Abstract
Abstract. In this study we compare three gridded observed datasets of daily precipitation (EOBS, MAP and NWIOI) over the Great Alpine Region (GAR) and a subregion in northwest Italy (NWI) in order to better understand the past variability of daily climate extremes and to set up a basis for developing regional climate scenarios. The grids are first compared with respect to their temporal similarity by calculating the correlation and relative mean absolute error of the time series. They are then compared with respect to their spatial similarity to the climatology of the ETCCDI indices (characterizing total precipitation, dry and wet spells and extremes with short return periods). The results indicate first that most EOBS gridpoint series in northeastern Italy have to be shifted back by 1 day to have maximum overlap of the measurement period and, second, that both the temporal and spatial similarities of most indices are higher between the NWIOI and MAP than between MAP or the NWIOI and EOBS. These results suggest that, although there is generally good temporal agreement between the three datasets, EOBS should be treated with caution, especially for extreme indices over the GAR region, and it does not provide reliable climatology over the NWI region. The high agreement between MAP and NWIOI, on the other hand, builds confidence in using these datasets. Users should consider carefully the limitations of the gridded observations available: the uncertainties of the observed datasets cannot be neglected in the overall uncertainties cascade that characterizes climate change studies.
Highlights
These results have been confirmed by Flaounas et al (2012), who estimate the uncertainties of the EOBS dataset for temperature and precipitation over three domains covered by HyMeX (HYdrological cycle in the Mediterranean EXperiment, http://www.hymex.org/) stations: (i) Israel, (ii) coastal region of southern France, and (iii) northeastern Italy. Their analysis indicates that the EOBS uncertainties are rather important and cannot be neglected during development of the regional scenarios. We extend these studies, (i) analyzing the latest available version of EOBS (v. 7.0), (ii) testing the new NWIOI dataset and (iii) calculating, in addition to standard measures of temporal similarity, their spatial similarity of aggregated values of a subset of the standard “moderate” extreme precipitation indices defined by the World Meteorological Organization (WMO) CC1/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI; for more details see http://cccma.seos.uvic.ca/ETCCDI or WMO, 2009)
To compare the three datasets, we focus on the common reliable period, 1971–1990, and the daily outputs of the MAP and NWIOI are bilinearly interpolated from their original resolution to the grid defined by EOBS
For each year in the period 1971–1990, we calculated the cross correlation between each gridpoint time series of the MAP and EOBS dataset and plotted the lag where there was the maximum correlation between the time series
Summary
We consider three public high-resolution datasets of interpolated observations: (i) MAP (Frei and Schar, 1998), (ii) EOBS (Haylock et al, 2008), and (iii) NWIOI (Ronchi et al, 2008; AAVV, 2011). MAP was developed using a modified version of the SYMAP interpolation method of Shepard (1984), which consists in areal-averaged values weighing the bias-uncorrected, quality-controlled observations in a search radius around the gridpoint This dataset is considered reliable for reproducing the mesoscale patterns of the present alpine climatology, at least qualitatively (Frei and Schar, 1998). To compare the three datasets, we focus on the common reliable period, 1971–1990, and the daily outputs of the MAP and NWIOI are bilinearly interpolated (upscaled) from their original resolution to the grid defined by EOBS While this process may introduce a small additional uncertainty, we considered it negligible
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