Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

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Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review. / Balsamo, Gianpaolo; Agusti-Parareda, Anna; Albergel, Clement et al.
Yn: Remote Sensing, Cyfrol 10, Rhif 12, 14.12.2018.

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HarvardHarvard

Balsamo, G, Agusti-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, Cronin, MF, Dahoui, M, De Rosnay, P, Dirmeyer, PA, Drusch, M, Dutra, E, Ek, MB, Gentine, P, Hewitt, H, Keeley, SPE, Kerr, Y, Kumar, S, Lupu, C, Mahfouf, J-F, McNorton, J, Mecklenburg, S, Mogensen, K, Munoz-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 2018, 'Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review', Remote Sensing, cyfrol. 10, rhif 12. https://doi.org/10.3390/rs10122038

APA

Balsamo, G., Agusti-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., Cronin, M. F., Dahoui, M., De Rosnay, P., Dirmeyer, P. A., Drusch, M., ... Zeng, X. (2018). Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review. Remote Sensing, 10(12). https://doi.org/10.3390/rs10122038

CBE

Balsamo G, Agusti-Parareda A, Albergel C, Arduini G, Beljaars A, Bidlot J, Bousserez N, Boussetta S, Brown A, Buizza R, et al. 2018. Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review. Remote Sensing. 10(12). https://doi.org/10.3390/rs10122038

MLA

VancouverVancouver

Balsamo G, Agusti-Parareda A, Albergel C, Arduini G, Beljaars A, Bidlot J et al. Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review. Remote Sensing. 2018 Rhag 14;10(12). doi: 10.3390/rs10122038

Author

Balsamo, Gianpaolo ; Agusti-Parareda, Anna ; Albergel, Clement et al. / Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review. Yn: Remote Sensing. 2018 ; Cyfrol 10, Rhif 12.

RIS

TY - JOUR

T1 - Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

AU - Balsamo, Gianpaolo

AU - Agusti-Parareda, Anna

AU - Albergel, Clement

AU - Arduini, Gabriele

AU - Beljaars, Anton

AU - Bidlot, Jean

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 - De Rosnay, Patricia

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 - Munoz-Sabater, Joaquin

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. Iestyn

AU - Zeng, Xubin

PY - 2018/12/14

Y1 - 2018/12/14

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 - earth-observations

KW - earth system modelling

KW - direct and inverse methods

U2 - 10.3390/rs10122038

DO - 10.3390/rs10122038

M3 - Article

VL - 10

JO - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 12

ER -