Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle
<p>State-of-the art climate prediction systems have recently included a carbon component. While physical-state variables are assimilated in reconstruction simulations, land and ocean biogeochemical state variables adjust to the state acquired through this assimilation indirectly instead of bei...
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Copernicus Publications
2021
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oai:doaj.org-article:a9a73a72361b41ce9ba6be80eb66d70e2021-11-15T08:29:10ZTrivial improvements in predictive skill due to direct reconstruction of the global carbon cycle10.5194/esd-12-1139-20212190-49792190-4987https://doaj.org/article/a9a73a72361b41ce9ba6be80eb66d70e2021-11-01T00:00:00Zhttps://esd.copernicus.org/articles/12/1139/2021/esd-12-1139-2021.pdfhttps://doaj.org/toc/2190-4979https://doaj.org/toc/2190-4987<p>State-of-the art climate prediction systems have recently included a carbon component. While physical-state variables are assimilated in reconstruction simulations, land and ocean biogeochemical state variables adjust to the state acquired through this assimilation indirectly instead of being assimilated themselves. In the absence of comprehensive biogeochemical reanalysis products, such an approach is pragmatic. Here we evaluate a potential advantage of having perfect carbon cycle observational products to be used for direct carbon cycle reconstruction.</p> <p>Within an idealized perfect-model framework, we reconstruct a 50-year target period from a control simulation. We nudge variables from this target onto arbitrary initial conditions, mimicking an assimilation simulation generating initial conditions for hindcast experiments of prediction systems. Interested in the ability to reconstruct global atmospheric <span class="inline-formula">CO<sub>2</sub></span>, we focus on the global carbon cycle reconstruction performance and predictive skill.</p> <p>We find that indirect carbon cycle reconstruction through physical fields reproduces the target variations. While reproducing the large-scale variations, nudging introduces systematic regional biases in the physical-state variables to which biogeochemical cycles react very sensitively. Initial conditions in the oceanic carbon cycle are sufficiently well reconstructed indirectly. Direct reconstruction slightly improves initial conditions. Indirect reconstruction of global terrestrial carbon cycle initial conditions are also sufficiently well reconstructed by the physics reconstruction alone. Direct reconstruction negligibly improves air–land <span class="inline-formula">CO<sub>2</sub></span> flux. Atmospheric <span class="inline-formula">CO<sub>2</sub></span> is indirectly very well reconstructed. Direct reconstruction of the marine and terrestrial carbon cycles slightly improves reconstruction while establishing persistent biases. We find improvements in global carbon cycle predictive skill from direct reconstruction compared to indirect reconstruction. After correcting for mean bias, indirect and direct reconstruction both predict the target similarly well and only moderately worse than perfect initialization after the first lead year.</p> <p>Our perfect-model study shows that indirect carbon cycle reconstruction yields satisfying initial conditions for global <span class="inline-formula">CO<sub>2</sub></span> flux and atmospheric <span class="inline-formula">CO<sub>2</sub></span>. Direct carbon cycle reconstruction adds little improvement to the global carbon cycle because imperfect reconstruction of the physical climate state impedes better biogeochemical reconstruction. These minor improvements in initial conditions yield little improvement in initialized perfect-model predictive skill. We label these minor improvements due to direct carbon cycle reconstruction “trivial”, as mean bias reduction yields similar improvements. As reconstruction biases in real-world prediction systems are likely stronger, our results add confidence to the current practice of indirect reconstruction in carbon cycle prediction systems.</p>A. SpringA. SpringI. DunklI. DunklH. LiV. BrovkinV. BrovkinT. IlyinaCopernicus PublicationsarticleScienceQGeologyQE1-996.5Dynamic and structural geologyQE500-639.5ENEarth System Dynamics, Vol 12, Pp 1139-1167 (2021) |
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Science Q Geology QE1-996.5 Dynamic and structural geology QE500-639.5 |
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Science Q Geology QE1-996.5 Dynamic and structural geology QE500-639.5 A. Spring A. Spring I. Dunkl I. Dunkl H. Li V. Brovkin V. Brovkin T. Ilyina Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle |
| description |
<p>State-of-the art climate prediction systems have recently included a carbon component. While physical-state variables are assimilated in reconstruction
simulations, land and ocean biogeochemical state variables adjust to the state acquired through this assimilation indirectly instead of being
assimilated themselves. In the absence of comprehensive biogeochemical reanalysis products, such an approach is pragmatic. Here we evaluate a potential
advantage of having perfect carbon cycle observational products to be used for direct carbon cycle reconstruction.</p>
<p>Within an idealized perfect-model framework, we reconstruct a 50-year target period from a control simulation. We nudge variables from this target
onto arbitrary initial conditions, mimicking an assimilation simulation generating initial conditions for hindcast experiments of prediction
systems. Interested in the ability to reconstruct global atmospheric <span class="inline-formula">CO<sub>2</sub></span>, we focus on the global carbon cycle reconstruction performance
and predictive skill.</p>
<p>We find that indirect carbon cycle reconstruction through physical fields reproduces the target variations. While reproducing the large-scale
variations, nudging introduces systematic regional biases in the physical-state variables to which biogeochemical cycles react very
sensitively. Initial conditions in the oceanic carbon cycle are sufficiently well reconstructed indirectly. Direct reconstruction slightly improves
initial conditions. Indirect reconstruction of global terrestrial carbon cycle initial conditions are also sufficiently well reconstructed by the
physics reconstruction alone. Direct reconstruction negligibly improves air–land <span class="inline-formula">CO<sub>2</sub></span> flux. Atmospheric <span class="inline-formula">CO<sub>2</sub></span> is indirectly very well
reconstructed. Direct reconstruction of the marine and terrestrial carbon cycles slightly improves reconstruction while establishing
persistent biases. We find improvements in global carbon cycle predictive skill from direct reconstruction compared to indirect
reconstruction. After correcting for mean bias, indirect and direct reconstruction both predict the target similarly well and only moderately worse
than perfect initialization after the first lead year.</p>
<p>Our perfect-model study shows that indirect carbon cycle reconstruction yields satisfying initial conditions for global <span class="inline-formula">CO<sub>2</sub></span> flux and
atmospheric <span class="inline-formula">CO<sub>2</sub></span>. Direct carbon cycle reconstruction adds little improvement to the global carbon cycle because imperfect reconstruction
of the physical climate state impedes better biogeochemical reconstruction. These minor improvements in initial conditions yield little improvement
in initialized perfect-model predictive skill. We label these minor improvements due to direct carbon cycle reconstruction “trivial”, as mean
bias reduction yields similar improvements. As reconstruction biases in real-world prediction systems are likely stronger, our results add
confidence to the current practice of indirect reconstruction in carbon cycle prediction systems.</p> |
| format |
article |
| author |
A. Spring A. Spring I. Dunkl I. Dunkl H. Li V. Brovkin V. Brovkin T. Ilyina |
| author_facet |
A. Spring A. Spring I. Dunkl I. Dunkl H. Li V. Brovkin V. Brovkin T. Ilyina |
| author_sort |
A. Spring |
| title |
Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle |
| title_short |
Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle |
| title_full |
Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle |
| title_fullStr |
Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle |
| title_full_unstemmed |
Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle |
| title_sort |
trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle |
| publisher |
Copernicus Publications |
| publishDate |
2021 |
| url |
https://doaj.org/article/a9a73a72361b41ce9ba6be80eb66d70e |
| work_keys_str_mv |
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