Ensemble-Based Analysis of the May 2010 Extreme Rainfall in Tennessee and Kentucky

2014 ◽  
Vol 142 (1) ◽  
pp. 222-239 ◽  
Author(s):  
Samantha L. Lynch ◽  
Russ S. Schumacher

Abstract From 1 to 3 May 2010, persistent heavy rainfall occurred in the Ohio and Mississippi River valleys due to two successive quasi-stationary mesoscale convective systems (MCSs), with locations in central Tennessee accumulating more than 483 mm of rain, and the city of Nashville experiencing a historic flash flood. This study uses operational global ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) to diagnose atmospheric processes and assess forecast uncertainty in this event. Several ensemble analysis methods are used to examine the processes that led to the development and maintenance of this precipitation system. Differences between ensemble members that correctly predicted heavy precipitation and those that did not were determined, in order to pinpoint the processes that were favorable or detrimental to the system's development. Statistical analysis was used to determine how synoptic-scale flows were correlated to 5-day area-averaged precipitation. The precipitation throughout Nashville and the surrounding areas occurred ahead of an upper-level trough located over the central United States. The distribution of precipitation was found to be closely related to the strength of this trough and an associated surface cyclone. In particular, when the upper-level trough was elongated, the surface cyclone remained weaker with a narrower low-level jet from the south. This caused the plume of moisture from the Caribbean Sea to be concentrated over Tennessee and Kentucky, where, in conjunction with focused ascent, heavy rain fell. Relatively small differences in the wind and pressure fields led to important differences in the precipitation forecasts and highlighted some of the uncertainties associated with predicting this extreme rainfall event.

2021 ◽  
Vol 169 (3-4) ◽  
Author(s):  
Linh N. Luu ◽  
Paolo Scussolini ◽  
Sarah Kew ◽  
Sjoukje Philip ◽  
Mugni Hadi Hariadi ◽  
...  

AbstractIn October 2020, Central Vietnam was struck by heavy rain resulting from a sequence of 5 tropical depressions and typhoons. The immense amount of water led to extensive flooding and landslides that killed more than 200 people, injured more than 500 people, and caused direct damages valued at approximately 1.2 billion USD. Here, we quantify how the intensity of the precipitation leading to such exceptional impacts is attributable to anthropogenic climate change. First, we define the event as the regional maximum of annual maximum 15-day average rainfall (Rx15day). We then analyse the trend in Rx15day over Central Vietnam from the observations and simulations in the PRIMAVERA and CORDEX-CORE ensembles, which pass our evaluation tests, by applying the generalised extreme value (GEV) distribution in which location and scale parameters exponentially covary with increasing global temperatures. Combining these observations and model results, we find that the 2020 event, occurring about once every 80 years (at least 17 years), has not changed in either probability of occurrence (a factor 1.0, ranging from 0.4 to 2.4) or intensity (0%, ranging from −8 to +8%) in the present climate in comparison with early-industrial climate. This implies that the effect of human-induced climate change contributing to this persistent extreme rainfall event is small compared to natural variability. However, given the scale of damage of this hazard, our results underline that more investment in disaster risk reduction for this type of rainfall-induced flood hazard is of importance, even independent of the effect of anthropogenic climate change. Moreover, as both observations and model simulations will be extended with the passage of time, we encourage more climate change impact investigations on the extreme in the future that help adaptation and mitigation plans and raise awareness in the country.


2020 ◽  
Vol 21 (3) ◽  
pp. 475-499 ◽  
Author(s):  
Francesca Viterbo ◽  
Kelly Mahoney ◽  
Laura Read ◽  
Fernando Salas ◽  
Bradford Bates ◽  
...  

AbstractThe NOAA National Water Model (NWM) became operational in August 2016, producing the first ever real-time, distributed, continuous set of hydrologic forecasts over the continental United States (CONUS). This project uses integrated hydrometeorological assessment methods to investigate the utility of the NWM to predict catastrophic flooding associated with an extreme rainfall event that occurred in Ellicott City, Maryland, on 27–28 May 2018. Short-range forecasts (0–18-h lead time) from the NWM version 1.2 are explored, focusing on the quantitative precipitation forecast (QPF) forcing from the High-Resolution Rapid Refresh (HRRR) model and the corresponding NWM streamflow forecast. A comprehensive assessment of multiscale hydrometeorological processes are considered using a combination of object-based, grid-based, and hydrologic point-based verification. Results highlight the benefits and risks of using a distributed hydrologic modeling tool such as the NWM to connect operational CONUS-scale atmospheric forcings to local impact predictions. For the Ellicott City event, reasonably skillful QPF in several HRRR model forecast cycles produced NWM streamflow forecasts in the small Ellicott City basin that were suggestive of flash flood potential. In larger surrounding basins, the NWM streamflow response was more complex, and errors were found to be governed by both hydrologic process representation, as well as forcing errors. The integrated, hydrometeorological multiscale analysis method demonstrated here guides both research and ongoing model development efforts, along with providing user education and engagement to ultimately engender improved flash flood prediction.


2021 ◽  
Author(s):  
Adhithiyan Neduncheran ◽  
Annalina Lombardi ◽  
Barbara Tomassetti ◽  
Marco Verdecchia ◽  
Valentina Colaiuda

<p>An extreme weather event hit the coastal city of Chennai, India, in November-December 2015 causing severe damage to infrastructure worth billions of dollars, people’s lives and their livelihood. Nearby districts to Chennai, such as Cuddalore, Kancheepuram and Tiruvallur were also affected by rainfall over 300mm during the first week of December. This was caused by the unusual wind surges in the troposphere providing favorable environmental conditions for the extensive rainfall and the formation of a deep depression in the Bay of Bengal on 30 November 2015, which was blocked by Eastern Ghats that inhibited the movement of the synoptic system. Electricity and telecommunication lines were suspended and some hospitals were shut down for a few days. It brought the whole city into a state of emergency and National Disaster Rescue Force were deployed in an effort to take care of the evacuation of people.</p><p>In this work, we present the estimation of the hydrological stress caused by the extreme rainfall event in Chennai and the nearby river basins during the course of this northeastern monsoon event in India. The hydrological stress is given through the application of Best Discharge based Drainage (BDD)  Index, calculated by the CETEMPS Hydrological Model (CHyM). Hydrological simulation is carried out by forcing the model with the 3-hourly NASA IMERG 0.1x0.1 grid precipitation dataset. Preliminary results show a spatial coherence between the hydrological stress detected by the index and the most impacted river segments, due to heavy precipitation. The application of hydrological stress indices is helpful for forecasting fluvial floods in the river network with minimum calibration requirements, providing a useful tool for warning the respective authorities for minimal losses due to natural calamities.</p>


2008 ◽  
Vol 136 (6) ◽  
pp. 1878-1897 ◽  
Author(s):  
Richard W. Moore ◽  
Michael T. Montgomery ◽  
Huw C. Davies

Abstract On 24–25 February 2005, a significant East Coast cyclone deposited from 4 to nearly 12 in. (∼10–30 cm) of snow on parts of the northeastern United States. The heaviest snowfall and most rapid deepening of the cyclone coincided with the favorable positioning of an upper-level, short-wave trough immediately upstream of a preexisting surface cyclone. The surface cyclone in question formed approximately 15 h before the heaviest snowfall along a coastal front in a region of frontogenesis and heavy precipitation. The incipient surface cyclone subsequently intensified as it moved to the northeast, consistently generating the strongest convection to the east-northeast of the low-level circulation center. The use of potential vorticity (PV) inversion techniques and a suite of mesoscale model simulations illustrates that the early intensification of the incipient surface cyclone was primarily driven by diabatic effects and was not critically dependent on the upper-level wave. These facts, taken in conjunction with the observed structure, energetics, and Lagrangian evolution of the incipient surface disturbance, identify it as a diabatic Rossby vortex (DRV). The antecedent surface vorticity spinup associated with the DRV phase of development is found to be integral to the subsequent rapid growth. The qualitative similarity with a number of observed cases of explosive cyclogenesis leaves open the possibility that a DRV-like feature comprises the preexisting positive low-level PV anomaly in a number of cyclogenetic events that exhibit a two-stage evolution.


2005 ◽  
Vol 5 (4) ◽  
pp. 505-525 ◽  
Author(s):  
R. Romero ◽  
A. Martín ◽  
V. Homar ◽  
S. Alonso ◽  
C. Ramis

Abstract. The HYDROPTIMET case studies (9–10 June 2000 Catalogne, 8–9 September 2002 Cévennes and 24–26 November 2002 Piémont) appear to encompass a sort of prototype flash-flood situations in the western Mediterranean attending to the relevant synoptic and mesoscale signatures identified on the meteorological charts. In Catalogne, the convective event was driven by a low-pressure system of relatively small dimensions developed over the mediterranean coast of Spain that moved into southern France. For Cévennes, the main circulation pattern was a synoptic-scale Atlantic low which induced a persistent southerly low-level jet (LLJ) over the western Mediterranean, strengthened by the Alps along its western flank, which guaranteed continuous moisture supply towards southern France where the long-lived, quasistationary convective system developed. The long Piémont episode, very representative of the most severe alpine flash flood events, shares some similarities with the Cévennes situation during its first stage in that it was controlled by a southerly moist LLJ associated with a large-scale disturbance located to the west. However, these circulation features were transient aspects and during the second half of the episode the situation was dominated by a cyclogenesis process over the Mediterranean which gave place to a mesoscale-size depression at surface that acted to force new heavy rain over the slopes of the Alps and maritime areas. That is, the Piémont episode can be catalogued as of mixed type with regard to the responsible surface disturbance, evolving from a large-scale pattern with remote action (like Cévennes) to a mesoscale pattern with local action (like Catalogne). A prominent mid-tropospheric trough or cut-off low can be identified in all events prior and during the period of heavy rain, which clearly served as the precursor agent for the onset of the flash-flood conditions and the cyclogenesis at low-levels. Being aware of the uncertainty in the representation of the upper-level disturbance and the necessity to cope with it within the operational context when attempting to issue short to mid-range numerical weather predictions of these high impact weather events, a systematic exploration of the predictability of the three selected case studies subject to uncertainties in the representation of the upper-level precursor disturbance is carried out in this paper. The study is based on an ensemble of mesoscale numerical simulations of each event with the MM5 non-hydrostatic model after perturbing in a systematic way the upper-level disturbance, in the sense of displacing slightly this disturbance upstream/downstream along the zonal direction and intensifying/weakening its amplitude. These perturbations are guided by a previous application of the MM5-adjoint model, which consistently shows high sensitivities of the dynamical control of the heavy rain to the flow configuration about the upper-level disturbance on the day before, thus confirming the precursor characteristics of this agent. The perturbations are introduced to the initial conditions by applying a potential vorticity (PV) inversion procedure to the positive PV anomaly associated with the upper-level disturbance, and then using the inverted fields (wind, temperature and geopotential) to modify under a physically consistent balance the model initial fields. The results generally show that the events dominated by mesoscale low-level disturbances (Catalogne and last stage of the Piémont episode) are very sensitive to the initial uncertainties, such that the heavy rain location and magnitude are in some of the experiments strongly changed in response to the "forecast errors" of the cyclone trajectory, intensity, shape and translational speed. In contrast, the other situations (Cévennes and initial stage of the Piémont episode), dominated by a larger scale system wich basically acts to guarantee the establishment and persistence of the southerly LLJ towards the southern France-north Italy orography, exhibit much higher predictability. That is, the slight modifications in the LLJ direction and intensity encompassed by the ensemble of perturbed forecasts are less critical with respect to the heavy precipitation potential and affected area.


2018 ◽  
Vol 75 (9) ◽  
pp. 2983-3009 ◽  
Author(s):  
Erik R. Nielsen ◽  
Russ S. Schumacher

Abstract In some prominent extreme precipitation and flash flood events, radar and rain gauge observations have suggested that the heaviest short-term rainfall accumulations (up to 177 mm h−1) were associated with supercells or mesovortices embedded within larger convective systems. In this research, we aim to identify the influence that rotation has on the storm-scale processes associated with heavy precipitation. Numerical model simulations conducted herein were inspired by a rainfall event that occurred in central Texas in October 2015 where the most extreme rainfall accumulations were collocated with meso-β-scale vortices. Five total simulations were performed to test the sensitivity of precipitation processes to rotation. A control simulation, based on a wind profile from the aforementioned event, was compared with two experiments with successively weaker low-level shear. With greater environmental low-level shear, more precipitation fell, in both a point-maximum and an area-averaged sense. Intense, rotationally induced low-level vertical accelerations associated with the dynamic nonlinear perturbation vertical pressure gradient force were found to enhance the low- to midlevel updraft strength and total vertical mass flux and allowed access to otherwise inhibited sources of moisture and CAPE in the higher-shear simulations. The dynamical accelerations, which increased with the intensity of the low-level shear, dominated over buoyant accelerations in the low levels and were responsible for inducing more intense low-level updrafts that were sustained despite a stable boundary layer.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Timothy David Hewson ◽  
Fatima Maria Pillosu

AbstractComputer-generated weather forecasts divide the Earth’s surface into gridboxes, each currently spanning about 400 km2, and predict one value per gridbox. If weather varies markedly within a gridbox, forecasts for specific sites inevitably fail. Here we present a statistical post-processing method for ensemble forecasts that accounts for the degree of variation within each gridbox, bias on the gridbox scale, and the weather dependence of each. When applying this post-processing, skill improves substantially across the globe; for extreme rainfall, for example, useful forecasts extend 5 days ahead, compared to less than 1 day without post-processing. Skill improvements are attributed to creation of huge calibration datasets by aggregating, globally rather than locally, forecast-observation differences wherever and whenever the observed “weather type” was similar. A strong focus on meteorological understanding also contributes. We suggest that applications for our methodology include improved flash flood warnings, physics-related insights into model weaknesses and global pointwise re-analyses.


Author(s):  
Hayley J. Fowler ◽  
Haider Ali ◽  
Richard P. Allan ◽  
Nikolina Ban ◽  
Renaud Barbero ◽  
...  

A large number of recent studies have aimed at understanding short-duration rainfall extremes, due to their impacts on flash floods, landslides and debris flows and potential for these to worsen with global warming. This has been led in a concerted international effort by the INTENSE Crosscutting Project of the GEWEX (Global Energy and Water Exchanges) Hydroclimatology Panel. Here, we summarize the main findings so far and suggest future directions for research, including: the benefits of convection-permitting climate modelling; towards understanding mechanisms of change; the usefulness of temperature-scaling relations; towards detecting and attributing extreme rainfall change; and the need for international coordination and collaboration. Evidence suggests that the intensity of long-duration (1 day+) heavy precipitation increases with climate warming close to the Clausius–Clapeyron (CC) rate (6–7% K −1 ), although large-scale circulation changes affect this response regionally. However, rare events can scale at higher rates, and localized heavy short-duration (hourly and sub-hourly) intensities can respond more strongly (e.g. 2 × CC instead of CC). Day-to-day scaling of short-duration intensities supports a higher scaling, with mechanisms proposed for this related to local-scale dynamics of convective storms, but its relevance to climate change is not clear. Uncertainty in changes to precipitation extremes remains and is influenced by many factors, including large-scale circulation, convective storm dynamics andstratification. Despite this, recent research has increased confidence in both the detectability and understanding of changes in various aspects of intense short-duration rainfall. To make further progress, the international coordination of datasets, model experiments and evaluations will be required, with consistent and standardized comparison methods and metrics, and recommendations are made for these frameworks. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.


Sign in / Sign up

Export Citation Format

Share Document