Jin Teong Ong

Performance of Site Diversity Investigated Through RADAR Derived Results

Site diversity is an effective rain attenuation mitigation technique, especially in the tropical region with high rainfall rate. The impact of different factors such as site separation distance, frequency, elevation angle, polarization angle, baseline orientation and wind direction is assessed. Results are compared to those reported in existing literature and also compared to the commonly used ITU-R site diversity prediction models. The effect of the wind direction on site diversity is also presented. It can be observed that diversity gain is highly dependent on the site separation distance, elevation angle and wind direction but independent of the frequency, baseline angle and polarization angle of the signal. This study is useful for the implementation of site diversity as a rain attenuation mitigation technique.

Truncated Gamma Drop Size Distribution Models for Rain Attenuation in Singapore

A model that is less sensitive to errors in the extreme small and large drop diameters, the gamma model with central moments (3, 4 and 6), is proposed to model the rain drop size distribution of Singapore. This is because, the rain rate estimated using measured drop size distribution shows that the contributions of lower drop diameters are small as compared to the central drop diameters. This is expected since the sensitivity of the Joss distrometer degrades for small drop diameters. The lower drop diameters are therefore removed from the drop size data and the gamma model is redesigned for its moments. The effects of the removal of a particular rain drop size diameter on the specific rain attenuation (in dB) and the slant-path rain attenuation calculations with forward scattering coefficients for vertical polarization are analyzed at Ku-band, Ka-band and Q-band frequencies. It is concluded that the sensitivity of the Joss distrometer although affects the rain rate estimation at low rain rates, does not affect the slant path rain attenuation on microwave links. Therefore, the small drop diameters can be ignored completely for slant path rain attenuation calculations in the tropical region of Singapore.

Raindrop size distribution using method of moments for terrestrial and satellite communication applications in Singapore

As communication services using higher frequencies are growing rapidly in the tropics, there is an increasing need for a finer model to predict the attenuation due to rain. The raindrop size distribution (DSD) is one of the major sources of error in any prediction model, mainly because of its variability in both space and time. The DSD parameters are computed from distrometer data that are classified into stratiform and convective types using S-band radar data. The method of moments is employed to estimate the parameters of lognormal DSD. The modeled DSD parameters are optimized by examining the root mean square (RMS) error and the average probability ratio (APR) in estimation of the rain rate, rain attenuation, and radar reflectivity factor simultaneously. The proposed model gives maximum (close to unity) APR and minimum RMS error when compared to any other set of DSD parameters.

Two-Parameter Gamma Drop Size Distribution Models for Singapore

Gamma model is fitted using the second, fourth, and sixth moments to model the rain drop size distribution (DSD) of Singapore. As the Joss distrometer measures the number of rain drops between the drop diameters from 0.3 to 5 mm, the truncated moment fitting between these drop diameter ranges is also used for modeling the DSD. Gamma DSD requires three-parameter estimation:N0, the intercept parameter; μ, the shape parameter; and Λ, the slope parameter. The aim of this paper is to find a suitable fixed μ and derive an appropriate μ-Λ relation for the tropical region in order to form a two-parameter gamma model. To find an appropriate μ value, observed DSDs are fitted with different μ values to estimate the rain rates, which are assessed by rain rate observations of the distrometer. Shape-slope relationships are fitted for different categories according to the rain rate and the number of drops. The derived μ-Λ relationships for the Singapore region are compared to the published results from two other regions, and the analysis is presented. Two-parameter gamma models are compared by retrieving the rain rate using the polarimetric radar variables. The effect of truncation on rain rate retrieval is also studied, and the use of the μ-Λ relationship for rain retrieval is recommended for the tropical region. The μ-Λ relation using the truncated moment method for the rain category R ≥ 5 mm/hr and rain counts ≥ 1000 drops retrieves the rain rates well compared to other μ-Λ relations.

Comparison of S-Band Radar Attenuation Prediction With Beacon Measurements

A comparative analysis of the rain attenuation evaluated from beacon measurements and from a single polarization S-band Radar is performed. The beacon measurements are obtained for two slant satellite paths with different elevation angles in the Ku- and Ka-band. The single polarization S-band Radar reflectivity data is used to predict the attenuation along the satellite propagation paths. This is done by first converting the reflectivity into rain rate using the Z-R relations suitable for the tropical region and, afterwards, by evaluating the slant path attenuation through the integration of the specific rain attenuation derived from the point rainfall rate. An empirical calibration factor for the Radar reflectivity is provided. A comparison of the rain fade suffered from the two satellite paths is presented both on event basis and in terms of cumulative distribution functions. The empirical calibration factor and a single Z-R relation suitable for the tropical region are used for rain attenuation evaluation from single polarization Radar data.

Rain Attenuation Prediction Model for Satellite Communications in Tropical Regions

This paper proposes a model for predicting rain attenuation in the tropical region. Slant path rain attenuation measurements were carried out in Singapore by analyzing the beacon signals from two satellites, namely WINDS and GE23, operating at frequencies of 18.9 and 12.75 GHz, respectively. Rainfall rates at the location of the beacon receivers were recorded. The cumulative distributions of the rainfall rate and the corresponding rain attenuation are presented and analyzed. It is found that the cumulative distribution of the measured rainfall rate is close to that predicted by the ITU-R model. Measurement data from a total of nine countries are compared with four existing rain attenuation prediction models, namely the Yamada, DAH, Karasawa, and Ramachandran models. Results show that although three of these models have relatively good prediction capability for the tropical region, they could be improved. Therefore, in this paper, a slant path rain attenuation model suitable for the tropical region is proposed. This is done by using the complementary cumulative distributions of rain attenuation for satellite links measured in Singapore and five other tropical countries. The proposed model is found to outperform exisitng models.

The role of particular rain drop size on rain attenuation at 11 GHz

This paper presents the specific attenuation (gamma) at 11 GHz based on measured drop size distribution (DSD). The influence of particular rain drop sizes (diameters) is presented with the conclusion that the drop diameters from 0.771 mm to 5.3 mm are important for DSD and specific rain attenuation (gamma) calculations. DSD for different rain rates are plotted using lognormal model with maximum likelihood estimators. The discrepancy between the measured and modeled values is found to be minimal even though rain drops of diameter less than 0.771 mm are excluded. Over these diameter ranges, the model fits very well to the measured data. The components of specific attenuation at 11 GHz due to individual drop diameters are calculated and drop diameters below 0.771 mm are found to have insignificant contribution to the specific attenuation.

Water Vapor Pressure Model for Cloud Vertical Structure Detection in Tropical Region

A new method using water vapor pressure (WVP) from a radiosonde profile to determine the cloud vertical structure for the tropical region is proposed in this paper. This includes both the cloud base height and the cloud occurrences at different levels in the atmosphere. Our study shows that the presence of clouds depends on the following criterion: the measured WVP is larger than the critical WVP at the same level. The applicable level is found to be within the range of 300-12 000 m. The estimated cloud vertical structure using the proposed method is compared with the Salonen and Uppala (SU) model, the ceilometer data, and two kinds of meteorological observation data, namely, SYNOP and METAR. The proposed model shows a higher accuracy level of prediction of the cloud vertical structure as compared with the existing SU model.

Cloud attenuation on Ka-band satellite link in the tropical region: Preliminary results and analysis

In this paper, preliminary results and analysis of cloud attenuation on a Ka-band satellite propagation link in tropical island of Singapore are reported. The received signal by a ground-based beacon receiver at 18.9 GHz was processed with a sliding window technique to minimize the system and scintillation effects. The results show that the Ka-band cloud attenuation is highly correlated with the observed solar radiation.

Detection of cloud vertical structure using water vapor pressure in tropical region

A new method is proposed in this paper to determine the cloud vertical structure using water vapor pressure estimated from radiosonde profile. The presence of a cloud depends on the following criteria: the measured water vapor pressure being larger than the critical water vapor pressure at the same level. The estimated results of cloud vertical structures using the proposed method are compared with the Salonen and Uppala model and ceilometer (CL31) data. Results show good agreement between the proposed model, the existing model and the measured data.