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Surface solar radiation (SSR) is an essential factor in the flow of surface energy, enabling accurate capturing of long-term climate change and understanding of the energy balance of Earth's atmosphere system. However, the long-term trend estimation of SSR is subject to significant uncertainties due to the temporal inhomogeneity and the uneven spatial distribution of in situ observations. This paper develops an observational integrated and homogenized global terrestrial (except for Antarctica) station SSR dataset (SSRIH station) by integrating all available SSR observations, including the existing homogenized SSR results. The series is then interpolated in order to obtain a 5 ∘ × 5 ∘ resolution gridded dataset (SSRIH grid). On this basis, we further reconstruct a long-term (1955–2018) global land (except for Antarctica) SSR anomaly dataset with a 5 ∘ × 2.5 ∘ resolution (SSRIH 20CR) by training improved partial convolutional neural network deep-learning methods based on 20th Century Reanalysis version 3 (20CRv3). Based on this, we analysed the global land- (except for Antarctica) and regional-scale SSR trends and spatiotemporal variations. The reconstruction results reflect the distribution of SSR anomalies and have high reliability in filling and reconstructing the missing values. At the global land (except for Antarctica) scale, the decreasing trend of the SSRIH 20CR (- 1.276 ± 0.205 W m -2 per decade) is smaller than the trend of the SSRIH grid (- 1.776 ± 0.230 W m -2 per decade) from 1955 to 1991. The trend of the SSRIH 20CR (0.697 ± 0.359 W m -2 per decade) from 1991 to 2018 is also marginally lower than that of the SSRIH grid (0.851 ± 0.410 W m -2 per decade). At the regional scale, the difference between the SSRIH 20CR and SSRIH grid is more significant in years and areas with insufficient coverage. Asia, Africa, Europe and North America cause the global dimming of the SSRIH 20CR , while Europe and North America drive the global brightening of the SSRIH 20CR. Spatial sampling inadequacies have largely contributed to a bias in the long-term variation of global and regional SSR. This paper's homogenized gridded dataset and the Artificial Intelligence reconstruction gridded dataset (Jiao and Li, 2023) are both available at 10.6084/m9.figshare.21625079.v1. [ABSTRACT FROM AUTHOR]

Surface solar radiation (SSR) is an essential factor in the flow of surface energy, enabling accurate capturing of long-term climate change and understanding the energy balance of Earth's atmosphere system. However, the long-term trend estimation of SSR is subjected to significant uncertainties due to the temporal inhomogeneity and the uneven spatial distribution of the in-situ observations. This paper develops an observational integrated and homogenized global-terrestrial (except for Antarctica)) stational SSR dataset (SSRIHstation) by integrating all available SSR observations, including the existing homogenized SSR results. The series are then interpolated in order to obtain a 5°×5° resolution gridded dataset (SSRIHgrid). On this basis, we further reconstruct a long-term (1955-2018) global land (except for Antarctica) SSR anomalies dataset with a 5°×2.5° resolution (SSRIH20CR) by training improved partial convolutional neural network deep learning methods based on the reanalysis 20CRv3. Based on this, we analysed the global land (except for Antarctica)/regional scale SSR trends and spatiotemporal variations: the reconstruction results reflect the distribution of SSR anomalies and have high reliability in filling and reconstructing the missing values. At the global land (except for Antarctica) scale, the decreasing trend of the SSRIH20CR (-1.276±0.205 W/m2 per decade) is slightly smaller than the trend of the SSRIHgrid (- 1.776±0.230 W/m2 per decade) from 1955 to 1991. The trend of SSRIH20CR (0.697±0.359 W/m2 per decade) from 1991 to 2018 is also marginally lower than that of the SSRIHgrid (0.851±0.410 W/m2 per decade). At the regional scale, the difference between the SSRIH20CR and SSRIHgrid is more significant in years and areas with insufficient coverage. Asia, Africa, Europe and North America cause the global dimming of the SSRIH20CR, while Europe and North America drive the global brightening of the SSRIH20CR. Spatial sampling inadequacies have largely contributed to a bias in the long-term variation of global/regional SSR. This paper's homogenized gridded dataset and the Artificial Intelligence reconstruction gridded dataset (Jiao and Li, 2023) are all available at. [ABSTRACT FROM AUTHOR]

Reconstructing the history of polar temperature from ice core water isotope (δ18O) calibration has remained a challenge in paleoclimate research, because of our incomplete understanding of various temperature--δ18O relationships. This paper resolves this classical problem in a new framework called the unified slope equations (USE), which illustrates the general relations among spatial and temporal δ18O--surface temperature slopes. The USE is applied to the Antarctica temperature change during the last deglaciation in model simulations and observations. It is shown that the comparable Antarcticamean spatial slope with deglacial temporal slope in δ18O--surface temperature reconstruction is caused, accidentally, by the compensation responses between the δ18O--inversion layer temperature relation and the inversion layer temperature itself. Furthermore, in light of the USE, we propose that the present seasonal slope of δ18O--inversion layer temperature is an optimal paleothermometer that is more accurate and robust than the spatial slope. This optimal slope suggests the possibility of reconstructing past Antarctic temperature changes using present and future instrumental observations. [ABSTRACT FROM AUTHOR]

The analytical solutions of the radiative transfer equation are needed for the solution of various applied atmospheric and snow optics problems. In this paper, we propose a simple analytical equation for the top-of-atmosphere (TOA) spectral reflectance. To simplify the problem under study we consider the case of Antarctica, where both snow and atmosphere are almost free of pollutants. This work is focused on the simulation of the moderate spectral resolution TOA measurements (1 nm or so) and the spectral range 400–1000 nm. The values of the coefficient of variance (CV) between the measured by the Ocean and Land Colour Instrument (OLCI) on board Sentinel-3A and modelled spectra are smaller than 10% for most cases in Antarctica. There are regions in Eastern Antarctica, where the values of CV are smaller than 5%. The areas with larger deviations between measured and retrieved spectra could be due to the presence of clouds or structures on the snow surface not captured by the proposed model. [ABSTRACT FROM AUTHOR]

Remote sensing is a very powerful tool that has been used to identify, map and monitor Antarctic features and processes for nearly one century. Satellite remote sensing plays the main role for about the last five decades, as it is the only way to provide multitemporal views at continental scale. But the emergence of small consumer-grade unoccupied aerial vehicles (UAVs) over the past two decades has paved the way for data in unprecedented detail. This has been also verified by an increasing noticeable interest in Antarctica by the incorporation of UAVs in the field activities in diversified research topics. This paper presents a comprehensive review about the use of UAVs in scientific activities in Antarctica. It is based on the analysis of 190 scientific publications published in peer-reviewed journals and proceedings of conferences which are organised into six main application topics: Terrestrial, Ice and Snow, Fauna, Technology, Atmosphere and Others. The analysis encompasses a detailed overview of the activities, identifying advantages and difficulties, also evaluating future possibilities and challenges for expanding the use of UAV in the field activities. The relevance of using UAVs to support numerous and diverse scientific activities in Antarctica becomes very clear after analysing this set of scientific publications, as it is revolutionising the remote acquisition of new data with much higher detail, from inaccessible or difficult to access regions, in faster and cheaper ways. Many of the advances can be seen in the terrestrial areas (detailed 3D mapping; vegetation mapping, discrimination and health assessment; periglacial forms characterisation), ice and snow (more detailed topography, depth and features of ice-sheets, glaciers and sea-ice), fauna (counting penguins, seals and flying birds and detailed morphometrics) and in atmosphere studies (more detailed meteorological measurements and air-surface couplings). This review has also shown that despite the low environmental impact of UAV-based surveys, the increasing number of applications and use, may lead to impacts in the most sensitive Antarctic ecosystems. Hence, we call for an internationally coordinated effort to for planning and sharing UAV data in Antarctica, which would reduce environmental impacts, while extending research outcomes. [ABSTRACT FROM AUTHOR]

The paper presents reconstructions of the heliospheric modulation potential based on data on the content of the cosmogenic isotope 10Be in the ice layers of Antarctica (Dome Fuji). The calculations involve the use of two models that describe the relationship between the 10Be concentration in layers of ice C with the rate of formation of this isotope in the Earth's atmosphere Q. The first model is described by a linear relationship between these quantities with a constant proportionality coefficient. In the second case, the proportionality coefficient between the concentration C and production rate Q changes over time in the considered model. The differences in the obtained reconstructions of the heliospheric modulation potential from Antarctica data from the reconstruction based on NGRIP data (Greenland) are analyzed. It was shown that the contradictions between the reconstructions can be removed if the dependence of the 10Be concentration in ice layers on the rate of its formation in the Earth's atmosphere changes with time, which may be the result of climate change. Moreover, these dependences may be different for different regions. [ABSTRACT FROM AUTHOR]

The knowledge of polychlorinated naphthalenes (PCNs) in the Antarctic atmosphere is quite limited compared to the Arctic. PCNs are a global concern because of their PBT characteristics (i.e., persistent, bioaccumulative, and toxic) and severe and often deadly biological effects on people and other animals. Therefore, the present study used a passive air sampling method to conduct long-term air monitoring of PCNs for almost a decade from 2013 to 2022, specifically on Fildes Peninsula, situated on King George Island, located in West Antarctica. The median sum of mono-CNs to octa-CN concentration (∑ 75 PCNs) in the Antarctic atmosphere was 12.4 pg/m3. In terms of homologues, mono-CNs to tri-CNs predominated. Among these, the prevalent congeners observed were PCN-1 and PCN-2, originating from mono-CNs, followed by PCN-5/7 from di-CNs, and PCN-24/14 from tri-CNs, respectively. Between 2013 and 2022, the total levels of PCNs were found to have decreased approximately fourfold. Ratio analyses and principal component analysis (PCA) showed that the long-range atmospheric transport and combustion-related sources as the potential PCN sources in the study area. This paper provides the most up-to-date temporal trend analysis of PCNs in the Antarctic continent and is the first to document all 75 congeners (mono-CNs to octa-CN homologue groups). [Display omitted] • This is the first study to report all 75 PCN congeners from the Antarctic continent. • A decreasing temporal trend was observed from 2013 to 2022. • The mono-CNs to tri-CNs consist of the dominating homologues group. • LRAT and combustion-related sources were the primary sources of the study area. [ABSTRACT FROM AUTHOR]