Operational Framework for Near-real Time Daily Drought Monitoring Using Global Remotely Sensed Precipitation Products and In-situ Datasets
- 1Cooperative Institute for Satellite Earth System Studies (CISESS), North Carolina State University, Asheville, NC, USA (opprat@ncsu.edu)
- 2NOAA/NCEI/Center for Weather and Climate (CWC), Asheville, NC, USA
- 3ISciences, L.L.C., National Centers for Environmental Information (NCEI), Asheville, NC, USA
- 4NOAA/NCEI/National Integrated Drought Information System (NIDIS), Asheville, NC, USA
- 5NASA Goddard Space Flight Center, Greenbelt, MD, USA
We present an operational near-real time drought monitoring framework on a global scale that uses quantitative precipitation estimates (QPEs) from gridded Satellite Precipitation Products (CMORPH-CDR, IMERG) and in-situ datasets (NClimGrid). The Standardized Precipitation Index (SPI) is computed daily for various time scales from the reprocessed, bias-corrected CMORPH-CDR. The near-real time availability of CMORPH-CDR permits for a daily update of global drought conditions starting in 1998. It provides a global daily SPI at a 0.25x0.25 degree spatial resolution. The global SPI is publicly available via the Global Drought Information System (GDIS) dashboard. The GDIS website includes an interactive map hosted within the NOAA GeoPlatform (ArcGIS Online). It provides 45 layers of drought indices and indicators in addition to the global daily CMORPH SPI (https://gdis-noaa.hub.arcgis.com/pages/drought-monitoring).
The pipeline assembled to produce CMORPH-SPI is extended to IMERG (Integrated Multi-satellitE Retrievals for GPM) to generate a daily global IMERG-SPI at a higher spatial resolution (0.1x0.1deg) from 2000 to the present. The 6-fold increase in spatial resolution comes at a higher computational cost which is alleviated by accessing cloud-scale computing resources such as Microsoft Planetary Computer and Azure that allows to optimize the process and reduce considerably the computation time. Similarly, we use the high resolution gridded in-situ precipitation dataset NClimGrid to generate a daily high resolution NClimGrid-SPI over CONUS (5x5-km). Because of NClimGrid longer period of record, it allows accessing daily drought conditions from 1950 up to the present day.
Comparisons between the generated SPIs (CMORPH-SPI, IMERG-SPI, NClimGrid-SPI) are conducted with a focus on the influence of the different resolutions, sensors characteristics, and SPI formulations (two parameter Gamma distribution: McKee et al. 1993; three parameter Pearson III distribution: Guttman 1999). When possible, an evaluation of the remotely sensed and in-situ SPIs is performed against existing droughts monitoring tools such as the US Drought Monitor (USDM). Finally, we present the results of the implementation of a drought relief module that quantifies the precipitation amount that would be needed (i.e. rainfall deficit) for drought relief as a function of the accumulation period considered.
How to cite: Prat, O., Coates, D., Leeper, R., Nelson, B., Bilotta, R., Ansari, S., and Huffman, G.: Operational Framework for Near-real Time Daily Drought Monitoring Using Global Remotely Sensed Precipitation Products and In-situ Datasets, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10806, https://doi.org/10.5194/egusphere-egu22-10806, 2022.
