Suchergebnisse

The expediency of using Weather Research and Forecasting (WRF) numerical weather forecast model as a source of meteorological data during modeling of radioactive substances transfer in the atmosphere is considered, WRF technical details are briefly described. As the reference emergency scenario, the scenario of the maximum design accident hypothetically occurring at Belarusian Nuclear Power Plant (BelNPP) 12 UTC 21.03.2021 was chosen. Four numerical experiments with Global Forecast System (GFS) and WRF meteorological data and RIMPUFF and LASAT atmospheric diffusion models were performed in JRODOS Decision Support Systems (DSS). For each experiment, maps of underlying surface potential radioactive contamination of I131 were created. The potential contamination of the underlying surface I131 from 5 to 100 km from the BelNPP was assessed. The dependency graph of the maximum underlying surface contamination with I131 on the distance from the BelNPP was plotted based on the experiments results. The obtained results indicate the prospects of using the WRF meteorological model in the DSS at various stages of the emergency situations development at the BelNPP.

Ponencia presentada en: VIII Congreso de la Asociación Española de Climatología celebrado en Salamanca entre el 25 y el 28 de septiembre de 2012. ; Recently, the demand of gridded wind datasets over sea areas has increased due to the ongoing development of offshore wind farms. Currently available reanalysis datasets do not have enough resolution to deal with complex coastlines and coastal topography, and these do interact with the winds and meteorological systems well into the open sea. Here we present the main characteristics of a high resolution wind climatology that has been produced using the Weather Research and Forecasting model to downscale the ERA-INTERIM reanalysis. The simulations were carried out in a domain covering the Mediterranean basin and most of Europe, and thus areas with different wind regimes. The model has been kept close to the driving reanalysis by restarting it daily, as this running mode provided better results than nudging techniques. Results show that WRF is able to produce realistic offshore wind climatologies, probabilistic wind distributions and annual cycle. It also reproduces well-known regional winds remarkably well. ; This paper is a contribution to the financed projects by the Spanish government CORWES (CGL2010-22158-C02-01), WRF4G (CGL2010-22158-C02-01), EXTREMBLES (CGL2010-21869), C3E (200800050084091), iMar21 (CTM201015009) and MARUCA (E17/08), and was partially funded by projects 'MAREN' (Atlantic Area Transnational Programme) and 'CoCoNet' (FP7-OCEAN-2011).

Hail is a significant convective hazard causing aviation delays and damage to property. However, accurately forecasting hail occurrence is problematic because convective hazards suffer from an additional penalty; a model must first generate convection at the correct time and location before the hazard can be correctly predicted. These errors in the timing and location of predicted convection, are also present in the forecasts of hail. Herein, we evaluate a hail classification scheme using object-based techniques from the Method for Object Based Diagnostic Evaluation (MODE), part of the Model Evaluations Tools (MET) software. These object-based techniques are designed to alleviate some of the aforementioned issues. Specifically, hail is added to an existing precipitation phase classification generated in a regional version of the Weather Research and Forecasting (WRF) model. The classification is based on graupel predicted as part of the Thompson microphysics scheme. Classified hail is examined on several military ranges across the United States and verified against the NEXRAD level 3 Hydrometeor classification. The ranges are located in diverse geographical regions with different storm modes and sizes to evaluate algorithm performance under a variety of conditions. This presentation will give results from some of these cases.

This study aims to compare the wind and concentration field generated by a coupling of WRF/CALMET model and CALMET/CALPUFF with no introduction of any gridded wind field. The domain was located at the city of Linhares, southeast region of Brazil, with a 15×15 grid cells and 1 km resolution. The chosen modelling period was April 1st, 2011, with the length of 90 h. The pollutants simulated by CALPUFF were NO2 and SO2. The final results of dispersion and concentration peak were compared against environmental legislation of 1 h average for NO2 and 24 h average for SO2. The first simulation, using WRF/CALMET model, shows plausible results. The second mode, CALMET/CALPUFF, generated a wind field with questionable results, which probably compromised the dispersion simulation. Both model results are within environmental legislation.

Abstract. An integrated modeling approach for forecasting flood events is presented in the current study. An advanced flood forecasting model, which is based on the coupling of hydrological and atmospheric components, was used for a twofold objective: first to investigate the potential of a coupled hydrometeorological model to be used for flood forecasting at two medium-size drainage basins in the area of Attica (Greece) and second to
investigate the influence of the use of the coupled hydrometeorological
model on the precipitation forecast skill. For this reason, we used
precipitation and hydrometric in situ data for six flood events at two
selected drainage regions of Attica. The simulations were carried out with
the Weather Research and Forecasting (WRF) model (WRF-only) and the
WRF-Hydro system in a fully coupled mode, under which surface, subsurface, and channel hydrological processes were parameterized at a fine-resolution
grid of 95 m approximately. Results showed that the coupled WRF-Hydro system was capable of producing the observed discharge during the flood episodes, after the adequate calibration method applied at the studied basins. This outcome provides confidence that the model configuration under the two-way atmospheric–hydrological coupling is robust and, thus, can be used for operational flood forecasting purposes in the area of Attica. In addition, the WRF-Hydro model showed a tendency to slightly improve the simulated precipitation in comparison to the precipitation produced by the atmospheric-only version of the model (WRF), demonstrating the capability of the coupled WRF-Hydro model to enhance the precipitation forecast skill for operational flood predictions.

Abstract. The e-Science environment developed in the framework of the EU-funded DRIHM project was used to demonstrate its ability to provide relevant, meaningful hydrometeorological forecasts. This was illustrated for the tragic case of 4 November 2011, when Genoa, Italy, was flooded as the result of heavy, convective precipitation that inundated the Bisagno catchment. The Meteorological Model Bridge (MMB), an innovative software component developed within the DRIHM project for the interoperability of meteorological and hydrological models, is a key component of the DRIHM e-Science environment. The MMB allowed three different rainfall-discharge models (DRiFt, RIBS and HBV) to be driven by four mesoscale limited-area atmospheric models (WRF-NMM, WRF-ARW, Meso-NH and AROME) and a downscaling algorithm (RainFARM) in a seamless fashion. In addition to this multi-model configuration, some of the models were run in probabilistic mode, thus giving a comprehensive account of modelling errors and a very large amount of likely hydrometeorological scenarios (> 1500). The multi-model approach proved to be necessary because, whilst various aspects of the event were successfully simulated by different models, none of the models reproduced all of these aspects correctly. It was shown that the resulting set of simulations helped identify key atmospheric processes responsible for the large rainfall accumulations over the Bisagno basin. The DRIHM e-Science environment facilitated an evaluation of the sensitivity to atmospheric and hydrological modelling errors. This showed that both had a significant impact on predicted discharges, the former being larger than the latter. Finally, the usefulness of the set of hydrometeorological simulations was assessed from a flash flood early-warning perspective.

Abstract. As an effective technique to improve the rainfall forecast, data assimilation plays an important role in meteorology and hydrology. The aim of this study is to explore the reasonable use of Doppler radar data assimilation to correct the initial and lateral boundary conditions of the numerical weather prediction (NWP) systems. The Weather Research and Forecasting (WRF) model is applied to simulate three typhoon storm events on the southeast coast of China. Radar data from a Doppler radar station in Changle, China, are assimilated with three-dimensional variational data assimilation (3-DVar) model. Nine assimilation modes are designed by three kinds of radar data and at three assimilation time intervals. The rainfall simulations in a medium-scale catchment, Meixi, are evaluated by three indices, including relative error (RE), critical success index (CSI), and root mean square error (RMSE). Assimilating radial velocity at a time interval of 1 h can significantly improve the rainfall simulations, and it outperforms the other modes for all the three storm events. Shortening the assimilation time interval can improve the rainfall simulations in most cases, while assimilating radar reflectivity always leads to worse simulations as the time interval shortens. The rainfall simulations can be improved by data assimilation as a whole, especially for the heavy rainfall with strong convection. The findings provide references for improving the typhoon rainfall forecasts at catchment scale and have great significance on typhoon rainstorm warning.

Abstract. Forecasting precipitation over the Mediterranean basin
is still a challenge because of the complex orographic region that
amplifies the need for local observation to correctly initialize the
forecast. In this context, data assimilation techniques play a key role
in improving the initial conditions and consequently the timing and position
of the precipitation forecast. For the first time, the ability of a cycling
4D-Var to reproduce a heavy rain event in central Italy, as well as to
provide a comparison with the largely used cycling 3D-Var, is evaluated in
this study. The radar reflectivity measured by the Italian ground radar
network is assimilated in the Weather Research and Forecasting (WRF) model to simulate an event that occurred on 3 May 2018 in central Italy. In order to evaluate the impact of data
assimilation, several simulations are objectively compared by means of a
fraction skill score (FSS), which is calculated for several threshold
values, and a receiver operating characteristic (ROC) curve. The results
suggest that both assimilation methods in the cycling mode improve the 1-, 3- and
6-hourly quantitative precipitation estimation. More specifically, the
cycling 4D-Var with a warm start initialization shows the highest FSS values
in the first hours of the simulation both with light and heavy precipitation.
Finally, the ROC curve confirms the benefit of 4D-Var: the area under the
curve is 0.91 compared to 0.88 for the control experiment without data
assimilation.

AbstractIn this study, the identification of PM sources during smog episodes in Debrecen is presented. The smog episodes were characterized by the high concentration of PM10, and were linked to a thermal inversion period in November 2011 in Hungary, when an anticyclone occurred across Europe. The sources of PM2.5 and PMcoarse were identified by positive matrix factorization (PMF). Additionally, the source locations were explored by using the conditional probability function (CPF). A numerical weather prediction model (WRF) was also applied to evaluate the air pollution situation. In order to meet the goals of the study, the elemental composition with high (2-h) time resolution, the elemental size distribution, and the planetary boundary layer were examined in an urban background site of downtown Debrecen, Hungary. Our results highlight the importance of biomass burning (39%) and traffic (31%) as the major contributors to PM2.5. The main tracers of these sources (K, Cl, Pb, Zn) appeared mainly in droplet mode (0.5–1 μm). The major sources of PMcoarse fraction were soil (32%), and dust attributed to tramline construction (30%). The combination of PMF and CPF results revealed that the PM10 concentrations were affected by sources within the urban agglomeration of Debrecen (city centre and suburban areas) under the given meteorological conditions. This conclusion is further validated by the fact that the diurnal variation of the identified source contributions presented a distinct pattern that depended strongly on the daily activities of the city's residents (compared to the usually unstructured diurnals of transported sources).

Abstract. The changing climate and anthropogenic activities raise the
likelihood of damage due to compound flood hazards, triggered by the
combined occurrence of extreme precipitation and storm surge during high
tides and exacerbated by sea-level rise (SLR). Risk estimates associated
with these extreme event scenarios are expected to be significantly higher
than estimates derived from a standard evaluation of individual hazards. In
this study, we present case studies of compound flood hazards affecting
critical infrastructure (CI) in coastal Connecticut (USA). We based the
analysis on actual and synthetic (considering future climate conditions for
atmospheric forcing, sea-level rise, and forecasted hurricane tracks)
hurricane events, represented by heavy precipitation and surge combined with
tides and SLR conditions. We used the Hydrologic Engineering Center's River
Analysis System (HEC-RAS), a two-dimensional hydrodynamic model, to simulate
the combined coastal and riverine flooding of selected CI sites. We forced a
distributed hydrological model (CREST-SVAS) with weather analysis data from
the Weather Research and Forecasting (WRF) model for the synthetic events
and from the National Land Data Assimilation System (NLDAS) for the actual
events, to derive the upstream boundary condition (flood wave) of HEC-RAS.
We extracted coastal tide and surge time series for each event from the
National Oceanic and Atmospheric Administration (NOAA) to use as the
downstream boundary condition of HEC-RAS. The significant outcome of this
study represents the evaluation of changes in flood risk for the CI sites
for the various compound scenarios (under current and future climate
conditions). This approach offers an estimate of the potential impact of
compound hazards relative to the 100-year flood maps produced by the Federal
Emergency Management Agency (FEMA), which is vital to developing mitigation
strategies. In a broader sense, this study provides a framework for
assessing the risk factors of our modern infrastructure located in
vulnerable coastal areas throughout the world.

Abstract. This study focuses on a single Mediterranean hurricane (hereafter medicane), to investigate its response to global warming during the middle of the 21st century and assesses the effects of a warmer ocean and a warmer
atmosphere on its development. Our investigation uses the state-of-the-art
regional climate model WRF to produce the six-member, multi-physics ensembles. Results show that our model setup simulates a realistic cyclone track and the transition from an initial disturbance to a tropical-like cyclone with a deep warm core. However, the simulated transition occurs earlier than for the observed medicane. The response of the medicane to future climate change is investigated with a pseudo global warming (PGW) approach. This is the first application of the PGW framework to medicanes. The PGW approach adds a climate change delta (defined as difference between future and present climate) to WRF's boundary conditions which is obtained for all prognostic variables using the mean change in an ensemble of CMIP5 simulations. A PGW simulation where the climate change delta is added to all prognostic variables (PGWALL) shows that most of the medicane characteristics moderately intensify, e.g. surface wind speed, uptake of water vapour, and precipitation. However, the minimum sea level pressure (SLP) is almost identical to that under present climate conditions. Two additional PGW simulations were undertaken; One simulation adds the projected change in sea surface and skin temperature only (PGWSST) while the second simulation adds the PGW changes to only atmospheric variables (PGWATMS); i.e. we use present-day sea surface temperatures. These simulations show opposing responses of the medicane. In PGWSST, the medicane is more intense than
PGWALL as indicated by lower SLP values, the stronger surface wind, and the more intense evaporation and precipitation. In contrast, the
medicane in PGWATMS still transitions into a tropical-like cyclone with a deep warm core, but the PGWATMS medicane weakens considerably (SLP, surface wind, and rainfall decrease). This difference can be explained by an increase in water vapour driven by the warmer ocean surface (favourable for cumulus convection). The warmer and drier atmosphere in PGWATMS tends to inhibit condensation (unfavourable for cumulus convection). The warmer ocean and warmer atmosphere have counteracting effects which leads to only a modest enhancement of the medicane by global warming. The novel approach in this study provides new insights into the different roles of warming of the ocean and atmosphere in medicane development.