwest of Kwajalein in the Republic of the Marshall Islands. The photo of the island of Legan in Fig. 4b shows the location of the profilers on this small island. The profilers were located a short distance downwind from a noisy diesel generator, which caused a problem for the JWD. This noisy environment compromised the ability of the JWD to detect drops less than about 1 mm in diameter. The effect on the profiler calibration by the disdrometer was judged to be small, however, because of the D6 dependence of reflectivity.
e. Sample measurements of reflectivity and Doppler velocity in stratiform rain
To gain confidence in the quantitative profiler measurements of reflectivity and Doppler velocity we have checked the consistency between measurements from the two profiler instruments. A typical comparison during stratiform rain in TRMM-LBA is shown in Figs. 5 and 6. Comparisons of 915- and 2835-MHz profiler reflectivities at 307 m above the surface on 25 February are shown in Fig. 5. Time series of profiler reflectivities are contained in Fig. 5a, and a scatterplot of these profiler reflectivities is presented in Fig. 5b. For the most part, the reflectivities seen by the two profilers agree to better than 1 dB. One exception occurs at reflectivities less than about 20 dBZ where the 915-MHz reflectivities may be influenced by the Bragg component. For example, in Fig. 5a the reflectivities observed by the two profilers track each other very well, but at low reflectivities the 915-MHz reflectivities sometimes exceed the 2835-MHz reflectivities by a few decibels. For the data in Fig. 5, the 915-MHz profiler has a bias of 0.5 dB relative to the 2835-MHz profiler, and the rms difference between the two sets of measurements is 0.8 dB. These results are typical of other stratiform rain events we have examined.
A comparison of 915- and 2835-MHz reflectivity-weighted Doppler velocities is presented in Fig. 6 for the same time period as in Fig. 5. As for the reflectivities, the Doppler velocity moments for the two profilers track each other very well, except that the velocities for the 915-MHz profiler are biased toward zero at small velocities. Since small Doppler velocities are associated with low reflectivities during precipitation, the problem with the Doppler velocities is related to the bias in reflectivities discussed above. Again, this effect appears to be due to the influence of the Bragg component in the 915-MHz observations and is even more obvious in the Doppler velocities than for the reflectivities. The scatterplot of Doppler velocities for this event is shown in Fig. 6b. The bias of the 915-MHz Doppler velocities toward zero is evident for small Doppler velocities.
3. Profiler observations of precipitating clouds during the TRMM field campaigns
In this section a sample of observations recorded by the profilers illustrates the vertical structure and temporal evolution of precipitating cloud systems during the TRMM Ground Validation field campaigns. The observations will be presented to illustrate the typical structure of convective systems experienced at these locations. It should be kept in mind, however, that each campaign was necessarily of fairly short duration, and that a 2-month campaign is insufficient to develop a complete climatology of convective cloud systems at any location. Nevertheless, the observations do serve to illustrate the evolution and structure of convective cloud systems often seen in the Tropics.
Figures 7–9 contain examples of time–height cross sections of profiler-observed reflectivities, Doppler velocities, and spectral width. The reflectivities are obtained as the zeroth moment of the Doppler spectra and are plotted in the top panels of the figures. The reflectivity-weighted Doppler velocities obtained from the first moment of the Doppler spectrum are plotted in the middle panels. The meteorological sign convention is used so that upward velocities are positive. For the most part, these Doppler velocities represent the actual fall velocities of hydrometeors. Since the fall velocities are always given relative to still air, the Doppler velocities contain fall velocities of hydrometeors convolved with the air motions. Since air motions can be quite large in convective cells, upward Doppler velocities are seen whenever the updraft velocities in the convective cells exceed the fall velocities of the hydrometeors in still air. Spectral width is shown in the bottom panels and is defined as twice the standard deviation about the mean of the Doppler velocity spectrum. These quantities are routinely produced by the Aeronomy Laboratory for each of the TRMM field campaigns. The complete set can be viewed at the Aeronomy Laboratory Web site (www.al.noaa.gov) under the link to recent field campaigns.
a. TEFLUN B: August–September 1998
Although central Florida began the summer of 1998 in a drought, there was ample precipitation in central Florida during TEFLUN B in August and September 1998. The profilers were installed in early July at the Triple N Ranch, which formed the nucleus of the dense rain gauge network (DNRG) for TEFLUN B. Besides the profilers, Triple N Ranch also was the location for radiosonde launches and surface meteorological instruments operated by a team based at the University of Central Florida in Orlando. For the purposes of this paper the most relevant ancillary measurements were provided by rain gauges and disdrometers. Both JWDs and 2DVDs were collocated at the Triple N Ranch site with the profilers.
An example of deep convection, followed by a transition to mature stratiform rain, was observed on 17 September 1998 and is shown in Fig. 7a. Convection begins in this example with a series of intermittent erect convective cells. Above 5 km there is evidence of updrafts and downdrafts extending up to about 10 km. Note, however, the large values of spectral width extending from about 2–7 km after 1900 UTC. The largest values of spectral width appear to be well correlated with the most intense rainshafts, judging from the reflectivities shown in the top panel.
Following the most active convection on 17 September, there is a transition to mature stratiform rainfall. The mature stratiform rainfall commences around 2145 UTC and can be recognized by the bright band in reflectivities at the melting level below 5.0 km. Above the melting level the period of stratiform precipitation is characterized by Doppler velocities of 1–2 m s−1 associated with falling ice and snow, and small spectral widths indicative of, at most, weak vertical motions and turbulence. Note the rainshaft of approximately 20-min duration that begins after 2200 UTC.
An example of mature stratiform rain observed on 19 September 1998 is shown in Fig. 7b. In this example the stratiform rain occurs in the evening after 0200 UTC and continues for about 4 h. Note the distinct bright band below 5.0 km and the fairly steady rain evidenced in the reflectivity and Doppler velocity in the first 2 h of the event. At the beginning of the event the tops of the precipitating clouds extend to about 9 km, and after that the level of deepest clouds descends gradually (but not monotonically). Near the end of the event diminished reflectivities are seen at all levels. In many cases we have observed, reflectivities around the melting level are the last to disappear.
b. TRMM-LBA: January–February 1999
TRMM-LBA provided an unusual opportunity to sample the continental convection over Amazonia in Brazil. The Amazon basin has many interesting meteorological features that made it a good choice for a field campaign in support of TRMM (Liebmann et al. 1999; Marengo et al. 2001; Petersen et al. 2002).
Examples of precipitating cloud systems observed by the profilers in TRMM-LBA are shown next. Figure 8a contains a convective cell that developed near the profiler on 17 February. The TOGA radar logs note that echoes formed very quickly over a large area following 1600 UTC on 17 February. The first profiler returns from the convection are recorded just before 1700 UTC and the entire event is over by 1800 UTC. The tops of the convective clouds are near 14 km in this event. Reflectivities in excess of 40 dBZ are seen below about 6 km from just after 1700 UTC until about 1730 UTC. Doppler velocities show evidence of updrafts and downdrafts, especially above 5 km. Also, above 5 km the spectral width is very large, providing further evidence of vertical motions and turbulence. There is no evidence of a bright band during this convective event.
Shown in Fig. 8b is a time–height cross section of a convective system that passed over the profiler on the early morning of 15 February. The sequence of events is described by the TOGA radar operators as the convective system approached Ji Parana from the east. At 0128 UTC the storm was about 150 km east of the TOGA radar, and by 0320 UTC the anvil was described as over the profiler. Profiler reflectivities show that the anvil first appeared over the profiler around 0230 UTC and that rain began soon after 0330 UTC. Echo tops are around 10 km and a bright band can be seen through much of the event. As seen from the TOGA radar, the system moved slowly westward and contained several electrically active cells, and a pronounced surface echo from the squall line was reported at 0358 UTC. An unusually low (3.5–4.0 km) bright band was reported at this time. Looking up at the storm from the profiler, the bright band before 0400 UTC does appear to be near 4.0 km. A surface echo is seen for 10–15 min before 0400 UTC. Just before 0400 UTC there appears to be a strong convective cell with a region of enhanced spectral width sloping upward from near the surface to 4–6 km just before 0400 UTC. After 0400 UTC, stratiform characteristics prevail for 30–45 min until the next rainshaft passes between 0440 and 0500 UTC. The second rainshaft is clearly visible in reflectivity falling out of a bright region connected and elevated somewhat from the bright band below. From 3–9 km there is a broad altitude region that shows enhanced spectral width in the 15–20 min ending just prior to 0500 UTC. Following the passage of this second embedded convective cell a third cell is evident 30–45 min later. The vertical structure of the Doppler velocity seems less perturbed than either the reflectivity or the spectral width. Nevertheless, there are some perturbations in the melting level that can be seen at the time of passage of each of the embedded convective cells.
An example of fairly steady stratiform rain is shown in Fig. 8c. The convective system first presented itself as convective cells organized in a north–south line (not shown) around 0500 UTC. The whole system was seen to be moving westward by the TOGA radar. A bright band just above 4.0 km is seen in the profiler reflectivities from 0600 until nearly 1030 UTC. The thickness of the bright band is seen to be directly related to the intensity of the reflectivity and is thickest at the time of heaviest rain before 0700 UTC. This is a common feature, which will be discussed in section 7. As rainfall gradually diminishes over the next few hours, cloud tops gradually descend and the bright band gets thinner and diminishes in intensity. Note the very small spectral width above the melting level. This is very characteristic of mature stratiform rain. Also note that some of the pixels, especially at the lower heights under light rain conditions, are corrupted by clear air returns.
c. KWAJEX: 23 July–15 September 1999
An important component of the TRMM field campaigns is the conducting of validation activities over the open ocean. While this is very difficult to achieve in practice, the TRMM ground validation site at Kwajalein Atoll, Republic of the Marshall Islands, has been instrumented to provide validation for TRMM. The intensive ground validation field campaign during KWAJEX was designed around the ongoing ground validation activities at the Kwajalein Atoll. Among the instruments being used at Kwajalein is NASA's S-band scanning radar located on Kwajalein Island and the AL profilers installed on Legan in July 1999. Legan is a remote, uninhabited, small island, visited several times per week by technicians who check on the status of the profilers.
The profilers operated on Legan through the entire KWAJEX field campaign. During this period they observed a variety of rain events, a sample of which are presented here. Common occurrences at Kwajalein are lines of convection that retain their identity for a few hours as they pass over the atoll. These squall lines form and dissipate in a matter of hours or less. From the profilers at Legan these squall lines appear to be isolated convective showers of varying duration and with no apparent organization. An example of these showers is shown for 17 September in Fig. 9a. The first significant event was associated with a SW–NE line of convection that moved northwest over Legan at about 0600 UTC. For the most part, these showers are confined to altitudes below about 6–7 km, although they are often deep enough to contain ice above the melting level and to show evidence of a “bright region” (see Fig. 9a).
A period of extended stratiform rain occurred on 12 August as shown in Fig. 9b. The convective system was first observed at Legan just after 2230 UTC 11 August as convective cells were passing over the island. These convective cells were followed by trailing, mature, stratiform conditions during the first few hours of 12 August. Beginning just after 0000 UTC on 12 August, a particularly heavy rain event is seen to be accompanied by an intense and broad rainband. At this time there appears to be a distinct but temporary lowering of the height of the bright band to a little below 4 km. Following 0100 UTC rainfall diminishes, and the bright band thins and becomes gradually less intense, until after 0400 UTC there is only a residual weak reflectivity layer close to the height of the preexisting bright band. We discuss the behavior of the bright band in section 7.
4. Calibration of the profilers by JWD
Absolute radar calibration is difficult to achieve. With scanning radars, it is possible to track a known target with the radar and perform a direct calibration of the radar. With a profiler, since the antenna beam is fixed, direct calibration using a known target is not a practical option. Indirect calibration done by careful measurement of all of the individual terms of the radar equation can be done, but the overall accuracy of this results in an uncertainty of 1–3 dB in the calibration. We have found that the 915-MHz profiler's calibration remains stable to within 0.4 dB over long periods of time. This allows the use of one calibration value to be used for an entire dataset. To refine the calibration for the final dataset, we rely on measurements made with a collocated disdrometer to calibrate profiler reflectivities in precipitation.
For the purposes of TRMM, we calculate reflectivity from the disdrometer drop sizes and use the calculated reflectivity as a reference for the profiler reflectivity. When the drop size distribution N(D) is known, radar reflectivity can be calculated as an integral over the drop size distribution weighted by the sixth power of drop size D. Other precipitation parameters can also be calculated from the drop size distribution, but these are not considered here. Disdrometers are therefore useful tools for calibration and validation of radar observations, although they only provide information for a very small volume just above the surface.
The JWD (Joss and Waldvogel 1967) is an impact disdrometer that produces a voltage when a drop strikes the surface of its 50-cm2 styrofoam cone. The voltage output is calibrated to provide a measurement of the momentum transfer of drops, which is related to their size. The JWD has a dead time immediately following the impact of a drop, and in heavy rain this can lead to undercounting of raindrops (Williams et al. 2000b). It is assumed that the momentum is entirely due to hydrometeor terminal fall velocities in still air, assuming drops are spherical. The momentum of individual drops is related to the size of the drop.
For calibration of the profiler we compare the profiler reflectivities at the lowest fully recovered height with the disdrometer calculated reflectivities. Using 1-min resolution data, the delay between drops falling through the lowest profiler range gates and impacting the disdrometer is a second-order effect and is ignored. Evaporation is likely to affect the smallest drops, which in the presence of larger drops do not affect the reflectivities very much.
In order to optimize the utility of the disdrometer as a calibration tool for the profiler, we have fully integrated the JWD into the profiler system so that the profiler and disdrometer are synchronized. The standard configuration of the JWD divides the distribution of drops into 20 bins. The JWD disdrometer is actually capable of binning drop sizes in 127 bins. The Aeronomy Laboratory has written software to provide a more complete drop size distribution that utilizes the full 127 bins in the JWD and calculates reflectivities over this distribution.
To calibrate the profiler using the JWD, we first compare the time series of reflectivities observed using the two platforms. The distributions of reflectivities from the two platforms are then compared. We only use reflectivities greater than 15 dBZ to create the distribution of reflectivity differences. The disdrometer is known to have problems with undersampling at low reflectivities (Smith et al. 1993), so only JWD reflectivities greater than 15 dBZ are used in the comparison. The mean reflectivity difference provides us with a number that can be used to adjust the profiler radar constant (PRC) to yield the desired calibration of the profiler.
a. Profiler calibration in TEFLUN B
The 915-MHz profiler is shown in Fig. 2 as deployed in TEFLUN B. The JWD is mounted on the tripod close to the modified shipping container that is used to house the electronics and computers. The aluminum shrouds for the two profiler antennas can be seen to the right of the container. Just to the right of the antenna shrouds is the portable generator used to power the instruments. In TEFLUN B the profilers were located east of Holopaw, Florida, on U.S. Route 192 at the Triple N Ranch. This site is 35 km west of the Melbourne WSR-88D and 38 km northwest of the NCAR S-Pol radar.
Figure 10 contains a time–height cross section of 915-MHz profiler reflectivities observed on 5 August 1998 at the Triple N Ranch and a time series of uncalibrated profiler reflectivities observed on 5 August 1998 at 307 m together with near-surface JWD reflectivities obtained near the profiler location (Fig. 2). By comparing the two sets of reflectivities over the entire TEFLUN B dataset, we choose the value of the PRC that gives the best overall fit in a statistical sense to the disdrometer reflectivities. This required a 0.16-dB decrease in the radar constant for TEFLUN B from the engineering value determined by indirect calibration.
Figure 11 compares calibrated 915-MHz profiler reflectivities with JWD reflectivities observed between 18 July and 29 September 1998, during TEFLUN B at the Triple N Ranch. Figure 11a shows the distribution of 915-MHz profiler reflectivities observed at 307 m above the surface. The profiler reflectivities are compared to JWD reflectivities in a scatterplot in Fig. 11b. Figure 11c contains the distribution of JWD reflectivities observed near the surface at the profiler site. Note that the disdrometer reflectivities have been truncated to exclude reflectivities less than 15 dBZ. All simultaneous observations between 18 July and 29 September 1998 are included in this figure. The scatter diagram in Fig. 11 shows that with PRC equal to 25.93, the red curve that connects the mean values of the individual points in 5-dB bins plotted in Fig. 11b crosses the diagonal line near 30 dBZ. Also plotted in Fig. 11 are the standard deviations of the points in the 5-dB bins. For reflectivities less than 20 dBZ, profiler reflectivities exceed JWD reflectivities by up to about 2 dBZ. For reflectivities in the range of 20–40 dBZ, profiler and JWD reflectivities agree within about 1 dBZ. Above 40 dBZ, the profiler reflectivities are less than the JWD reflectivities by up to about 2 dBZ.
The reflectivity-dependent bias between the observed profiler reflectivities and the calculated reflectivities from the JWD may be due to several factors. First of all, there is always a time–space mismatch between the profiler observations, which are made over a large volume several hundred meters above the disdrometer. The low bias (due to inadequate sampling) in disdrometer reflectivities discussed by Smith et al. (1993) may be responsible for the disagreement at low reflectivities. Another factor that may influence the bias at low reflectivities is Bragg scatter, which would tend to raise the 915-MHz reflectivities above what would be observed with the Rayleigh component alone (cf. Fig. 5). At high reflectivities other factors may be responsible for the disagreement. For example, the JWD reflectivity calculation is based on the assumption that the drops impacting the disdrometer are falling at terminal velocities in still air. However, in convective cells and gust fronts, in particular, there are likely to be downdrafts of sufficient magnitude to impart additional momentum to the drops as they impact the disdrometer. Accordingly, some of the large disdrometer reflectivities (relative to the profiler) may be due to the velocity-enhanced momentum of drops in downdrafts, which are interpreted as mass enhancements by the disdrometer. We are currently exploring these possibilities with the objective of decreasing the uncertainties in profiler calibration by disdrometers.
5. Calibration of scanning radars using profilers
As shown in Gage et al. (2000), one of the applications of the profilers to TRMM Ground Validation campaigns is to provide an independent means to calibrate scanning radars. As shown in section 4, the profiler can be calibrated within a decibel or so using the JWD. This calibration is good for the duration of a field campaign, provided there is no change in the instrumentation or failure in the electronics.
An example of how a profiler can be used for calibration of a scanning radar is shown in Figs. 12 and 13. Figure 12 shows a comparison of a time–height cross section of WSR-88D reflectivities on 18 April at Dickinson, Texas, during TEFLUN A over the location of the profiler with the 915-MHz profiler reflectivities. The top panel of Fig. 12 shows the time–height cross section of 915-MHz profiler reflectivities recorded on 18 April in Houston with 105-m resolution. The middle panel of Fig. 12 shows the time–height cross section of 915-MHz reflectivities smoothed to match the vertical and time resolution of the WSR-88D scanning radar over the profiler site. The bottom panel of Fig. 12 shows the WSR-88D reflectivities recorded over the profiler site. The WSR-88D reflectivities were provided by Texas A&M University and were calibrated using the standard National Weather Service (NWS) calibrations.
The three sets of reflectivities contained in Fig. 12 show the same overall vertical structure and evolution of the precipitating clouds over the profiler. The vertical resolution of the scanning radar is dependent upon range. At a range of 20–40 km the beam spreading effect from the scanning radar is minimal, so that the vertical resolution over the profiler is relatively good. Moreover, the separation distance is large enough to allow the scanning radar to sample over the profiler through a substantial fraction of the troposphere.
For calibration of the WSR-88D, it is of interest to examine the reflectivity difference between the two platforms. Figure 13 shows the reflectivity difference of the WSR-88D compared to the profiler. In Fig. 13a the distribution of reflectivity differences is shown. In Fig. 13b reflectivity differences are plotted as a function of WSR-88D reflectivity, and in Fig. 13c the distribution of WSR-88D reflectivities is shown. In most cases the profiler reflectivity exceeds the WSR-88D reflectivity by about 2–3 dB, suggesting that the WSR-88D values are low by about 2.5 dB. Although there are relatively few points for reflectivities below 10 dBZ, the profiler reflectivities are relatively greater. This is likely due to the Bragg component seen by the 915-MHz profiler. For a discussion of the relative sensitivity of 915-MHz and S-band profilers to Bragg scatter, see Gage et al. (1999b). For a more detailed discussion of the use of profilers for calibration of scanning radars, see Gage et al. (2000).
There are a number of outstanding issues in WSR-88D calibration, and the profiler technique outlined above has the potential of providing improved calibration by comparing reflectivities directly. Calibration issues for the WSR-88D are detailed in the Federal Meteorological Handbook No. 11B (Office of Federal Coordinator and Supporting Research 1990, section 5.3) and include “hardware calibration, ground clutter, anomalous propagation, partial beam filling, and wet radome attenuation.” Anagnostou et al. (2001) use the TRMM precipitation radar to show that these calibration errors can be several decibels. Other researchers (e.g., Vieux and Bedient 1998) use rain gauges to calibrate the WSR-88D, concentrating mainly on the Z–R relationship used to relate reflectivity to rain rate. The profiler provides a direct comparison of reflectivity in the same volume and at the same time as the WSR-88D. This allows direct calibration without having to resort to the uncertainties associated with Z–R relationships.
6. Retrieval of drop size distributions
As is widely recognized, drop size distributions are fundamental to precipitation. The size and number of raindrops determines all of the integrated quantities of the precipitation, including reflectivity, rain rate, and water content. For TRMM, drop size distributions are important factors in key algorithms used for rain retrieval from the PR and the TMI. For these reasons, accurately retrieving the drop size distributions from profiler measurements has become a major goal of profiler precipitation research.
The vertical air motions and turbulence in the profiler-resolved pulse volume have a profound influence on the drop size distribution retrieval. It has been shown by several investigators (Currier et al. 1992; Rajopadhyaya et al. 1998, 1999; Cifelli et al. 2000) that drop size distributions can be retrieved when two collocated profilers are used. One profiler must be sensitive to the Bragg component of the Doppler spectra due to turbulence and provide estimates of the mean vertical air motion and spectral broadening. The other profiler must be sensitive to the Rayleigh component of the Doppler spectra due to hydrometeors and estimate the drop size distribution given the air motion estimates from the other profiler. Some of the early work was done at a single frequency when it was possible to distinguish Bragg and Rayleigh components in the same Doppler spectra (Wakasugi et al. 1986; Gossard 1988).
Building on prior work (Hauser and Amayenc 1981, 1983; Sangren et al. 1984; Sato et al. 1990), Williams (2002, hereafter WIL) has recently explored several approaches for retrieving the drop size distribution, using only the Rayleigh component of the Doppler spectra from profiler observations taken during the TRMM field campaigns. Figure 14 shows the profiler-retrieved drop size distribution compared with the JWD and 2DVD observed on 17 September 1998 at the Triple N Ranch during TEFLUN B. All three instruments observe similar features for the medium to large drop sizes (greater than 1.5 mm), yet there are differences at the smaller drop sizes. The uncertainties at the smaller drop sizes are due to the different technologies used by the instruments and affect the calculated integrated parameters of mean drop diameter and rain rate (Williams et al. 2000b).
The drop size distribution modeling described in WIL accounts for the presence of intense turbulence and strong vertical motions. Therefore, the profiler-retrieved drop size distributions can be performed at altitudes below the melting layer during stratiform and convective rain events. More work is needed in this area to quantify the error bounds of the retrieved air motions and modeled drop size distributions.
7. Synthesis of observations
The observations shown in section 3 are samples of the different types of precipitating cloud systems seen in the TRMM field campaigns. The two most common types of precipitating cloud structures observed are the convective cells with no bright band present and the stratiform rain with bright band present. An example of a convective cell is shown in Fig. 8a, and examples of mature stratiform precipitating clouds are shown in Figs. 7b, 8c, and 9b. The mature stratiform precipitating clouds often persist for many hours and possess a vertical structure that sets them apart from the convective cells. As is shown in Fig. 7a, the entire life cycle of a mesoscale convective system is sometimes seen above the profiler in which convective cells are initially observed transitioning into mature stratiform precipitating cloud structures. Convective cells and stratiform cloud structures are very common and were observed in each of the field campaigns. A less commonly observed structure is the stratiform precipitating cloud structure with embedded convection, as shown in Fig. 8b.
a. Melting layer structure
Several examples of mature stratiform precipitating clouds are included in section 3 to illustrate some common features in their vertical structure. In every example a region of falling ice/snow overlays a melting region in the vicinity of 4–5 km, with rainfall below the melting region. Characteristics that delineate the melting region can be seen in reflectivity, Doppler velocity, and spectral width.
The melting layer has received much attention in the literature (Drummond et al. 1996). Microphysical studies utilizing airborne in situ probes have been presented by Stewart et al. (1984) and by Willis and Heymsfield (1989). Early work by Findeisen (1940) recognized the importance of an “isothermal layer” formed at the top of the melting region in stratiform precipitation. Atlas et al. (1969) developed a simple model to relate the thickness of the “isothermal layer” to the amount of snow being melted in the layer. According to these authors, an isothermal layer may be as large as 1.9 km.
Based on observations and theoretical models, Willis and Heymsfield (1989) provide a useful synthesis of the melting region. These authors divide the melting region into three layers: 1) the region just above the 0°C isotherm, 2) the isothermal layer, and 3) the layer just below the isothermal layer. In the top layer, just above the isothermal layer, aggregation is important. Within the isothermal layer aggregation continues to be important. Melting of the smallest particles occurs in this region. The isothermal layer is created by the cooling produced by the melting of the smallest particles. The largest particles continue to grow by aggregation and by accretion of small liquid drops. Evidently, particle breakup is important since there is still a substantial number of small particles present throughout the isothermal layer. Below the isothermal layer the large particles melt, and it is in this region that the bright band in reflectivity is thought to reside.
Clearly, the isothermal layer plays an important role in the nature and location of the bright band observed by radar. In profiler observations we typically see the results of aggregation in the layer above the isothermal layer. The result of aggregation can be seen in profiler observations as enhanced reflectivity and increased Doppler fall velocities. Since the largest particles dominate the profiler reflectivity and Doppler velocity, it is unlikely that the melting within the isothermal layer of the smallest particles directly affects the Doppler spectral moments, although it may affect the reflectivity if the large aggregates are sufficiently coated with liquid. Otherwise, the rapid change in Doppler velocity and peak reflectivity associated with the bright band should be restricted to the region below the isothermal layer.
In the observations presented in section 3 it was pointed out that often during a rainburst a broadening and intensification of the bright band can be observed. Under these circumstances the isothermal layer ought to increase in depth, but this does not seem to be the case. If, for whatever reason, larger particles fall into a preexisting isothermal layer, they may form larger aggregates and the bright band may extend into the isothermal layer. The larger aggregates will take longer to melt, and the bright band may extend to lower heights as well. When the larger particles cease to enter the isothermal layer from above, the bright band will become thinner and increase in altitude.
In at least one case (Fig. 9b), a bright band has been observed to drop appreciably in altitude during a rainburst. In this case we suspect that the isothermal layer has deepened, temporarily displacing the bright band downward. It should not be too surprising to have a deepened isothermal layer, but it is not clear why the examples cited earlier did not also show evidence of deeper isothermal layers. Coordinated profiler and in situ observations are needed to sort this out.
8. Concluding remarks
Profiler observations of hydrometeors in precipitating cloud systems have been taken during several TRMM Ground Validation field campaigns and are illustrated here with observations from TEFLUN, TRMM-LBA, and KWAJEX. A precipitation profiler system, using a 915- and 2835-MHz profiler pair, was developed and utilized for this research. The two profilers provide simultaneous independent measurements of reflectivities, Doppler velocities, and spectral width from a large common volume. Measurements with a collocated JWD show that reflectivities observed at the lowest reliable heights of the profilers track the calculated reflectivities deduced from the JWD.
Profiler and disdrometer reflectivities are expected to show differences because the disdrometer samples a much smaller volume close to the surface, while the profiler observes a much larger volume above the surface. Nevertheless, at least during stratiform rain, the agreement between the two sets of measurements appears to be good enough to use the disdrometer to calibrate the profiler observations. Intercomparisons between profiler reflectivities and scanning radar reflectivities over the profiler also track each other quite well. A well-calibrated profiler can then be used to calibrate or validate a scanning radar. To perform the calibration under optimal conditions there should be continuous, preferably stratiform, rain and the scanning radar should be directed over the profiler to maximize sampling of the same volume observed by the profiler.
Profiler observations from the TRMM field campaigns provide substantial information about the vertical structure and evolution of precipitating cloud systems in the Tropics. These observations readily lend themselves to the classification of precipitation. The nearly continuous measurements over long periods can be used for studies of the diurnal variability of convection.
Profilers have proved to be useful tools for the retrieval of drop size distributions in a variety of precipitating cloud systems. The retrievals appear to be routinely possible using a single profiler under a broad variety of conditions, including all but the most active periods of convection when vertical motions are large and turbulence is intense.
In future satellite missions, it will be necessary to reduce the uncertainty of rainfall estimation. Profilers are vertical-pointing radars that can be built at any frequency. The profilers have the potential of providing precise measurements of vertically resolved precipitation. Recent advances in the retrieval of drop size distributions from profiler measurements suggest that it may be possible in the future to provide accurate, continuous, high-spatial-resolution measurements of precipitation parameters from profiler observations. Finally, they can be utilized in future missions as a test bed for algorithms for spaceborne radars.
Acknowledgments
Aeronomy Laboratory research for the TRMM field campaigns has been supported in part by funding from NASA Headquarters through the NASA TRMM Project Office. We thank Prof. Ed Zipser for supplying the Joss–Waldvogel disdrometer and Dr. Anton Kruger for analyzing the raw two-dimensional video disdrometer data at the profiler site. We also thank the City of Houston Department of Public Works and Engineering for providing the site for the profilers at the Simms South Water Treatment Plant, and Mr. Nick Gahr for his help and cooperation in maintaining the profilers at the Water Treatment Plant. Houston NEXRAD data were supplied to us by Prof. Mike Biggerstaff. We thank the Florida Fresh Water Fish and Game Department for making the Triple N Ranch sites available for our use in TEFLUN B. We thank Mr. Mark Haeg for his assistance with logistical arrangements and for helping with the installation of the profilers in Florida and Brazil. We gratefully acknowledge the many contributions of Warner Ecklund to the development of the profilers used in this research.
REFERENCES
Adler, R. F., Huffman G. J. , Bolvin D. T. , Curtis S. , and Nelkin E. J. , 2000: Tropical rainfall distributions determined using TRMM combined with other satellite and rain gauge information. J. Appl. Meteor., 39 , 2007–2023.
Anagnostou, E. N., Morales C. A. , and Dinku T. , 2001: The use of TRMM precipitation radar observations in determining ground radar calibration biases. J. Atmos. Oceanic Technol., 18 , 616–628.
Atlas, D., Tatehira R. , Srivastava R. C. , Marker W. , and Carbone R. E. , 1969: Precipitation induced mesoscale wind perturbations in the melting layer. Quart. J. Roy. Meteor. Soc., 95 , 544–560.
Atlas, D., Srivastava R. S. , and Sekhon R. S. , 1973: Doppler radar characteristics of precipitation at vertical incidence. Rev. Geophys. Space Sci., 11 , 1–35.
Carter, D. A., Gage K. S. , Ecklund W. L. , Angevine W. M. , Johnston P. E. , Riddle A. C. , Wilson J. , and Williams C. R. , 1995: Developments in lower tropospheric wind profiling at the NOAA Aeronomy Laboratory. Radio Sci., 30 , 977–1001.
Cifelli, R., and Rutledge S. A. , 1994: Vertical motion structure in Maritime Continent mesoscale convective systems: Results from a 50 MHz profiler. J. Atmos. Sci., 51 , 2631–2652.
Cifelli, R., . 1998: Vertical motion, diabatic heating and rainfall characteristics in N. Australia convective systems. Quart. J. Roy. Meteor. Soc., 124 , 1133–1162.
Cifelli, R., Williams C. R. , Ecklund W. L. , Rajopadhyaya D. K. , Avery S. K. , Gage K. S. , and May P. T. , 2000: Drop-size distribution characteristics in tropical mesoscale convective systems. J. Appl. Meteor., 39 , 760–777.
Currier, P. E., Avery S. K. , Balsley B. B. , and Gage K. S. , 1992: Use of two wind profilers for precipitation studies. Geophys. Res. Lett., 19 , 1017–1020.
Drummond, F. J., Rogers R. R. , Cohn S. A. , Ecklund W. L. , Carter D. A. , and Wilson J. S. , 1996: A new look at the melting layer. J. Atmos. Sci., 53 , 759–769.
Ecklund, W. L., Gage K. S. , and Williams C. R. , 1995: Tropical precipitation studies using a 915-MHz wind profiler. Radio Sci., 30 , 1055–1064.
Ecklund, W. L., Williams C. R. , Johnston P. E. , and Gage K. S. , 1999: A 3-GHz profiler for precipitating cloud studies. J. Atmos. Oceanic Technol., 16 , 309–322.
Findeisen, W., 1940: The formation of the 0°C-isothermal layer and fractocumulus under nimbostratus. Meteor. Z., 57 , 49–54.
Gage, K. S., Williams C. R. , and Ecklund W. L. , 1994: UHF wind profilers: A new tool for diagnosing tropical convective cloud systems. Bull. Amer. Meteor. Soc., 75 , 2289–2294.
Gage, K. S., . 1996: Application of the 915 MHz profiler for diagnosing and classifying tropical precipitating cloud systems. Meteor. Atmos. Phys., 59 , 141–151.
Gage, K. S., and Johnston P. E. , 1999a: Development and application of Doppler radar profilers to ground validation of satellite precipitation measurements. Adv. Space Res., 24 , 931–934.
Gage, K. S., . 1999b: Use of two profilers during MCTEX for unambiguous identification of Bragg scattering and Rayleigh scattering. J. Atmos. Sci., 56 , 3679–3691.
Gage, K. S., Johnston P. E. , Ecklund W. L. , Cifelli R. , Tokay A. , and Carter D. A. , 2000: Doppler radar profilers as calibration tools for scanning radars. J. Appl. Meteor., 39 , 2209–2222.
Gossard, E. E., 1988: Measuring drop size distributions in cloud with clear-air sensing Doppler radar. J. Atmos. Oceanic Technol., 5 , 640–649.
Hartmann, D. L., Hendon H. H. , and Houze Jr. R. A. , 1984: Some implications of the mesoscale circulations in tropical cloud clusters for large-scale dynamics and climate. J. Atmos. Sci., 41 , 113–121.
Hauser, D., and Amayenc P. , 1981: A new method for deducing hydrometeor-size distributions and vertical air motions from Doppler radar measurements at vertical incidence. J. Appl. Meteor., 20 , 547–555.
Hauser, D., . 1983: Exponential size distributions of raindrops and vertical air motions deduced from vertically pointing Doppler radar using a new method. J. Climate Appl. Meteor., 22 , 407–418.
Heymsfield, G. M., and Coauthors. 1996: The EDOP radar system on the high-altitude NASA ER-2 aircraft. J. Atmos. Oceanic Technol., 13 , 795–809.
Heymsfield, G. M., Geerts B. , and Tian L. , 2000: TRMM precipitation radar reflectivity profiles as compared with high-resolution airborne and ground-based radar measurements. J. Appl. Meteor., 39 , 2080–2102.
Hou, A. Y., Zhang S. Q. , Da Silva A. M. , Olson W. S. , Kummerow C. D. , and Simpson J. , 2001: Improving global analysis and short-range forecast using rainfall and moisture observations derived from TRMM and SSM/I passive microwave sensors. Bull Amer. Meteor. Soc., 82 , 659–679.
Houze, R. A. Jr,, 1989: Observed structure of mesoscale convective systems and implications for large-scale heating. Quart. J. Roy. Meteor. Soc., 115 , 425–461.
Iguchi, T., Kozu T. , Meneghini R. , Awaka J. , and Okamoto K. , 2000: Rain-profiling algorithm for the TRMM precipitation radar. J. Appl. Meteor., 39 , 2038–2052.
Joss, J., and Waldvogel A. , 1967: A raindrop spectrograph with automatic analysis. Pure Appl. Geophys., 68 , 240–246.
Krishnamurti, T. N., Kishtawal C. M. , Shin D. W. , and Williford C. E. , 2000: Improving tropical precipitation forecasts from a multianalysis superensemble. J. Climate, 13 , 4217–4227.
Kummerow, C., Barnes W. , Kozu T. , Shiue J. , and Simpson J. , 1998: The Tropical Rainfall Measuring Mission (TRMM) sensor package. J. Atmos. Oceanic Technol., 15 , 809–817.
Kummerow, C., and Coauthors. 2000: The status of the Tropical Rainfall Measuring Mission (TRMM) after two years in orbit. J. Appl. Meteor., 39 , 1965–1982.
Liebmann, B., Kiladis G. N. , Marengo J. A. , Ambrizzi T. , and Glick J. D. , 1999: Submonthly convective variability over South America and the South Atlantic convergence zone. J. Climate, 12 , 1877–1891.
Marengo, J. A., Liebmann B. L. , Kousky V. E. , Filizola N. P. , and Wainer I. C. , 2001: Onset and end of the rainy season in the Brazilian Amazon basin. J. Climate, 14 , 833–852.
May, P. T., and Rajopadhyaya D. K. , 1996: Wind profiler observations of vertical motion and precipitation microphysics of a tropical squall line. Mon. Wea. Rev., 124 , 621–633.
McCollum, J. R., and Krajewski W. F. , 1997: Oceanic rainfall estimation: Sampling studies of the fractional–time-in-rain method. J. Atmos. Oceanic Technol., 14 , 133–142.
Morrissey, M. L., Krajewski W. F. , and McPhaden M. J. , 1994: Estimating rainfall in the Tropics using the fractional time raining. J. Appl. Meteor., 33 , 387–393.
Office of Federal Coordinator and Supporting Research, 1990: Doppler radar meteorological observations. Part B, Doppler radar theory and meteorology. Federal Meteorological Handbook No. 11. Publication FCM-H11B-1990, Office of Federal Coordinator and Supporting Research, Rockville, MD, 228 pp.
Petersen, W. A., and Rutledge S. A. , 2001: Regional variability in tropical convection: Observations from TRMM. J. Climate, 14 , 3566–3586.
Petersen, W. A., Nesbitt S. W. , Blakeslee R. J. , Cifelli R. , Hein P. , and Rutledge S. A. , 2002: TRMM observations of intraseasonal variability in convective regimes over the Amazon. J. Climate, 15 , 1278–1294.
Rajopadhyaya, D. K., May P. T. , Cifelli R. C. , Avery S. K. , Williams C. R. , Ecklund W. L. , and Gage K. S. , 1998: The effect of vertical air motions on rain rates and median volume diameter determined from combined UHF and VHF wind profiler measurements. J. Atmos. Oceanic Technol., 15 , 1306–1319.
Rajopadhyaya, D. K., Avery S. K. , May P. T. , and Cifelli R. C. , 1999: Comparison of precipitation estimation using single- and dual-frequency wind profilers: Simulations and experimental results. J. Atmos. Oceanic Technol., 16 , 165–173.
Rogers, R. R., Ecklund W. L. , Carter D. A. , Gage K. S. , and Ethier S. A. , 1993: Research applications of a boundary-layer wind profiler. Bull. Amer. Meteor. Soc., 74 , 567–580.
Sangren, K. L., Ray P. S. , and Walker G. B. , 1984: A comparison of techniques to estimate vertical air motions and raindrop size distributions. J. Atmos. Oceanic Technol., 1 , 152–165.
Sato, T., Hiroshi D. , Iwai H. , Kimura I. , Fukao S. , Yamamoto M. , Tsuda T. , and Kato S. , 1990: Computer processing for deriving drop-size distributions and vertical air velocities from VHF Doppler radar spectra. Radio Sci., 25 , 961–973.
Short, D. A., and Nakamura K. , 2000: TRMM radar observations of shallow precipitation over the tropical oceans. J. Climate, 13 , 4107–4124.
Simpson, J., Adler R. F. , and North G. R. , 1988: A proposed Tropical Rainfall Monitoring Mission (TRMM) satellite. Bull. Amer. Meteor. Soc., 69 , 278–295.
Smith, P. L., Liu Z. , and Joss J. , 1993: A study of sampling–variability effects in raindrop size observations. J. Appl. Meteor., 32 , 1259–1269.
Stewart, R. E., Marwitz J. D. , Pace J. C. , and Carbone R. E. , 1984: Characteristics through the melting layer of stratiform clouds. J. Atmos. Sci., 41 , 3227–3237.
Tao, W. K., Simpson J. , Lang S. , McCumber M. , Adler R. , and Penc R. , 1990: An algorithm to estimate the heating budget from vertical hydrometeor profiles. J. Appl. Meteor., 29 , 1232–1244.
Thiele, O. W., 1992: Ground truth for rain measurement from space. The Global Role of Tropical Rainfall, J. S. Theon et al., Eds., A. Deepak, 245–260.
Vieux, B. E., and Bedient P. B. , 1998: Estimation of rainfall for flood prediction from WSR-88D reflectivity: A case study, 17–18 October 1994. Wea. Forecasting, 13 , 407–415.
Wakasugi, K., Mizutani A. , Matsuo M. , Fukao S. , and Kato S. , 1986: A direct method for deriving drop-size distributions and vertical air velocities from VHF Doppler radar spectra. J. Atmos. Oceanic Technol., 3 , 623–629.
Webster, P. J., 1994: The role of hydrological processes in ocean–atmosphere interactions. Rev. Geophys., 32 , 427–476.
Williams, C. R., 2002: Simultaneous ambient air motion and raindrop size distributions retrieved from UHF vertical incident profiler observations. Radio Sci., in press.
Williams, C. R., Ecklund W. L. , and Gage K. S. , 1995: Classification of precipitating clouds in the tropics using 915 MHz wind profilers. J. Atmos. Oceanic Technol., 12 , 996–1012.
Williams, C. R., Johnston P. E. , and Gage K. S. , 2000a: Cluster analysis techniques to separate air motion and hydrometeors in vertical incident profiler observations. J. Atmos. Oceanic Technol., 17 , 949–962.
Williams, C. R., Kruger A. , Gage K. S. , Tokay A. , Cifelli R. , Krajewski W. F. , and Kummerow C. , 2000b: Comparison of simultaneous rain drop size distributions estimated from two surface disdrometers and a UHF profiler. Geophys. Res. Lett., 27 , 1763–1766.
Willis, P. T., and Heymsfield A. J. , 1989: Structure of the melting layer in mesoscale convective system stratiform precipitation. J. Atmos. Sci., 46 , 2008–2025.
Maps of instrument locations in (a) Houston and (b) central Florida.
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Picture of the Aeronomy Laboratory profilers in central Florida during TEFLUN B
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Map showing locations of instruments in TRMM-LBA. Map courtesy of the Radar Meteorology Group, Colorado State University
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
(a) Map of Kwajalein and neighboring atolls showing the location of Legan and the S-band scanning radar at Kwajalein. (b) Aerial photo of Legan showing the location of profilers (photo credit: U.S. Army)
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Sample comparison of 915- and 2835-MHz profiler reflectivities observed during stratiform rain in Brazil. (a) Time series. (b) Scatterplot
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Sample comparison of 915- and 2835-MHz profiler observations of Doppler velocity during stratiform rain in Brazil (a) Time series. (b) Scatterplot
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Profiler observations of precipitating cloud systems from the Triple N Ranch during TEFLUN B. (top) The time–height cross section of the equivalent reflectivities recorded by the 915-MHz profiler. (middle) The time–height cross section of Doppler velocity. (bottom) The time–height cross section of spectral width. (a) Convection transitioning to stratiform rain on 17 Sep 1998. (b) Mature stratiform rain on 19 Sep 1998
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Profiler observations of precipitating cloud systems from Ji Parana during TRMM-LBA. (top) The time–height cross section of the equivalent reflectivities recorded by the 915-MHz profiler. (middle) The time–height cross section of Doppler velocity. (bottom) The time–height cross section of spectral width. (a) Deep convection and heavy rain observed on 17 Feb 1999. (b) Anvil with stratiform rain and embedded convection on 15 Feb 1999. (c) Mature stratiform rain on 18 Feb 1999
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
(Continued)
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
(Continued)
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Profiler observations of precipitating cloud systems from Legan during KWAJEX. (top) The time–height cross section of the equivalent reflectivities recorded by the 915- or 2835-MHz profilers. (middle) The time–height cross section of Doppler velocity. (bottom) The time–height cross section of spectral width. (a) Squall lines on 17 Sep 1999. (b) Mature stratiform rain on 12 Aug 1999
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
(a) Time–height cross section of 915-MHz profiler reflectivities observed at the Triple N Ranch on 5 Aug 1998. (b) Time series of uncalibrated profiler reflectivities measured on 5 Aug 1998 with nominal 100-m range gate centered at 307 m AGL compared to reflectivities calculated from the JWD disdrometer
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Scatterplot of calibrated profiler reflectivities measured with nominal 100-m range gate centered at 307 m AGL compared to reflectivities calculated from the JWD disdrometer
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Comparison of profiler reflectivities with WSR-88D reflectivities from Houston, TX, on 18 Apr 1998 during TEFLUN A
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Reflectivity differences between profiler and WSR-88D on 18 Apr 1998 during TEFLUN A.
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Comparison of drop size distributions recorded on 17 Sep 1998 during TEFLUN B at the Triple N Ranch with drop size distributions recorded using the JWD and the 2DVD (after Williams et al. 2000b)
Citation: Journal of Atmospheric and Oceanic Technology 19, 6; 10.1175/1520-0426(2002)019<0843:PCTTRM>2.0.CO;2
Typical profiler operating parameters used in TRMM field campaigns
