A framework for high‐resolution meteorological surface reanalysis through offline data assimilation in an ensemble of downscaled reconstructions
2019
The knowledge of historical French weather has recently been improved through the development of the Spatially COherent Probabilistic Extended (SCOPE) climate reconstructions. This high‐resolution ensemble daily reconstruction dataset of precipitation and temperature covers the period 1871-2012 and is derived through a statistical downscaling of the Twentieth Century Reanalysis. Historical surface observations - even though rather scarce and sparse - do exist from at least the beginning of the period considered, and this information does not currently feed SCOPE Climate. We propose to construct a new high‐resolution surface reanalysis over France - called FYRE Climate (French hYdrometeorological REanalysis Climate) - by assimilating daily temperature and precipitation observations into SCOPE Climate through an offline Ensemble Kalman Filter. The goal of the study is to test methodological choices for developing the future FYRE Climate surface reanalysis. The data assimilation scheme is evaluated over the 2009-2012 period with an increasing assimilated observation density reproducing historical densities. A consistent set of independent stations is retained for validation in terms of continuous ranked probability score, daily bias and daily correlation. Results highlight the importance of the localization as well as the Gaussian anamorphosis for precipitation. They show that: (a) the reanalysis has a lower uncertainty than the initial SCOPE Climate reconstructions, (b) its reliability is similar, and (c) the data assimilation allows reaching the performance of the reference Safran surface reanalysis over France, even for a density of observations as low as the one of 1950. These results thus pave the way for a full 140‐year high‐resolution precipitation and temperature surface reanalysis over France.
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