2019
DOI: 10.5194/asr-16-149-2019
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Climate monitoring and heat and cold waves detection over France using a new spatialization of daily temperature extremes from 1947 to present

Abstract: Abstract. For many years real-time climate monitoring for temperature over France has been performed using a national index built by averaging the daily mean temperatures of constant subset of 30 stations with long-term series. In order to derive climate indices at finer scales, a spatialization of extreme daily temperatures (called ANASTASIA) had been produced on a 1 km regular grid using a regression-kriging method. The production covers 1947 to present period. Cross-validation shows low biases after the 196… Show more

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Cited by 5 publications
(1 citation statement)
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“…The ANASTASIA (Analyse Spatiale des Températures de Surface avec Initialisation AURELHY) product is a gridded dataset of minimum (TN) and maximum (TX) daily temperature at 1-km horizontal resolution over Metropolitan France for the time period 1947-2016 (Besson et al, 2019). It uses a regression-kriging method (Hengl et al, 2007) with two sources of information: in situ observations of extreme daily TN and TX recorded by the weather stations of the operational Météo-France network and a monthly climatological field of daily TN and TX defined over the 1982-2010period (Cannelas et al, 2014.…”
Section: Long Time Series Of Gridded Weather Datamentioning
confidence: 99%
“…The ANASTASIA (Analyse Spatiale des Températures de Surface avec Initialisation AURELHY) product is a gridded dataset of minimum (TN) and maximum (TX) daily temperature at 1-km horizontal resolution over Metropolitan France for the time period 1947-2016 (Besson et al, 2019). It uses a regression-kriging method (Hengl et al, 2007) with two sources of information: in situ observations of extreme daily TN and TX recorded by the weather stations of the operational Météo-France network and a monthly climatological field of daily TN and TX defined over the 1982-2010period (Cannelas et al, 2014.…”
Section: Long Time Series Of Gridded Weather Datamentioning
confidence: 99%