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Iberia01: A new gridded dataset of daily precipitation and temperatures over Iberia
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Abstract. The present work introduces a new observational gridded dataset produced using a dense network (thousands) of stations over the Iberian Peninsula (referred to as Iberia01, Gutiérrez et al. (2019), DOI: http://dx.doi.org/10.20350/digitalCSIC/8641), providing daily precipitation and temperatures for the period 1971–2015 at 0.1° regular (and 0.11° rotated CORDEX compliant) resolutions. A comparison with both the standard and ensemble version of the E-OBS v17 dataset (at 0.25° and 0.1° resolutions, respectively) is undertaken in order to assess observational uncertainty in this region. First, a standard comparison is performed for several weather indices, obtaining the differences between both datasets. Secondly, a new probabilistic intercomparison analysis is introduced, using the E-OBS ensemble (v17e) to characterize observational uncertainty and testing the hypothesis that Iberia01 is a realization of the ensemble (i.e. it falls within the observational uncertainty range provided by E-OBS). Finally, the effective resolution of the auxiliar very high resolution grid (0.01°) built to obtain the area-average representativity of the final dataset, and thus the possibility to increase the resolution of the dataset by means of pure interpolation methods, is analyzed considering an extreme event of convective precipitation affecting the Iberian Peninsula. As a result, we show that Iberia01 produces more realistic patterns than E-OBS v17 in the case of precipitation for all the indices considered, although both are comparable for temperatures. These differences are assessed using the probabilistic approach based on the E-OBS ensemble showing a quite homogeneous spatial pattern for precipitation (with less than 25 % significantly – at a 10 % level – different days between both datasets) and a very inhomogeneous pattern for temperatures, with either a small (in most of the regions) or large fraction of significantly different days. The great uncertainty of the precipitation given by E-OBS ensemble, in which the standard deviation of the ensemble has the same order than the mean value, increases the significance of the results obtained for this variable reflecting the differences between both datasets.
Title: Iberia01: A new gridded dataset of daily precipitation and
temperatures over Iberia
Description:
Abstract.
The present work introduces a new observational gridded dataset produced using a dense network (thousands) of stations over the Iberian Peninsula (referred to as Iberia01, Gutiérrez et al.
(2019), DOI: http://dx.
doi.
org/10.
20350/digitalCSIC/8641), providing daily precipitation and temperatures for the period 1971–2015 at 0.
1° regular (and 0.
11° rotated CORDEX compliant) resolutions.
A comparison with both the standard and ensemble version of the E-OBS v17 dataset (at 0.
25° and 0.
1° resolutions, respectively) is undertaken in order to assess observational uncertainty in this region.
First, a standard comparison is performed for several weather indices, obtaining the differences between both datasets.
Secondly, a new probabilistic intercomparison analysis is introduced, using the E-OBS ensemble (v17e) to characterize observational uncertainty and testing the hypothesis that Iberia01 is a realization of the ensemble (i.
e.
it falls within the observational uncertainty range provided by E-OBS).
Finally, the effective resolution of the auxiliar very high resolution grid (0.
01°) built to obtain the area-average representativity of the final dataset, and thus the possibility to increase the resolution of the dataset by means of pure interpolation methods, is analyzed considering an extreme event of convective precipitation affecting the Iberian Peninsula.
As a result, we show that Iberia01 produces more realistic patterns than E-OBS v17 in the case of precipitation for all the indices considered, although both are comparable for temperatures.
These differences are assessed using the probabilistic approach based on the E-OBS ensemble showing a quite homogeneous spatial pattern for precipitation (with less than 25 % significantly – at a 10 % level – different days between both datasets) and a very inhomogeneous pattern for temperatures, with either a small (in most of the regions) or large fraction of significantly different days.
The great uncertainty of the precipitation given by E-OBS ensemble, in which the standard deviation of the ensemble has the same order than the mean value, increases the significance of the results obtained for this variable reflecting the differences between both datasets.
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