scholarly journals The MISTRAL Project provides a new tool for Flash Flood Forecasting in Italy 

2021 ◽  
Author(s):  
Estíbaliz Gascón ◽  
Andrea Montani ◽  
Tim Hewson
Keyword(s):  
Heavy Rainfall ◽  
Positive Impact ◽  
Flash Flood ◽  
Flash Floods ◽  
Processing Technique ◽  
Added Value ◽  
Limited Area ◽  
The European Union ◽  
Post Processing ◽  
The World

<p>Localized heavy rainfall, which can be associated with flash floods, is difficult to predict accurately: both the predicted location and the intensity can exhibit large errors. Moreover, weather forecasts should be provided for points and not for the large regions represented by global model grid boxes. This mismatch can in principle be addressed using high-resolution limited-area models, or by applying some post-processing to global forecast models, as used in “ecPoint-rainfall”, a new ECMWF probabilistic post-processing technique to improve precipitation forecasts. One novel premise of ecPoint, which has a major positive impact on the calibration, is that the forecast-versus-point-observation relationship depends on “gridbox weather types” that could potentially occur in many parts of the world.</p><p>The MISTRAL (Meteo Italian SupercompuTing PoRtAL) project, funded under the Connecting Europe Facility (CEF) – Telecommunication Sector Programme of the European Union came to its end in January 2021. The main project goal was to facilitate and foster the re-use of datasets by weather-dependent communities, to provide added value services using HPC resources. ECMWF participated in the project with the goal of improving probabilistic 6-h rainfall forecast products, to improve the prediction of flash floods in Italy and nearby Mediterranean regions. One of the objectives was to exploit the CINECA supercomputer facilities in Bologna to extract maximum benefit from ecPoint-Rainfall and from a 2.2km resolution COSMO limited area ensemble. To address that, we applied a new and innovative scale-selective neighbourhood post-processing technique to the COSMOS output, which, on the one hand, identifies and preserves the most reliable heavy rainfall signals and, on the other, spreads out those signals which are less consistently handled. Then, it is blended with a new 6h ecPoint-Rainfall product in order to leverage the most skilful aspects of the two systems. The 6-h ecPoint Rainfall forecasts were also developed during the project, building on the pre-existing ecPoint-Rainfall 12h product (already delivered to ECMWF customers in real-time). The final blended product includes, for lead times of 1-10 days, 6-h accumulated rainfall for each COSMO gridbox in percentiles (1, 2,..99) and probabilities of exceeding certain thresholds.</p><p>The main objective of this work was to improve forecasts and support weather-alert decisions for flash flood prediction. As a legacy of the project, we are now providing forecast data for Italy and nearby regions with a higher level of quality and resolution than has hitherto been possible,  and we are also delivering a robust gateway to products for the European community within the MISTRAL portal (https://meteohub.hpc.cineca.it/app/maps/flashflood). The principles could also be usefully applied in other parts of Europe, or indeed the world, where limited area ensembles are running operationally.</p><p>In this presentation, we will introduce the methodologies, the verification results and will illustrate with forecast examples.</p>

scholarly journals Improvement of Heavy Rainfall Simulated with SST Adjustment Associated with Mesoscale Convective Complexes Related to Severe Flash Flood in Luwu, Sulawesi, Indonesia

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1445
Author(s):  
Erma Yulihastin ◽  
Danang Eko Nuryanto ◽  
Trismidianto ◽  
Robi Muharsyah
Keyword(s):  
Heavy Rainfall ◽  
Flash Flood ◽  
Wrf Model ◽  
Flash Floods ◽  
Heavy Rainfall Event ◽  
Limited Area ◽  
Pressure System ◽  
The North ◽  
Mesoscale Convective ◽  
Persistent Heavy Rainfall

Flash flooding is an important issue as it has a devastating impact over a short time and in a limited area. However, predicting flash floods is challenging because they are connected to convection systems that rapidly evolve and require a high-resolution forecasting system. In addition, modeling a case study of a mesoscale convective complex (MCC) is the key to improving our understanding of the heavy rainfall systems that trigger flash floods. In this study, we aim at improving modeling skills to simulate a heavy rainfall system related to flash-flood-producing MCCs. We simulated a heavy rainfall event related to a severe flash flood in Luwu, Sulawesi, Indonesia, on 13 July 2020. This flood was preceded by persistent heavy rainfall from 11 to 13 July 2020. In this case, we investigated the role of sea surface temperature (SST) in producing the persistent heavy rainfall over the region. Therefore, we explore the physical and dynamic processes that caused the heavy rainfall using a convection-permitting model with 1 km resolution and an experiment comparing the situation with and without updated SST. The results show that the heavy rainfall was modulated by the development of a pair of MCCs during the night. The pair of MCCs was triggered by a meso-low-pressure system with an anti-cyclonic circulation anomaly over the Makassar Strait and was maintained by the warm front passing between the sea and land over central Sulawesi. This front was characterized by moist–warm and cold–dry low-level air, which may have helped extend the lifetime of the MCCs. The north-westward propagation of the MCCs was due to the interaction between predominantly a south-easterly monsoon and SST anomalies. This study suggested that the long-lived (>10 h) MCCs (>80,000 km2 cloud shield) and persistent precipitation are reproduced well in the updated SST scenario in the WRF model. This relatively simple technique in the running model provides a new strategy for improving flash flood forecasting by better predicting rainfall as an input in the hydrological model. Our findings also indicated a long-lived MCC maintained by back-building mechanisms from night to morning inland as an exceptional MCC, which does not correspond to a previous study.

scholarly journals Impacts of Assimilating ATMS Radiances on Heavy Rainfall Forecast in RMAPS-ST

2020 ◽  
Vol 12 (7) ◽  
pp. 1147
Author(s):  
Yanhui Xie ◽  
Min Chen ◽  
Jiancheng Shi ◽  
Shuiyong Fan ◽  
Jing He ◽  
...  
Keyword(s):  
Heavy Rainfall ◽  
Initial Conditions ◽  
Positive Impact ◽  
Weather Prediction ◽  
Advanced Technology ◽  
Added Value ◽  
Rainfall Forecast ◽  
Hourly Rainfall ◽  
Radiance Data ◽  
The Impact

The Advanced Technology Microwave Sounder (ATMS) mounted on the Suomi National Polar-Orbiting Partnership (NPP) satellite can provide both temperature and humidity information for a weather prediction model. Based on the rapid-refresh multi-scale analysis and prediction system—short-term (RMAPS-ST), we investigated the impact of ATMS radiance data assimilation on strong rainfall forecasts. Two groups of experiments were conducted to forecast heavy precipitation over North China between 18 July and 20 July 2016. The initial conditions and forecast results from the two groups of experiments have been compared and evaluated against observations. In comparison with the first group of experiments that only assimilated conventional observations, some added value can be obtained for the initial conditions of temperature, humidity, and wind fields after assimilating ATMS radiance observations in the system. For the forecast results with the assimilation of ATMS radiances, the score skills of quantitative forecast rainfall have been improved when verified against the observed rainfall. The Heidke skill score (HSS) skills of 6-h accumulated precipitation in the 24-h forecasts were overall increased, more prominently so for the heavy rainfall above 25 mm in the 0–6 h of forecasts. Assimilating ATMS radiance data reduced the false alarm ratio of quantitative precipitation forecasting in the 0–12 h of the forecast range and thus improved the threat scores for the heavy rainfall storm. Furthermore, the assimilation of ATMS radiances improved the spatial distribution of hourly rainfall forecast with observations compared with that of the first group of experiments, and the mean absolute error was reduced in the 10-h lead time of forecasts. The inclusion of ATMS radiances provided more information for the vertical structure of features in the temperature and moisture profiles, which had an indirect positive impact on the forecasts of the heavy rainfall in the RMAPS-ST system. However, the deviation in the location of the heavy rainfall center requires future work.

Innovation – Populist Slogan, Why?

2014 ◽  
Vol 33 (3) ◽  
pp. 25-34
Author(s):  
Peter Ponický ◽  
Vítězslav Zamarský
Keyword(s):  
Economic Growth ◽  
Life Experiences ◽  
Poor Quality ◽  
Added Value ◽  
The European Union ◽  
Asian Countries ◽  
Positive Effects ◽  
The World ◽  
Leading Position ◽  
Catch Up

Nowadays, innovation is perhaps the most widely spoken global keyword in the field of economy. Everyone talks about innovation and the European Union already for more than a decade, has wanted through innovation to catch up with and take the leading position in the world. However, what is the reality? Europe still has difficulties with the pace of economic growth, which according to many is joined combined with innovation and knowledge. Asian countries often set a price of an innovated product of poor quality and with no added value that includes huge cost of efficient marketing and aggressive advertising. Therefore, is innovation everything what is called this way? Though the world controls the speed and acceleration of changes, it does not mean necessarily an advantage or positive effects. And evolution of a star in a supernova and then a black hole is in the final stages accelerated in an unusual way. The inspiration for our article was slanted to cheap using the word “innovation”, just because it is a European priority. We just drew from his knowledge and life experiences.

scholarly journals A low-cost post-processing technique improves weather forecasts around the world

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Timothy David Hewson ◽  
Fatima Maria Pillosu
Keyword(s):  
Flash Flood ◽  
Low Cost ◽  
Extreme Rainfall ◽  
Processing Technique ◽  
Processing Method ◽  
Weather Type ◽  
Post Processing ◽  
Ensemble Forecasts ◽  
Weather Forecasts ◽  
Strong Focus

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.

scholarly journals Developing a Knowledge-Based Economy as a Factor to Raise The Competitiveness of The Serbian Economy

2015 ◽  
Vol 53 (2) ◽  
pp. 185-210
Author(s):  
Milorad Filipović ◽  
Miroljub Nikolić ◽  
Vojislav Ilić
Keyword(s):  
European Union ◽  
International Competitiveness ◽  
Added Value ◽  
High Tech ◽  
Domestic Economy ◽  
The European Union ◽  
Knowledge Based ◽  
Knowledge Based Economy ◽  
The World

Abstract The most developed and most competitive countries today (including the leading countries of the European Union) are so-called “knowledge-based economies”, where knowledge, information and highly sophisticated skills play an important role in the development of the business and public sector. Knowledge and technology are becoming ever more complex, participation in knowledge-based economic activities is significantly increased (high-tech production and knowledge-based services), and connecting companies in these areas with private and public institutions facilitates development and the successful application of new innovations, thus raising the level of competitiveness of companies, industries and the country as a whole. In the last few years, rapid growth in the international trade of high-tech products and knowledge-based services has significantly changed a large number of countries’ international competitiveness. These trends show that creating, implementing and commercializing new technology and knowledge facilitates the development of high-tech products and knowledge-based services, which have become an important source of increasing productivity and manufacturing and export competitiveness. Thus high-tech sectors have become an important source of high added value and well-paid jobs, plus sustainable economic growth and global competitiveness. According to the World Economic Forum’s competitiveness rankings, Serbia is 95th out of 144 countries and is in the group of the 33 countries whose competitiveness is efficiency-driven. The achieved level of competitiveness of the domestic economy and the achieved level of economic development (Serbia is 75th in the world for GDP per capita in dollars) points to low productivity in the use of available (human, capital, financial, etc.) resources accompanied by high current spending, which is not a situation that is sustainable in the long-term. The research starts from the assumption that the development of high-tech- and knowledge-based activities plays a significant role in strengthening the competitiveness of the economy. A comparative analysis examines the link between the lagging Serbian economy in terms of competitiveness and the slower development of a knowledge-based economy, compared to the most highly developed European countries and selected countries in the region. A structural analysis and comparison of the most important business indicators (employment, productivity and added value) of high technology and knowledge-based companies shows the development and basic characteristics of the knowledge-based economy in Serbia and the macro-competitive position of Serbia compared to the leading and neighboring European Union countries. The paper also identifies the most important factors of developing a knowledge-based economy in Serbia, which needs to be improved to facilitate significant development of high-tech and knowledge-based activities as the basis for the future competitiveness of the domestic economy. The final objective of the paper is to point out the need for more substantial and faster development of a knowledge-based economy as a prerequisite for achieving long-term international competitiveness and sustainable development of the Serbian economy.

Real-Time Flash Flood Forecasting

2018 ◽  
Author(s):  
Jonathan J. Gourley ◽  
Robert A. Clark
Keyword(s):  
United States ◽  
Real Time ◽  
Flash Flood ◽  
Weather Prediction ◽  
The United States ◽  
Flood Forecasting ◽  
Flash Floods ◽  
Hydrologic Model ◽  
The World ◽  
Flash Flood Forecasting

Flash floods are one of the world’s deadliest and costliest weather-related natural hazards. In the United States alone, they account for an average of approximately 80 fatalities per year. Damages to crops and infrastructure are particularly costly. In 2015 alone, flash floods accounted for over $2 billion of losses; this was nearly half the total cost of damage caused by all weather hazards. Flash floods can be either pluvial or fluvial, but their occurrence is primarily driven by intense rainfall. Predicting the specific locations and times of flash floods requires a multidisciplinary approach because the severity of the impact depends on meteorological factors, surface hydrologic preconditions and controls, spatial patterns of sensitive infrastructure, and the dynamics describing how society is using or occupying the infrastructure. Real-time flash flood forecasting systems rely on the observations and/or forecasts of rainfall, preexisting soil moisture and river-stage states, and geomorphological characteristics of the land surface and subsurface. The design of the forecast systems varies across the world in terms of their forcing, methodology, forecast horizon, and temporal and spatial scales. Their diversity can be attributed at least partially to the availability of observing systems and numerical weather prediction models that provide information at relevant scales regarding the location, timing, and severity of impending flash floods. In the United States, the National Weather Service (NWS) has relied upon the flash flood guidance (FFG) approach for decades. This is an inverse method in which a hydrologic model is run under differing rainfall scenarios until flooding conditions are reached. Forecasters then monitor observations and forecasts of rainfall and issue warnings to the public and local emergency management communities when the rainfall amounts approach or exceed FFG thresholds. This technique has been expanded to other countries throughout the world. Another approach, used in Europe, relies on model forecasts of heavy rainfall, where anomalous conditions are identified through comparison of the forecast cumulative rainfall (in space and time) with a 20-year archive of prior forecasts. Finally, explicit forecasts of flash flooding are generated in real time across the United States based on estimates of rainfall from a national network of weather radar systems.

scholarly journals The Role of Local Orography on the Development of a Severe Rainfall Event over Western Peninsular Malaysia: A Case Study

2020 ◽  
Vol 148 (5) ◽  
pp. 2191-2209
Author(s):  
Mohd Fadzil Firdzaus Mohd Nor ◽  
Christopher E. Holloway ◽  
Peter M. Inness
Keyword(s):  
Heavy Rainfall ◽  
Flash Floods ◽  
Peninsular Malaysia ◽  
Rainfall Event ◽  
Heavy Rainfall Event ◽  
Limited Area ◽  
Rainfall Events ◽  
Low Level ◽  
Sumatra Island ◽  
Strait Of Malacca

Abstract Severe rainfall events are common in western Peninsular Malaysia. They are usually short and intense, and occasionally cause flash floods and landslides. Forecasting these local events is difficult and understanding the mechanisms of the rainfall events is vital for the advancement of tropical weather forecasting. This study investigates the mechanisms responsible for a local heavy rainfall event on 2 May 2012 that caused flash floods and landslides using both observations and simulations with the limited-area high-resolution Met Office Unified Model (MetUM). Results suggest that previous day rainfalls over Peninsular Malaysia and Sumatra Island influenced the development of overnight rainfall over the Strait of Malacca by low-level flow convergence. Afternoon convection over the Titiwangsa Mountains over Peninsular Malaysia then induced rainfall development and the combination of these two events influenced the development of severe convective storm over western Peninsular Malaysia. Additionally, anomalously strong low-level northwesterlies also contributed to this event. Sensitivity studies were carried out to investigate the influence of the local orography on this event. Flattened Peninsular Malaysia orography causes a lack of rainfall over the central part of Peninsular Malaysia and Sumatra Island and produces a weaker overnight rainfall over the Strait of Malacca. By removing Sumatra Island in the final experiment, the western and inland parts of Peninsular Malaysia would receive more rainfall, as this region is more influenced by the westerly wind from the Indian Ocean. These results suggest the importance of the interaction between landmasses, orography, low-level flow, and the diurnal cycle on the development of heavy rainfall events.

scholarly journals The Role of Multinational Corporations in the European Union

2020 ◽  
Vol 11 (4) ◽  
pp. 109-126
Author(s):  
Raluca Pârjoleanu ◽  
Keyword(s):  
Multinational Corporations ◽  
Global Economy ◽  
Positive Impact ◽  
Local Development ◽  
Decisive Role ◽  
Local Economy ◽  
The European Union ◽  
Production Lines ◽  
Frontline Workers ◽  
The World

Organizations such as multinational corporations are the most important form of business globally. The defining role on the world economy could be seen at the onset of the financial crisis of 2008, but also in the recent events related to the Covid-19 pandemic, when corporations transformed their production lines to respond to the need for protective equipment for the frontline workers in the health system, but also for the broader population. Through Foreign Direct Investment (FDI), multinational corporations make a positive impact on economies around the world. In addition to contributing to the local development of areas where they setup subsidiaries, multinational corporations are a form of integration of a local economy into the global economy. In the Romanian economy, multinational corporations play a decisive role, representing the companies with the highest turnover, but also the most desired employers for those looking for a job.

Spatiotemporal Variation of Flash Floods in the Hengduan Mountains Region Affected by Rainfall Properties and Land-use

2021 ◽  
Author(s):  
Xiaoyun Sun ◽  
Guotao Zhang ◽  
Jiao Wang ◽  
Chaoyue Li ◽  
Shengnan Wu ◽  
...  
Keyword(s):  
Land Use ◽  
High Risk ◽  
Heavy Rainfall ◽  
Flash Flood ◽  
Linear Trend ◽  
Flash Floods ◽  
Spatiotemporal Variation ◽  
Hengduan Mountains ◽  
Flood Events ◽  
Accurate Identification

Abstract Understanding the spatiotemporal characteristic of flash floods is significant for the reasonable and accurate identification of high-risk regions of disasters as well as future prediction of hydrological regimes. Therefore, this study collected time-series datasets (1979-2015) of historical flash flood events, rainfall, and land-use in the Hengduan Mountains region, China to characterize the spatiotemporal variation in flash floods affected by the change in rainfall and land-use. Using linear trend, a significant increase with 12 times/10a for flash flood events was found while 82% of events occurred in the flood season (June–August). They were closely related to the increase in frequency (3.5 d/10a) and magnitude (215.55 mm/10a) of heavy rainfall as well as the amplified artificial (999 km2). Affected by heavy rainfall due to climate change and human activity, significant periodic variations on the scales of 3-7a, 8-15a, and 21-31a were derived based on the Morlet wavelet analysis. Meanwhile, utilizing the standard elliptical difference, we identified the moving route of the gravity center of flash floods, with the direction from northwest to southeast. More recorded disasters generally were found in the south of the Hengduan Mountain region, where was mainly controlled by frequent rainstorms and the formation of more cropland and artificial with higher runoff potential. These findings can be an appropriate supplement for lack of understanding of the spatiotemporal dynamics of flash floods in the Hengduan Mountains region and could provide policymakers with evidence to identify high-risk areas which is difficult to cope with in the mountainous watershed.

scholarly journals Toward Real-Time Daily PQPF by an Analog Sorting Approach: Application to Flash-Flood Catchments

2012 ◽  
Vol 51 (3) ◽  
pp. 505-520 ◽  
Author(s):  
Renaud Marty ◽  
Isabella Zin ◽  
Charles Obled ◽  
Guillaume Bontron ◽  
Abdelatif Djerboua
Keyword(s):  
Heavy Rainfall ◽  
Prediction Models ◽  
Flash Flood ◽  
Weather Prediction ◽  
Ensemble Prediction ◽  
Limited Area ◽  
Ensemble Prediction System ◽  
Rainfall Events ◽  
Sorting Technique ◽  
Heavy Rainfall Events

AbstractHeavy-rainfall events are common in southern France and frequently result in devastating flash floods. Thus, an appropriate anticipation of future rainfall is required: for early flood warning, at least 12–24 h in advance; for alerting operational services, at least 2–3 days ahead. Precipitation forecasts are generally provided by numerical weather prediction models (NWP), and their associated uncertainty is generally estimated through an ensemble approach. Precipitation forecasts also have to be adapted to hydrological scales. This study describes an alternative approach to commonly used limited-area models. Probabilistic quantitative precipitation forecasts (PQPFs) are provided through an analog sorting technique, which directly links synoptic-scale NWP output to catchment-scale rainfall probability distributions. One issue concerns the latest developments in implementing a daily version of this technique into operational conditions. It is shown that the obtained PQPFs depend on the meteorological forecasts used for selecting analogous days and that the method has to be reoptimized when changing the source of synoptic forecasts, because of the NWP output uncertainties. Second, an evaluation of the PQPFs demonstrates that the analog technique performs well for early warning of heavy-rainfall events and provides useful information as potential input to a hydrological ensemble prediction system. It is shown that the obtained daily rainfall distributions can be unreliable. A statistical correction of the observed bias is proposed as a function of the no-rain frequency values, leading to a significant improvement in PQPF sharpness.

Sign in / Sign up

Export Citation Format

Share Document