GB2529271A - Meteorological hazard identification apparatus, moving craft and methods - Google Patents

Abstract

A meteorological hazard identification apparatus which performs a method comprising receiving a plurality of measurement sample tracks, each of the measurement sample tracks having been generated by a moving craft, such as an aircraft, using a measurement device mounted on the craft. Each of the measurement sample tracks comprises a plurality of captured samples of one or more meteorological parameters, such as particle concentration, measured with respect to geographical co-ordinates providing a location of the captured sample. The method includes storing the plurality of sample tracks into a data store, retrieving each of the measurement tracks from the data store, combining the plurality of measurement tracks, to form, with respect to mapping information, a representation at geographical locations within a region, of a variation in the one of more meteorological parameters with respect to displacement within the region, and generating a representation of the variation of the one or more meteorological parameters with respect to displacement within the region with respect to a map of the Earth for access by one or more devices for display to users. Also disclosed is a method of protecting an aero engine in accordance with the hazard identified.

Description

METEOROLOGICAL I IAZARD IDENTIFICATION APPARATUS, MOVING CRAFT AN I)

METHODS

BACKGROUND

Field of Disclosure

The present. disclosure relates to meteorological hazard identification apparatus for forming an adaptive assimilation platform for generating a representation of meteorological hazards within a region of the Earth such as in a region of the Earth's airspace and methods of identifying meteorological hazards.

Description of Related Art

The "background" description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it is described in this background section, as well as aspects of the description which may not otherwise quality as prior art at the time of filing, are neither expressly or impliedly admitted as prior art against the present invention.

Meteorological hazards are a routine component of flight operations in the aviation industry. These hazards include: airframe icing, ice particle aeroenginc icing, turbulence, wind shear, convection, lightning, volcanic ash, and mineral dust. Safe flight operations are reinforced by the availability of timely and accurate observational infonnation on the spatial extent of hazards, and how the hazard is predicted or forecast to evolve over time.

Aircraft airspeed and temperature pitot probes are hollow and require a flow of air through the device.

These probes are heated to avoid blockages related to ice accretion if the aircraft passes through a cloud of supercooled liquid water. However, if the aircraft passes through a cloud of small ice crystals, the heated probes can cause melting of the ice crystals, which melt inside the probe. In some cases (high number concentration of small ice crystals), the heat removed by the enviromnent (i.e., through ice crystal melting) can exceed the capability of the heating elements to supply heat. In the case of pitot tubes, ice crystals may melt at the inlet and form a flow of liquid water into the sensing element. This water may then re-freeze inside the pitot tube and reduce the diameter of the pitot tube. This causes a reduction of the air flow through the device. In the case of air temperature measurements, the reduction of air flow through the device causes an apparent temperature increase that maybe interpreted as loss of altitude or engine power. In the case of air speed measurements, the reduction of air flow through the device by acereled ice causes a decrease in total pressure that may be interpreted as loss of airspeed or engine power. In Europe, probes used to measure airspeed, altitude and temperature on aircraft are tested and certified according to specific European Aviation Safety Agency (EASA) rules covering altitude and temperature envelopes for continuous and intermittent maximum icing conditions for supercooled liquid droplets. There are currently no requirements for ice crystal testing. Icing of the pitot tubes on the Air France Flight 447 Airbus A330 aircraft which crashed on 1 June 2009 was the cause of erroneous airspeed and altitude measurements that created confusion on the flight deck and the following errors.

Since the 1990s. there have been an increasing number of aeroengine power loss incidents associated with convective weather at al1itudes above (i.e., colder than) classical icing conditions. The problems occur when small ice crystals (I Os microns in diameter) pass into the aeroengine core in high concentrations, which may partially melt, accrete on surfaces in the compressor section of the turbine, and cause power loss, or cause damage to turbine components following shedding of ice from the compressor components that pass backwards through the engine into the turbine section. The industry coined the tenn ice particle icing' to discriminate the process from airframe icing related to passage through a mixed-phase cloud containing supereooled liquid water droplets and ice crystals.

SUMMARY OF THE DISCLOSURE

According to one example embodiment of the present technique, there is provided a meteorological hazard identification apparatus which performs a method of identif'ing meteorological hazards. The method comprises receiving a plurality of measurement sample tracks, each ofthe measurement sample tracks having been generated by a moving craft using a measurement device mounted on the craft and each of the measurement sample tracks comprising a plurality of captured samples of one or more meteorological parameters measured with respect to geographical co-ordinates providing location and time stamps of the captured sample. The craft may he an airborne craft such as an aircraft, each of the measurement tracks being gencraled by a different aircraft, may he a sea-borne craft such as a ship, each of the measurement tracks being generated by a different ship, or a land-borne craft such as an automobile, truck or a train, each of the measurement tracks being generated by a different automobile, truck or train. The method includes storing the plurality of sample tracks into a data store, retrieving each of the measurement tracks from the data store, combining the plurality of measurement tracks, to fonn, with respect to mapping information, a representation at geographical locations within a region, of a variation in the one of more meteorological parameters with respect to displacement within the region, and generating a representation of the variation of the one or more meteorological parameters with respect to displacement within the region with respect to a map of the Barth for access by one or more accessing devices for display to users.

According to another example embodiment of the present technique, there is provided a meteorological hazard identification apparatus comprising a receiver for receiving data comprising a plurality of measurement sample tracks, each of the measurement sample tracks having been generated by an airborne craft using a measurement device mounted on the craft and each of the measurement sample tracks comprising a plurality of captured samples of one or more meteorological parameters measured with respect to geographical co-ordinates providing location and time stamps of the captured sample within the Earth's airspace and at the altitude of the craft. The captured samples of meteorological parameters may include at least one of particle size, particle concentration in respect of number/mass/volume and phase or type being liquid water, ice, dust, volcanic ash, with respect to atmospheric parameters including temperature, pressure and water vapour content. A data processor is configured to store the plurality of sample tracks into a data store in accordance with a predetermined format, and to retrieve each of the measurement tracks from the data store, and to combine the plurality of measurement tracks to form with respect to mapping information a representation of airspace showing geographical locations within The Earth's airspace at determined altitudes and determined time of detected airborne particulatcs. An access interface configured to generate a representation of the detected airborne particles with respect to an airspace map of the Barth's airspace for access by one or more client devices for display to users.

Embodiments of the present technique can provide an arrangement for receiving samples of airborne particles produced using a measurement device for measuring meteorological parameters such as for example a light backseatter measurement device, which may be installed on each of a plurality of airborne craft which are travelling along a flight path within an airspace which is of interest for display to assist in navigation Embodiments of the present technique can provide a moving craft comprising a geographical measurement device for generating data representing geographical co-ordinates of a location of the moving craft and a meteorological measurement device configured to generate measurement data comprising one or more measurement sample tracks, each of the measurement sample tracks comprising a plurality of captured samples of one or more meteorological parameters measured with respect to the geographical co-ordinates providing a location and time stamps of the captured sample. The craft includes a transmitter configured to transmit the measurement sample tracks to a meteorological hazard identification apparatus, the meteorological hazard identification apparatus being configured to generate a representation of the variation of the one or more meteorological parameters with respect to displacement within the region with respect to a map of the Barth for access by one or more accessing devices for display to users, and a controller configured to control the transmitter to transmit the measurement sample tracks to the meteorological hazard identification apparatus wherein the controller is configured to control the meteorological measurement device to generate the captured samples of one or more meteorological parameters measured periodically, and if a difference between one or more successively captured samples is below a predetermined threshold, then not transmitting the one or more successively captured samples as part of the measurement track.

The foregoing paragraphs have been provided by way of general introduction, and are not intended to limit the scope of the following claims. The described embodiments, together with further advantages, will be best understood by reference to the following detailed description taken in coniunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete appreciation of the disclosure and many of the attendant advantages thereof will be readily obtained as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings wherein like reference numerals designate identical or corresponding parts throughout the several views, and wherein: Figure 1 provides a graphical illustration of a system for identif'ing meteorological hazards according to the present technique; Figure 2 is a graphical representation of discrimination of samples of different particle types such as ice, volcanic ash and dust, determined using a hackscatter cloud probe with polarisation detector provided from (K. Beswick et al 2014 12011) as an example of a type of atmospheric data that may be captured with a sensor on-board the aircraft; Figure 3 is a schematic block diagram showing components which are part of an example system for identifring aviation meteorological hazards according to the present technique; Figure 4a is a graphical representation of cloud particle measurements taken on a commercial ifight between London Heathrow and New York JFK airports, with measurement points indicated by grey circles and cloud encounters, dark grey markers indicating ice crystals and light grey circles indicate that ice crystals were encountered at levels below a threshold quantity for aeroengine operation; Figure 4h is a graphical representation illustrating a vertical profile of cloud particle number concentration generated as an aircraft left a departure airport; and Figure 4c is a graphical representation illustrating a. vertical profile of cloud particle average size generated as the aircraft left the departure airport during an ascent phase of flight; Figure 5 is a schematic block diagram representing segments of an example of a system for identifying meteorological hazards for aircraft, ship, or terrestrial vehicle according to the present teclmique, the segjnents being identified as aircraft based, space based and ground based; Figure 6 is a schematic block diagram representing components of an alternative representation of an example of a system for identif'ing meteorological hazards according to the present technique; Figure 7 isa schematic block diagram representing components parts of a meteorological hazard identification device for forming an adaptive assimilation platform according to the presem technique; Figure 8 is a graphical representation of a data assimilation process in which a prediction model is mapped to measured data points of measurement tracks; Figure 9 is a schematic representation of the meteorological hazard identification device of Figure 7; Figure 10 is a flow diagram representing a. method of operation of the meteorological hazard identification device according to the present technique; Figure 11 is a flow diagram representing a communications protocol for transmitting meteorological hazard map information from a ground station to a mobile platform or segment (airborne, maritime, or terrestnal mobile); Figure 12 is a flow diagram representing a communications protocol for transmitting meteorological measurement data from a mobile platfonn (airborne, maritime or land mobile) to a ground station; and Figure 13 is a flow diagram representing a communications protocol for generating measurement data for measurement tracks that can be used to generate meteorological hazard map information (for an airborne application of the present technique).

DETAITAILD DESCRIPTION 01? TIlE EMBODIMENTS

The following section describes the application of the present technique to an airborne craft. It should he noted that the present technique is equally applicable to the maritime and land mobile crafts.

At present, the primary method of communication bcl.wcen pilots and air traftic control (ATC) is voice over radio (VOR), either using veiy high frequency (VHF) for line-of-sight communication, or high frequency (HF) for long distance communication. Some of the issues related to using VOR communication include: aircraft have a fixed number of available frequency channels so as air traffic increases the available radio channels for VOR may become congested; and ATC control towers operate VOR communication on (a) predefmed channel(s) and there is a time demand of>lOs seconds to complete a single exchange between ATC and a pilot of a single aircraft. Therefore, capacity issues are quickly reached as the number of aircraft communicating with ATC reaches a threshold determined by the time taken to deal with each aircraft.

Controller-pilot data link communications (CPDLC) is technology that allows Alt at the surface to comnrunicatc with pilots in the air using a text-based data-link. Through this method, ATC can send instructions to pilots that may include flight level assignments, course deviations, route changes and clearances, speed assignments, radio frequency assignments, and other requests for information. There are 2 implementations of CPDLC: (1) FANS-i/A system primarily used by wide-bodied jets over oceanic routes, which implements Aircraft Communications Addressing and Reporting System (ACARS); and (2) European ATN/CPDLC system that uses VDL Mode 2 networks provided by ARINC and SITA.

ACARS is a standard digital data-link system used for transmission of short messages between aircraft and ground stations using a.irband radio or satellite, The entire system comprises hardware elements at the surface and on the aircraft, and includes a data-link service provider (e.g., St IA and ARINC). The system transmits text messages via, a. central processing location. AC.ARS iuterfaces with the flight management systems in the cockpit and can be used to send updated weather infonnation up to the aircraft while in flight. ACARS may also be used to scud engine and airframe health information from the aircraft to the surface, in addition to information on faults and other abnormalities. Flight crews may send and receive basic messages (e.g., weather information, flight clearance or status). ACARS uses VHF where available (range -2O0 run), HF or satellite assets such as the Intnarsat Data-2 (Classic Acro) service.

The Aircraft Meteorological Data Relay (A'mAR) observing system is a subcomponent of the WTVK) Global Observing System that collects, processes and transmits meteorological data from sensors on hoard the global fleet of commercial aircraft. Aircraft carry a suite of sensors that measure static and total air pressure (pitot-static head), total air temperature (immersion thermometer probe), and 3-D acceleration (inertial reference platform). Other relevant measurements include: relative humidity (solid state sensor), aircraft pitch (flow angle sensor) and the presence of ice on the airframe. Atmospheric turbulence may be determined: based on rapid changes in vertical acceleration measured using the inertial navigation system; as a derived vertical gust; or as an index related to eddy dissipation rate. Maximum measured vertical acceleration is routinely related to the severity of turbulence, but this also depends on altitude and airspeed, aircraft weight, and the nature of turbulence. Airframe icing may he measured using capacitive or mechanical sensors attached to the aerofoil. These data are transmitted to ground stations using satellite or telTestrial radio links via ACARS, and relayed to national meteorological offices where it is used for weather forecasting and climate studies. While these data are already used in global weather forecast models, there is not a tailored service available for individual users. Furthermore, there currently arc not any measurements made directly of cloud particles.

The Single European Sky ATM Research (SESAR) project was established in 2004 to guide the modcruisatiou of the European air traflic control system. The aim is to enhance coordination of surface and airborne systems to increase safety and capacity, and to coordinate between civil and military technologies. The major objectives are to improve surface to air coordination and to develop a 4-D trajectory management system.

IRIS is a project funded by the European Space Agency under element 10 of the ARTES programme and will supply a validated satellite-based communication solution for the European ATM System. The programme will speci' system design and communications technical standards according to the requirements defined through SESAR activities, and will develop and deploy infrastructure for validation of end-to-end performance of the new satellite-based air-ground communication system for Air Traffic Management. A draft of the updated communications standard (ANFARES) was released in 2013.

As indicated above, embodiments of the present technique can provide an arrangement for combining SO different measurement samples of at least particle density to generate a predicted dispersion of particles.

Accordingly embodiments of the present technique can be applied to link flight planning done at the surface with operational air traffic management through the provision of best-available observational and forecast information. Sensors carried by aircraft can provide observational information on exposure to ) either known hazards, or previously unknown hazards along the flight path, which will allow the pilot to make a reactive decision to reduce the risk associated with the hazard. An ability to uplink graphical synoptic-scale forecast and observation products, and downlink observational data from in-flight aircraft, leads to an enhanccd hazard situational awarcncss. forceasting and "now-casting", to reinforce proactivc dccision making during managcment of aviation hazards.

In the wakc of the Air France flight 447(1 June 2009), Malaysian Airlines flight 17(17 July 2014) and AirAsia Flight 8501 (28 December 2014) incidents, flight operations maybe required to make greater use of satellite communications. It follows that the development of a situational awareness system based around satellite communications would complement current efforts to advance data communication capabilities.

The embodiments of the present technique can provide an arrangement in which a meteorological hazard identification apparatus forms an adaptive assimilation platform for generating a representation of air-, sea-or land-space of the Barth where aircraft typically fly which, for example, shows regions or areas in which a concentration or density of particles of a predetermined nature exceed a predetermined maximum. The generated representation of the air-, sea-or land-space of the Barth can be in the form of a hazard map created by the adaptive assimilation platlbnn, which is time variable based on the underlying meteorological forecast model being used. Accordingly, for the example of airborne meteorological hazards, the time variable meteorological forecast can be provided for an airline planning facility, an aircraft pilot, and air traffic control to have a synchronized representation of the hazard map.

An example illustration of die present technique is showing in Figure 1.

Figure 1 provides an example of a system for collecting and generating hazard map infhrniation for aviation. Other applications of the present technique are in the maritime and land domains. In Figure 1.

an aircraft A is flying along a flight, path FP above the Barth ft According to a conventional arrangement the aircraft A is arranged to transmit and receive data via a satellite S which is relayed to a ground station (1 in accordance with a known protocol.

According to the present technique the aircraft A includes an atmospheric sensing detector ASD. In one example the aircraft A includes a light scattering type detector LSTD mounted on the aircraft A. The ba.ckseatter cloud particle detector with polarization, BCP-D [20J is an example of a LSTD manufactured by Droplet Measurement Technologies. The LSTD is one example of possible atmospheric hazard sensors on-board the aircraft whereas in other examples a generic multi-dimensional atmospheric sensor device may be installed on-board the aircraft. As shown in the example of Figure 1, an atmospheric sensing device (ASD) is installed on board the aircraft for rapid and accurate detection of particles of ash, dust, ice cnjstais and water vapour to determine their concentration. Other aviation hazards may be discriminated, for example, clear air turbulence, lightning, wind shear, heavy precipitation, etc. According to an example of the present technique an end-to-end system can be provided which supports situational awareness of natural aviation hazards, and the associated service offering that links to operational flight planning and flight operations. The system assimilates aircraft-mounted sensor measurements. Earth observation satellite (EOS) measurement products, forecast model products, and generates advanced forecast and now-cast' products. Communication between airborne platforms and the surface is two-way and directed through the existing aeronautical communications system that may include high bandwidth satellite telecommunications, or other terrestrial solutions if available. The sensor data collected on-board the aircraft may be used for real-time hazard detection and can also be used as observational constraints for initialising forecast models.

The system involves a number of space-based, aircraft-based and snrface-based assets including: communications satellites (SalCom), FOS, global positioning satellites (GPS), aircraft and associated systems, surface-based communications infrastructure and surface-based information technology infrastructure. The combined system can provide a stream of products to a user interface, that can be accessed using a personal computer or tablet, or directly through the avionics system of an aircraft, The overall service offering includes: * Generation and provision of near real-time situational awareness data products, containing near-real-time updates on flight hazard information; * Observational products (EOS, aircraft-sensor, pilot reports, other meteorological); o Hazard forecast / "now-cast" products; and o Aircraft location products (by nature of the geo/time-referenced data products).

A system diagram of component embodiment of the present technique is shown in Figure 3. Tn Figure 3 the aircraft A includes an AS!) and therefore is arranged to periodically measure properties of samples of S particles within the atmosphere of the Earth as the aft-craft flies along a flight path FP. The aircraft A is arranged to transmit data representing the sample performed by the atmospheric particle sensor to satellites Si, S.2. In accordance with a conventional arrangement the satellites SI, Si transmit the data to ground stations G.l, G.2. The ground stations are provided with an interface to a receiving interface of a receiver 39 which forms part of a meteorological hazard identification device 37 according to the present technique. The meteorological hazard identification device 37 also includes a server which forms a database DB as well as a processor 50 and a presentation interface 44.

Although Figure 3 focuses on aviation hazards and contains an airborne craft, which generates data measuring meteorological hazards, as mentioned above, embodiments of the present technique can also be applied to oilier applications including maritime craft and land crafts. Furthermore as mentioned above, other meteorological sensors could he used other than an atmospheric particle sensor, which is one example of aviation hazard sensor on-board an aircraft.

In accordance with the present technique the processor 50 combines measurements received from a plurality of aircraft which perform measurement of tracks along the flight path ofthe aircraft Data.

representing the measurement tracks are transmitted to the satellites S. I. 5.2 and to the receiving interface 39 via, the ground stations GA, G.2. The processor 50 controls the storage of the data comprising the measurement track samples into the database DB in accordance with a predetermined format. The processor 50 then combines the measurement tracks received from a plurality of different aircraft A and forms fAte measurements into a predicted forecast of particles along flight paths of aircraft withrn a region of the Earth's airspace. This is achieved through use of the measurement data provided by sensors to validate model predictions of quantities of interest. The measurement data of airborne samples are used to provide the "truth" and the model source term can he adjusted accordingly, by mnning the model in reverse and then forward again, to reduce a mismatch between observed particle concentrations and predicted particle concentrations. This is described in more detail below. The combined measurement tracks are used therefore to fonn predictive areas or regions to he avoided which are published by a presentation server 50 for access by client devices 44 which present the areas for avoidance to users of the device 44 with respect to a map of the Earth's airspace through which aircraft are to fly. An example of such a graphical representation is shown in Figure 4a. Figure 4a provides a graphical representation of cloud particle measurements taken on a commercial Eight between London Heathrow and New York JFK airports. Measurement points are indicated by grey circles and cloud encounters are indicated by coloured markers. Dark grey markers indicate that ice crystals were encountered at levels above a threshold required for acrocngine protection system operation. Light grey circles indicate that ice crystals were encountered at levels below a threshold quantity for aeroengine operation. Figure 4h is a. graphical representation illustrating a vertical profile of cloud particle number concentration generated as the aircraft left the departure airport during the ascent phase of flight used for Air Traffic Management at an aerodrome. Individual cloud layers can be discriminated based on particle concentration peaks. These vertical profiles would be generated for each particle type (supcrcoolcd liquid waLer. ice, volcanic ash, dust). Figure 4c is a further example providing a graphical representation illustrating a vertical profile of cloud particle average size generated as the aircraft left the departure airport during the ascent phase of flight used for Air Traffic Management at an aerodroma As will be appreciated from the example diagrams which are provided by Figures 4a, 4h and 4e according to embodiments of the present technique airhourne hazard information providing a representation of the variation of the one or more meteorological parameters with respect to displacement within region with respect to a map of the Earth can be used in combination with a current location of a moving craft to control propulsion devices on the craft. Therefbre for the example of an aircraft which is adapted to receive the hazard information generated by the meteorological hazard identification information according to the present technique, the hazard information can be used to control the engines of the aircraft in accordance with a location of a hazard. For example some aeroenginc manufactures provide a facility for increasing an operating temperature of the aeroengine in response to a detecting of a meteorological hazard such as ice crystals, whereas others provide an additional vent as well as running the aeroengine at a higher operating temperature. T-Towever by collecting sample tracks generated by one or more aircraft from which the hazard information can he generated and transmitted to an aircraft, areas of hazard can be identified and where for example a particle size of ice crystals exceeds a predetermined size or density then the aeroengine can be turned off or adjusted in this region. Accordingly an aircraft which does not itself have any on board sensors can take advantage of the meteorological hazard information to control its aeroengines based on its location to protect its engines, if the protection measure includes adjusting the operation of the aeroengine to burn more fuel then fuel economy can be improved because the protective measure is only employed where it is needed.

A more detailed presentation of functional components a system embodying the present technique is showing in FigureS, 6 and 7, for the example of an airborne hazards for aviation safety, but it will be appreciated that other examples include applications to maritinie hazards and craft and land based hazards and craft.

As shown in Figure 5, an aircraft A includes sensors 1 for measuring atmospheric parameters, a GPS satellite receiver 2 For generating location and time infomiation representing the location and time of ihe airspace where measurement samples are taken. A network router and interfaces 3 provide a communications network for providing a facility for communicating between the different components on the aircraft A, a microprocessor 4 running numerical code for handling sensor data and interpreting hazards and attaching location and time tags to the sensor data, and an electronic storage device 5 for recording measurement data. An adaptive router 6 is provided to switch between different communications channels, which may he provided by a satellite communications transceiver 7 including satellite antenna and associated interfaces and a teiTestrial radio-link communications device 8, wInch includes radio antenna. and associated interfaces. A user interface 9 is provided on personal computer or tablet for optionally controlling and monitoring the measurement gathering process along the flight path to produce a measurement track.

In space orbit around the Earth a satellite 10 provides a satellite communications facility for communicating data transfer between airborne platforms A in the atmosphere and ground segment U at the Earth's surface. Furthermore the navigation signals of UPS satellites 11 are used by the UPS receiver 2 to measure the location of the airborne plalfoun. Data from Earth observation satellites 12 containing properties of the geosphere and atmosphere is received by the ground segment Ci for processing by the adaptive assimilation platform 20.

On the ground, as shown in Figure 5 a terrestrial communications link is maintained between radio-link ground station 13 in the ground segment C and radio link communications terminal S on-board the airborne platform A. A complementary SatCom link is maintained between the SatCom ground station 14 in the ground segment Ci and SatCom terminal 7 on-board the airborne platfonn A via conmiunications satellite 10. EQS data downlink station 15 receives data from [OS 12. A terrestrial data network 16 such as for example an Internet is provided, which forms a communications network between the radio-link ground station 13, the satellite communications ground station 14 and the Earth observation down-link station 1 5 and the adaptive assimilation platform 20. Also provided on the ground are sensors 17 which are provided on platforms measuring atmospheric parameters, servers running computer forecast models 18 of atmospheric parameters and/or aviation hazards, servers running meteorological observational databases 19, a meteorological hazard identification and mapping device which may comprise in one example a server(s) running an adaptive assimilation platform. The adapted, assimilated and mapped hazard data is sent and presented to the user via the user interface 21, providing a user with a facility for viewing the particle concentration or oilier hazard data within a region of the Earth's airspace of interest.

According to the functional block diagram shown in Figure 5 and 6, an aircraft A, includes sensors which provide measurements of meteorological parameters (such as temperature, pressure, water content), cloud particle characteristics, and atmospheric composition, so there may be multiple meteorological sensors on a given airborne platfomi 1, The UPS receiver 2 is used to measure the aircraft location and retrieve UPS time, used to synchronise all measurements. Sensor and GPS data are transmitted via the router 3 to the microprocessor 4, which creates a georeferenced and time-stamped data matrix for each parameter measured 26 and saves to the electronic storage media 5. As already mentioned, other applications include land based meteorological hazards and land-based craft and sea-based meteorological hazards and sea-borne craft.

Data in the matrix is intelTogated by a process running on the microprocessor 4 which generates a hazard discrimination product 28. These data are used to identiñ' aviation hazards including airframe icing, aero-engine icing, turbulence, volcanic ash and dust particulates (external and cabin), and hazardous gases (external and cabin). Measurements from sensors on the airframe and engine iii lets may be uscd to monitor changes in engine and airframe health that can result from exposure to atmospheric particles (supercooled liquid water droplets, ice crystals, volcanic ash, mineral dust) and hazardous gases and vapours (e.g., sulphur dioxide, acids, etc.). These products are displayed in a user interface running on a personal computer or tablet, or displayed on a screen in the avionics system 29. According to the present technique threshold values of parameters arc used to define hazardous regions of airspace, for example, in accordance with the aeroengine manufacturer's definition of a "safe" ambient ash concentration.

Data are also sent to the surface using either radio-link data communications or satellite communications.

The adaptive router 6 determines the optimal communications links, based on availability and cost. Data may be transmitted through Controller-pilot data link communications (CPDLC) technology using Aircraft Communications Addressing mid Reporting System (AC\RS) protocol: (1) FANS-i/A system is primarily used by wide-bodied jets over oceanic routes 31; and ATN/CPDLC systeni that implements VDL Mode 2 networks used in Europe 32. ACARS uses VHF where available (range -200 nm), 1ff or satellite assets such as the lnmarsat Data-2 (Classic Aero) service 33. More details of an optimised communications protocol according to the present technique are provided below.

Data may also be transferred using the standalone satellite communications link 7. In all cases (31, 32, 33, 7), data transmission is hi-directional. Signals transmitted by the aircraft are received by a surface communications links 35. Data are then transferred using a terrestrial network such as the internet 36.

These data are transmitted to the adaptive assimilative platform 20, Meteorological Hazard Identification Device Providing an Adaptive Assimilation Platform Figure 7 provides an illustrative block diagram of an example implementation of a meteorological hazard identification device according to the present technique. Observational data from aircraft-mounted sensors, satellite-based sensors, and sensors at the surface 38, which may form measurement tracks from aircraft are fed into the adaptive situational awareness database using the most economical communications channel 39. Satellite-based sensor data are processed by algorithms to generate products of cloud and atmospheric properties. Parameter values are assimilated, time synchronized 40, re-cast on a common geographic projection location synchronized 41 and stored as a function of location, both at the surface and atmosphere, and as a function of time, i.e., 4-D data matrix for each parameter 42. Initial observational products are generated from this 4-D database 43, such as vertical profiles of measured cloud properties made by the aircraft carrying meteorological sensors from ascent or descent profiles, and these are sent to be displayed by tbe users via a user interface 44. Data stored in the data base DB, provides the 4D data matrix 42 which are used in forecast models 45, both as input data 46, and also to perform model inversion to optimize boundary conditions 47 used to initialize a model forecast prediction. In this process, the forecast model is first run using a set of initial (a priori) conditions to generate a forecast product 48, which can be sent to be displayed by the user via the user interface 44.

In one example the processor 50 is configured to perform a modelling process which combines the measurement tracks of airborne particles in accordance with a technique disclosed in l0j.

Data assimilation is the process of combining the best available information to obtain the best possible knowledge of a given system as a fimetion of' time. Data assimilation has successive predictive and analytical stages used to estimate the state of a system given: obscrvations (direct, i.e., in situ and indirect, i.e., remotely-sensed), forecast model predictions (to provide a priori data, given too few observations) and observation operators (to connect model state with observations). Data assimilation estimates are sensitive to uncertainty characteristics, which are often poorly known, and account for random and systematic errors. The final assimilated model result also has an associated uncertainty.

This technique is referred to in the following description as data assimilation or "now-casting".

Essentially, a first step involves a model prediction of some quantity, for example wind, temperature, pressure, water content, cloud particle phase, number, size etc. This is performed by the forecast models 45. The model prediction is then compared against measured samples, then the model is re-mn to reproduce the measured samples, and Imally run forward to generate the prediction. These steps are performed respectively by the temporal synchronisation clement 40, the geographic synchronisation element 41, the 4-D data matrix 42 and the product generation 43, 48, 49. The overall process is referred to as data assimilation, which is a process of combining the best available information to obtain the best possible imowledge of a given system as a ifinetion of time.

Given a measurement of some atmospheric state variable, x, statistics (typically Gaussian) may be applied to provide an estimate of x11 + c11, where c is the measurement uncertainty.

In general terms: x is the state vector (in elements) y is the model version of the observations (n elements) 1 0 h is the forward model or ohservation operator (input n elements, output p elements) , is the observation vector (n elements) y h(x) The data assimilation process provides the best fit between y0 and y, as represented in Figure S. The 3D structure of the state vector includes meteorological parameters (wind, temperature, pressure, water content, cloud particle phase, number, size); 3-D structure of the state vector includes nieteorologica There are several methods of data assimilation which include: (a) data. insertion (replace values of x with observation values. y); (b) variationa.l data assimilation (minimisation of a cost function); (c) Kalman filtering (evaluation of Kalman filter equations); (d) ensemble Kalinan filtering (approximate Kahnan filter equations with ensemble) ; (e) a hybrid approach combining (c) and (d); and (1) particle filter (assits weights to ensemble members to represent any probability density function).

Often die observations are insufficient to determine x so prior information is introduced using a model ("a priori"), Xf.

Variational data assimilation example: Variational data assimilation constructs a cost functional and minimizes with respect to the mis-match between predicted, x, and observed, y (a generalised least-squares problem): J(x) Ix_xiD2 +y-h(xf The cost function may be derived from Bayes' theorem under the assumption that forecast and observational errors obey Gaussian statistics. The method formally propagates stochastic errors in the input data. These model result is obtained through application of forward simulations by means of an iterative loop.

A posteriori uncertainties of the model result are derived by propagating the uncertainties associated with the a priori prediction, observations and model calculations through the algorithm.

Ti additional observational data are available, the model may be run backwards to compare predicted parameters with observed at a given point hi time. This process may be repeated many limes through a.

model inversion process, making small changes to the boundary conditions, to minimise the difference between observed and predicted parameter values 47. Once the difference between observed and predicted has reached a minimum, boundary conditions are fixed (aposteriori) and the model is run forwards to generate an optimised forecast product in a process (hereby defined as a "now-east" product) 49.

According to this modelling and prediction technique, an inverse modelling method is used to determine airborne particle concentration profiles, which is then merged with a priori information on airborne particles from sampled data and simulations with a dispersion model to derive improved aposteriori particle concentration profiles.

The components of the system that comprise the ineteorologial hazard identification apparatus which forms an adaptive assimilative platform may be performed by the processor 50 in combination with the measurement data stored in the data store DB. These products are interpreted to generate aviation hazard products. All products are made available to the end user in a layer-type format such as KMI, which allows quantities to be plotted on a geographical grid, as a thnction of time. Within the user interface 44, individual products are presented as layers that can be overlain on, or integrated directly into, navigational flight charts, this resource forms an integral component of software used by operational flight planning departments (dispatch) and the electronic flight bag. The spatial and temporal components of specific product layers may he custornised to the requirements of individua] users; for example, products can he automatically tailored around specific scheduled flight routes flown by commercial airlines.

Observational products, such as vertical profiles of cloud phases, will be generated for ah traffic managers at aerodromes.

Figure 9 provides a more functional representation of system components according to the present techniqoc. In Figure 9. the navigate assistance device is formed by the data, a simulation and adaptive platform 20 which receives data sets 100 forming tracks of measurement data generated by different aircraft A.1, A.2. The data from samples produced along the measurement track are combined and communicated via a communications channel (terrestrial or satellite) S to be received by the data simulation and adaptive platform 20 which combined the diTerent tracks to generate a "now forecast" providing a model predicting the concentration or disbursement of particles within a region of the Earth's airspace. The interface function 21 publishes the concentration of particles at particular areas and altitudes within the region of the airspace which can be accessed by user devices 44 to determine whether the airspace should he avoided or not.

Figure 10 provides an example flow diagram of a technique for combining the measurement tracks of examples with respect to location an altitude, each sample providing a 41) matrix of components including altitude, geographical co-ordinates as well as particle intensity and size. Figure 10 is summarised as follows: SI: The meteorological hazard identification device is configured to receive from a plurality of airborne craft measurement data comprising for each airborne craft a measurement track, each measurement track providing an indication of at least a density of particles at a geographical location within airspace with respect to time.

52: For each of a set of quantised volumes within each of a set of altitudes in a region of the airspace of interest, at a common temporal reference, interpolate between samples derived from the plurality of the measurement tracks which samples are within a common quantised volume. According to this arrangement the samples from different measurement tracks can be combined, which fall within each discrete quantised volume at a. given time step. lids is perfonned using the data assimilation process explained above.

84: For each of the quantised volumes in the set of quantised volumes for each of the set of altitudes an averaged density of particles within each quantised volume of airspace of the set of altitudes is formed from the interpolated samples within that quantised volume.

56: The averaged density of particles within a quantised volume of airspace for each of the set of altitudes is compared with reference to a predetermined scale of values.

58: In accordance with the predetermined scale, a representation of the density of particles within the quantized region is assigned, for each of the quantised regions for each of the sets of altitudes.

S 10: The representations are collected together to form the representation of the particles within the region of the airspace.

Optimising communications between the mobile segment (airborne, maritime or land) and the ground segment According to the present technique a communications protocol can be provided to transfer data more efficiently between a ground segment U and a mobile platform A (airborne, maritime or land mobile).

Redundancy reduction protocol, ground segment G to mobile platform A (Figure 11) Embodiments of the present technique can provide an arrangement for economising the quantity of the hazard situational awareness data communicated from the ground segment G to the mobile platform or segment A. The routing maps sent by the ground segment G to the mobile platform A normally vary at a relatively low rate, following the rate of change of the atmosphere. Therefore successive routing map updates may contain a significant level ofredundancy, According to an example embodiment of the present technique, the ground station reduces such redundancy by implementing a communications protocol between the ground segment G and the mobile platform A as presented in Figure 11, which is summarised as follows for the example of an airborne platform: As part of the flight preparations the airborne syslem (i.e.. electronic flight bag, hosted on either a portable electronic device or directly on hardware comprising the avionics console) is uploaded with an initial routing hazard map. containing all static map graphics (i.e. all land features). In addition the initial routing hazard routing map includes the latest hazard information, updated in real-time. This initial routing hazard map is uploaded via the communications link available at the surface, using either a wired or wireless connection, e.g., WiFi to internet.

Routing hazard map updates are generated and stored at the ground station 0, ready to be sent to the end user. The routing hazard map updates are time stamped to ensure synchronisation between the different users of the hazard map (i.e. the air traffic controller, the airline planner, and the aircraft pilot). The routing hazard map data points are quantized to the minimum number of possible values with the purpose of minimising the amount of data to be sent without compromising the usefiflncss of the map for the end-user. (Sl) Successive flight routing data updates only contain changes from the previous transmitted update: Updates are checked for changes compared to the previous transmitted routing map (S2). Updates with changes that are below a pre-defined threshold quantity are not transmitted (Dl). In that case the ground segment does not. send a routing map update until the variation from the previous transmission reaches the threshold (S4). The ground station 0 sends a routing map update only once the variation from the previous transmission reaches or exceed the pre-dcfmed threshold quantity (S3) System integrity considerations: Regardless of the amount of variability accumulated in the flight routing map the ground segment sends periodic routing map updates at relatively low rate to ensure integrity of the routing map data stored and maintained by the airborne segment (this is implemented in decision box D2 in Figure 11).

The airborne segment can request the hill hazard data set for the routing hazard tna.p to he transmitted from time to time to eliminate any potential previously accumulated variation errors in the routing hazard map. I'his procedure may be invoked as a verification mechanism in cases where large variations in hazard data points are experienced (this is implemented in decision box D3 in Figure 11.).

Correspondingly, the present technique can provide a further communications protocol to transfer data more efficiently from the mobile platform A to the ground segment 0. Embodiments of the present teclmique can provide an arrangement for ceonomising on the communication of the data sent from the mobile platform A to the ground segment Ci. The measurement sample tracks collected by the on-board sensor may contain a significani level of redundancy. Accordingly, the mobile platfonn A reduces such redundancy asing a communications protocol presented in Figure 12, as described in the following protocols for the example of an airborne platform: Redundancy reduction protocol, mobile platform A to ground segment G (Figure 12): Sensor measurement data vector is generated and stored by the airborne platform together with the corresponding geographic and temporal tags. (SI) The sensor measurement data for transmission may be quantized to the minimum number of possible values with the purpose of minimising the amount of data to be sent while not compromising the usefulness of the data to be processed by the Daedalus ground segment.

[he variation between the latest generaled sensor data and the previous transmitted sensor data is calculated (52).

Wben there are only minor variations in successive measurement samples in the track (below the quantisation level) the airborne platform holds off sending measurement sample updates until the sample variation from the previous transmission reaches the quantisation threshold (decision box D2).

Ibis may he a common occurrence while in flight cruising altitudes. [his technique may significantly reduce the real-time demand (and cost.) on the communications system while still transmitting real-time measurement samples when significant variations are dctected.

Further compression may be obtained from transmitting the difference between transmitted samples rather than the measurement sample itself. The data to be transmitted contains geographic and temporal tags to allow the ground segment to correctly map the data into the Daedalus assimilation platfonn (S 5).

1 0 System integrity considerations: Regardless of the variability in the measurement samples thc airborne segment sends short periodic messages at relatively low rate to the ground segment to maintain system integrity (including aircraft position and time) while minimising the amount of data that is transmitted (D3 and 54).

The ground segment can request a full mcasurcmcnl. (quanl.izcd) sample t.o be transmitted from time to 1 5 time for validation / quality control! assessment of instrumental drift etc. This procedure may be invoked as a verification mechanism in cases where large measurement variations are experienced (Dl and S6).

Thus according to the present technique an integrity timer, which includes a clock measuring a time since a previous transmission of samples of a track, which defines an interval for sending updates, without regard to any variation from previous transmission. According to an alternative embodiment the airborne segment can request an update of the samples of the track without regard to any variation from a previous transmission. Accordingly there is provided an increase in an integrity of measurement samples providing the track which complements the protocol and increases an integrity of the caprured samples of the track.

Data transmission protocol profile adjusted to the flight phases (see Figure 13): Take-off phase (up to cruise phase)-basic protocol: During the take-off phase, the aircraft climbs rapidly and measures changes in atmospheric parameters and cloud properties. These measurements are converted into a quasi-vertical profile of parameters, such as cloud particle properties as a function of height around the aerodrome. At this stage the data needs to be captured at high temporal resolution.

Therefore the baseline transmission protocol for this flight phase is to transmit the measurement sample data at a sufficient rate to capture the variability as a function of height in the atmosphere. The integrity interval period may be shorter in this flight phase (Dl and S2).

Cruising phase: typically characterised by long periods of low variability in the data measured by the sensors. Therefore the integrity interval may be set to a longer period and overall transmission efficiency may be enhanced (D2 and S3).

Approach phase (from leaving cruise phase): same as take-off phase (Dl and S2).

At airport gate: raw sensor data stored on hardware aboard the aircraft is transmitted via the available communications links on the ground (wired or wireless, e.g. Wifi to Internet) from the aircraft to the gate.

This is later used for validation, quality control, and post-processing (54).

Optimising the Meteorological Hazard Routing Map Product for the Airline Route Planner and the Pilot According to one example of the present technique, a routing map product is designed around presenting a pilot with the most relevant data for every point in space and time along the flight route, i.e. the meteorologiea.l and hazard data presented to the pilot should be eurreci fur the projected tinie the aircraft will be flying through that part of the flight route.

The following are key design details: The flight route map should provide both the horizontal (X, Y) and vertical view (Z) of the meteorological hazard; the X-Y plan-view shows the hazard map along the flight route vector which is represented by the X axis, where Y represents the perpendicular horizontal axis; the vertical X-Z cross-section view shows the hazard map along the flight route vector which is represented by the X axis, where Z represents the perpendicular vertical axis.

The "width" of the horizontal flight route map (i.e. number of miles shown in perpendicular to the flight route vector) may be determined based on operational requirements and flight type (shorL / medium / long S haul) The "height" of the vertical flight route cross-section may be determined based on operational requirements and flight type (short / medium / long haul) The flight route vector includes phases of take-off and ascent. flight cruise, and flight descent and approach.

Ihe aviation hazard information at a give!) point along the flight route vector (and the points on the perpendicular axis to that point) should be corrected for the projected time (he aircraft will arrive at that point (i.e. generated by the forecast models according to the present technique). With this feature the pilot (and the ANSI' controller) will always make decisions based on the relevant forecast of hazard data at the projected time along the flight route.

Catering for flight route changes: The flight route ma.p product may include more than one horizontal plan-view, i.e. providing a horizontal view at more than one possible altitude range (flight level), in the ease of a required altitude change during the flight.

Similarly the flight route map product may include more than one vertical cross-section view, i.e., providing a vertical cross-section view along more than one flight trajectory compared to the original route, in the case of a necessary direction change to avoid a hazardous area along the flight.

For situations where both altitude and trajectory changes may he required, an ad hoc routing map update can be requested from the system (using the communications protocols described above) to capture the hazard information along the modified part of the route.

In summary embodiments of the present technique can provide: Collection of real-time meteorological data (atmospheric parameters including temperature, water content, hydrometeor characteristics) from the population of aircraft served by the system * Collection of cloud and atmospheric data. from Earth Observation satellite (EOS) sources * Interpretation of all meteorological data to identify and discriminate aviation hazards based on characteristic signatures * Processing and assimilation of the derived hazard products into a near real-time global situational awareness database * Generation of hazard products compatible with the Client format (airlines, air traffic managers (ATM) electronic flight bag) * Data delivered 1.0 the client domain (flight operations, ATM, electronic flight bag) in real-time.

including updated electronic flight maps to (he cockpit via, available coinnumications.

* Compatibility with commercially available flight planning and operations software used by airlines and Air Traffic Managers * Global coverage real-time transmission over satellite communications (or other available communications ehamiels): * Georeferenced quantitative graphical plan view products for cloud and atmospheric characteristics at different flight levels; and * Georeferenced quantitative graphical cross-section view products for cloud and atmospheric characteristics at different flight levels.

An example of sensor data acquisition and processing on-board aircraft, and the efficient data transfer to the ground for processing by the adaptive assimilation platffirm are described as follows: Cloud particle sensor data acquisition and processing 1. Aircraft-mounted cloud particle sensor generates measurement at constant rate.

In one example of an available cloud particle sensor, the sensor emits a focussed beam of light energy at a discrete wavelength outwards away from the aircraft fuselage, and optics capture emitted energy hack-scattered from particles in the atmosphere adjacent to the aircraft onto a detector array within the sensor body. Raw data acquired include quantification of baekseaftered energy intensity and depolarisation at different angles relative to the emission source beam. A separate patent exists for the instrument owned by Droplet Measurement Technologies, incorporated.

2. The raw data files are large and are stored locally in a binaiy format, e.g.. NETCDF.

A microprocessor communicates with the sensor hardware and routes the raw data to a local hard-drive on board the aircraft.

3. Measurement stream is analysed in real-time to generate particle size and vohime/mass concentrations.

The microprocessor processes the raw data using a standard optics inversion (e.g.. Mie Theory) to convert the diffracted energy measurement into a physical quantitative approximation of the airborne particle distribution (particle number, size and mass/volume relative to a. discrete volume of the atmosphere). A separate patent exists for the instrument owned by Droplet Measurement Technologies, lncoiporated.

4. Real-time air-surface data communication The processed data are analysed in real-time for a number of applications that require air-surface communication. These include; meteorological forecasting; aircraft exposure to supcreooled liquid water (SLW); aeroengine exposure to ice crystals, and aireraft/acroengine exposure to volcanic ash. According to the present technique, on ascent and descent phases, measurements of cloud particle phase (type), number and size will be transmitted to the surface at high frequency and directed into the data assimilation platform database. During the cruise phase, measurements will be transmitted at a lower rate according to the communications protocols described above.

During flight, measured airborne particle concentration is compared to known thresholds for ice, supercooled liquid water (SLW) and volcanic ash hazards. If the measurement exceeds the threshold value for airframe or aeroengine exposure, a hazard flag will be added to the data. This hazard flag may be linked to a. situational awareness interface on the flight deck to provide information for the pilot. The flag is also transmitted via onboard communications to the surface and directed into the data assimilation platform database. The hazard flag may then be directed to airline dispatch offices, air traffic control, or to the airframe and aeroengine manufacturers.

At certain times, it may be necessary to request the raw data, e.g., for quality control/verification.

Therefore the system requires communication capability in both directions (push/pull). In this scenario, the system will send a request up to the aircraft via the communications for a subset of the raw data. The onboard processor then accesses the locally-stored copy of the raw data, copies a segment of interest, and transmits this back down to the surface where it is directed into the data assimilation platform database.

Various further aspects and features of the present technique are defined in the appended claims. The following numbered paragraphs provided further example aspects are features of the present technique: 1. A meteorological hazard identification apparatus for generating a representation of meteorological hazards, comprising a receiver for receiving data comprising a plurality of measurement sample tracks, each of the measurement sample tracks having been generated by a mobile craft using an atmospheric! meteorological hazard sensor measurement device mounted on the craft and each of the measurement sample tracks comprising a plurality of captured samples of atmospheric! meteorological hazard measurements, measured with respect to geographical co-ordinates providing a location and time stamps of the captured sample within the Earth's airspace and at the longitude, latitude and altitude of the craft, a data processor which is configured to store the plurality of sample tracks into a data store in accordance with a. predetermined format, and to retrieve each of the measurement tracks from the data store, to combine the plurality of measurement tracks to form, with respect to mapping information, a representation of airspace showing geographical locations within the Earth's airspace at determined altitudes and time of at least a density of detected particles, and an access interface configured to generate a representation of the detected particle density with respect to an airspace map of the Earth's airspace for access by one or more client devices for display to users.

2. A meteorological hazard identification apparatus according to paragraph 1, wherein the data processor is configured to combine the plurality of measurement tracks using a model of dispersion of the particles detected in accordance with each of the measurement tracks, the model providing an interpolation of particle samples with respect to a geographical location and time stamp of the samples to form a predicted dispersion of the particles within the region of the Earth's airspace.

to compare the predicted dispersion of the particles provided by the model of dispersion of the particles with further measurement tracks to refine the predicted dispersion of the particles within the region of the Earth's airspace, and to form with respect to the mapping information the representation of airspace avoidance regions from the refined predicted dispersion of the particles within the region of the Earth's space.

3. A meteorological hazard identification apparatus according to paragraph 1, wherein the receiver is configured to receive data representing meteorological modeling data representing weather forecast data within a part of the Earth's airspace, and the data processor is configured to combine the plurality of measurement tracks with the meteorological data to generate the airspace avoidance regions based on the measured particle size and density with respect to altitude, location and time with a prediction of the modelled meteorological conditions determined from the modeling data.

4. A meteorological hazard identification apparatus according to paragraph 1,2 or 3, wherein the data processor is configured to determine regions of the airspace at respective altitudes which are hazardous to aircraft based on at least the density of the detected particles, and to generate a representation of the hazardous regions for presentation on the map of the Earth's airspace for access by one or more client devices for display to users.

5. A method of idcnti4ng meteorological hazards, comprising receiving data comprising a plurality of measurement sample tracks, each of the measurement sample tracks having been generated by a mobile craft using an atmosphcric/ meteorological hazard sensor measurement device mounted on the craft and each of the measurement sample tracks comprising a plurality of captured samples of atmospheric/meteorological hazard measurements measured with respect to geographical co-ordinates providing a location and time stamps of the captured sample within the Earth's airspace and at the longitude, latitude and altitude of the craft, storing the plurality of sample tracks into a data store in accordance with a predetermined format, retrieving each of the measurement tracks from the data store, combining the plurality of measurement tracks to form with respect to mapping information a representation of airspace showing geographical locations within the Earth's airspace at detennined altitudes of at least a density of detected particles, and generating a representation of the detected particle density with respect to an airspace map of the Earth's airspace for access by one or more client devices for display to users.

6. A method according to paragraph 5, wherein the combining the plurality of measurement tracks comprises combining the plurality of measurement tracks using a model of dispersion of the particles detected in accordance with each of the measurement tracks, the model providing an interpolation of particle samples with respect to a geographical location of the samples to form a predicted dispersion of the particles within the region of the Earth's airspace, comparing the predicted dispersion of tile particles provided by the model of dispersion of the particles jth further measurement tracks to refine the predicted dispersion of the particles within the region of the Earth's airspace, and forming with respect to the mapping information the representation of airspace avoidance regions from the refined predicted dispersion of the particles within the region of the Earth's space.

7. A method according to paragraph 5 or 6, wherein the receiving data includes receiving data representing meteorological modeling data representing weather forecast infonnation within a region of the Earth's airspace, and the combining the plurality of measurement tracks includes combining the plurality of measurement tracks with the meteorological data to generate the airspace avoidance regions based on the measured particle size and density with respect to altitude and location with a prediction of the modelled ineteoro logical conditions determined from the meteorological modeling data.

8. A method according to paragraph 5, 6 or 7, comprising determining regions of the airspace at respective altitudes which are hazardous to aircraft based on at least the density of the detected particles, and generating a representation of the hazardous regions for presentation on the map of the Earth's airspace for access by one or more client devices for display to users.

9. A method according to any of paragraphs 5 to 8, wherein combining the plurality of measurement tracks using a model of dispersion of the particles detected in accordance with each of the measurement tracks comprises interpolating between measurement samples which fall within a predetennined range of values with respect to a geographical range of samples with respect to a time at which the samples were taking, forming for a determined temporal reference a representation of a density of particles within a quantized volume, comparing the density of particles within the quantized volume with a predetermined scale, and in accordance with the predetermined scale, assigning a representation of the density of particles within the quantized region, and combining the representations to form the representalion of the particles within the region of the airspace.

References: [1] US 8,395,534 B2 Method and system for meteorological monitoring aboard an aircraft [2] US 8,548,727 B2 Cognitive aircraft hazard advisory system (CAI1AS) [3] US 6,525,674 B1 Conditional hazard alerting display [4] US 6,002,347 A Integrated hazard avoidance system [5] US patent application 2012/415,314 [6] US 6,662,627 B2 Analytical spectrometer [7] US 5,889,589 System inchidcs spectrometer; [8] US 7,656,510 [9] US 5,920,388 [10] Stohol A. et al, "Detennination of time-and height-resolved volcanic ash emissions for quantitative ash dispersion modeling: the 2010 Eyjafjalljokull eruption," Atmospheric Chemistry and Physics Discussions, 11, 5541-5588, 20i 1.

[11] Kalnay, 2003, "Atmospheric Modeling, Data Assimilation and Predictability". Cambridge University Press, ISBN 0521796296.

[12] Daley, 1991, "Atmospheric Data Analysis." Cambridge Atmospheric and Space Science Series, Cambridge University Press, Cambridge, 1991. Pp. 457, ISBN 0521 382157 [13] It. M. Errico, Peter Bauer, and Jean-Prançois Mahfouf, 2007, "Issues Regarding the Assimilation of Cloud and Precipitation Data." J. Atmos. Sci., 64, 3785-3798.

[14] Lorenc, 2003, "The potential of the ensemble Knlman Filter for NW P -a comparison with 4d-Var", QJRMS 129, 3 183-3203.

[151 Peter Jan van Leeuwen, 2009, "Particle Filtering in GeophysieaJ Systems". Mon. Wea. Rev., 137, 4089-4114.

[16] Rodgers,2000, "inverse methods for atmospheric sounding, theory and praetiee", World Scientific. Singapore.

[17] P. Seibert and A. Frank, "Source-receptor matrix calculation with a Laangian particle dispersion model in backward mode", ACP, 4, 5 1-63, 2004.

[18] A Stohl. A.T Prata. Sabinc Eckhardt, Lievcn Clarisse, Adam Duraiit, S Tlenne, \1 Kristiansen, A Minikin, U Schumann, P Seibert. K Stebel, HE Thomas, T Thorsteinsson, K Tørseth, B Weinzicrl.

"Determination of time-and height-resolved volcanic ash emissions and their use for quantitative ash dispersion modeling: the 2010 Evjafiallajokull eruption", Atmospheric Chemistry and Physics. 11, 9, 4333-435 1.

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[20] Beswick K., Baumgardncr D., Gallagher M., Volz-Thornas A., Nedelec P., Wang K.-Y., and Lance S., "The hackseatter cloud probe -a compact low-profile autonomous optical spectrometer" Atmos. Meas. Tech., 7, 1443-1457, compac,www.atmos-meas-tech.nett7/1 443/2014/ [21] Glen A., Brooks S. I).. "A new method for measuring optical scattering properties of atmospherically relevant dusts using the Cloud and Aerosol Spectrometer with Polarization (CASPOL)". Atmos. Chem. Phys., 13, 1345-1356, 2013, www.atmos-chem-phys.net/13/1345/2013/ doi:l0.5194/acp-l3-1345-20l3

Claims (33)

1. CLAIMS1. A meteorological hazard identification apparatus for generating a representation of meteorological hazards, comprising a receiver for receiving data comprising a plurality of measurement sample tracks, each of the measurement sample tracks having been generated by a. moving craft using a measurement device mounted on the craft and each of the measurement sample tracks comprising a plurality of captured samples of one or more meteorological parameters measured with respect to geographical co-ordinates providing a location and time stamps of the captured sample, a data processor which is configured to store the plurality of sample tracks into a data store, and to retrieve each of the measurement tracks from the data store, to combine thc plurality of measurement tracks, to form, with respect to mapping information, a representation at geographical locations within a region of a variation in the one of more meteorological parameters with respect to displacement within the region, and an access interface configured to generate a representation of the variation of the one or more meteorological parameters with respect to displacement within the region with respect to a ma.p of the Earth for access by one or more accessing devices for display to users.
2. 2. A meteorological hazard identification apparatus as claimed in Claim I, wherein the data processor is configured to perform a data assimilation process to combine the plurality of measurement tracks using a model of variation of at least one of the meteorological parameters in accordance with each of the measurement tracks, the model providing an interpolation of the at least one meteorological parameter with respect to a geographical location of the samples to font a predicted variation of the meteorological parameter within the region of the Earth, to compare the predicted variation of the meteorological parameter provided by the model of the variation of the meteorological parameter with further measurement tracks to refine the predicted variation of the meteorological parameter within the region of the Earth, and to form with respect to the mapping information the representation of the region of the Earth with the refined variation of the meteorological parameter within the region of the Earth.
3. 3. A meteorological hazard identification apparatus as claimed in Claim 2, wherein the at least one meteorological parameter includes a sample of particle concentration at a determined geographical location and altitude within the Barth's airspace, the receiver is configured to receive data representing meteorological modeling data representing weather forecast data within a part of the Earth's airspace, and the data processor is configured to combine the plurality of measurement tracks with the meteorological data to generate the predicted variation of the particle concentration provided by the model of the variation of the particle concentration within the region of the Earth's airspace.
4. 4. A meteorological hazard identification apparatus as claimed in Claim 1, 2 or 3, wherein the data processor is configured to determine regions of the airspace at respective altitudes which are hazardous to aircraft based on at least the concentration of the detected particles provided by one of the meteorological parameters, and to generate a representation of the hazardous regions for presentation on the map of the Earth's airspace for access by one or more client devices for display to users.
5. 5. A meteorological hazard identifications apparatus as claimed in Claim 2, 3 or 4, wherein the data processor is configured to perform the data assimilation process by comparing the model prediction of a meteorological parameter with the measured meteorological parameter in accordance with the measurement track for the meleorological parameter, to generate an error between the prediction and the measured meteorological parameter, and adapting the model prediction of the meteorological parameter in order to reduce the error.
6. 6. A meteorological hazard identification apparatus as claimed in Claim 5, wherein the data processor is configured to repeat the comparing the model prediction of a meteorological parameter with the measured meteorological parameter in accordance with the measurement track for the meteorological parameter, to generate the error, and adapting the model prediction, one or more times to refine the prediction model for the meteorological parameter.
7. 7. A meteorological hazard identification apparatus as claimed in any of Claims 1 to 6, wherein the access interface is configured to transmit the variation of the one or more meteorological parameters with respect to displacement within the map of the Earth to the one or more accessing devices, wherein the variation of the meteorological parameters comprises a plurality of data points which are quantized to a predetermined scale, and the access interface is configured to transmit the variation of the one or more meteorological parameters with respect to displacement within the map of the Earth as an update with respect to a previous transmission, and when one or more of the plurality of data points have not changed with respect to a previous transmission then not transmitting an update for the data point.
8. 8. A meteorological hazard identification apparatus as claimed in Clahn 7, wherein the access interface is configured to transmit the update with respect to the previous transmission whether or not the one or more data points have changed with respect to the previous transmission after receiving a request for the update from one or more of the accessing devices.
9. 9. A meteorological hazard identification apparatus as claimed in Claim 7, comprising a clock for providing a temporal reference and the access interface is configured to transmit the update to the one or more accessing devices with respect to the previous transmission whether or not the one or more data points have changed with respect to the previous transmission after a predetermined time has elapsed since the previous update was transmitted determined with respect to the temporal reference.
10. 10. A method of identiing meteorological hazards, comprising receiving data comprising a plurality of measurement sample tracks, each of the measurement sample tracks having been generated by a moving craft using a measurement device mounted on the craft and each of the measurement sample tracks comprising a plurality of captured samples of one or more meteorological parameters measured with respect to geographical co-ordinates providing a location and time stamps of the captured sample, storing the phiralily of sample tracks into a data store in accordance with a predetermined format, retrieving each of the measurement tracks from the data store, combining the plurality of measurement tracks, to form, with respect to mapping information, a representation showing at geographical locations within a region a variation in the one of more meteorological parameters with respect to displacement within the region, and generating a representation of the variation of the one or more meteorological parameters with respect to displacement within the region with respect to a map of the Earth for access by one or more devices for display to users. 2.
11. 11. A method as claimed in Claim 10, wherein the combining the plurality of measurement tracks to perform a data assimilation process to comprises combining the plurality of measurement tracks using a model of variation of at least one of the meteorological parameters in accordance with each of the measurement tracks, the model providing an interpolation of the at least one meteorological parameter with respect to a geographical location of the samples to form a predicted variation of the meteorological parameter within the region of the Earth comparing tile predicted variation of the meteorologiea.l parameter provided by the model of the variation of the meteorological parameter with further measurement tracks to refine the predicted variation of the meteorological parameter within the region of the Earth, and forming with respect to the mapping infonnation the representation of the region of the Earth with the refined variation of the meteorological parameter within the region of the Earth.
12. 12. A method as claimed in Claim 10 or 11, wherein the at least one meteorological parameter includes a sample of particle concentration at a determined geographical location and altitude within the Earth's airspace, and the receiving the data includes receiving data representing meteorological modeling data representing weather forecast infonnation within a region of the Earth's airspace, and the combining the plurality of measurement tracks includes combining the plurality of measnreinent tracks with the meteorological data to generate the predicted variation of the particle concentration provided by the model of the variation of the particle concentration within the region of the Earth's airspace.
13. 13. A method as claimed in Claim 10, 11 or 12, comprising determining regions of the airspace at respective altitudes which are hazardous to aircraft based on at least the concentration of the detected particles provided by one of the meteorological parameters, and generating a representation of the hazardous regions for presentation on the map of the Earth's airspace for access by one or more client devices for display to users.
14. 14. A method as claimed in any of Claims 10 to 13, wherein the combining the plurality of measurement tracks using a model of the variation of the meteorological parameter in accordance with each of the measurement tracks comprises interpolating between measurement samples wiuch fall within a predctcnnincd range of values with respect to a geographical range of samples with respect to a time at which the samples were taking, forming for a determined temporal reference a representation of a value of the meteorological parameter within a quantized volume, comparing the value of the meteorological parameter within a quantized volume with a predetennined scale, and in accordance with the predetermined scale, assigning a representation of the value of the meteorological parameter within the quantized volume, and combining the representations to form the representation of the predicted variation of the meteorological parameter within the region of the Earth.
15. 15. A method as claimed in Claim 14, wherein the measurement tracks provide samples of at. least a concentration of particles at a geographical location at a determined altitude, the model of the variation of the meteorological parameter providing a model of a variation of the concentration of the particles within a. region of the Earth's airspace.
16. 16. A method as claimed in Claim 15, wherein the meteorological parameters include at least one of an indication of the particle size, particle phase or particle type, and the method includes generating the representation of the variation in the particle concentration in combination with at least one of the indication of the particle size, particle phase or particle type for presentation as a meteorological hazard according to predetermined conditions to the accessing devices.
17. 17. A method as claimed in Claims 14, 15 or 16, the method comprising comparing the model prediction of a. meteorological parameter with the measured meteorological parameter in accordance with the measurement track for the meteorological parameter, to generate an error between the prediction and the meas tired meteorological parameter, adapting the model prediction of the meteorological parameter in order to reduce the error.
18. 18. A method as claimed in Claim 17, comprising repeating the comparing the model prediction of the meteorological parameter with the measured meteorological parameter in accordance with the measurement track for the meteorological parameter. to generate the error, and the adapting the model prediction, one or more times to refine the prediction model for the meteorological parameter.
19. 19. A method as claimed in any of Claims 10 to 18, comprising transmitting the variation of the one or more meteorological parameters with respect to displacement within the map of the Earth to the one or more accessing devices, wherein the variation of the meteorological parameters comprises a plurality of data points which are quantized to a predetermined sea le, and wherein the transmitting the variation of the one or more meteorological parameters includes transmitting the variation of the one or more meteorological parameters with respect to displacement within the map of the Earth as an update with respect to a previous transmission, and when one or more of the plurality of data points have not changed with respect to a previous transmission then not transmitting an update for the sample point.
20. 20. A method as claimed in Claim 19, wherein the transmitting the variation of the one or more meteorological parameters comprises transmitting the update with respect to the previous transmission whether or not the one or more data points have changed with respect to the previous transmission after receiving a request for the update from one or more of the accessing devices.
21. 21. A method as claimed in Claim 19, wherein the transmitting the variation of the one or more meteorological parameters comprises transmitting the update to the one or more accessing devices with respect to the previous transmission whether or not the one or more data points have changed with respect to the previous transmission after a predetermined time has elapsed since the previous update was transmitted determined with respect to the temporal reference.
22. 22. A moving craft comprising a geographical measurement device for generating data representing geographical co-ordinates of a location and time stamp of the moving craft.a meteorological measurement device configured to generate measurement data comprising one orntore measurement sample tracks, each of the measurement sample tracks comprising a plurality of captured samples of one or more meteorological parameters measured with respect to the geographical co-ordinates providing a location and time stamp of the captured sample, a transmitter configured to transmit the measurement sample tracks to a meteorological hazard identification apparatus, the metcorologica.I hazard identification apparatus being configured to generate a representation of the variation of the one or more meteorological parameters with respect to displacement within the region with respect to a map of the Earth for access by one or more accessing dcvices for display to users, and a controller configured to control the transmitter to transmit the measurement sample tracks to the meteorological hazard identification apparatus wherein the controller is configured to control the meteorological measurement device to generate the captured samples of one or more meteorological parameters measured periodically, and if a difference between one or more successively captured samples is below a predetermined threshold, then not transmitting the one or more successively captured samples as part of the measurement track.
23. 23. A moving craft as claimed in Claim 22, comprising a. receiver for receiving data representing a meteorological hazard warning map for a region on the Earth into which the craft is moving, the meteorological hazard warning map being time stamped, and a display for displaying a representation of the meteorological hazard warning map to a user, wherein the controller is configure to control the receiver to receive update data representing a difference between the meteorological hazard warning map at a first time stamp with respect to a previous time stamp.
24. 24. A moving craft as claimed in Claim 22 or 23, wherein the measurement data forming the sample tracks is quantized with respect to a set of discrete values for reducing an amount of information to be transferred to represent the measurement samples of the measurement tracks.
25. 25. A moving craft as claimed in Claim 24, wherein the controller is configured to control the transmitter to transmit a. measurement sample of a meteorological parameter for a measurement track when the measurement sample has changed from a previously quantized value for the measurement sample.
26. 26. A moving craft as claimed in any of Claims 22 to 25, wherein the controller is configured to control the transmitter to transmit the measurement sample tracks to the meteorological hazard identification apparatus whether or not the difference between one or more successively captured samples is below a predetermined threshold, after receiving a request for the captured sanples from the meteorological hazard identification apparatus.
27. 27. A moving craft as claimed in any of Claims 22 to 25, comprising a clock for providing a temporal reference wherein the controller is configured to control the transmitter to transmit the measurement sample tracks to the meteorological hazard identification apparatus whether or not the difference between one or more successively captured samples is below a predetermined threshold, after a predetermined time has elapsed since the previous update was transmitted determined with respect to the temporal reference.
28. 28. A method of generating measurement data samples of measurement tracks for generating a representation of the variation of the one or more meteorological parameters with respect to displacement within a region with respect to a map of the Earth, the method comprising generating data representing geographical co-ordinates of a location and time stamp of a moving craft, 1' generating measurement data comprising one or more measurement sample tracks, each of the measurement sample tracks comprising a plurality of captured samples of one or more meteorological parameters measured with respect to the geographical co-ordinates providing a location and time stamp of the captured sample, transmitting the measurement sample tracks to a meteorologica.l hazard identification apparatus, the meteorological hazard identification apparatus being configured to generate a representation of the variation of the one or more meteorological parameters with respect to displacement within the region with respect to a map of the Earth for access by one or more accessing devices for display to users, and transmitting the measurement sample tracks to the meteorological hazard identification apparatus wherein the generating measurement data comprising one or more measurement sample tracks comprises generating the captured samples of one or more meteorological parameters measured periodically, and if a difference between one or more successively captured samples is below a predetermined threshold, then not transmitting the one or more successively captured samples as part of the nieasurement track.
29. 29. A method as claimed in Claim 28, comprising receiving data representing a meteorological hazard waning map for a region on the Earth into which the craft is moving, the meteorological hazard warning map being time stamped, and displaying a representation of the meteorological hazard warning map to a user, wherein the receiving the data includes receiving update data representing a difference between the meteorological hazard warning map at a first time stamp with respect to a previous time stamp.
30. 30. A method as claimed in Claim 28 or 29, wherein the measurement data forming the sample tracks is quantized with respect to a set of discrete values for reducing an amount of information to be transferred to represent the measurement samples of the measurement tracks.
31. 31. A method as claimed in Claim 30, wherein the transmitting the measurement sample tracks to the meteorological hazard identification apparatus comprises transmitting a measurement sample of a meteorological parameter for a measurement track when the measurement sample has changed from a previously quantized value for the measurement sample.
32. 32. An aircraft comprising an aeroenginc for propelling the airerafi, a geographical location device for generating an indication of a location of the aircraft lit airspace, a receiving device for receiving meteorological hazard information generated by the meteorological hazard identification apparatus as claimed in Claim 1, and a controller for controlling the a.croenginc. wherein in response to detecting that the aircraft is in a location in which there is a meteorological hazard identified by the received meteorological hazard infonnation, controlling an operating mode of the aeroengine to protect the aeroengine in accordance with the meteorological hazard identified.
33. 33. A method of protecting an aeroengine of an aircraft comprising generating an indication of a location of the aircraft in airspace, receiving meteorological hazard information generated by the rnctcoroogica.1 hazard identification apparatus as claimed in Claim 1, and controlling the aeroengine, wherein in response to detecting that the aircraft is in a location in which there is a meteorological hazard identified by the received metcorological hazard infonnation, controlling an operating mode of the aeroengine to protect the aeroengine in accordance with the meteorological hazard identified.