| 27 Dec 2025
The catastrophic floods in 2008, 2010 and 2020 in western Ukraine: Hydrometeorological processes and the role of upper-level dynamics
Abstract. Western Ukraine has encountered significant challenges due to three extensive summer rainfall events and major floods in July 2008, July 2010, and June 2020, resulting in numerous fatalities and substantial economic damage. This study investigates the hydrometeorological conditions, as well as the atmospheric processes, that led to these three devastating flood events in the basins of the Tisza, Prut, Siret, and Dniester rivers in western Ukraine. Emphasis is placed on the role of upper-level potential vorticity (PV) structures, analyzed through two complementary approaches: (1) case studies linking the surface weather evolution with upper-level PV dynamics, and (2) a climatological composite analysis on the link between precipitation and upper-level PV, including 22 heavy precipitation events in the period 2000–2022, using reanalysis (ERA5) and satellite-based (IMERG) datasets. The results show that all three floods were driven by multi-day heavy precipitation events, which differed in intensity, spatial extent, and dominant forcing mechanisms. The 2008 event was the most severe, associated with a PV cutoff, intense moisture transport, and extreme precipitation, leading to river levels surpassing historical records. In contrast, the heavy precipitation in July 2010 was driven primarily by direct upper-level dynamic forcing and less moisture transport, which probably caused more localized flooding. The flood in 2020 was notable for its hydrological complexity and evolved more rapidly than the 2008 flood. This event was characterized by remote PV influence, with moisture advection and mesoscale processes playing a more prominent role. In all cases, a persistent atmospheric block hindered the eastward movement of PV structures, maintaining quasi-stationary conditions of prolonged precipitation and moist low-level flow continuously advected against the Carpathian Mountains. Also worth noting, both the 2010 and 2020 events were preceded by several episodes of prolonged precipitation, resulting in saturated soil, gradually increasing river levels and creating favorable conditions for subsequent flooding. The climatological analysis further confirms the strong association between upper-level PV structures and heavy precipitation in the region: 64% of them are associated with a PV streamer, 23% with a PV cutoff, and 13% with combined occurrences of PV streamers and cutoffs. The amplitude and frequency of upper-level PV cutoffs and streamers associated with the heavy precipitation events are largest over eastern Europe, particularly in Romania and Slovenia, pointing out the significance of PV dynamics for heavy precipitation and flood generation in western Ukraine.
Dear Authors,
the paper is overall well written and presents interesting insights into dynamic drivers of extreme precipitation. Please note, that while I have a general understanding of fluid dynamics and potential vorticity, I am not an expert on detailed potential vorticity dynamics, which is affecting the perspective from which the following comments stem from. I suggest to revise the paper as follows.
GENERAL COMMENTS
The overall storyline is clear and well written and the research questions are clearly stated. The paper is well structured, but I think it could benefit further from some slight restructuring in a few places and from enriching some paragraphs with more detailed information.
While PV structures for predicting floods is mentioned (e.g. line 65 in the introduction and line 640 in the conclusions) it is unclear in what way. Since extreme precipitation (in terms of the case studies) coincides with PV structures, what is the benefit of incorporating them for flood prediction on top of precipitation predictions themselves? Is it related to better medium-range predictability of the large-scale patterns and could it enhance early-warning systems in that way? Further, what about "false-positives" for PV structures, meaning that while PV structures capture the dynamics, there still needs to be enough moisture available for extreme precipitation. Is this included indirectly due to the regional geography, or could only looking at PV structures lead to false-positives for extreme flood prediction? Perhaps you could comment on that and/or elaborate on the specifics on how this can enhance flood prediction more clearly and how moisture sources in combination with PV structures are relevant.
For the climatological analysis, the separation between PV streamers and cutoffs is quantified, but the composites are only provided for both together. I wonder if the climatological analysis could benefit from a separate look into either PV state and in particular their influence for the most extreme precipitation.
SPECIFIC COMMENTS
- Regarding the restructuring, the hydrological overviews for the case studies in sections 3.2.1, 3.3.1, 3.4.1 contain last paragraphs about various impacts. I think moving these into the introduction and talk about impacts there improves the flow of the text, due to the hydrology (and following precipitation) not being interrupted by impacts.
- In section 2.1, the catchments are described and therein for Dniester, peak discharge characteristics are explained. Perhaps consider also adding similar information for the other catchments to highlight typical peak discharge characteristics.
- The period covered is 2000–2022, but ERA5 at least is available for longer. While it may be out of scope for this study, an outlook could mention extending this analysis to investigate potential changes/trends/intensification of PV dynamics.
- lines 233-234: it is mentioned that first "the most significant precipitation" and then the "highest precipitation intensity" followed the day after. What is meant with most significant if it's not the highest?
- Fig. 4b: It looks like there is a significant difference between the station data for Yaremche and the gridded data. Perhaps this can be commented on, including possible conclusions about uncertainty in either dataset. Same in Fig. 7b and the station Plai and in Fig. 11b for Yaremche.
- In section 3.3, the very first paragraph discusses not just the particular case study, but also other extreme weather events globally. These fit better into the introduction rather than the specific section for the case study.
TECHNICAL COMMENTS
- line 61: "mountainous"
- Fig. 1, 3, 6, 10: labels/units on the map (°N, °E, ..)
- Fig. 3, 6, 10: I find the flood magnitude symbols hard to read, specifically the differences between 51 and 76 as well as between 101 and 150.
- Fig. 4a, 7a, : The overlapping colours between catchments/lineplots and the y-axis are confusing at first. Perhaps consider different colours for the two y-axes.
- Fig. 5, 8, 9, 12: The precipitation values in the left-hand column plots are very hard to read
- line 252: How many stations did report new records? Perhaps consider just adding the numerical value.
- line 307: "it is plausible" (missing "is")
- line 417, 418, 683: Rossby Wave Breaking is abbreviated as RWB, please just add the explanation the first time it's mentioned (or vice versa add "(RWB)" the first time rossby wave breaking is mentioned)
- line 510: 99th percentile from all days, or wet-days only?
- line 560, 609: looks like there are two spaces before "(Fig. 14b,e)" and between "the high-pressure"
- line 678: please properly link the IMERG doi as url
- line 684: "Index of /staff..." looks like a mistake, please add a correct link/url/doi