In situ measurement station for monitoring wind and water properties in extreme hydrodynamic conditions
The present disclosure describes various embodiments of systems, apparatuses, and methods for large-scale processing of weather-related data. For one such system, the system comprises a database of weather-related data providing from a plurality of weather monitoring stations and a plurality of interconnected processors for coordinating a data processing job for processing a set of input weather-related data from the database. Accordingly, the input data comprises sensor data from an array of weather monitoring stations positioned on an open shoreline during a hydrodynamic event, weather model data for the hydrodynamic event, and at least one of air-craft reconnaissance data or satellite reconnaissance data regarding the hydrodynamic event, wherein the plurality of interconnected processors are configured to assimilate the input data and generate, using machine learning, an improved weather prediction model for the hydrodynamic event. Other systems, apparatuses, and methods are also provided.
1. A system for large-scale processing of weather-related data comprising:
a database of weather-related data providing from a plurality of weather monitoring stations;
a plurality of interconnected processors for coordinating a data processing job for processing a set of input weather-related data from the database,
wherein the input weather-related data comprises sensor data from an array of weather monitoring stations positioned on an open shoreline during a hydrodynamic event, weather model data for the hydrodynamic event, and at least one of air-craft reconnaissance data or satellite reconnaissance data regarding the hydrodynamic event;
wherein the plurality of interconnected processors is configured to assimilate the input data and generate, using machine learning, an improved weather prediction model for the hydrodynamic event.
2. The system of claim 1 , wherein the plurality of interconnected processors is further configured to identify and predict patterns of extreme hydrodynamic events based on an assimilation of meteorological observations derived from the weather-related data that include surface wind observations at the open shoreline.
3. The system of claim 2 , wherein the sensor data comprises surface wind velocity measurements obtained from the weather monitoring stations at the open shoreline.
4. The system of claim 3 , wherein the sensor data comprises water level measurements obtained from the weather monitoring stations at the open shoreline.
5. The system of claim 4 , wherein the sensor data comprises wind pressure sensor data and air temperature sensor data from the open shoreline.
6. The system of claim 5 , wherein the sensor data further comprises water temperature data and salinity sensor data from the open shoreline.
7. The system of claim 6 , wherein the sensor data further comprises erosion sensor data from the open shoreline.
8. The system of claim 7 , wherein the sensor data is augmented with video data obtained from the weather monitoring stations at the open shoreline.
9. The system of claim 1 , wherein an individual weather monitoring station comprises:
an upper mast section having an instrumentation package, wherein the instrumentation package at the upper mast section includes an orientation sensor to detect an orientation of the upper mast section relative to the earth surface's coordinate system, communications circuitry that is configured to establish a communications network with a network base station; at least a wind velocity sensor, and a control unit that is configured to at least receive sensor data and transmit communication data via the communications circuitry;
at least one lower mast section that is coupled to the upper mast section; and
an anchoring system that is coupled to the lower mast section, wherein the anchoring system includes at least one subsurface anchor for inserting into a ground surface within a littoral zone of a coastal area.
10. The system of claim 1 , wherein the plurality of interconnected processors is configured to utilize machine learning to extract wave field information from the sensor data supplied by the plurality of weather monitoring stations.
11. The system of claim 1 , wherein the plurality of interconnected processors is configured to compute parameters of a storm structure based on the sensor data supplied by the plurality of weather monitoring stations.
12. The system of claim 1 , wherein the plurality of interconnected processors is configured to predict behavior of a storm based on the sensor data supplied by the plurality of weather monitoring stations.
13. The system of claim 1 , wherein the plurality of interconnected processors is configured to train the improved weather prediction model using the sensor data obtained from the weather monitoring stations at the open shoreline during an actual landfall hurricane event.
14. A method for large-scale processing of weather-related data comprising:
accessing, by a computer-based system, a database of weather-related data providing from a plurality of weather monitoring stations; and
assimilating a set of input weather-related data from the database and generating, using machine learning, an improved weather prediction model for a hydrodynamic event,
wherein the input weather-related data comprises sensor data from an array of weather monitoring stations positioned on an open shoreline during a hydrodynamic event, weather model data for the hydrodynamic event, and at least one of air-craft reconnaissance data or satellite reconnaissance data regarding the hydrodynamic event.
15. The method of claim 14 , further comprising predicting, by the computer-based system using machine learning, patterns of extreme hydrodynamic events based on an assimilation of meteorological observations derived from the weather-related data that include surface wind observations at the open shoreline.
16. The method of claim 14 , wherein the sensor data comprises surface wind velocity measurements, water level measurements, wind pressure sensor data, air temperature sensor data, water temperature data, salinity sensor data, and erosion sensor data, each obtained from the weather monitoring stations on the open shoreline.
17. The method of claim 14 , wherein the sensor data is augmented with video data obtained from the weather monitoring stations at the open shoreline.
18. The method of claim 14 , wherein an individual weather monitoring station comprises:
an upper mast section having an instrumentation package, wherein the instrumentation package at the upper mast section includes an orientation sensor to detect an orientation of the upper mast section relative to the earth surface's coordinate system, communications circuitry that is configured to establish a communications network with a network base station; at least a wind velocity sensor, and a control unit that is configured to at least receive sensor data and transmit communication data via the communications circuitry;
at least one lower mast section that is coupled to the upper mast section; and
an anchoring system that is coupled to the lower mast section, wherein the anchoring system includes at least one subsurface anchor for inserting into a ground surface within a littoral zone of a coastal area.
19. The method of claim 14 , further comprising:
extracting, by the computer-based system using machine learning, wave field information from the sensor data supplied by the plurality of weather monitoring stations;
computing, by the computer-based system using machine learning, parameters of a storm structure based on the sensor data supplied by the plurality of weather monitoring stations; and
predicting, by the computer-based system using machine learning, behavior of a storm based on the sensor data supplied by the plurality of weather monitoring stations.
20. The method of claim 14 , further comprising training, by the computer-based system using machine learning, the improved weather prediction model using the sensor data obtained from the weather monitoring stations at the open shoreline during an actual landfall hurricane event.