The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time. Very few previous studies have examined this crucial and challenging weather forecasting problem from the machine learning perspective. In this paper, we formulate precipitation nowcasting as a spatiotemporal sequence forecasting problem in which both the in...

The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI) and the standardized precipitation evaporation index (SPEI) and were ...

In this paper, we propose a new hidden Markov model (HMM) for the space-time evolution of daily rainfall. The hidden Markov chain represents the different meteorological regimes (“weather types”) and it is assumed that this variable explains the dynamics of the precipitation. The spatial structure within hidden weather types is modelled by censored power-transformed Gaussian distributions. It p...

Downscaling global weather prediction model outputs to individual locations or local scales is a common practice for operational weather forecast in order to correct the model outputs at subgrid scales. This paper presents an empirical-statistical downscaling method for precipitation prediction which uses a feed-forward multilayer perceptron MLP neural network. The MLP architecture was optimize...

Although it has been documented that daily precipitation extremes are increasing worldwide, faster increases may be expected for subdaily extremes. Here after a careful quality control procedure, we compared trends in hourly and daily precipitation extremes using a large network of stations across the United States (U.S.) within the 1950–2011 period. A greater number of significant increasing t...

A new hidden Markov model (HMM) for the space-time evolution of daily rainfall is developed which models precipitation within hidden regional weather types by censored power-transformed Gaussian distributions. The latter provide flexible and interpretable multivariate models for the mixed discrete-continuous variables that describe both precipitation, when it occurs, and no precipitation. Param...

in different regions, precipitation takes place with different persistencies and every persistency supplies a share of rainfall days and precipitation. therefore, the importance of rainfall persistence could be evaluated in all places. iran is located in mid-latitude of an arid region, in which the mean rainfall is 250 mm and it has dramatic tempo-spatial changes. rainfalls with short persisten...