Using Gravity Recovery and Climate Experiment data to derive corrections to precipitation data sets and improve modelled snow mass at high latitudes
-
Published:2020-04-09
Issue:4
Volume:24
Page:1763-1779
-
ISSN:1607-7938
-
Container-title:Hydrology and Earth System Sciences
-
language:en
-
Short-container-title:Hydrol. Earth Syst. Sci.
Author:
Robinson Emma L.ORCID, Clark Douglas B.ORCID
Abstract
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 the 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 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.
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences,General Engineering,General Environmental Science
Reference85 articles.
1. Adam, J. C. and Lettenmaier, D. P.: Adjustment of global gridded precipitation
for systematic bias, J. Geophys. Res.-Atmos., 108, 4257,
https://doi.org/10.1029/2002JD002499, 2003. a, b, c, d, e, f, g 2. Adam, J. C., Clark, E. A., Lettenmaier, D. P., and Wood, E. F.: Correction of
Global Precipitation Products for Orographic Effects, J. Climate, 19,
15–38, https://doi.org/10.1175/JCLI3604.1, 2006. a, b, c 3. Alkama, R., Decharme, B., Douville, H., Becker, M., Cazenave, A., Sheffield,
J., Voldoire, A., Tyteca, S., and Le Moigne, P.: Global Evaluation of the
ISBA-TRIP Continental Hydrological System. Part I: Comparison to GRACE
Terrestrial Water Storage Estimates and In Situ River Discharges, J.
Hydrometeorol., 11, 583–600, https://doi.org/10.1175/2010JHM1211.1, 2010. a 4. Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M., Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J., and Wood, E. F.: Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling, Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, 2017. a 5. Behrangi, A., Christensen, M., Richardson, M., Lebsock, M., Stephens, G.,
Huffman, G. J., Bolvin, D., Adler, R. F., Gardner, A., Lambrigtsen, B., and
Fetzer, E.: Status of high-latitude precipitation estimates from observations
and reanalyses, J. Geophys. Res.-Atmos., 121,
4468–4486, https://doi.org/10.1002/2015JD024546, 2016. a, b
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|