Rain pattern analysis and forecast model based on GPS estimated atmospheric water vapor content

Seco, A.; Ramírez, Francisco; Serna, Eduardo Morera; Prieto, Eduardo; García, Rafael; Moreno, Aitor; Cantera, Juan Carlos; Miqueleiz, L.; Priego, E.

doi:10.1016/j.atmosenv.2011.12.019

Cited by 38 publications

(21 citation statements)

References 9 publications

(1 reference statement)

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“…Figure 3 compares the GPS PWV retrievals with direct PWV measurements made by radiosondes from Lisbon, mostly at 12:00 UTC. Results are overall excellent, with a 0.99 correlation between the two data sets, and a very small negative bias in the GPS signal (about 0.1 mm), corroborating other published comparisons (namely, Seco et al (2012) and Galisteo et al (2014), both concerning data in Spain).…”

Section: The Annual Cycle Of Pwvsupporting

confidence: 88%

“…A study evaluating 1 month of data in Japan (Shoji, 2013) verified, as in this work, that the precipitation frequency increased rapidly when the PWV reached a certain threshold as a function of the surface temperature, which was not considered in this study but is worth exploring in future work. A much larger amount of continuous data of 9 years in north-eastern Spain was evaluated, being developed a neural network system to forecast rain from GPS PWV data and observed surface pressure in a single point, concluding for the existence of some predictability in a range beyond 2 days (Seco et al, 2012). Their method is not directly comparable with the one proposed here, but it clearly supports the idea of using GPS data to improve rain forecasts.…”

Section: Discussionmentioning

confidence: 81%

“…Remote sensing of water vapour by different space-borne platforms, namely geostationary and polar orbiting sensors, also suffers from severe time and/or spatial sampling problems. In recent years, GNSS (Global Navigation Satellite System) data, mostly that associated with the more popular GPS (Global Positioning System) system, obtained from ground-based stations, started to offer an alternative image of the distribution of the vertically integrated water vapour (precipitable water vapour, PWV), and that information was found to contribute positively to atmospheric analysis for weather forecast (Bevis et al, 1994;Baker et al, 2001;Vedel et al, 2004;Bock et al, 2007;Seco et al, 2012). The rapid increase in the density of such networks in some regions has been motivating the exploration of GNSS data for other meteorological applications.…”

Section: Introductionmentioning

confidence: 99%

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On the inclusion of GPS precipitable water vapour in the nowcasting of rainfall

Benevides

Catalão

Miranda

2015

Nat. Hazards Earth Syst. Sci.

138

122

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Abstract. The temporal behaviour of precipitable water vapour (PWV) retrieved from GPS delay data is analysed in a number of case studies of intense precipitation in the Lisbon area, in the period 2010-2012 and in a continuous annual cycle of 2012 observations. Such behaviour is found to correlate positively with the probability of precipitation, especially in cases of severe rainfall. The evolution of the GPS PWV in a few stations is analysed by a least-squares fitting of a broken line tendency, made by a temporal sequence of ascents and descents over the data. It is found that most severe rainfall events occur in descending trends after a long ascending period and that the most intense events occur after steep ascents in PWV. A simple algorithm, forecasting rain in the 6 h after a steep ascent of the GPS PWV in a single station, is found to produce reasonable forecasts of the occurrence of precipitation in the nearby region, without significant misses in what concerns larger rain events, but with a substantial amount of false alarms. It is suggested that this method could be improved by the analysis of 2-D or 3-D time-varying GPS PWV fields or by its joint use with other meteorological data relevant to nowcast precipitation.

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Section: The Annual Cycle Of Pwvsupporting

confidence: 88%

Section: Discussionmentioning

confidence: 81%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On the inclusion of GPS precipitable water vapour in the nowcasting of rainfall

Benevides

Catalão

Miranda

2015

Nat. Hazards Earth Syst. Sci.

138

122

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“…The conclusion is that the realtime GPS IWV maps are of good quality and can be helpful for nowcasting of severe thunderstorms. A nine-year study in northern Spain, conducted by Seco et al (2012), reports that rain events are usually from atmospheric low pressure systems and water vapour entries are caused by Atlantic disturbances. They identify three precipitation patterns associated with different behaviour of water vapour during the year.…”

Section: Introductionmentioning

confidence: 99%

The Sofia University Atmospheric Data Archive (SUADA)

2014

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Abstract. Atmospheric sounding using the Global Navigation Satellite Systems (GNSS) is a well-established research field in Europe. At present, GNSS data from 1800 stations are available for model validation and assimilation in stateof-the-art models used for operational numerical weather prediction centres in Europe. Advances in GNSS data processing make it possible also to use the GNSS data for climatic trend analysis, an emerging new application. In Bulgaria and southeastern Europe, the use of GNSS for atmospheric sounding is currently under development.As a first step, the Sofia University Atmospheric Data Archive (SUADA) is developed. SUADA is a user-friendly database, and includes GNSS tropospheric products like zenith total delay (ZTD) and derivatives like vertically integrated water vapour (IWV), as well as observations from radiosonde (RS) and surface atmospheric data. Archived in SUADA are (1) GNSS tropospheric products (over 12 000 000 individual observations) and derivatives (over 55 000) from five GNSS processing strategies and 37 stations for the period 1997-2013, with temporal resolutions from 5 min to 6 h, and (2) radiosonde IWV data (over 6000 observations) for station Sofia (1999Sofia ( -2012.Presented are two applications of the SUADA data for the study of long-and short-term variations of IWV over Bulgaria during the 2007 heatwave and intense precipitation events in 2012.

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“…Este análisis ha sido publicado por el autor en el número 49 de la revista científica "Atmospheric Environment" ) y presentado en el 5 th HYMEX workshop (HYdrological cicle in Mediterranean EXperiment) celebrado en Menorca (Seco et al, 2011).…”

Section: Conclusionesunclassified

Análisis y predicción de lluvias intensas en la Comunidad Valenciana basados en la estimación del contenido de vapor de agua atmosférico obtenido con técnicas GNSS

Santos¹,

Enríque²

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AgradecimientosA Maru, de la que he aprendido que cada día es el mejor del año, a mis hijos, mi mejor fortuna, y a mis padres, mis primeros maestros.A mis tutores, José Luis Berné y Andrés Seco, por su amistad, sus consejos, su confianza y trasmitirme la perseverancia necesaria para realizar esta tesis.A los compañeros del grupo de investigación de la Universidad Pública de Navarra, especialmente a Eduardo Serna, por su paciencia y ayuda con los procesados, sin olvidarme de Xavier Archanco y Eduardo Prieto, a todos ellos por su atención en mis visitas a Pamplona.A Pascual Garrigues, Emilio Benítez y Fernando Cruz, que me han facilitado la colocación de los equipos GNSS. A Pascual agradecerle también todo el apoyo logístico, y a Emilio la ayuda en la descarga de datos y cálculos.A Rafael Doménech, por facilitarme el acceso a los datos de las estaciones GNSS de la Autoridad Portuaria de Valencia.A José Ángel Núñez (AEMET) y Álvaro Muñoz (UPV), por gestionarme de forma eficiente el suministro de los muchos datos meteorológicos que les he solicitado.A Mónica López y Albert Barniols (TVE) por su asesoramiento meteorológico.A Raquel Capilla y Mar Rubio por su apoyo material y humano desde el ICV.A Txomin Hermosilla, por atenderme y facilitarme todo aquello que le he pedido para materializar esta tesis.A Alfonso Fernández por estar siempre predispuesto a cualquier tipo de ayuda.A Josep Pardo y Luis Ángel Ruiz, por sus consejos y traducciones. ResumenLos Sistemas Globales de Navegación por Satélite (GNSS) han transformado las técnicas de posicionamiento, la navegación y el tiempo, llegando a ser indispensables en muchas de las actividades de la vida diaria. Aparte de las aplicaciones civiles y comerciales ya conocidas, la tecnología GNSS puede utilizarse como sistema de observación atmosférica, puesto que se ha demostrado su capacidad para estimar el contenido de vapor de agua en la atmosfera a partir del retraso troposférico que sufre la propagación de la señal en la dirección satélite-receptor.La distribución y evolución del vapor de agua es determinante en el funcionamiento climático y meteorológico de la atmosfera terrestre, siendo una de las variables climáticas esenciales de observación sistemática que actualmente ha definido el Sistema de Observación del Clima Mundial (GCOS, Global Climate Observing System). El comportamiento del vapor de agua atmosférico es esencial para estudios de cambio climático, puesto que es el principal gas de efecto invernadero que influye en el calentamiento global. Además, es un componente primordial en la estabilidad vertical de la atmósfera, interviniendo activamente en la evolución de los sistemas tormentosos.Hasta hace poco tiempo, esta variable atmosférica no estaba bien definida al no disponerse de medidas con la suficiente resolución para representar su alta inestabilidad espacial y temporal. El incremento en los últimos años de estaciones de referencia permanentes GNSS a escala mundial, supone un importante avance para la monitorización del vapor de agua o cantidad de agua prec...

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Rain pattern analysis and forecast model based on GPS estimated atmospheric water vapor content

Cited by 38 publications

References 9 publications

On the inclusion of GPS precipitable water vapour in the nowcasting of rainfall

On the inclusion of GPS precipitable water vapour in the nowcasting of rainfall

The Sofia University Atmospheric Data Archive (SUADA)

Análisis y predicción de lluvias intensas en la Comunidad Valenciana basados en la estimación del contenido de vapor de agua atmosférico obtenido con técnicas GNSS

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