Quantitative comparison of radar QPE to rain gauges for the 26 September 2007 Venice Mestre flood

Rossa, Andrea; Cenzon, G.; Monai, M.

doi:10.5194/nhess-10-371-2010

Cited by 13 publications

(6 citation statements)

References 13 publications

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“…Such events are significant for hazards such as flash flooding but may be missed altogether from point gauge records and cause difficulties for gauge-radar comparisons (e.g. Vasiloff et al, 2009;Rossa et al, 2010a).…”

Section: Perspectivesmentioning

confidence: 99%

Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality

McMillan

Krueger

Freer

2012

Hydrological Processes

405

366

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This review and commentary sets out the need for authoritative and concise information on the expected error distributions and magnitudes in observational data. We discuss the necessary components of a benchmark of dominant data uncertainties and the recent developments in hydrology which increase the need for such guidance. We initiate the creation of a catalogue of accessible information on characteristics of data uncertainty for the key hydrological variables of rainfall, river discharge and water quality (suspended solids, phosphorus and nitrogen). This includes demonstration of how uncertainties can be quantified, summarizing current knowledge and the standard quantitative results available. In particular, synthesis of results from multiple studies allows conclusions to be drawn on factors which control the magnitude of data uncertainty and hence improves provision of prior guidance on those uncertainties. Rainfall uncertainties were found to be driven by spatial scale, whereas river discharge uncertainty was dominated by flow condition and gauging method. Water quality variables presented a more complex picture with many component errors. For all variables, it was easy to find examples where relative error magnitudes exceeded 40%. We consider how data uncertainties impact on the interpretation of catchment dynamics, model regionalization and model evaluation. In closing the review, we make recommendations for future research priorities in quantifying data uncertainty and highlight the need for an improved ‘culture of engagement’ with observational uncertainties. Copyright © 2012 John Wiley & Sons, Ltd.

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Section: Perspectivesmentioning

confidence: 99%

Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality

McMillan

Krueger

Freer

2012

Hydrological Processes

405

366

View full text Add to dashboard Cite

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“…This event, thoroughly described and investigated in Davolio et al () and Rossa et al (), was the most intense rainfall episode that occurred during the operational period of the MAP‐DPHASE project (Rotach et al , ). It was responsible for a severe, although localised, flood over a flat area near Venice (location in Figure ) on 26 September 2007.…”

Section: Heavy Precipitation Events Over Neimentioning

confidence: 99%

Mechanisms producing different precipitation patterns over north‐eastern Italy: insights from HyMeX‐SOP1 and previous events

Davolio

Volonté

Manzato³

et al. 2016

Quart J Royal Meteoro Soc

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During the first HyMeX Special Observation Period (SOP1) field campaign, the target site of north‐eastern Italy (NEI) experienced a large amount of precipitation, locally exceeding the climatological values and distributed among several heavy‐rainfall episodes. In particular, two events that occurred during the last period of the campaign drew our attention. These events had common large‐scale patterns and a similar mesoscale setting, characterised by southerly low‐level flow interacting with the Alpine orography, but the precipitation distribution was very different. During Intensive Observing Period IOP18 (31 October–1 November 2012), convective systems were responsible for intense rainfall mainly located over a flat area of the eastern Po Valley, well upstream of the orography. Conversely, during IOP19 (4/5 November 2012), heavy precipitation affected only the Alpine area. In addition to IOP18 and IOP19, the present study analyses other heavy‐precipitation episodes that display similar characteristics and which occurred over NEI during the autumn of recent years. A high‐resolution (2 km grid spacing) non‐hydrostatic NWP model and available observations are used for this purpose. The two different observed precipitation patterns are explained in terms of interaction between the impinging flow and the Alps. Depending on the thermodynamic profile, convection can be triggered when the impinging flow is forced to rise over a pre‐existing cold‐air layer at the base of the orography. In this situation a persistent blocked‐flow condition and upstream convergence are responsible for heavy rain localized over the plain. Conversely, if convection does not develop, flow‐over conditions are established and heavy rain affects the Alps. Numerical parameters proposed in the literature are used to support the analysis. Finally, the role of evaporative cooling beneath the convective systems is evaluated. It turns out that the stationarity of the systems upstream of the Alps is mainly attributable to persistent blocked‐flow conditions, while convective outflow slightly modifies the location of precipitation.

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“…Hydrometeorological hazards are relatively frequent and constitute a major threat to life and property within the palette of natural hazards [1]. The Global Positioning System-Interferometric Reflectometry (GPS-IR) technique is used to monitor sea-level measurements by using a geodetic quality GPS receiver for identifying the nearby environment, including the benefits of climate dependent and independent sea level information [2].…”

Section: Introductionmentioning

confidence: 99%

Global Positioning System Interferometric Reflectometry for Accurate Tide Gauge Measurement: Insights from South Beach, Oregon, United States

Ansari

Bae

İnyurt

2020

Preprint

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Global Positioning System (GPS) stations located along coastal areas have the ability to measure tide gauge (TG) records by reflected signal reception from the sea water surface. In this study we used the GPS signal-to-noise ratio (SNR) data from the SEPT station (44.63 ⁰N, 124.05 ⁰W) located at South Beach, Oregon, USA, to estimate the TG records using only a few measurements. First, we derived the TG record from a GPS station (GPS-TG) and used traditional TG data from the National Water Level Observation Network (NWLON) sentinel station (Station ID: 9435380) located in Oregon for validation purposes because it was closest to the SEPT station. Our results show that the GPS-TG and NWLON-TG correlate well with the correlation coefficient (CC) of 0.942 and the root mean square (RMS) of their residuals was about 12.90 cm. The corresponding TG prediction by autoregressive moving average (ARMA-TG) and singular spectrum analysis (SSA-TG) models are evaluated for their effectiveness over the station. The comparative analysis demonstrates that the GPS-TG has improved correlation with ARMA-TG (CC of ~0.981 CC, RMS of ~4.80 cm), and SSA-TG (CC of ~0.998 CC, RMS of ~ 0.88 cm) compared to the NWLON-TG (CC of ~0.942 CC, RMS of ~12.90 cm) values. We believe the outcomes from this study contribute to a better understanding of the numerical modeling of TG records as well as other measurements based on reflectometry techniques.

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Quantitative comparison of radar QPE to rain gauges for the 26 September 2007 Venice Mestre flood

Cited by 13 publications

References 13 publications

Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality

Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality

Mechanisms producing different precipitation patterns over north‐eastern Italy: insights from HyMeX‐SOP1 and previous events

Global Positioning System Interferometric Reflectometry for Accurate Tide Gauge Measurement: Insights from South Beach, Oregon, United States

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