Irene Suomi
Finnish Meteorological Institute
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Publication
Featured researches published by Irene Suomi.
International Journal of Biometeorology | 2013
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
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
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
Irene Suomi; Sven-Erik Gryning; Rogier Ralph Floors; Timo Vihma; Carl Fortelius
Meteorological Applications | 2014
Andrea Vajda; Ari Venäläinen; Irene Suomi; Päivi Junila; Hanna M. Mäkelä
Quarterly Journal of the Royal Meteorological Society | 2013
Irene Suomi; Timo Vihma; Sven-Erik Gryning; Carl Fortelius
Quarterly Journal of the Royal Meteorological Society | 2016
Irene Suomi; Christof Lüpkes; Jörg Hartmann; Timo Vihma; Sven-Erik Gryning; Carl Fortelius
Quarterly Journal of the Royal Meteorological Society | 2017
Irene Suomi; Sven-Erik Gryning; Ewan J. O'Connor; Timo Vihma
Atmosphere | 2018
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
Sven-Erik Gryning; Torben Mikkelsen; Christophe Baehr; Alain Dabas; Paula Gómez; Ewan J. O'Connor; Lucie Rottner; Mikael Sjöholm; Irene Suomi; Nikola Vasiljevic