TY - JOUR
T1 - Testing instrumental and downscaled reanalysis time series for temperature trends in NE of Spain in the last century
AU - Turco, M.
AU - Marcos, R.
AU - Quintana-Seguí, P.
AU - Llasat, M. C.
N1 - Funding Information:
Acknowledgments This work was supported by esTcena project (Exp. 200800050084078), a strategic action from Plan Nacional de I?D?i 2008–2011 funded by the Spanish Ministry of Medio Ambi-ente y Medio Rural y Marino. We are most grateful to AEMET, the Ebre Observatory and the Reial Academia de Ciències i Arts de Barcelona for the data and metadata support. Special thanks to
Publisher Copyright:
© 2012, Springer-Verlag Berlin Heidelberg.
PY - 2014/8/1
Y1 - 2014/8/1
N2 - In the context of climatic temperature studies, more often than not a time series is affected by artificial inhomogeneities. To overcome such limitation, we propose a new simple methodology in which promising results point not only toward the detection of unknown inhomogeneous periods but also toward the possibility of reconstructing the uncertain portion of the series. It is based on a parsimonious statistical downscaling (Multiple Linear Regression) of the large-scale 20CR reanalysis data. This method is successfully applied upon two long-range temperature series from a couple of centennial observatories (Ebre and Fabra, NE of Spain) which do not have nearby suitable temperature series to compare with. Results of trend analysis point to a clear signal of warming, with a larger rate of increase for the maximum temperature (respect to the minimum one), for the more recent decades (respect to the whole available period), and for the original series (respect to the reconstructed ones).
AB - In the context of climatic temperature studies, more often than not a time series is affected by artificial inhomogeneities. To overcome such limitation, we propose a new simple methodology in which promising results point not only toward the detection of unknown inhomogeneous periods but also toward the possibility of reconstructing the uncertain portion of the series. It is based on a parsimonious statistical downscaling (Multiple Linear Regression) of the large-scale 20CR reanalysis data. This method is successfully applied upon two long-range temperature series from a couple of centennial observatories (Ebre and Fabra, NE of Spain) which do not have nearby suitable temperature series to compare with. Results of trend analysis point to a clear signal of warming, with a larger rate of increase for the maximum temperature (respect to the minimum one), for the more recent decades (respect to the whole available period), and for the original series (respect to the reconstructed ones).
KW - Inhomogeneities
KW - Multiple linear regression
KW - Series reconstruction
KW - Statistical downscaling
UR - http://www.scopus.com/inward/record.url?scp=84907697344&partnerID=8YFLogxK
U2 - 10.1007/s10113-012-0363-9
DO - 10.1007/s10113-012-0363-9
M3 - Article
AN - SCOPUS:84907697344
SN - 1436-3798
VL - 14
SP - 1811
EP - 1823
JO - Regional Environmental Change
JF - Regional Environmental Change
IS - 5
ER -