A predictive real time and prospective environmental analysis and display system accessible by one or more client computing devices through a network to depict on the display surface of a computing device a graphical representation of a geographic environment which can be delimited into one or more two or three-dimensional zones in which visual indicators provide predicted current or prospective airflow speed or direction values associated with the geographic environment.

Disclosed embodiments include systems, vehicles, and methods for presenting weather conditions a traveler may encounter while traveling a route. In an illustrative embodiment, a computing device executes instructions to present an integrated route map. An input is received indicative of a trip to be made to a destination by a traveler. A store of route data for an area encompassing the trip is accessed. At least one route is identified. A weather forecasting service is accessed from which expected weather conditions are accessible for the area through the projected time. The expected weather conditions are identified for the location at the projected time. An integrated route map is displayed showing the at least one route and the expected weather conditions for the location at the projected time.

Methods and systems for generating a multi-model ensemble of global climate simulation data from a plurality of pre-existing global climate simulation model (GCM) datasets, are disclosed. The methods and systems perform steps of computing a GCM dataset validation measure based on at least one sample statistic for at least one climate variable from the pre-existing GCM dataset; selecting a validated subset of the plurality of pre-existing GCM datasets; selecting a subset of GCM datasets; generating candidate ensembles of GCM datasets; computing an ensemble forecast skill score for each candidate ensemble based on a model analog; generating the multi-model ensemble of GCM datasets by selecting a candidate ensemble with a best ensemble forecast skill score; and training the NN-based climate forecasting model using the multi-model ensemble of GCM datasets. Embodiments of the present invention enable accurate climate forecasting without the need to run new dynamical global climate simulations on supercomputers.

Improved mechanisms for collecting information from a diverse suite of sensors and systems, calculating the current precipitation, atmospheric water vapor, atmospheric liquid water content, or precipitable water and other atmospheric-based phenomena, for example presence and intensity of fog, based upon these sensor readings, predicting future precipitation and atmospheric-based phenomena, and estimating effects of the atmospheric-based phenomena on visibility, for example by calculating runway visible range (RVR) estimates and forecasts based on the atmospheric-based phenomena.

A computer-implemented method includes obtaining a worksite condition corresponding to a worksite operation of a mobile work machine, generating a machine performance metric representing operational performance of the mobile work machine for the worksite operation, generating a machine impact metric based on a comparison of the machine performance metric and a base performance metric, generating a correlation between the machine impact metric and the worksite condition, and generating a machine control signal based on the correlation.

The amount of carbon dioxide absorbed by plants grown in a field can more accurately be estimated based on environmental information of the field. A plurality of types of mutually-differing environmental information are measured regarding an installation field. For the plurality of types of environmental information, the correspondence relationship between each type of environmental information and a carbon dioxide (CO.sub.2) absorption amount is stored. A plurality of CO.sub.2 absorption amounts are acquired by referring to the respective correspondence relationship for each type of measured environmental information. The acquired plurality of CO.sub.2 absorption amounts are compared with each other and the minimum value thereof is selected as the estimated value. Information regarding the selected estimated value is displayed.

A method for characterizing gas emissions includes sampling each of a plurality of sectors having a common geographic center. For each sector, a first laser beam is transmitted from the geographic center to a first retroreflection location, where it is retroreflected into a first retroreflected beam. Near the geographic center, the first retroreflected beam is measured to obtain a first absorption. A second laser beam is then transmitted from the geographic center to a second retroreflection location, where it is retroreflected into a second retroreflected beam. Near the geographic center, the second retroreflected beam is measured to obtain a second absorption. The first and second retroreflection locations are both located within the same sector. First and second concentrations are determined from the first and second absorptions and processed to determine emission information about a known or potential gas source whose source lies within the sector.

A method for quantifying the extent and recurrence of a predetermined natural event, such as a flooding event, in a geographical area, in particular in spite of the absence of reliable data from sensors on the ground where the natural event develops. The method relies on remote sensing data, such as satellite imagery, and data processing, and reaps the benefits of computational models based on accurate remote sensing of the area under consideration.

Concepts are proposed for augmenting a plurality of climate impact and hazard models. In particular, the plurality of climate impact and hazard models are modified/altered based on a user-specified requirement (i.e., a specified geographical location, temporal location or hazard type) and at least one intelligent (i.e., AI-enabled) workflow. Each modified climate impact and hazard model is then analyzed/processed using a machine learning model to identify model parameters which may improve the climate impact and machine learning model. An operation is then identified and executed based on the intelligent workflow, and model parameter. In this way, speed, efficiency and accuracy of climate impact and hazard models may be improved at scale.

The system as described collects and utilizes weather data sensor information in order to rapidly collect and update weather forecasts using real-time weather data collected at high rates of frequency, and use this collected high frequency weather data to rapidly correct and update the weather forecasts generated by the system.