Advanced Numerical Methods for Complex Environmental Models: Needs and Availability

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High air pollution levels pose a significant threat to plants, animals and human beings. Efforts by researchers are directed towards keeping air pollution levels below well defined ‘critical‘ ...
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Part C: Uncertainty Analysis of the Regional Climate Model PRECIS

Pp. 394-415 (22)

Ildikó Pieczka, Rita Pongrácz and Judit Bartholy

Abstract

In this chapter, we study the effect of initial and lateral boundary conditions (IC&LBC) on regional climate change simulations. To achieve this, different sets of IC&LBC were used: data from the ERA40 reanalysis, and global climate model HadCM3 (versions HadAM3P and HadCM3Q0) for the reference period 1961–1990, and for the future. Emission scenarios A2 and B2 were considered for 2071–2100, and A1B for 1961–2100. In case of temperature a clear connection can be found between regional climate change and the applied emission scenarios: the higher the estimated CO2 concentration level in the scenario, the larger the projected seasonal mean warming rate. Significant warming is projected at 0.05 level for any of the A2, A1B, and B2 scenarios; the largest warming is estimated in summer. Not only the mean is likely to change, but also the distribution of daily mean temperature. Projections for precipitation involve much more uncertainty than for temperature and do not depend linearly on the estimated CO2 change. By the end of the century the annual precipitation in the Carpathian Basin is likely to decrease, and the annual distribution of monthly mean precipitation is expected to change. Significant drying is projected in the region in summer, while in winter the precipitation is estimated to increase.

Keywords:

A1B scenario, A2 scenario, B2 scenario, bias correction, Carpathian Basin, climate change, climate projection, consecutive dry days (CDD), distribution, E-OBS database, ERA-40 reanalysis, extreme climate index, HadCM global model, model PRECIS, precipitation, projected seasonal mean change, regional climate modeling, simple daily intensity index (SDII), temperature, validation.

Affiliation:

Department of Meteorology, Eötvös Loránd University, Budapest, Hungary.