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Keywords:

  • precipitation;
  • wind profiler;
  • fall velocity;
  • turbulence;
  • planetary boundary layer

Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information

[1] For the first time in India, an L-band (1357.5 MHz) lower atmospheric wind profiler (LAWP) has been installed and successfully operated at Gadanki, India, since September 1997. The first results of the accuracy can be given on the basis of about 24-day intercomparisons between LAWP and mesosphere-stratosphere-troposphere radar data. The root-mean-square differences (RMS deviation) have been found to range between 1.18 m/s and 1.6 m/s for the wind speed. The two wind profilers compliment each other quite well, considering both the availability and the reliability of the wind measurements. Statistics of the data availability can be shown based on 775 days of data in low mode and about 532 days of data in high mode. The 80% availability of the LAWP was determined with 3.6-km wind measurements in low mode and 5-km wind measurements in high mode. LAWP observations show well-marked planetary boundary layer diurnal variation on clear sunny days. We found that with a few exceptions the drier period has a higher boundary layer compared with the wet period, indicating that in the wet season, most of the net solar radiation evaporated moisture rather than heating the surface and therefore contributed little to buoyant forcing. We classified precipitating clouds into three types: convective, transition, and stratiform. Diurnal and seasonal variation of the occurrence of precipitating cloud systems shows that the precipitation primarily occurs in the afternoon and the convective and transition clouds are most frequent in the summer monsoon, while the occurrence of stratiform clouds is predominant in the winter monsoon.

1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information

[2] The wind and wind variability in the planetary boundary layer (PBL) are important for various application fields, like meteorology, atmospheric physics, environmental protection, wind energy utilization, and air-traffic control. To understand these phenomena, detailed observations are necessary in both time and space. Several types of radar for lower atmospheric observation are designed for certain targets, height range, and operating frequency. The wind profilers operating between 915 MHz and 1.3 MHz range are widely used for understanding the PBL dynamics, weather forecasting, and precipitating cloud systems [Martner et al., 1993; Hashiguchi et al., 1995; Engelbart et al., 1996; Yeung, 1998; Hadi et al., 2000; Krishna Reddy et al., 2001a]. During the past several years the lower atmospheric wind profilers (LAWPs) [Ecklund et al., 1988; Strauch et al., 1989; Gage et al., 1990; Rogers et al., 1993; Clifford et al., 1994; Carter et al., 1995; Hashiguchi et al., 1996; Griesser and Richner, 1998] have left the stage of pure research and technical development and become operational in different countries. Because of their capabilities the development of wind profilers is increasing, and many networks are under study or construction or in operation for research purposes and meteorological prediction, in the Pacific Ocean [Gage et al., 1990], in the United States [Strauch et al., 1984; Carter et al., 1995], in Europe [James et al., 1991], and in Asia [Ohno et al., 1994; Hashiguchi et al., 1995].

[3] Wind profilers are primarily used to measure wind; it has become evident from the research studies of Gossard et al. [1992], Ralph [1995], Alonso et al. [1998], and Rajopahdyaya et al. [1999] that they are well suited for precipitation measurement as well. While VHF wind profilers have been shown to be useful for research on precipitation [Fukao et al., 1985; Wakasugi et al., 1987; Sato et al., 1990; Roettger and Larsen, 1990; Chu et al., 1991; May and Rajopadhyaya, 1999; Rao et al., 1999; Cifelli et al., 2000], UHF wind profilers [Currier et al., 1992; Rogers et al., 1993; Gage et al., 1994; Williams et al., 1995, 2000; Ecklund et al., 1995; Cifelli and Rutledge, 1998; Atlas et al., 1999; Tokay et al., 1999] are especially useful because of their sensitivity to hydrometeors.

[4] The depth or height of the convective boundary layer (CBL) is a critical parameter for dispersion modeling, but it is difficult to parameterize accurately. White and Fairall [1991] have used the wind profiler reflectivity to detect the growth of the CBL in noncloudy conditions. Angevine et al. [1994] demonstrated the capability of the UHF wind profilers for estimation of the CBL. Neff [1994] examined the potential of sodars and wind profilers to get air quality and mesoscale meteorological phenomena data along the eastern slope of the Rocky Mountains in Colorado and the Central Valley of California. Hashiguchi et al. [1995] and Hadi et al. [2000] studied the tropical sea breeze circulation and related lower atmospheric phenomena using the 1.3-GHz wind profiler in Indonesia. In India, Gadanki LAWP is the first boundary layer radar dedicated for PBL characterization. Compared to conventional methods of balloon sounding [Stull, 1988; Garratt, 1992; Kaimal and Finnigan, 1994], the ground-based remote sensing technique has the advantage of being capable to observe vertical profiles of atmospheric parameters at a relatively short time interval, continuously. The high-resolution (both in time and height) observations with the lower atmospheric wind profilers are expected to improve our knowledge and interpretation of the PBL [Clifford et al., 1994].

[5] The occurrence of deep convection in the tropics plays an important role in the global circulation, since it transports heat, water vapor, and so on, from the PBL to the upper troposphere. The vertical distribution of diabatic heating depends on the vertical structure of the convective system; hence it is important to study the vertical structure of the precipitating clouds occurring in the tropics. Most of the wind profiler studies on precipitating clouds have been conducted in the Pacific Ocean. For example, a study of precipitating cloud systems in the tropics using a 915-MHz wind profiler has been carried out by Williams et al. [1995] on Manus Island. Ohno et al. [2000] used similar radar systems on Biak and Christmas Island to study the occurrence of precipitating clouds along the Pacific Ocean. In the Indian region, radar remote sensing of the tropical monsoon cloud systems is sparse. The Deccan Plateau is one of the key regions for the Asia monsoon. Gadanki is an ideal site for understanding tropical precipitating cloud systems and ground validation of the Tropical Rainfall Measuring Mission (TRMM) satellite because of its location and good facility of multiple sensors [Krishna Reddy et al., 2001a].

2. Data Sources and Analysis Techniques

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information

[6] For the first time in India, a LAWP system was installed at Gadanki (13.5°N, 79.2°E), near Tirupati, India (Figure 1a), with major collaboration between Ministry of Post and Telecommunications Communications Research Laboratory (CRL), Japan, and Indian Space Research Organisation National MST Radar Facility (NMRF), India, for detailed investigation of winds, turbulence, and precipitating weather systems in the tropical latitudes. The LAWP was fabricated at Meisei Electric Co., Ltd., Tokyo, Japan, with the specifications given by CRL, Tokyo, Japan. The Gadanki LAWP is a coherent pulse radar with an effective peak power aperture product of about 1.2 × 104 Wm2. Figure 1b shows the antenna assembly of the wind profiler, while the basic system specifications are presented in Table 1. It uses a phased array of 3.8 m × 3.8 m organized in four quadrants, each having 24 × 24 circular conducting patch antenna elements. The antenna beam can be positioned through electrical phase switching at any of the three fixed orientations: zenith, and 15°E, and 15°N. The transmitter is of solid-state design with the final stage having a parallel array of power amplifiers, delivering a peak power of about 1 kW. The receiver is phase coherent, employing quadrate detection and having a maximum gain of about 120 dB. The signal processor performs coherent integration and a fast Fourier transform (FFT), while the online computer performs the computation of the three low-order spectral moments and three velocity components. The data of spectral moments and velocity field in height and time are archived on magnetic optical disk through a separate computer. For a detailed Gadanki wind profiler description, refer to Krishna Reddy et al. [2001a].

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Figure 1. (a) Location of the VHF and L-band wind profilers, (b) wind profiler antenna assembly, and (c) main topography of Gadanki area.

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Table 1. Gadanki LAWP System Specifications
ParameterSpecification
LocationGadanki (13.4°N, 79.18°E), India
Frequency1357.5 MHz
Maximum bandwidth2 MHz
Peak power1 kW
Maximum duty ratio5%
Antenna
  Antenna typephased arrays
  Antenna aperture3.8 × 3.8 m2
  Beam width
  Number of beams for automatic scanelectrical steering three directions
 
Data processing
  Pulse width0.33, 1, and 2 μs
  Interpulse period20–999 μs
  Number of coherent integrations1–256
  Number of incoherent integrations100
  Number of FFT points64–2048
 
Height sampling
  Number of heights (range gates)1–64
  Beam switchingvertical, north, and east with 15° zenith angle

[7] The NMRF is situated in a rural environment about 120 km to the northwest of Chennai (Madras) on the east coast of the southern peninsula. The terrain surrounding the radar site is illustrated by the three-dimensional contour map in Figure 1c. The local and general topography is rather complex, with a number of hills and a very irregular mix of agricultural, small-scale industrial, and rural population centers. The LAWP antenna assembly is installed in a bowl of hills, and the complex hilly terrains influence the boundary layer over Gadanki. The Gadanki LAWP system was installed on 28 August 1997 and has been working quite satisfactorily since 15 September 1997. Observations with the Gadanki LAWP were carried out fairly continuously from 15 September 1997 to 30 September 2000 as shown in Figure 2. A total of 775 days of wind profiler data are available until September 2000 for analysis. Although Figure 2 shows the observation period as of the end of September 2000, wind profiler operation will be continued. During the observational period, nonavailability of the data for several days was mainly due to system failure, system maintenance, and severe weather hazards. The data were not recorded for the entire month of April 1998 because of trouble with the FTP transfer from the online to the off-line computer. The LAWP was nonoperational from 26 August 1998 to 16 March 1999 due to major damage of the outdoor unit. Since 17 March 1999 the LAWP has been working satisfactorily and providing continuous data. Since 17 March 1999, Gadanki LAWP is operated in two modes, low and high mode, alternatively (as shown in Table 2).

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Figure 2. Wind profiler data availability from 15 September 1997 to 30 September 2000.

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Table 2. Gadanki LAWP Parameters
ParametersLow ModeHigh Mode
Pulse width1 μs2 μs
Interpulse period60 μs80 μs
Sampling interval1 μs1 μs
Start height150 m150 m
Number of coherent integrations7050
Number of incoherent integrations10064
Number of FFT points128128
Number of beams3 (north, east, and zenith)3 (north, east, and zenith)

[8] To assure the quality of the wind profiles obtained with the Gadanki LAWP, intercomparisons with the Indian mesosphere-stratosphere-troposphere (MST) radar wind data have been performed from three campaign periods (as shown in Table 3). The Indian MST radar is a high-powered, phase coherent, and pulsed VHF radar operating at a frequency of 53 MHz with an average power aperture product of 3 × 1010 Wm2. It is generally operated with six beams of 3° beam width, two each in the east-west and north-south planes, and two in the vertical directions with a lag of a few seconds between successive beams. For the detailed Indian MST radar system description and characteristics, refer to Rao et al. [1995].

Table 3. Three-Campaign Wind Data for Intercomparisona
 PeriodData Used for Comparison
  • a

    Obtained from Gadanki LAWP and Indian MST radar.

First campaign15–23 May 199815, 16, 17, 18, 19, 21, and 23 May
Second campaign1–5 June 19981, 2, 3, and 5 June
Third campaign17 July 1999 to 14 August 199917, 23, 24, 26, 27, 28, 29, 30, and 31 July and 2, 4, 5, and 6 August

[9] Our MST-LAWP algorithm is based on single-peak detection for producing the moment and horizontal wind data from the spectra by simply picking the strongest peak outside the clutter bounds. Quality control procedures [Brewster, 1989; Weber and Wuertz, 1991] are used to obtain the hourly horizontal winds. This signal-processing method works well for most of the time; however, there are limitations due to unrealistic wind data or when the consensus averaging method fails. To improve the data quality, we are planning to adopt advanced signal-processing methods [Griesser and Richner, 1998; Wilfong et al., 1999].

[10] The CBL height is deduced from the signal-to-noise ratio (SNR) recorded by the wind profiler. The technique is based on experimental and theoretical evidence indicating that the profile of structure intensity parameter Cn2 exhibits a peak at the inversion capping the mixed layer [Wyngaard and LeMone, 1980; Fairall, 1991]. The wind profiler SNR at a given range is directly proportional to Cn2 [VanZandt et al., 1978]. The CBL height is determined using two algorithms, similar to the method of Angevine et al. [1994]. In the first method the peak SNR of each sample is found, and then the median of the heights at which the peaks occur over some period is computed. In the second method the order can be reversed, taking the median of the SNR profiles first and then finding the height at which the peak occurs. Contour plots of the SNR can be used to find the CBL height by eye and also indicate when the measurement is reliable and how well defined the CBL is.

[11] The most important feature in the meteorology of south peninsular India is the seasonal alternation of atmospheric flow patterns associated with the monsoon. During the northeast (NE) monsoon (November–December) the general flow of surface air over the region is from the northeast, mainly of continental origin with low humidity, and also substantial precipitation falls over this region. In the summer months of June to September the surface winds take the opposite direction from sea to land, bringing with them vast amounts of moisture, cloudiness, and precipitation. The direction of winds in the major parts of the Bay of Bengal being southwesterly, the season is named as the southwest (SW) or summer monsoon season. Between these two principal seasons are the transitional seasons of the hot weather or premonsoon months from March to May, and retreating monsoon or postmonsoon month, October. For the first time, in India at Gadanki the collocated facility of lower atmospheric wind profiler, disdrometer, and optical rain gauge (ORG) observations is used for understanding the monsoon precipitation. To classify/determine the precipitating cloud type from Gadanki wind profiler data, the 10-min averaged reflectivity, Doppler velocity, and spectral width derived from the vertical pointing beam are calculated. From the vertical structure of the precipitating cloud systems we have classified each profile into convective, transition (mixed convective-stratiform), and stratiform rain based on a modified version of the classification of Williams et al. [1995] and Gage et al. [1996].

3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information

[12] In order to test the reliability and consistence of the wind profiler data, simultaneous measurements with other wind-profiling systems are necessary. Numerous studies have compared wind-profiler-measured winds with winds measured by other type of instruments (spatial separation between the two measurements is 5 km or greater) [Balsley and Farley, 1976; Fukao et al., 1982; McAfee et al., 1995; Luce et al., 2001]. Very few UHF and VHF wind profiler intercomparison experiments have been performed [Ecklund et al., 1990; McAfee et al., 1994, 1995]. Simultaneous measurements of the Gadanki LAWP and Indian MST radar (spatial separation of ∼200 m) seem to be of considerable interest for the following reasons: (1) Wind measurements of both the systems are based on the same physical principle, i.e., Doppler shift of signals, scattered at small-scale inhomogeneities of the refractivity index fields. (2) A comparable regime is realized with the two systems because of continuous operation, quasi-simultaneous measurements over the whole range, cycled measurement of single radial velocities, and measuring volume above the system site. (3) Atmospheric wind profilers' data are known for a high vertical resolution and reliable data quality from near the surface.

[13] We adopted a simple statistical procedure similar to that of Weber et al. [1993] for the comparison of Gadanki LAWP and MST radar wind data. The rainy periods are excluded for the intercomparison of wind data. The observation parameters of the LAWP and the Indian MST radar are shown in Table 4. The simultaneous observations of wind speed and wind direction measured by LAWP and MST radar on 19 May 1998 and 27 July 1999 are shown in Figure 3. Typical vertical profiles of strong and moderate wind speed observed on different days in different seasons show a good agreement between LAWP and MST radar data. In Figure 3b, tropical jet stream (at 2.7-km altitude) wind speed is noticed. In a number of situations a nearly constant bias between the LAWP and MST radar winds has been found over the range of overlap, although the structure of the wind profiles was nearly the same. Taking into account all the differences in the two-profiler systems, fairly good agreement between the two sets of observations can be noticed/reported.

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Figure 3. Typical example of wind speed measured simultaneously with Gadanki LAWP and Indian MST radar on (a) 19 May 1998 and (b) 27 July 1999.

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Table 4. Experimental Specification
ParametersLAWPMST Radar
Frequency1357.5 MHz53 MHz
Peak power1 kW2.5 MW
Antenna aperture4 × 4 m2130 × 130 m2
Pulse width1 μs1 μs
Interpulse period50 μs1000 μs
Number of coherent integrations100128
Number of incoherent integrations1001
FFT points128128
Number of beams15°E, zenith, 15°N10°E, zenith, 10°N

[14] To evaluate the performance of the Gadanki LAWP, we have performed a statistical intercomparison with the simultaneous observation of the Indian MST radar. The two profilers are about 200 m apart. Comparison is made only when valid data are available from both wind profilers. To avoid several scatterplots of intercomparison, only a typical scatterplot at 2.1 km for wind speed is shown in Figure 4. The correlation coefficient is around 0.92, which is probably acceptable in view of the differences in measurement technique. For the remaining heights/data set the results are summarized in Table 5. For the wind speed a slight bias with a tendency toward higher values from the MST radar at heights greater than 2.4 km can be noticed. The root-mean-square differences (RMS deviation) are in the range between 1.16 and 1.48 m/s without any obvious height dependence. However, the slight height dependence of the wind speed bias is probably due to the occasional occurrence of questionable wind values from the profilers at the lowermost level, which were not obviously wrong.

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Figure 4. Scatterplot of wind speed measured simultaneously with Gadanki LAWP and VHF radar.

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Table 5. Statistical Results From the Intercomparison of Gadanki LAWP and MST Radar
Height, mNumber of SamplesWind Speed, m/s
BiasRMS DeviationCorrelation Coefficient
18003670.371.180.89
21005480.291.240.92
2400867−0.221.560.94
2700984−0.391.620.95
30001024−0.181.470.96
33001089−0.271.490.93
3600823−0.321.300.92
3900672−0.411.240.90

[15] Weber and Wuertz [1990] made an extensive comparison of wind measured with a UHF wind profiler and rawinsondes at Stapleton Airport in Denver, Colorado. Differences with standard deviations of 2.5 m/s were attributed mainly to natural variability in the wind fields. Strauch et al. [1987] used a five-beam UHF wind profiler to derive independent near-simultaneous three-beam measurements of the horizontal wind. They found a standard deviation of 1.3 m/s for clear-air observations. Wuertz et al. [1988] repeated the experiment between May and August during the rainy period. When raindrop fall speeds were properly included in the horizontal wind calculations, errors of 2–4 m/s were found. Schlatter and Zbar [1994] documented a detailed assessment/performance report for the Wind Profiler Demonstration Network in the United States. McAfee et al. [1995] have examined in detail the quality of agreement in simultaneous measurements of vertical velocities measured by two collocated profilers in Platteville, Colorado. They found that the long-term mean vertical velocities agree within about 1 cm/s after the data have been edited to remove spurious values. Our results show that the root-mean-square differences for the LAWP-MST radar intercomparison have been found to range within about 1.62 m/s for the wind speed. The two systems are shown to compliment each other quite well considering both the availability and the reliability of the wind measurements.

4. Availability of Wind Measurements

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information

[16] For the application of Gadanki LAWP and, especially, for future use in wind climatology and numerical weather prediction, the availability of wind measurements at different height levels is an important question. Regarding the operational use of Gadanki LAWP, range limitation should be investigated. In particular, this limitation is the result of the dependence of backscattered signal intensity on several processes and parameters. We calculated the quality control rate, defined as the percentage ratio of the number of valid measurements, passing the consensus averaging as well as the quality control algorithm, to the total number of measurements for each range gate over the whole observation time, using hourly averaged measurements. Periods of system failures are excluded from the statistics. Figure 5 shows the relative availability of wind measurements during the observational period. In the “high” and “low” modes the wind velocities below 300 m were difficult to obtain (probability <80%). The attainable altitude coverage depends on the operating frequency and the power aperture product of the Gadanki LAWP. Moreover, performance is also dependent upon the quality of signal processing in the software design and receiver sensitivity. In the clear atmosphere without precipitation, the echo intensity increases with humidity, temperature, and their vertical gradients. This is why the height coverage was limited to below 3.6 km (with probability ≥ 80%) in the low mode. The Gadanki LAWP is very sensitive to precipitation particles, so that the height coverage is greatly increased up to 5 km in the high mode (with probability ≥ 80%). Although the general statistics during the observational period includes a high number of different synoptic situations, there is large variability in the atmospheric moisture content. This investigation is of the highest interest with respect to the intended operational use of the system.

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Figure 5. Relative availability of wind measurements with the Gadanki LAWP from 15 September 1997 to 30 September 2000.

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5. Planetary Boundary Layer Studies Using Gadanki LAWP

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information

[17] The planetary boundary layer (PBL) is the part of the atmosphere between the Earth's surface and the free atmosphere. The importance of the study of the PBL arises when we consider the direct impact of the PBL on our everyday life. However, many aspects of the complex structure and the dynamics of the PBL have not yet been clarified. Unfortunately, simple parameterization of CBL height in terms of surface meteorological data is often insufficient, especially in tropical regions. New knowledge about the tropical PBL has to be built on the basis of more reliable observations. Ground-based remote sensing instruments such as lower atmospheric wind profilers can be used for PBL dynamics. Several lower atmospheric wind profilers have been installed in various places around the world in the last two decades [White et al., 1991; Rogers et al., 1993; May and Wilczak, 1993; Angevine et al., 1994; Hashiguchi et al., 1995; Grimsdell and Angevine, 1998], following the first successful operation of 915-MHz wind profilers specially designed for the boundary layer and the lower atmosphere [Ecklund et al., 1988]. Therefore observations using this type of atmospheric wind profiler are useful to delineate the diurnal evolution of the PBL structure. CBL observations using wind profilers in tropical regions are very few compared to those in the midlatitudes.

[18] We have selected 2 days of data to show the boundary layer phenomena and also to introduce the Gadanki lower atmospheric wind profilers' ability to measure boundary layer height and structure. The intensity of the signal-to-noise ratio (SNR) is determined by the refractivity turbulence seen by the LAWP, which depends on the strength of mechanical turbulence and the background refractive index gradient [Gage et al., 1990]. The top of a convective boundary layer is present as a distinctive signature in a time-height plot of reflectivity. Generally, a strong peak of reflectivity is seen at the boundary layer top, though the strength of this peak depends on a variety of factors. The reflectivity peak is the result of strong gradients of temperature and, especially, humidity. Such gradients, although not usually as strong, may also be present at the boundaries of other atmospheric layers. Figure 6a shows a time-height cross section of range-corrected reflectivity (SNR) observed with the Gadanki LAWP during the dry period on 19 and 20 March 1998 (clear, sunny days). Two-day observations show that a thin enhanced reflectivity layer appeared in the morning (∼0700 local time (LT)) at about 600 m and ascended to about 1.5 km in the afternoon (∼1500 LT). After 1500 LT the enhanced layer gradually disappeared. The boundary layer top, as shown by the reflectivity plot, on 19 and 20 March 1998 grew rapidly into the residual layer between 0930 and 1200 LT and then was prevented from significant further growth by the strong and sharp capping inversion. At night the CBL was replaced by a stable or nocturnal boundary layer. The Gadanki LAWP cannot clearly measure the height of the nocturnal boundary layer because it is at or below the minimum height of the profiler. It must be noted that such remarkable diurnal PBL variations on other clear days in dry and wet seasons showed similar diurnal variations. On cloudy days, such features were weak or disappeared. On rainy days, strong echoes caused by rainfall appeared, but they are entirely different and are distinguished from the typical behavior of clear-air echoes mentioned above.

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Figure 6. Time-height cross section of the Gadanki LAWP (a) reflectivity (SNR) and (b) vertical velocity averaged over 5 min for the vertical beam on clear, sunny days (19 and 20 March 1998). (c) Ground temperature measured by the automatic weather station near LAWP.

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[19] Figure 6b shows the time-height cross section of vertical wind velocity on 19 and 20 March 1998. The vertical wind shows the presence of downdrafts and updrafts related to the morning rise of the inversion associated with convective activity. Figure 6c shows the surface automatic weather station temperature fluctuations at the NMRF site on 19 and 20 March 1998. The surface temperature shows typical diurnal characteristics on a clear day (maximum after local noon and minimum before local sunrise). We have found well-marked PBL diurnal variation on the clear, sunny days. The observational features of the PBL in this study were quite similar to those observed by boundary layer wind profilers at equatorial latitudes on clear days [Hashiguchi et al., 1995] in the dry season.

[20] The depth of the convective boundary layer is of first-order importance for air quality monitoring, and prediction can also be important in initializing and evaluating numerical weather prediction models. Using the reflectivity (SNR) data from the vertical beam, Gadanki LAWP can be used to monitor the top of the CBL. The CBL is clearly visible (on 2 and 3 March 1998) in the top plot of Figure 7 as a peak reflectivity (yellows) that rises from the near ground at sunrise and then breaks up in the late afternoon. On both of these days the automatic CBL height (1-hour average) find algorithm-produced height estimates are shown in the bottom plot of Figure 7. Because of the lack of supporting data (from radiosonde and lidar) at Gadanki the observed CBL height results are not validated/compared. The observational evidence from the LAWP was quite consistent with the time evolution of the PBL height estimated by Krishna Reddy et al. [1995] using an acoustic sounder (sodar) at Tirupati about 40 km northeast of the wind profiler site.

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Figure 7. Determinations of convective boundary layer height on 2 and 3 March 1998.

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[21] Gadanki is an intrinsically interesting site because of the influence of the local topography, in addition to the strong variations in surface heat flux that occur between the summer and winter months. We utilized the Gadanki LAWP capability for characterization of the convective boundary layer in the dry and wet periods. We analyzed the Gadanki LAWP data for dry and wet seasons during 1998–1999. Table 6 shows the periods of observations when we obtained qualified data. Figure 8 shows the midday boundary layer height for all days with a well-formed convective boundary layer. The height shown for each day is the average of 3 hours in early afternoon (1200–1500 local time). The boundary layer heights are determined for each hour by subjective examination of the results of a peak-finding algorithm using SNR from the Gadanki LAWP. The boundary layer height is determined by a variety of factors and is not simply related to any local surface meteorological variables, but we can see some broad relationships. The dry period/premonsoon in the beginning of summer is hot and very humid in southern India. During this period, maturation of the crops and consequent cessation of evapotranspiration occur. No measurable rain fell during the dry season, so soil moisture was probably quite low. It is an ideal situation for the convective boundary layer to form in this region. With the onset of the SW monsoon the cloudiness and humid conditions associated with the monsoon season high potential evapotranspiration. Hence, in the wet season, most of the net solar radiation evaporated moisture rather than heating the surface and therefore contributed little to buoyant forcing. In the dry period, during good convective days, smooth diurnal variation in wind is observed up to 2 km, and winds are northeasterly and southeasterly. Whereas in the wet period, the winds are mostly southwesterly and westerly, and there is frequent occurrence of low-level jets between 1- and 2-km heights associated with the monsoon flow [Krishna Reddy et al., 2001b]. We found that with a few exceptions the drier period has a higher boundary layer compared with the wet period. Sugimoto et al. [2000] also found similar results using lidar observations over Jakarta, Indonesia. Hashiguchi et al. [1995] examined the diurnal variations of the mixing PBL on clear days in the equatorial region using a wind profiler. They reported that the CBL heights were approximately 2–3 km, sometimes reached up to 3–5 km in the afternoon, and were accompanied by strong vertical wind fluctuations.

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Figure 8. Boundary layer heights from Gadanki LAWP measurements. Heights shown are the average over 1200–1500 local time for each day: (a) dry season and (b) wet season.

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Table 6. LAWP Observations Analyzed for Convective Boundary Layer Information
SeasonYearDaysNumber of Days
Dry19982–4, 19, 20, 25, and 26 March8
Wet19981–4, 10–14, and 28–31 July11
Dry19991–6, 20–23, and 25–31 March15
Wet19991–10 and 14–31 July23

6. Precipitating Cloud Systems of the Southern India Monsoon

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information

[22] The Earth's monsoon circulations are characterized by regions of large-scale ascent and heavy rains, which are essential to agricultural production through much of Asia. Tragic consequences occur when this precipitation is inadequate or ill timed. The cloud systems from which the rain falls strongly influence large-scale monsoon flow patterns and the global atmospheric circulation through the enormous amount of latent heat released and the effects of the clouds on the transfer of solar and terrestrial radiation. Understanding of the structure and behavior of monsoon cloud systems is therefore a prerequisite for accurate representation of diabatic processes in large-scale numerical simulation and prediction of monsoons and of the global circulation. Local forecasting of monsoon rains also requires detailed understanding of the precipitating cloud systems [Johnson and Houze, 1987; Yasunari, 1991]. During the past decade, atmospheric wind profilers have become the accepted tools for meteorological research and for operational applications [Gage et al., 1996; Williams et al., 2000; Renggono et al., 2001; Rao et al., 2001]. We illustrate the capability of the Gadanki wind profiler to observe the structure of precipitating cloud systems observed during SW and NE monsoon seasons. The vertical structure of the cloud systems leads straightforwardly to the identification of the bright band and stratiform precipitation. Mesoscale convective systems can be identified by disturbances above the melting level [Gage et al., 1996]. Since Gadanki LAWP operates continuously and unattended, this is an ideal instrument for resolving the annual and diurnal cycle of the precipitating cloud systems.

[23] The Doppler spectra are power-weighted distributions of the radial velocities of the scatterers within the radar resolution volume. Typical examples of the Doppler spectra observed by the Gadanki LAWP on 17 September 2000 during convection, transition, and stratiform periods of a mesoscale convective system (MCS) are shown in Figures 9a9c, respectively. A Doppler shift of 1 Hz corresponds to a radial velocity of 0.109 m/s. The positive Doppler shift indicates upward motion. In Figure 9a we can clearly see that the radar reflectivity is intense for the whole height range, and no melting layer and no sharp decrease in the fall speed profile are found. Figure 9a shows a large downward Doppler velocity of about 7 m/s from the ground up to a height of ∼8 km, indicating the presence of deep convection. The Doppler spectra in the transition period (Figure 9b) show two echoes up to a height of ∼1 km. The echo near zero Doppler shifts corresponds to the background air, while the echo on the negative side of the Doppler spectrum is due to hydrometeors. The hydrometeor radar reflectivity factor and Doppler velocity are found to be smaller during the transition period compared to the convection. In the Figure 9c the enhancement of the equivalent radar reflectivity with the melting layer, donated by the radar bright band, appears around 4.5 km. This enhancement is associated with the melting of ice particles to liquid water drops. The sharp drop-off of reflectivity in the lower portion of the melting layer is produced by two effects. If the melting process is completed and all particles collapse to form smaller size raindrops, then the reflectivity decreases. If its process is in the steady stratiform rain, the mean concentration of rainwater must decrease sharply, which corresponds to the decrease in reflectivity [Houze, 1993]. Together with the decrease in the reflectivity, the fall speed of the particles suddenly increases. This tendency can be noticed in Figure 9c, the downward velocity that increases from 2 m/s to 9 m/s. The decrease in the fall speed seen below 4 km is likely a result of evaporation, droplet breakup, and decreased Doppler velocity with increasing density.

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Figure 9. Doppler spectra observed during (a) convection, (b) transition, and (c) stratiform precipitation observed on 17 September 2000.

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[24] The shape of the Doppler spectra is characterized by the first three pieces of spectral moment information about the hydrometeors in the precipitating cloud systems. The moments yield the reflectivity of the hydrometeors, the reflectivity-weighted fall speed of the hydrometeors, and the variance of the hydrometeor fall speeds within the observing volume. A time-height cross section of equivalent reflectivity and Doppler velocity observed on 17–18 May 1999 during the passage of MCS is shown in Figure 10. This figure illustrates the Gadanki LAWP's potential for diagnosing the vertical structure of precipitating cloud systems. Several different types of vertical structure are evident in this figure during periods of rainfall observed at the surface, as the convective systems pass over the profiler. On 17–18 May between 2300 LT and 0300 LT and also on 18 May between 1730 LT and 1930 LT a bright band in the reflectivity and a melting layer signature of rapidly accelerating hydrometeor fall speeds below 4.6 km provide a clear example of stratiform rain. A heavier rain episode that occurred between 2100 LT and 2200 LT on 17 May illustrates deep convection without a melting layer signature.

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Figure 10. Time-height cross section of (a) 10-min mean reflectivity and (b) Doppler velocity observed by the vertical beam of the Gadanki LAWP on 17 and 18 May 1999. (c) The 1-min disdrometer-derived rain rate and reflectivity. In Figure 10a, C, T, and S indicate convective, transition, and stratiform cloud types, respectively.

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[25] The pattern of rainfall during a storm, however, will be largely deterministic since it depends upon the precipitating cloud system. Convectional rainfall is usually of higher intensity and shorter duration than rain from frontal systems. In general, convective- and frontal-type storms tend to have their peak rates near the beginning, while cyclonic events reach their maximum intensity nearer the middle of the storm period [Eagleson, 1970]. The mesoscale convective system signature can be clearly seen in the disdrometer time series plot (Figure 10c). However, the results of cloud classification are shown at the top of Figure 10a. C, T, and S indicate convective, transition, and stratiform precipitating cloud systems, respectively.

[26] In order to investigate the characteristics of the occurrence of convective, transition, and stratiform precipitating clouds, a long period of data from April 1999 to March 2000 by the Gadanki LAWP has been analyzed. Precipitation data of Gadanki LAWP observations have been chosen on the basis of large values of reflectivity and Doppler velocity (fall speed). To determine the thresholds of reflectivity and fall speed, disdrometer- or ORG-observed rain rate greater than 0.5 mm/h is considered as the echoes from the precipitation. After having evaluated 775 days of data of LAWP, a total of 6917 min of rain data with their corresponding reflectivity and fall speed derived from LAWP were accumulated. Figure 11a shows the observation results of the precipitating cloud systems in Gadanki during 1997–2000. The occurrence of precipitating clouds reaches a maximum in the SW monsoon compared with the NE monsoon. Krishna Reddy et al. [2000] used Gadanki disdrometer data to estimate the raindrop size distribution (DSD) parameters in different seasons. They found that there was a clear distinction of the DSD parameters in SW and NE monsoon seasons. During the SW monsoon the frequent occurrence of convective precipitating clouds is mostly associated with thunderstorms and lightning whereas during the NE monsoon the precipitating clouds are cyclonic in nature. Diurnal variation of convection seems to occur within 1100–1500 LT (Figure 11b). The occurrence of stratiform clouds is different from that of convective clouds. The highest percentage of occurrence appears from 1200 to 2000 LT. The peak of stratiform precipitating cloud has a smaller value and comes later than the convective clouds. The time delay between the peak of the stratiform and convective precipitating clouds corresponds to the life cycle of the mesoscale convective system. The occurrence of the diurnal cycle of the precipitating cloud systems over Gadanki is possibly caused by diurnally convective boundary layer patterns established by the monsoon thermal circulations. In subsequent papers, we will compare and validate our results with disdrometer and TRMM Precipitation Radar data.

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Figure 11. (a) Annual and (b) diurnal variations of precipitating cloud systems observed at Gadanki, India.

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7. Summary and Conclusion

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information

[27] An L-band (1357.5 MHz) lower atmospheric wind profiler (LAWP) has been operating continuously since 15 September 1997 at Gadanki, India. The LAWP and VHF profiler are nearly collocated (about 200 m apart) at the experimental site, Gadanki. The statistical comparison of the wind data shows a fairly good agreement between the two wind profilers. In the entire observational period, 80% availability of the LAWP was determined with 3.6-km wind measurements in low mode and 5-km wind measurements in high mode.

[28] We have found from the Gadanki LAWP observations that a strong diurnal cycle can appear in the PBL (or mixed layer) over hilly terrain, if the weather is fine and atmospheric conditions are suitable. Gadanki wind profiler results show that after sunrise the CBL forms and grows rapidly through the morning. The growth may continue in the afternoon, or the CBL height may stabilize, depending on the synoptic conditions and the amount of surface buoyancy flux. Sometimes in the afternoon the surface buoyancy flux becomes insufficient to support the CBL, and the turbulence decays. Furthermore, the Gadanki LAWP data revealed that, with a few exceptions, the drier period has a higher boundary layer compared with the wet period.

[29] Gadanki LAWP is sensitive to hydrometeors as well as to fluctuations of the radar refractive index in the clear air. In order to study the monsoon precipitation at Gadanki the vertical structure of precipitating cloud systems has been examined by using LAWP vertical beam data. It has been confirmed that during the occurrence of stratiform cloud, radar bright band is observed by the LAWP as an increase of radar reflectivity below the melting level. During the occurrence of convective cloud, intense reflectivity is detected at the whole sampling height range. Diurnal variations of the occurrence of precipitating cloud systems over Gadanki showed that the precipitation occurring in the afternoon and the peak of the stratiform cloud comes after the peak of the convective cloud. The precipitating cloud systems, which occur in the early morning, are dominated by stratiform cloud. Concerning seasonal variations of the precipitating clouds, we have found that the occurrence of the statiform precipitating cloud systems is more frequent in the NE monsoon, while the occurrence of the convective precipitating cloud systems is predominant in SW monsoon. Moreover, in the NE monsoon, a higher occurrence of precipitating cloud systems was observed.

Acknowledgments

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information

[30] The lower atmospheric wind profiler and the disdrometer were deployed at National MST Radar Facility (NMRF) under India-Japan collaboration. The optical rain gauge was supported by the National Space Development Agency of Japan. The NMRF is being operated by the Department of Space (DOS), Government of India, with partial funding support from the Council for Scientific and Industrial Research (CSIR). The principal author, K. Krishna Reddy, is thankful to the authorities of the Frontier Observational Research System for Global Change (FORSGC) for the necessary facilities to carry out the research work.

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  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data Sources and Analysis Techniques
  5. 3. Intercomparison of Gadanki LAWP and Indian MST Radar Wind Measurements
  6. 4. Availability of Wind Measurements
  7. 5. Planetary Boundary Layer Studies Using Gadanki LAWP
  8. 6. Precipitating Cloud Systems of the Southern India Monsoon
  9. 7. Summary and Conclusion
  10. Acknowledgments
  11. References
  12. Supporting Information
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rds4645-sup-0001-tab01.txtplain text document1KTab-delimited Table 1.
rds4645-sup-0002-tab02.txtplain text document0KTab-delimited Table 2.
rds4645-sup-0003-tab03.txtplain text document0KTab-delimited Table 3.
rds4645-sup-0004-tab04.txtplain text document0KTab-delimited Table 4.
rds4645-sup-0005-tab05.txtplain text document0KTab-delimited Table 5.
rds4645-sup-0006-tab06.txtplain text document0KTab-delimited Table 6.

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