The state prediction device smoothes a state vector including a flow rate and a water level of a tsunami at each of a plurality of points set two-dimensionally in a region including a coverage area, by using flow velocity observed values of a sea surface in a plurality of cells extending in a plurality of range directions and a plurality of beam directions in the coverage area of a radar.

In some examples, a system includes a weather radar device configured to transmit radar signals, receive first reflected radar signals at a first time, and receive second reflected radar signals at a second time. In some examples, the system also includes processing circuitry configured to determine a first magnitude of reflectivity based on the first reflected radar signals and determine a second magnitude of reflectivity based on the second reflected radar signals. In some examples, the processing circuitry is also configured to determine a temporal variance in reflectivity magnitudes based on determining a difference in reflectivity between the first magnitude and the second magnitude. In some examples, the processing circuitry is further configured to determine a presence of ice crystals based on the first magnitude of reflectivity, the second magnitude of reflectivity, and the temporal variance in reflectivity magnitudes.

Predicting weather radar images by building a first machine learning model to generate first predictive radar images based upon input weather forecast data, and a second machine learning model to generate second predictive radar images based upon historical radar images and the first predictive radar images. Further by generating enhanced predictive radar images by providing the first machine learning model weather forecast data for a location and time and providing the second machine learning model with historical radar images for the location and an output of the first machine learning model.

In some examples, a system is configured for determining an estimated altitude of a melting layer, and the system includes a weather radar device configured to transmit radar signals and receive reflected radar signals. In some examples, the system also includes processing circuitry configured to determine the estimated altitude of the melting layer based on the reflected radar signals.

An apparatus for composition for dual-polarization weather radar observation data includes: a coordinate system converting unit that converts a reference grid of an orthogonal coordinate system into a grid of a dual-polarization weather radar spherical coordinate system based on a latitudinal-longitudinal coordinate system for each individual dual-polarization weather radar by using an earth spherical coordinate system; a CAPPI data generating unit that generates CAPPI data based on the orthogonal coordinate system after mapping individual items of dual-polarization weather radar observation data on grid coordinates of the dual-polarization weather radar spherical coordinate system; and a CAPPI data compositing unit that performs composition of CAPPI data for each of the individual dual-polarization weather radars located at the same coordinate of the orthogonal coordinate system obtained by mapping the individual items of dual-polarization weather radar observation data thereon.

A method for forecasting flood, the method including: calibrating the hydrological model by using an objective function that is a sum of squared difference between the observed streamflow and the corresponding forecasted streamflow at each lead time to obtain the optimized hydrological model; using the optimized hydrological model to forecast floods; and evaluating forecasting performance of the optimized hydrological model. The method improves the forecasting accuracy and provides forecasting results at various lead times.

An apparatus and a method for estimating rainfall of hail and rain using a dual-polarization weather radar improve accuracy of classification of hail and rain zones and estimation of rainfall intensity by classifying hail and rain zones using a distribution of horizontal reflectivity and differential reflectivity of radar observation values, discriminating between a convective zone and a stratiform zone depending on reflection intensity, and applying a dual-polarization-based rainfall estimating relational equation for each type in a weighted mean technique.

In some examples, a system includes a weather radar device configured to transmit radar signals, receive first reflected radar signals at a first time, and receive second reflected radar signals at a second time. In some examples, the system also includes processing circuitry configured to determine a first magnitude of reflectivity based on the first reflected radar signals and determine a second magnitude of reflectivity based on the second reflected radar signals. In some examples, the processing circuitry is also configured to determine a temporal variance in reflectivity magnitudes based on determining a difference in reflectivity between the first magnitude and the second magnitude. In some examples, the processing circuitry is further configured to determine a presence of ice crystals based on the first magnitude of reflectivity, the second magnitude of reflectivity, and the temporal variance in reflectivity magnitudes.

Disclosed in some examples are methods, systems, devices, and machine-readable media for 3D radar weather data rendering techniques. A computer-implemented method for 3D radar weather data rendering includes retrieving weather data from a weather radar. Gridded data is generated based on the weather data. The gridded data includes a uniform grid of cubes, where each of the cubes is associated with at least one weather parameter value of a plurality of weather parameter values corresponding to the weather data. A triangular mesh for a data grouping within the gridded data is extracted. An object file including vertices and faces associated with the triangular mesh is generated. The object file is communicated to a three-dimensional (3D) visualization system to present a 3D rendering of the object file.

A forensic weather analyzer compares actual meteorological readings with data from multiple weather models. The data is compared and a forensic weather model is selected as the weather model that most closely matches the meteorological readings. The forensic weather model is then used to provide meteorological information pertaining to a weather event such as a hurricane, at a specific location such as a street address.