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- Anav, Alessandro, et al.
(författare)
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Spatiotemporal patterns of terrestrial gross primary production : A review
- 2015
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Ingår i: Reviews of geophysics. - 8755-1209 .- 1944-9208. ; 53:3, s. 785-818
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Forskningsöversikt (refereegranskat)abstract
- Great advances have been made in the last decade in quantifying and understanding the spatiotemporal patterns of terrestrial gross primary production (GPP) with ground, atmospheric, and space observations. However, although global GPP estimates exist, each data set relies upon assumptions and none of the available data are based only on measurements. Consequently, there is no consensus on the global total GPP and large uncertainties exist in its benchmarking. The objective of this review is to assess how the different available data sets predict the spatiotemporal patterns of GPP, identify the differences among data sets, and highlight the main advantages/disadvantages of each data set. We compare GPP estimates for the historical period (1990-2009) from two observation-based data sets (Model Tree Ensemble and Moderate Resolution Imaging Spectroradiometer) to coupled carbon-climate models and terrestrial carbon cycle models from the Fifth Climate Model Intercomparison Project and TRENDY projects and to a new hybrid data set (CARBONES). Results show a large range in the mean global GPP estimates. The different data sets broadly agree on GPP seasonal cycle in terms of phasing, while there is still discrepancy on the amplitude. For interannual variability (IAV) and trends, there is a clear separation between the observation-based data that show little IAV and trend, while the process-based models have large GPP variability and significant trends. These results suggest that there is an urgent need to improve observation-based data sets and develop carbon cycle modeling with processes that are currently treated either very simplistically to correctly estimate present GPP and better quantify the future uptake of carbon dioxide by the world's vegetation.
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| 2. |
- Fang, Keyan, et al.
(författare)
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An interdecadal climate dipole between Northeast Asia and Antarctica over the past five centuries
- 2019
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Ingår i: Climate Dynamics. - : Springer Science and Business Media LLC. - 0930-7575 .- 1432-0894. ; 52:1/2, s. 765-775
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Tidskriftsartikel (refereegranskat)abstract
- © 2018 Springer-Verlag GmbH Germany, part of Springer Nature Climate models emphasize the need to investigate inter-hemispheric climatic interactions. However, these models often underestimate the inter-hemispheric differences in climate change. With the wide application of reanalysis data since 1948, we identified a dipole pattern between the geopotential heights (GPHs) in Northeast Asia and Antarctica on the interdecadal scale in boreal summer. This Northeast Asia/Antarctica (NAA) dipole pattern is not conspicuous on the interannual scale, probably in that the interannual inter-hemispheric climate interaction is masked by strong interannual signals in the tropics associated with the El Niño-Southern Oscillation (ENSO). Unfortunately, the instrumental records are not sufficiently long-lasting to detect the interdecadal variability of the NAA. We thus reconstructed GPHs since 1565, making using the proxy records mostly from tree rings in Northeast Asia and ice cores from Antarctica. The strength of the NAA is time-varying and it is most conspicuous in the eighteenth century and after the late twentieth century. The strength of the NAA matches well with the variations of the solar radiation and tends to increase in along with its enhancement. In boreal summer, enhanced heating associated with high solar radiation in the Northern Hemisphere drives more air masses from the South to the North. This inter-hemispheric interaction is particularly strong in East Asia as a result of the Asian summer monsoon. Northeast Asia and Antarctica appear to be the key regions responsible for inter-hemispheric interactions on the interdecadal scale in boreal summer since they are respectively located at the front and the end of this inter-hemispheric trajectory.
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