A5028697103- Meteorological Phenomena and Simulations
- Precipitation Measurement and Analysis
- Image and Signal Denoising Methods
- Underwater Acoustics Research
- Geophysical Methods and Applications
- Hydrological Forecasting Using AI
- Speech and Audio Processing
- Solar and Space Plasma Dynamics
- Flood Risk Assessment and Management
- Soil Moisture and Remote Sensing
- Atmospheric Ozone and Climate
- Spacecraft Design and Technology
National University of Defense Technology
2019-2024
Weather radar echo is the data detected by weather sensor and reflects intensity of meteorological targets. Using technique extrapolation, which prediction future echoes based on historical observations, approaching short-term conditions can be forecasted, warnings raised with regard to disastrous weather. Recently, deep learning extrapolation methods have been proposed show significant application potential. However, there are two limitations existing should considered. First, few...
Weather radar echo extrapolation has been one of the most important means for weather forecasting and precipitation nowcasting. However, effective time current methods is usually short. In this paper, to meet demand long-term in actual practice, we propose a hierarchical prediction recurrent neural network (HPRNN) extrapolation. HPRNN composed hierarchically stacked RNN modules refinement module, it employs both strategy coarse-to-fine mechanism alleviate accumulation error with contribute...
Abstract. Weather radar echo is one of the fundamental data for meteorological workers to weather systems identification and classification. Through technique extrapolation, future short-term conditions can be predicted severe convection storms warned. However, traditional extrapolation methods cannot offer accurate enough results since their modeling capacity limited, recent deep learning based make some progress but still remains a problem blurry prediction when making deeper which may due...
Radar echo extrapolation has been widely developed in previous studies for precipitation and storm nowcasting. However, most have focused on two-dimensional radar images, of multi-altitude which can provide more informative visual forecasts about weather systems realistic space, less explored. Thus, this paper proposes a 3D-convolutional long short-term memory (ConvLSTM)-based model to perform three-dimensional gridded severe First, neural network (CNN) is used extract the 3D spatial...
Radar quantitative precipitation estimation (RQPE) is the most common measurement for area rainfall with high spatial and temporal resolution. The radar reflectivity ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Z$ </tex-math></inline-formula> ) measured by Doppler weather strongly related to rate notation="LaTeX">$R$ ). However, conventional RQPE methods have limited capability of modeling complex...
Weather radar echo extrapolation, which predicts future echoes based on historical observations, is one of the complicated spatial–temporal sequence prediction tasks and plays a prominent role in severe convection precipitation nowcasting. However, existing extrapolation methods mainly focus defective echo-motion paradigm finite observational dynamics, neglecting that actual has more evolution process contains both nonlinear motions lifecycle from initiation to decay, resulting poor...
Radar echo extrapolation is a common approach to weather nowcasting, which has become significant support detect potential disastrous few hours ahead. The dynamics pattern inside an intensity sequence beneficial for prediction. However, existing methods have limited ability consider entire time series context in from given historical timestamp future timestamp, leading low long-term accuracy. To solve this issue, we introduce spatiotemporal self-attention and propose deep learning model...
The wind and temperature fields at 20 to 55 km above the Antigua launch site (17°N, 61°W) were analyzed by using sounding rocket data published research organization on Stratosphere-Troposphere Processes their Role in Climate (SPARC). results showed distinct variations different heights from 1960s 1990s. overall zonal speed a significant increasing trend with year, change meridional falling 1976 1990, whereas field cooling 1964 1990. times trends mutated varied levels. By taking altitudes...