Satellite and in situ observations for advancing global earth surface modelling

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Satellite and in situ observations for advancing global earth surface modelling

A review

Review (2018)

Author(s)

Gianpaolo Balsamo (European Centre for Medium Range Weather Forecasts - Reading)

Anna Agusti-Panareda (European Centre for Medium Range Weather Forecasts - Reading)

Clement Albergel (Meteo France)

Gabriele Arduini (European Centre for Medium Range Weather Forecasts - Reading)

Anton Beljaars (European Centre for Medium Range Weather Forecasts - Reading)

Jean Bidlot (European Centre for Medium Range Weather Forecasts - Reading)

Nicolas Bousserez (European Centre for Medium Range Weather Forecasts - Reading)

Souhail Boussetta (European Centre for Medium Range Weather Forecasts - Reading)

Andy Brown (European Centre for Medium Range Weather Forecasts - Reading)

Roberto Buizza (European Centre for Medium Range Weather Forecasts - Reading)

Carlo Buontempo (European Centre for Medium Range Weather Forecasts - Reading)

Frederic Chevallier (Laboratoire des Sciences du Climat et de l'Environment)

Margarita Choulga (European Centre for Medium Range Weather Forecasts - Reading)

Hannah Cloke (University of Reading)

Meghan F. Cronin (National Oceanic and Atmospheric Administration)

Mohamed Dahoui (European Centre for Medium Range Weather Forecasts - Reading)

Patricia De Rosnay (European Centre for Medium Range Weather Forecasts - Reading)

Paul A. Dirmeyer (Center for Ocean-Land-Atmosphere Studies)

Matthias Drusch (European Space Agency (ESA))

Emanuel Dutra (Universidade de Lisboa)

Michael B. Ek (University Corporation for Atmospheric Research)

Pierre Gentine (Columbia University)

Helene Hewitt (UK MetOffice)

Sarah P.E. Keeley (European Centre for Medium Range Weather Forecasts - Reading)

Yann Kerr (Centre d’Études Spatiales de la Biosphère - Centre national de la recherche scientifique)

Sujay Kumar (NASA Goddard Space Flight Center)

Cristina Lupu (European Centre for Medium Range Weather Forecasts - Reading)

Jean Francois Mahfouf (Meteo France)

Joe McNorton (European Centre for Medium Range Weather Forecasts - Reading)

Susanne Mecklenburg (European Space Agency (ESA))

Kristian Mogensen (European Centre for Medium Range Weather Forecasts - Reading)

Joaquín Muñoz-Sabater (European Centre for Medium Range Weather Forecasts - Reading)

Rene Orth (Max Planck Institute for Biogeochemistry)

Florence Rabier (European Centre for Medium Range Weather Forecasts - Reading)

Rolf Reichle (NASA Goddard Space Flight Center)

Ben Ruston (Naval Research Laboratory)

Florian Pappenberger (European Centre for Medium Range Weather Forecasts - Reading)

Irina Sandu (European Centre for Medium Range Weather Forecasts - Reading)

Sonia I. Seneviratne (ETH Zürich)

Steffen Tietsche (European Centre for Medium Range Weather Forecasts - Reading)

Isabel F. Trigo (Instituto Português do Mar e da Amosfera (IPMA))

Remko Uijlenhoet (Wageningen University & Research)

Nils Wedi (European Centre for Medium Range Weather Forecasts - Reading)

R. Iestyn Woolway (University of Reading)

Xubin Zeng (University of Arizona)

University

External organisation

Earth system modelling Direct and inverse methods Earth-observations

DOI related publication

https://doi.org/10.3390/rs10122038 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:7be53825-3271-478b-81af-06084b76570e

More Info

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Publication Year

2018

Language

English

Abstract

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.