Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems
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 ch...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-07-01
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| Series: | Biogeosciences |
| Online Access: | https://www.biogeosciences.net/14/3401/2017/bg-14-3401-2017.pdf |
| Summary: | 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 CO<sub>2</sub> 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).<br><br>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. |
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| ISSN: | 1726-4170 1726-4189 |