Abstract:
A system for in-situ forecasting including a first vehicle including a measuring device recording weather data correlating to an external environmental condition of interest, a storage device on the first vehicle in which the weather data is received, the storage device being operatively connected to the measuring device, a processor on the first vehicle, the processor operatively connected to the storage device, the processor accessing an automatic detection algorithm to generate environmental event condition data to be stored on the storage device, a forecast algorithm accessed by the processor wherein the processor accesses the environmental event condition data for use in the forecast algorithm, a forecast created by the processor, the processor accessing the forecast algorithm and wherein the forecast is stored on the storage device, and a risk mitigation instruction created by the processor wherein the risk mitigation instruction in based on the forecast.

Description:
FIELD OF THE INVENTION 
       [0001]    The present invention relates generally to an apparatus, system and method of mitigating the risks associated with adverse operational environmental conditions which may change rapidly. More particularly, though not exclusively, the present invention relates to an apparatus, system and method of mitigating the risks associated with adverse operational environmental conditions by performing forecasting at the site of interest and subsequently taking actions based on anticipated environmental changes. 
       Problems in the Art 
       [0002]    Currently, it is well known that adverse environmental conditions can occur rapidly and, at the same time, that with enough advance warning, many of the risks associated with adverse environmental conditions can be avoided or lessened. Solar flares and other solar activity can disrupt spacecraft performance, cause damage to semi-conductor based electronic systems, whether terrestrial or space based. Ionizing radiation associated with solar eruptions increases health risk to high-polar route flight passengers and astronauts. Signal disruption is also a problem created by adverse environmental conditions. For example, GPS satellites are very sensitive to space weather disturbances. Other communications systems which rely on low frequency signals, can also be disturbed. Electrical power companies can also be affected, particularly with transformers. The events forecasted are usually classified as low-frequency high-risk events. If a large space weather event occurs much of the technological world will be affected. Lloyd&#39;s estimated that a Carrington-like event would cost the eastern US power grid on order of $2-3 trillion. Between 1996-2006 it is estimated that the US lost $2-3 billion per year due solar storms affecting the power grids alone. It is also estimated the satellite industry would lose $30 billion. 
         [0003]    Systems such as those described in U.S. Pat. No. 7,096,121, which is incorporated in its entirety herein by reference, are used to forecast environmental changes on space-based systems, using historical data and observational data gathered remotely. These systems compile data and perform predictive analysis at a centralized location, remote from the spacecraft, aircraft, or land based vehicle or location which will ultimately rely on the forecasts. Ironically, such remotely calculated forecasting systems rely on a notification that must then be transmitted to the system of interest and this system must then use the notification or rely on another remotely based controller to take corrective action to mitigate the forecasted environmental changes. The transmission of the forecasts and notification/mitigation instructions must rely on clean and timely transmissions and these transmissions can themselves be adversely impacted by environmental changes, making reliability an issue. Further, the transmission delay may sometimes be significant enough to prevent or lessen the opportunity to address incoming adverse environmental conditions. 
         [0004]    Current forecasts are improving as knowledge of environmental conditions improves. Typically, forecasting improvements are relying more and more on locally gathered data. Aircraft can fly into storms to measure wind speeds, temperatures and pressures. Seismic monitors have been placed across the globe to measure more and more movements of the earth&#39;s crust. Even satellites and other spacecraft have been sent with detectors and other sensors to measure relevant environmental data in and from space. For example, space based systems, such as those discussed in U.S. Pat. No. 8,193,968 can measure a condition of interest and the relative position of the spacecraft. 
         [0005]    While forecasting models and data gathering are both improving, neither provides the ability for a system to independently measure, predict and act. Most current notification and automated action systems, such autopilot systems are purely reactionary, based on environmental changes that have already occurred. It is therefore desirable to have an apparatus, system or method that allows for in situ predictive capabilities that permit better risk mitigation actions both locally to the system and to remote locations that the apparatus or system can transmit. 
       SUMMARY 
       [0006]    Therefore, it is a primary object, feature, or advantage of the present invention to improve over the state of the art. 
         [0007]    It is a further object, feature, or advantage of the present invention to enable an apparatus, system and method of mitigating the risks associated with adverse operational environmental conditions by performing forecasting at the site of interest. For example, the forecasts can cover the whole spectrum of space weather events, including: X-ray events (solar flares), particle events (radiation), and CMEs (geomagnetically induced currents (GICs)). 
         [0008]    Another object, feature, or advantage of the present invention is to provide an apparatus, system and method of mitigating the risks associated with adverse operational environmental conditions by performing forecasting at the site of interest and subsequently taking actions based on anticipated environmental changes which can be dependent on local data gathering. 
         [0009]    Yet another object, feature, or advantage of the present invention is to provide an apparatus, system and method of mitigating the risks associated with adverse operational environmental conditions by performing forecasting at the site of interest and subsequently taking actions based on anticipated environmental changes which is independent from external forecasting. 
         [0010]    One or more of these and/or other objects, features, or advantages of the present invention will become apparent from the specification and claims that follow. No single embodiment of the present invention need exhibit all objects, feature, or advantages of the present invention. 
         [0011]    A system for in-situ forecasting is accordingly provided, the system comprising a first vehicle including a measuring device recording weather data correlating to an external environmental condition of interest, a storage device on the first vehicle in which the weather data is received, the storage device being operatively connected to the measuring device, a processor on the first vehicle, the processor operatively connected to the storage device, the processor accessing an automatic detection algorithm to generate environmental event condition data to be stored on the storage device, a forecast algorithm accessed by the processor wherein the processor accesses the environmental event condition data for use in the forecast algorithm, a forecast created by the processor, the processor accessing the forecast algorithm and wherein the forecast is stored on the storage device, and a risk mitigation instruction created by the processor wherein the risk mitigation instruction in based on the forecast. A transceiver on the first vehicle can be provided for communication with a second vehicle. In this manner, a copy of the risk mitigation instruction can be sent to the second vehicle. A ground station and a copy of the weather data can be sent to the ground station through the transceiver so that a second forecast can be created at the ground station, the second forecast based on the same data used by the first vehicle to create the forecast so that a verification event occurs wherein the forecast is compared to the second forecast. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0012]      FIG. 1  illustrates an exemplary embodiment of a spacecraft based system according to the present invention. 
           [0013]      FIG. 2  illustrates an exemplary embodiment of some of the instrumentation which could typically be found on a spacecraft based system according to the present invention. 
           [0014]      FIG. 3 . illustrates an exemplary embodiment of one type of remote sensing using image based data collection according to the present invention. 
           [0015]      FIGS. 4A  and B illustrate an exemplary embodiment of additional in-situ data collection according to the present invention. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
       [0016]    The present invention will be described as it applies to its preferred embodiment. It is not intended that the present invention be limited to the described embodiment. It is intended that the invention cover all modifications and alternatives which may be included within the spirit and scope of the invention. 
         [0017]    The present invention generally includes an apparatus  10  on which forecasts  12  can be created, received, stored and transmitted. Additional equipment  14  on the apparatus will also include equipment to detect  16  one or more environmental conditions  18 , equipment  20  to incorporate the data  22  sensed relating to that environmental condition  18  into a forecast  12 , and equipment  24  to store, transmit or use the current forecast  18  to reduce the impact of upcoming environmental changes. For example, software  26  of a forecast model  28  can be uploaded to an operational piece of equipment  10  such as a power grid controller, an aircraft, spacecraft or a seismic station. Due to the small size of algorithms, they can easily be allocated onboard without taking away from much of the data storage and memory. The equipment  16  at the desired location is able to measure a physical parameter such as a geomagnetically induced current, a radiation environment such as one exposed to particles and photons, electromagnetic fields, Richter scale measurements or other physical parameters. 
         [0018]    With such equipment  16  locally available, these one or more physical parameters or environmental conditions  18  can be measured in real time and data  22  is created from these measurements. Such data  22  is then used to create a forecast  12  using the forecasting model(s)  28  in the software  26 . 
         [0019]    Adverse forecasts  12  can be shared with other equipment  30  in the general area or transmitted to a remote location for notifications. Preferably, locally created adverse forecasts  12  electronically trigger either automatic operational changes or human notifications. For example, a satellite  10  detecting an incoming solar flare  18  or other adverse solar activity can shut down or go into a safety mode to protect sensitive equipment, current loads in a power grid can be reduced, or aircraft can be rerouted to new altitudes or in new directions. Preferably, the system  10  of the present invention can also provide notifications outside of its local area to notify other equipment  30  which lacks in-situ forecasting ability or to provide human notifications. For example, an adverse forecast  12  can automatically trigger a noise or visual alarm to tell humans to seek shelter and this alarm message can be sent to other locations deemed to be in the path of the incoming adverse conditions  18 . 
         [0020]    Forecasts  12  need to be disseminated as quickly and as effectively as possible in order for risk mitigation to be optimized. The present invention ensures this by coupling the forecasting system  32  with the systems originally used to obtain the measurements that form the inputs for the forecast model algorithm  34 . In this manner, the present invention minimizes the delay in receiving remote adverse forecasts  12  and optimizes the time to take actions to minimize potential impact from an adverse weather event  18 . Absent the present invention, astronauts on the way to Mars would have to wait to receive a solar radiation forecast from Earth, which could significantly impact their ability to timely take shelter or position sensitive equipment so as to reduce harmful effects. With the present invention onboard, the risks associated with an adverse environmental event which can be forecast can be more effectively mitigated. 
         [0021]    Focusing on one example which is an embodiment, but not the exclusive embodiment of the invention, space weather is likely the most transparent because the effects are usually felt globally and require spacecraft technologies. As shown in  FIG. 1 , automatic space weather event detection algorithms  36  are uploaded to the GOES-R spacecraft  10  (pre or post launch) and stored on a computer  20 . Space weather forecasting/predicting algorithms  34  are also uploaded to the GOES-R spacecraft  10  to be used by the computer  20 . The GOES-R spacecraft  10  is typical of a spacecraft embodiment of the present invention and includes a solar array  38  or other power source for various onboard instrumentation and systems  14 . Such systems  14  can include many types of data collection instrumentation  16 , such as a solar ultraviolet imager  40 , extreme ultraviolet and x-ray irradiance sensors  42 , particle sensors  44 , a magnetometer  46 , a geostationary lighting mapper  48  or an advanced baseline imager  50 , examples of which are shown in  FIG. 2 . 
         [0022]    Preferably, the computer  20  includes a space environment in-situ suite to allow for onboard forecasting using algorithms  34 ,  36  located and stored onboard or uploaded as desired through the spacecraft&#39;s transceivers  54 . Once onboard, such algorithms  34 ,  36  are placed into data storage  24  or memory chips operatively connected to the space environment in-situ suite computer  20 . The space environment in-situ suite computer  20  also preferably includes one or more processors  56  to use the algorithms  34 ,  36 , wherein the processors  56  are operatively linked to the power source  38  and data collection instrumentation  16 . This allows the processors  56  to use the collected data  22  with the algorithms  34 ,  36  to create a locally generated forecast  12 . The processors  56  are also operatively linked to additional memory  24  to store the locally generated forecast  12  and one or more transceivers  54  to transmit any forecasts  12  of interest, data  22  of interest or other information as desired. These transceivers  54  also allow the system  10  to receive updated forecasting algorithms  34  as well as additional data  22  from external sources  58  that may be considered in the forecasting model  28 . 
         [0023]    More information on the GOES-R spacecraft  10  can be found at: http://www.goes-r.gov/mission/mission.html, which is incorporated herein in its entirety by reference (GOES future missions—4 satellites: 2016-2034). The space weather event detections  60  can include, but not are not limited to run on the solar imaging as shown in  FIG. 2 , magnetic field, proton, and photon instruments  16 , which generate data  22  that is visualized as shown in  FIGS. 3 and 4 . Utilizing the SUVI, instrument automatic detection algorithms  36  can extract metadata  62  on filaments, coronal holes, active regions, dimmings, and flares as discussed at http://www.goes-r.gov/spacesegment/suvi.html. Utilizing the MAG instrument automatic detection algorithms  36  will extract information on coronal mass ejections&#39; (CMEs) magnetic fields. http://www.goes-r.gov/spacesegment/mag.html. Utilizing the SEISS instrument automatic detection algorithms  36  will extract information on incoming protons and electrons (radiation events). http://www.goes-r.gov/spacesegment/seiss.html. Utilizing the EXIS instrument automatic detection algorithms  36  will extract information on the Sun&#39;s X-ray and EUV output. http://www.goes-r.gov/spacesegment/seiss.html. 
         [0024]    Based on the benchmarked metadata an algorithm  34  desired for space weather event prediction is developed. Preferably, this algorithm  34  is then uploaded to the spacecraft  10  and integrated to all of the event detection algorithms  36  that are needed to produce the prediction/forecast  12 . Onboard forecasting allows for more frequent forecasting as the data  22  can be gathered in real time and the forecasts  12  are preferably produced continually. If forecasting suggests a large enough adverse event  18 , GOES-R  10  may be pre-programmed to enter into safety mode  64  to protect sensitive hardware/software. It should be noted that this satellite  10  is designed to continually monitor the Sun and a safety mode turning off all the instruments is unlikely. The forecasts  12  may also be disseminated to a ground station  66  and/or nearby spacecraft  30  for risk-mitigation purposes. The forecasts  12  cover the most impactful of space weather events  18 : X-ray events (solar flares), particle events (radiation), and CMEs (geomagnetically induced currents (GICs)). 
         [0025]    A general flow chart illustrating the exemplary embodiment discussed above is shown in  FIG. 4A . As can be seen, data  22  collected from onboard sensors  16  is initially stored in memory  24 , on a hard disk or otherwise as desired, until downloaded to a receiving station  66  on Earth and is preferably erased after detection algorithms  36  have been performed to create the necessary metadata  62  desired for forecasting. This helps to minimize both onboard memory  24  requirements as well as minimizing power usage and weight associated with such systems. After data  22  from measurements performed by the desired detection equipment  16  has been gathered, it is stored and preferably also transmitted to another remote location or device  30 . Onboard automatic detection algorithms  36  are then employed to create the desired metadata  62 . This onboard metadata  62  is preferably temporarily stored for use in the desired forecasting model or models  28 . Additionally, this metadata  62  is also preferably transmitted via the onboard transceivers  54  or other downlinks to remote or ground based locations  66 . This allows for forecast verifications  68  based on common data  22 ,  62  as both the in-situ automatic detection algorithms  36  and the ground based automatic detection algorithms run on the same data  22 ,  62  and the output metadata can then be compared. This will help to improve risk mitigation procedures at both locations. 
         [0026]    Multiple forecasting models  28  can be run if the end-user or system  10  desires a variety of space weather predictions or forecasts  12  in order to achieve the best risk mitigation. Subsequently, the forecasts  12  are created and may be utilized in preferably automated risk mitigation efforts onboard the spacecraft  10 . For example, an adverse forecast  12  can prompt an automatic equipment reaction, such as prompting a thruster  72  to reposition the spacecraft  10  or prompting sensitive equipment to enter a safe mode  64 , or an automated alert  70  can be generated by the computer  20  to indicate steps to be taken to protect sensitive equipment or crew. Additionally, the created forecast(s)  12  can be sent to other spacecraft  30  or ground based operations  66  as desired. 
         [0027]    It should also be noted that this example focuses strictly on a spacecraft implementation. However, there may be the possibility of having the same system run wherever provided that it is in the necessary environment (measurements) to predict a natural event. For instance, algorithms could be run at PJM power grid stations that measure GICs. GIC events combined with forecasts disseminated by GOES may give the grid industry better risk-mitigation procedures. As another example, if you have a colony on Mars, you would want the forecast system on the ground as well onboard a satellite orbiting Mars. 
         [0028]    A general description of the present invention as well as a preferred embodiment of the present invention has been set forth above. Those skilled in the art to which the present invention pertains will recognize and be able to practice additional variations in the methods and systems described which fall within the teachings of this invention. Accordingly, all such modifications and additions are deemed to be within the scope of the invention which is to be limited only by the claims appended hereto.