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Capability of the variogram to quantify the spatial patterns of surface fluxes and soil moisture simulated by land surface models
- Source :
- Progress in Physical Geography, Progress in Physical Geography, SAGE Publications, 2021, 45 (2), pp.279-293. ⟨10.1177/0309133320986147⟩
- Publication Year :
- 2021
- Publisher :
- HAL CCSD, 2021.
-
Abstract
- International audience; 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.
- Subjects :
- Surface (mathematics)
010504 meteorology & atmospheric sciences
surface fluxes
0208 environmental biotechnology
Geography, Planning and Development
land surface model
[SDU.STU]Sciences of the Universe [physics]/Earth Sciences
Soil science
02 engineering and technology
01 natural sciences
Spatial variability
variogram analysis
Earth and Planetary Sciences (miscellaneous)
Quantitative assessment
Variogram
Water content
0105 earth and related environmental sciences
Spatial structure
spatial pattern
15. Life on land
spatial structure
020801 environmental engineering
Agriculture and Soil Science
13. Climate action
Spatial ecology
General Earth and Planetary Sciences
Common spatial pattern
Environmental science
soil moisture
Subjects
Details
- Language :
- English
- ISSN :
- 03091333 and 14770296
- Database :
- OpenAIRE
- Journal :
- Progress in Physical Geography, Progress in Physical Geography, SAGE Publications, 2021, 45 (2), pp.279-293. ⟨10.1177/0309133320986147⟩
- Accession number :
- edsair.doi.dedup.....ab0edf55d9882f9963256e946d01a007