Satellite and in situ observations for advancing global earth surface modelling: A review

Gianpaolo Balsamo, Anna Agusti-Panareda, Clement Albergel, Gabriele Arduini, Anton Beljaars, Jean Bidlot, Nicolas Bousserez, Souhail Boussetta, Andy Brown, Roberto Buizza, Carlo Buontempo, Frederic Chevallier, Margarita Choulga, Hannah Cloke, Meghan F. Cronin, Mohamed Dahoui, Patricia De Rosnay, Paul A. Dirmeyer, Matthias Drusch, Emanuel DutraMichael B. Ek, Pierre Gentine, Helene Hewitt, Sarah P.E. Keeley, Yann Kerr, Sujay Kumar, Cristina Lupu, Jean Francois Mahfouf, Joe McNorton, Susanne Mecklenburg, Kristian Mogensen, Joaquín Muñoz-Sabater, Rene Orth, Florence Rabier, Rolf Reichle, Ben Ruston, Florian Pappenberger, Irina Sandu, Sonia I. Seneviratne, Steffen Tietsche, Isabel F. Trigo, Remko Uijlenhoet, Nils Wedi, R. Iestyn Woolway, Xubin Zeng

Research output: Contribution to journalReview articlepeer-review

104 Scopus citations


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.

Original languageEnglish (US)
Article number2038
JournalRemote Sensing
Issue number12
StatePublished - Dec 1 2018


  • Direct and inverse methods
  • Earth system modelling
  • Earth-observations

ASJC Scopus subject areas

  • General Earth and Planetary Sciences


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