| Ai, S. T., S. S. Wang, Y. S. Li, G. Moholdt, C. X. Zhou, L. B. Liu, and Y. D. Yang, 2019: High-precision ice-flow velocities from ground observations on Dalk Glacier, Antarctica. Polar Science, 19, 13−23, https://doi.org/10.1016/j.polar.2018.09.003. |
| Aun, M., and Coauthors, 2020: Solar UV radiation measurements in Marambio, Antarctica, during years 2017−2019. Atmospheric Chemistry and Physics, 20, 6037−6054, https://doi.org/10.5194/acp-20-6037-2020. |
| Bian, L. G., L. H. Lu, C. G. Lu, Z. F. Xue, P. Q. Jia, and Y. Wang, 1998: A study of radiative features at the Great Wall and Zhongshan Stations of Antarctica. Quarterly Journal of Applied Meteorology, 9, 160−168. (in Chinese with English abstract |
| Bintanja, R., 1995: The local surface energy balance of the ecology glacier, King George Island, Antarctica: Measurements and modelling. Antarctic Science, 7(3), 315−325, https://doi.org/10.1017/S0954102095000435. |
| Braun, M., and R. Hock, 2004: Spatially distributed surface energy balance and ablation modelling on the ice cap of King George Island (Antarctica). Global and Planetary Change, 42, 45−58, https://doi.org/10.1016/j.gloplacha.2003.11.010. |
| Che, H. Z., G. Y. Shi, X. Y. Zhang, R. Arimoto, J. Q. Zhao, L. Xu, B. Wang, and Z. H. Chen, 2005: Analysis of 40 years of solar radiation data from China, 1961−2000. Geophys. Res. Lett., 32, L06803, https://doi.org/10.1029/2004GL022322. |
| Che, H. Z., and Coauthors, 2019: Large contribution of meteorological factors to inter-decadal changes in regional aerosol optical depth. Atmospheric Chemistry and Physics, 19, 10497−10523, https://doi.org/10.5194/acp-2019-360. |
| Chen, C., Q. M. Zhang, Q. Ma, and B. Yu, 2019: LightGBM-PPI: Predicting protein-protein interactions through LightGBM with multi-information fusion. Chemometrics and Intelligent Laboratory Systems, 191, 54−64, https://doi.org/10.1016/j.chemolab.2019.06.003. |
| Chen, G., Y. C. Wang, S. S. Li, W. Cao, H. Y. Ren, L. D. Knibbs, M. J. Abramson, and Y. M. Guo, 2018: Spatiotemporal patterns of PM10 concentrations over China during 2005−2016: A satellite-based estimation using the random forests approach. Environmental Pollution, 242, 605−613, https://doi.org/10.1016/j.envpol.2018.07.012. |
| Chen, J.-L., G.-S. Li, and S.-J. Wu, 2013: Assessing the potential of support vector machine for estimating daily solar radiation using sunshine duration. Energy Conversion and Management, 75, 311−318, https://doi.org/10.1016/j.enconman.2013.06.034. |
| Chen, Y. M., C. X. Zhou, S. T. Ai, Q. Liang, L. Zheng, R. X. Liu, and H. B. Lei, 2020: Dynamics of Dalk Glacier in East Antarctica derived from multisource satellite observations since 2000. Remote Sensing, 12, 1809, https://doi.org/10.3390/rs12111809. |
| Choi, T. I., S.-J. Kim, J. H. Kim, H. Kwon, and M. A. Lazzara, 2019: Characteristics of surface meteorology at Lindsey Islands, Amundsen Sea, West Antarctica. J. Geophys. Res., 124, 6294−6306, https://doi.org/10.1029/2018JD029556. |
| Cortes, C., and V. Vapnik, 1995: Support-vector networks. Machine Learning, 20, 273−297, https://doi.org/10.1023/A:1022627411411. |
| Ding, M. H., D. Y. Yang, M. R. Van Den Broeke, I. Allison, C. D. Xiao, D. H. Qin, and B. J. Huai, 2020: The surface energy balance at Panda 1 station, Princess Elizabeth Land: A typical katabatic wind region in East Antarctica. J. Geophys. Res., 125, e2019JD030378, https://doi.org/10.1029/2019JD030378. |
| Dou, Y. K., G. Y. Zuo, X. M. Chang, and Y. Chen, 2019: A study of a standalone renewable energy system of the Chinese Zhongshan station in Antarctica. Applied Sciences, 9, 1968, https://doi.org/10.3390/app9101968. |
| Garbe, J., T. Albrecht, A. Levermann, J. F. Donges, and R. Winkelmann, 2020: The hysteresis of the Antarctic Ice Sheet. Nature, 585, 538−544, https://doi.org/10.1038/s41586-020-2727-5. |
| Gui, K., and Coauthors, 2019: Satellite-derived PM2.5 concentration trends over Eastern China from 1998 to 2016: Relationships to emissions and meteorological parameters. Environmental Pollution, 247, 1125−1133, https://doi.org/10.1016/j.envpol.2019.01.056. |
| Gui, K., and Coauthors, 2020: Construction of a virtual PM2.5 observation network in China based on high-density surface meteorological observations using the Extreme Gradient Boosting model. Environment International, 141, 105801, https://doi.org/10.1016/j.envint.2020.105801. |
| Guo, J. P., and Coauthors, 2017: Declining frequency of summertime local-scale precipitation over eastern China from 1970 to 2010 and its potential link to aerosols. Geophys. Res. Lett., 44, 5700−5708, https://doi.org/10.1002/2017GL073533. |
| He, Y. Y., and K. C. Wang, 2020: Variability in direct and diffuse solar radiation across China from 1958 to 2017. Geophys. Res. Lett., 47, e2019GL084570, https://doi.org/10.1029/2019GL084570. |
| He, Y. Y., K. C. Wang, C. L. Zhou, and M. Wild, 2018: A revisit of global dimming and brightening based on the sunshine duration. Geophys. Res. Lett., 45, 4281−4289, https://doi.org/10.1029/2018GL077424. |
| Huang, G. H., M. G. Ma, S. L. Liang, S. M. Liu, and X. Li, 2011: A LUT-based approach to estimate surface solar irradiance by combining MODIS and MTSAT data. J. Geophys. Res., 116(D22), D22201, https://doi.org/10.1029/2011JD016120. |
| Jaross, G., and J. Warner, 2008: Use of Antarctica for validating reflected solar radiation measured by satellite sensors. J. Geophys. Res., 113, D16S34, https://doi.org/10.1029/2007JD008835. |
| Jiang, Y. N., 2009: Computation of monthly mean daily global solar radiation in China using artificial neural networks and comparison with other empirical models. Energy, 34, 1276−1283, https://doi.org/10.1016/j.energy.2009.05.009. |
| Ke, G. L., Q. Meng, T. Finley, T. F. Wang, W. Chen, W. D. Ma, Q. W. Ye, and T.-Y. Liu, 2017: LightGBM: A highly efficient gradient boosting decision tree. Proc. 31st Int. Conf. on Neural Information Processing Systems, Long Beach, NIPS, 3146−3154. |
| Lacelle, D., C. Lapalme, A. F. Davila, W. Pollard, M. Marinova, J. Heldmann, and C. P. McKay, 2016: Solar radiation and air and ground temperature relations in the cold and hyper-arid Quartermain Mountains, McMurdo Dry Valleys of Antarctica. Permafrost and Periglacial Processes, 27, 163−176, https://doi.org/10.1002/ppp.1859. |
| Ohmura, A., 2009: Observed decadal variations in surface solar radiation and their causes. J. Geophys. Res., 114, D00D05, https://doi.org/10.1029/2008JD011290. |
| Park, S.-J., T.-J. Choi, and S.-J. Kim, 2013: Heat flux variations over sea ice observed at the coastal area of the sejong station, Antarctica. Asia-Pacific Journal of Atmospheric Sciences, 49, 443−450, https://doi.org/10.1007/s13143-013-0040-z. |
| Qin, J., Z. Q. Chen, K. Yang, S. L. Liang, and W. J. Tang, 2011: Estimation of monthly-mean daily global solar radiation based on MODIS and TRMM products. Applied Energy, 88, 2480−2489, https://doi.org/10.1016/j.apenergy.2011.01.018. |
| Quinlan, J., 1986: Induction of decision trees. Machine Learning, 1, 81−106, https://doi.org/10.1023/A:1022643204877. |
| Scott, R. C., D. Lubin, A. M. Vogelmann, and S. Kato, 2017: West Antarctic ice sheet cloud cover and surface radiation budget from NASA A-Train satellites. J. Climate, 30, 6151−6170, https://doi.org/10.1175/JCLI-D-16-0644.1. |
| Soares, J., M. Alves, F. N. D. Ribeiro, and G. Codato, 2019: Surface radiation balance and weather conditions on a non-glaciated coastal area in the Antarctic region. Polar Science, 20, 117−128, https://doi.org/10.1016/j.polar.2019.04.001. |
| Stanhill, G., and S. Cohen, 1997: Recent changes in solar irradiance in Antarctica. J. Climate, 10, 2078−2086, https://doi.org/10.1175/1520-0442(1997)010<2078:RCISII>2.0.CO;2. |
| Tang, W. J., K. Yang, J. He, and J. Qin, 2010: Quality control and estimation of global solar radiation in China. Solar Energy, 84, 466−475, https://doi.org/10.1016/j.solener.2010.01.006. |
| Tang, W.-J., K. Yang, J. Qin, C. C. K. Cheng, and J. He, 2011: Solar radiation trend across China in recent decades: A revisit with quality-controlled data. Atmospheric Chemistry and Physics, 11, 393−406, https://doi.org/10.5194/acp-11-393-2011. |
| Tang, W. J., K. Yang, J. Qin, and M. Min, 2013: Development of a 50-year daily surface solar radiation dataset over China. Science China Earth Sciences, 56, 1555−1565, https://doi.org/10.1007/s11430-012-4542-9. |
| Tang, W. J., K. Yang, J. Qin, M. Min, and X. L. Niu, 2018: First effort for constructing a direct solar radiation data set in china for solar energy applications. J. Geophys. Res., 123, 1724−1734, https://doi.org/10.1002/2017JD028005. |
| Wang, G. C., and X. Z. Xiong, 1991: Analysis of some characteristics of solar radiation at Zhongshan Station, Antarctica. Antarctic Research, 3, 64−68. (in Chinese with English abstract |
| Wang, L. C., O. Kisi, M. Zounemat-Kermani, G. A. Salazar, Z. M. Zhu, and W. Gong, 2016: Solar radiation prediction using different techniques: Model evaluation and comparison. Renewable and Sustainable Energy Reviews, 61, 384−397, https://doi.org/10.1016/j.rser.2016.04.024. |
| Wang, R. H., 2012: AdaBoost for feature selection, classification and its relation with SVM, a review. Physics Procedia, 25, 800−807, https://doi.org/10.1016/j.phpro.2012.03.160. |
| Wang, Y. W., and M. Wild, 2016: A new look at solar dimming and brightening in China. Geophys. Res. Lett., 43, 11777−11785, https://doi.org/10.1002/2016GL071009. |
| Wen, J., J. L. Zhao, S. W. Luo, and Z. Han, 2002: The improvements of BP neural network learning algorithm. Proc. 5th Int. Conf. on Signal Processing Proceedings. 16th World Computer Congress 2000, Beijing, IEEE, 1647−1649, https://doi.org/10.1109/ICOSP.2000.893417. |
| Wild, M., 2009: Global dimming and brightening: A review. J. Geophys. Res., 114, D00D16, https://doi.org/10.1029/2008JD011470. |
| Wild, M., and Coauthors, 2005: From dimming to brightening: Decadal changes in solar radiation at Earth’s surface. Science, 308, 847−850, https://doi.org/10.1126/science.1103215. |
| Xue, W. T., and Coauthors, 2019: Declining diurnal temperature range in the North China Plain related to environmental changes. Climate Dyn., 52, 6109−6119, https://doi.org/10.1007/s00382-018-4505-8. |
| Yang, Y. K., S. P. Palm, A. Marshak, D. L. Wu, H. B. Yu, and Q. Fu, 2014: First satellite-detected perturbations of outgoing longwave radiation associated with blowing snow events over Antarctica. Geophys. Res. Lett., 41, 730−735, https://doi.org/10.1002/2013GL058932. |
| Yu, L., and Coauthors, 2019: The variability of surface radiation fluxes over landfast sea ice near Zhongshan Station, east Antarctica during austral spring. International Journal of Digital Earth, 12, 860−877, https://doi.org/10.1080/17538947.2017.1304458. |
| Zelterman, D., 2015: Applied Multivariate Statistics with R. Springer, 393 pp, https://doi.org/10.1007/978-3-319-14093-3. |
| Zeng, Z. L., and Coauthors, 2020: Daily global solar radiation in china estimated from high-density meteorological observations: A random forest model framework. Earth and Space Science, 7, e2019EA001058, https://doi.org/10.1029/2019EA001058. |
| Zhang, T., C. X. Zhou, and L. Zheng, 2019: Analysis of the temporal−spatial changes in surface radiation budget over the Antarctic sea ice region. Science of the Total Environment, 666, 1134−1150, https://doi.org/10.1016/j.scitotenv.2019.02.264. |
| Zhang, X. T., S. L. Liang, G. X. Wang, Y. J. Yao, B. Jiang, and J. Cheng, 2016: Evaluation of the reanalysis surface incident shortwave radiation products from NCEP, ECMWF, GSFC, and JMA using satellite and surface observations. Remote Sensing, 8, 225, https://doi.org/10.3390/rs8030225. |