Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy

During the night between 9 and 10 September 2017, multiple flash floods associated with a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours was recorded. This rainfall intensity is associated with a return period of higher than 200 years. As a consequence, all the largest streams of the Livorno municipality flooded several areas of the town. We used the limited-area weather research and forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. A more accurate description of the low-level flows and a better assessment of the atmospheric water vapor field showed how the assimilation of radar data can improve quantitative precipitation forecasts.

Assimilating X- and S-band Radar Data for a Heavy Precipitation Event in Italy

During the night between 9 and 10 September 2017, multiple flash floods associated to a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours, associated with a return period higher than 200 years, caused all the largest streams of the Livorno municipality to flood several areas of the town. We used the limited-area Weather Research and Forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. By providing more accurate descriptions of the low-level flow and a better assessment of the atmospheric water vapour, the results demonstrate that assimilating radar data improved the quantitative precipitation forecasts.

The heavy precipitation event of 14–15 October 2018 in the Aude catchment: a meteorological study based on operational numerical weather prediction systems and standard and personal observations

The case of the heavy precipitation event on 14 and 15 October 2018 which has led to severe flash flooding in the Aude watershed in south-western France is studied from a meteorological point of view using deterministic and probabilistic numerical weather prediction systems, as well as a unique combination of observations from both standard and personal weather stations. This case features typical characteristics of Mediterranean heavy precipitation events such as its classic synoptic situation and its quasi-stationary convective precipitation that regenerates continuously, as well as some peculiarities such as the presence of a former hurricane and a pre-existing cold air mass close to the ground. Mediterranean Sea surface temperature and soil moisture anomalies are briefly reviewed, as they are known to play a role in this type of hydrometeorological events. A study of rainfall forecasts shows that the event had limited predictability, in particular given the small size of the watersheds involved. It is shown that the stationarity of precipitation, whose estimation benefits from data from personal stations, is linked to the presence near the ground of a trough and a strong potential virtual temperature gradient, the stationarity of both of which is highlighted by a combination of observations from standard and personal stations. The forecast that comes closest to the rainfall observations contains the warmest, wettest, and fastest low-level jet and also simulates near the ground a trough and a marked boundary between cold air in the west and warm air in the east, both of which are stationary.

Assessment of Urbanization Impact On Heavy Precipitation in Istanbul, Turkey

<p>Cities have undergone a substantial increase in urbanization over the past decades. Whether the change in land-use type and the consequent Urban Heat Island (UHI) affects the extreme precipitation was of interest and has been under investigation for various developing cities. This study pursued a similar purpose and investigated the impact of urbanization on a heavy precipitation incident that took place in Istanbul on 18 July 2017. Two particular land-use scenarios were used to simulate the event by Weather Research and Forecasting Model (WRF). First, the control simulation (WRF-urban) was performed using the default CORINE 2018 land-use dataset. Subsequently, the test simulation (WRF-nourban) was implemented by replacing the urbanized land-use type of Istanbul with the most dominant land use category of arid cultivated area. Comparison of the WRF-urban simulation with station observations and satellite data reveal that the WRF captured the heavy precipitation event reasonably well over Istanbul.  Results showed that urbanization has a notable impact on both the magnitude and timing of heavy rainfall.  Event day total precipitation amount increased considerably over and downstream of Istanbul on the control run. Although the start time and location of the incident reasonably matched for both runs, the test run without urbanization advanced the rainfall quicker, and the heavy precipitation event took place 1 hour earlier than the control run. The most pronounced distinction between the simulations with and without urbanization is detected over the northern coasts of Istanbul as the maximum daily total precipitation amount was approximately 250 mm higher just upstream and downstream of Istanbul Airport (IGA) on the WRF-urban run. Analysis of both vertical cross-sections and sensible heat fluxes on the city revealed that urbanized areas increased the atmospheric instability, thus caused heavier precipitation.</p>

Trois phénomènes météorologiques exceptionnels durant l'automne 2020

Durant cet automne 2020, la France est concernée par trois phénomènes météorologiques exceptionnels. Tout d'abord, le 19 septembre, un épisode cévenol intense apporte 700 mm en 12 heures sur la région de Valleraugue. Puis, le 1er octobre, la tempête Alex traverse le nord-ouest de la France, où les rafales atteignent 186 km/h à Belle-Île-en-Mer en raison de la présence d'un sting jet. Le lendemain, un nouvel épisode fortement précipitant déverse localement 500 mm de pluie sur les Alpes-Maritimes. Ces trois phénomènes ont tous relevé d'une vigilance rouge. During fall 2020, France is concerned by three extreme weather events. First, on september 19th , an intense cévenol event brings 700 mm in 12 hours over Valleraugue area. Then, on October the 1 st , Alex windstorm crosses northwestern France where gusts reach 186 km/h over Belle-Île-en-Mer because of the occurrence of a sting jet. The day after, a new heavy precipitation event spills a 500 mm rainfall locally over Alpes-Maritimes. All those three events received a red warning.

Dependence of predictability of precipitation in the northwestern Mediterranean coastal region on the strength of synoptic control

The weather-regime-dependent predictability of precipitation in the convection-permitting kilometric-scale AROME-EPS is examined for the entire HyMeX-SOP1 employing the convective adjustment timescale. This diagnostic quantifies variations in synoptic forcing on precipitation and is associated with different precipitation characteristics, forecast skill and predictability. During strong synoptic control, which dominates the weather on 80 % of the days in the 2-month period, the domain-integrated precipitation predictability assessed with the normalized ensemble standard deviation is above average, the wet bias is smaller and the forecast quality is generally better. In contrast, the pure spatial forecast quality of the most intense precipitation in the afternoon, as quantified with its 95th percentile, is superior during weakly forced synoptic regimes. The study also considers a prominent heavy-precipitation event that occurred during the NAWDEX field campaign in the same region, and the predictability during this event is compared with the events that occurred during HyMeX. It is shown that the unconditional evaluation of precipitation widely parallels the strongly forced weather type evaluation and obscures forecast model characteristics typical for weak control.