In 2010–2012 spring, atmospheric duct observation experiments were performed throughout three open cruises over the South China Sea and the Tropical Eastern Indian Ocean. The data used for ducting analysis were measured by high resolution balloon-borne GPS radiosondes. Through data quality control and diagnostic analysis, the probability of ducting occurrence and characteristic quantities of the three typical ducts were given. The total percentage occurrence of evaporation duct, surface-based duct and elevated duct were 75.3%, 5% and 43.7%, respectively. The mean evaporation duct height was 15.3 m. The mean values of duct height, thickness and magnitude were 84.1 m, 14.9 m and 10 M-units for surfaced-based duct, and 1003.6 m, 62.2 m and 7.9 M-units for elevated duct. These preliminary statistical results can serve as a basis for future comprehensive and comparative studies of atmospheric duct for the research region.

Atmospheric duct is an anomalous atmospheric structure that affects electromagnetic wave propagation. The important characteristics of the atmospheric ducts include duct probability, duct height, duct strength, and the thickness of the trapping layer. To investigate the statistical characteristics of atmospheric ducts over the American mainland, four stations in different regions are chosen. The seasonal and diurnal variation of the characteristics of ducts is presented. The mechanism of the seasonal and variation of ducts is revealed and the relationship between the characteristics is researched. The duct strength correlates positively with the thickness of the trapping layer, and the duct height correlates with them negatively. Moreover, the duct relationship with precipitation over different stations is clarified. It is found that the precipitation correlates positively with the probability of ducts caused by the vertical moisture gradient, and the relation is negative when the ducts are caused by temperature inversion. This work is of great value to the statistical characteristics of atmospheric ducts over the American mainland.

Retrieving atmospheric refractivity profiles from the sea surface backscattered radar clutter is known as the refractivity-from-clutter (RFC) technique. Because the relationship between refractivity and radar sea clutter is clearly nonlinear and ill posed, it is difficult to get analytical solutions according to current theories. Previous works treat this problem as a model parameter estimation issue and some optimization algorithms are selected to get approximate solutions. Two main factors that limit the accuracy of the estimation are that 1) the refractive environments are described by using some idealized refractivity parameter models that cannot describe the exact information of the refractivity profile, and 2) accurate modeling of the sea surface radar cross section (RCS) is very difficult. Rather than estimating a few model parameters, this paper puts forward possibilities of using the variational adjoint approach to jointly retrieve the every-height refractivity values and sea surface RCS using radar clutter data. The derivation of the adjoint model is accomplished by an analytical transformation of the parabolic equation (PE) in the continuous domain. Numerical simulations including range-independent and range-dependent RCS cases are presented to demonstrate the ability of this method for RFC estimations. Making use of the refractivity retrievals, propagation loss predictions are also presented.

The evaporation duct is a special atmospheric stratification that significantly influences the propagation path of electromagnetic waves at sea, and hence, it is crucial for the stability of the radio communication systems. Affected by physical parameters that are not universal, traditional evaporation duct theoretical models often have limited accuracy and poor generalization ability, e.g., the remote sensing method is limited by the inversion algorithm. The accuracy, generalization ability and scientific interpretability of the existing pure data-driven evaporation duct height prediction models still need to be improved. To address these issues, in this paper, we use the voyage observation data and propose the physically constrained LightGBM evaporation duct height prediction model (LGB-PHY). The proposed model integrates the Babin–Young–Carton (BYC) physical model into a custom loss function. Compared with the eXtreme Gradient Boosting (XGB) model, the LGB-PHY based on a 5-day voyage data set of the South China Sea provides significant improvement where the RMSE index is reduced by 68%, while the SCC index is improved by 6.5%. We further carried out a cross-comparison experiment of regional generalization and show that in the sea area with high latitude and strong adaptability of the BYC model, the LGB-PHY model has a stronger regional generalization performance than that of the XGB model.

Six-year high-precision surface bulk measurements are used to analyze the evaporation duct height (EDH) distributions over Yongxing Island. Yearly statistics of the EDH computed by the PJ model and the NPS model are compared with an existed historical climatology results used in the AREPS tool. The EDH occurrence frequency distributions (OFD) of the PJ and NPS estimations in different atmospheric regimes are also presented. The findings are outlined as follows: (1) The mean EDHs for the PJ model and the NPS model are 14.3 m and 11.9 m, respectively. (2) The yearly EDH distributions of the PJ estimations are similar to, but with approximately 2 m lower than that of the AREPS climatology. However, the distributions of the NPS estimations are different, with the highest EDHs occurred in Apr., May, and Jun. of an average height of 14.2 m, compared to that of the PJ estimations occurred in Oct., Nov., and Dec. of an average height of 16.3 m. (3) For all the partitioned atmospheric regimes, there exists a shifted threshold for the OFD comparisons. Above the threshold, the OFDs of the PJ estimations are higher than that of the NPS estimations, and an opposite situation arises below the threshold.