Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

Forskningsoutput: TidskriftsbidragÖversiktsartikel

Standard

Reviews and syntheses : Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems. / Scholze, Marko; Buchwitz, Michael; Dorigo, Wouter A.; Guanter, Luis; Quegan, Shaun.

I: Biogeosciences, Vol. 14, Nr. 14, 19.07.2017, s. 3401-3429.

Forskningsoutput: TidskriftsbidragÖversiktsartikel

Harvard

APA

CBE

MLA

Vancouver

Author

Scholze, Marko ; Buchwitz, Michael ; Dorigo, Wouter A. ; Guanter, Luis ; Quegan, Shaun. / Reviews and syntheses : Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems. I: Biogeosciences. 2017 ; Vol. 14, Nr. 14. s. 3401-3429.

RIS

TY - JOUR

T1 - Reviews and syntheses

T2 - Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

AU - Scholze, Marko

AU - Buchwitz, Michael

AU - Dorigo, Wouter A.

AU - Guanter, Luis

AU - Quegan, Shaun

PY - 2017/7/19

Y1 - 2017/7/19

N2 - The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations.

AB - The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhouse gas emissions. An improved understanding of the carbon cycle can be achieved by data assimilation systems, which integrate observations relevant to the carbon cycle into coupled carbon, water, energy and nutrient models. Hence, the ingredients for such systems are a carbon cycle model, an algorithm for the assimilation and systematic and well error-characterised observations relevant to the carbon cycle. Relevant observations for assimilation include various in situ measurements in the atmosphere (e.g. concentrations of CO2 and other gases) and on land (e.g. fluxes of carbon water and energy, carbon stocks) as well as remote sensing observations (e.g. atmospheric composition, vegetation and surface properties).We briefly review the different existing data assimilation techniques and contrast them to model benchmarking and evaluation efforts (which also rely on observations). A common requirement for all assimilation techniques is a full description of the observational data properties. Uncertainty estimates of the observations are as important as the observations themselves because they similarly determine the outcome of such assimilation systems. Hence, this article reviews the requirements of data assimilation systems on observations and provides a non-exhaustive overview of current observations and their uncertainties for use in terrestrial carbon cycle data assimilation. We report on progress since the review of model-data synthesis in terrestrial carbon observations by Raupach et al.(2005), emphasising the rapid advance in relevant space-based observations.

U2 - 10.5194/bg-14-3401-2017

DO - 10.5194/bg-14-3401-2017

M3 - Review article

VL - 14

SP - 3401

EP - 3429

JO - Biogeosciences

JF - Biogeosciences

SN - 1726-4189

IS - 14

ER -