Scholarly record

CONSISTENCY OF TEMPERATURE AND PRECIPITATION EXTREMES ACROSS INTERNATIONAL AND NATIONAL GRIDDED IN EXTRA-CARPATHIAN REGION OF ROMANIA

Constantin Nechita

Abstract

Nowadays, various climate data sources offer free-access information regarding interpolated climatological data, used in forest research studies (dendroecology and dendroclimatology). The most utilised are the international data grids, for reasons of length of time series and offboard coverage. Changes in the climate extremes from the last decades are frequently monitored using global climate gridded datasets (we used CRU-TS and E-OBS). Our study evaluates their accuracy relative to the national data grid (ROCADA) in the extra-Carpathian region of Romania. Analysis was performed on monthly (for all three datasets) and daily data (only for E-OBS and ROCADA), for both temporal and spatial pattern of mean temperature (Tmean), minimum temperature (Tmin), maximum temperature (Tmax) and mean precipitation (Pmean). Four ETCCDI climate change extreme indices were used to evaluate daily data (daily minimum temperature per day / year (TNij < 0°C), daily maximum temperature (TXij > 25°C), annual number of days with TX < 0°C, annual number of days with precipitation ? 10mm (R10mm). Analysis was performed for the common data period (1961-2013). Results showed that the values of annual extremes of daily data differ consistently in some years across the different databases. The interpretation of disagreement between data sets is partially related to different interpolation methods and number of meteorological data stations which are used by each grid. The most representative difference was found for the precipitation climate product. However, a reasonable agreement between datasets is preserved, and only aspects regarding underestimating/overestimating the extreme climate indices were noted. We consider this an essential investigation for a further potential application involving evaluation climate extreme through different proxy. Moreover, the different assets such as resolution in time and space or number of climate products included conferee a high importance of each datasets.

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