Definition and impact of a quality index for radar-based reference measurements in the H-SAF precipitation product validation

Rinollo, A.; Vulpiani, G.; Puca, Silvia; Pagliara, Paola; Kaňák, Ján; Lábó, Eszter; Okon, Ľuboslav; Roulin, Emmanuel; Baguis, Pierre; Cattani, Elsa; Laviola, Sante; Levizzani, Vincenzo

doi:10.5194/nhess-13-2695-2013

Cited by 19 publications

(31 citation statements)

References 17 publications

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“…This makes it difficult to set up a reliable, spatially and temporally continuous reference field, suitable to be matched to the satellite estimates: ground weather radar (Chandrasekar et al, 2008;Capacci and Porcù, 2009;Lábó, 2012;Rinollo et al, 2013) and rain gauge networks (Dinku et al, 2007;Sohn et al, 2010) are mainly used to provide rainfall reference fields for validation studies. A number of studies, however, point out that care should be taken in comparing satellite and ground-based precipitation estimates for validation purposes.…”

Section: Introductionmentioning

confidence: 99%

“…A representativeness error is introduced when comparing areal instantaneous data (from satellites) with punctual cumulated values (from rain gauges) (Zawadzki, 1975;Kitchen and Blackall, 1992;Habib et al, 2009), pointing out that this error is not negligible (Porcù et al, 2014). Intrinsic discrepancies between satellite and ground radar estimates are also to be expected due to the different points of view of the two sensors (Habib and Krajeski, 2002;Chandrasekar et al, 2008;Rinollo at al., 2013). To cope with these difficulties, satellite missions devoted to precipitation studies have developed their own validation structures, such as the Tropical Rainfall Measuring Mission (TRMM) (Wolff et al, 2005) and the Global Precipitation Measurement (GPM) Mission (Schwaller et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

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The validation service of the hydrological SAF geostationary and polar satellite precipitation products

Puca

Porcú

Rinollo

et al. 2014

Nat. Hazards Earth Syst. Sci.

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Abstract. The development phase (DP) of the EUMETSAT Satellite Application Facility for Support to Operational Hydrology and Water Management (H-SAF) led to the design and implementation of several precipitation products, after 5 yr (2005)(2006)(2007)(2008)(2009)(2010) of activity. Presently, five precipitation estimation algorithms based on data from passive microwave and infrared sensors, on board geostationary and sun-synchronous platforms, function in operational mode at the H-SAF hosting institute to provide near real-time precipitation products at different spatial and temporal resolutions.In order to evaluate the precipitation product accuracy, a validation activity has been established since the beginning of the project. A Precipitation Product Validation Group (PPVG) works in parallel with the development of the estimation algorithms with two aims: to provide the algorithm developers with indications to refine algorithms and products, and to evaluate the error structure to be associated with the operational products.In this paper, the framework of the PPVG is presented: (a) the characteristics of the ground reference data available to H-SAF (i.e. radar and rain gauge networks), (b) the agreed upon validation strategy settled among the eight European countries participating in the PPVG, and (c) the steps of the validation procedures. The quality of the reference data is discussed, and the efforts for its improvement are outlined, with special emphasis on the definition of a ground radar Published by Copernicus Publications on behalf of the European Geosciences Union. S. Puca et al.:The validation service of the hydrological SAF geostationary products quality map and on the implementation of a suitable rain gauge interpolation algorithm. The work done during the H-SAF development phase has led the PPVG to converge into a common validation procedure among the members, taking advantage of the experience acquired by each one of them in the validation of H-SAF products. The methodology is presented here, indicating the main steps of the validation procedure (ground data quality control, spatial interpolation, upscaling of radar data vs. satellite grid, statistical score evaluation, case study analysis).Finally, an overview of the results is presented, focusing on the monthly statistical indicators, referred to the satellite product performances over different seasons and areas.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The validation service of the hydrological SAF geostationary and polar satellite precipitation products

Puca

Porcú

Rinollo

et al. 2014

Nat. Hazards Earth Syst. Sci.

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“…The SRI product used here represents the best estimate from the radar network available for the period under analysis, and it has already been used to validate satellite rainfall estimates (Cimini et al, 2013), including EUMETSAT H-SAF products (Puca et al, 2014). Procedures to improve the quality of the SRI product, including attenuation compensation, polarimetric rainfall inversion techniques, and adaptive algorithms to retrieve the mean vertical profiles of reflectivity have recently been developed at DPC (Vulpiani et al, 2012;Rinollo et al, 2013). All the products are available on a grid of 1400 × 1400 km 2 , with a spatial resolution of circa 1 km and a temporal resolution of 15 min.…”

Section: E Ricciardelli Et Al: a Statistical Approach For Rain Intementioning

confidence: 99%

A statistical approach for rain intensity differentiation using Meteosat Second Generation–Spinning Enhanced Visible and InfraRed Imager observations

Ricciardelli

Cimini

Paola

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. This study exploits the Meteosat Second Generation (MSG)-Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations to evaluate the rain class at high spatial and temporal resolutions and, to this aim, proposes the Rain Class Evaluation from Infrared and Visible observation (RainCEIV) technique. RainCEIV is composed of two modules: a cloud classification algorithm which individuates and characterizes the cloudy pixels, and a supervised classifier that delineates the rainy areas according to the three rainfall intensity classes, the non-rainy (rain rate value < 0.5 mm h −1 ) class, the light-to-moderate rainy class (0.5 mm h −1 ≤ rain rate value < 4 mm h −1 ), and the heavyto-very-heavy-rainy class (rain rate value ≥ 4 mm h −1 ). The second module considers as input the spectral and textural features of the infrared and visible SEVIRI observations for the cloudy pixels detected by the first module. It also takes the temporal differences of the brightness temperatures linked to the SEVIRI water vapour channels as indicative of the atmospheric instability strongly related to the occurrence of rainfall events.The rainfall rates used in the training phase are obtained through the Precipitation Estimation at Microwave frequencies, PEMW (an algorithm for rain rate retrievals based on Atmospheric Microwave Sounder Unit (AMSU)-B observations). RainCEIV's principal aim is that of supplying preliminary qualitative information on the rainy areas within the Mediterranean Basin where there is no radar network coverage. The results of RainCEIV have been validated against radar-derived rainfall measurements from the Italian Operational Weather Radar Network for some case studies limited to the Mediterranean area. The dichotomous assessment related to daytime (nighttime) validation shows that RainCEIV is able to detect rainy/non-rainy areas with an accuracy of about 97 % (96 %), and when all the rainy classes are considered, it shows a Heidke skill score of 67 % (62 %), a bias score of 1.36 (1.58), and a probability of detection of rainy areas of 81 % (81 %).

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“…That is the reason why the training database for the PNPR algorithm is based on the same physical foundation used for the CDRD algorithm. Moreover, the two algorithms use the same procedures to determine the phase of the retrieved precipitation (following the studies of Grody et al, 2000;Rosenkranz, 2003;and Surussavadee and Staelin, 2009), as well as the same precipitation screening methodology following an algorithm developed by Chen and Staelin (2003), and finally the same specially tailored surface identification procedures (see Mugnai et al, 2013).…”

Section: Pr-obs-2mentioning

confidence: 99%

“…For this reason, quality index maps are produced and associated to all ground data. The quality index, which is a function of position and time, is subsumed into a single number ranging between 0 and 1, and uses all essential information available to quantify the reliability of the ground data to which the index must be associated (see Vulpiani et al, 2008, andRinollo et al, 2013).…”

Section: A Mugnai Et Al: Precipitation Products From the Hydrology mentioning

confidence: 99%

Precipitation products from the hydrology SAF

Mugnai

Casella

Cattani

et al. 2013

Nat. Hazards Earth Syst. Sci.

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The EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) was established by the EUMETSAT Council on 3 July 2005, starting activity on 1 September 2005. The Italian Meteorological Service serves as Leading Entity on behalf of twelve European member countries. H-SAF products include precipitation, soil moisture and snow parameters. Some products are based only on satellite observations, while other products are based on the assimilation of satellite measurements/products into numerical models. In addition to product development and generation, H-SAF includes a product validation program and a hydrological validation program that are coordinated, respectively, by the Italian Department of Civil Protection and by the Polish Institute of Meteorology and Water Management. The National Center of Aeronautical Meteorology and Climatology (CNMCA) of the Italian Air Force is responsible for operational product generation and dissemination.

In this paper we describe the H-SAF precipitation algorithms and products, which have been developed by the Italian Institute of Atmospheric Sciences and Climate (in collaboration with the international community) and by CNMCA during the Development Phase (DP, 2005–2010) and the first Continuous Development and Operations Phase (CDOP-1, 2010–2012). The precipitation products are based on passive microwave measurements obtained from radiometers onboard different sun-synchronous low-Earth-orbiting satellites (especially, the SSM/I and SSMIS radiometers onboard DMSP satellites and the AMSU-A + AMSU-B/MHS radiometer suites onboard EPS-MetOp and NOAA-POES satellites), as well as on combined infrared/passive microwave measurements in which the passive microwave precipitation estimates are used in conjunction with SEVIRI images from the geostationary MSG satellite. Moreover, the H-SAF product generation and dissemination chain and independent product validation activities are described. Also, the H-SAF program and its associated activities that currently are being carried out or are planned to be performed within the second CDOP phase (CDOP-2, 2012–2017) are presented in some detail. Insofar as CDOP-2 is concerned, it is emphasized that all algorithms and processing schemes will be improved and enhanced so as to extend them to satellites that will be operational within this decade – particularly the geostationary Meteosat Third Generation satellites and the low-Earth-orbiting Core Observatory of the international Global Precipitation Measurement mission. Finally, the role of H-SAF within the international science and operations community is explained

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Definition and impact of a quality index for radar-based reference measurements in the H-SAF precipitation product validation

Cited by 19 publications

References 17 publications

The validation service of the hydrological SAF geostationary and polar satellite precipitation products

The validation service of the hydrological SAF geostationary and polar satellite precipitation products

A statistical approach for rain intensity differentiation using Meteosat Second Generation–Spinning Enhanced Visible and InfraRed Imager observations

Precipitation products from the hydrology SAF

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