Abstract

Abstract. The HYdrological cycle in the Mediterranean EXperiment (HyMeX) is intended to improve the capabilities of predicting high-impact weather events. Within its framework, the aim of the first special observation period (SOP1), 5 September to 6 November 2012, was to study heavy precipitation events and flash floods. Here, we present high-impact weather events over Croatia that occurred during SOP1. Particular attention is given to eight intense observation periods (IOPs), during which high precipitation occurred over the eastern Adriatic and Dinaric Alps. During the entire SOP1, the operational model forecasts generally well represented medium intensity precipitation, but heavy precipitation was frequently underestimated by the ALADIN model at an 8 km grid spacing and was overestimated at a higher resolution (2 km grid spacing). During IOP2, intensive rainfall occurred over a wider area around the city of Rijeka in the northern Adriatic. The short-range maximum rainfall totals were the largest ever recorded at the Rijeka station since the beginning of measurements in 1958. The rainfall amounts measured in intervals of 20, 30 and 40 min were exceptional, with return periods that exceeded a thousand, a few hundred and one hundred years, respectively. The operational precipitation forecast using the ALADIN model at an 8 km grid spacing provided guidance regarding the event but underestimated the rainfall intensity. An evaluation of numerical sensitivity experiments suggested that the forecast was slightly enhanced by improving the initial conditions through variational data assimilation. The operational non-hydrostatic run at a 2 km grid spacing using a configuration with the ALARO physics package further improved the forecast. This article highlights the need for an intensive observation period in the future over the Adriatic region to validate the simulated mechanisms and improve numerical weather predictions via data assimilation and model improvements in descriptions of microphysics and air–sea interactions.

Highlights

  • The special observation period 1 (SOP1) of the HYdrological cycle in the Mediterranean Experiment (HyMeX) project was performed from 5 September to 6 November 2012 (Drobinski et al, 2014)

  • The smallest value of polychoric correlation coefficient (PCC) was for intense observation periods (IOPs) 9, because they overestimated the number of strong precipitation events, especially ALADIN 2 km, which can be seen www.nat-hazards-earth-syst-sci.net/16/2657/2016/

  • The scores show that ALADIN 2 km tended to overestimate the frequency of strong events, whereas ALADIN 8 km tended to underestimate the frequency of strong events, with the sole exception of IOP19, for which both models overestimated the number of strong precipitation events

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Summary

Introduction

The special observation period 1 (SOP1) of the HYdrological cycle in the Mediterranean Experiment (HyMeX) project was performed from 5 September to 6 November 2012 (Drobinski et al, 2014). B. Ivancan-Picek et al.: Overview of the first HyMeX special observation period over Croatia nance, and to improve the ability of NWPs for forecasting the locations and intensities of heavy precipitation events in the Mediterranean. The Adriatic Sea is a north-west–south-east elongated basin in the central Mediterranean Sea, which is approximately 250 km wide and 800 km long and is almost entirely enclosed by mountains, namely the Apennines to the west and south-west, the Alps to the north and the Dinaric Alps to the east and south-east Those topographic features play a large role in the structure and evolution of the weather systems associated with heavy precipitation

HyMeX SOP1 in Croatia: observations and models
Observations
Mesoscale models
Heavy precipitation events over the Adriatic TA during SOP1
Overview of IOPs over the Adriatic TA
19 Rijeka inland
IOP16 and IOP18
Verification of the precipitation forecasts during SOP1
IOP2 over the north-eastern Adriatic TA
Extreme value analysis of the short-term precipitation maxima
Observational analysis
12 Sep 2012
Operational model forecasts
Influence of the data assimilation
Findings
Summary and conclusions
Full Text
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