Rainfall Rate Field Space-Time Interpolation Technique for North West Europe

Abstract

The ability to predict rain characteristics at small space-time scales is important, particularly in the planning, design, and deployment of wireless networks operating at frequencies above 10 GHz. For wide area networks, high space and time resolution rainfall data are often not available, and the cost of such measurements is prohibitive. This paper thus presents a new approach to address this problem using rain radar measurements to obtain rain estimates at finer resolutions than that available from the original measured data. This paper proposes three innovative methodologies: 1) the approach is not directly applied to measured rainfall rate data but focuses on the parameters of fitted lognormal distribution parameters and/or computed rain characteristics for each location; 2) to facilitate the application in wireless communication networks operating above 10 GHz, a set of databases and contour maps of rain parameters spanning North West Europe have been created. These conveniently and efficiently provide rain parameters for any location within the area under study; and 3) the proposed 3D space-time interpolation approach can extrapolate rain parameters at space-time resolutions that are shorter than those found in NIMROD radar databases. The results show that the approach presented in this paper can be used to provide {1 km, 5 mins} space-time rain rate resolution from {5 km, 15 mins} data for the whole North West Europe with error percentages of less than 4%. This is far superior to estimates provided by the International Telecommunication Union recommended model.

Space-Time Modeling of Rainfall Rate for Satellite Networks

“…To reduce computation time, the authors have created databases for users to easily obtain the rain characteristic parameter values using Eq. (19) and (20) [33] to convert the coordinates into longitude and latitude values at location of interest; z (longitude) = 0.0658y − 19.8364 (19) z (latitude) = −0.0409y + 59.430 (20) where y denotes either row or column number of the NIM-ROD data grid and z is the corresponding coordinate value in either latitude or longitude. R 0.01 has been analyzed over the whole of the British Isles using the downscaled data from the proposed model and the error percentages (E) between the model estimates and values calculated from UK measured data is calculated using…”

“…This is because in [32] Bell has demonstrated that a reasonable lognormal distribution of rain fields can be simulated provided systematic knowledge of the key rain characteristics are known. Therefore, in [33], the authors have proposed a new space-time interpolation approach that can interpolate the key rain characteristics to finer scales of the order of seconds, in time, and meters, in space, with high accuracy.…”

Deep Spatial Interpolation of Rain Field for U.K. Satellite Networks

“…For example, Luini and Capsoni [13] investigated the effect of space and/or time integration on the spatial correlation functions of rain. Also, the authors' previous work proposed a new interpolation approach with a comprehensive study of four key rain characteristics using the averaging theory as well [14]. It provides a wide range of space and/or time resolution rain field simulations for Northwest Europe with high levels of accuracy.…”