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The atmospheric carbon dioxide (CO2) concentration has been increasing rapidly since the Industrial Revolution, which has led to unequivocal global warming and crucial environmental change. It is extremely important to investigate the interactions among atmospheric CO2, the physical climate system, and the carbon cycle of the underlying surface for a better understanding of the Earth system. Earth system models are widely used to investigate these interactions via coupled carbon-climate simulations. The Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2.0) has successfully fixed a two-way coupling of atmospheric CO2 with the climate and carbon cycle on land and in the ocean. Using CAS-ESM2.0, we conducted a coupled carbon-climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment. This paper examines the modeled CO2 by comparison with observed CO2 at the sites of Mauna Loa and Barrow, and the Greenhouse Gases Observing Satellite (GOSAT) CO2 product. The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO2 during the period 1850–2014, and in capturing the seasonal cycle of CO2 at the two baseline sites, as well as over northern high latitudes. These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon-climate interactions, even though uncertainties remain in the processes involved. This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate, which will provide significant scientific support for climate research and China's goal of carbon neutrality. [ABSTRACT FROM AUTHOR]

Many regions around the world are facing climate changes, with substantial increase in air temperature over the past decades, which is mainly related to continental and global warming forced by the higher greenhouse gas (GHG) emissions. The objectives of this study were to use the Köppen climate classification to detect local climate change based on a historical series of 100 years and to assess if such change is related to those that are occurring in other spatial scales as a likely consequence of increasing GHG. This paper brings a content full of innovative results. The study area presented an average annual air temperature increase by 0.9 °C between 1917 and 2016, rising from 21.4 °C for the first climatological normal (1917–1946) to 22.3 °C for the last one (1987–2016). Furthermore, in the summer months, the temperature rose from 24.5 to 25.3 °C, and in the winter months, such increase was from 17.1 (1917–1946) to 18.3 °C (1987–2016). Our findings showed the subtropical conditions (Cfa in Köppen's classification) in the study area persisted from the beginning of the analysis (1917–1946) until the climatological normal of 1979–2008, with a clear tendency of tropicalization after that with a change in the climate type of Piracicaba from subtropical to tropical, which can now be classified as tropical with dry winter (Aw climate type). The local average air temperature showed concordances with the long-term air temperature anomalies from regional, continental, and global scales, indicating that all of them may be linked with increasing GHG emissions, since well-defined long-term linear relationships (r2 = 0.99) were observed between continental and global average air temperature anomalies and atmospheric CO2 concentration observed at the NOAA Lab in Mauna Loa in the last 59 years. While the local and regional forcing effects remain to be fully unraveled, our study provided a valid and strong scientific sound evidence that climate change occurred in Piracicaba, southeastern Brazil, in the last 100 years. [ABSTRACT FROM AUTHOR]

We show that the terrestrial land and seafloor contain no volcano-tectonic mega landforms expressed in relief that could be similar in size to those identified on Mars, and could have analogous structure and origin to the giant landforms whose volumes of constituent rocks are (1‒2.4) × 106 km3 (Alba Patera, Olympus Mons, Arsia Mons, Ascraeus Mons, Pavonis Mons, and Elysium Mons). No fragments or traces of similar features have ever been unambiguously identified and described in geological rock sequences, not only in Mesozoic and Cenozoic rock sequences, but also in those dating back to Paleozoic time. The same applies to the older epochs on Earth. Now the topographic constituent components of Martian mega landforms have the appearance of very magnified copies of well-known and repeatedly described terrestrial volcanic edifices, viz., dominantly shield-like and lava volcanoes, lava domes, as well as calderas of various types. However, the edifices of the above types of volcanoes are not identical with their Martian counterparts as to morphology, being shorter in height and having steeper slopes. The calderas are smaller by factors of multiple times. The Martian volcanic landforms are much older. There is a unique edifice, namely, Olympus Mons, a mega landform that stands in a large glacier sheet and for whose origin glacial processes are also responsible. It is classified as belonging to the type of giant tuyas. Its mini analogues are glacial subaerial tuyas of different ages and parameters that have been subjected to glaciation in volcanic areas on Earth. [ABSTRACT FROM AUTHOR]

An adaptive model is proposed to describe time-varying seasonal effects. The seasonal average function is constructed using an iterative algorithm that provides a neat decomposition of the signal into a generalized trend, seasonal and residual components. By a trend, we mean long-term evolutionary changes in the average signal level, both unidirectional and chaotic, in the form of a slow random drift. This algorithm allows one to obtain unbiased estimates for each of the signal components, even in the presence of a significant number of missing observations. The series length is not required to be a multiple of an integer number of years. In contrast to the usual "Climate Normals" (CN) model, the considered adaptive model of seasonal effects assumes a continuous slow change in the properties of the seasonal component over time. The degree of allowable variability in seasonal effects from year to year is entered as a tunable parameter of the model. In particular, this allows one to show the dynamics of the growth of the amplitude of seasonal fluctuations in time in the form of a continuous (smooth) function without necessarily linking these changes to predetermined calendar epochs. The algorithm was tested on the atmospheric CO2 concentration monitoring series at Barrow, Mauna Loa, Tutuila, and South Pole stations located at different latitudes. The form of the seasonal variation was estimated, and the average amplitude of the seasonal variation and the rate of its change at each station were calculated. Noticeable differences in the dynamics of the studied parameters between stations are demonstrated. Mean amplitude of seasonal variation in CO2 concentration at Barrow, Mauna Loa, Tutuila, and South Pole stations in the epoch 2010–2019 was estimated as 18.15, 7.08, 1.30, and 1.26 ppm, respectively, and the average rate of increase in the amplitude of the seasonal variation in the increase in CO2 concentration in the interval 1976–2019 is 0.085, 0.0100, 0.0165, and 0.0031 ppm/year. In relative terms, the increase is 0.57 ± 0.03, 0.11 ± 0.02, 2.24 ± 0.24, and 0.27 ± 0.04% per year. [ABSTRACT FROM AUTHOR]

The contrasting dynamics between Mauna Loa and Kīlauea have been studied over the last 100 years from multiple viewpoints. The fact that dynamic changes of one volcano trigger a dynamic response of the other volcano indicates a connection may exist. Petrological works show a direct relationship between the magmatic systems of these two volcanoes is not possible. We analysed DInSAR data and GPS measurements of ground deformation patterns associated with the activity of Mauna Loa and Kīlauea volcanoes. The DInSAR SBAS dataset spans the interval between 2003 and 2010, and was acquired along ascending and descending orbits of the ENVISAT (ESA) satellite under different look angles. Of the 10 tracks that cover the Big Island (Hawai'i), 4 cover both volcanic edifices. Using GPS measurements, we computed the areal strain on 15 triplets of stations for Kīlauea volcano and 11 for Mauna Loa volcano. DInSAR data was analysed by applying Independent Component Analysis (ICA) to decompose the time-varying ground deformation pattern of both volcanoes. The results revealed anticorrelated ground deformation behaviour of the main calderas of Mauna Loa and Kīlauea, meaning that the opposite response is seen in the ground deformation of one volcano with respect to the other. At the same time, Kīlauea exhibits a more complex pattern, with an additional component, which appears not to be correlated with the dynamics of Mauna Loa. The GPS areal strain time series support these findings. To corroborate and help interpret the results, we performed inverse modelling of the observed ground deformation pattern using analytical source models. The results indicate that the ground deformation of Mauna Loa is associated with a dike-shaped source located at 6.2 km depth. In comparison, the anticorrelated ground deformation of Kīlauea is associated with a volumetric source at 1.2 km depth. This excludes a hydraulic connection as a possible mechanism to explain the anticorrelated behaviour; instead, we postulate a stress-transfer mechanism. To support this hypothesis, we performed a 3D numerical modelling of stress and strain fields in the study area, determining the elastic interaction of each source over the others. The most relevant finding is that the Mauna Loa shallow plumbing system can affect the shallowest magmatic reservoir of Kīlauea, while the opposite scenario is unlikely. Conversely, the second independent component observed at Kīlauea is associated to a sill-shaped source located at a depth of 3.5 km, which is less affected by this interaction process. [ABSTRACT FROM AUTHOR]