Comparison of two methodologies for long term rainfall monitoring using a commercial microwave communication system

Rayitsfeld, Asaf; Samuels, Rana; Zinevich, A.; Hadar, Uri; Alpert, Pinhas

doi:10.1016/j.atmosres.2011.08.011

Cited by 47 publications

(40 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…mean or instantaneous received signal powers for shorter or longer time intervals, the code should be modified. Although many networks have constant transmitted powers (Messer et al, 2006;Leijnse et al, 2007a;Chwala et al, 2012;Rayitsfeld et al, 2012;Bianchi et al, 2013), other networks may not operate with constant transmitted powers. For links using Automatic Transmit Power Control (ATPC) the transmitted power can become higher in case of a reduced received power at the end of the link, to compensate for large losses along the link path.…”

Section: Transferability Of Codementioning

confidence: 99%

“…Since 2006 various studies have shown that microwave links from operational cellular communication networks may be used for rainfall monitoring for various networks and climates (e.g. Messer et al, 2006;Leijnse et al, 2007a;Zinevich et al, 2009;Overeem et al, 2011Overeem et al, , 2013Chwala et al, 2012;Rayitsfeld et al, 2012;Bianchi et al, 2013;Doumounia et al, 2014). The ability to observe other types of precipitation, such as snow, is limited however.…”

Section: Introductionmentioning

confidence: 99%

“…Messer and Sendik (2015) provide more information on different methods of wet-dry classification and reference signal determination. Sometimes powers are sampled every second (Doumounia et al, 2014), every minute (Rayitsfeld et al, 2012), or only once or twice every 15 min (Leijnse et al, 2007a). Other approaches to identify rainy and non-rainy spells make use of auxiliary sources but are not considered in this paper.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

2016

View full text Add to dashboard Cite

Abstract. Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide ( ≈ 35 500 km 2 ) 15 min rainfall maps can be derived from the signal attenuations of approximately 2400 microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm. Moreover, the documented, modular, and user-friendly code (a package in the scripting language "R") is made available, including a 2-day data set of approximately 2600 commercial microwave links from the Netherlands. The purpose of this paper is to promote rainfall mapping utilising microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

show abstract

Section: Transferability Of Codementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

2016

View full text Add to dashboard Cite

show abstract

“…Current methods such as rain gauges, radar, microwave links (ML), and even satellites can provide measurements, yet the ability to generate high-resolution maps from them is limited. Rain gauges, which provide the most reliable estimates, are limited due to their point location measurements, which cannot provide accurate spatial estimates, especially in areas of complex topography or high spatial variability (Rayitsfeld et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

et al. 2014

View full text Add to dashboard Cite

Abstract. One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date, the most effective methods for large-scale rainfall estimates are radar, satellites, and, more recently, received signal level (RSL) measurements derived from commercial microwave networks (CMNs). While these methods provide improved spatial resolution over traditional rain gauges, they have their limitations as well. For example, wireless CMNs, which are comprised of microwave links (ML), are dependant upon existing infrastructure and the ML' arbitrary distribution in space. Radar, on the other hand, is known in its limitation for accurately estimating rainfall in urban regions, clutter areas and distant locations. In this paper the pros and cons of the radar and ML methods are considered in order to develop a new algorithm for improving rainfall measurement and mapping, which is based on data fusion of the different sources. The integration is based on an optimal weighted average of the two data sets, taking into account location, number of links, rainfall intensity and time step. Our results indicate that, by using the proposed new method, we not only generate more accurate 2-D rainfall reconstructions, compared with actual rain intensities in space, but also the reconstructed maps are extended to the maximum coverage area. By inspecting three significant rain events, we show that our method outperforms CMNs or the radar alone in rain rate estimation, almost uniformly, both for instantaneous spatial measurements, as well as in calculating total accumulated rainfall. These new improved 2-D rainfall maps, as well as the accurate rainfall measurements over large areas at sub-hourly timescales, will allow for improved understanding, initialization, and calibration of hydrological and meteorological models mainly necessary for water resource management and planning.

show abstract

“…Since the first proposed method of path-averaged rainfall rate estimation using microwave attenuation by Atlas and Ulbrich [9], the path-averaged rainfall rate has been estimated using microwave links (10-30 GHz) by Olsen et al [10], Kramer et al [11], Messer et al [12], Overeem et al [13], and Mercier et al [14]. In Israel, the application of the 10-40 GHz wavelength, which can complement the rain gauges and weather radar networks, has been proposed for its usability [15][16][17][18]. Microwave links, through which very high temporal resolution data can be observed and compared with rain gauge data, are useful for estimating accurate near-surface rainfall rates in urban areas [19,20] and can also be used to estimate variations in drop size distribution (DSD) [21].…”

Section: Introductionmentioning

confidence: 99%

Rainfall Detection and Rainfall Rate Estimation Using Microwave Attenuation

Kim

Kwon

2018

Atmosphere

View full text Add to dashboard Cite

Eight microwave links operating at frequencies ranging from 6 to 8 GHz and with path lengths ranging from 5.7 to 37.4 km traversing the city of Seoul, Korea are used to detect rainfall and estimate path-averaged rainfall rates. Rainfall detection using rain-induced attenuation (dB) was validated by rain detectors installed at automatic weather stations, and the results confirmed that microwave links can be used to detect rainfall with an accuracy ≥80%. The power-law R-k relationships between rain-induced specific attenuation, k (dB km −1 ), and the rainfall rate, R (mm h −1 ), were established and cross-validated by estimating the path-averaged rainfall rate. The mean bias of the path-averaged rainfall rate, as compared to the rainfall rate from ground rain gauges, was between −3 and 1 mm h −1 . The improved accuracy of rainfall detection led to the improved accuracy of the path-averaged rainfall rate. Hence, it was confirmed that microwave links, used for broadcasting and media communications, can identify rainy or dry periods (rain spells or dry spells) in a way comparable to rain detectors and provide high time-resolution rainfall rates in real time.

show abstract

Comparison of two methodologies for long term rainfall monitoring using a commercial microwave communication system

Cited by 47 publications

References 27 publications

Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

Rainfall Detection and Rainfall Rate Estimation Using Microwave Attenuation

Contact Info

Product

Resources

About