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Earth System Science Data The Data Publishing Journal
https://doi.org/10.5194/essd-2017-64
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Review article
28 Aug 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Earth System Science Data (ESSD).
Evaluation of seNorge2, a conventional climatological datasets for snow- and hydrological modeling in Norway
Cristian Lussana1, Tuomo Saloranta2, Thomas Skaugen2, Jan Magnussson2, Ole Einar Tveito1, and Jess Andersen2 1Norwegian Meteorological Institute, Oslo, Norway
2Norwegian Water Resources and Energy Directorate, Oslo, Norway
Abstract. The conventional climate datasets based on observations only are a widely used source of information for climate and hydrology. On the Norwegian mainland, the seNorge datasets of daily mean temperature and total precipitation amount constitute a valuable meteorological input for snow- and hydrological simulations which are routinely conducted over such a complex and heterogeneous terrain. A new seNorge version (seNorge2) has been released recently and to support operational applications for civil protection purposes, it must be updated daily and presented on a high-resolution grid (1 km of grid spacing). The archive goes back to 1957. The seNorge2 statistical interpolation schemes can provide high-resolution fields for applications requiring long-term datasets at regional or national level, where the challenge is to simulate small-scale processes often taking place in complex terrain. The statistical schemes build upon classical spatial interpolation methods, such as Optimal Interpolation and successive-correction schemes, and introduce original approaches. For both temperature and precipitation, the spatial interpolation exploits the concept of (spatial) scale-separation and the first-guess field is derived from the observed data. Furthermore, the geographical coordinates and the elevation are used as complementary information. The evaluation of the seNorge2 products is presented both from a general point of view, through systematic cross-validations, and specifically as the meteorological input in the operational model chains used for snow- and hydrological simulations. The seNorge snow model is used for simulation of snow fields and the DDD (Distance Distribution Dynamics) rainfall-runoff model is the hydrological model used. The evaluation points out important information for the future seNorge2 developments: the daily mean temperature fields constitute an accurate and precise dataset, on average the predicted temperature is an unbiased estimate of the actual temperature and its precision (at grid points) varies between 0.8 °C and 2.4 °C; the daily precipitation fields provide a reasonable estimate of the actual precipitation, the cross-validation shows that on average the precision of the estimates (at grid points) is about ±20 %, though a systematic underestimation of precipitation occurs in data-sparse areas and for intense precipitation. Both the seNorge snow and the DDD models have been able to make profitable use of seNorge2, partly because of the automatic calibration procedure they incorporate for precipitation. The dataset described in this article is available for public download at http://doi.org/10.5281/zenodo.845733.

Citation: Lussana, C., Saloranta, T., Skaugen, T., Magnussson, J., Tveito, O. E., and Andersen, J.: Evaluation of seNorge2, a conventional climatological datasets for snow- and hydrological modeling in Norway, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2017-64, in review, 2017.
Cristian Lussana et al.
Cristian Lussana et al.

Data sets

seNorge2 dataset
C. Lussana and O. E. Tveito
https://doi.org/10.5281/zenodo.845733

Model code and software

seNorge2 code release 2017.08
C. Lussana
https://doi.org/10.5281/zenodo.848582
Cristian Lussana et al.

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Short summary
The conventional climate datasets based on observations only are among the primary sources of information for climate monitoring. The seNorge datasets of daily mean temperature and total precipitation amount constitute a valuable meteorological input for snow- and hydrological simulations which are routinely conducted over Norway for research and to support operational applications for civil protection purposes. The datasets and the source code are publicly available for download.
The conventional climate datasets based on observations only are among the primary sources of...
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