go through: Professor Keith Haines and Samantha Petch
atmospheric carbon dioxide2 Carbon dioxide concentrations are rising every year, mainly due to human activities, Figure 1.2 absorbed by terrestrial ecosystems.
Figure 1. Recent changes in atmospheric carbon dioxide concentration. Interannual variation is almost visible.
The ability of land to absorb carbon dioxide2 Determined by the balance between photosynthesis and respiration, it is the least understood part of the global carbon cycle. this land Carbon sinks play a vital role in offsetting anthropogenic CO2 emissions2 emissions, accounting about 30 ±10% of annual emissions (Friedlingstein et al., 2020). Controls of this land surface carbon sink remain poorly understood and will have significant consequences for future CO22 growth rates (CGR) if they change significantly. The CGR increases significantly during El Niño events and decreases significantly during La Niña events (Keeling and Revelle, 1985), and it is generally believed that changes in tropical ecosystems have the most significant impact on global CGR.
Tropical temperatures are shows a strong positive correlation with CGR (Wang et al., 2013), and given that tropical temperatures are generally considered optimal for photosynthesis, any increase in these temperatures is likely to amplify CGR under global warming. However, recently it has been recognized that water availability also plays a very important role, see Figure 2.
Figure 2 shows the detrended interannual variability of atmospheric CGR in black and total land water storage (TWS on the reverse axis) in blue, as measured by the GRACE satellite, which transmits the mass of the Earth's surface Redistribution to detect water (from Petch et al. following Humphreys et al. 2018, 2024).
less water on land, such as during El Niñono In 2015/6, atmospheric concentration increased rapidly carbon monoxide2 With reduced absorption from land surfaces. This absorption range (up to 4GtC/year) is very large and to better understand this relationship we really need to regionalize the surface response, see Figure 3.
Figure 3 shows the regional interannual correlation of GRACE surface water storage and global CGR (Petch et al., 2024).
Page et al. (2024) found that the tropics alone can explain the entire global TWS-CGR relationship shown in Figure 2, with only minor offsetting contributions from the temperate regions of the Northern and Southern Hemispheres. Furthermore, tropical forests (e.g., Amazonia) were found to be the dominant land cover type controlling this relationship, despite occupying only a relatively small portion of the land surface. While the negative correlation in Figure 3 (and other evidence) shows the importance of the tropics in the global relationship shown in Figure 2, it is also important to have direct regional surface CO2 Flux data to support this.
Having a verifiable method to compare surface CO2 fluxes is of course of the highest scientific and political importance. At present, anthropogenic carbon dioxide emissions in various countries rely on national inventories, which are difficult to verify or compare. Atmospheric carbon dioxide mixes relatively quickly, at least at the hemispheric level, so only frequent and reliable satellite-based atmospheric measurements have a chance of achieving this, such as ESA's CO2M-(A,B ,C) Multi-satellite mission/6. At the same time, less frequent satellite measurements, such as GOSAT (since 2009), can be assimilated into atmospheric transport models, which can then be used to infer surface sources and sinks that best match observed atmospheric CO2 concentrations. Given the importance of these estimates, many groups have produced such surface CO flux products, although many still rely solely on in situ measurements and there are many disagreements between regional results (Fig. 4).
Figure 4 shows the percentage contribution of four atmospheric CO2 retrieval model products to the interannual variability of global terrestrial carbon fluxes from 2001 to 2023. Note that the NISMON-CO2 map is drawn over a larger area due to the larger contribution of tropical forests. According to Petch et al., although these products agree well with the global CGR in Figure 2, rather poor regional agreement can be seen. (2024).
We believe it is possible to introduce more satellite-based information from the land surface, such as the GRACE water data shown earlier, and perhaps other data sets such as ESA's Climate Change Initiative land surface temperature measurements (https://climate.esa.int/en/projects/land-surface-Temperature/), providing additional constraints on these atmospheres carbon monoxide2 transport models and bring greater confidence to space-based area estimates carbon monoxide2 flux. This will help improve understanding of ecosystem responses to climate change and provide better validation tools to monitor anthropogenic emissions in a more verifiable way.
refer to
Friedlingstein, P., O'Sullivan, M., Jones, MW, Andrew, RM, Hauck, J., Olsen, A.,. . . Zaller, S. (2020). Global carbon budget 2020. science. Data, 12, 3269–3340. https://doi.org/10.5194/essd-12-3269-2020
Humphrey, V., Zscheischler, J., Ciais, P., Gudmundsson, L., Sitch, S., & Seneviratne, SI (2018). Sensitivity of atmospheric carbon dioxide growth rates to observed changes in terrestrial water storage. Nature, 560, 628–631. https://doi.org/10.1038/s41586-018-0424-4
Keeling, C. D., and Revell, R. (1985). Effects of El Niño/Southern Oscillation on atmospheric carbon dioxide levels. Meteorology, 20, 437-450. https://doi.org/10.1093/nsr/nwab150
Petch, S., Feng, L., Palmer, P. King, RP, Quaife, T. and Haines, K. (2024) Close relationships between atmospheric carbon dioxide growth rates and tropical forest terrestrial water storage on interannual time scales . Submitted to Glob. Biogeochemistry. cycle. There is also the ESS open archive. https://doi.org/10.22541/essoar.172132358.83519012/v1
Wang, W., Ciais, P., Nemani, RR, Canadell, JG, Piao, S., Sitch, S., . . ., Maineni, R.B. (2013). Changes in atmospheric carbon dioxide growth rate and tropical temperature. process. National Academy of Sciences. Science, 110, 13061–13066. https://doi.org/10.1073/pnas.1219683110
