Analysis of climate change influences on the wind characteristics in Hungary

Csilla Péliné Németh, J. Bartholy, R. Pongrácz, Kornélia Radics

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Due to intense human presence and various anthropogenic activities, global climate change has been detected. Increasing temperature values and an overall warming are projected, which will certainly affect the global circulation patterns and regional climatic conditions throughout Europe. As an indirect consequence, global warming may also alter the wind conditions in the Carpathian Basin. In order to provide reliable projections for the future, the first task is to analyze wind climatology of the recent past using various tools from mathematical statistics. In this paper, detailed analysis of observed wind fields, trends of different percentiles, return values, wind related climate indices, and their spatial distributions are discussed over Hungary using the homogenized Hungarian synoptic data sets and the homogenized and gridded CARPATCLIM database. Wind related climate indices are defined to evaluate the frequency occurrence and the trend of moderate and strong wind days at the stations in the last few decades. The annual daily maxima of wind speed and wind gust are determined on the basis of available time series fitted to the generalized extreme value distribution at every station and grid cell. 50-year and 100-year return values are estimated from these fitted distributions. In addition, simulated wind climate variability is evaluated for the future periods of 2021–2050 and 2071–2100 relative to the 1961–1990 reference period. Since projected wind speed is highly overestimated by the simulation of the regional climate model RegCM for the reference period (1961–1990), a bias correction is necessary to apply to the raw simulated wind data using CARPATCLIM as a reference database. The bias correction method is based on fitting the empirical cumulative density functions of simulated daily time series to the observations for each gridcell using monthly multiplicative correction factors.

Original languageEnglish
Pages (from-to)53-71
Number of pages19
JournalIdojaras
Volume120
Issue number1
Publication statusPublished - Jan 1 2016

    Fingerprint

Keywords

  • CARPATCLIM
  • Extremes
  • Homogeneity
  • Hungarian wind climate
  • RegCM climate model

ASJC Scopus subject areas

  • Atmospheric Science

Cite this