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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hess-2019-109
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2019-109
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 27 Mar 2019

Research article | 27 Mar 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Using GRACE to derive corrections to precipitation data sets and improve modelled snow mass at high latitudes

Emma L. Robinson and Douglas B. Clark Emma L. Robinson and Douglas B. Clark
  • Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford OX10 8BB

Abstract. The amount of lying snow calculated by a land surface model depends in part on the amount of snowfall in the meteorological data that are used to drive the model. We show that commonly-used data sets differ in the amount of snowfall, and more generally precipitation, over four large Arctic basins. An independent estimate of the cold season precipitation is obtained by combining water balance information from the Gravity Recovery and Climate Experiment (GRACE) with estimates of evaporation and river discharge, and is generally higher than that estimated by four commonly-used meteorological data sets. We use the Joint UK Land Environment Simulator (JULES) land surface model to calculate the snow water equivalent (SWE) over the four basins. The modelled seasonal maximum SWE is 38 % less than observation-based estimates on average and the modelled basin discharge is significantly underestimated, consistent with the lack of snowfall. We use the GRACE-derived estimate of precipitation to define per-basin scale factors that are applied to the driving data and increase the amount of cold season precipitation by 28 % on average. In turn this increases the modelled seasonal maximum SWE by 30 %, although this is still underestimated compared to observations by 19 % on average. A correction for undercatch of precipitation by gauges is compared with the the GRACE-derived correction. Undercatch correction increases the amount of cold season precipitation by 23 % on average, which indicates that some, but not all, of the underestimation can be removed by implementing existing undercatch correction algorithms. However, even undercatch-corrected data sets contain less precipitation than the GRACE-derived estimate in some regions, and it is likely that there are other biases that that are not currently accounted for in gridded meteorological data sets. This study shows that revised estimates of precipitation can lead to improved modelling of SWE, but much more modest improvements are found in modelled river discharge. By providing methods to better define the precipitation inputs to the system, the current study paves the way for subsequent work on key hydrological processes in high-latitude basins.

Emma L. Robinson and Douglas B. Clark
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Status: open (until 22 May 2019)
Status: open (until 22 May 2019)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Emma L. Robinson and Douglas B. Clark
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Short summary
An important part of the Arctic water cycle is the snow that falls in winter, which builds up into a snow pack and then melts in spring. To estimate the amount of snowfall, we use the water balance: precipitation is equal to evaporation plus riverflow plus change in soil moisture and lying snow. We use estimates of the latter to infer what the snowfall must have been and use this to correct the amount of snow in four data sets. This improves how a land surface model represents Arctic hydrology.
An important part of the Arctic water cycle is the snow that falls in winter, which builds up...
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