Literature DB >> 22367169

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 Schreier1, Irene Suomi, Peter Bröde, Herbert Formayer, Harald E Rieder, Imram Nadeem, Gerd Jendritzky, Ekaterina Batchvarova, Philipp Weihs.   

Abstract

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.

Mesh:

Year:  2012        PMID: 22367169     DOI: 10.1007/s00484-012-0525-y

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  8 in total

1.  Global sulfur emissions from 1850 to 2000.

Authors:  David I Stern
Journal:  Chemosphere       Date:  2005-01       Impact factor: 7.086

2.  Deriving the operational procedure for the Universal Thermal Climate Index (UTCI).

Authors:  Peter Bröde; Dusan Fiala; Krzysztof Błażejczyk; Ingvar Holmér; Gerd Jendritzky; Bernhard Kampmann; Birger Tinz; George Havenith
Journal:  Int J Biometeorol       Date:  2011-05-31       Impact factor: 3.787

3.  Physiological responses to temperature and humidity compared to the assessment by UTCI, WGBT and PHS.

Authors:  Bernhard Kampmann; Peter Bröde; Dusan Fiala
Journal:  Int J Biometeorol       Date:  2011-02-20       Impact factor: 3.787

4.  UTCI-Fiala multi-node model of human heat transfer and temperature regulation.

Authors:  Dusan Fiala; George Havenith; Peter Bröde; Bernhard Kampmann; Gerd Jendritzky
Journal:  Int J Biometeorol       Date:  2011-04-19       Impact factor: 3.787

5.  The uncertainty of UTCI due to uncertainties in the determination of radiation fluxes derived from measured and observed meteorological data.

Authors:  Philipp Weihs; Henning Staiger; Birger Tinz; Ekaterina Batchvarova; Harald Rieder; Laurent Vuilleumier; Marion Maturilli; Gerd Jendritzky
Journal:  Int J Biometeorol       Date:  2011-02-23       Impact factor: 3.787

6.  Validation of the Fiala multi-node thermophysiological model for UTCI application.

Authors:  Agnes Psikuta; Dusan Fiala; Gudrun Laschewski; Gerd Jendritzky; Mark Richards; Krzysztof Błażejczyk; Igor Mekjavič; Hannu Rintamäki; Richard de Dear; George Havenith
Journal:  Int J Biometeorol       Date:  2011-06-08       Impact factor: 3.787

7.  Predicting urban outdoor thermal comfort by the Universal Thermal Climate Index UTCI--a case study in Southern Brazil.

Authors:  Peter Bröde; Eduardo L Krüger; Francine A Rossi; Dusan Fiala
Journal:  Int J Biometeorol       Date:  2011-05-22       Impact factor: 3.787

8.  Comparison of UTCI to selected thermal indices.

Authors:  Krzysztof Blazejczyk; Yoram Epstein; Gerd Jendritzky; Henning Staiger; Birger Tinz
Journal:  Int J Biometeorol       Date:  2011-05-26       Impact factor: 3.787

  8 in total
  3 in total

1.  Human cold stress of strong local-wind "Hijikawa-arashi" in Japan, based on the UTCI index and thermo-physiological responses.

Authors:  Yukitaka Ohashi; Takumi Katsuta; Haruka Tani; Taiki Okabayashi; Satoshi Miyahara; Ryoji Miyashita
Journal:  Int J Biometeorol       Date:  2018-03-30       Impact factor: 3.787

Review 2.  Occupational heat stress assessment and protective strategies in the context of climate change.

Authors:  Chuansi Gao; Kalev Kuklane; Per-Olof Östergren; Tord Kjellstrom
Journal:  Int J Biometeorol       Date:  2017-04-25       Impact factor: 3.787

Review 3.  Is There a Need to Integrate Human Thermal Models with Weather Forecasts to Predict Thermal Stress?

Authors:  Jakob Petersson; Kalev Kuklane; Chuansi Gao
Journal:  Int J Environ Res Public Health       Date:  2019-11-19       Impact factor: 3.390

  3 in total

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