Example embodiments provide systems and methods for simulating a disease outbreak using a relatively simple formula based on a limited number of input parameters. In particular, disease severity is computed based on a relationship between leaf wetness duration and average temperature during a wetness period. The resulting model is a physical, deterministic model that accepts hourly weather data as input and outputs the most significant severity event of disease infection during a specified (e.g., one-day) period. This information can then be used to guide the application of various treatments when they can be most effective (e.g., when predicted disease severity is at its worst).

Example embodiments provide systems and methods for simulating a disease outbreak using a relatively simple formula based on a limited number of input parameters. In particular, disease severity is computed based on a relationship between leaf wetness duration and average temperature during a wetness period. The resulting model is a physical, deterministic model that accepts hourly weather data as input and outputs the most significant severity event of disease infection during a specified (e.g., one-day) period. This information can then be used to guide the application of various treatments when they can be most effective (e.g., when predicted disease severity is at its worst).

An atmospheric turbulence detection method includes: providing a temperature difference measuring device including a thermocouple element and two sensing probes, wherein the thermocouple element has two opposite end portions, the two sensing probes are respectively disposed at the two end portions, and there is an ambient distance between the two end portions; placing the temperature difference measuring device in an atmospheric environment to generate an electromotive force by a temperature difference between the two end portions; analyzing the electromotive force to convert the electromotive force into an ambient temperature difference of an environment where the two end portions of the thermocouple element are located, an atmospheric refractive index structure constant is calculated according to the ambient temperature difference and the ambient distance, and a value of the atmospheric refractive index structure constant corresponds to an ambient disturbance of an atmospheric turbulence. An atmospheric turbulence detection device is also provided.

An atmospheric turbulence detection method includes: providing a temperature difference measuring device including a thermocouple element and two sensing probes, wherein the thermocouple element has two opposite end portions, the two sensing probes are respectively disposed at the two end portions, and there is an ambient distance between the two end portions; placing the temperature difference measuring device in an atmospheric environment to generate an electromotive force by a temperature difference between the two end portions; analyzing the electromotive force to convert the electromotive force into an ambient temperature difference of an environment where the two end portions of the thermocouple element are located, an atmospheric refractive index structure constant is calculated according to the ambient temperature difference and the ambient distance, and a value of the atmospheric refractive index structure constant corresponds to an ambient disturbance of an atmospheric turbulence. An atmospheric turbulence detection device is also provided.

Example embodiments provide systems and methods for simulating a disease outbreak based on a limited number of input parameters. In one embodiment, a disease severity level is computed based on a relationship between leaf wetness duration and average temperature during a wetness period. The resulting model can be a physical, deterministic model that accepts hourly weather data as input and outputs the most significant severity event of disease infection during a specified period.

Example embodiments provide systems and methods for simulating a disease outbreak based on a limited number of input parameters. In one embodiment, a disease severity level is computed based on a relationship between leaf wetness duration and average temperature during a wetness period. The resulting model can be a physical, deterministic model that accepts hourly weather data as input and outputs the most significant severity event of disease infection during a specified period.

One or more computing devices, systems, and/or methods for generating profiles, such as weather profiles, based upon signals from vehicle devices are provided. In an example, a plurality of vehicle measure signals is received from a plurality of vehicle devices. A first vehicle measure signal of the plurality of vehicle measure signals is received from a first vehicle device, of the plurality of vehicle devices, connected to a first vehicle. The first vehicle measure signal is indicative of a first location of the first vehicle and one or more first vehicle measures determined using one or more first sensors of the first vehicle. A vehicle measure profile associated with a region is generated based upon the plurality of vehicle measure signals. The vehicle measure profile is indicative of one or more second vehicle measures at one or more locations within the region.

One or more computing devices, systems, and/or methods for generating profiles, such as weather profiles, based upon signals from vehicle devices are provided. In an example, a plurality of vehicle measure signals is received from a plurality of vehicle devices. A first vehicle measure signal of the plurality of vehicle measure signals is received from a first vehicle device, of the plurality of vehicle devices, connected to a first vehicle. The first vehicle measure signal is indicative of a first location of the first vehicle and one or more first vehicle measures determined using one or more first sensors of the first vehicle. A vehicle measure profile associated with a region is generated based upon the plurality of vehicle measure signals. The vehicle measure profile is indicative of one or more second vehicle measures at one or more locations within the region.

Embodiments of a system, device and method improve weather modeling approaches for use by air vehicles to mitigate weather hazards and/or optimize air vehicle operations. Various embodiments collect a set of independent measurements of atmospheric parameters of interest, collect a set of onboard measurements from one or more non-traditional atmospheric sensors onboard an air vehicle, process the collected measurements to identify values of selected atmospheric parameters and generate a model for relating raw sensor outputs from the non-traditional atmospheric sensors to the atmospheric parameters of interest.

Determining, broadcasting and using reference pressure data in a network of transmitters. Particular embodiments described herein include machines that select atmospheric data from weather stations within a transmitter network, use the selected atmospheric data to determine a reference atmospheric value, and transmit the reference atmospheric value from a transmitter to a mobile device for use in estimating an altitude of the mobile device. The atmospheric data may include any of reference pressures form the weather stations, measured temperatures from the weather stations, or reference temperatures from the weather stations. The reference atmospheric value may include a reference pressure value of a reference altitude, or a reference temperature value.