the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 May 2023
Assessing the ability of a new seamless short-range ensemble rainfall product to anticipate flash floods in the French Mediterranean area
Abstract. Flash floods have dramatic economic and social consequences, and efficient adaptation policies are required to reduce their impacts, especially in a context of global change. Developing more efficient flash flood forecasting systems can largely contribute to these adaptation requirements. The aim of this study was to assess the ability of a new seamless short range (0–6 h) ensemble quantitative precipitation forecast (QPF) product, called PIAF-EPS and recently developed by Météo-France, to predict flash floods when used as input of an operational hydrological forecasting chain. For this purpose, eight flash flood events that occurred in the French Mediterranean region between 2019 and 2021 were reanalysed, using a similar hydrological modeling chain to the one implemented in the French “Vigicrues-Flash” operational flash flood monitoring system. The hydrological forecasts obtained from PIAF-EPS were compared to the forecasts obtained with different deterministic QPFs from which PIAF-EPS is directly derived (i.e. the AROME-NWC numerical weather prediction model, and the deterministic PIAF product). The verification method applied in this work uses scores calculated on contingency tables, and combines the forecasts issued on each 1 km2 pixel of the territory. This offers a detailed view of the forecast performances, covering the whole river network and including the small ungauged rivers. The results confirm the added value of the ensemble PIAF-EPS approach for flash flood forecasting, in comparison to the different deterministic scenarios considered.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(6724 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-907', Anonymous Referee #1, 23 Jun 2023
The research work presented in the paper “Assessing the ability of a new seamless short-range ensemble rainfall product to anticipate flash floods in the French Mediterranean area” aims at the evaluation of the added value of a seamless short range (0-6h) ensemble quantitative precipitation forecast (QPF) product, called PIAF-EPS for flash floods forecasting.
The work shows the results in terms of the skills of the system comparing the PIAF-EPS system with different deterministic QPFs calculated for eight intense rainfall events occurred between 2019 and 2021 in the French Mediterranean region.
The paper is quite-well written and readable even if some adjustment can be made in the order of the paragraph to make it clearer; the abstract and conclusions are satisfactory; the scientific methods and assumptions valid and well outlined. As a general comment I think the work of the paper is interesting from the point of view of the method of the research and for the analysis of the results. There are some parts less clear than other that need improvements and maybe further insight in some sections. Corrections and comments can be found in details in the pdf attached.
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AC1: 'Reply on RC1', Juliette Godet, 29 Aug 2023
First of all, we thank Referee #1 for this positive evaluation of our work and for the useful comments provided which will help to improve the overall quality of the manuscript. We provide in the pdf attached detailed answers showing how we plan to adapt the manuscript according to these suggestions.
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AC1: 'Reply on RC1', Juliette Godet, 29 Aug 2023
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RC2: 'Comment on egusphere-2023-907', Anonymous Referee #2, 08 Aug 2023
General comments:
This article presents a comparison between different QPF-forced hydrologic predictions of flash flooding events, featuring a recently developed ensemble technique at Meteo France. Selected events are used to assess the ability of these predictions to detect the occurrence of streamflow values exceeding defined frequency-based thresholds. QPE-forced hydrologic simulations are used as reference data. Metrics based on contingency table data such as the Critical Success Index are used to assess skill. While I don’t see any new scientific insights into QPF-forced hydrologic forecasts, this is a good contribution to the literature of tools with operational implementation. The article’s methods are based on robust work previously published by others. The manuscript is written well and in a concise manner. My only concern is that the authors do not provide enough details about the featured technique that is central to the study. My recommendation is that following some minor revisions, they paper could be accepted.
- My main comment is that the PIAF-EPS methodology is not described with enough details. The workflow schematic in Figure 2 does not provide any information on how the perturbations are computed, which seems to be an important aspect of the technique. Authors should include an example of these perturbations, so readers can get a sense of what they look like.
- Many acronyms not spelled out the first time they appear in the text. At least some of them are spelled out later in the document, but they should be spelled out as soon as they are used for the first time, so the reader is not left wondering about it.
Specific comments:
Line 61
“…for flash flood nowcasting purposes” Is it appropriate to say “flash flood nowcasting”? I have only seen nowcasting being used to describe QPE extrapolation.Line 81
“SMASH” (L80)
Is “PANTHERE” an acronym? If so, please spell it out.
Line 94
What is “…a ten-minute observation cutoff”? Do you mean only the first ten minutes worth of observations are assimilated? How many observations (how many data points) are actually assimilated? Also, specify what data are assimilated (radar, satellite, rain gauge?).
Line 96 – 97
Spelling out this acronym (PIAF) should occur earlier in the document, as soon as it is first used. Same with all other acronyms.
Line 92 – 112
Use of “Lead time”. Consider replacing the term “Lead time” with something like forecast length, or simply referring to a particular forecast by its length. For example, the 3h forecast, to refer to a forecast that goes out 3 hours into the future. The term “Lead time” implies skill associated to a particular forecast length, and not a configurable parameter.
Line 119
With “equiprobable”, do you mean perturbations are “drawn” from a uniform probability distribution?
Line 121
What do you mean with “subrandom”?
Line 126
A better term to replace “lead time” here would be forecast length.
Line 172 – 173
How costly? How often is the system changing?
Line 176
“…the importance of hydrological reaction response”?
Table 1
“Duration” does not seem appropriate. Use “Date”? Also, I see the order of the events in here is by date, but labels “A-H” are all over the place. Not a big deal, but this is very odd order to follow here and Figure 5. It feels like the labels’ purpose was to make it easier for the events to be organized/classified, but the way they are presented in this table seems to defeat said purpose?
Line 211 – 212
The word “assimilated” is misleading. Do you recursively use reference streamflow to improve model states and/or parameters? If not, then I strongly recommend using a different term here.
Line 255
Why was the 60th percentile chosen for the comparison? I could not see anything in the previous texts that would give indication that a particular percentile was to be used.
Line 360 – 361
More than confirming, a robust study on a large enough sample dataset should inform how truly valuable and applicable is the ensemble-based technique, particularly in real-time.
Citation: https://doi.org/10.5194/egusphere-2023-907-RC2 - AC2: 'Reply on RC2', Juliette Godet, 29 Aug 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-907', Anonymous Referee #1, 23 Jun 2023
The research work presented in the paper “Assessing the ability of a new seamless short-range ensemble rainfall product to anticipate flash floods in the French Mediterranean area” aims at the evaluation of the added value of a seamless short range (0-6h) ensemble quantitative precipitation forecast (QPF) product, called PIAF-EPS for flash floods forecasting.
The work shows the results in terms of the skills of the system comparing the PIAF-EPS system with different deterministic QPFs calculated for eight intense rainfall events occurred between 2019 and 2021 in the French Mediterranean region.
The paper is quite-well written and readable even if some adjustment can be made in the order of the paragraph to make it clearer; the abstract and conclusions are satisfactory; the scientific methods and assumptions valid and well outlined. As a general comment I think the work of the paper is interesting from the point of view of the method of the research and for the analysis of the results. There are some parts less clear than other that need improvements and maybe further insight in some sections. Corrections and comments can be found in details in the pdf attached.
-
AC1: 'Reply on RC1', Juliette Godet, 29 Aug 2023
First of all, we thank Referee #1 for this positive evaluation of our work and for the useful comments provided which will help to improve the overall quality of the manuscript. We provide in the pdf attached detailed answers showing how we plan to adapt the manuscript according to these suggestions.
-
AC1: 'Reply on RC1', Juliette Godet, 29 Aug 2023
-
RC2: 'Comment on egusphere-2023-907', Anonymous Referee #2, 08 Aug 2023
General comments:
This article presents a comparison between different QPF-forced hydrologic predictions of flash flooding events, featuring a recently developed ensemble technique at Meteo France. Selected events are used to assess the ability of these predictions to detect the occurrence of streamflow values exceeding defined frequency-based thresholds. QPE-forced hydrologic simulations are used as reference data. Metrics based on contingency table data such as the Critical Success Index are used to assess skill. While I don’t see any new scientific insights into QPF-forced hydrologic forecasts, this is a good contribution to the literature of tools with operational implementation. The article’s methods are based on robust work previously published by others. The manuscript is written well and in a concise manner. My only concern is that the authors do not provide enough details about the featured technique that is central to the study. My recommendation is that following some minor revisions, they paper could be accepted.
- My main comment is that the PIAF-EPS methodology is not described with enough details. The workflow schematic in Figure 2 does not provide any information on how the perturbations are computed, which seems to be an important aspect of the technique. Authors should include an example of these perturbations, so readers can get a sense of what they look like.
- Many acronyms not spelled out the first time they appear in the text. At least some of them are spelled out later in the document, but they should be spelled out as soon as they are used for the first time, so the reader is not left wondering about it.
Specific comments:
Line 61
“…for flash flood nowcasting purposes” Is it appropriate to say “flash flood nowcasting”? I have only seen nowcasting being used to describe QPE extrapolation.Line 81
“SMASH” (L80)
Is “PANTHERE” an acronym? If so, please spell it out.
Line 94
What is “…a ten-minute observation cutoff”? Do you mean only the first ten minutes worth of observations are assimilated? How many observations (how many data points) are actually assimilated? Also, specify what data are assimilated (radar, satellite, rain gauge?).
Line 96 – 97
Spelling out this acronym (PIAF) should occur earlier in the document, as soon as it is first used. Same with all other acronyms.
Line 92 – 112
Use of “Lead time”. Consider replacing the term “Lead time” with something like forecast length, or simply referring to a particular forecast by its length. For example, the 3h forecast, to refer to a forecast that goes out 3 hours into the future. The term “Lead time” implies skill associated to a particular forecast length, and not a configurable parameter.
Line 119
With “equiprobable”, do you mean perturbations are “drawn” from a uniform probability distribution?
Line 121
What do you mean with “subrandom”?
Line 126
A better term to replace “lead time” here would be forecast length.
Line 172 – 173
How costly? How often is the system changing?
Line 176
“…the importance of hydrological reaction response”?
Table 1
“Duration” does not seem appropriate. Use “Date”? Also, I see the order of the events in here is by date, but labels “A-H” are all over the place. Not a big deal, but this is very odd order to follow here and Figure 5. It feels like the labels’ purpose was to make it easier for the events to be organized/classified, but the way they are presented in this table seems to defeat said purpose?
Line 211 – 212
The word “assimilated” is misleading. Do you recursively use reference streamflow to improve model states and/or parameters? If not, then I strongly recommend using a different term here.
Line 255
Why was the 60th percentile chosen for the comparison? I could not see anything in the previous texts that would give indication that a particular percentile was to be used.
Line 360 – 361
More than confirming, a robust study on a large enough sample dataset should inform how truly valuable and applicable is the ensemble-based technique, particularly in real-time.
Citation: https://doi.org/10.5194/egusphere-2023-907-RC2 - AC2: 'Reply on RC2', Juliette Godet, 29 Aug 2023
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Cited
Juliette Godet
Olivier Payrastre
Pierre Javelle
François Bouttier
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(6724 KB) - Metadata XML