Radar rainfall: Separating signal and noise fields to generate meaningful ensembles
| Autor: | Daniel Sempere-Torres, Xavier Llort, Geoff Pegram |
|---|---|
| Přispěvatelé: | Universitat Politècnica de Catalunya. Departament d'Enginyeria del Terreny, Cartogràfica i Geofísica, Universitat Politècnica de Catalunya. Departament d'Enginyeria Hidràulica, Marítima i Ambiental, Universitat Politècnica de Catalunya. CRAHI - Centre de Recerca Aplicada en Hidrometeorologia |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
Atmospheric Science
Variance inflation 010504 meteorology & atmospheric sciences Computer science 0207 environmental engineering 02 engineering and technology 01 natural sciences Multiplicative noise law.invention law Radar ensamble Value noise Radar 020701 environmental engineering Physics::Atmospheric and Oceanic Physics 0105 earth and related environmental sciences Remote sensing Radar QPE Noise measurement Noise (signal processing) Matched filter Probabilistic QPE Noise floor Radar en la meteorologia Gradient noise Radar rainfall images Algorithm |
| Zdroj: | Atmospheric Research Recercat. Dipósit de la Recerca de Catalunya instname UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| ISSN: | 0169-8095 |
| DOI: | 10.1016/j.atmosres.2010.11.018 |
| Popis: | For the purpose of generating meaningful stochastic ensembles of radar estimates of rainfall, a relatively simple and objective method of separating a radar rainfall image into signal and noise is described. An alternative noise field, with the same spectrum as the original noise, can then be simulated and combined with the signal field of each successive image, to generate an ensemble member for performing sensitivity studies. The method is based on identifying the appropriate wavelength in the power spectrum which defines the variance threshold used to separate noise from signal. The algorithm is explained and figures illustrate the efficacy of the procedure. |
| Databáze: | OpenAIRE |
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