Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/springer_journal/retrieval-of-temperature-profiles-using-radio-acoustic-sounding-system-ZWYL0AR00u
- Publisher
- Springer Journals
- Copyright
- Copyright © 2018 by The Author(s)
- Subject
- Earth Sciences; Earth Sciences, general; Geology; Geophysics/Geodesy
- eISSN
- 1880-5981
- DOI
- 10.1186/s40623-018-0784-x
- Publisher site
- See Article on Publisher Site
Abstract
The radio acoustic sounding system (RASS) with the equatorial atmosphere radar (EAR) at Koto Tabang, Indonesia was adapted to test the effects of the acoustic source location and acoustic frequency range on the continuous measure - ment of height profiles of temperature in the tropical troposphere. We installed the acoustic transmitting system by using six high-power horn speakers and four subwoofers. We developed a three-dimensional ray-tracing method of acoustic waves to predict the shape of acoustic wavefronts, accounting for the effects of the background winds on acoustic wave propagation. Then, we selected the appropriate antenna beam directions for EAR that satisfy the Bragg condition between the radar and acoustic wave propagation vectors. We carried out eight campaign observations in 2016, testing the performance of EAR–RASS. We found that the location and acoustic frequency range affected the RASS echoes. We also tested the compensation method of the background wind velocity with EAR to obtain the true sound speed. We intensively analyzed the RASS results from August 29 to September 3, 2016, when radiosondes were launched 12 times from the EAR site. We successfully retrieved the temperature profiles from RASS from 2 to 6–14 km with time and height resolutions of about 10 min and 150 m, respectively. Some temperature profiles were obtained up to about the tropopause at 17 km, although the observation period was short. During the RASS campaign, we detected a few interesting events regarding temperature variations as well as large perturbations in the three compo- nents of wind velocity. Keywords: Virtual temperature profile, EAR, RASS, Three-dimensional ray tracing, Tropical troposphere, Cloud convection Emanuel 1987; Frank and Cohen 1987; Welsh et al. 1999; Introduction Zhang and Fritsch 1988). The behavior of atmospheric disturbances in the trop - Because local and mesoscale effects are more dominant ics was studied by using various observation techniques, than synoptic influences in the tropics, continuous obser - such as radiosonde, weather radar, wind profiling radar vations are required. Therefore, ground-based remote (WPR), lidars, and satellite images. Mesoscale numerical sensing techniques are useful for studying tropical con- weather prediction (NWP) models were also adopted to vection. Given these conditions, equatorial atmosphere investigate dynamical characteristics during the events radar (EAR) was constructed in 2001 in Koto Tabang, of intense cumulonimbus convection, land–sea circula- West Sumatra under intensive collaboration between tion, and diurnal variations of convective activities (e.g., Japan and Indonesia (Fukao et al. 2003). EAR is equipped with an active phased array antenna and can measure *Correspondence: tsuda@rish.kyoto-u.ac.jp 2 three components of wind velocity. Research Institute for Sustainable Humanosphere (RISH), Kyoto University, Kyoto, Japan Full list of author information is available at the end of the article © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 2 of 20 In addition to winds, the observation of the atmos- measurements. RASS echoes were not stably obtained pheric temperature is vital for clarification of meteorolog - because the RASS echoing region did not always exist in ical phenomena. To profile temperature, a balloon-borne these beam directions, being considerably affected by the radiosonde is commonly employed at an operational background winds. weather station. Because the radiosonde is normally This study is concerned with improvements in the released at intervals of 6 to 24 h, the temporal resolu- EAR–RASS, by incorporating the ray-tracing method of tion of the soundings is insufficient for the studies of the acoustic waves and investigation of the sound sources. detailed structure of mesoscale meteorological phenom- We carried out eight campaign observations with EAR ena. Ground-based remote sensing methods, using radio in 2016, testing the performance of RASS. We show a and optical techniques such as microwave radiometer preliminary analysis of the specific disturbance events (e.g., Westwater 1970), Rayleigh and Raman lidars (e.g., observed during the EAR–RASS campaign from August Behrendt 2005), and the radio acoustic sounding system 29 to September 3, 2016. (RASS) (e.g., Marshall et al. 1972; Matuura et al. 1986), are developed for continuous monitoring of atmos- Basic principles of RASS pheric temperature profiles. Among these techniques, we Determination of temperature from sound speed focused on RASS in this study, which is a combination of For the RASS experiment, we first emit a large sound a high-power sound transmitter and WPR for observa- upward into the sky. Then, the density fluctuations due to tions of time and height variations in temperature in the the sound waves produce sinusoidal refractive index per- tropical troposphere. turbations that can effectively return the radio scattering RASS has been applied to WPRs operating at about 50, (RASS echo). The speed of sound, C , is determined with 400, and 1.3 GHz, corresponding to the acoustic frequency WPR from the Doppler frequency shift of the RASS echo. of about 100 Hz, 1, and 3 kHz, respectively, considering The atmospheric virtual temperature, T , can be deter- the Bragg condition between the radar and sound wave- mined using the relationship that the speed of sound is lengths (e.g., Masuda et al. 1990; May et al. 1988). Sounds proportional to the square of the atmospheric tempera- with frequencies higher than a few kHz immediately decay ture (see “Appendix”). in the atmosphere because of the effects of turbulence, and It is noteworthy that C is the sound speed in the air therefore, they do not reach great heights (e.g., Clifford parcel in which the sound waves are propagating. Mean- and Wang 1977; Peters 2000). Hence, the height coverage while, the ground-based WPR detects the apparent was restricted to, at most, several kilometers. However, sound speed, C , which is a summation of C and the a s RASS with a 50-MHz WPR, such as the MU radar in Japan motion of the air parcel itself. Hence, we need to com- (Matuura et al. 1986; Tsuda et al. 1989, 1994; Adachi et al. pensate for the background wind velocity in the direction 1993) and the Gadanki MST radar in India (Sarma et al. of the sound wave propagation, V , before we calculate T r v 2008, 2010), used the sound at about 100 Hz, which made from C (hereafter, we use T as the virtual temperature it possible to measure atmospheric temperatures up to observed with RASS). about 23 km, exceeding the tropopause. Furthermore, the In our study, we combined two sets of radar observa- height coverage of RASS was significantly determined by tion modes—one for the sound speed measurement the effects of the background wind velocity on the propa - with the RASS echo and the other for the conventional gation of acoustic waves (Masuda 1988). five-beam wind velocity measurements, pointing the RASS was applied to EAR operating at 47 MHz, aiming vertical and four oblique beams at 10° zenith angle into to measure the temperature in the troposphere over the north, east, south, and west azimuth directions. We com- equatorial region (e.g., Alexander et al. 2006; Furumoto posed V by a vector combination of the vertical and the et al. 2006). The intensive campaign called Coupling four radial wind velocities. This manipulation of V may Processes in the Equatorial Atmosphere (CPEA) was induce additional measurement error because of the conducted in 2001–2007, by coordinating many obser- interpolation of height coordinates and the possible spa- vation instruments gathered around the EAR observa- tial variations in the wind field within the antenna beam tory (Fukao 2006). Key results of the CPEA campaigns steering range. were summarized in special issues of J. Meteorol. Soc. We additionally employed a third mode to directly Japan (2006). The behavior of the tropical convection measure V by steering the antenna beam into the direc- was reported by Alexander et al. (2006), using EAR– tion of the RASS echoes. Then, we do not need any vec - RASS results. For the RASS experiments, we used fixed tor combination or coordinate interpolation for V . In antenna beams at five directions, a vertical and four a later section, we will discuss the improvement in the oblique beams at 10° zenith angle, which are used for measurement accuracy of EAR–RASS, comparing the the standard wind velocity and turbulence parameter two methods in compensating for the radial winds. Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 3 of 20 Bragg condition for RASS echoes increases from the value on the Earth’s surface at a cer- The Bragg condition is essential in detecting the atmos - tain rate with increasing height, the shape of the sound pheric turbulence echo with WPR, requiring that half wave surface is such that the principal axis of the sphe- of the radar wavelength must lie within the turbulence roid is tilted. If this happens, the orthogonality condition spectrum. This Bragg condition is also applied to RASS, cannot be met even if the radar antenna is pointed in the interpreted as the relationship between the wavenumber vertical direction. vectors of radar radio waves, k and the acoustic waves, k , We employed the 3-D ray-tracing method to estimate r a the sound wavefronts, assuming the realistic profiles of � � k = 2k , (1) a r the temperature and the background horizontal wind velocity. Then, we steered the antenna beam to satisfy � � the orthogonality condition (Eq. 3), which depends on k = 2 k , a r (2) the relative geometric arrangement between the radar and the acoustic source. When a sound source is installed k //k . (3) a r in the windward direction with respect to the radar, the That is, the magnitude ratio of these vectors should be antenna beam pointed in the windward direction is the 2:1 (Eq. 2), and these vectors should be parallel (Eq. 3). optimal condition. The former condition requires that the sound wavelength The RASS echo can be expected when the returned should be half of the radar wavelength, which is called the radio signal points to the center of the WPR antenna. resonance condition. The latter condition refers to the fact To infer the allowance of the RASS echo detection, we that the radar antenna beam should be steered into the assume that the returned echo falls in the area within direction perpendicular to the sound wave surface, which some distance from the antenna center. We define the is called the orthogonality condition. distance between the RASS echo from the antenna center as the index of the RASS echo intensity. 3‑D ray tracing of sound waves Assuming the wind velocity profiles in Fig. 1 observed To satisfy the orthogonal condition of the Bragg condi- with EAR at 00:00 LT on September 3, 2016, we con- tion, it is important to investigate the propagation char- ducted the 3-D ray-tracing of acoustic wavefronts. acteristics of the sound waves. Then, the antenna beam Because the wind velocity above about 11 km was not of WPR should be steered into the appropriate directions fully obtained by EAR, we refer to the nearby radiosonde that intersect the sound wavefront perpendicularly. The data archived at NOAA (https://esrl.noaa.gov/) for the MU radar and EAR have an advantage in the capability wind velocity profiles above 11 km. The shape of the to point the antenna beam into any direction by employ- acoustic wavefronts is nearly concentric, but the spacing ing the active phased array. Masuda (1988) developed a between the wavefronts becomes shorter as they propa- two-dimensional ray-tracing algorithm for RASS experi- gate higher because of the decrease in the sound speed ments with the MU radar, leading to the expansion of associated with the temperature decrease. the RASS height coverage. The method was improved The RASS echoing region of the acoustic wavefronts to treat a three-dimensional (3-D) case for RASS with was determined as in Fig. 2, where the shading gradation Gadanki MST radar (Sarma et al. 2008). However, for the Gadanki MST radar, the antenna beam was steered into only two orthogonal azimuth directions, aligned in the north–south and east–west directions. In this study, we developed a 3-D ray-tracing method, aiming its applica- tion of RASS to EAR, having full antenna steerability. When the sound wave is emitted into the sky, the wave surfaces propagate as approximately concentric spheres. However, the temperature decreases along with height; therefore, the sound speed decreases with increasing height. The sound wavefront is deformed from a concen - tric sphere to a spheroid. Therefore, if the sound source and the radar are placed at the same point, the orthogo- nality condition is satisfied only when the radar antenna is pointed into the zenith direction. In a real atmosphere, the background winds affect the propagation of sound Fig. 1 Eastward (left) and northward (right) wind velocity profiles observed with EAR at 00:00 LT on September 3, 2016 waves. For example, when the horizontal wind speed Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 4 of 20 beam, shown by the green line in Fig. 3, successfully observed the RASS echoes in a wider height range. During the EAR–RASS campaigns, we checked the variations in the wind fields about every hour and repeated the 3-D ray-tracing computation. Then, the antenna beam directions were changed appropriately, if necessary. When the EAR wind data were not available, we referred to the operational radiosonde data taken at Singapore and Kuala Lumpur at 00:00 and 12:00 UT. As these stations are about 400 km away from EAR, details of the wind velocity fluctuations may not fully represent the wind field over the EAR site. The straight ray path of the RASS echoes does not nec - essarily return to the antenna center, and only a part of Fig. 2 Distribution of the RASS echoing region that satisfies the the antenna area is illuminated by the RASS echo. Then, Bragg condition. The shading depth is changed as a function of the the effective beam direction becomes slightly different distance between the return point of the RASS echo on the ground from the antenna boresight, which could produce an and the center of the EAR antenna. The figure shows four levels of the shading for a distance up to 80 m with a step of 20 m. The green line error in the estimation of the radial wind velocity (May indicates the antenna beam with the zenith angle at 13° et al. 1996). Here, we assume that the vertical beam is employed to detect the RASS echo whose ray path returned to the is changed, depending on the distance of the echo return point 50 m away from the antenna center. The effective point from the antenna center every 20 m. The straight zenith angle of the antenna beam is not zero anymore, line corresponds to the antenna beam direction that can becoming about 0.017° and 0.005° at 1.5 and 5 km alti- detect RASS echoes up to about 13 km, although the tude, respectively. Then, the background radial wind echo power may be reduced at around 7 km. The asym - measurement is contaminated by the projection of the metry of the wavefronts can be clearly recognized, which horizontal winds. Assuming the horizontal wind velocity −1 was caused by the zonal winds. A 3-D plot of the RASS is 3 and 10 m s at 1.5 and 5 km, respectively, the error echoing region is shown in Fig. 3. The five blue lines indi - in the radial wind velocity can be estimated at about −1 cate the antenna beam directions used in the conven- 0.05 m s at both altitudes, which corresponds to a tem- tional five-beam method for EAR–RASS experiments in perature error of about 0.08 K. Therefore, the anticipated 2001–2005, which did not effectively detect the RASS error by May et al. (1996) seems to be insignificant. echoes. Meanwhile, the appropriately steered antenna EAR–RASS experiments Outline of RASS experiments Basic specifications of EAR are shown in Table 1. EAR is equipped with a quasi-circular active phased array of 560 three-element Yagi antennas and has a diameter of Table 1 Specification of the equatorial atmosphere radar (EAR) Location 100.32°E, 0.2°S, 865 m MSL Active phased array antenna 110 m in diameter with 560 3-ele- ment Yagi Operating frequency 47 MHz Peak transmitting power 100 kW Shortest pulse width 1 µs Height resolution 150 m Fig. 3 An example of the 3-D projection of the ray-tracing results. Antenna beam steering Any direction within 30° from the The conditions are the same as in Fig. 2, but the shading distance is zenith limited to 60 m. Five blue lines indicate the vertical and four oblique antenna beams at the 10° zenith angle and the green line at (90°, 13°) Eec ff tive antenna beam width (3 dB) 3.4° Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 5 of 20 approximately 110 m (Fukao et al. 2003). The peak trans - Table 3 Radar parameters for the RASS measurements with EAR mitting power is 100 kW, which is 1/10 of the MU radar, with a maximum duty factor of 5%. Therefore, the sen - Range resolution 150 m sitivity of EAR is somewhat poorer than the MU radar. Minimum height 1050 m The maximum echoing height varies depending on the Beam steering 5 beams, depending on 3-D ray- refractive index turbulence intensity and the background tracing results conditions. During our RASS experiments, the effective IPP (beam steering interval) 200 µs height range of the turbulence echoes was mostly limited Number of coherent integration 16 to 10–11 km, while the lowest height of the EAR wind Number of incoherent integration 5 measurements is about 1 km above the ground because Number of FFT points 512 of the blanking of a receiver by the transmitted pulse. Pulse code 8-bit optimum code of Spano and Here, the fundamental procedure and the observation Ghebrebrhan (1996) parameters of the EAR–RASS experiments are sum- Number of height samples 150 marized. First, we conducted the 3-D ray tracing to the Duration 41.0 s acoustic wave shape, referring to the updated wind veloc- ity profiles with EAR and the climatological tempera - ture profiles from archived radiosonde results. Then, we for five beams was obtained every 16.4 s. The range of the selected antenna beam directions that can cover a wide Doppler spectrum was 3.9 Hz, and the frequency resolu- height range for RASS echoes. The frequency range of tion was 0.03 Hz. So, the maximum radial wind velocity −1 −1 the FM-chirped acoustic signal was also appropriately ranged up to 12.5 m s with a resolution of 0.10 m s . adjusted (Masuda et al. 1992). Once RASS experiments We take this resolution as the nominal measurement began, the performance of the RASS echo acquisition was error (r.m.s. standard deviation) of the radial wind veloc- checked, and the observations parameters, especially the ity measurements with EAR. Assuming the sound speed −1 antenna beam directions, were changed every few hours. can be determined with the same r.m.s. (0.1 m s ), we We interleaved the conventional wind velocity meas- can estimate the accuracy of the RASS temperature to be urements with turbulence echoes and RASS measure- about 0.17 K on the ground and about 0.13 K near the ments. The former is necessary to determine the wind tropopause. velocity variations, which can be combined with the We derived the horizontal wind velocity by combining RASS temperature data for studies of meteorological a pair of radial winds in either the east–west or north– phenomena. In addition, real-time wind information is south directions at a zenith angle of 10°. Assuming the important for the 3-D ray tracing of the sound waves as error distribution is the same for the beam pair, we can well as the compensation of radial wind velocity from estimate the error of the resulting horizontal wind veloc- ◦ −1 the apparent sound speed. Tables 2 and 3 show system ity to be 2×0.1 2sin 10 = 0.407 m s . parameters for both turbulence and RASS experiments, The sound speed in the troposphere normally ranges −1 respectively. from 270 to 350 m s , which is far away from the zero Considering that IPP was 400 µs and the number of Doppler shift. Thus, the major part of the Doppler spec - coherent integrations was 64, one set of Doppler spectra trum is not used for RASS measurements. We employed an additional receiver channel for RASS, which can shift the frequency of the intermediate frequency (IF) signal Table 2 Radar parameters for the turbulence echo meas- by about 100 Hz so as to move the RASS signal toward urements with EAR the center of the Doppler spectrum. Because a small fre- quency drift in this offset is anticipated, we analyzed the Range resolution 150 m exact offset value by investigating the frequency shift of Minimum height 1050 m the ground clutter. Bean direction (Azimuth, Zenith (0°, 0°), (0°, 10°), (90°, 10°), (180°, 10°), angle) (270°, 10°) We added another observation mode for the turbu- IPP (beam steering interval) 400 µs lence echoes by steering the antenna beam into the same Number of coherent integration 64 directions as the RASS mode. However, we did not apply Number of incoherent integration 4 a frequency shift in the receiver channel. Thus, we meas - Number of FFT points 128 ured directly the radial wind velocity in the beam direc- Pulse code 16-bit optimum code of Spano and tion of RASS echoes. Interleaving the pair of RASS and Ghebrebrhan (1996) turbulence echo modes took 113 s, increasing to about Number of height samples 150 181 s with the addition of another mode for the radial Duration 65.5 s wind velocity measurements. Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 6 of 20 Acoustic transmitter Assuming a temperature range in the troposphere from Considering the resonance condition for RASS, we 25 to − 90 °C, the corresponding sound speed ranges −1 needed an efficient acoustic transmitter at 80–110 Hz, from 346 to 271 m s . As the radar wavelength is 6.38 m, corresponding to the radar wavelength of 6.38 m. We the acoustic frequency ranges from 108.5 to 85.0 Hz. We employed a horn speaker designed by Adachi (1996), used a WAVE file for the FM-chirped signal sweeping which was used for the MU radar and the Gadanki MST from 110 to 85 Hz in 2 s. The control PC produced this radar. Figure 4 shows the design of the horn speaker. Two FM-chirped signal every 10 s. sets of woofer speakers (Electro-Voice DL-15X or Kappa Pro 15A) with a nominal output of 400 W were installed Observation periods of EAR–RASS experiments in the horn. We repeated the EAR–RASS experiments eight times in In addition, we made a simple acoustic transmit- 2016 as summarized in Table 4, where the local time in ter using a subwoofer speaker with an enclosure (TOA, Indonesia (LT) precedes UT by seven hours. During the FB120B). We placed two sets of subwoofers in a wooden first three periods, the sweep range of the FM-chirped box with the front facing down. The bottom of the box is acoustic signal was set at 115–90 Hz to measure the tem- open. Sound waves were emitted downward, reflected on perature up to 14 km. During period (3), we tested sev- the ground, and transmitted upward to the sky. eral different acoustic frequency ranges. After period (4), The sound source is generated by a control PC, con - we expanded the range to 115–85 Hz, aiming to reach nected to four preamplifiers located inside the control the tropopause. For period (8), two sets of signals with a building. Two outputs from each preamplifier are fed to a duration of 2 s at 110–90 Hz and 95–75 Hz were used, power amplifier in the antenna field. As the power ampli - interleaving every 10 s. fier has two outputs, a total of 16 speakers can operate. Climatological results of the wind fields over Koto Figure 5 shows the location of these acoustic trans- Tabang from an earlier EAR dataset indicate that the mitters. We put four sets of high-power speakers in the meridional winds are normally weak, while the zonal −1 antenna center, and an additional two sets were placed winds sometimes exceed about 30 m s . In particular, northwest and southwest of the antenna. Two sets of sub- both zonal and meridional winds were weak in April; woofer speakers were located east of the antenna, and then, the vertical beam could capture the RASS echo in one subwoofer speaker each was placed north and south the entire troposphere. On the other hand, zonal winds of the antenna. After several test experiments, we final - were stronger in October–December. Throughout the ized the setup of all speakers on May 31, 2016. year, the zonal winds were westward at 10–14 km, so the Fig. 4 Cross section of the horn speaker (Adachi 1996). A blue triangle indicates a woofer speaker that is commercially available Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 7 of 20 −1 temperature decreases at 6.5 K km from the surface up to the tropopause at 17 km. Then, the temperature −1 increases in the stratosphere at 2 K km . The thresh - old of temperature variability was set at 15 and 20 K in the troposphere and stratosphere, respectively, which is much larger than the actual temperature fluctuations. Figure 6 shows an example of the Doppler spectrum in two different formats: power spectra at each range gate (top) and a contour plot (bottom), which were obtained at 00:14 LT on September 3, 2016 with the antenna beam at the azimuth and zenith angles at 90° and 13°, respectively. It is noteworthy that a positive Doppler shift indicates a target moving away from the radar, which is oppo- site to the conventional definition of the Doppler shift. The RASS echo was strong up to about 5 km, becoming weaker at 5–10 km with a clear echo again at 10–13 km. These spectra correspond to the 3-D ray-tracing shown in Fig. 2, indicating that the ray-tracing method properly predicted the RASS echoing region. Fig. 5 Location of acoustic speaker for EAR–RASS. Type (A) is a high- power horn speaker, and type (B) is a subwoofer speaker Location of acoustic speakers We were interested in determining which speakers on the antenna field were effective in producing the RASS ech - antenna beam was mostly steered toward the east for the oes. During campaign period (4), shown in Table 4, we RASS experiment. selected a calm condition without significant wind varia - During the observation periods (1) and (2), we tions. We first operated all speakers, and we stopped the employed the standard five-beam method with the zenith four speakers in the antenna center from 14:37 LT on angle at 10°, because RASS echoes were expected by the May 31 so that only the speakers outside the antenna vertical beam. For other periods after April 30, 2016, we were running. Then, we turned on the central speakers selected the beam directions referring to the 3-D ray one by one at 14:45, 14:48, 14:56, and 15:02 LT. tracing on a real-time basis. Using the wind velocity profiles in Fig. 7 observed For the turbulence echo, we apply a fitting to the with EAR at 14:30 LT on May 31, 2016, we conducted a observed Doppler spectrum assuming the Gaussian 3-D ray-tracing analysis, and we show in Fig. 8a, b the distribution. We also adopted a Gaussian fitting for the cross section at an azimuth angle of 60° for the speakers RASS echo. As the height profile of the sound speed is located in the antenna center and east side, respectively. roughly known a priori, we limited the range of the mean Note that the wind data were limited up to about 11 km, Doppler shift from a climatological profile, where the so the ray-tracing plots may not be reliable above 11 km. Table 4 Observation periods of EAR–RASS in 2016 No Start Stop Sweep range of FM chirp (Hz) Month Day LT Month Day LT (1) Feb 1 12:00 Feb 4 13:00 115 90 (2) Mar 24 16:00 Mar 27 15:00 115 90 (3) Apr 30 16:00 May 1 12:00 115 90 (4) May 29 14:00 Jun 2 16:00 115 85 (5) Jun 27 9:00 Jul 1 15:00 115 85 (6) Aug 5 9:00 Aug 6 15:00 115 85 (7) Aug 29 8:00 Sep 3 6:00 115 85 (8) Nov 21 14:00 Nov 24 16:00 110 90 95 75 Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 8 of 20 Fig. 7 Eastward (left) and northward (right) wind velocity profiles observed with EAR at 14:30 LT on May 31, 2016 Fig. 6 Doppler spectra for RASS echoes observed at 00:14 LT on September 3, 2016, with the radar beam pointed at (90°, 13°). The horizontal axis shows the sound speed before correcting for the fre- quency shift (100 Hz) in the mixer. The top panel shows over plotting of the spectra, while the bottom panel shows the spectra as a con- tour plot. The black line indicates the fitted mean Doppler shift, while the yellow and orange lines are the standard temperature profile and ranges for removing outliers Figure 9 shows the RASS echo power measured with the beam at (60°, 10°) at 1.64, 4.48, and 7.92 km altitudes. When all the speakers were turned on at the beginning of the period, the RASS echo intensity was the largest at 1.64 km, diminishing at 4.48 km, and again becom- ing stronger at 7.92 km, consistent with the ray-tracing Fig. 8 Cross sections of the ray-tracing results with an azimuth results. The speakers in the antenna center were turned angle of 60°, assuming the background wind velocity profiles shown in Fig. 7, for the acoustic source located in the center of the EAR on one by one, whose timing is indicated by the dashed antenna (top panel) and the speakers located 50 m away from the lines in Fig. 9. Although the echo intensity showed con- antenna center toward east (bottom panel) siderable fluctuations, it increased stepwise according to Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 9 of 20 Sweep range of FM‑chirped signal During experiment (4) from May 29 to June 2, we tested the effects of the sweep range of the acoustic frequencies. By selecting the sweep range from 90 to 115 Hz, the height range from the ground up to 14 km is covered. We nar- rowed the range to 90–100 Hz from 16:23 LT on May 31, which corresponds to a height range above 6.6 km. Then, after this change of the acoustic frequency range, RASS echoes disappeared below about 6.5 km in Fig. 10, and the RASS echo power above about 7.5 km became stronger. Time variations of the RASS echo power are plotted in Fig. 11 at 8.67, 8.97, and 9.26 km, where the sweep range Fig. 9 Time variations of the RASS echo power at 1.64 km (black), 4.48 km (blue), and 7.92 km (red) from 14:22 to 15:24 LT on May 31, was switched at 16:23 LT as indicated by the straight 2016. Operation of the speakers was changed at the timing of the line. When the sweep rate became slower, the sound on vertical dashed lines (see text) the same frequency was emitted 2.5 times longer after 16:23 LT. Thus, we expected the increase in the echo power to be 2.5 = 8.0 dB. We calculated the arithmetic the number of speakers at 1.64 and 7.92 km. The echo mean of the RASS echo power during 16:12–16:20 LT power finally returned to a similar value after 15:02 LT. and 16:25–16:33 LT, which were the periods before and u Th s, the RASS echo power was basically in proportion after the change in the acoustic signals. The mean value to the number of the speakers in the antenna center. increased by 7.6 dB from 10.2 to 17.8 dB at 8.67 km. The Meanwhile, at 4.48 km, the echo power was nearly con- increase was 16.5 dB from − 7.9 to 8.6 dB at 8.97 km stant during this experiment, indicating that the speak- and 14.0 dB from − 16.9 to − 2.9 dB at 9.26 km. Fig- ers outside the antenna contributed to produce RASS ure 10 shows that the RASS echo was most continuous echoes. These outside speakers were also effective at at 8.67 km among the three altitudes, where the increase 1.64 km, but not at 7.92 km, probably because the sound in the RASS echo power (7.6 dB) was consistent with the output was not large enough to reach higher altitudes. theoretical prediction (8 dB). To summarize, placing more speakers within the It is recognized that the sweep range, which is related antenna area is recommended, but those outside the to the number of wave acoustic cycles on a specific antenna also contributed to RASS echoes, depending on acoustic frequency, affected the RASS echo power. the background wind conditions. Fig. 10 Time and height variations of the temperature observed with EAR–RASS from 16:05 to 16:38 LT on May 31, 2016. Sweep range of the FM- chirped acoustic signals was changed at 16:23 LT (see text) Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 10 of 20 wind measurement were interleaved in the RASS beam directions. We launched radiosondes (VAISALA RS41- SG) from the EAR site 12 times during campaign (7), as summarized in Table 5. We selected the antenna beam directions that covered the widest RASS echoing height range, so the selected antenna beams varied time to time, as shown in Fig. 12. We determined the temperature for individual antenna beam directions from the fit of the Doppler spectra shown in Fig. 6. Because the height coordinate of each beam is not uniform throughout the campaign, but depends on the zenith angle, we projected it to the standard height coor- Fig. 11 Time variations of the RASS echo intensity from 16:05 to 16:58 on May 31, 2016, at 8.67 km (black), 8.97 km (blue), and 9.26 km dinate with the zenith angle at 10°. This is also used as the (red) altitudes. The sweep range of the acoustic signal was changed height coordinate of horizontal wind velocity with EAR. at the timing of the vertical line We applied a second-order inverse distance weighting interpolation (Wilks 2006) to obtain the T profiles on the standard height coordinate. Due to some missing RASS Emitting combinations of several FM-chirped acoustic echoes in a single profile, the nearest two RASS data pulses with different sweep ranges is useful for obtaining points to the standard height were not always available strong RASS echoes. for the interpolation. Therefore, we restricted the inter - polation when the height difference (distance) from the Compensation of radial wind velocity standard coordinate point was within 0.6 km. If the RASS WPR observes the apparent sound speed; then, the true results were missing for longer than this range, we skipped sound speed is obtained by compensating for the radial the interpolation. Thus, we obtained the T profiles with wind velocity. Referring the temperature estimation using the five RASS beams on the same height coordinate. −1 Eq. (4), a radial wind velocity of 1 m s would produce After the interpolation process, we applied the data an error of 1.7 and 1.4 K near the ground and at 16 km screening of EAR–RASS T profiles using radiosonde altitude, respectively. data for removing unrealistic values. The mean tem - We can obtain the radial wind velocity in the direction perature profile is mostly stable in the tropical tropo - of the RASS beams by composing it from the vertical sphere. So, we estimated the range of the temperature and two horizontal wind velocities. Assuming the error deviation, referring to earlier radiosonde data at the for the vertical and horizontal wind velocities to be 0.1 EAR site. An intensive campaign was conducted in −1 and 0.41 m s , respectively, the anticipated radial wind December 2005, in which radiosondes were launched velocity error in the direction of RASS beams is about −1 0.32 m s . For the direct measurement of the radial wind −1 velocity, the error is 0.1 m s . For the RASS experiment Table 5 Radiosonde launch schedule during EAR–RASS during period (7), the radial direction for RASS was (90°, campaign in August–September, 2016 13°). We calculated two sets of radial wind velocities from 14:30 to 18:30 LT on August 30, calculated the r.m.s. dif- No Date Launch time Maximum Comparison (LT = 7 h + UT) altitude/balloon of N with RASS ference, and averaged them at 3–7 km. The difference was burst (km) −1 0.23 m s for the radial wind velocity and 0.45 K for the temperature. Therefore, employing additional radial wind 1 Aug 30 08:45 27.0 – velocity measurements is recommended for improving 2 Aug 30 11:31 26.0 Yes the accuracy of the RASS temperature results. 3 Aug 30 15:34 25.8 – 4 Aug 31 07:26 26.2 Yes Results of the EAR–RASS measurements 5 Aug 31 11:58 27.1 Yes Temperature variations observed with EAR–RASS 6 Aug 31 19:01 24.7 – in August–September 2016 7 Sep 01 07:08 26.7 Yes We focus on the EAR–RASS results during campaign (7) 8 Sep 01 10:55 24.4 Yes from 08:56 LT on August 29 to 06:18 LT on September 9 Sep 01 15:08 18.4 Yes 3. The original time resolution of the EAR–RASS T pro - 10 Sep 02 07:22 25.6 – files is about 3 min (181 s), as the three radar modes for 11 Sep 02 11:07 24.4 – the standard wind measurements, RASS, and the radial 12 Sep 02 18:55 20.8 – Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 11 of 20 Fig. 12 Variation of zenith and azimuth angles during the EAR–RASS campaign from Aug 29 to Sep 3, 2016. Tick mark in the horizontal axis indi- cates 00:00 LT with a time interval of 1 h on December 9–10, 12–13, 1-h time resolution ranged between 0.8 and 1.0 K 15–16, and 18–19, using three sets of radiosonde at 1–4 km, increasing to 1.2 K at 4–5 km, and then receivers (Ratnam et al. 2009). We estimated the decreasing to 0.6 K above 6 km. We assumed that the range of the temperature variations with different bal - EAR–RASS observation with a 3-min time resolu- loon launch intervals of 1, 2, 4, 6, and 12 h, as shown tion may have a larger standard deviation. So, we took in Fig. 13. The standard deviation of T profiles with three times the maximum deviation in Fig. 13, i.e., 1.2 × 3 = 3.6 K as the threshold for removing outli- ers. We constructed a mean temperature profile from 12 radiosonde soundings during RASS campaign (7) in 2016. When the RASS values at each altitude devi- ated from this mean more than 3.6 K, we rejected the RASS data as an erroneous determination. Note that the standard deviation of T from 12 radiosonde profiles in 2016 was between 0.5 and 0.7 K in the troposphere up to 16 km, much smaller than the above threshold. At each height coordinate, we averaged all available data among the five beams every 10 min, as the tempera - ture is a scalar quantity. The time and height variations of the RASS temperature are plotted in Fig. 14 with time resolutions of 3 min (original time interval), 10 min, and 1 h. The data availability rate increased for longer time resolutions because of the interpolation along height and time averaging. With 10-min time resolution, the tem- perature was obtained at 2–6 km with 50–80% availabil- ity, and the availability rate became 30–10% at 7–14 km. Fig. 13 Profiles of temperature perturbations (standard deviation) for different balloon launch intervals of 1, 2, 4, 6, and 12 h from the The results in Fig. 14 are the basis of further data analysis. intensive radiosonde campaign in December 2005 at the EAR site Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 12 of 20 Fig. 14 Time and height plots of T (left) and the data availability rate (right) for the original RASS data with 3-min resolution (top) and averaged results with 10 min (middle) and 1 h (bottom) averaging Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 13 of 20 Comparison between RASS and radiosonde by estimating the system delay in the radar hardware. For a few cases, we successfully obtained temperature Although we adjusted the system delay (about 200 m), profiles from RASS data up to the lapse rate tropopause comparing the EAR wind velocity profile with the simul - at about 16 km as in Fig. 14. However, the radial wind taneous radiosonde, there seemed to remain an addi- velocity was not fully observed because of the limit of the tional delay of about 100 m. The standard deviation of the EAR sensitivity, and the temperature results may not be temperature difference from the mean values was esti - accurate above about 11 km. mated to be 0.4 K, which we think is the implicit accu- Figure 15 shows the mean (virtual) temperature from racy of RASS in comparison with a radiosonde. the 12 radiosondes launched from August 30 to Septem- ber 2, as listed in Table 5. We also averaged all RASS pro- Temperature disturbance events files with 10-min resolution as shown in Fig. 15. Because Figure 16 shows the perturbation components of the we set the threshold for the outlier of RASS data, refer- RASS temperature with time resolutions of 10 min and ring to the radiosonde profiles, the RASS and radiosonde 1 h. Taking advantage of the continuous temperature profiles are naturally consistent. However, the allow - monitoring with RASS, we plotted in Fig. 17 the time ance range of the deviation is rather modest (3.6 K); and height distribution of the Brunt Väisälä frequency 2 g ∂T g thus, we investigated the consistency between the two squared, N , which is defined as + , where T T ∂z c measurements. is the virtual temperature observed with RASS, g is the The middle panel in Fig. 15 shows the standard devia- gravitational acceleration, and c is the specific heat tion from each mean profile, which was about 0.6 K for capacity of dry air at a constant pressure. The N results radiosondes and 1.0–1.5 K with RASS. The difference with 10-min resolution in Fig. 17 indicate a layer of between the two profiles is plotted in the right panel in higher N at 4–5 km altitude throughout the campaign Fig. 15. A persistent discrepancy of about 0.9 K was evi- period. Referring to the radiosonde profiles, this stable dent for the entire height range. We suspect this differ - layer appeared near the freezing level. ence (bias) may be attributed to the discrepancy in the We aimed to compare details of the enhancements of height coordinates between the two measurements. The N at 2–6 km altitude between the RASS and simultane- altitude of a radiosonde is determined with GPS above ous radiosonde profiles. Balloon release timings are indi - the MSL, while the height coordinate for EAR is inferred cated in Fig. 17 (top panel). We selected six cases when Fig. 15 Comparison of the EAR–RASS temperature profile averaged over all 10-min resolution results (blue) and the mean of 12 radiosonde results (red) from August 29 to September 3, 2016. Standard deviation of the temperature for RASS and radiosondes during the campaign is plotted in the middle panel. The mean temperature difference is shown in the right panel Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 14 of 20 Fig. 17 Time and height variations of N using the T values in Fig. 14 for the averaging of 10 min (top panel) and 1 h (bottom panel), Fig. 16 Time and height variations of the temperature perturbations respectively. Arrows in the top panel indicate radiosonde launch tim- during the EAR–RASS campaign from August 29 to September 3, ing, where only profiles indicated in black are used for comparison of 2016, where the averaging was conducted for 10 min (top panel) and N with RASS in Fig. 18 1 h (bottom panel), respectively height variations of the zonal (eastward) and meridional (northward) wind velocity observed with the standard the RASS data were available for one hour after the bal- five-beam mode of EAR. A peculiar wind perturbation loon launch as shown in Fig. 18. These radiosondes are was recognized on September 1. Figure 20 shows the also indicated in Table 5. For the three launches on Sep- enlarged plots of wind velocity and temperature on Sep- tember 2, RASS data were also available. But, the layered tember 1 with the 10-min time resolution, which vividly structure of N was not evident, so, we eliminated these exhibited large and rapid variations in both the zonal and cases from the comparison. Between 2 and 6 km alti- meridional wind velocity at 2–12 km altitude in the after- tude, the RASS and radiosonde results in Fig. 18 show noon. The structure of the zonal and meridional winds a reasonable agreement of the overall height structure, was generally systematic. The vertical wind velocity although considerable fluctuations were recognized. indicated a strong downdraft wind below about 10 km, During 09:00–12:00 LT on August 30, the temperature which changed direction to upward above about 10 km. suddenly became colder by about 1–2 K, extending from Figure 21 shows the radar reflectivity results of the micro 4 km to about 10 km. The colder T started at 09:00 LT rain radar (MRR) operating at the EAR site, indicating and continued until noon. However, there is no clear fea- rain clouds at 12:00–15:00 LT, with a maximum intensity ture in the zonal wind in Fig. 19. Precipitation was not at 12:30 LT. recognized during this cold event. Infrared satellite images with the Himawari-8 in Fig. 22 On September 1, the temperature profiles showed indicate that from 09:00 LT until 21:00 LT on September enhanced fluctuations. Figure 19 shows the time and Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 15 of 20 2 2 Fig. 18 Comparison of individual N profiles between RASS and radiosondes. The N with RASS is derived from the mean temperature profile aver - aged for one hour after the radiosonde launch Fig. 19 Time and height variations of the eastward (top) and northward (bottom) wind velocity observed with the standard five-beam method with EAR from August 29 to September 3, 2016 Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 16 of 20 Fig. 20 Enlarged plots of u (top-left), v (top-right), w (bottom-left), and T’ (bottom-right) from 00:00 LT on September 1 to 12:00 LT on September 2, 2016. Averaging time is 10 min Fig. 21 Radar reflectivity observed with MRR at the EAR site from 00:00 LT on September 1 to 12:00 LT on September 2, 2016. Averaging time is 10 min Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 17 of 20 Fig. 22 Himawari satellite images at 09, 13, 17, and 21 LT on September 1, 2016. Black circle indicates the location of EAR 1 developed clouds passed over the EAR site from east to Concluding remarks west, which seemed to produce the wind velocity distur- In this study, we carried out a total of eight campaigns of bances. Using the radiosonde data, we derived the con- EAR–RASS in 2016, aiming to establish a stable tempera- vective available potential energy (CAPE) as an index of ture observation system with RASS. First, we examined atmospheric convective activity. The CAPE at 10:55 LT the Bragg condition of RASS echoes, separating it into −1 on September 1 was as high as 4.4 J kg . Temperature orthogonal and resonance conditions. perturbations were enhanced in the morning of Sep- Regarding the orthogonal condition, we adopted the tember 1 as seen in Fig. 16. However, the peculiar wind 3-D ray tracing of acoustic waves for determining the disturbances occurring during 12:00–23:00 LT, shown appropriate antenna directions for obtaining RASS ech- in Fig. 20, did not coincide with a signal of temperature oes. The 3-D ray tracing worked well when referring to variations. the actual wind velocity profiles observed with EAR. We Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 18 of 20 selected the appropriate antenna beam directions every investigated in a future study. Preliminary analysis of few hours during the campaign. Then, we obtained the these two events showed that EAR–RASS can provide temperature profiles continuously. The range resolu - the temperature profiles together with the three com - tion was 150 m. One cycle of RASS and turbulence echo ponents of wind velocity, which are useful for the stud- measurements lasted 2 min using the standard mode ies of peculiar atmospheric phenomena in the equatorial only, while it lasted 3 min when the additional radial regions. wind measurements were added. The EAR observatory, having many remote sens - Second, we investigated the acoustic sources, including ing and in situ instruments, plays an important role the location of speakers and the sweep frequency range in the investigation of the convective activities associ- of the FM-chirped acoustic signals. We found that the ated with cloud clusters. The EAR observatory is a core speakers located in the center of the EAR antenna were of a growing regional network in the Southeast Asia, most effective, but speakers outside the antenna were which will improve our knowledge of various equatorial also useful for obtaining the RASS echoes in the lower phenomena. altitudes when the wind velocity became large. We applied a spectral fitting for RASS echoes assum - Abbreviations ing a Gaussian distribution. We studied the effects of the EAR: equatorial atmosphere radar; RASS: radio acoustic sounding system; WPR: background winds on the estimation of the true sound wind profiling radar; MST: mesosphere–stratosphere–troposphere; MRR: micro rain radar; CAPE: convective available potential energy; IUGONET: Inter-univer- speed from the apparent sound speed, which contains the sity Upper atmosphere Global Observation NETwork. projection of the background winds onto the radial direc- tion. We found that the accuracy of the RASS tempera- Authors’ contributions IJ conducted the EAR–RASS experiments, including radiosonde launches and ture improved by using direct measurements of the radial MRR, and joined data interpretation. HT designed the acoustic transmitting winds in the same directions as the RASS beams. system and developed the 3-D ray-tracing method. N carried out analysis of After screening unrealistic values, referring to the the EAR–RASS data and participated in the discussions. HH led the data analy- sis of EAR wind and RASS temperature data. H led the EAR–RASS experiment. mean temperature profile obtained by radiosondes, we TT coordinated the EAR–RASS experiments and led the overall data analysis. obtained the temperature profiles for the five beam direc - All authors read and approved the final manuscript. tions. Then, all the available RASS results were projected Authors’ information on the single height coordinate that is used for the stand- The author (HT ) is now at ENEGATE, Co. Ltd., Osaka, Japan. The author ( TT ) ard five-beam mode, where the interpolation was done works at Research Organization of Information and Systems (ROIS), Tokyo, along height within a height interval of up to 600 m. Japan. The author (N) is a researcher from the Center for Atmospheric Science and Technology, National Institute of Aeronautics and Space (LAPAN), Indone- Finally, we constructed the RASS temperature data, sia, studying at Kyoto University, Japan. averaging over the five beams, with time resolutions of 3, 10 min, and 1 h. The RASS temperature with 10-min Author details Center for Atmospheric Science and Technology, National Institute of Aero- resolution was determined at 2–6 km with 50–80% avail- nautics and Space (LAPAN), Bandung, Indonesia. Research Institute for Sus- ability, and up to about 14 km with about 10% availability. tainable Humanosphere (RISH), Kyoto University, Kyoto, Japan. u Th s, we have constructed temperature datasets, which Acknowledgements will be available for the scientific community via the The EAR observatory is operated jointly between the Research Institute for IUGONET system (www.iugonet.org). Sustainable Humanosphere (RISH), Kyoto University, Japan and the Indonesian We launched radiosondes between August 30 and National Institute of Aeronautics and Space (LAPAN). This study is supported by the Asia Research Node (ARN) of RISH, Kyoto University. The authors would September 2, 2016 and compared the temperature pro- like to thank Syafrijon and his colleagues at the EAR site who have helped to files with the RASS results, showing a good consistency make the EAR–RASS campaign a success. We also appreciate the devoted sup- between the profiles. However, we noticed a shift in these port by Yuki Shiono, Soni Aulia Rahayu, Ginaldi Ari Nugroho, and Siti Azizah. This study is partly supported by JSPS KAKENHI Grant Numbers JP15H03724, profiles along altitude probably due to a possible dis - JP17H00852, and 22253006. One of the authors (N) received a scholarship for crepancy in the height coordinate for EAR. The stand - his Ph.D. from the Program of Research and Innovation in Science and Tech- ard deviation from the mean temperature difference was nology (RISET-Pro), Ministry of Research, Technology, and Higher Education (RISTEKDIKTI) of Indonesia. about 0.4 K. In a few cases, RASS measured the tempera- ture up to the tropopause, although the correction of the Competing interests background winds was not sufficient above about 11 km. The authors declare that they have no competing interests. We found a few interesting meteorological distur- Availability of data bances that occurred between August 30 and Septem- The EAR–RASS virtual temperature and EAR wind data were provided by ber 1, 2016. A preliminary report was presented on the RISH and LAPAN. Radiosonde data were provided by LAPAN. The Himawari-8 satellite images are released by the Japan Meteorological Agency with 10-min behavior of the wind velocity and temperature variations time resolution. The hourly Himawari-8 IR1 data also can be found at http:// in association with the rain data and satellite images on weather.is.kochi-u.ac.jp/archive-e.html. September 1. Details of the disturbances will be further Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 19 of 20 Funding Received: 4 September 2017 Accepted: 17 January 2018 This study is partially supported by JSPS KAKENHI Grant Numbers JP15H03724, JP17H00852, 22253006, and LAPAN. Appendix: Relation between the sound speed References and the atmospheric temperature Adachi T (1996) Detailed temperature structure of meteorological distur- WPR detects radio wave scattering due to small vari- bances observed with RASS (radio acoustic sounding system). Ph.D. ations in the refractive index, n, which is a function of Dissertation, Kyoto University Adachi T, Tsuda T, Masuda Y, Takami T, Kato S, Fukao S (1993) Eec ff ts of a ratio the atmospheric density, humidity, and temperature. between acoustic and radar pulse lengths on accuracy of RASS tempera- Changes in the atmospheric density accompanying the ture measurements. Radio Sci 28:571–583 sound waves produce periodic perturbations of n, which Alexander SP, Tsuda T, Furumoto J, Shimomai T, Kozu T, Kawashima M (2006) A statistical overview of tropospheric convection during CPEA campaign. J can be a target for WPR. We estimate the sound speed Meteorol Soc Jpn 84A:57–93 from the Doppler shift of the RASS echo. Then, the Behrendt (2005) A temperature measurements with lidar. In: C. Weitkamp (ed) atmospheric temperature can be determined from the Lidar: range-resolved optical remote sensing of the atmosphere. Springer −1 series in optical sciences, vol 102. Springer-Verlag, New York, pp 273–305 relation that the speed of sound, C (m s ), is propor- Clifford C, Wang T (1977) The range limitation on radar-acoustic sounding sys- tional to the square root of the atmospheric tempera- tem (RASS) due to atmospheric refractive turbulence. IEEE Trans Antenna ture, T (K). C is determined by the characteristics of the Propag. https://doi.org/10.1109/tap.1977.1141574 Emanuel KA (1987) An air–sea interaction-model of intraseasonal oscillations propagation medium, such as its pressure, density, and in the tropics. J Atmos Sci 44:2324–2340 temperature. Under the standard atmospheric condition, Frank WM, Cohen C (1987) Simulation of tropical convective systems, Part I: A −1 C on the ground is about 340 m s , and, as the altitude cumulus parameterization. J Atmos Sci 44:3787–3799 Fukao S (2006) Coupling processes in the equatorial atmosphere (CPEA): a goes higher, C decreases. We briefly introduce the rela - project overview. J Meteorol Soc Jpn 84A:1–18 tion between C and T below. Fukao S, Hashiguchi H, Yamamoto M, Tsuda T, Nakamura T, Yamamoto MK, Assuming an adiabatic condition, we adopt the equa- Sato T, Hagio M, Yabugaki Y (2003) Equatorial atmosphere radar (EAR): system and description and first results. Radio Sci 38(3):1053. https://doi. tion of state of ideal gas and the wave equation of sound. org/10.1029/2002rs002767 Then, C can be expressed in the following equation: Furumoto J, Tsuda T, Iwai S, Kozu T (2006) Continuous humidity monitoring in a tropical region with the equatorial atmosphere radar (EAR). J Atmos Ocean Technol 23:538–551 C = γ T = K T , (4) Marshall JM, Peterson AM, Barnes AA Jr (1972) Combined radar-acoustic sounding system. Appl Opt 11:108–112 where γ is the specific heat ratio, R is the gas constant, Masuda Y (1988) Influence of wind and temperature on the height limit of a radio acoustic sounding system. Radio Sci 23:647–654 and M is the mean molecular weight. Note that K is a Masuda Y, Awaka J, Okamoto K, Tsuda T, Fukao S, Kato S (1990) Echo power constant, determined by M, and K is about 20.047 (=K ) loss with RASS (radio acoustic sounding system) due to defocusing in a dry atmosphere. However, in a moist atmosphere effects by distorted acoustic wave front. Radio Sci 25:975–982 Masuda Y, Awaka J, Nakamura K, Adachi T, Tsuda T (1992) Analysis of the radio below about 10 km in the tropics, K varies depending acoustic sounding system using a chirped acoustic wave. Radio Sci on the humidity. It is difficult, however, to continuously 27:681–691 monitor the humidity during RASS experiments, so we Matuura N, Masuda Y, Inuki H, Kato S, Fukao S, Sato T, Tsuda T (1986) Radio acoustic measurement of temperature profile in the troposphere and substitute K for the dry atmosphere in estimating the lower stratosphere. Nature 323:426–428 temperature, resulting in the determination of the vir- May PT, Strauch RG, Moran KP (1988) The altitude coverage of temperature tual temperature, T , which is slightly higher than T measurements using RASS with wind profiler radars. Geophys Res Lett 15(12):1381–1384. https://doi.org/10.1029/gl015i012p01381 by a few degrees in the lower troposphere below about May PT, Adachi T, Tsuda T, Lataitis RJ (1996) The spatial structure of RASS ech- 8 km in the tropics. T is approximately related to T as oes. J Atmos Ocean Technol 13:1275–1290 follows: Peters G (2000) History of RASS and its use for turbulence measurements. In: IGARSS 2000, Proceedings of the geoscience and remote sensing e symposium, 2000. IEEE T ≈ 1 + 0.61 , v (5) Ratnam MV, Alexander SP, Kozu T, Tsuda T (2009) Characteristics of gravity waves observed with intensive radiosonde campaign during November– December 2005 over Western Sumatera. Earth Planets Space 61(8):983– where m and m are the weights of the water vapor and e d 993. https://doi.org/10.1186/bf03352948 the dry atmosphere, respectively, and this ratio is called Sarma TVC, Rao DN, Furumoto J, Tsuda T (2008) Development of radio acoustic the water vapor mixing ratio. T is commonly used in sounding system (RASS) with Gadanki MST radar—first results. Ann Geophys 26(9):2531–2542 meteorology, which is sometimes useful in investigations Sarma TVC, Kodama Y, Tsuda T (2010) Characteristics of atmospheric waves in of the atmospheric condition, including both sensible the upper troposphere observed with the Gadanki MST Radar—RASS. and latent heat energy. J Atmos Solar Terr Phys 73(2011):1020–1030. https://doi.org/10.1016/j. jastp.2010.08.010 Spano E, Ghebrebrhan O (1996) Pulse coding techniques for ST/MST radar Publisher’s Note systems: a general approach based on a matrix formulation. IEEE Trans Springer Nature remains neutral with regard to jurisdictional claims in pub- Geosci Remote Sens 34:304–316 lished maps and institutional affiliations. Juaeni et al. Earth, Planets and Space (2018) 70:22 Page 20 of 20 Tsuda T, Masuda Y, Inuki H, Takahashi K, Takami T, Sato T, Fukao S, Kato S (1989) Westwater ER (1970) ground-based determination of temperature profiles by High time resolution monitoring of tropospheric temperature with a microwaves. Ph.D. Dissertation, University of Colorado radio acoustic sounding system (RASS). Pure appl Geophys 130:497–507 Wilks DS (2006) Statistical methods in the atmospheric sciences, 2nd edn. Tsuda T, Adachi T, Masuda Y, Fukao S, Kato S (1994) Observations of tropo- Academic Press, New York spheric temperature fluctuations with the MU radar/RASS. J Atmos Zhang D-L, Fritsch JM (1988) Numerical sensitivity experiments on structure, Ocean Technol 11:50–62 evolution and dynamics of two mesoscale convective systems. J Atmos Welsh PT, Santos P, Christopher CG (1999) A study of sea breeze convective Sci 45:261–293 interactions using mesoscale numerical modeling. Natl Weather Dig Montgomery AL 23(3):33–45
Journal
Earth, Planets and Space – Springer Journals
Published: Feb 7, 2018