caa a22 4500 469040653 CHVBK 20180323132810.0 cr unu---uuuuu 170328e19920301xx s 000 0 eng 10.1007/BF01581673 doi (NATIONALLICENCE)springer-10.1007/BF01581673 A Monte Carlo study of rainfall forecasting with a stochastic model [Elektronische Daten] [M. French, R. Bras, W. Krajewski] A procedure for short-term rainfall forecasting in real-time is developed and a study of the role of sampling on forecast ability is conducted. Ground level rainfall fields are forecasted using a stochastic space-time rainfall model in state-space form. Updating of the rainfall field in real-time is accomplished using a distributed parameter Kalman filter to optimally combine measurement information and forecast model estimates. The influence of sampling density on forecast accuracy is evaluated using a series of a simulated rainfall events generated with the same stochastic rainfall model. Sampling was conducted at five different network spatial densities. The results quantify the influence of sampling network density on real-time rainfall field forecasting. Statistical analyses of the rainfall field residuals illustrate improvement in one hour lead time forecasts at higher measurement densities. Springer-Verlag, 1992 Rainfall nationallicence Precipitation nationallicence Forecasting nationallicence Real-time nationallicence Modeling nationallicence Simulation nationallicence Stochastic nationallicence Prediction nationallicence Sampling nationallicence Measurement nationallicence Updating nationallicence Filtering nationallicence Estimation nationallicence Short-term nationallicence French M. Iowa Institute of Hydraulic Research, University of Iowa, 52242, Iowa City, IA aut Bras R. Massachusetts Institute of Technology, 02139, Cambridge, MA aut Krajewski W. Iowa Institute of Hydraulic Research, University of Iowa, 52242, Iowa City, IA aut Stochastic Hydrology and Hydraulics Springer-Verlag 6/1(1992-03-01), 27-45 0931-1955 6:1<27 1992 6 477 https://doi.org/10.1007/BF01581673 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF01581673 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- French M. Iowa Institute of Hydraulic Research, University of Iowa, 52242, Iowa City, IA aut NATIONALLICENCE 700 1- Bras R. Massachusetts Institute of Technology, 02139, Cambridge, MA aut NATIONALLICENCE 700 1- Krajewski W. Iowa Institute of Hydraulic Research, University of Iowa, 52242, Iowa City, IA aut NATIONALLICENCE 773 0- Stochastic Hydrology and Hydraulics Springer-Verlag 6/1(1992-03-01), 27-45 0931-1955 6:1<27 1992 6 477 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer