Session 12 | Additional posters (Tuesday)

Session 12

Additional posters (Tuesday)
Posters
| Attendance Tue, 09 May, 14:30–16:00 (EEST) | Display Mon, 08 May, 09:00–Tue, 09 May, 18:30|Exhibition area
Tue, 14:30

Posters: Tue, 9 May, 14:30–16:00 | Exhibition area

Display time: Mon, 8 May, 09:00–Tue, 9 May, 18:30
P44
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ECSS2023-60
Dario Pumo, Marco Avanti, Antonio Francipane, and Leonardo Noto

The growing expansion of urban areas has profoundly modified the processes of generation and transferring of surface runoff; the increase in the density of infrastructures, human activities and population in urban settlements also implies a considerable rise of the elements exposed to flood risk. In the last years, climate change has induced an intensification of the hydro-climatic extreme events, and it has been globally observed an increase in the frequency of water related catastrophic events in urban areas, such as fluvial and pluvial floods.

Among the possible different approaches to mitigate hydraulic risk, non structural mitigation measures probably offer the highest potentialities in the short term. This study proposes a prototypal Early Warning System (EWS) for fluvial flood risk developed over a densely populated subarea of Palermo (Italy) threatened by the presence of the Oreto River. The proposed EWS is capable of determining a relationship between possible event scenarios and some potential precursors. Each event scenario identifies potential first points of flooding, flooding areas and water levels, providing hazard maps specific for people, vehicles and infrastructures. Forecast rainfall, antecedent soil moisture and initial river stage conditions are considered as event precursors. Rainfall characteristics considered are the 24/48 h forecast of the expected cumulative depth and duration, retrieved from the National Surveillance Bulletins based on a Sicily Local Area Model. Water levels monitored in real-time by the Oreto a Ponte Parco hydrometric station are used to derive a proxy measure for the antecedent soil moisture and the initial river stage conditions.

The system is based on numerical rainfall depth-duration thresholds previously defined for the basin under analysis that, for fixed antecedent moisture condition and rainfall hyetotype, provide a family of isocritical discharge curves. From such curves, once the characteristics of the expected rainfall event are known, it is possible to estimate the expected hydrograph peak. Coupling this information with the initial river stage, the EWS is able to retrieve a corresponding event scenario, exploiting a pre-built library of event scenarios previously developed offline through a coupled hydrological-hydraulic model, considering several project hydrographs under different initial river stage conditions. The computation domain was previously accurately defined, starting from a 2m DEM, opportunely corrected to account for the exact geometry of bridges and other infrastructures. The EWS was tested with respect to an historical flood event occurred in 2018, demonstrating satisfactory performances in terms of predicted flooding area and water levels.

How to cite: Pumo, D., Avanti, M., Francipane, A., and Noto, L.: An early warning system for urban fluvial floods based on a predefined library of hazard maps and rainfall depth-duration thresholds: the case study of Palermo (Italy), 11th European Conference on Severe Storms, Bucharest, Romania, 8–12 May 2023, ECSS2023-60, https://doi.org/10.5194/ecss2023-60, 2023.

P45
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ECSS2023-180
Rob Warren, Ivor Blockley, Dean Sgarbossa, and Harald Richter

The Australian Bureau of Meteorology (BoM) has recently operationalized a post-processing suite called ConvParams, which computes a wide array of convective parameters using output from the BoM’s global deterministic and ensemble NWP models. Outputs from the suite include parcel parameters such as CAPE and CIN (computed for a range of different initial parcels), kinematic diagnostics such as bulk wind difference and storm-relative helicity (computed for a range of different atmospheric layers), and composite indices such as the supercell composite parameter and significant tornado parameter. In addition, the suite also identifies important features in the atmospheric profile such as capping inversions and elevated mixed layers. A unique feature of ConvParams, compared to other similar codebases (NSHARP/SHARPpy, MetPy) is its use of high-order polynomials to approximate pseudoadiabatic processes, which permits parcel calculations that are both fast and highly accurate. Significant computational advantages also come from the use of an ahead-of-time compiler (Pythran), which “transpiles” the native Python code into fast C++ code. As well as being used in operations, ConvParams is being run as part of the second-generation BoM Atmospheric Regional Reanalysis for Australia (BARRA2), a regional downscaling of the ERA5 reanalysis, and the BoM Atmospheric Regional Projections for Australia (BARPA), a regional downscaling of CMIP6 climate projections. Once complete, these simulations will provide the most comprehensive picture of historical and future convective environments in Australia to date, supporting major research in this space over the coming years. This presentation will provide an overview of the ConvParams suite and highlight its applications in both operational forecasting and future research endeavours.

How to cite: Warren, R., Blockley, I., Sgarbossa, D., and Richter, H.: Convective parameters for severe weather forecasting and research in Australia, 11th European Conference on Severe Storms, Bucharest, Romania, 8–12 May 2023, ECSS2023-180, https://doi.org/10.5194/ecss2023-180, 2023.