Journal cover Journal topic
Earth System Science Data The data publishing journal
Journal topic

Journal metrics

Journal metrics

  • IF value: 10.951 IF 10.951
  • IF 5-year value: 9.899 IF 5-year
    9.899
  • CiteScore value: 9.74 CiteScore
    9.74
  • SNIP value: 3.111 SNIP 3.111
  • IPP value: 8.99 IPP 8.99
  • SJR value: 5.229 SJR 5.229
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 38 Scimago H
    index 38
  • h5-index value: 33 h5-index 33
ESSD | Articles | Volume 11, issue 4
Earth Syst. Sci. Data, 11, 1711–1744, 2019
https://doi.org/10.5194/essd-11-1711-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Earth Syst. Sci. Data, 11, 1711–1744, 2019
https://doi.org/10.5194/essd-11-1711-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  21 Nov 2019

21 Nov 2019

WHU-SGCC: a novel approach for blending daily satellite (CHIRP) and precipitation observations over the Jinsha River basin

Gaoyun Shen et al.
Related subject area  
Atmosphere – Meteorology
A new merge of global surface temperature datasets since the start of the 20th century
Xiang Yun, Boyin Huang, Jiayi Cheng, Wenhui Xu, Shaobo Qiao, and Qingxiang Li
Earth Syst. Sci. Data, 11, 1629–1643, https://doi.org/10.5194/essd-11-1629-2019,https://doi.org/10.5194/essd-11-1629-2019, 2019
Short summary
seNorge_2018, daily precipitation, and temperature datasets over Norway
Cristian Lussana, Ole Einar Tveito, Andreas Dobler, and Ketil Tunheim
Earth Syst. Sci. Data, 11, 1531–1551, https://doi.org/10.5194/essd-11-1531-2019,https://doi.org/10.5194/essd-11-1531-2019, 2019
Short summary
1-km monthly temperature and precipitation dataset for China from 1901–2017
Shouzhang Peng, Yongxia Ding, and Zhi Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-145,https://doi.org/10.5194/essd-2019-145, 2019
Revised manuscript accepted for ESSD
Short summary
FROGS: a daily 1°  ×  1° gridded precipitation database of rain gauge, satellite and reanalysis products
Rémy Roca, Lisa V. Alexander, Gerald Potter, Margot Bador, Rômulo Jucá, Steefan Contractor, Michael G. Bosilovich, and Sophie Cloché
Earth Syst. Sci. Data, 11, 1017–1035, https://doi.org/10.5194/essd-11-1017-2019,https://doi.org/10.5194/essd-11-1017-2019, 2019
Short summary
A unified data set of airborne cloud remote sensing using the HALO Microwave Package (HAMP)
Heike Konow, Marek Jacob, Felix Ament, Susanne Crewell, Florian Ewald, Martin Hagen, Lutz Hirsch, Friedhelm Jansen, Mario Mech, and Bjorn Stevens
Earth Syst. Sci. Data, 11, 921–934, https://doi.org/10.5194/essd-11-921-2019,https://doi.org/10.5194/essd-11-921-2019, 2019
Short summary
Cited articles  
AghaKouchak, A., Behrangi, A., Sorooshian, S., Hsu, K., and Amitai, E.: Evaluation of satellite-retrieved extreme precipitation rates across the central United States, J. Geophys. Res.-Atmos., 116, D02115, https://doi.org/10.1029/2010jd014741, 2011. 
Agutu, N. O., Awange, J. L., Zerihun, A., Ndehedehe, C. E., Kuhn, M., and Fukuda, Y.: Assessing multi-satellite remote sensing, reanalysis, and land surface models' products in characterizing agricultural drought in East Africa, Remote Sens. Environ., 194, 287–302, https://doi.org/10.1016/j.rse.2017.03.041, 2017. 
Ali, H. and Mishra, V.: Contrasting response of rainfall extremes to increase in surface air and dewpoint temperatures at urban locations in India, Sci. Rep.-UK, 7, 1228, https://doi.org/10.1038/s41598-017-01306-1, 2017. 
Anders, A. M., Roe, G. H., Hallet, B., Montgomery, D. R., Finnegan, N. J., and Putkonen, J.: Spatial patterns of precipitation and topography in the Himalaya, Tectonics, Climate, and Landscape Evolution, 398, 39–53, https://doi.org/10.1130/2006.2398(03), 2006. 
Aonashi, K., Awaka, J., Hirose, M., Kozu, T., Kubota, T., Liu, G., Shige, S., Kida, S., Seto, S., Takahashi, N., and Takayabu, Y. N.: GSMaP Passive Microwave Precipitation Retrieval Algorithm: Algorithm Description and Validation, J. Meteorol. Soc. Jpn., 87, 119–136, https://doi.org/10.2151/jmsj.87A.119, 2009. 
Download
Short summary
The development of effective methods for high-accuracy precipitation estimates over complex terrain and on a daily scale is important for mountainous hydrological applications. This study offers a novel approach called WHU-SGCC by blending rain gauge and satellite data to estimate daily precipitation at 0.05° resolution over the Jinsha River basin, the complicated mountainous terrain with sparse rain gauge data, considering the spatial correlation and historical precipitation characteristics.
The development of effective methods for high-accuracy precipitation estimates over complex...
Citation