scholarly journals A novel method to identify sub-seasonal clustering episodes of extreme precipitation events and their contributions to large accumulation periods

2021 ◽  
Vol 25 (9) ◽  
pp. 5153-5174 ◽  
Author(s):  
Jérôme Kopp ◽  
Pauline Rivoire ◽  
S. Mubashshir Ali ◽  
Yannick Barton ◽  
Olivia Martius
Keyword(s):  
Extreme Precipitation ◽  
Time Window ◽  
Heat Waves ◽  
Reanalysis Data ◽  
Data Set ◽  
The North ◽  
Extreme Precipitation Events ◽  
Compound Event ◽  
Central Canada ◽  
Precipitation Events

Abstract. Temporal (serial) clustering of extreme precipitation events on sub-seasonal timescales is a type of compound event. It can cause large precipitation accumulations and lead to floods. We present a novel, count-based procedure to identify episodes of sub-seasonal clustering of extreme precipitation. We introduce two metrics to characterise the prevalence of sub-seasonal clustering episodes and their contribution to large precipitation accumulations. The procedure does not require the investigated variable (here precipitation) to satisfy any specific statistical properties. Applying this procedure to daily precipitation from the ERA5 reanalysis data set, we identify regions where sub-seasonal clustering occurs frequently and contributes substantially to large precipitation accumulations. The regions are the east and northeast of the Asian continent (northeast of China, North and South Korea, Siberia and east of Mongolia), central Canada and south of California, Afghanistan, Pakistan, the southwest 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 sub-seasonal time window (here 2–4 weeks). This procedure could also be used to identify temporal clustering of other variables (e.g. heat waves) and can be applied on different timescales (sub-seasonal to decadal). The code is available at the listed GitHub repository.

scholarly journals A novel method to identify sub-seasonal clustering episodes of extreme precipitation events and their contributions to large accumulation periods

2021 ◽  
Author(s):  
Jérôme Kopp ◽  
Pauline Rivoire ◽  
S. Mubashshir Ali ◽  
Yannick Barton ◽  
Olivia Martius
Keyword(s):  
Time Scales ◽  
Extreme Precipitation ◽  
Time Window ◽  
Heat Waves ◽  
Reanalysis Data ◽  
Data Set ◽  
The North ◽  
Extreme Precipitation Events ◽  
Compound Event ◽  
Precipitation Events

Abstract. Temporal (serial) clustering of extreme precipitation events on sub-seasonal time scales is a type of compound event. It can cause large precipitation accumulations and lead to floods. We present a novel, count-based procedure to identify episodes of sub-seasonal clustering of extreme precipitation. We introduce two metrics to characterise the frequency of sub-seasonal clustering episodes and their relevance for large precipitation accumulations. The procedure does not require the investigated variable (here precipitation) to satisfy any specific statistical properties. Applying this procedure to daily precipitation from the ERA5 reanalysis data set, we identify regions where sub-seasonal clustering occurs frequently and contributes substantially to large precipitation accumulations. The 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 southwest 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 sub-seasonal time window (here 2–4 weeks). This procedure could also be used to identify temporal clustering of other variables (e.g. heat waves) and can be applied on different time scales (sub-seasonal to decadal). The code is available at the listed GitHub repository.

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.

Predictability of precipitation extremes over the Mediterranean

2020 ◽  
Author(s):  
Ignazio Giuntoli ◽  
Federico Fabiano ◽  
Susanna Corti
Keyword(s):  
Extreme Precipitation ◽  
Winter Season ◽  
Seasonal Prediction ◽  
Reanalysis Data ◽  
Economic Activities ◽  
Weather Regimes ◽  
Extreme Precipitation Events ◽  
The Mediterranean ◽  
Prediction Systems ◽  
Precipitation Events

<p>Intense precipitations events are associated with impacts like damages to infrastructures, economic activities, agricultural crops, power production and society in general. The ability to predict extreme precipitation events months in advance is therefore of great value in densely populated areas like the Mediterranean and may be achieved using seasonal prediction systems like the Copernicus Climate Change Services (C3S) suite of models. Using weather regimes (WRs) from 500 hPa geopotential heights over the Mediterranean the two main objectives of this study are: first to identify how these regimes are linked to extreme precipitation events over the region using reanalysis data; and second to assess the ability of the C3S models in reproducing/predicting these extreme events. We identify four weather regimes for the winter season (DJF) describing the atmospheric circulation in the Mediterranean using the 1993-2016 period as reference, i.e. maximum availability of C3S hindcasts. We thus provide an assessment of the models’s ability in predicting extreme precipitation over the Mediterranean having quantified how daily precipitation anomalies are associated to each WR.</p>

Scale-dependent representation of extreme precipitation processes in regional and CPM scale simulations for the greater Alpine region

2021 ◽  
Author(s):  
Alberto Caldas-Alvarez ◽  
Hendrik Feldmann ◽  
Joaquim G. Pinto
Keyword(s):  
Extreme Precipitation ◽  
Rare Events ◽  
Potential Temperature ◽  
Low Pressure ◽  
Scale Dependency ◽  
Data Set ◽  
Extreme Precipitation Events ◽  
Spatial Coverage ◽  
Precipitation Processes ◽  
Precipitation Events

<p>Extreme precipitation events with return periods above 100-years (Most Extreme Precipitation Events; MEPE) are rare events by definition, as the observational record covers very few of such events. Therefore, our knowledge is insufficient to assess their potential intensities and physical processes on different scales. To fill this gap, large regional climate ensembles, like the one provided by the German Decadal Climate Predictions (MiKlip) project (> 10.000 years), are of great value as they provide a larger sample size of such rare events. The RCM ensemble samples present day climate conditions multiple times (Ehmele et al., 2020) with a resolution of 25 km, and thus it does not resolve the convection permitting scales (CPM).</p><p>In this study, we aim to combine the large RCM ensemble with episodic CPM-scale downscaling simulations to derive a better statistical and process related representation of MEPEs for Central Europe. As a first step, we evaluate two re-analysis driven long-term simulations with COSMO-CLM (CCLM) from MiKlip and CORDEX-FPS Convection with respect to their scale-dependent representation.</p><p>The simulations span the period 1971 to 2016 with the 25 km simulation and are forced by ERA40 until 1979 and by ERA-interim afterwards. The CPM simulation (~3 km) is forced by ERA-40 between 1971 and 1999 and by ERA-interim between 2000 and 2016. We validate the simulations against E-OBS (25 km) and the unique HYdrologische RASterdatensätze (HYRAS) precipitation data set (5 km). The investigation area is the greater Alpine area. We employ a Precipitation Severity Index (PSI) adapted from extreme wind detection (Leckebusch et al., 2008; Pinto et al., 2012) for extreme precipitation cases. The advantage of the PSI is its ability to account for extreme grid point precipitation as well as spatial coverage and event duration. The events are categorized objectively into composite Weather Types (WT) to enable further generalization of the findings.</p><p>The results show a clear overestimation of precipitation for the analysed period and area by the RCMs at both resolutions. However, large differences exist the representation of extreme precipitation. Compared to observations, the 3 km (25km) resolution overestimates (underestimates) precipitation intensity for extreme cases. This agrees with previous literature. Five different WTs are identified for the analysed period, with Autumn-Winter WT being the most common, followed by convective summer WT. The Autumn-Winter WT is characterized by deep, cold, low-pressure areas located over Northern Europe. Summer WT cases are characterized by stable high-pressure situations affected by incurring small low-pressure systems on its western flank (convective-prone situations). Regarding the scale dependency of precipitation processes, the coarse resolution tends to overestimate surface moisture in situations of heavy precipitation, leading to larger latent instability (CAPE) in the 25 km resolution than in its 3 km counterpart. Furthermore, a large-scale dependency is found in summer extreme precipitation cases for two stability-related variables, Equivalent Potential Temperature (θ<sub>e</sub><sup>850</sup>) at 850 hPa and moisture flux at the Lower Free Troposphere (LFT-moisture). In these cases, the overestimation (underestimation) of  and LFT-moisture by either resolution is in line with their precipitation overestimation (underestimation).</p>

scholarly journals North American extreme precipitation events and related large-scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends

2019 ◽  
Vol 53 (11) ◽  
pp. 6835-6875 ◽  
Author(s):  
Mathew Barlow ◽  
William J. Gutowski ◽  
John R. Gyakum ◽  
Richard W. Katz ◽  
Young-Kwon Lim ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Climate Models ◽  
Early Stage ◽  
Reanalysis Data ◽  
Model Representation ◽  
Dynamics Modeling ◽  
Considerable Uncertainty ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.

scholarly journals Extreme Precipitation in Models: An Evaluation

2016 ◽  
Vol 31 (6) ◽  
pp. 1853-1879 ◽  
Author(s):  
Gregory R. Herman ◽  
Russ S. Schumacher
Keyword(s):  
Extreme Precipitation ◽  
Wrf Model ◽  
Ensemble Forecast ◽  
Forecast Skill ◽  
Forecast System ◽  
Severe Storms ◽  
The North ◽  
Extreme Precipitation Events ◽  
The U.S ◽  
Precipitation Events

Abstract A continental United States (CONUS)-wide framework for analyzing quantitative precipitation forecasts (QPFs) from NWP models from the perspective of precipitation return period (RP) exceedances is introduced using threshold estimates derived from a combination of NOAA Atlas 14 and older sources. Forecasts between 2009 and 2015 from several different NWP models of varying configurations and spatial resolutions are analyzed to assess bias characteristics and forecast skill for predicting RP exceedances. Specifically, NOAA’s Global Ensemble Forecast System Reforecast (GEFS/R) and the National Severe Storms Laboratory WRF (NSSL-WRF) model are evaluated for 24-h precipitation accumulations. The climatology of extreme precipitation events for 6-h accumulations is also explored in three convection-allowing models: 1) NSSL-WRF, 2) the North American Mesoscale 4-km nest (NAM-NEST), and 3) the experimental High Resolution Rapid Refresh (HRRR). The GEFS/R and NSSL-WRF are both found to exhibit similar 24-h accumulation RP exceedance climatologies over the U.S. West Coast to those found in observations and are found to be approximately equally skillful at predicting these exceedance events in this region. In contrast, over the eastern two-thirds of the CONUS, GEFS/R struggles to predict the predominantly convectively driven extreme QPFs, predicting far fewer events than are observed and exhibiting inferior forecast skill to the NSSL-WRF. The NSSL-WRF and HRRR are found to produce 6-h extreme precipitation climatologies that are approximately in accord with those found in the observations, while NAM-NEST produces many more RP exceedances than are observed across all of the CONUS.

Global Occurrences of Extreme Precipitation and the Madden–Julian Oscillation: Observations and Predictability

2004 ◽  
Vol 17 (23) ◽  
pp. 4575-4589 ◽  
Author(s):  
Charles Jones ◽  
Duane E. Waliser ◽  
K. M. Lau ◽  
W. Stern
Keyword(s):  
Extreme Precipitation ◽  
General Circulation ◽  
Circulation Model ◽  
Global Scale ◽  
Madden Julian Oscillation ◽  
Potential Predictability ◽  
The North ◽  
Extreme Precipitation Events ◽  
Realistic Representation ◽  
Precipitation Events

Abstract This study investigates 1) the eastward propagation of the Madden–Julian oscillation (MJO) and global occurrences of extreme precipitation, 2) the degree to which a general circulation model with a relatively realistic representation of the MJO simulates its influence on extremes, and 3) a possible modulation of the MJO on potential predictability of extreme precipitation events. The observational analysis shows increased frequency of extremes during active MJO phases in many locations. On a global scale, extreme events during active MJO periods are about 40% higher than in quiescent phases of the oscillation in locations of statistically significant signals. A 10-yr National Aeronautics and Space Administration (NASA) Goddard Laboratory for the Atmospheres (GLA) GCM simulation with fixed climatological SSTs is used to generate a control run and predictability experiments. Overall, the GLA model has a realistic representation of extremes in tropical convective regions associated with the MJO, although some shortcomings also seem to be present. The GLA model shows a robust signal in the frequency of extremes in the North Pacific and on the west coast of North America, which somewhat agrees with observational studies. The analysis of predictability experiments indicates higher success in the prediction of extremes during an active MJO than in quiescent situations. Overall, the predictability experiments indicate the mean number of correct forecasts of extremes during active MJO periods to be nearly twice the correct number of extremes during quiescent phases of the oscillation in locations of statistically significant signals.

scholarly journals Characterisation of Extreme Precipitation Events in the Pyrenees: From the Local to the Synoptic Scale

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 665
Author(s):  
Marc Lemus-Canovas ◽  
Joan Albert Lopez-Bustins ◽  
Javier Martín-Vide ◽  
Amar Halifa-Marin ◽  
Damián Insua-Costa ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Western Mediterranean ◽  
Synoptic Scale ◽  
Air Mass ◽  
The North ◽  
Eastern Pyrenees ◽  
Extreme Precipitation Events ◽  
The Mediterranean ◽  
Precipitation Events ◽  
Western Pyrenees

Mountain systems within the Mediterranean region, e.g., the Pyrenees, are very sensitive to climate change. In the present study, we quantified the magnitude of extreme precipitation events and the number of days with torrential precipitation (daily precipitation ≥ 100 mm) in all the rain gauges available in the Pyrenees for the 1981–2015 period, analyzing the contribution of the synoptic scale in this type of event. The easternmost (under Mediterranean influence) and north-westernmost (under Atlantic influence) areas of the Pyrenees registered the highest number of torrential events. The heaviest events are expected in the eastern part, i.e., 400 mm day−1 for a return period of 200 years. Northerly advections over the Iberian Peninsula, which present a low zonal index, i.e., implying a stronger meridional component, give rise to torrential events over the western Pyrenees; and easterly advections favour extreme precipitation over the eastern Pyrenees. The air mass travels a long way, from the east coast of North America, bringing heavy rainfall to the western Pyrenees. In the case of the torrential events over the eastern Pyrenees, the trajectory of the air mass causing the events in these areas is very short and originates in the Mediterranean Basin. The North Atlantic Oscillation (NAO) index has no influence upon the occurrence of torrential events in the Pyrenees, but these events are closely related to certain Mediterranean teleconnections such as the Western Mediterranean Oscillation (WeMO).

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