Correction: Balsamo, G., et al. 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, Eleanor Blyth, 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 & 26 others Emanuel Dutra, Michael 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.I. Woolway, Xubin Zeng

*Corresponding author for this work

Research output: Contribution to journalComment/Letter to the editorAcademic

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.

Original languageEnglish
Article number941
JournalRemote Sensing
Volume11
Issue number8
DOIs
Publication statusPublished - 18 Apr 2019

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remote sensing
modeling
cryosphere
hydrosphere
climate prediction
in situ
biosphere
discontinuity
weather
monitoring
prediction

Keywords

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

Cite this

Balsamo, G., Agusti-Panareda, A., Albergel, C., Arduini, G., Beljaars, A., Bidlot, J., ... Zeng, X. (2019). Correction: Balsamo, G., et al. Satellite and in situ observations for advancing global earth surface modelling: A review. Remote Sensing, 11(8), [941]. https://doi.org/10.3390/rs11080941
Balsamo, Gianpaolo ; Agusti-Panareda, Anna ; Albergel, Clement ; Arduini, Gabriele ; Beljaars, Anton ; Bidlot, Jean ; Blyth, Eleanor ; Bousserez, Nicolas ; Boussetta, Souhail ; Brown, Andy ; Buizza, Roberto ; Buontempo, Carlo ; Chevallier, Frederic ; Choulga, Margarita ; Cloke, Hannah ; Cronin, Meghan F. ; Dahoui, Mohamed ; Rosnay, Patricia De ; 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 Francois ; 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.I. ; Zeng, Xubin. / Correction: Balsamo, G., et al. Satellite and in situ observations for advancing global earth surface modelling : A review. In: Remote Sensing. 2019 ; Vol. 11, No. 8.
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title = "Correction: Balsamo, G., et al. Satellite and in situ observations for advancing global earth surface modelling: A review",
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.",
keywords = "Direct and inverse methods, Earth system modelling, Earth-observations",
author = "Gianpaolo Balsamo and Anna Agusti-Panareda and Clement Albergel and Gabriele Arduini and Anton Beljaars and Jean Bidlot and Eleanor Blyth and Nicolas Bousserez and Souhail Boussetta and Andy Brown and Roberto Buizza and Carlo Buontempo and Frederic Chevallier and Margarita Choulga and Hannah Cloke and Cronin, {Meghan F.} and Mohamed Dahoui and Rosnay, {Patricia De} and Dirmeyer, {Paul A.} and Matthias Drusch and Emanuel Dutra and Ek, {Michael B.} and Pierre Gentine and Helene Hewitt and Keeley, {Sarah P.E.} and Yann Kerr and Sujay Kumar and Cristina Lupu and Mahfouf, {Jean Francois} and Joe McNorton and Susanne Mecklenburg and Kristian Mogensen and Joaqu{\'i}n Mu{\~n}oz-Sabater and Rene Orth and Florence Rabier and Rolf Reichle and Ben Ruston and Florian Pappenberger and Irina Sandu and Seneviratne, {Sonia I.} and Steffen Tietsche and Trigo, {Isabel F.} and Remko Uijlenhoet and Nils Wedi and R.I. Woolway and Xubin Zeng",
year = "2019",
month = "4",
day = "18",
doi = "10.3390/rs11080941",
language = "English",
volume = "11",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "MDPI",
number = "8",

}

Balsamo, G, Agusti-Panareda, A, Albergel, C, Arduini, G, Beljaars, A, Bidlot, J, Blyth, E, Bousserez, N, Boussetta, S, Brown, A, Buizza, R, Buontempo, C, Chevallier, F, Choulga, M, Cloke, H, Cronin, MF, Dahoui, M, Rosnay, PD, Dirmeyer, PA, Drusch, M, Dutra, E, Ek, MB, Gentine, P, Hewitt, H, Keeley, SPE, Kerr, Y, Kumar, S, Lupu, C, Mahfouf, JF, McNorton, J, Mecklenburg, S, Mogensen, K, Muñoz-Sabater, J, Orth, R, Rabier, F, Reichle, R, Ruston, B, Pappenberger, F, Sandu, I, Seneviratne, SI, Tietsche, S, Trigo, IF, Uijlenhoet, R, Wedi, N, Woolway, RI & Zeng, X 2019, 'Correction: Balsamo, G., et al. Satellite and in situ observations for advancing global earth surface modelling: A review', Remote Sensing, vol. 11, no. 8, 941. https://doi.org/10.3390/rs11080941

Correction: Balsamo, G., et al. Satellite and in situ observations for advancing global earth surface modelling : A review. / Balsamo, Gianpaolo; Agusti-Panareda, Anna; Albergel, Clement; Arduini, Gabriele; Beljaars, Anton; Bidlot, Jean; Blyth, Eleanor; Bousserez, Nicolas; Boussetta, Souhail; Brown, Andy; Buizza, Roberto; Buontempo, Carlo; Chevallier, Frederic; Choulga, Margarita; Cloke, Hannah; Cronin, Meghan F.; Dahoui, Mohamed; Rosnay, Patricia De; 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 Francois; 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.I.; Zeng, Xubin.

In: Remote Sensing, Vol. 11, No. 8, 941, 18.04.2019.

Research output: Contribution to journalComment/Letter to the editorAcademic

TY - JOUR

T1 - Correction: Balsamo, G., et al. Satellite and in situ observations for advancing global earth surface modelling

T2 - A review

AU - Balsamo, Gianpaolo

AU - Agusti-Panareda, Anna

AU - Albergel, Clement

AU - Arduini, Gabriele

AU - Beljaars, Anton

AU - Bidlot, Jean

AU - Blyth, Eleanor

AU - Bousserez, Nicolas

AU - Boussetta, Souhail

AU - Brown, Andy

AU - Buizza, Roberto

AU - Buontempo, Carlo

AU - Chevallier, Frederic

AU - Choulga, Margarita

AU - Cloke, Hannah

AU - Cronin, Meghan F.

AU - Dahoui, Mohamed

AU - Rosnay, Patricia De

AU - Dirmeyer, Paul A.

AU - Drusch, Matthias

AU - Dutra, Emanuel

AU - Ek, Michael B.

AU - Gentine, Pierre

AU - Hewitt, Helene

AU - Keeley, Sarah P.E.

AU - Kerr, Yann

AU - Kumar, Sujay

AU - Lupu, Cristina

AU - Mahfouf, Jean Francois

AU - McNorton, Joe

AU - Mecklenburg, Susanne

AU - Mogensen, Kristian

AU - Muñoz-Sabater, Joaquín

AU - Orth, Rene

AU - Rabier, Florence

AU - Reichle, Rolf

AU - Ruston, Ben

AU - Pappenberger, Florian

AU - Sandu, Irina

AU - Seneviratne, Sonia I.

AU - Tietsche, Steffen

AU - Trigo, Isabel F.

AU - Uijlenhoet, Remko

AU - Wedi, Nils

AU - Woolway, R.I.

AU - Zeng, Xubin

PY - 2019/4/18

Y1 - 2019/4/18

N2 - 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.

AB - 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.

KW - Direct and inverse methods

KW - Earth system modelling

KW - Earth-observations

U2 - 10.3390/rs11080941

DO - 10.3390/rs11080941

M3 - Comment/Letter to the editor

VL - 11

JO - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 8

M1 - 941

ER -