nerc.ac.uk

Capability of the variogram to quantify the spatial patterns of surface fluxes and soil moisture simulated by land surface models

Garrigues, S.; Verhoef, A.; Blyth, E.; Wright, A.; Balan-Sarojini, B.; Robinson, E.L. ORCID: https://orcid.org/0000-0002-3746-4517; Dadson, S.; Boone, A.; Boussetta, S.; Balsamo, G.. 2021 Capability of the variogram to quantify the spatial patterns of surface fluxes and soil moisture simulated by land surface models. Progress in Physical Geography: Earth and Environment. https://doi.org/10.1177/0309133320986147

Before downloading, please read NORA policies.
[img]
Preview
Text
0309133320986147.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial 4.0.

Download (782kB) | Preview

Abstract/Summary

Up to now, relatively little effort has been dedicated to the quantitative assessment of the differences in spatial patterns of model outputs. In this paper, we employed a variogram-based methodology to quantify the differences in the spatial patterns of root-zone soil moisture, net radiation, and latent and sensible heat fluxes simulated by three land surface models (SURFEX/ISBA, JULES and CHTESSEL) over three European geographic domains – namely, UK, France and Spain. The model output spatial patterns were quantified through two metrics derived from the variogram: i) the variogram sill, which quantifies the degree of spatial variability of the data; and ii) the variogram integral range, which represents the spatial length scale of the data. The higher seasonal variation of the spatial variability of sensible and latent heat fluxes over France and Spain, compared to the UK, is related to a more frequent occurrence of a soil-moisture-limited evapotranspiration regime during summer dry spells in the south of France and Spain. The small differences in spatial variability of net radiation between models indicate that the spatial patterns of net radiation are mostly driven by the climate forcing data set. However, the models exhibit larger differences in latent and sensible heat flux spatial variabilities, which are related to their differences in i) soil and vegetation ancillary datasets and ii) physical process representation. The highest discrepancies in spatial patterns between models are observed for soil moisture, which is mainly related to the type of soil hydraulic function implemented in the models. This work demonstrates the capability of the variogram to enhance our understanding of the spatiotemporal structure of the uncertainties in land surface model outputs. Therefore, we strongly encourage the implementation of the variogram metrics in model intercomparison exercises.

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.1177/0309133320986147
UKCEH and CEH Sections/Science Areas: Hydro-climate Risks (Science Area 2017-)
ISSN: 0309-1333
Additional Information. Not used in RCUK Gateway to Research.: Open Access paper - full text available via Official URL link.
Additional Keywords: spatial variability, spatial structure, spatial pattern, variogram analysis, land surface model, surface fluxes, soil moisture
NORA Subject Terms: Agriculture and Soil Science
Date made live: 23 Mar 2021 16:10 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/529938

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...