The impact of spatial-temporal averaging on the dynamic-statistical properties of rain fields

Guangguang Yang; David Ndzi; Boris Grimont; Kevin Paulson; Misha Filip; Abdul-Hadi Al-Hassani

doi:10.1109/TAP.2019.2930137

The impact of spatial-temporal averaging on the dynamic-statistical properties of rain fields

Guangguang Yang, David Ndzi, Boris Grimont, Kevin Paulson, Misha Filip, Abdul-Hadi Al-Hassani

Faculty of Technology

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Abstract

Knowledge of the spatial-temporal variation of rain fields is required for the planning and optimization of wide area high frequency terrestrial and satellite communication networks. This paper presents data and a method for characterizing multi-resolutions statistical/dynamic parameters describing the spatial-temporal variation of rain fields across ocean climate in North-Western Europe. The data is derived from the NIMROD network of rain radars. The characterizing parameters include: (i) statistical distribution of point one-minute rainfall rates, (ii) spatial and temporal correlation function of rainfall rate and, (iii) the probability of rain/no-rain. The main contributions of this paper are the assessment of the impact of varying spatial and temporal integration lengths on these parameters, their dependencies on the integration volumes and area sizes, and the model for both temporal and spatial correlation parameters.

Original language	English
Pages (from-to)	7505-7517
Number of pages	13
Journal	IEEE Transactions on Antennas and Propagation
Volume	67
Issue number	12
Early online date	29 Jul 2019
DOIs	https://doi.org/10.1109/TAP.2019.2930137
Publication status	Published - 1 Dec 2019

Keywords

RCUK
NERC

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10.1109/TAP.2019.2930137

08779588Final published version, 4.85 MBLicence: CC BY

https://ieeexplore.ieee.org/document/8779588/

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AU - Yang, Guangguang

AU - Ndzi, David

AU - Grimont, Boris

AU - Paulson, Kevin

AU - Filip, Misha

AU - Al-Hassani, Abdul-Hadi

PY - 2019/12/1

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N2 - Knowledge of the spatial-temporal variation of rain fields is required for the planning and optimization of wide area high frequency terrestrial and satellite communication networks. This paper presents data and a method for characterizing multi-resolutions statistical/dynamic parameters describing the spatial-temporal variation of rain fields across ocean climate in North-Western Europe. The data is derived from the NIMROD network of rain radars. The characterizing parameters include: (i) statistical distribution of point one-minute rainfall rates, (ii) spatial and temporal correlation function of rainfall rate and, (iii) the probability of rain/no-rain. The main contributions of this paper are the assessment of the impact of varying spatial and temporal integration lengths on these parameters, their dependencies on the integration volumes and area sizes, and the model for both temporal and spatial correlation parameters.

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The impact of spatial-temporal averaging on the dynamic-statistical properties of rain fields

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