Seasonal predictability of the 2010 Russian heat wave

The atmospheric blocking over eastern Europe and western Russia that prevailed during July and August of 2010 led to the development of a devastating Russian heat wave. Therefore the question of whether the event was predictable or not is highly important. The principal aim of this study is to examine the predictability of this high-impact atmospheric event on a seasonal timescale. To this end, a set of dynamical seasonal simulations have been carried out using an atmospheric global circulation model (AGCM). The impact of various model initializations on the predictability of this large-scale event and its sensitivity to the initial conditions has been also investigated. The ensemble seasonal simulations are based on a modified version of the lagged-average forecast method using different lead-time initializations of the model. The results indicated that only a few individual members reproduced the main features of the blocking system 3 months ahead. Most members missed the phase space and the propagation of the system, setting limitations in the predictability of the event

A 2-year intercomparison of the WAM-Cycle4 and the WAVEWATCH-III wave models implemented within the Mediterranean Sea

In this work we present the implementation of a wave forecast/hindcast system for the Mediterranean Sea at a 1/10º horizontal resolution and we show a first assessment of its performance by inter-comparing model results to observational data time series at selected points for the period 2000-2001. The system which is part of the POSEIDON-II operational system includes the WAM – Cycle4 and the WAVEWATCH-III wave forecast models (implemented within the same region) one way coupled with the non-hydrostatic version of the ETA atmospheric model which provides at 3-hour intervals the necessary wind velocity fields to the wave models. The same system but based on the WAM-Cycle4 wave model, has been used in the past for the production of the Aegean Sea wind and wave Atlas. Overall, the inter-comparison shows that both wave models are rather skilful in predicting the integral wave parameters with significant wave height skill scores in the range 0.85-0.90 and mean period scores in the range 0.77-0.83. It is also evident that WAM model has a tendency to overestimate mean wave periods while the opposite is true for WAVEWATCH-III model. Differences between the two models simulated spectra exist along the main passage of cyclonic systems over the Mediterranean Sea while in the wind seas dominated areas of the basin (the Aegean Sea for example) the two models show almost the same behavior

Latest LAPS developments Assimilating remote sensing data and its impact on LAPS predictability

Presentación realizada en la 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019

Dynamic downscaling of the ERA-40 data using a mesoscale meteorological model

A sophisticated downscaling procedure that was applied to reproduce high resolution historical records of the atmospheric conditions across the Mediterranean region is presented in this paper. This was accomplished by the dynamical downscaling of the European Center for Medium-Range Forecasts ERA-40 reanalyses with the aid of the atmospheric model of the POSEIDON weather forecasting system. The full three dimensional atmospheric fields with 6 hours of temporal resolution and the surface meteorological parameters at hourly intervals were produced for a 10-year period (1995-2004). The meteorological variables are readily available at 10 km resolution and may constitute the atmospheric forcing to drive wave, ocean hydrodynamic and hydrological models, as well as the baseline data for environmental impact assessment studies. A brief overview of the procedure and a quantitative estimation of the benefit of the new dynamical downscaling dataset are presented

Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering

International audienceThis paper studies the application of Kalman filtering as a post-processing method in numerical predictions of wind speed. Two limited-area atmospheric models have been employed, with different options/capabilities of horizontal resolution, to provide wind speed forecasts. The application of Kalman filter to these data leads to the elimination of any possible systematic errors, even in the lower resolution cases, contributing further to the significant reduction of the required CPU time. The potential of this method in wind power applications is also exploited. In particular, in the case of wind power prediction, the results obtained showed a remarkable improvement in the model forecasting skill

Global forecasting of thermal health hazards: the skill of probabilistic predictions of the Universal Thermal Climate Index (UTCI)

Although over a hundred thermal indices can be used for assessing thermal health hazards, many ignore the human heat budget, physiology and clothing. The Universal Thermal Climate Index (UTCI) addresses these shortcomings by using an advanced thermo-physiological model. This paper assesses the potential of using the UTCI for forecasting thermal health hazards. Traditionally, such hazard forecasting has had two further limitations: it has been narrowly focused on a particular region or nation and has relied on the use of single ‘deterministic’ forecasts. Here, the UTCI is computed on a global scale,which is essential for international health-hazard warnings and disaster preparedness, and it is provided as a probabilistic forecast. It is shown that probabilistic UTCI forecasts are superior in skill to deterministic forecasts and that despite global variations, the UTCI forecast is skilful for lead times up to 10 days. The paper also demonstrates the utility of probabilistic UTCI forecasts on the example of the 2010 heat wave in Russia

The impact of atmosphere–ocean–wave coupling on the near-surface wind speed in forecasts of extratropical cyclones

Accurate modelling of air–sea surface exchanges is crucial for reliable extreme surface windspeed forecasts. While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between the atmosphere, ocean and wave model components. Here, we investigate the sensitivity of extreme surface wind speeds to air–sea exchanges at the kilometre scale using coupled and uncoupled configurations of the Met Office’s UK Regional Coupled Environmental Prediction system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 ms−1 over the UK. Compared with the atmosphere-only results, coupling to the ocean decreases the domain-average sea-surface temperature by up to 0.5 K. Inclusion of coupling to waves reduce the 98th percentile 10-m wind speed by up to 2 ms−1 as young, growing wind waves reduce the wind speed by increasing the sea-surface aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1 ms−1, due to enhanced boundary-layer turbulence which partially offsets air–sea momentum transfer. Using a new drag parametrization based on the Coupled Ocean–Atmosphere Response Experiment 4.0 parametrization, with a cap on the neutral drag coefficient and reduction for wind speeds exceeding 27 ms−1, the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind-speed skill as coupling to waves, with the advantage of saving the computational cost of the ocean and wave models

Model-derived seasonal amounts of dust deposited on Mediterranean Sea and Europe

The dust amounts deposited on the surface depends critically upon the seasonal varia- bility of the dust cycle in the atmosphere. Analyses of ground and satellite-based obser- vations can lead to useful results in relation to the seasonal variability of dust deposition. However, to gain a feeling of the magnitude and the geographical distribution of the dust deposition on ground surfaces and on coastal and open seas, the use of a credible numerical model is considered essential. In this study, using the SKIRON/Eta weather forecasting system, a database of seasonal amounts of dust deposited on Mediterranean Sea and Europe has been created. © 2003 Elsevier B.V. All rights reserved

Regional atmospheric response to tropical Pacific SST perturbations

An extended domain limited area model was implemented for seasonal-range simulations to assess the effect of tropical Pacific SST perturbations on weather patterns over Europe and Mediterranean. The experimental method consisted of Skiron/Eta model integrations with coarse and fine grid increment using artificially-modified as well as analysis SST forcing. The selected period was August-October 1997. Model simulations with coarse grid increment produced a weak signal in the precipitation pattern and the synoptic scale circulation over Europe, implying a damping of the North Atlantic atmospheric response to the tropical Pacific SST perturbation. Fine resolution experiments suggested an amplified dynamic response providing a direct link between tropical Pacific SST and North Atlantic synoptic circulation. The output signal is mainly attributed to the effective representation of the regional/ mesoscale atmospheric features due to the model implementation with a fine mesh grid. Copyright 2005 by the American Geophysical Union