WO2013124853A1 - System and method for identifying a hydrometeor - Google Patents

Abstract

A method of estimating a level a hydrometeor is disclosed. The method comprises: obtaining signal level data from a plurality of free-space electromagnetic communication links distributed over a region; and analyzing attenuation levels associated with the links as a function of path lengths associated with the links, so as to extract at least a first parameter which vary with the path lengths and a second parameter which generally does not vary with the path lengths. The method further comprises estimating a level of the hydrometeor, responsively to the analysis.

Description

SYSTEM AND METHOD FOR IDENTIFYING A HYDROMETEOR

RELATED APPLICATION

This application claims the benefit of priority of U.S. Provisional Patent Application No. 61/602,156 filed February 23, 2012, the contents of which are incorporated herein by reference in their entirety.

FIELD AND BACKGROUND OF THE INVENTION

The present invention, in some embodiments thereof, relates to meteorology and, more particularly, but not exclusively, to a system and method for identifying and/or estimating the level of a hydrometeor.

Hydrometeors are a family of atmospheric phenomena including precipitation, water vapor, sleet, mist and fog. Fog is a condition in which water droplets suspended in the atmosphere near the surface of earth and reduce visibility. The impact of fog on humans and on the environment is considerable. Fog harvesting, for example, can produce fresh water for gardening, afforestation and even potable water that may have a significant contribution particularly in water scarce regions (Oliver, 2004; Klemm et al., 2012). Moreover, in forest ecosystems, fog takes a part in the water balance of natural environments (e.g., Dawson, 1998; Wrzesinsky and Klemm, 2000). Information concerning the Liquid Water Content (LWC) of fog makes it possible to define the concentration of air pollutants through analysis of fog droplet samples (e.g., Tago et al., 2006). Fog plays a role of cleaning the atmosphere through the process of particle scavenging and then drop deposition (Herckes et al., 2007).

On the other hand, smog (a portmanteau of smoke and fog) may harm human health, adversely affect plants and damage structures (e.g., Wichmann et al., 1989; Dam and Hoang, 2008). The main negative effect attributed to fog is the reduced visibility that can lead to heavy financial damages, grave accidents and loss of life (Croft et al., 1995; Pagowski et al., 2004, Gultepe et al., 2009). The total economic impact of the presence of fog on aviation, marine and land transportation can be compared to the impact of tornadoes or, in some cases, even those of hurricanes (Gultepe et al, 2007). Furthermore, it has been recently shown that while the number of road accidents due to rain has declined considerably, the totals in foggy conditions have not changed significantly (Pisano et al., 2008).

Predominant techniques for the detection of fog and measuring visibility include: trained human observers and transmissometers.

A trained human observer assesses visibility by the appearance or occlusion of objects at known distances from the observer's present location.

Transmissometers include a light source, such as a laser, and a detector for detecting either light from the light source directly or light from the light source reflected back to the detector from a reflector such as a mirror. Transmissometers operate by detecting a reduction in the intensity of the light which results from the introduction of particulate matter or intervening weather conditions such as fog (WMO, 2008).

Another detection technique includes use of systems that measure the scatter coefficient. In these systems, the scatter coefficient is measured and is correlated to the extinction coefficient.

Other detection techniques include use of satellites (Ellrod, 1995), measurements of fog liquid water content (Gerber, 1984; Arends et al., 1992; Emert, 2001; Schwarzenboeck et al., 2009), and use of systems such as Particle Volume Monitor, Forward Scattering Spectrometer Probe and hot-wire probes.

SUMMARY OF THE INVENTION

According to an aspect of some embodiments of the present invention there is provided a method of estimating a level a hydrometeor. The method comprises: obtaining signal level data from a plurality of free- space electromagnetic communication links distributed over a region; and analyzing attenuation levels associated with the links as a function of path lengths associated with the links, so as to extract at least a first parameter which vary with the path lengths and a second parameter which generally does not vary with the path lengths. The method further comprises estimating a level of the hydrometeor, responsively to the analysis.

According to some embodiments of the invention the analysis comprises performing a linear fit to provide a slope and an intercept, and wherein the first parameter is the slope and the second parameter is the intercept. According to some embodiments of the invention the method comprises repeating the estimation for each of at least a few of the links so as to map the hydrometeor over the region according to geographic locations of the links.

According to some embodiments of the invention the method comprises indentifying a presence of the hydrometeor if the attenuation levels are above a baseline level for at least a few of the links.

According to some embodiments of the invention the hydrometeor comprises at least fog.

According to some embodiments of the invention the first parameter is the slope and the second parameter is the intercept, wherein the estimating the level comprises linearly correlating the slope to the level.

According to some embodiments of the invention the invention the method comprises estimating liquid water content based on the first parameter.

According to some embodiments of the invention the invention the method comprises calculating a first set of attenuation levels corresponding to links associated with path length below a predetermined threshold, and using the first set of attenuation levels for correcting at least one of the first and the second parameters. According to some embodiments of the invention the predetermined threshold equals at most 500 meters.

According to an aspect of some embodiments of the present invention there is provided a method of at least identifying a hydrometeor. The method comprises: obtaining signal level data from a plurality of free- space electromagnetic communication links distributed over a region; calculating a first set of attenuation levels associated with a first set of links characterized by path lengths below a predetermined threshold, and a second set of attenuation levels associated at least with links other than the first set of links; processing attenuation levels of the second set using attenuation levels of the first set, to provide processed attenuation levels; and using the processed attenuation levels for identifying the hydrometeor. According to some embodiments of the invention the predetermined threshold equals at most 500 meters.

According to some embodiments of the invention the processing comprises subtracting attenuation levels of the first set from attenuation levels of the second set. According to some embodiments of the invention the invention the method comprises estimating a level of the hydrometeor based on the processed attenuation levels.

According to some embodiments of the invention the invention the method comprises indentifying a presence of the hydrometeor if the attenuation levels are above a baseline level for at least a few of the links.

According to some embodiments of the invention the method comprises obtaining additional data pertaining to at least one hydrometeor other than fog, and correcting the estimation based on the additional data.

According to some embodiments of the invention the method comprises obtaining temperature data, and correcting the estimation based on the temperature data.

According to some embodiments of the invention the method comprises defining a baseline signal level, independently for each link of the plurality of links, so as to correct for water vapor induced attenuation.

According to some embodiments of the invention the method comprises estimating liquid water content based on the processed attenuation levels.

According to some embodiments of the invention the method comprises estimating a visibility level, based on the liquid water content.

According to some embodiments of the invention the electromagnetic communication links are microwave links. According to some embodiments of the invention a characteristic frequency of the microwave links is from about 1 GHz to about 1000 GHz.

According to an aspect of some embodiments of the present invention there is provided a system for identifying a hydrometeor, comprising: an input unit for obtaining signal level data from a plurality of free-space electromagnetic communication links distributed over a region; and a processing unit configured for executing one or more of the operations of the method as delineated hereinabove and further detailed hereinbelow.

According to an aspect of some embodiments of the present invention there is provided a system for identifying a hydrometeor, comprising: an input unit for obtaining signal level data from a plurality of free-space electromagnetic communication links distributed over a region; and a processing unit configured for executing one or more of the operations of the method as delineated hereinabove and further detailed hereinbelow. Unless otherwise defined, all technical and/or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention pertains. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the invention, exemplary methods and/or materials are described below. In case of conflict, the patent specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be necessarily limiting.

Implementation of the method and/or system of embodiments of the invention can involve performing or completing selected tasks manually, automatically, or a combination thereof. Moreover, according to actual instrumentation and equipment of embodiments of the method and/or system of the invention, several selected tasks could be implemented by hardware, by software or by firmware or by a combination thereof using an operating system.

For example, hardware for performing selected tasks according to embodiments of the invention could be implemented as a chip or a circuit. As software, selected tasks according to embodiments of the invention could be implemented as a plurality of software instructions being executed by a computer using any suitable operating system. In an exemplary embodiment of the invention, one or more tasks according to exemplary embodiments of method and/or system as described herein are performed by a data processor, such as a computing platform for executing a plurality of instructions. Optionally, the data processor includes a volatile memory for storing instructions and/or data and/or a non-volatile storage, for example, a magnetic hard-disk and/or removable media, for storing instructions and/or data. Optionally, a network connection is provided as well. A display and/or a user input device such as a keyboard or mouse are optionally provided as well.

BRIEF DESCRIPTION OF THE DRAWINGS

Some embodiments of the invention are herein described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of embodiments of the invention. In this regard, the description taken with the drawings makes apparent to those skilled in the art how embodiments of the invention may be practiced.

In the drawings:

FIG. 1 is a flowchart diagram of a method suitable for identifying and/or estimating the level of a hydrometeor, according to various exemplary embodiments of the present invention;

FIG. 2 is a schematic illustration of a system for identifying and/or estimating the level of a hydrometeor, according to some embodiments of the present invention;

FIGs. 3A-B show theoretical expected attenuation levels per 1 km (FIG. 3 A) and 5 km (FIG. 3B), as a function of the frequency of a microwave link.

FIG. 4 shows locations of different measuring means and deployment of microwave links, in a region-of-interest defined during a first experiment performed according to some embodiments of the present invention;

FIGs. 5A-B show visibility assessments obtained according to some embodiments of the present invention during the first experiment;

FIGs. 6A-B show attenuation measurements, as measured according to some embodiments of the present invention during the first experiment for a foggy night (FIG. 6A) and a humid night without fog (FIG. 6B);

FIG. 7 shows locations of different measuring means and deployment of microwave links, in a region-of-interest defined during a second experiment performed according to some embodiments of the present invention;

FIGs. 8A-B show visibility assessments obtained according to some embodiments of the present invention during the second experiment; and

FIGs. 9A-B show attenuation measurements, as measured according to some embodiments of the present invention during the second experiment for a foggy night (FIG. 9A) and a humid night without fog (FIG. 9B).

DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

The present invention, in some embodiments thereof, relates to meteorology and, more particularly, but not exclusively, to a system and method for identifying and/or estimating the level of a hydrometeor. Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not necessarily limited in its application to the details of construction and the arrangement of the components and/or methods set forth in the following description and/or illustrated in the drawings and/or the Examples. The invention is capable of other embodiments or of being practiced or carried out in various ways.

Some embodiments of the present invention relate to a method suitable for identifying and/or estimating a level of a hydrometeor in a region-of-interest. One or more operations of the method can be executed by a data processor, which can be a general purpose computer or dedicated circuitry.

Computer programs implementing the method of this invention can commonly be distributed to users on a distribution medium such as, but not limited to, a floppy disk or CD-ROM. From the distribution medium, the computer programs can be copied to a hard disk or a similar intermediate storage medium. The computer programs can be run by loading the computer instructions either from their distribution medium or their intermediate storage medium into the execution memory of the computer, configuring the computer to act in accordance with the method of this invention. All these operations are well-known to those skilled in the art of computer systems.

The method can be embodied in many forms. For example, it can be embodied in on a tangible medium such as a computer for performing the method steps. It can be embodied on a computer readable medium, comprising computer readable instructions for carrying out the method steps. It can also be embodied in electronic device having digital computer capabilities arranged to run the computer program on the tangible medium or execute the instruction on a computer readable medium.

Referring now to the drawings, FIG. 1 is a flowchart diagram of the method, according to various exemplary embodiments of the present invention. It is to be understood that, unless otherwise defined, the operations described hereinbelow can be executed either contemporaneously or sequentially in many combinations or orders of execution. Specifically, the ordering of the flowchart diagrams is not to be considered as limiting. For example, two or more operations, appearing in the following description or in the flowchart diagrams in a particular order, can be executed in a different order (e.g., a reverse order) or substantially contemporaneously. Additionally, several operations described below are optional and may not be executed.

The method begins at 10 and optionally and preferably continues to 11 at which signal level data are obtained from a plurality of free- space electromagnetic communication links distributed over a region.

As used herein an "electromagnetic communication link" refers to a transmitter- receiver pair including an electromagnetic transmitter and an electromagnetic receiver spaced from each other. An electromagnetic communication link is therefore characterized at least by a path length describing the distance that is traversed by a signal from the transmitter to the receiver. The path length is approximately the physical distance between the respective transmitter and the respective receiver.

Typically, the communication links correspond to a deployment of a set of electromagnetic communication stations over a region. Each station can include a transceiver (i.e., both a receiver and a transmitter), where the communication link is established between the transmitter part of one station of the set and the receiver part of another station of the set. Generally, any pair of communication stations in the set can form a communication link, wherein the number of possible links for a given set of stations equals the number of pair combinations among the set.

It is to be understood, however, that it is not necessary for the method to employ all possible links for a given set of stations. A typical number of links useful for the present embodiments is at least 30 or at least 40 or at least 50.

The electromagnetic communication links are preferably, but not necessarily, microwave links. A characteristic frequency of the microwave links can be, without limitation, from about 1 GHz to about 1000 GHz, or from about 1 GHz to about 500 GHz, or from about 10 GHz to about 500 GHz, or from about 10 GHz to about 400 GHz, or from about 10 GHz to about 300 GHz, or from about 10 GHz to about 200 GHz, or from about 10 GHz to about 100 GHz, or from about 10 GHz to about 50 GHz.

In some embodiments of the present invention, the communication links comprise cellular communication links established between pairs of cellular communication transceivers of a cellular communication network or part thereof.

As used herein the term "about" refers to ± 10 %. The advantage of using links established among cellular communication transceivers is that cellular communication networks are widely spread across the terrain and provide continuous measurements at high temporal and spatial resolution. Another advantage is that the use of such links significantly reduces the implementation costs since, in various exemplary embodiments of the invention the method can utilize data which are routinely collected and logged by the communication providers. An additional advantage is that the antennas of the cellular communication transceivers are typically installed at heights which are suitable for identifying and/or estimating the level of the hydrometeor.

In some embodiments of the present invention the method continues to 13 at which the presence of the hydrometeor is identified. This is optionally and preferably achieved by a thresholding procedure including one or more thresholds. In various exemplary embodiments of the invention the presence of the hydrometeor is identified if the attenuation levels are above a baseline attenuation level for at least a few of the links.

Optionally, at least one additional threshold other than the baseline attenuation level is employed for the identification. The additional threshold preferably relates to one or more atmospheric conditions such as, but not limited to, relative humidity, temperature, droplet number concentration and the like. Thus, in some embodiments of the present invention 13 is preceded by 12 at which the method obtains data pertaining to at least one atmospheric condition. It was found by the present inventors that a threshold pertaining to the relative humidity is useful in combination with the baseline attenuation level for identifying a hydrometeor, particularly, but not exclusively, when the hydrometeor is fog. A representative thresholding procedure suitable for the present embodiments is provided in the Examples section that follows.

In various exemplary embodiments of the invention the method continues to 14 at which attenuation levels associated with the links are calculated.

The attenuation levels can be calculated from the signal level data using any procedure known in the art. For example, a baseline signal level can be defined independently for each link, and the attenuation level can be calculated relative to the defined baseline signal level, e.g. , by calculating the difference between the received signal level (RSL) and the baseline signal level. In some embodiments of the present invention the baseline signal level is defined so as to correct for water vapor induced attenuation. This can be done by selecting the baseline level as the median value from RSL measurements taken over a period of several hours, during which the no fog is present but the relative humidity is within a predetermined range that is sufficiently high. A representative example of a predetermined range suitable for the present embodiments is without limitation from about 85% to about 80%. The base line level is optionally and preferably selected from time frames with close proximity (e.g., within less than 30 days or less than 20 days or less than 10 days or less than 5 days or less than 2 days or less than 24 hours or less than 18 hours or less than 12 hours or less than 6 hours) to the event of interest.

Alternatively, the method can obtain signal level data during a period at which the hydrometeor of interest (e.g., fog) is absent and apply a humidity correction procedure to these signal level data for defining the baseline level. The humidity correction procedure can be based on a physical model, such as the model described in Rec. ITU-R P.676-6: Attenuation by atmospheric gases, 2005, the contents of which are hereby incorporated by reference.

In some exemplary embodiments of the invention the method continues to 15 at which the calculated attenuation levels are analyzed as a function of the path lengths, optionally and preferably so as to extract at least a first parameter which vary with the path lengths, and a second parameter which generally does not vary with the path lengths.

As used herein, a "parameter which generally does not vary with the path length," means a parameter whose value does not change by more that X% when the path length changes by at least Y%, where X/Y is less than 0.5 or less than 0.1 or less than 0.02.

A representative example of an analysis procedure suitable for the present embodiments is a linear fit which provides a slope and an intercept. In these embodiments, the first parameter can be the slope and the second parameter can be the intercept. Other types of analyses are not excluded from the scope of the present invention. Representative examples for additional types of analyses include, without limitation, a non-linear fit featuring two or more parameters, a principle component analysis, and a neural network analysis. The method optionally and preferably continues to 17 at which the level of the hydrometeor is estimated based on the analysis. This is optionally and preferably done by relating the level of the hydrometeor to the value of the first parameter. For example, it was found by the present inventors that when a linear fit is employed to express the attenuation level γ_; of the ith link as a linear function of the path length L, of the ith link, the slope of the linear function correlates with the level of fog (e.g. , liquid water content). Specifically, it was found by the present inventors that the liquid water content is linearly proportional to the slope with a proportion coefficient Φ that depends on the characteristic frequency of the links and the dielectric permittivity of the water. A suitable expression for the coefficient Φ is provided in the examples section that follows.

The second parameter that is extracted during the analysis can be used for estimating contribution to the attenuation from conditions nearby or at the communication station. For example, the second parameter can relate to contribution to the attenuation due to the presence of water layer on the transceivers.

In some embodiments of the present invention the method proceeds to 18 at which the method estimates a visibility level. This embodiment is particularly useful when the hydrometeor of interest is fog, in which case the visibility can be estimated based on a predetermined relation between the fog level (e.g. , the liquid water content) and the visibility. A preferred relation for calculating the estimated visibility is V = a-LWC^"5, where V is the estimated visibility, LWC is the estimated liquid water content and a and δ are predetermined positive parameters. A typical value for a is without limitation from about 0.01 to about 3, and a typical value for δ is, without limitation, from about 0.5 to about 1.5. As a representative example, which is not to be considered as limiting, a can be set to about 0.027 and δ can be set to about 0.88. Other values are not excluded from the scope of the present invention.

The method optionally and preferably can be supplemented with one or more optional operations.

In some embodiments, additional data are obtained, e.g. , from an external source of data, and the estimation 17 is corrected based on the additional data. The additional data can pertain to at least one additional hydrometeor and be used for estimating the contribution of the additional hydrometeor to the attenuation. In this embodiment, the correction optionally and preferably includes removing that contribution from the attenuation as obtained from the RSL. As a representative example, when the method is used for estimating the fog level, the additional data can pertain to a hydrometeor other than fog (e.g., precipitation, water vapor, sleet, mist).

The additional data can also include data pertaining to one or more atmospheric conditions. For example, droplet number concentration data can be obtained and used for improving the estimated visibility. A preferred relation for calculating the estimated visibility using the droplet number concentration ND is V = a-(No-LWC)^"5, where the parameter a and δ were already introduced above. When droplet number concentration data are not available, temperature data can be obtained and be used for estimating the droplet number concentration, e.g. , by expressing the droplet number concentration as power series of the temperature. A representative example of such power series is provided in the Examples section that follows.

In some embodiments of the present invention the method calculates 16 a set of attenuation levels corresponding to links associated with path length below a predetermined threshold (e.g. , path length below 500 m or below 400 m or below 300 m or below 250 m). This set is optionally and preferably used for correcting the estimation 17. It was found by the present inventors that the effect of fog and water vapors on the signal attenuation at short ranges is much smaller comparing to the attenuation created in longer links. Thus, by calculating attenuation levels corresponding to relatively short links, the contribution of local conditions at or nearby the communication stations (e.g. , presence of water layer on the antennas of the transceivers) can be estimated. This contribution can be removed from the attenuation levels as calculated from the entire dataset, or a portion of the dataset corresponding only to long links, thereby correcting the estimation of hydrometeor level.

The set obtained at 16 can optionally and preferably be used as an additional input or for defining weights during the analysis 15. For example, during the analysis, the set obtained at 16 can be used for defining upper and/or lower bounds for the second parameter. Alternatively or additionally, the method can define reduced weights for links associated with the set obtained at 16 and/or enhanced weights for other links.

Alternatively, the method can skip 15 and estimate the presence and/or level of the hydrometeor by processing the attenuation levels associated with all links (or links other than the short links) using attenuation levels associated with short links. This is optionally and preferably done by subtracting the short link attenuation levels from the attenuation levels associated with all links or the attenuation levels associated with links other than the short links. Once the attenuation levels are processed, they can be used for estimating the level of the hydrometeor.

For example, when the hydrometeor of interest is fog, the processed attenuation level can be linearly correlated to the path length, and coefficient of correlation can be linearly correlated to the fog level (e.g., liquid water content). As a representative example, denoting the processed attenuation level of the ith link by P; and the length of the ith link by L_;, the ratio P L, can be expressed as Φ-LWC, where LWC is the liquid water content and Φ is a coefficient depends on the characteristic frequency of the links and the dielectric permittivity of the water. A suitable expression for the coefficient Φ is provided in the examples section that follows. Thus, in this exemplary embodiment, an estimate of LWC can be calculated using the relation LWC = Ρ_;/(Φ·^).

The estimation of the hydrometeor level based on 16 while skipping 15 is preferred from the standpoint of simplicity, since it can be performed separately for each individual link. Estimating the hydrometeor level based on 15 is preferred from the standpoint of accuracy since the collective analysis of a plurality of attenuation levels reduces the statistical error.

In various exemplary embodiments of the invention the method proceeds to 19 at which the results (e.g. , the presence/absence of the hydrometeor, the level of the hydrometeor, the visibility level) are transmitted to a computer readable medium and/or a display device.

The method ends at 20.

Reference is now made to FIG. 2 which is a schematic illustration of a system 30 for identifying and/or estimating the level of a hydrometeor, according to some embodiments of the present invention. System 30 preferably comprises an input unit, 32 which typically includes an electronic circuitry configured for receiving data, optionally and preferably digital data. Unit 32 can receive data either wirelessly or via a wired communication line (not shown). In use, unit 32 receives signal level data from communication links 40 as further detailed hereinabove. System 30 further comprises a processing unit 34, which can include a computer (e.g. , general purpose computer) and/or dedicated circuitry. Unit 34 is configured for executing one or more of the operations described above with respect to FIG. 1. In some embodiments of the present invention unit 34 is a computer which is configured to receive a computer software product comprising a computer-readable medium. The medium stores program instructions, which, when read by the computer, cause the computer to receive signal level data and execute one or more of the operations described above with respect to FIG. 1.

In some embodiments of the present invention system 30 comprises a plurality of free-space (wireless) electromagnetic communication transceivers 36 deployed over a region 38 to form a wireless electromagnetic communication network therein. Transceivers 36 can transmit to unit 32 signal level data corresponding to signals transmitted over free-space communication links 40 formed among transceivers 36.

It is expected that during the life of a patent maturing from this application many relevant communication techniques will be developed and the scope of the term electromagnetic communication links is intended to include all such new technologies a priori.

The word "exemplary" is used herein to mean "serving as an example, instance or illustration." Any embodiment described as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments and/or to exclude the incorporation of features from other embodiments.

The word "optionally" is used herein to mean "is provided in some embodiments and not provided in other embodiments." Any particular embodiment of the invention may include a plurality of "optional" features unless such features conflict.

The terms "comprises", "comprising", "includes", "including", "having" and their conjugates mean "including but not limited to".

The term "consisting of means "including and limited to".

The term "consisting essentially of" means that the composition, method or structure may include additional ingredients, steps and/or parts, but only if the additional ingredients, steps and/or parts do not materially alter the basic and novel characteristics of the claimed composition, method or structure. As used herein, the singular form "a", "an" and "the" include plural references unless the context clearly dictates otherwise. For example, the term "a compound" or "at least one compound" may include a plurality of compounds, including mixtures thereof.

Throughout this application, various embodiments of this invention may be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.

Whenever a numerical range is indicated herein, it is meant to include any cited numeral (fractional or integral) within the indicated range. The phrases "ranging/ranges between" a first indicate number and a second indicate number and "ranging/ranges from" a first indicate number "to" a second indicate number are used herein interchangeably and are meant to include the first and second indicated numbers and all the fractional and integral numerals therebetween.

It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination or as suitable in any other described embodiment of the invention. Certain features described in the context of various embodiments are not to be considered essential features of those embodiments, unless the embodiment is inoperative without those elements. Various embodiments and aspects of the present invention as delineated hereinabove and as claimed in the claims section below find experimental support in the following examples. EXAMPLES

Reference is now made to the following examples, which together with the above descriptions illustrate some embodiments of the invention in a non limiting fashion.

EXAMPLE 1

Dense Fog Monitoring Using Cellular Network Infrastructure

This Example describes a study directed to the monitoring of dense fog based on existing Received Signal Level (RSL) measurements from commercial microwave communication networks.

At frequencies of tens of GHz, various atmospheric hydrometeors: precipitation, water vapor, sleet, mist and fog affect microwave beams, causing perturbations to radio signals (Rec. ITU-R P.838-2, 2004; Rec. ITU-R P.676-6, 2005; Rec. ITU-R P.840-4, 2009). It was demonstrated that wireless communication networks can be used for rainfall observations (Messer et al. 2006; Leijnse et al., 2007a; Overeem et al., 2011 ; Rayitsfeld et al., 2011). In particular, wireless communication networks seem to have suitable properties and the potential to monitor fog with certain potential advantages over existing monitoring tools. Typically, the Microwave Links (MLs) utilized in these networks are installed at heights of a few tens of meters off the surface, they are widely spread across the terrain and provide continuous measurements at high temporal and spatial resolution. The implementation costs are minimal since the requested data are standard data collected and logged routinely by the communication providers.

MLs have also been suggested for estimating areal evaporation (Leijnse et al., 2007b), measuring the atmospheric water vapor (David et al., 2009, 2011) and monitoring characteristics of vegetation (Hunt et al., 2011).

Methods

Fog is one of the several atmospheric phenomena that affect MLs, causing an additional signal loss to the microwave electromagnetic beams with respect to that created during non-foggy periods (e.g. , Liebe et al., 1989). FIGs. 3A-B present theoretical (Rec. ITU-R P.840-4, 2009) expected attenuation levels per 1 km (FIG. 3A) and 5 km (FIG. 3B), as a function of the operation ML frequency. Shown in FIGs. 3A-B are attenuation levels created by different levels of fog concentration at temperatures of 15 (red) and 10 (blue) degrees centigrade. Given a certain LWC value, the expected attenuation is greater for higher frequencies, at lower temperatures. The LWC within fogs typically ranges between 0.01 to 0.4 gr/m (Gultepe et al., 2007). The calculations presented in FIGs. 3A-B were performed for different LWC values starting at 0.1 gr/m , and at different temperatures (10 and 15 °C). The maximum values of LWC were taken from field measurements (including five minute average values) carried out in the conducting of recent comprehensive field campaigns in different places in the world, using specialized equipment (Klemm et al., 2005, Herckes et al., 2007, Gultepe et al., 2009, Niu et al., 2010). The horizontal dashed line indicates the typical measurement resolution of a commercial MLs (links with a coarser measurement resolution exist, but will not be the focus of this paper).

It is notes that for longer links (FIG. 3B), the effective sensitivity per km increases, and lighter fogs can potentially be detected.

Two fundamental stages in fog monitoring using measurements from multiple MLs are distinguished in the present example: identification of the fog phenomenon, and the estimation of its degree using additional standard meteorological instruments (temperature, humidity and rain gauges).

In the present example, the technique was restricted to situations where other hydrometeors (rainfall, sleet, snow) were nonexistent along the propagation path and only extreme fog events were considered.

Fog Identification

A set L_V,...., L_N of MLs, spread across the observed region within the same fog patch, was used. In a typical cellular backhaul network, microwave links at different lengths and direction exist at an area of a size similar to a dense fog field, e.g., on the order of several square kilometers (see, e.g., Pagowski et al., 2004, Zinevich et al., 2008). The availability of diverse RSL measurements allows to identify the fog induced component with higher statistical precision.

A simplified model describing the attenuation of the ith microwave signal, γ;, can be described as follows (Zinevich et al., 2010):

Yi = [ A_fi + A_Pi + A_wi + A_vi + Noise; ]_qi (1) where the index i denotes the measurement obtained from the ith ML. In EQ. 1, Αβ is the fog induced attenuation, A_Pi is the attenuation as a result of other-than-fog precipitation (rain, sleet, snow), A_wi is wet antenna attenuation (because of the high level of humidity during fog, a thin layer of water may accumulate on the outside covers of the microwave antenna and may create additional attenuation to the received signal, beyond that caused by the fog in the atmospheric path), A_v is the water vapor attenuation, and Noise; includes all other random signal perturbations (e.g., perturbations created as a result of winds that may oscillate the antennas, variations of the atmospheric refractive index, or temperature variations which may affect the analogue circuitry of the microwave units). The notation [ ]q; in EQ. 1 is to be understood as a quantized measurement according to a given magnitude resolution of each ML.

In the present study, A_pi was assumed to be zero. This assumption was validated using nearby standard measurements of rain gauges and temperature meters.

In order to estimate the amount of wet antenna attenuation, A_w, measurements over particularly short MLs (preferably of up to a few hundreds of meters long) that are located near longer links were used. This is because the effect of fog, even a heavy fog, as well as of water vapor on the signal attenuation at short ranges is much smaller comparing to the attenuation created in longer MLs of several km in lengths (Rec. ITU- R P.676-6, 2005; Rec. ITU-R P.840-4., 2009). This being the case, any additional attenuation, if detected, can be directly attributed to the layer of water on the antennas, its value measured, and that value can be used to adjust the measurements on the longer links.

In order to identify the specific attenuation created as a result of the fog itself, a baseline, zero RSL value was set, separately for each link. Since the density of water vapor in the atmosphere affects MLs (Rec. ITU-R P.676-6, 2005; David et al., 2009, 2011) and since humidity is particularly high during fog, the zero level can be selected as the median value from RSL measurements taken over a period of several hours, during which the relative humidity in the area, as measured by the meteorological stations at the site, is around 90%.

Alternatively, since the humidity difference between the foggy day and the reference day is known, the median RSL from the days adjacent to the event can be selected (e.g. , in cases where measurement occurs once daily), and a humidity correction to the baseline can be carried out using a known physical model (Rec. ITU-R P.676-6, 2005). By this selection of the base line, the water vapor effect, A_v, is minimized and is assumed to be zero. Thus, in this Example, fog is identified as being present when the measured RSL value is above a predetermined threshold during times of high relative humidity (of about 95% or more), while additional attenuation relative to the baseline level is observed simultaneously by numerous MLs spread across the area.

Fog Density Estimation

After identifying the existence of fog, the average amount of LWC per unit volume in the fog was calculated, from which an estimation of the range of visibility was acquired.

Liquid water content calculation

Under the above assumptions, EQ. 1 is reduced to the form:

r_i = A_fi + A_wi + Noise_i (2) In EQ. 2 and the following description, the notation [ ]_qi is omitted, and the effective noise component, Noise_t should be understood as including the contribution from system quantization error.

The relation between the fog induced attenuation, A_fl , and the total water content per unit volume is given by (Rec. ITU-R P.840-4, 2009):

(dB) (3) where L [km] is the length of the ith link, Φ_; is a frequency and temperature dependent coefficient (known parameters), and LWC is the liquid water content [g m^" ]. In this study, it is assumed that all links deployed across the same fog field observe at the same time the same LWC.

Given γ_; measurements from N links operating around the same frequency and over the same fog patch, the LWC can be obtained according to the following procedure.

A set of N parameterizations of EQ. 2 are defined:

r_t = a_f - L_i + A_w + Noise, (dB) (4) where a_f is an effective fog induced attenuation parameter, and

is the estimated wet antenna component. a_f can be extracted from this set of equations using by any extraction technique, such as, but not limited to, a least squares method. The advantage of using a set of equations is that it increases the accuracy relative to the obtainable accuracy when a measurement from a single link is employed. Once the effective fog induced attenuation parameter is extracted, the LWC within the fog field can be derived from the relation:

a_f = <b - LWC (dB/km). (5)

A mathematical model (ITU-R P.840-4, 2009) based on Rayleigh approximation was used for the calculation of Φ, for frequencies of up to 200 GHz (fog drops typically range in size from several microns to a few tens of microns, small with respect to microwaves at frequencies of about 200 GHz or less):

Φ = ⁰-⁸¹⁹ (dB/km)/(g/m³) (6) £^■" (1 + β )

where/is the link frequency (GHz), and: β = (7)

The dielectric permittivity of water is (Rec. ITU-R P.840-4, 2009):

ε ( ) = ε < ( ; Τ) + ιε " (f, T)

Visibility estimation

Visibility is defined in the literature as the greatest distance in a given direction at which it is possible to see and identify a prominent black object against the sky at the horizon in the daylight, or the greatest distance it could be seen and recognized during night if the general illumination were raised to the level of normal daylight (WMO, 2008).

In order to estimate the visibility (V) a warm fog visibility parameterization was used (Gultepe et al, 2006):

w ere N_D is the droplet number concentration.

The parameterization is suitable for warm fog (T > 0 °C) conditions. D can be measured directly using specialized equipment. Alternatively, N_D can be estimated given the temperature, T, by using the following parameterization (Gultepe and Isaac, 2004):

N_D = -0.071 ² + 2.213 + 141.56 (cm^-3) (9) In this example, N_D was estimated using EQ. 9. Preliminary estimates of the upper and lower bounds of V were obtained based on the uncertainty in estimating V.

The primary source of uncertainty in estimating the LWC is the uncertainty in estimating the effective fog induced attenuation, a_f . In order to estimate the error in this value an error estimation formula for a linear slope was employed:

where n is number of samples, is the attenuation measured by the ith link, _; is the attenuation as estimated by the linear approximation for the ith link, L; is the length of the ith link, and L is the average length of the links.

Based on EQ. (5), the uncertainty in estimating the attenuation also induces an uncertainty in the LWC estimation which is given by: fiLWC = (I D

In the present study, the uncertainty caused due to temperature variations was neglected while deriving EQ. (11). The difference between the temperature measurements of the different gauges (with an instrument error of 0.1 °C) in the observed area was between 1 and 2 °C at the time of the microwave system measurement. This uncertainty created LWC variations which are an order of magnitude less than the uncertainty created from the effective fog induced attenuation using the model (Rec. ITU-R P.840-4, 2009).

The estimation of attenuation resulting from a possible wet antenna, A_w, was carried out by evaluating the y-intercept of the line (which represents a theoretical zero distance between the antennas). The error in A_w was estimated using an error estimation formula for the intercept in a linear approximation:

The warm-fog visibility parameterization (EQ. 8), was estimated to have an uncertainty of about 29 %. It is noted that the estimation of _D in this example was derived from the temperature (EQ. 9), which may introduce additional uncertainty. Thus, approximated upper and lower preliminary bounds for the visibility assessment were set based on the contribution from two factors: the uncertainty derived directly from the link measurements (EQ. 11), and the estimated uncertainty from the visibility parameterization.

Results

The data for the present study relate to two extreme fog events that took place in the state of Israel. In both cases, visibility dropped to or below several tens of meters, and the events continued throughout the night and the following morning. The thick fog developed to a scale of a few tens of km, covered the southern and central coastal plain and lowland regions of Israel as well as parts of the Sinai Peninsula in Egypt. The extremely low visibility conditions during these fog events led to disruption, cancellations and delays in the flight schedule for the Ben Gurion international airport in Israel.

The region-of-interest for the analysis presented in this example is the central western coastal region (from the Tel-Aviv city area to the Ben Gurion international airport area) where several means for measuring the phenomenon exist. The microwave data used were gathered from tens of commercial MLs operating at frequencies of about 38 GHz in the area that were located in the vicinity of the specialized measuring equipment. Each of the links provided one measurement per day at a O.ldB resolution. The measurements were taken instantaneously and simultaneously across all of the links in the system at prescribed times as reported by the cellular providers. During both events, no rainfall, sleet or snow were measured in the region-of-interest according to the observations of the surface stations.

Event 1

The event started at the late evening and ended at the morning hours of the next day.

A heavy fog front passing through central Israel was recorded by different observation techniques found in the area. At the surface, a ridge from the west with weak westerlies (and a long fetch over the Mediterranean Sea) was accompanied by a deep ridge aloft, which was causing significant subsidence. Since the microwave system that provided the data used for this study recorded measurements at 01:30, this time frame was used as the focal point for the study (all hours are in Universal Time Coordinated).

FIG. 4 shows the location of the different measuring means in the region-of- interest as well as the deployment of the MLs. 88 MLs were located in the region-of- interest, all operating at a frequency of approximately 38 GHz. The links were deployed over 47 different paths, and were installed at elevations between about 5 and about 60 m Above Sea Level (ASL) and between about 10 and about 100 m Above Ground Level (AGL). The links range in length from 100 m to about 3.5 km, and span an area of 5 x 6 km . Three transmissometers, and a professional human observer were located at Ben Gurion airport (41 m ASL). The three meteorological ground stations (5-35 m ASL) are indicated by asterisks. An additional human observer was located at the Beit Dagan ground station (35 m ASL).

According to the measurements of the three regional stations in the observed area, the Relative Humidity (RH), as measured between 01:00 and 02:00, ranged from about 97% to about 100% (with temperature of about +13 °C and wind speed of about 1- 2.5 m/s).

FIGs. 5A-B show visibility assessments obtained for this event. The assessments were carried out between the hours of 15:00 before the event and 12:00 after the event. FIG. 5A shows visibility assessments as registered by human observers at a meteorological station located at the Beit Dagan and at the Ben Gurion airport (see FIG. 4). The assessments were made every 3 hours by the observer at the meteorological station and once an hour by the observer at the airport. Fog was detected between 00:00 to 06:00-07:00, dropping to a minimum of about 100 m (Ben Gurion observer). FIG. 5B shows Meteorological Optical Range (MOR) measurements taken by three transmissometers located at the Ben Gurion airport. The instruments are arrayed over three separate 50 m visual paths at an elevation of 2.5m AGL. FIG. 5B is based on instantaneous measurements at 10 minute intervals. According to these instruments, fog was detected starting from about 22:00 until about 07:00 of the following morning dropping to a minimum of about 50 m.

Each of the links provided one measurement every 24 hours (at 01:30, as stated). The attenuation measurements from the foggy night were compared to those taken on a humid night without fog (according to the records from the different specialized measuring instruments).

During the foggy night of the event, an RSL drop was recorded by numerous MLs, of different lengths, located in the area (at RH of above 95%).

FIGs. 6A-B show the attenuation measurements, as measured by the MLs system during the foggy night of the event (FIG. 6A) and during a humid night without fog (FIG. 6B). Each point in FIGs. 6A-B represents a measurement from a single link, taken at 01:30. The linear fit approximations of the measurement sets are listed at the top of each panel. During the foggy night Pearson correlation r =0.55 was calculated between observed attenuation to link length, with a P-value of less than 0.05 (based on 88 data points). Humidity measurements during the humid night close to the time the attenuation measurements took place were about 65%, about 90% and about 85% at the measuring stations on the Tel-Aviv coast, central Tel-Aviv, and Beit Dagan, respectively. The slope of the graph in FIG. 6A represents the effective attenuation measured in the fog patch, where the y-axis intercept represents the estimated attenuation as a result of antenna wetness. The slope of the graph generated for the non foggy night, as well as the y-intercept tend to zero (based on 68 samples acquired according to the availability of RSL data from the system during that night). Given the high RH and the additional attenuation observed by the multiple MLs, fog was identified as being present in the area.

The estimate of the effective fog induced attenuation parameter a_f , is given by the slope of the resulting plot (FIG. 6A). The estimate for the wet antenna component, , is given by the intercept. A similar plot was created for the non foggy night, where the slope of the resulting graph tends to zero (FIG. 6B).

Given the estimated value of the a_f parameter, the temperature and the MLs frequency, the LWC was estimated using EQ. (5). Then, lower and upper bounds on the range of visibility were derived using EQs. (8)-(l l). The resulting values were 0.71 + 0.1 gr/m and 30 to 70 m, respectively.

Table 1, below lists the results of the ML measurements and the visibility assessments received. The observations listed in Table 1 were made over the same time when the ML measurements were taken, where the hour / time period indicated in parentheses in the respective rows is the period during which the measurement was taken by each mean (the visibility range based on ML measurements indicates the upper and lower bound for the estimate). Temperature and RH measurements were acquired (at 10-minute intervals) by the three ground stations between 01:20 and 01:40. The Ben Gurion and Beit Dagan observers provided visibility estimates once an hour and once every 3 hours, respectively. The MOR measurements are based on 10-minute intervals as acquired by each of the three transmissometers. The LWC, wet antenna and fog induced attenuation values measured by the MLs, are also listed.

Table 1

As demonstrated, the visibility assessments derived from the ML measurements are of a similar order of magnitude as the assessments from the specialized measurement equipment.

Event 2

The event started at the evening and ended at late morning hours of the next day.

A heavy fog front began developing and expanding along the area of Israel's Mediterranean coast. At the surface, a Red Sea Trough with a central axis was moving eastward, allowing for northwesterly flow from the Mediterranean Sea to move into the coastal area. Aloft, a deep ridge was moving eastward.

FIG. 7 shows the location of the different measuring means in the region-of- interest as well as the deployment of the MLs. 58 MLs in the region-of-interest were deployed over 39 physical paths of between 100 m and about 3 km, and spread across an area of aboutl5 x 10 km. The links were installed at elevations of from bout 15 to about 90 m ASL on towers that range from about 5 to about 55 m AGL. The system operates approximately at the 38 GHz frequency range. There were three transmissometers located at Ben Gurion airport (41m ASL) as well as a human observer. Another human observer, as well as a scattermeter were located at the Beit Dagan ground station (35m ASL).

The microwave system that provided the data used for this event recorded measurements at 22:00 and this time frame was therefore as the focal point for the analysis.

The following analysis relates to the area of Beit Dagan station in the proximity of MLs where the measured humidity was from about 90% to about 97% between 21:30 and 22:30 (with a temperature range of 18.5 -19 °C and wind speed of from about 1 to about 3 m/s).

FIGs. 8A-B show visibility and Runway Visual Range (RVR) measurements obtained during this event. The observations were taken between 20:00 before the event and 10:00 in the following day. FIG. 8A shows visibility assessments as registered by the human observers (at the Ben Gurion airport and Beit Dagan station). Observations were taken once an hour by each observer (the observer at the Beit Dagan station estimates between 22:00 to 01:00 of several meters to 100 m, are plotted as 50 m during this time frame). Also shown, are MOR measurements at 1 minute intervals which were acquired by a scattermeter located at Beit Dagan. FIG. 8B shows RVR measurements taken by the three transmissometers deployed at the airport over three different physical paths. The plot is based on instantaneous measurements at 5 minute intervals.

According to these observations, between 21:30 and 07:30 of the following day severe visibility limitations were observed, decreasing to the order of a few tens of meters and less between 22:00 and 01:00.

58 MLs deployed in the observed region over 39 separate paths were used during the event (FIG. 7). The system was spread across an area of approximately 10x15 km , and captured one instantaneous measurement from each link every night (at 22:00, as stated). The measurements taken on the foggy night were compared to those taken during a humid night without fog at the same hour.

FIGs. 9A-B show the attenuation measurements, as measured by the MLs system during the foggy night of the event (FIG. 9A) and during a humid night without fog (FIG. 9B). Each point in FIGs. 9A-B represents a measurement from a single link, taken simultaneously at 22:00. The linear fit approximations of the measurement sets for each night are listed at the top of each panel. The Pearson correlation between observed attenuation and link length during the foggy night was r=0.57 (P- value less than 0.05, based on 58 data points). The RH during the humid night in which there was no additional attenuation (relative to the baseline level), was about 87%, as measured at the Beit Dagan station (at about 22:00). Given the high RH of about 95% and the additional attenuation observed by the multiple MLs during the event, fog was identified as being present in the region-of-interest.

The LWC value was calculated as described above and a value of 0.68 + 0.15 gr/m was obtained for this event. The range of visibility was assessed to be from about 30 to about 70 m.

Table 2 below lists the results of the ML measurements and the visibility assessments received. The observations listed in Table 2 were made over the same time when ML measurements were taken, where the hour / time period indicated in parentheses in the respective rows is the period during which the measurement was taken by each measuring mean. Temperature and RH measurements were acquired by the Beit Dagan ground station between 21:50 and 22: 10 (at 10-minute intervals). Observers provided visibility estimates once an hour. The MOR measurements were taken by the scattermeter at Beit Dagan, in 1 minute intervals. The notation "Med" indicates the median value.

Table 2

B. Dagan Observer [m] Several meters- 100

(22:00- 23:00 h)

Conclusions

The results presented in this study demonstrate the ability of the method and system of the present embodiments to monitor fog, particularly in cases of heavy fog that creates severe visibility limitations, e.g. , visibility of several tens of meters or less.

The liquid water content values calculated according to some embodiments of the present invention from the microwave system measurements match field measurements taken from the literature. The visibility assessments calculated according to some embodiments of the present invention are of the same order of magnitude as the values measured directly by the different visibility measuring instruments and human observers.

In order to reduce measurement errors resulting from various factors, the availability and diversity of multiple measurement sources were utilized. The present inventors were able to derive an estimate for the wet antenna attenuation, and reduced the sources of random error.

Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims.

All publications, patents and patent applications mentioned in this specification are herein incorporated in their entirety by reference into the specification, to the same extent as if each individual publication, patent or patent application was specifically and individually indicated to be incorporated herein by reference. In addition, citation or identification of any reference in this application shall not be construed as an admission that such reference is available as prior art to the present invention. To the extent that section headings are used, they should not be construed as necessarily limiting. REFERENCES

[1] Acker, K., Wieprecht, W., Kalass, D., Moller, D., and Chaloupecky, P.:

Relationship between liquid water content and visibility in low clouds occurred at Mt. Brocken, International Aerosol Conference (IAC), Helsinki, Finland, 29 August- 3 September, 2010.

[2] American Meteorological Society (AMS): glossary of meteorology, 2nd edition, Allen Press, 2000.

[3] Arends, B.C., Kos, G.P.A., Wobrock, W., Schell, D., Noone, K.J., Fuzzi, S., and

Pahl, S.: Comparison of techniques for measurements of fog liquid water content,

Tellus, 44B, 604-611, 1992.

[4] Benjamin, S. G., Devenyi, D., Weygandt, S. S., Brundage, K. J., Brown, J. M.,

Grell, G. A., Kim, D., Schwartz, B. E., Smirnova, T. G., Smith, T. L., and

Manikin, G. S.: An hourly assimilation-forecast cycle: The RUC, Mon. Weather.

Rev., 132, 495-518, 2004.

[5] Croft, P. J., Darbe, D., and Garmon, J.: Forecasting significant fog in southern

Alabama, Natl. Wea. Dig., 19, 10-16, 1995.

[6] Csurgai-Horvath, L., and Bito, J.: Fog attenuation on V band terrestrial radio and a low-cost measurement setup, In Future Network and Mobile Summit, 2010, IEEE,

2010.

[7] Dam, D. A., and Hoang, X. C: Nguyen T.K.O. Photochemical smog introduction and episode selection for the ground-level ozone in Hanoi, Vietnam, VNU Journal of Science, Earth Sciences, 24, 169-175, 2008.

[8] David, N., Alpert, P., and Messer, H.: Technical Note: Novel method for water vapour monitoring using wireless communication networks measurements, Atmos.

Chem. Phys., 9, 2413-2418, 2009.

[9] David, N., Alpert, P., and Messer, H.: Humidity measurements using commercial microwave links, Advanced Trends in Wireless Communications, InTech publications, Croatia, 65-78, 2011.

[10] David, N., Alpert, P., and Messer, H.: The potential of cellular network infrastructures for sudden rainfall monitoring in dry climate regions, Atmos. Res., doi: 10.1016/j.atmosres.2013.01.004, 2013. [11] Dawson, T. E.: Fog in the California redwood forest: ecosystem inputs and use by plants, Oecologia, 117, 476-485, 1998.

[12] Ellrod, G. P.: Advances in the detection and analysis of fog at night using GOES multispectral infrared imagery, Wea. Forecasting., 10, 606-619, 1995.

[13] Ellrod, G. P., and Gultepe, I.: Inferring low cloud base heights at night for aviation using satellite infrared and surface temperature data, Pure Appl. Geophys., 164,

1193-1205, 2007.

[14] Emert, S.E.: Design, construction and evaluation of the CSU optical fog detector,

M.Sc thesis, Colorado State University, Fort Collins, Colorado, 2001.

[15] Gerber, H.: Liquid water content of fogs and hazes from visible light scattering, J.

Climate Appl. Meteor., 23, 1247-1252, 1984.

[16] Goldshtein, O., Messer, H., and Zinevich, A.: Rain Rate Estimation Using

Measurements From Commercial Telecommunications Links, IEEE Trans. Signal

Process., 57, 1616-1625, 2009.

[17] Gultepe, I., and Isaac, G. A.: Aircraft observations of cloud droplet number concentration: Implications for climate studies, Q. J. R. Meteorolog. Soc, 130,

2377-2390, 2004.

[18] Gultepe, I., Miiller, M. D., and Boybeyi, Z.: A new visibility parameterization for warm-fog applications in numerical weather prediction models, J. Appl. Meteor.

ClimatoL, 45, 1469-1480, 2006.

[19] Gultepe, I., Tardif, R., Michaelides, S. C, Cermak, J., Bott, A., Bendix, J., Muller,

M. D., Pagowski, M., Hansen, B., Ellord, G., Jacobs, W., Toth, G., Cober, S. G.:

Fog research: a review of past achievements and future perspectives, Pure Appl.

Geophys., 164, 1121-1159, 2007.

[20] Gultepe I., G. Pearson, J. A. Milbrandt, B. Hansen, S. Platnick, P. Taylor, M.

Gordon, J. P. Oakley, and S. G. Cober: The fog remote sensing and modeling field project. Bull. Amer. Meteor. Soc, 90(3), 341-359, 2009.

[21] Herckes, P., Chang, H., Lee, T., and Collet, Jr., J. L.: Air pollution processing by radiation fogs, Water Air Soil Poll, 181, 65-75, 2007.

[22] Hunt, K. P., Niemeier, J. J., Da Cunha, L., K., Kruger, A.: Using cellular network signal strength to monitor vegetation characteristics, IEEE Geosci. Remote. S., 8,

346-349, 2011. [23] Kenney, J. F. and Keeping, E. S.: Linear regression and correlation. Van Nostrand

Publishers, Princeton, N.J., 252-285, 1962

[24] Klemm, O., Wrzesinsky, T. and Scheer, C: Fog water flux at a canopy top: direct measurement versus one-dimensional model, Atmos. Environ., 39, 5375-5386,

2005.

[25] Ku, H.H.: Notes on the use of propagation of error formulas. J. Res. Nbs. C. Eng.

Inst, 70, 263-273, 1966.

[26] Kunkel, B.: Parameterization of droplet terminal velocity and extinction coefficient in fog models, J. Appl. Meteor. Climatol, 23, 34-41, 1984.

[27] Leijnse, H., Uijlenhoet, R., and Strieker, J.: Rainfall measurement using radio links from cellular communication networks, Water Resour. Res., 43, W03201, doi:

10.1029/2006WR005631, 2007a.

[28] Leijnse, H., Uijlenhoet, R., and Strieker, J.: Hydrometeorological application of a microwave link: 1. Evaporation. Water Resour. Res. 43, W04416, doi:

10.1029/2006WR004988, 2007b.

[29] Leijnse, H., Uijlenhoet, R. and Strieker, J.: Microwave link rainfall estimation:

Effects of link length and frequency, temporal sampling, power resolution and wet antenna attenuation, Adv. Water Resour, 31, 1481-1493, doi: 10.1016/j.advwatres.2008.03.004, 2008.

[30] Lensky, I. M. and Rosenfeld, D.: Clouds-Aerosols-Precipitation Satellite Analysis

Tool (CAPSAT), Atmos. Chem. Phys., 8, 6739-6753, doi: 10.5194/acp-8-6739-

2008, 2008.

[31] Liebe, H. J., Manabe, T., and Hufford, G. A.: Millimeter-wave attenuation and delay rates due to fog/cloud conditions, IEEE T. Antenn. Propag., 37(12), 1617- 1612, 1989.

[32] Messer, H., Zinevich, A., and Alpert, P.: Environmental monitoring by wireless communication networks, Science, 312, 713, 2006.

[33] Meyer, M. B., J. E. Jiusto, and G. G. Lala.: Measurements of visual range and radiation-fog (haze) microphysics, J. Atmos. Sci., 37, 622-629, 1980.

[34] Niu, S.J., Lu, C.S., Zhao, L.J., Lu, J.J, and Yang, J.: Analysis of the microphysical structure of heavy fog using a droplet spectrometer: a case study, Adv. Atmos.

Sci., 27(6), 1259-1275, doi: 10.1007/s00376-010-8192-6, 2010b. [35] Neter, J., Kutner, M. H., Nachtsheim, C, and Wasserman, W.: Applied Linear Statistical Models, 4th Edition, McGraw Hill, Inc., 640-645, 1996.

[36] Oliver, J.: Fog harvesting: An alternative source of water supply on the West Coast of South Africa, GeoJournal, 61, 203-214, 2004.

[37] Overeem, A., Leijnse, H., and Uijlenhoet, R.: Measuring urban rainfall using microwave links from commercial cellular communication networks, Water Resour. Res., 47, W12505, doi: 10.1029/2010WR010350, 2011.

[38] Pagowski, M., Gultepe, I., and King, P.: Analysis and modeling of an extremely dense fog event in southern Ontario, J. Appl. Meteor., 43, 3-16, 2004.

[39] Pinnick, R. G., Hoihjelle, D. L., Fernandez, G., Stenmark, E. B., Lindberg, J. D., and Hoidale, G. B.: Vertical structure in atmospheric fog and haze and its effects on visible and infrared extinction, J. Atmos. Sci., 35, 2020-2032, 1978,

[40] Pisano, P. A., Goodwin, L. C, and Rossetti, M. A.: U.S. highway crashes in adverse road weather conditions, Proceedings of the 88th Annual American Meteorological Society meeting, New Orleans, L.A., U.S. A, 20-24 January, 1-15, 2008.

[41] Rayitsfeld, A., Samuels, R. Zinevich, A., Hadar, U., and Alpert, P.: Comparison of two methodologies for long term rainfall monitoring using a commercial microwave communication system, Atmos. Res., 104-105, 119-127, 2011.

[42] Rec. ITU-R P.838-2: Specific attenuation model for rain for use in prediction methods, 2004.

[43] Rec. ITU-R P.676-6: Attenuation by atmospheric gases, 2005.

[44] Rec. ITU-R P.840-4: Attenuation due to clouds and fog, 2009.

[45] Schwarzenboeck, A., Mioche, G., Armetta, A., Herber, A., and Gayet, J.-F.:

Response of the Nevzorov hot wire probe in clouds dominated by droplet conditions in the drizzle size range, Atmos. Meas. Tech., 2, 779-788, doi: 10.5194/amt-2-779-2009, 2009.

[46] Tago., H, Kimura, H., Kozawa, K., and Fujie, K.: Long-term observation of fogwater composition at two mountainous sites in Gunma Prefecture, Japan, Water

Air Soil Pollut, 175, 375-391, 2006. [47] Terradellas, E., and Bergot, T.: Comparison between two single-column models designed for short-term fog and low-clouds forecasting, Fisica Tierra, 19, 189-203, 2007.

[48] Tomasi, C, and Tampieri, F.: Features of the proportionality coefficient in the relationship between visibility and liquid water content in haze and fog,

Atmosphere, 14, 61-76, 1976.

[49] Wichmann, H. E., Mueller, W., Allhoff, P., Beckmann, M., Bocter, N., Csicsaky,

M. J., Jung, M., Molik, B., and Schoeneberg, G.: Health effects during a smog episode in West Germany in 1985, Environ Health Perspect, 79, 89-99, 1989.

[50] World Meteorological Organization (WMO): Guide to meteorological instruments and methods of observation, 7th edition, ISBN 978-92-63-10008-5, 2008.

[51] Wrzesinsky, T., and Klemm, O.: Summertime fog chemistry at a mountainous site in central Europe, Atmos. Environ., 34, 1487-1496, 2000.

[52] Zinevich, A., Alpert, P., and Messer, H.: Estimation of rainfall fields using commercial microwave communication networks of variable density, Adv. Water

Resour., 31, 1470-1480, 2008.

[53] Zinevich, A., Messer, H., and Alpert, P.: Frontal rainfall observation by a commercial microwave communication network, J. Appl. Meteor. Climatol., 48,

1317-1334, 2009.

[54] Zinevich, A., Messer, H., and Alpert, P.: Prediction of rainfall intensity measurement errors using commercial microwave communication links, Atmos. Meas. Tech., 3, 1385-1402, 2010.

Claims

WHAT IS CLAIMED IS:

1. A method of estimating a level a hydrometeor, comprising:

obtaining signal level data from a plurality of free-space electromagnetic communication links distributed over a region;

analyzing attenuation levels associated with said links as a function of path lengths associated with said links, so as to extract at least a first parameter which vary with said path lengths and a second parameter which generally does not vary with said path lengths; and

estimating a level of the hydrometeor, responsively to said analysis.

2. The method according to claim 1, wherein said analyzing comprises performing a linear fit to provide a slope and an intercept, and wherein said first parameter is said slope and said second parameter is said intercept.

3. The method according to any of claims 1 and 2, further comprising repeating said estimation for each of at least a few of said links so as to map the hydrometeor over said region according to geographic locations of said links.

4. The method according to any of claims 1 and 2, further comprising indentifying a presence of the hydrometeor if said attenuation levels are above a baseline level for at least a few of said links.

5. The method according to any of claims 1 and 2, wherein said hydrometeor comprises at least fog.

6. The method according to claim 5, wherein said analyzing comprises performing a linear fit to provide a slope and an intercept, wherein said first parameter is said slope and said second parameter is said intercept, and wherein said estimating said level comprises linearly correlating said slope to said level.

7. The method according to claim 5, further comprising obtaining additional data pertaining to at least one hydrometeor other than fog, and correcting said estimation based on said additional data.

8. The method according to claim 5, further comprising obtaining temperature data, and correcting said estimation based on said temperature data.

9. The method according to claim 5, further comprising defining a baseline signal level, independently for each link of said plurality of links, so as to correct for water vapor induced attenuation.

10. The method according to any of claims 1 and 2, further comprising estimating liquid water content based on said first parameter.

11. The method according to claim 10, further comprising estimating a visibility level, based on said liquid water content.

12. The method according to any of claims 1-9, further comprising estimating liquid water content based on said first parameter, and optionally estimating a visibility level, based on said liquid water content.

13. The method according to any of claims 1 and 2, wherein said electromagnetic communication links are microwave links.

14. The method according to claim 13, wherein a characteristic frequency of said microwave links is from about 1 GHz to about 1000 GHz.

15. The method according to any of claims 1 and 2, further comprising calculating a first set of attenuation levels corresponding to links associated with path length below a predetermined threshold, and using said first set of attenuation levels for correcting at least one of said first and said second parameters.

16. The method according to claim 15, wherein said predetermined threshold equals at most 500 meters.

17. The method according to any of claims 1-14, further comprising calculating a first set of attenuation levels corresponding to links associated with path length below a predetermined threshold, and using said first set of attenuation levels for correcting at least one of said first and said second parameters.

18. A method of identifying a hydrometeor, comprising:

obtaining signal level data from a plurality of free- space electromagnetic communication links distributed over a region;

calculating a first set of attenuation levels associated with a first set of links characterized by path lengths below a predetermined threshold, and a second set of attenuation levels associated at least with links other than said first set of links;

processing attenuation levels of said second set using attenuation levels of said first set, to provide processed attenuation levels; and

using said processed attenuation levels for identifying the hydrometeor.

19. The method according to claim 18, wherein said processing comprises subtracting attenuation levels of said first set from attenuation levels of said second set.

20. The method according to any of claims 18 and 19, further comprising estimating a level of the hydrometeor based on said processed attenuation levels.

21. The method according to any of claims 18 and 19, further comprising indentifying a presence of the hydrometeor if said attenuation levels are above a baseline level for at least a few of said links.

22. The method according to any of claims 18 and 19, wherein said hydrometeor comprises at least fog.

23. The method according to claim 22, further comprising obtaining additional data pertaining to at least one hydrometeor other than fog, and correcting said identification based on said additional data.

24. The method according to claim 22, further comprising obtaining temperature data, and correcting said identification based on said temperature data.

25. The method according to claim 22, further comprising defining a baseline signal level, independently for each link of said plurality of links, so as to correct for water vapor induced attenuation.

26. The method according to any of claims 18 and 19, further comprising estimating liquid water content based on said processed attenuation levels.

27. The method according to claim 26, further comprising estimating a visibility level, based on said liquid water content.

28. The method according to any of claims 18-25, further comprising estimating liquid water content based on said processed attenuation levels, and optionally estimating a visibility level, based on said liquid water content.

29. The method according to any of claims 18 and 19, wherein said electromagnetic communication links are microwave links.

30. The method according to claim 29, wherein a characteristic frequency of said microwave links is from about 1 GHz to about 1000 GHz.

31. The method according to any of claims 18 and 19, wherein said predetermined threshold equals at most 500 meters.

32. A system for identifying a hydrometeor, comprising:

an input unit for obtaining signal level data from a plurality of free- space electromagnetic communication links distributed over a region; and

a processing unit configured for executing the method according to any of claims 1 and 2.

33. A system for identifying a hydrometeor, comprising:

an input unit for obtaining signal level data from a plurality of free- space electromagnetic communication links distributed over a region; and

a processing unit configured for executing the method according to any of claims

1-31.

34. A computer software product, comprising a computer-readable medium in which program instructions are stored, which instructions, when read by a data processor, cause the data processor to receive signal level data from a plurality of free- space electromagnetic communication links distributed over a region, and execute the method according to any of claims 1 and 2.

35. A computer software product, comprising a computer-readable medium in which program instructions are stored, which instructions, when read by a data processor, cause the data processor to receive signal level data from a plurality of free- space electromagnetic communication links distributed over a region, and execute the method according to any of claims 1-31.