Open Access
MATEC Web Conf.
Volume 246, 2018
2018 International Symposium on Water System Operations (ISWSO 2018)
Article Number 01096
Number of page(s) 5
Section Main Session: Water System Operations
Published online 07 December 2018
  1. Wang, C., et al., Global intercomparison and regional evaluation of GPM IMERG Version-03, Version-04 and its latest Version-05 precipitation products: Similarity, difference and improvements. Journal of Hydrology, 564: p. 342-356, (2018) [CrossRef] [Google Scholar]
  2. Tang, G., et al., Similarities and differences between three coexisting spaceborne radars in global rainfall and snowfall estimation. Water Resources Research, 53(5): p. 3835-3853, (2017) [CrossRef] [Google Scholar]
  3. Foelsche, U., et al., Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria. Hydrology and Earth System Sciences, 21(12): p. 6559-6572, (2017) [CrossRef] [Google Scholar]
  4. Worqlul, A.W., et al., Comparison of rainfall estimations by TRMM 3B42, MPEG and CFSR with ground-observed data for the Lake Tana basin in Ethiopia. Hydrology and Earth System Sciences, 18(12): p. 4871-4881, (2014) [CrossRef] [Google Scholar]
  5. Yang, Z., et al., Bias adjustment of satellite‐based precipitation estimation using gauge observations: A case study in Chile. Journal of Geophysical Research: Atmospheres, 121(8): p. 3790-3806, (2016) [CrossRef] [Google Scholar]
  6. Condom, T., P. Rau and J.C. Espinoza, Correction of TRMM 3B43 monthly precipitation data over the mountainous areas of Peru during the period 1998– 2007. Hydrological Processes, 25(12): p. 1924-1933, (2011) [CrossRef] [Google Scholar]
  7. Habib, E., et al., Effect of bias correction of satelliterainfall estimates on runoff simulations at the source of the Upper Blue Nile. Remote Sensing, 6(7): p. 6688-6708, (2014) [CrossRef] [Google Scholar]
  8. Worqlul, A.W., et al., Performance of bias corrected MPEG rainfall estimate for rainfall-runoff simulation in the upper Blue Nile Basin, Ethiopia. Journal of Hydrology, 556: p. 1182-1191, (2018) [CrossRef] [Google Scholar]
  9. Vernimmen, R., et al., Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia. Hydrology and Earth System Sciences, 16(1): p. 133-146, (2012) [CrossRef] [Google Scholar]
  10. Shin, J., et al., Bias correction of RCM outputs using mixture distributions under multiple extreme weather influences. Theoretical and Applied Climatology, 2018: p. 1-16, (2018) [Google Scholar]
  11. Scheuerer, M. and T.M. Hamill, Statistical postprocessing of ensemble precipitation forecasts by fitting censored, shifted gamma distributions. Monthly Weather Review, 143(11): p. 4578-4596, (2015) [CrossRef] [Google Scholar]
  12. Wright, D.B., D.B. Kirschbaum and S. Yatheendradas, Satellite Precipitation Characterization, Error Modeling, and Error Correction Using Censored Shifted Gamma Distributions. Journal of Hydrometeorology, 18(10): p. 2801-2815, (2017) [CrossRef] [Google Scholar]
  13. Ning, S., et al., Error analysis and evaluation of the latest GSMap and IMERG precipitation products over Eastern China. Advances in Meteorology, 2017. (2017) [CrossRef] [Google Scholar]
  14. Baran, S. and D. Nemoda, Censored and shifted gamma distribution based EMOS model for probabilistic quantitative precipitation forecasting. Environmetrics, 27(5): p. 280-292, (2016) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.