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A Big Earth Data Platform for Three Poles

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Zhang, D.J., Xia, H., Chen, F.H., Li, B., Slon, V., Cheng, T., Yang, R.W., Jacobs, Z.B., Dai, Q.Y., Massilani, D., Shen, X.K., Wang, J., Feng, X.T., Cao, P., Yang, M.A., Yao, J.T., Yang, J.S., Madsen, D.B., Han, Y.Y., Ping, W.J., Liu, F., Perreault, C., Chen, X.S., Meyer, M., Kelso, J., Pääbo, S., & Fu, Q.M. (2020). Denisovan DNA in Late Pleistocene sediments from Baishiya Karst Cave on the Tibetan Plateau. Science, 370, 584-587.
Ma, Y., Wang, Y., Wu, R., Hu, Z., Yang, K., & Li, M., et al. (2009). Recent advances on the study of atmosphere-land interaction observations on the tibetan plateau. Hydrology and Earth System Sciences, 13(7), 1103-1111.
Han, C.T., Chen, R.S., Liu, Z.W., Yang, Y., Liu, J.F., Song, Y.X., Wang, L., Liu, G.H., Guo, S.H.,, & Wang, X.Q. (2018). Cryospheric Hydrometeorology Observation in the Hulu Catchment (CHOICE), Qilian Mountains, China. Vadose Zone Journal, 17(1), 1-18.
Guo,W.Q., Liu, S.Y., Xu, L., Wu, L.Z., Shangguan, D.H., Yao, X.J., Wei, J.F., Bao, W.J., Yu, P.C., Liu, Q., & Jiang, Z.L. (2015). The second Chinese glacier inventory: data, methods and results. Journal of Glaciology, 61(226), 357-372.
Feng,X.L, Wu,B.F,Yan,N.N, Zhu,W.W. Method to derived mixed boundary layer height from MODIS atmospheric profile data product at Heihe river basin. Boundary-layer Meteorology. Under Review.
SUN Jia, JIANG Hao, et al. (2011).The Fine Spatial Distribution of Mean Precipitation and the Estimation of Total Precipitation in Heihe River Basin[J]. Journal of Glaciology and Geocryology, 33(2):318-324
Xu, Z.W., Ma, Y.F., Liu, S.M., Shi, S.J., &Wang, J.M. (2017). Assessment of the energy balance closure under advective conditions and its impact using remote sensing data. Journal of Applied Meteorology and Climatology, 56, 127-140.
Anomalies (unusual patterns) in time-series data give essential, and often actionable information in critical situations. Examples can be found in such fields as healthcare, intrusion detection, finance, security and flight safety. In this paper we propose new conformalized density- and distance-based anomaly detection algorithms for a one-dimensional time-series data. The algorithms use a combination of a feature extraction method, an approach to assess a score whether a new observation differs significantly from a previously observed data, and a probabilistic interpretation of this score based on the conformal paradigm.
Ma, Y.M., Menenti, M., Feddes, R., & Wang, J. (2008). Analysis of the land surface heterogeneity and its impact on atmospheric variables and the aerodynamic and thermodynamic roughness lengths. Journal of Geophysical Research: Atmospheres, 113.
Yu, G.R., Zhu, X.J., Fu, Y.L., He, H.L., Wang, Q.F., Wen, X.F., Li, X.R., Zhang, L.M., Zhang, L., Su, W., Li, S.G., Sun, X.M., Zhang, Y.P., Zhang, J.H., Yan, J.H., Wang, H.M., Zhou, G.S., Jia, B.R., Xiang, W.H., Li, Y.N., Zhao, L., Wang, Y.F., Shi, P.L., Chen, S.P., Zhao, F.H., Wang, Y.Y., & Tong, C.L. (2013). Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China. Global Change Biology, 19, 798–810.

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