Improvement of daily precipitation estimations using PRISM with inverse-distance weighting

Abstract

Improved daily precipitation estimations were attempted using the parameter-elevation regressions on a parameter-elevation regression on independent slopes model (PRISM) with inverse-distance weighting (IDW) and a precipitation-masking algorithm for precipitation areas. The PRISM (PRISM_ORG) suffers two overestimation problems when the daily precipitation is estimated: overestimation of the precipitation intensity in mountainous regions and overestimation of the local precipitation areas. In order to solve the problem of overestimating the precipitation intensity, we used the IDW technique that employs the same input stations as those used in the PRISM regression (PRISM_IDW). A precipitation-masking algorithm that selectively masks the precipitation estimation grid points was additionally applied to the PRISM_IDW results (PRISM_MSK). For 6 months from March to August 2012, daily precipitation data were produced in a horizontal resolution of 1 km based on the above two experiments and PRISM_ORG. Afterwards, each experiment was evaluated for improvements. The monthly root mean squared errors (RMSEs) of PRISM_IDW and PRISM_MSK were reduced by 0.83 mm/day and 0.86 mm/day, respectively, compared to PRISM_ORG.

The impact of rainfall distribution methods on streamflow throughout multiple elevations in the Rocky Mountains using the APEX model—Price River watershed, Utah

“…The PRISM data captured the measured precipitation well, with a R 2 ranging from .75 to .96, which indicated that the PRISM rainfall captured 75-96% of the gauged rainfall variability with an average of 91% and a median of 93%. Similar performance of PRISM data was reported in mountainous areas, including Kandal, Cambodia (Lee et al, 2014); South Korea (Jeong et al, 2020); and the northwestern corner of Washington State, United States (Currier et al, 2017). Overall, the PRISM data are well situated in mountainous terrains because the data incorporate a conceptual framework that considers orographic precipitation (Daly et al, 1994).…”

Identifying hotspots cities vulnerable to climate change in Pakistan under CMIP5 climate projections

“…First, we used only 34 meteorological station data to downscale CMIP5 simulations. Second, it is recommended to use an advanced method such as PRISM (e.g., Daly et al ., 2002; Daly, 2006; Jeong et al ., 2020) for the preparation of finer resolution reference data and downscaling.…”

A New Modeling Approach for Spatial Prediction of Flash Flood with Biogeography Optimized CHAID Tree Ensemble and Remote Sensing Data

“…The higher the rainfall in a range, the greater the likelihood of a flood. In this research, the highest 16-day rainfall during the last 3 years at 30 stations in and around the study area was used to generate the rainfall pattern map using the Inverse Distance Weight technique [68]. The rainfall map (Figure 3a), with 142 mm in the northern areas and 620 mm in the central and southeastern areas, was interpolated through the station of the regional gauges rain in ArcGIS software.…”