Sökning: "nederbördsprognoser"

Hittade 3 uppsatser innehållade ordet nederbördsprognoser.

  1. 1. Precipitation Nowcasting using Deep Neural Networks

    Master-uppsats, KTH/Fysik

    Författare :Valter Fallenius; [2022]
    Nyckelord :Deep Neura Networks; Artificial Intelligence; Meteorology; Precipitationa Nowcasting; Djupa neurala nätverk; artificiell intelligens; nederbördsprognoser; meteorologi;

    Sammanfattning : Deep neural networks (DNNs) based on satellite and radar data have shown promising results for precipitation nowcasting, beating physical models and optical flow for time horizons up to 8 hours. “MetNet”, developed by Google AI, is a 225 million parameter DNN combining three different types of architectures that was trained on satellite and radar data over the United States. LÄS MER

  3. 2. Data assimilation of GPS-RO atmospheric profile data for improved rainfall forecasts over West Africa

    Master-uppsats, Uppsala universitet/Luft-, vatten- och landskapslära

    Författare :Jon Jörpeland; [2016]
    Nyckelord :GPS-RO; West Africa; rainfall; satellite; GPS-RO; Västafrika; nederbörd; satellit;

    Sammanfattning : Forecasting rainfall is of great importance for the farmers in West Africa. However, due too lack of reliable weather observations, rainfall forecats in West Africa are difficult and primarly based on satellite observations. LÄS MER

  4. 3. Hybrid Rainfall Estimates from Satellite, Lightning and Ground Station Data in West Africa

    Master-uppsats, Uppsala universitet/Institutionen för geovetenskaper

    Författare :Henrik Enbäck; Charlotta Eriksson; [2015]
    Nyckelord :rainfall estimates; West Africa; lightning; satellite; nederbördsestimat; Västafrika; blixtar; satellit;

    Sammanfattning : Most of the working population in Ghana are farmers. It is of importance for them to know where and when precipitation will occur to prevent crop losses due to droughts and floodings. In order to have a sustainable agriculture, improved rainfall forecasts are needed. One way to do that is to enhance the initial conditions for the rainfall models. LÄS MER