EGU23-11265, updated on 26 Feb 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Near-real Time Daily Drought Monitoring Using an Ensemble of Gridded Precipitation Datasets

Olivier Prat1, David Coates1, Scott Wilkins1, Denis Willett1, Ronald Leeper1, Brian Nelson2, Michael Shaw3, Steve Ansari3, and George Huffman4
Olivier Prat et al.
  • 1Cooperative Institute for Satellite Earth System Studies (CISESS), North Carolina State University, Asheville, NC, USA (
  • 2NOAA/NCEI/Center for Weather and Climate (CWC), Asheville, NC, USA
  • 3NOAA/NCEI/National Integrated Drought Information System (NIDIS), Asheville, NC, USA
  • 4NASA Goddard Space Flight Center, Greenbelt, MD, USA

We present a near-real time drought monitoring framework that uses precipitation estimates from a selection of satellite (CMORPH-CDR, IMERG) and in-situ (NClimGrid) gridded precipitation products datasets. The near-real time availability of precipitation datasets allows for the computation of the standardized precipitation index (SPI) over various time scales (30-, 90-, 180-, 270-, 365-, 730-day) and daily update of drought conditions. The three drought products generated: CMORPH-SPI (Global; 1998-present; 0.25°x0.25°degree spatial resolution), NClimGrid-SPI (CONUS; 1951-present; 0.05°x0.05°), and IMERG-SPI (Global; 2000-present; 0.1°x0.1°) are being evaluated focusing on the influence of the sensors characteristics and resolutions, differing period of record, and various SPI formulations. The remotely sensed and in-situ SPIs are also compared against existing droughts monitoring resources and in particular the US Drought Monitor (USDM).

The use of cloud-scale computing resources (Microsoft Azure, Amazon Web Services) reduces considerably the computation time. Gain in computational time and process optimization allow for the implementation of a drought amelioration module that is run conjointly with the daily SPI. The drought conditions derived from the precipitation datasets enable us to estimate the amount of deficit precipitation needed to alleviate drought conditions as a function of drought severity and accumulation periods. The process flexibility also allows for the addition of other variables (i.e. temperature, ET) to develop more complex drought indices.  For instance, daily temperature information available from NClimGrid, is used to compute the Standardized Precipitation-Evapotranspiration Index (SPEI) that is evaluated against NClimGrid-SPI over CONUS.

Finally, we present the effort to transfer the SPI from research to operation (R2O). The global daily SPI derived from CMORPH-CDR is publicly available via the Global Drought Information System (GDIS) dashboard ( The other products developed (NClimGrid-SPI, IMERG-SPI) are expected to be added to the existing portfolio of near-real time drought monitoring capabilities.

How to cite: Prat, O., Coates, D., Wilkins, S., Willett, D., Leeper, R., Nelson, B., Shaw, M., Ansari, S., and Huffman, G.: Near-real Time Daily Drought Monitoring Using an Ensemble of Gridded Precipitation Datasets, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11265,, 2023.