Improving QPF by blending techniques at the Meteorological Service of Catalonia

Atencia, A. and Rigo, T. and Sairouni, A. and Moré, J. and Bech, J. and Vilaclara, E. and Cunillera, J. and Llasat, M.C. and Garrote de Marcos, Luis (2010). Improving QPF by blending techniques at the Meteorological Service of Catalonia. "Natural Hazards and Earth System Sciences", v. 10 (n. 7); pp. 1443-1455. ISSN 1561-8633. https://doi.org/10.5194/nhess-10-1443-2010.

Description

Title: Improving QPF by blending techniques at the Meteorological Service of Catalonia
Author/s:
  • Atencia, A.
  • Rigo, T.
  • Sairouni, A.
  • Moré, J.
  • Bech, J.
  • Vilaclara, E.
  • Cunillera, J.
  • Llasat, M.C.
  • Garrote de Marcos, Luis
Item Type: Article
Título de Revista/Publicación: Natural Hazards and Earth System Sciences
Date: July 2010
ISSN: 1561-8633
Volume: 10
Subjects:
Faculty: E.T.S.I. Caminos, Canales y Puertos (UPM)
Department: Ingeniería Civil: Hidráulica y Energética [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (778kB) | Preview

Abstract

The current operational very short-term and short-term quantitative precipitation forecast (QPF) at the Meteorological Service of Catalonia (SMC) is made by three different methodologies: Advection of the radar reflectivity field (ADV), Identification, tracking and forecasting of convective structures (CST) and numerical weather prediction (NWP) models using observational data assimilation (radar, satellite, etc.). These precipitation forecasts have different characteristics, lead time and spatial resolutions. The objective of this study is to combine these methods in order to obtain a single and optimized QPF at each lead time. This combination (blending) of the radar forecast (ADV and CST) and precipitation forecast from NWP model is carried out by means of different methodologies according to the prediction horizon. Firstly, in order to take advantage of the rainfall location and intensity from radar observations, a phase correction technique is applied to the NWP output to derive an additional corrected forecast (MCO). To select the best precipitation estimation in the first and second hour (t+1 h and t+2 h), the information from radar advection (ADV) and the corrected outputs from the model (MCO) are mixed by using different weights, which vary dynamically, according to indexes that quantify the quality of these predictions. This procedure has the ability to integrate the skill of rainfall location and patterns that are given by the advection of radar reflectivity field with the capacity of generating new precipitation areas from the NWP models. From the third hour (t+3 h), as radar-based forecasting has generally low skills, only the quantitative precipitation forecast from model is used. This blending of different sources of prediction is verified for different types of episodes (convective, moderately convective and stratiform) to obtain a robust methodology for implementing it in an operational and dynamic way

Funding Projects

TypeCodeAcronymLeaderTitle
FP7226555IMPRINTSUnspecifiedIMproving Preparedness and RIsk maNagemenT for flash floods and debriS flow events

More information

Item ID: 7164
DC Identifier: http://oa.upm.es/7164/
OAI Identifier: oai:oa.upm.es:7164
DOI: 10.5194/nhess-10-1443-2010
Official URL: http://www.nat-hazards-earth-syst-sci.net/10/1443/2010/nhess-10-1443-2010.html
Deposited by: Memoria Investigacion
Deposited on: 20 May 2011 10:03
Last Modified: 26 Jan 2015 11:48
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM