Opportunistic rain rate estimation from measurements of satellite downlink attenuation: A survey

Recent years have witnessed a growing interest in techniques and systems for rainfall surveillance on regional scale, with increasingly stringent requirements in terms of the following: (i) accuracy of rainfall rate measurements, (ii) adequate density of sensors over the territory, (iii) space‐time continuity and completeness of data and (iv) capability to elaborate rainfall maps in near real time. The devices deployed to monitor the precipitation fields are traditionally networks of rain gauges distributed throughout the territory, along with weather radars and satellite remote sensors operating in the optical or infrared band, none of which, however, are suitable for full compliance to all of the requirements cited above. More recently, a different approach to rain rate estimation techniques has been proposed and investigated, based on the measurement of the attenuation induced by rain on signals of pre‐existing radio networks either in terrestrial links, e.g., the backhaul connections in cellular networks, or in satellite‐to‐earth links and, among the latter, notably those between geostationary broadcast satellites and domestic subscriber terminals in the Ku and Ka bands. Knowledge of the above rain‐induced attenuation permits the retrieval of the corresponding rain intensity provided that a number of meteorological and geometric parameters are known and ultimately permits estimating the rain rate locally at the receiver site. In this survey paper, we specifically focus on such a type of “opportunistic” systems for rain field monitoring, which appear very promising in view of the wide diffusion over the territory of low‐cost domestic terminals for the reception of satellite signals, prospectively allowing for a considerable geographical capillarity in the distribution of sensors, at least in more densely populated areas. The purpose of the paper is to present a broad albeit synthetic overview of the numerous issues inherent in the above rain monitoring approach, along with a number of solutions and algorithms proposed in the literature in recent years, and ultimately to provide an exhaustive account of the current state of the art. Initially, the main relevant aspects of the satellite link are reviewed, including those related to satellite dynamics, frequency bands, signal formats, propagation channel and radio link geometry, all of which have a role in rainfall rate estimation algorithms. We discuss the impact of all these factors on rain estimation accuracy while also highlighting the substantial differences inherent in this approach in comparison with traditional rain monitoring techniques. We also review the basic formulas relating rain rate intensity to a variation of the received signal level or of the signal‐to-noise ratio. Furthermore, we present a comprehensive literature survey of the main research issues for the aforementioned scenario and provide a brief outline of the algorithms proposed for their solution, highlighting their points of strength and weakness. The paper includes an extensive list of bibliographic references from which the material presented herein was taken

Rainfall Map from Attenuation Data Fusion of Satellite Broadcast and Commercial Microwave Links

The demand for accurate rainfall rate maps is growing ever more. This paper proposes a novel algorithm to estimate the rainfall rate map from the attenuation measurements coming from both broadcast satellite links (BSLs) and commercial microwave links (CMLs). The approach we pursue is based on an iterative procedure which extends the well-known GMZ algorithm to fuse the attenuation data coming from different links in a three-dimensional scenario, while also accounting for the virga phenomenon as a rain vertical attenuation model. We experimentally prove the convergence of the procedures, showing how the estimation error decreases for every iteration. The numerical results show that adding the BSL links to a pre-existent CML network boosts the accuracy performance of the estimated rainfall map, improving up to 50% the correlation metrics. Moreover, our algorithm is shown to be robust to errors concerning the virga parametrization, proving the possibility of obtaining good estimation performance without the need for precise and real-time estimation of the virga parameters

Multi-Satellite Rain Sensing: Design Criteria and Implementation Issues

In this paper, we propose a novel opportunistic multi-satellite sensor system which overcomes the limitations of the conventional single-satellite solutions of the literature. The considerable robustness to the possible unavailability of some satellites, besides being well suited for powerful 2D reconstruction techniques of the rain field, makes it an appealing solution for experimental tests within national and EU-funded research projects

Study of real-time estimation of the power attenuation due to rainfall along microwave link

The problem of rainfall monitoring is a topic task in areas where precipitations are characterized by high intensity and very fast development. Tuscany is a region interested by flood and logistic problems due to strong intensity storms. The topic task is to find a rainfall method that can permit to monitor in real time risk areas so that, in case of hazard, citizens can be alerted earlier. Nowadays rain gauges, weather radar, microwave networks and satellite sensing are the most employed approaches to the task of rainfall monitoring. Unfortunately, all of these methods show substantial weakness that, in different ways, limit their employment in any scenario. Although the attenuation of a microwave link is not entirely due to rain, and generally the precipitation events are characterized by a simultaneous multiple status of water, from the point of view of both the probability of occurrence and the severity of effect, the rain scattering is however the most important of the hydrometeor phenomena, especially for operative frequencies above 10 GHz. In this thesis a novel method for rainfall monitoring has been proposed: it is based on the employment of an opportunistic commercial kit for satellite internet services, operating in KA-band. Since the signals within this band are particularly affected by hydrometeors fading, in order to guarantee a continuity of the service in all-weather conditions, the employed device needs to carry out a continuous adjustment of the uplink transmitted power in function of the intensity of the signal received from the satellite. This mechanism, that gives to the service a certain weather independency, is the basic principle of the proposed low-cost digital rain gauge. This power-control technique, essential for KA-band satellite internet applications, can be exploited to measure in real time the signal fading induced by hydrometeors along the Tropospheric segment of the Earth-space link. The proposed algorithm is named Rainfall rate EsTimation - Attenuation Based (RET-AB): it consists on collecting data with the KA-band system and then it processes them in order to retrieve the cumulated rainfall rate along the microwave link. Two measurement campaign have been held in order to validate the results obtained by the whole system

Temporal Characteristics of P-band Tomographic Radar Backscatter of a Boreal Forest

Temporal variations in synthetic aperture radar (SAR) backscatter over forests are of concern for any SAR mission with the goal of estimating forest parameters from SAR data. In this article, a densely sampled, two-year long time series of P-band (420 to 450 MHz) boreal forest backscatter, acquired by a tower-based radar, is analyzed. The experimental setup provides time series data at multiple polarizations. Tomographic capabilities allow the separation of backscatter at different heights within the forest. Temporal variations of these multi-polarimetric, tomographic radar observations are characterized and quantified. The mechanisms studied are seasonal variations, effects of freezing conditions, diurnal variations, effects of wind and the effects of rainfall on backscatter. An emphasis is placed on upper-canopy backscatter, which has been shown to be a robust proxy for forest biomass. The canopy backscatter was most sensitive to freezing conditions but was more stable than ground-level backscatter and full-forest backscatter during non-frozen conditions. The analysis connects tree water transport mechanisms and P-band radar backscatter for the first time. The presented results are useful for designing boreal forest parameter estimation algorithms, using data from P-band SARs, that are robust to temporal variations in backscatter. The results also present new forest remote sensing opportunities using P-band radars

Combining commercial microwave link and rain gauge observations to estimate countrywide precipitation: a stochastic reconstruction and pattern analysis approach

Accurate spatiotemporal precipitation quantification is a crucial prerequisite for hydrological analyses. The optimal reconstruction of the spatial distribution, that is, the rainfall patterns, is particularly challenging. In this study, we reconstructed spatial rainfall on a countrywide scale for Germany by combining commercial microwave link and rain gauge observations for a better representation of the variability and spatial structure of rainfall. We further developed and applied the Random-Mixing-Whittaker-Shannon method, enabling the stochastic reconstruction of ensembles of spatial fields via linear combinations of unconditional random fields. The pattern of rainfall objects is evaluated by three performance characteristics, that is, ensemble Structure-, Amplitude-, and Location-error. Precipitation estimates obtained are in good agreement with the gauge-adjusted weather radar product RADOLAN-RW of the German Weather Service (DWD) which was used as a reference. Compared to reconstructions by Ordinary Kriging, Random Mixing showed clear advantages in the pattern representation via a five times smaller median structure error

Combining Commercial Microwave Link and Rain Gauge Observations to Estimate Countrywide Precipitation: A Stochastic Reconstruction and Pattern Analysis Approach

Accurate spatiotemporal precipitation quantification is a crucial prerequisite for hydrological analyses. The optimal reconstruction of the spatial distribution, that is, the rainfall patterns, is particularly challenging. In this study, we reconstructed spatial rainfall on a countrywide scale for Germany by combining commercial microwave link and rain gauge observations for a better representation of the variability and spatial structure of rainfall. We further developed and applied the Random-Mixing-Whittaker-Shannon method, enabling the stochastic reconstruction of ensembles of spatial fields via linear combinations of unconditional random fields. The pattern of rainfall objects is evaluated by three performance characteristics, that is, ensemble Structure-, Amplitude-, and Location-error. Precipitation estimates obtained are in good agreement with the gauge-adjusted weather radar product RADOLAN-RW of the German Weather Service (DWD) which was used as a reference. Compared to reconstructions by Ordinary Kriging, Random Mixing showed clear advantages in the pattern representation via a five times smaller median structure error

Transboundary Rainfall Estimation Using Commercial Microwave Links

Unlike actual rainfall, the spatial extent of rainfall maps is often determined by administrative and political boundaries. Similarly, data from commercial microwave links (CMLs) is usually acquired on a national basis and exchange among countries is limited. Up to now, this has prohibited the generation of transboundary CML-based rainfall maps despite the great extension of networks across the world. We present CML based transboundary rainfall maps for the first time, using independent CML data sets from Germany and the Czech Republic. We show that straightforward algorithms used for quality control strongly reduce anomalies in the results. We find that, after quality control, CML-based rainfall maps can be generated via joint and consistent processing, and that these maps allow to seamlessly visualize rainfall events traversing the German-Czech border. This demonstrates that quality control represents a crucial step for large-scale (e.g., continental) CML-based rainfall estimation