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Dive into the research topics where Irene Suomi is active.

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Featured researches published by Irene Suomi.


International Journal of Biometeorology | 2013

The uncertainty of UTCI due to uncertainties in the determination of radiation fluxes derived from numerical weather prediction and regional climate model simulations

Stefan F. Schreier; Irene Suomi; Peter Bröde; Herbert Formayer; Harald E. Rieder; Imram Nadeem; Gerd Jendritzky; Ekaterina Batchvarova; Philipp Weihs

In this study we examine the determination accuracy of both the mean radiant temperature (Tmrt) and the Universal Thermal Climate Index (UTCI) within the scope of numerical weather prediction (NWP), and global (GCM) and regional (RCM) climate model simulations. First, Tmrt is determined and the so-called UTCI-Fiala model is then used for the calculation of UTCI. Taking into account the uncertainties of NWP model (among others the HIgh Resolution Limited Area Model HIRLAM) output (temperature, downwelling short-wave and long-wave radiation) stated in the literature, we simulate and discuss the uncertainties of Tmrt and UTCI at three stations in different climatic regions of Europe. The results show that highest negative (positive) differences to reference cases (under assumed clear-sky conditions) of up to −21°C (9°C) for Tmrt and up to −6°C (3.5°C) for UTCI occur in summer (winter) due to cloudiness. In a second step, the uncertainties of RCM simulations are analyzed: three RCMs, namely ALADIN (Aire Limitée Adaptation dynamique Développement InterNational), RegCM (REGional Climate Model) and REMO (REgional MOdel) are nested into GCMs and used for the prediction of temperature and radiation fluxes in order to estimate Tmrt and UTCI. The inter-comparison of RCM output for the three selected locations shows that biases between 0.0 and ±17.7°C (between 0.0 and ±13.3°C) for Tmrt (UTCI), and RMSE between ±0.5 and ±17.8°C (between ±0.8 and ±13.4°C) for Tmrt (UTCI) may be expected. In general the study shows that uncertainties of UTCI, due to uncertainties arising from calculations of radiation fluxes (based on NWP models) required for the prediction of Tmrt, are well below ±2°C for clear-sky cases. However, significant higher uncertainties in UTCI of up to ±6°C are found, especially when prediction of cloudiness is wrong.


Sensors | 2018

Wind Gust Measurement Techniques—From Traditional Anemometry to New Possibilities

Irene Suomi; Timo Vihma

Information on wind gusts is needed for assessment of wind-induced damage and risks to safety. The measurement of wind gust speed requires a high temporal resolution of the anemometer system, because the gust is defined as a short-duration (seconds) maximum of the fluctuating wind speed. Until the digitalization of wind measurements in the 1990s, the wind gust measurements suffered from limited recording and data processing resources. Therefore, the majority of continuous wind gust records date back at most only by 30 years. Although the response characteristics of anemometer systems are good enough today, the traditional measurement techniques at weather stations based on cup and sonic anemometers are limited to heights and regions where the supporting structures can reach. Therefore, existing measurements are mainly concentrated over densely-populated land areas, whereas from remote locations, such as the marine Arctic, wind gust information is available only from sparse coastal locations. Recent developments of wind gust measurement techniques based on turbulence measurements from research aircraft and from Doppler lidar can potentially provide new information from heights and locations unreachable by traditional measurement techniques. Moreover, fast-developing measurement methods based on Unmanned Aircraft Systems (UASs) may add to better coverage of wind gust measurements in the future. In this paper, we provide an overview of the history and the current status of anemometry from the perspective of wind gusts. Furthermore, a discussion on the potential future directions of wind gust measurement techniques is provided.


Wind Energy | 2013

Production of the Finnish Wind Atlas

Bengt Tammelin; Timo Vihma; Evgeny Atlaskin; Jake Badger; Carl Fortelius; Hilppa Gregow; Matti Horttanainen; Reijo Hyvönen; Juha Kilpinen; Jenni Latikka; Karoliina Ljungberg; Niels Gylling Mortensen; Sami Niemelä; Kimmo Ruosteenoja; Kirsti Salonen; Irene Suomi; Ari Venäläinen


Quarterly Journal of the Royal Meteorological Society | 2015

On the vertical structure of wind gusts

Irene Suomi; Sven-Erik Gryning; Rogier Ralph Floors; Timo Vihma; Carl Fortelius


Meteorological Applications | 2014

Assessment of forest fire danger in a boreal forest environment: description and evaluation of the operational system applied in Finland

Andrea Vajda; Ari Venäläinen; Irene Suomi; Päivi Junila; Hanna M. Mäkelä


Quarterly Journal of the Royal Meteorological Society | 2013

Wind‐gust parametrizations at heights relevant for wind energy: a study based on mast observations

Irene Suomi; Timo Vihma; Sven-Erik Gryning; Carl Fortelius


Quarterly Journal of the Royal Meteorological Society | 2016

Gust factor based on research aircraft measurements: A new methodology applied to the Arctic marine boundary layer: Gust Factors in the Marine Arctic

Irene Suomi; Christof Lüpkes; Jörg Hartmann; Timo Vihma; Sven-Erik Gryning; Carl Fortelius


Quarterly Journal of the Royal Meteorological Society | 2017

Methodology for obtaining wind gusts using Doppler lidar

Irene Suomi; Sven-Erik Gryning; Ewan J. O'Connor; Timo Vihma


Atmosphere | 2018

Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer (ISOBAR)—The Hailuoto 2017 Campaign

Stephan T. Kral; Joachim Reuder; Timo Vihma; Irene Suomi; Ewan O’Connor; Rostislav Kouznetsov; Burkhard Wrenger; Alexander Rautenberg; Gabin Urbancic; Marius Opsanger Jonassen; Line Båserud; Björn Maronga; Stephanie Mayer; Torge Lorenz; Albert A. M. Holtslag; G.J. Steeneveld; Andrew Seidl; Martin Müller; Christian Lindenberg; Carsten Langohr; Hendrik Voss; Jens Bange; Marie Hundhausen; Philipp Hilsheimer; Markus Schygulla


Renewable Energy Forecasting#R##N#From Models to Applications | 2017

Measurement methodologies for wind energy based on ground-level remote sensing

Sven-Erik Gryning; Torben Mikkelsen; Christophe Baehr; Alain Dabas; Paula Gómez; Ewan J. O'Connor; Lucie Rottner; Mikael Sjöholm; Irene Suomi; Nikola Vasiljevic

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Timo Vihma

Finnish Meteorological Institute

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Sven-Erik Gryning

Technical University of Denmark

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Carl Fortelius

Finnish Meteorological Institute

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Ewan J. O'Connor

Finnish Meteorological Institute

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Christof Lüpkes

Alfred Wegener Institute for Polar and Marine Research

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Jörg Hartmann

Alfred Wegener Institute for Polar and Marine Research

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Ari Venäläinen

Finnish Meteorological Institute

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Minttu Tuononen

Finnish Meteorological Institute

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