Abstract

<p>Accurate, global rainfall estimates are crucial for many fields, e.g. agriculture or disaster management. While developed countries typically enjoy a dense network of rain gauges and radar, in many less developed areas across the globe, precipitation measurement networks are sparse. To obtain rainfall data for these regions, opportunistic sensing techniques are especially valuable: the use of unconventional sources to extract valuable data that can allow us to estimate precipitation. One of the more prominent data sources is the use of Commercial Microwave Links –CMLs– to measure rainfall, by making use of the signal attenuation between cell phone towers. This method of estimating rainfall has been mostly tested and applied in developed countries that already have reasonable coverage of conventional precipitation measurements. However, the strongest benefits are to be gained in developing regions lacking such measurement networks, where CML data can make a big difference. Only few studies address this, generally using relatively small datasets.</p><p>This research focuses on tropical CML rainfall estimation in Nigeria. Nigeria has a dense network of CMLs and relatively few official measurement stations, making it an interesting area to study the effectiveness of CML precipitation measurements. Our dataset spans 4 regions within Nigeria, from the coast to inland, with several large cities (Lagos; Ibadan) as well as areas with less dense CML networks to investigate the influence. We employ the open-source R package RAINLINK to obtain 15-min rainfall maps based on data from several thousand CMLs during the rainy season. We optimise the most important RAINLINK parameters by comparing to rain gauge data, considering local network and environmental conditions. In addition, disdrometer data from Nigeria (or similar climates) are used to compute the values of the physically-based coefficients relating specific attenuation to rainfall rate.</p><p> </p>

Highlights

  • OSA1.3 : Meteorological observations from GNSS and other space-based geodetic observing techniques OSA1.7: The Weather Research and Forecasting Model (WRF): development, research and applications

  • OSA3.5: MEDiterranean Services Chain based On climate PrEdictions (MEDSCOPE)

  • UP2.1 : Cities and urban areas in the earth- OSA3.1: Climate monitoring: data rescue, atmosphere system management, quality and homogenization 14:00-15:30

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Introduction

OSA1.3 : Meteorological observations from GNSS and other space-based geodetic observing techniques OSA1.7: The Weather Research and Forecasting Model (WRF): development, research and applications. EMS Annual Meeting Virtual | 3 - 10 September 2021 Strategic Lecture on Europe and droughts: Hydrometeorological processes, forecasting and preparedness Serving society – furthering science – developing applications: Meet our awardees ES2.1 - continued until 11:45 from 11:45: ES2.3: Communication of science ES2.2: Dealing with Uncertainties

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