Seasonal and Diurnal Variations of Vertical Profile of Precipitation over Indonesian Maritime Continent

This chapter presents variabilities in the vertical structure of precipitation over the Indonesian maritime continent (IMC), which were inferred from the gradients of the radar reflectivity (dBZ) below the freezing level and were gathered from the latest 2A25 TRMM–Precipitation Radar product over a 17-year time span (1998–2014). In general, the downward increasing (DI) pattern of dBZ toward the surface is more dominant than the downward decreasing (DD) pattern, which has a ratio of 1.3. The DI is frequently observed over the ocean, and the higher prevailing rain top heights over land are associated with DD, in most cases. Shallow convective rains have the largest ratio of DI to DD (>4), followed by deep convective rains. The largest ratio is observed during December–January–February (DJF) when wetter conditions are dominant over the IMC, which is a favorable condition for raindrop growth. The stratiform rains show a dominant DD in which the ratio of DD to DI is greater than 1.6 for each season. The spatial distribution of the stratiform gradient is more complex than that of convective rain and does not show a robust land-ocean contrast. The diurnal variation in the reflectivity gradient for stratiform rain is less pronounced. With convective rain, DD is more dominant in the afternoon and evening over a large island, indicates a decrease in the raindrop concentration due to the evaporation and updraft associated with the intense convection

Atmospheric Kelvin-Helmholtz b illows captured by the MU radar, lidars and a fish-eye camera

On June 11, 2015, a train of large-amplitude Kelvin–Helmholtz (KH) billows was monitored by the Middle and Upper Atmosphere (MU) radar (Shigaraki MU Observatory, Japan) at the altitude of ~ 6.5 km. Four to five KH billows in formation and decay stages were observed for about 20 min at the height of a strong speed shear (> ~ 30 m s⁻¹km⁻¹), just a few hundred meters above a mid-level cloud base. The turbulent billows had a spacing of about 3.5–4.0 km (3.71 km in average) and an aspect ratio (depth/spacing) of ~ 0.3. The turbulence kinetic energy dissipation rate estimated was of the order of 10–50 mWkg⁻¹, corresponding to moderate turbulence according to ICAO (2010) classification. By chance, an upward-looking fish-eye camera producing pictures once every minute detected smooth protuberances at the cloud base caused by the KH billows so that comparisons of their characteristics could be made for the first time between the radar observations and the pictures. The main characteristics of the KH wave (horizontal wavelength, phase front direction and phase speed) obtained from the analysis of the pictures were fully consistent with those found from radar data. The pictures indicated that the billows were advected by the wind observed at the height of the critical level. They also revealed a very small transverse extent (about twice the horizontal spacing) suggesting that the large-amplitude KH billows were generated by a very localized source. Micro-pulse lidar and Raman–Rayleigh–Mie lidar data also collected during the event permitted us to confirm some of the characteristics of the billows

Retrieval of Vertical Structure of Raindrop Size Distribution from Equatorial Atmosphere Radar and Boundary Layer Radar

This work develops an algorithm to retrieve the vertical structure of the raindrop size distribution (DSD) of rain from simultaneous observations of 47 MHz Equatorial Atmosphere Radar (EAR) and 1.3 GHz Boundary Layer Radar (BLR) at Koto Tabang, West Sumatra, Indonesia (0.20°S, 100.32°E, 865 m above sea level). EAR is sensitive to the detection of turbulence, and BLR is susceptible to identifying precipitation echo. The EAR Doppler spectrum broadening effects due to turbulence and finite radar beam width were reduced using the convolution process. The Gaussian function was used to model the turbulence Doppler spectrum. A non-linear least-squares fitting method was applied to retrieve DSD parameters. Subsequently, the equations to estimate DSD using this dual-frequency algorithm assume the gamma DSD model to retrieve the distribution from the Doppler spectrum of precipitation echo. The precipitation events on April 23, 2004 on the Coupling Processes in the Equatorial Atmosphere (CPEA-I) project have been analyzed. Results show that the precipitation spectrum obtained using the dual-frequency method is higher, more precise, and well-fitted than the single-frequency method, meaning the dual-frequency method has great potential to be used in observing the microphysical process and remote sensing application analysis of DSD in Indonesia, particularly at Koto Tabang. The analyses show various microphysical processes that occur in the rain, such as coalescence, evaporation, break-up, and condensation. Furthermore, for the purpose of easier remote sensing application analysis of profile DSD characteristics, we use a DSD ΔΖMP parameter. ΔΖMP is a rain rate insensitive DSD parameter representing mean drop size. The trend of ΔZMP is not totally uniform with regards to rain rate and reflectivity factors, with ΔZMP higher in the first half of the event and becoming lower toward the end. This suggests that we have to use different Z-R relations within the event. Doi: 10.28991/ESJ-2022-06-03-02 Full Text: PD

Estimation of Raindrop Size Distribution Parameters Using Lightning Data over West Sumatra

In situ observations of raindrop size distributions (DSDs) are still limited, especially in the tropics. Therefore, this study develops an alternative method to calculate DSD parameters by utilizing lightning data from the World-Wide Lightning Location Network (WWLLN) observation. DSD data was obtained from Parsivel's observations in the equatorial regions of Indonesia, i.e., Kototabang (100.32◦E, 0.20◦S, 865 m above mean sea level/ASL), Padang (100.46°E, 0.915°S, 200 m ASL), and Sicincin (100.30°E, 0.546°S, 134 m ASL). A gamma distribution parameterized the DSD. Three analysis domains were examined, with a grid of 0.1° x 0.1°, 0.5° x 0.5°, and 1° x 1°.  We examined the possibility to calculate the near-instantaneous DSD parameter, so three short time intervals, namely, one, five and ten minutes, were used. The results showed that the number of lightning strokes does not adequately correlate with DSD parameters. This is observed in all time intervals and analysis domains. Thus, the use of lightning data to calculate DSD parameters is not possible for short time interval of DSD (near instantaneous DSD). However, lightning data can estimate the average DSD parameters for an average time of more than one hour, as recommended by previous studies

Observations of Coherent Turbulence Structures in the Near-Neutral Atmospheric Boundary Layer

Turbulence structures of high Reynolds number flow in the near-neutral atmospheric boundary layer (ABL) are investigated based on observations at Shionomisaki and Shigaraki, Japan. A Doppler sodar measured the vertical profiles of winds in the ABL. Using the integral wavelet transform for the time series of surface wind data, the pattern of a descending high-speed structure with large vertical extent (from the surface to more than 200-m level) is depicted from the Doppler sodar data. Essentially this structure is a specific type of coherent structure that has been previously shown in experiments on turbulent boundary-layer flows. Large-scale high-speed structures in the ABL are extracted using a long time scale (240 s) for the wavelet transform. The non-dimensional interval of time between structures is evaluated as 3.0–6.2 in most cases. These structures make a large contribution to downward momentum transfer in the surface layer. Quadrant analyses of the turbulent motion measured by the sonic anemometer (20-m height) suggest that the sweep motion (high-speed downward motion) plays a substantial role in the downward momentum transfer. In general, the contribution of sweep motions to the momentum flux is nearly equal to that of ejection motions (low-speed upward motions). This contribution of sweep motions is related to the large-scale high-speed structures

PERBANDINGAN KARAKTERISTIK DISTRIBUSI UKURAN BUTIRAN HUJAN DI PADANG DAN DI KOTOTABANG

ABSTRAKDistribusi ukuran butiran hujan atau raindrop size distribution (RDSD) di Padangdan di Kototabang, Sumatera Barat,  telah dibandingkan.  Perbandingan dilakukan melalui pengamatan particle size velocity (Parsivel) selama Maret 2014 – Mei 2015 untuk Padang dan Januari 2014 – Januari 2015 untuk Kototabang.  RDSD dimodelkan dengan distribusi gamma dan parameternya didapatkan menggunakan metode momen.  Terlihat bahwa intensitas curah hujan yang tinggi lebih banyak di Padang daripada di Kototabang.  Selain itu, butiran hujan yang berukuran besar di Padang lebih banyak daripada di Kototabang.  Banyaknya butiran hujan yang berukuran besar ini berdampak pada nilai radar reflectivity (Z) di Padang yang sedikit lebih besar dari Kototabang untuk intensitas curah hujan yang sama.  Karena itu nilai koefisien A yang ada dalam persamaan Z-R di Padang juga sedikit lebih besar dari Kototabang.  Sedikitnya perbedaan karakteristik RDSD antara Padang dan Kototabang, disebabkan oleh hujan yang terjadi  di Padang dan di Kototabang kemungkinan berasal dari awan konvektif yang sama, yaitu awan dari Samudra Hindia.  Awan tersebut mengalami proses yang berbeda di Kototabangdisebabkan oleh adanya pegunungan di sekitar daerah ini sehingga menimbulkan hujan dengan RDSD yang agak berbeda dengan di Padang. Kata kunci: raindrop size distribution, metode momen, Parsivel, Padang, KototabangAbstractCharacteristics of raindrop size distribution (RDSD) in Padang and Kototabang have been compared through particle size distribution (Parsivel) observation during March 2014 – May 2015 for Padang and January 2014 – January 2015 for Kototabang.  The RDSD was parameterized by the modified gamma distribution and its parameter was calculated by the moment method.  It was found that the occurrence frequency of heavy rain in Padang is higher than Kototabang.  Moreover, rains in Padang have more large-sized drop than Kototabang.  As consequence, the radar reflectivity factor (Z) in Padang was slightly larger than Kotabang for the same rainfall rate.  A small difference in the RDSD between Padang and Kototabang may indicate that the precipitating cloud of the two regions is the same, i.e., same origin (Indian Ocean).  However, the cloud will undergo different process when it reaches Sumatera.  At Kototabang, it will be influenced by the mountain around this region which can cause orographic precipitation.  The orographic precipitation is characterized by the large concentration of small size drops as found at Kototabang in this study.Keywords: raindrop size distribution, moment method, Parsivel, Padang, Kototaban

Turbulence Kinetic Energy Dissipation Rates Estimated from Concurrent UAV and MU Radar Measurement s

We tested models commonly used for estimating turbulence kinetic energy dissipation rates ε from very high frequency stratosphere–troposphere radar data. These models relate the root-mean-square value σ of radial velocity fluctuations assessed from radar Doppler spectra to ε. For this purpose, we used data collected from the middle and upper atmosphere (MU) radar during the Shigaraki unmanned aerial vehicle (UAV)—radar experiment campaigns carried out at the Shigaraki MU Observatory, Japan, in June 2016 and 2017. On these occasions, UAVs equipped with fast-response and low-noise Pitot tube sensors for turbulence measurements were operated in the immediate vicinity of the MU radar. Radar-derived dissipation rates ε estimated from the various models at a range resolution of 150 m from the altitude of 1.345 km up to the altitude of ~ 4.0 km, a (half width half power) beam aperture of 1.32° and a time resolution of 24.6 s, were compared to dissipation rates (εU) directly obtained from relative wind speed spectra inferred from UAV measurements. Firstly, statistical analysis results revealed a very close relationship between enhancements of σ and εU for εU≳10⁻⁵m²s⁻³, , indicating that both instruments detected the same turbulent events with εU above this threshold. Secondly, εU was found to be statistically proportional to σ³, whereas a σ² than the longitudinal and transverse dimensions of the radar sampling volume. The σ³ dependence was found even after excluding convectively generated turbulence in the planetary boundary layer and below clouds. The best agreement between εU and radar-derived ε was obtained with the simple formulation based on dimensional analysis ε=σ³ /Lc where LC ≈ 50–70 m. This empirical expression constitutes a simple way to estimate dissipation rates in the lower troposphere from MU radar data whatever the sources of turbulence be, in clear air or cloudy conditions, consistent with UAV estimates

Differences in Mechanisms of Orographic Rainfall over West Sumatra (Case Study: 10 April and 23 April 2004)

Two different mechanisms of orographic rainfall enhancement  in West Sumatra were investigated utilizing observed data during the Coupling Processes in the Equatorial Atmosphere (CPEA)-I campaign. The variation of the atmospheric conditions during the campaign was shown by rainfall, surface wind, humidity, and stability index. An X-band Doppler radar captured the atmospheric conditions related to the enhancement of orographic rainfall mechanisms. The dry and less stable atmospheric conditions resulted in the convective type of rainfall. In contrast, the humid and stable atmospheric conditions brought the large-scale rainfall in the mountainous region where the events took place coincided with the inactive and active MJO phases.

Humidity Dependence of Charge Transport through DNA Revealed by Silicon-Based Nanotweezers Manipulation

AbstractThe study of the electrical properties of DNA has aroused increasing interest since the last decade. So far, controversial arguments have been put forward to explain the electrical charge transport through DNA. Our experiments on DNA bundles manipulated with silicon-based actuated tweezers demonstrate undoubtedly that humidity is the main factor affecting the electrical conduction in DNA. We explain the quasi-Ohmic behavior of DNA and the exponential dependence of its conductivity with relative humidity from the adsorption of water on the DNA backbone. We propose a quantitative model that is consistent with previous studies on DNA and other materials, like porous silicon, subjected to different humidity conditions