Zobrazeno 1 - 10
of 162
pro vyhledávání: '"Landschützer, P."'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract The sailboat Seaexplorer collected underway sea surface partial pressure of CO2 (pCO2) data for 129 days (2018–2021), including an Antarctic circumnavigation. By comparing ensembles of data-driven air-sea CO2 fluxes computed with and witho
Externí odkaz:
https://doaj.org/article/a1046be2d6c4476db50336f2e29a075a
Publikováno v:
Earth System Science Data, Vol 16, Pp 421-441 (2024)
In recent years, advancements in machine learning based interpolation methods have enabled the production of high-resolution maps of sea surface partial pressure of CO2 (pCO2) derived from observations extracted from databases such as the Surface Oce
Externí odkaz:
https://doaj.org/article/ab52697a076d4f8ab3cc7b23ceecd1ca
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 9, Pp n/a-n/a (2024)
Abstract Observation‐based quantification of ocean carbon dioxide (CO2) uptake relies on synthesis data sets such as the Surface Ocean CO2 ATlas (SOCAT). However, the data collection effort has dramatically declined and the number of annual data se
Externí odkaz:
https://doaj.org/article/4deac0ceae8b4864b205b88263436a5c
Autor:
Annika Jersild, Peter Landschützer
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 4, Pp n/a-n/a (2024)
Abstract In order to understand the oceans role as a global carbon sink, we must accurately quantify the amount of carbon exchanged at the air‐sea interface. A widely used machine learning neural network product, the SOM‐FFN, uses observations to
Externí odkaz:
https://doaj.org/article/f7f5fefd6c4a441889b17c1f8589b57f
Autor:
P. J. Duke, R. C. Hamme, D. Ianson, P. Landschützer, M. M. M. Ahmed, N. C. Swart, P. A. Covert
Publikováno v:
Biogeosciences, Vol 20, Pp 3919-3941 (2023)
The global ocean takes up nearly a quarter of anthropogenic CO2 emissions annually, but the variability in this uptake at regional scales remains poorly understood. Here we use a neural network approach to interpolate sparse observations, creating a
Externí odkaz:
https://doaj.org/article/6e95f7d117d049658fee6d471a98e168
Publikováno v:
npj Climate and Atmospheric Science, Vol 6, Iss 1, Pp 1-8 (2023)
Abstract Interannual variability of the ocean carbon sink is often assessed using annual air–sea carbon fluxes, but the drivers of the variability may instead arise from seasonal processes that are neglected in the annual average. The seasonal cycl
Externí odkaz:
https://doaj.org/article/c28b111c6abe41eca89f6c08a79f941c
Akademický článek
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Akademický článek
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Publikováno v:
Communications Earth & Environment, Vol 3, Iss 1, Pp 1-9 (2022)
Uncertainties in the CO2 flux in the Southern Ocean, produced by a lack of direct wintertime observations, can be addressed by a combination of pseudo observations and neural network machine learning-based mapping.
Externí odkaz:
https://doaj.org/article/3ed678eeb49a494cb28ba4c1bbdecc67
Autor:
Alexandre Mignot, Karina von Schuckmann, Peter Landschützer, Florent Gasparin, Simon van Gennip, Coralie Perruche, Julien Lamouroux, Tristan Amm
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-9 (2022)
Ocean CO2 uptake at mid-latitudes counteracts CO2 release in the tropics, but we know little about the effects of marine heatwaves that modulate this process. Here, the authors use joint analysis of satellite measurements, in situ observation, recons
Externí odkaz:
https://doaj.org/article/0decb677cf7c44d9875a8417a81f95dd