Predictability of large-scale atmospheric flow patterns connected to extreme precipitation events in the Mediterranean

2021 ◽  
Author(s):  
Nikolaos Mastrantonas ◽  
Linus Magnusson ◽  
Florian Pappenberger ◽  
Jörg Matschullat
Keyword(s):  
Extreme Precipitation ◽  
Mediterranean Region ◽  
Large Scale ◽  
Prediction Models ◽  
Weather Prediction ◽  
Flow Patterns ◽  
Atmospheric Flow ◽  
Extreme Precipitation Events ◽  
The Mediterranean ◽  
Precipitation Events

<p>The Mediterranean region frequently experiences extreme precipitation events with devastating consequences for the affected societies, economies, and environment. Being able to provide reliable and skillful predictions of such events is crucial for mitigating their adverse impacts and related risks. One important part of the risk mitigation chain is the sub-seasonal predictability of such extremes, with information provided at such timescales supporting a range of actions, as for example warn decision-makers, and preposition materials and equipment.</p><p>This work focuses on the predictability of large-scale atmospheric flow patterns connected to extreme precipitation events in the Mediterranean. Previous research has identified strong connections between localized extremes and large-scale patterns. This is promising to provide useful information at sub-seasonal timescales. For such lead times, the Numerical Weather Prediction models are more skillful in predicting large-scale patterns than localized extremes. Here, we analyze the usefulness of these connections at sub-seasonal timescales by using the ECMWF extended-range forecasts. We aim at quantifying related benefits for the different areas in the Mediterranean region and providing insights that are of interest to the operational community.</p><p>Initial results suggest that the ECMWF forecasts provide skillful information in the predictability of large-scale patterns up to about 15 days lead time.</p><p> </p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.3687c29b370068376801161/sdaolpUECMynit/12UGE&app=m&a=0&c=49e65b5908090e0787f0f7f4f8930219&ct=x&pn=gnp.elif&d=1" alt=""></p><p>Large-scale patterns over the Mediterranean based on anomalies of sea level pressure (color shades) and geopotential at 500 hPa (contours) (Figure adapted from Mastrantonas et al, 2020)</p>

Extreme precipitation events in the Mediterranean region: their characteristics and connection to large-scale atmospheric patterns

2020 ◽  
Author(s):  
Nikolaos Mastrantonas ◽  
Linus Magnusson ◽  
Florian Pappenberger ◽  
Jörg Matschullat
Keyword(s):  
Natural Hazards ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Mediterranean Region ◽  
Large Scale ◽  
Early Warning Systems ◽  
Spatiotemporal Variability ◽  
Extreme Precipitation Events ◽  
The Mediterranean ◽  
Precipitation Events

<p>The Mediterranean region is an area with half a billion population, about 10 percent contribution to the world’s GDP, and locations of global natural, historical and cultural significance. In this context, natural hazards in the area have the potential for severe negative impacts on society, economy, and environment. </p><p>Some of the most frequent and devastating natural hazards that affect the Mediterranean relate to extreme precipitation events causing flash floods and landslides. Thus, given their adverse consequences, it is of immense importance to better understand their statistical characteristics and connection to large-scale atmospheric patterns. Such advances can substantially support the accurate and early identification of these extreme events, improve early warning systems, and contribute to mitigating related risks. </p><p>This work focuses on the characteristics and spatiotemporal variability of extreme precipitation events of large spatial coverage across the Mediterranean region. The study uses the ERA5 dataset, the latest, state of the art, reanalysis dataset from Copernicus/ECMWF. Initially, exploratory analysis is performed to assess the different characteristics at various subdomains within the study area. Furthermore, composite analysis is used to understand the connection of extreme events with large-scale atmospheric patterns. Finally, the Empirical Orthogonal Function (EOF) analysis is implemented to quantify the importance of weather regimes with respect to the frequency of extreme precipitation events. </p><p>Preliminary results indicate that there is a spatial division in the occurrence of identified events. Winter and autumn are the seasons of the highest frequency of extreme precipitation for the east and west Mediterranean respectively. Troughs and cut-off lows in the lower and middle-level troposphere have a strong association with such extreme events, and the effect is modulated by other parameters, such as local orography. Results of this work are in accordance with previous studies in the region and provide information that can be utilized by future research for improving the predictability of such events in the medium- and extended-range forecasts. </p><p>This work is part of the Climate Advanced Forecasting of sub-seasonal Extremes (CAFE) project. The project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844.</p>

The role of the export of tropical moisture into midlatitudes for extreme precipitation events in the Mediterranean region

2014 ◽  
Vol 121 (3-4) ◽  
pp. 499-515 ◽  
Author(s):  
Simon O. Krichak ◽  
Joseph Barkan ◽  
Joseph S. Breitgand ◽  
Silvio Gualdi ◽  
Steven B. Feldstein
Keyword(s):  
Extreme Precipitation ◽  
Mediterranean Region ◽  
Extreme Precipitation Events ◽  
The Mediterranean ◽  
Tropical Moisture ◽  
Precipitation Events

scholarly journals Discussing the role of tropical and subtropical moisture sources in extreme precipitation events in the Mediterranean region from a climate change perspective

2015 ◽  
Vol 3 (6) ◽  
pp. 3983-4005 ◽  
Author(s):  
S. O. Krichak ◽  
S. B. Feldstein ◽  
P. Alpert ◽  
S. Gualdi ◽  
E. Scoccimarro ◽  
...  
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Mediterranean Region ◽  
Extreme Weather Events ◽  
Recent Past ◽  
Atmospheric Rivers ◽  
Extreme Precipitation Events ◽  
The Mediterranean ◽  
Precipitation Events

Abstract. Extreme precipitation events in the Mediterranean region during the cool season are strongly affected by the export of moist air from tropical and subtropical areas into the extratropics. The aim of this paper is to present a discussion of the major research efforts on this subject and to formulate a summary of our understanding of this phenomenon, along with its recent past trends from a climate change perspective. The issues addressed are: a discussion of several case studies; the origin of the air moisture and the important role of atmospheric rivers for fueling the events; the mechanism responsible for the intensity of precipitation during the events, and the possible role of global warming in recent past trends in extreme weather events over the Mediterranean region.

scholarly journals The impact of Ensemble-Based Assimilation of Thermodynamic Lidar Profiles on Forecasts of the Pre-Convective Environment and Convection Initiation of Heavy Precipitation Events over the Mediterranean region: The German contribution to WaLiNeAs

2021 ◽  
Author(s):  
Rohith Muraleedharan Thundathil ◽  
Thomas Schwitalla ◽  
Andreas Behrendt ◽  
Diego Lange ◽  
Cyrille Flamant ◽  
...  
Keyword(s):  
Water Vapor ◽  
Extreme Precipitation ◽  
Mediterranean Region ◽  
Heavy Precipitation ◽  
Water Levels ◽  
Measurement Campaign ◽  
Extreme Precipitation Events ◽  
The Mediterranean ◽  
The Impact ◽  
Precipitation Events

<p>Probabilistic quantitative precipitation forecasting (PrQPF) is a challenging field of meteorology, which is fundamental for the prediction and quantification of extreme precipitation events. With advanced remote-sensing instruments such as lidar systems, it is possible to acquire the high-resolution temporal and spatial dynamical and thermodynamic data for input to the numerical weather prediction (NWP) models through data assimilation (DA) techniques. During the fall, the Mediterranean region is often stricken by heavy precipitation events (HPEs), resulting in a sudden rise of water levels in the rivers and flash floods. Severe damage to life and property arises during these extreme precipitation events every year. A unique and innovative French initiative project, called the Water Vapor Lidar Network assimilation (WaLiNeAs), will start a measurement campaign in early September 2022, deploying a network of autonomous water vapor lidars from research groups of France, Germany, and Italy across the Western Mediterranean. The project aims to implement an integrated prediction tool to enhance the forecast of HPEs in southern France, primarily demonstrating the benefit of assimilating vertically resolved water vapor data in the new version of the French operational AROME NWP system. The Atmospheric Raman Temperature and Humidity Sounder (ARTHUS, (Lange et al. 2019)), from the University of Hohenheim (UHOH), will operate in synergy with other lidar systems. The data collected from the measurement campaign, water vapor and temperature, will be assimilated in the Weather Research and Forecasting (WRF) model system at the Institute of Physics and Meteorology (IPM), UHOH. A thermodynamic lidar operator developed by some of us (Thundathil et al. 2020) will be used to assimilate lidar temperature and water vapor mixing ratio independently. The operator avoids undesirable cross sensitivities to temperature enabling maximum moisture information of the observation to be propagated into the model. An advanced hybrid three-dimensional Variational - Ensemble Transform Kalman Filter (3DVAR-ETKF) DA system with 50 ensemble members, on a convection-permitting resolution of 1.5 km, will be set up for the research study. For the prediction and quantification of the HPE event, the assimilation will be performed in a rapid update cycle mode every 15 minutes before its occurrence. A prototype of the DA system with ten ensemble members and a one-hour rapid update cycle was already developed at IPM (Thundathil et al., 2021). In this case, the impact from a single ground-based lidar spreads spatially for a radius of 100 km. Apart from the improvement in the analyses, the planetary boundary layer height (PBLH) forecast impact persisted 7 hours into forecast time compared with respect to independent ceilometer observations. The results show a promising initiative for future operational lidar network assimilation. We will present the outline and DA setup of the study, highlighting results from our previous lidar DA research.</p>

Lagrangian review of the origin of the humidity for the case of two extreme precipitation events in the Mediterranean region 

2021 ◽  
Author(s):  
Sara Cloux ◽  
Damián Insua-Costa ◽  
Gonzalo Miguez-Macho ◽  
Vicente Perez-Muñuzuri
Keyword(s):  
Relative Humidity ◽  
Extreme Precipitation ◽  
Mediterranean Region ◽  
Weather Data ◽  
Earth System ◽  
Atmospheric Moisture ◽  
Extreme Precipitation Events ◽  
The Mediterranean ◽  
Atmospheric Phenomena ◽  
Precipitation Events

<div> <p>Extreme precipitation events are atmospheric phenomena causing floods that generate great economic and social losses. The Mediterranean region is characterized by a strong variability in time and space that favors the appearance of this type of phenomena. Therefore, determining the origin of humidity must be done.     </p> </div><div> <p>The UTrack-atmospheric-moisture model [1] is a Lagrangian tool to track atmospheric moisture flows forward in time using ERA-5 reanalysis weather data. The labeled moisture is released into the atmosphere in the form of evaporation. After determine the allocated moisture precipitated at each time, this model allows us to know the percentage of relative humidity that has precipitated for each of the labeled sources.  Here we present a comparison of these results with previous results obtained by other Lagrangian methods. </p> </div><div> <p>[1] Tuinenburg, Obbe A., and Arie Staal. Tracking the global flows of atmospheric moisture and associated uncertainties." Hydrology and Earth System Sciences 24.5 (2020): 2419-2435. </p> </div>

A novel method to identify subseasonal clustering episodes of extreme precipitation events and their contribution to large accumulations

2021 ◽  
Author(s):  
Jérôme Kopp ◽  
Pauline Rivoire ◽  
S. Mubashshir Ali ◽  
Yannick Barton ◽  
Olivia Martius
Keyword(s):  
Time Scales ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Time Window ◽  
Heat Waves ◽  
Reanalysis Data ◽  
Data Set ◽  
Temporal Clustering ◽  
Extreme Precipitation Events ◽  
Precipitation Events

<p>Temporal clustering of extreme precipitation events on subseasonal time scales is a type of compound event, which can cause large precipitation accumulations and lead to floods. We present a novel count-based procedure to identify subseasonal clustering of extreme precipitation events. Furthermore, we introduce two metrics to characterise the frequency of subseasonal clustering episodes and their relevance for large precipitation accumulations. The advantage of this approach is that it does not require the investigated variable (here precipitation) to satisfy any specific statistical properties. Applying this methodology to the ERA5 reanalysis data set, we identify regions where subseasonal clustering of annual high precipitation percentiles occurs frequently and contributes substantially to large precipitation accumulations. Those regions are the east and northeast of the Asian continent (north of Yellow Sea, in the Chinese provinces of Hebei, Jilin and Liaoning; North and South Korea; Siberia and east of Mongolia), central Canada and south of California, Afghanistan, Pakistan, the southeast of the Iberian Peninsula, and the north of Argentina and south of Bolivia. Our method is robust with respect to the parameters used to define the extreme events (the percentile threshold and the run length) and the length of the subseasonal time window (here 2 – 4 weeks). The procedure could also be used to identify temporal clustering of other variables (e.g. heat waves) and can be applied on different time scales (e.g. for drought years). <span>For a complementary study on the subseasonal clustering of European extreme precipitation events and its relationship to large-scale atmospheric drivers, please refer to Barton et al.</span></p>

scholarly journals Large-Scale Flow Patterns Associated with Extreme Precipitation and Atmospheric Rivers over Norway

2019 ◽  
Vol 147 (4) ◽  
pp. 1415-1428 ◽  
Author(s):  
Imme Benedict ◽  
Karianne Ødemark ◽  
Thomas Nipen ◽  
Richard Moore
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Moisture Flux ◽  
Cold Season ◽  
Fuzzy Cluster ◽  
The South ◽  
Atmospheric Rivers ◽  
The North ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract A climatology of extreme cold season precipitation events in Norway from 1979 to 2014 is presented, based on the 99th percentile of the 24-h accumulated precipitation. Three regions, termed north, west, and south are identified, each exhibiting a unique seasonal distribution. There is a proclivity for events to occur during the positive phase of the NAO. The result is statistically significant at the 95th percentile for the north and west regions. An overarching hypothesis of this work is that anomalous moisture flux, or so-called atmospheric rivers (ARs), are integral to extreme precipitation events during the Norwegian cold season. An objective analysis of the integrated vapor transport illustrates that more than 85% of the events are associated with ARs. An empirical orthogonal function and fuzzy cluster technique is used to identify the large-scale weather patterns conducive to the moisture flux and extreme precipitation. Five days before the event and for each of the three regions, two patterns are found. The first represents an intense, southward-shifted jet with a southwest–northeast orientation. The second identifies a weak, northward-shifted, zonal jet. As the event approaches, regional differences become more apparent. The distinctive flow pattern conducive to orographically enhanced precipitation emerges in the two clusters for each region. For the north and west regions, this entails primarily zonal flow impinging upon the south–north-orientated topography, the difference being the latitude of the strong flow. In contrast, the south region exhibits a significant southerly component to the flow.

scholarly journals Large-Scale Predictors for Extreme Hourly Precipitation Events in Convection-Permitting Climate Simulations

2018 ◽  
Vol 31 (6) ◽  
pp. 2115-2131 ◽  
Author(s):  
Steven C. Chan ◽  
Elizabeth J. Kendon ◽  
Nigel Roberts ◽  
Stephen Blenkinsop ◽  
Hayley J. Fowler
Keyword(s):  
Extreme Precipitation ◽  
Land Surface ◽  
Large Scale ◽  
Future Climate ◽  
Cumulus Parameterization ◽  
Hourly Precipitation ◽  
Vertical Stability ◽  
Extreme Precipitation Events ◽  
Climate Simulations ◽  
Precipitation Events

Midlatitude extreme precipitation events are caused by well-understood meteorological drivers, such as vertical instability and low pressure systems. In principle, dynamical weather and climate models behave in the same way, although perhaps with the sensitivities to the drivers varying between models. Unlike parameterized convection models (PCMs), convection-permitting models (CPMs) are able to realistically capture subdaily extreme precipitation. CPMs are computationally expensive; being able to diagnose the occurrence of subdaily extreme precipitation from large-scale drivers, with sufficient skill, would allow effective targeting of CPM downscaling simulations. Here the regression relationships are quantified between the occurrence of extreme hourly precipitation events and vertical stability and circulation predictors in southern United Kingdom 1.5-km CPM and 12-km PCM present- and future-climate simulations. Overall, the large-scale predictors demonstrate skill in predicting the occurrence of extreme hourly events in both the 1.5- and 12-km simulations. For the present-climate simulations, extreme occurrences in the 12-km model are less sensitive to vertical stability than in the 1.5-km model, consistent with understanding the limitations of cumulus parameterization. In the future-climate simulations, the regression relationship is more similar between the two models, which may be understood from changes to the large-scale circulation patterns and land surface climate. Overall, regression analysis offers a promising avenue for targeting CPM simulations. The authors also outline which events would be missed by adopting such a targeted approach.

Sign in / Sign up

Export Citation Format

Share Document