Hyunglok Kim bio photo

Hyunglok Kim

Terrestrial Water Cycle
Remote Sensing
Bayesian Inference
Machine Learning
Deep Learning

Email Google Scholar LinkedIn Instagram Github ResearchGate Orcid

Ready-to-use grid-based data produced from the current projects

Ready-to-use grid-based data produced from the current projects

1. Data sets in Kim et al. 2021 ERL

Global-scale sub-daily CYGNSS and SMAP assimilated data including soil moisture (4 layers), evapotranspiration, land surface temperature (4 layers), excess rainfall, etc., from the Noah-MP3.6 land surface model can be downloaded here

2. Data sets shown in Kim and Lakshmi 2018 GRL

CONUS-scale CYGNSS-based soil moisture data can be downloaded here

3. Data sets in Le et al. 2020 JoH-RS

Evapotranspiration, surface temperature, and preciptiation data can be download here

  • If you need certain formats for the data sets (e.g., NetCDF, HDF, bin, text, etc.), please let me know.
  • If the links above do not work, please email me.


  1. H. Kim, V. Lakshmi, Y. Kwon, and S. Kumar (2021), First attempt of global-scale assimilation of subdaily scale soil moisture estimates from CYGNSS and SMAP into a land surface model, Environmental Research Letters (link)
  2. H. Kim & Lakshmi, V. (2018). Use of Cyclone Global Navigation Satellite System (CYGNSS) observations for estimation of soil moisture. Geophysical Research Letters (link)
  3. M. Le, H. Kim, H. Moon, R. Zhang, V. Lakshmi, and L. Nguyen (2020), Assessment of drought conditions over Vietnam using standardized precipitation evapotranspiration index, MERRA-2 re-analysis, and dynamic land cover, Journal of Hydrology: Regional Studi (link)