Toward Real-Time Daily PQPF by an Analog Sorting Approach: Application to Flash-Flood Catchments

Marty, Renaud; Zin, Isabella; Obled, Charles; Bontron, Guillaume; Djerboua, Abdelatif

doi:10.1175/jamc-d-11-011.1

Cited by 51 publications

(54 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both PP and MOS methods are also applied for operational precipitation forecast (e.g. Marty et al, 2008Marty et al, , 2012Marty et al, , 2013Voisin et al, 2010;Nam et al, 2011;Liu and Coulibaly, 2011;Muluye, 2011).…”

Section: Statistical Downscaling Methodsmentioning

confidence: 99%

Optimising predictor domains for spatially coherent precipitation downscaling

Radanovics¹,

Vidal²,

Sauquet³

et al. 2013

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Statistical downscaling is widely used to overcome the scale gap between predictors from numerical weather prediction models or global circulation models and predictands like local precipitation, required for example for medium-term operational forecasts or climate change impact studies. The predictors are considered over a given spatial domain which is rarely optimised with respect to the target predictand location. In this study, an extended version of the growing rectangular domain algorithm is proposed to provide an ensemble of near-optimum predictor domains for a statistical downscaling method. This algorithm is applied to find five-member ensembles of near-optimum geopotential predictor domains for an analogue downscaling method for 608 individual target zones covering France. Results first show that very similar downscaling performances based on the continuous ranked probability score (CRPS) can be achieved by different predictor domains for any specific target zone, demonstrating the need for considering alternative domains in this context of high equifinality. A second result is the large diversity of optimised predictor domains over the country that questions the commonly made hypothesis of a common predictor domain for large areas. The domain centres are mainly distributed following the geographical location of the target location, but there are apparent differences between the windward and the lee side of mountain ridges. Moreover, domains for target zones located in southeastern France are centred more east and south than the ones for target locations on the same longitude. The size of the optimised domains tends to be larger in the southeastern part of the country, while domains with a very small meridional extent can be found in an east-west band around 47 • N. Sensitivity experiments finally show that results are rather insensitive to the starting point of the optimisation algorithm except for zones located in the transition area north of this east-west band. Results also appear generally robust with respect to the archive length considered for the analogue method, except for zones with high interannual variability like in the Cévennes area. This study paves the way for defining regions with homogeneous geopotential predictor domains for precipitation downscaling over France, and therefore de facto ensuring the spatial coherence required for hydrological applications.

show abstract

Section: Statistical Downscaling Methodsmentioning

confidence: 99%

Optimising predictor domains for spatially coherent precipitation downscaling

Radanovics¹,

Vidal²,

Sauquet³

et al. 2013

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…The atmospheric analog days retained for the regression stage are identified with an analog model defined from the developments of several past studies in France (e.g., Obled et al, 2002;Marty et al, 2012;Chardon et al, 2014).…”

Section: Atmospheric Analogsmentioning

confidence: 99%

“…Statistical downscaling models (SDMs) have been widely used to generate local weather scenarios for past or future climates from outputs of climate models (e.g., Wilby et al, 1999;Hanssen-Bauer et al, 2005;Boé et al, 2007;Lafaysse et al, 2014) and to produce local weather forecasts from outputs of numerical weather prediction models (e.g., Obled et al, 2002;Gangopadhyay et al, 2005;Marty et al, 2012;Ben Daoud et al, 2016). For recent years, they have also been used to reconstruct past weather conditions from atmospheric reanalysis data (e.g., Kuentz et al, 2015;Caillouet et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…The analog model (AM) used for the analog stage is based on developments from different studies initially focusing on the probabilistic quantitative precipitation forecasts in southern France (e.g., Bontron and Obled, 2005;Marty et al, 2012) and extended to the prediction of precipitation on larger spatial domains (e.g., Chardon et al, 2014). The statistical distribution of daily precipitation is strongly non-Gaussian with a non-negligible mass in zero (corresponding to the probability of a dry day), and a skewed distribution for non-zero daily amounts.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

Chardon

Hingray

Favre

2018

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Statistical downscaling models (SDMs) are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

show abstract

“…Several methodologies are actively studied to deal with this source of uncertainty, e. g., ensemble forecasts [3] or the analogous sorting approach [4]. Hydrological and hydraulic modelling uncertainty (including parameter uncertainty) is far from being negligible either.…”

Section: Operational Forecasts Uncertainty Sourcesmentioning

confidence: 99%

Operational forecast uncertainty assessment for better information to stakeholders and crisis managers

Berthet

Piotte²,

Gaumé³

et al. 2016

E3S Web Conf.

Self Cite

View full text Add to dashboard Cite

Abstract. Flood forecasting uncertainty is crucial information for decision makers. However, deterministic only forecasts have been communicated in France until now, like in many other countries. The French Flood Forecast Centres (FFCs) recently set up a new service which aims at publishing quantitative forecasts along with their associated uncertainty. Two surveys (one of the greater audience and identified end-users, another of FFCs worldwide) were conducted to design it. The forecasters' toolbox was then supplemented with two new tools. The first one provides automatic forecasting uncertainty estimations calibrated on past forecasting error series. The second one allows the forecasters to incorporate their own expertise to adjust the automatically calculated uncertainty estimation. The evaluation of the forecast uncertainty estimations issued in real time in 2014 suggests that even if these assessments are perfectible, they are already informative and useful for end-users. The first feedbacks from forecasters and crisis managers also show that if the assessment of probabilistic forecasts remains a technical challenge, their use is foremost a human challenge. This move is a paradigm change for both forecasters and decision makers. Therefore, they have to be accompanied in order to achieve this deep shift in their professional practice.

show abstract

Toward Real-Time Daily PQPF by an Analog Sorting Approach: Application to Flash-Flood Catchments

Cited by 51 publications

References 29 publications

Optimising predictor domains for spatially coherent precipitation downscaling

Optimising predictor domains for spatially coherent precipitation downscaling

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

Operational forecast uncertainty assessment for better information to stakeholders and crisis managers

Contact Info

Product

Resources

About