Accessibility navigation


Satellite and in situ observations for advancing global Earth surface modelling: a review

Balsamo, G., Agustì-Parareda, A., Albergel, C., Arduini, G., Beljaars, A., Bidlot, J., Bousserez, N., Boussetta, S., Brown, A., Buizza, R., Buontempo, C., Chevallier, F., Choulga, M., Cloke, H. ORCID: https://orcid.org/0000-0002-1472-868X, Cronin, M., Dahoui, M., De Rosnay, P., Dirmeyer, P., Drusch, M., Dutra, E. , Ek, M., Gentine, P., Hewitt, H., Keeley, S., Kerr, Y., Kumar, S., Lupu, C., Mahfouf, J.-F., McNorton, J., Mecklenburg, S., Mogensen, K., Muñoz-Sabater, J., Orth, R., Rabier, F., Reichle, R., Ruston, B., Pappenberger, F., Sandu, I., Seneviratne, S., Tietsche, S., Trigo, I., Uijlenhoet, R., Wedi, N., Woolway, R. I. ORCID: https://orcid.org/0000-0003-0498-7968 and Zeng, X. (2018) Satellite and in situ observations for advancing global Earth surface modelling: a review. Remote Sensing, 10 (12). 2038. ISSN 2072-4292

[img]
Preview
Text (Open access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.

23MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.3390/rs10122038

Abstract/Summary

In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:81462
Publisher:MDPI

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation