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

Balsamo, Gianpaolo; Agusti-Parareda, Anna; Albergel, Clement; Arduini, Gabriele; Beljaars, Anton; Bidlot, Jean; Blyth, Eleanor ORCID: https://orcid.org/0000-0002-5052-238X; Bousserez, Nicolas; Boussetta, Souhail; Brown, Andy; Buizza, Roberto; Buontempo, Carlo; Chevallier, Frédéric; Choulga, Margarita; Cloke, Hannah; Cronin, Meghan F.; Dahoui, Mohamed; De Rosnay, Patricia; Dirmeyer, Paul A.; Drusch, Matthias; Dutra, Emanuel; Ek, Michael B.; Gentine, Pierre; Hewitt, Helene; Keeley, Sarah P.E.; Kerr, Yann; Kumar, Sujay; Lupu, Cristina; Mahfouf, Jean-François; McNorton, Joe; Mecklenburg, Susanne; Mogensen, Kristian; Muñoz-Sabater, Joaquín; Orth, Rene; Rabier, Florence; Reichle, Rolf; Ruston, Ben; Pappenberger, Florian; Sandu, Irina; Seneviratne, Sonia I.; Tietsche, Steffen; Trigo, Isabel F.; Uijlenhoet, Remko; Wedi, Nils; Woolway, R. Iestyn; Zeng, Xubin. 2018 Satellite and in situ observations for advancing global Earth surface modelling: a review [in special issue: Advancing Earth surface representation via enhanced use of Earth observations in monitoring and forecasting applications] Remote Sensing, 10 (12), 2038. 72, pp. https://doi.org/10.3390/rs10122038

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Official URL: http://dx.doi.org/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:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.3390/rs10122038
UKCEH and CEH Sections/Science Areas:	Hydro-climate Risks (Science Area 2017-)
ISSN:	2072-4292
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	earth-observations, earth system modelling, direct and inverse methods
NORA Subject Terms:	Earth Sciences
Date made live:	30 May 2019 09:50 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/523582

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.3390/rs10122038

UKCEH and CEH Sections/Science Areas:

Hydro-climate Risks (Science Area 2017-)

ISSN:

2072-4292

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

earth-observations, earth system modelling, direct and inverse methods