Reconstruction and Nowcasting of Rainfall Field by Oblique Earth-Space Links Network: Preliminary Results from Numerical Simulation

Abstract

High-precision rainfall field reconstruction and nowcasting play an important role in many aspects of social life. In recent years, the rain-induced signal attenuation of oblique earth-space links (OELs) has been presented to monitor regional rainfall. In this paper, we set up the first OEL in Nanjing, China, for the estimation of rain intensity. A year of observations from this link are also compared with the measurements from laser disdrometer OTT-Parsivel (OTT), between which the correlation is 0.86 and the determination coefficient is 0.73. Then, the simulation experiment is carried out: an OELs network is built, and the Kriging interpolation algorithm is employed to perform rainfall field reconstruction. The rainfall fields of plum rain season from 2016 to 2019 have been reconstructed by this network, which shows a good agreement with satellite remote sensing data. The resulting root-mean-square errors are lower than 3.46 mm/h and spatial correlations are higher than 0.80. Finally, we have achieved the nowcasting of rainfall field based on a machine-learning approach, especially deep learning. It can be seen from experiment results that the motion of rain cell and the position of peak rain intensity are predicted successfully, which is of great significant for taking concerted actions in case of emergency. Our experiment demonstrates that the densely distributed OELs are expected to become a futuristic rainfall monitoring system complementing existing weather radar and rain gauge observation networks.

A Global-Scale Investigation of Stochastic Similarities in Marginal Distribution and Dependence Structure of Key Hydrological-Cycle Processes

“…An overall conclusion from this study is that the Hurst parameter is estimated significantly above 0.5 for all processes (Table 2 and Figures 12 and 13), indicating that the observed uncertainty and climatic variability in the hydrological cycle may be caused by the presence of the long-term persistent (LTP) behavior (see also discussion in [143,144]). This is consistent with the universality of LTP behavior as confirmed in various other studies (than the ones mentioned in Section 2.1) and statistical attributes in literature (for a review see [18,[145][146][147]), such as in global-scale key hydrometeorological processes [3,18], trend analysis [148] and extremes [149,150], precipitation [151][152][153][154][155], streamflow [155][156][157], turbulent jets [158,159] and grid turbulence [160,161].…”

Statistical Study of Rainfall Inversion Using the Earth-Space Link at the Ku Band: Optimization and Validation for 1 Year of Data

“…4 and Table II. The analysis indicates that the local atmospheric 0 ℃-layer height is not a fixed value throughout a year and has obvious seasonal variation characteristics [24]. Therefore, in the statistical analysis of the annual rainfall obtained using the ESL, the fixed statistical value of h0 is not in line with the actual local situation.…”

“…When rainfall occurs in the atmosphere, the microwave signals transmitted by satellites reach the satellite antenna on the ground through the ESL and are transmitted to the receiver for signal processing. When we express the transmitting power of the satellite with Pt, the receiving power Pr of the ground receiver can be expressed as [24] ( ) ( ) ( )…”

“…When there is no rain in the atmosphere, the SNRno-rain value received by the ESL can be used as the attenuation baseline SNRrefer; that is, the SNR of factors other than rainfall [24].…”

“…In previous studies, h0 mostly uses statistical fixed constants. In ITU-R recommendation P.839 [24], the value of the atmospheric 0 ℃-Layer height h0 in the Nanjing area can be taken as 4.67 km. As shown in Fig.…”