DYNAMIC STORM ENVIRONMENT ENGINE APPARATUSES, METHODS AND SYSTEMS

• US 20160356922A1
• Filed: 12/22/2014
• Published: 12/08/2016
• Est. Priority Date: 12/22/2013
• Status: Abandoned Application

• Current Assignee: DTN, LLC (TBG AG)
• Original Assignee: Telvent DTN Incorporated (TBG AG)
• Inventors: MCCANN, Donald, LENNARTSON, Daniel W., BLOCK, James H.
• Application Number:
  US15/104,147
• Publication Number:
  US 20160356922A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01W 1/00 Meteorology
• CPC Class Codes: G01W 1/10 Devices for predicting weather conditions computers per se G06; display devices G09
• CPC Class Codes: G01W 2001/003 Clear air turbulence detection or forecasting, e.g. for aircrafts
• CPC Class Codes: G01W 2203/00 Real-time site-specific personalized weather information, e.g. nowcasting
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The DYNAMIC STORM ENVIRONMENT ENGINE (DSEE) transforms flight profiles, atmospheric data, and convective and non-convective turbulence predictions and observations into dynamic turbulence alerts, nowcasts, and optimized flight paths. The DSEE determines four-dimensional grid points for a temporal geographic area and determines atmospheric potential instability and potential turbulence intensity at each grid point. The DSEE masks potential turbulence intensity at least one grid point and determines and outputs at least one of the TKE and the total EDR for each grid point. In some implementations, the DSEE receives a flight profile for an aircraft, including an initial route. The DSEE can identify an initial predicted comprehensive turbulence for the at least one initial route and/or turbulence nowcast, and the predicted comprehensive turbulence and/or turbulence nowcast utilized generate a notification or exception, and/or are used to reroute the aircraft to avoid or minimize the effects of turbulence on the flight.

Claims

1. A dynamic storm environment short-term in-flight turbulence forecast processor-implemented method, comprising:

receiving a flight profile for an aircraft, the flight profile including an at least one initial route;

determining non-convective turbulence and a convective turbulence forecast for at least a portion of the at least one initial route;

receiving lightning data for at least the portion of the at least one initial route;

masking the convective turbulence forecast by the received lightning data;

projecting the masked convective turbulence forecast for a specified nowcast period;

integrating the projected masked convective turbulence forecast and the non-convective turbulence to determine a preliminary turbulence estimate;

transforming the preliminary turbulence estimate by at least one turbulence observation associated with the at least the portion of the at least one initial route, via a processor, to determine a turbulence nowcast for the specified nowcast period;

determining turbulence threshold compliance based on the turbulence nowcast and the flight profile; and

generating a turbulence exception if the turbulence nowcast exceeds threshold turbulence parameters.

2. The method of claim 1, wherein the turbulence exception comprises an alert for the aircraft and/or determining an at least one adjusted route.

4. The method of claim 2, wherein determination of the at least one adjusted route is based on flight profile data.

5. The method of claim 4, wherein the flight profile data comprises at least one of flight service type, flight destination location, aircraft airframe, and available fuel reserves.

7. The method of claim 1, wherein determining non-convective turbulence and a convective turbulence forecast for at least the portion of the at least one initial route includes:

determining a plurality of four-dimensional grid points for a specified temporal geographic space-time area associated with the portion of the at least one initial route;

obtaining atmospheric data based on the temporal geographic space-time area;

for each point of the plurality of four-dimensional grid points, determining at least one of;

areas of atmospheric potential instability;

a potential turbulence intensity at each grid point;

an upper level non-dimensional gravity wave amplitude;

a buoyant turbulent kinetic energy;

a boundary layer eddy dissipation rate;

storm velocity and eddy dissipation rate from updrafts;

maximum updraft speed at grid point equilibrium level;

storm divergence while the updraft speed is above the equilibrium level and identifying storm top;

storm overshoot and storm drag;

Doppler speed;

eddy dissipation rate above the storm top;

eddy dissipation rate from downdrafts; and

determining at least one of the turbulent kinetic energy and/or the total eddy dissipation rate for each grid point.

8. The method of claim 7, wherein the atmospheric data comprises at least one of temperature data, wind data, numerical weather forecast model data, aircraft sensor data, and humidity data.

10. The method of claim 1, wherein determining non-convective turbulence and a convective turbulence forecast for at least the portion of the at least one initial route includes:

determining a plurality of four-dimensional grid points for a specified temporal geographic space-time area;

obtaining atmospheric data;

for each point of the plurality of four-dimensional grid point,

determining areas of atmospheric potential instability, and

determining a potential turbulence intensity at each grid point;

masking potential turbulence intensity at an at least one grid point; and

determining at least one of the turbulent kinetic energy and the total eddy dissipation rate for each grid point.

11. The method of claim 10, wherein the masking of potential turbulence intensity is based on at least one of:

convective observations, future-derived observations, lightning density, satellite data, and storm overshoot data.

16. The method of claim 1, wherein projecting the masked convective turbulence forecast includes moving each of a plurality of eddy dissipation rate grid points associated with the masked convective turbulence forecast based on storm advecting wind and storm propagating vector for the specified nowcast period.

17. The method of claim 1, wherein the at least one turbulence observation is from before the nowcast period.

18. The method of claim 1, wherein the at least one turbulence observation includes at least one of an in-flight turbulence observation, PIREP data, and a real-time turbulence observation.

21. The method of claim 18, wherein the PIREP data is weighted by an aircraft response factor.

22. The method of claim 7, wherein transforming the preliminary turbulence estimate by turbulence observations, is, for a particular point of the plurality of four-dimensional grid points, based on the difference between the preliminary turbulence estimate for the point and the at least one turbulence observation, inversely weighted by a factor of the distance between the point and the at least one turbulence observation.

23. The method of claim 1, wherein determining non-convective turbulence and a convective turbulence forecast for at least a portion of the at least one initial route includes:

determining non-dimensional mountain wave amplitude (â

_mv) and the mountain top wave drag;

determining upper level non-dimensional gravity wave amplitude (â

_ul);

summing â

_mv and â

_ul into (â

) to determine buoyant turbulent kinetic energy (TKE_buoy);

setting TKE_buoy=TKE_mv+TKE_ul-buoy if a is greater than 1, and setting TKE_buoy=0 if a is not greater than 1;

setting TKE=TKE_{ul,wshr if} â

greater than â

_min;

determining a boundary layer EDR, wherein if EDR_bl is greater than zero and â

_mv is not enhanced, then setting EDR=EDR_bl, else setting EDR as TKE^1/3.

24. The method of claim 1, wherein determining non-convective turbulence and a convective turbulence forecast for at least a portion of the at least one initial route includes:

determining if an associated parcel or portion is moist, and if not, setting an associated EDR to null, wherein if the parcel or portion is moist, and if a lifted condensation level pressure is greater than a current layer pressure level, determining a difference between a parcel or portion temperature and environmental temperature and vertical acceleration, and wherein if the parcel or portion is moist, and if the lifted condensation level pressure is not greater than the current layer pressure level, setting the vertical acceleration to zero;

determining an updraft EDR and a downdraft EDR, the downdraft EDR based on actual downward vertical velocity; and

setting an overall EDR for the associated parcel or portion based on the larger of the updraft EDR and downdraft EDR.

25. The method of claim 1, wherein masking the convective turbulence forecast by the received lightning data comprises setting an associated EDR based on lightning data.

26. The method of claim 1, wherein determining non-convective turbulence and a convective turbulence forecast for at least a portion of the at least one initial route includes, for each parcel associated with the at least one portion of the at least one initial route:

determining an indication of moist or not moist, wherein if the parcel not moist, setting EDR set to null, and if the parcel is moist and if the lifted condensation level pressure is not greater than the current layer pressure level, setting a vertical acceleration to zero, and if the parcel is moist and if the lifted condensation level pressure is greater than a current layer pressure level then determining a vertical acceleration based on parcel temperature and environmental temperature, wherein if the vertical acceleration is negative, setting the vertical velocity at the top to zero, while if the vertical acceleration is not negative, determining the vertical velocity at the top of the layer and the mean upward vertical velocity; and

determining an updraft EDR based on the mean vertical velocity

3. (canceled)

6. (canceled)

9. (canceled)

12-15. -15. (canceled)

19-20. -20. (canceled)

27. A processor-implemented method of providing an aircraft turbulence nowcast for a geospatial aviation volume, comprising:

determining non-convective turbulence values for a geospatial aviation volume associated with an at least one aircraft;

determining convective turbulence forecast values for the geospatial aviation volume;

masking convective turbulence forecast values for the geospatial aviation volume by lightning data for the geospatial aviation volume to provide masked convective turbulence values for the geospatial aviation volume;

projecting the masked convective turbulence values through the geospatial aviation volume for a specified nowcast period;

integrating the non-convective turbulence values and projected masked convective turbulence values to provide a preliminary turbulence estimate for the geospatial aviation volume for the specified nowcast period;

transforming the preliminary turbulence estimate by actual turbulence observations associated with the geospatial aviation volume to generate an aircraft turbulence nowcast for the geospatial aviation volume associated with the at least one aircraft; and

transmitting the aircraft turbulence nowcast to a control system associated with the at least one aircraft.

28. The method of claim 27, wherein determining non-convective turbulence values includes:

determining non-dimensional mountain wave amplitude (â

_mv) and the mountain top wave drag;

determining upper level non-dimensional gravity wave amplitude (â

_ul);

summing â

_mv and â

_ul into (a) to determine buoyant turbulent kinetic energy (TKE_buoy);

setting TKE_buoy=TKE_mv+TKE_ul-buoy if a is greater than 1, and setting TKE_buoy=0 if a is not greater than 1;

setting TKE=TKE_{ul-wshr if} â

greater than â

_min; and

determining a boundary layer EDR, wherein if EDR_bl is greater than zero and â

_mv is not enhanced, then setting EDR=EDR_bl, else setting EDR as TKE^1/3.

29. The method of claim 27, wherein determining convective turbulence values includes:

determining if an associated parcel or portion is moist, and if not, setting an associated EDR to null, wherein if the parcel or portion is moist, and if a lifted condensation level pressure is greater than a current layer pressure level, determining a difference between a parcel or portion temperature and environmental temperature and vertical acceleration, and wherein if the parcel or portion is moist, and if the lifted condensation level pressure is not greater than the current layer pressure level, setting the vertical acceleration to zero;

determining an updraft EDR and a downdraft EDR, the downdraft EDR based on actual downward vertical velocity; and

determining an overall EDR for the associated parcel or portion based on the larger of the updraft EDR and downdraft EDR.

30. The method of claim 27, wherein determining convective turbulence values includes, for each of a plurality of parcels associated with the geospatial aviation volume:

determining an indication of moist or not moist, wherein if the parcel not moist, setting EDR set to null, and if the parcel is moist and if the lifted condensation level pressure is not greater than the current layer pressure level, setting a vertical acceleration to zero, and if the parcel is moist and if the lifted condensation level pressure is greater than a current layer pressure level then determining a vertical acceleration based on parcel temperature and environmental temperature, wherein if the vertical acceleration is negative, setting the vertical velocity at the top to zero, while if the vertical acceleration is not negative, determining the vertical velocity at the top of the layer and the mean upward vertical velocity; and

determining an updraft EDR based on the mean vertical velocity.

31. The method of claim 27, wherein transforming the preliminary turbulence estimate by actual turbulence observations associated with the geospatial aviation volume for a specified point within the geospatial aviation volume includes transforming the preliminary turbulence estimate by turbulence observations based on the difference between the preliminary turbulence estimate for the point and the at least one turbulence observation, inversely weighted by a factor of the distance between the point and the at least one turbulence observation.

32. (canceled)

33. (canceled)