Drought information is being increasingly relied upon at county and sub-county spatial scales, yet most in situ observation-based tools are only available at much coarser resolution. The NOAA/NWS River Forecast Centers operationally produce high-resolution multi-sensor precipitation estimates (MPE) at ~4 km spatial resolution, and these data have become an invaluable resource for local, state, and national drought monitoring. Recent efforts by members of this project team have led to operational production and public web delivery of daily updated Standardized Precipitation Indices (SPI) with national coverage using MPE as the primary input. However, SPI is a relatively crude index for drought, and even the most sophisticated index, while useful, provides much less information than a well-calibrated land surface model.
We are now in the process of developing long-term bias correction methods to convert MPE into a reliable measure of long-term precipitation deficits and surpluses. We propose to use this biascorrected MPE to calculate drought indices such as the Standardized Precipitation Evapotranspiration Index (SPEI) and the various Palmer Drought Indices (PDI), both of which can be more informative than SPI because they incorporate effects of evaporation as well as precipitation. Gridded daily temperature data will be obtained from daily PRISM temperature grids, MODIS Daily Land Surface Temperature, or NWS national gridded MOS of daily maximum and minimum temperatures. As with our present SPI analyses, these gridded indices would be publicly available over the web through a convenient interface and would be downloadable as shapefiles.
In addition, we shall develop and test the implementation of bias-corrected MPE as input into the North American Land Data Assimilation System (NLDAS). Using the Noah land surface model, we shall perform comparison runs with and without bias-correction and evaluate impacts on soil moisture profiles and streamflow. The results will be evaluated using streamflow gauge measurements in natural basins. The initial comparison will be performed with MPE aggregated to the 1/8 degree grid that is conventional for NLDAS, but as NLDAS migrates to higher spatial resolution, the benefits of full-resolution bias-corrected MPE will be tested and are expected to be even larger. The methods being developed are not resolution-specific and can continue to be applied even as MPE methods and resolution change.
This project squarely addresses the Modeling, Analysis, Predictions, and Projections (MAPP) competition priority of advancing the development of a national drought monitoring and prediction system. The project explicitly involves drought monitoring, and since precipitation deficits precede drought impacts, having high-resolution meteorological drought information can provide the basis for drought impact prediction. The project specifically addresses the NOAA’s Strategic Plan by providing improved “assessment of current and future states of the climate systems that identify potential impacts” and by providing “timely climate services” (NGSP 2013). The output from this project will directly benefit many existing NOAA initiatives, including drought.gov, NIDIS, NLDAS, and the U.S. Drought Monitor.