4.5 Article

SHARPEN: A Scheme to Restore the Distribution of Averaged Precipitation Fields

Journal

JOURNAL OF HYDROMETEOROLOGY
Volume 22, Issue 8, Pages 2105-2116

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JHM-D-20-0225.1

Keywords

Precipitation; Rainfall; Algorithms; Remote sensing; Satellite observations; Statistics

Funding

  1. NASA Precipitation Measurement Missions funding
  2. NASA [NNX17AG74G]
  3. NASA [1001575, NNX17AG74G] Funding Source: Federal RePORTER

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Combining observations from multiple fields and using weighted averaging is a key strategy in obtaining complete global coverage of high-resolution precipitation. The SHARPEN scheme is introduced to recover the distribution of averaged precipitation fields and improve precipitation detection skill, with a slight reduction in correlation likely due to a sharper precipitation field.
A key strategy in obtaining complete global coverage of high-resolution precipitation is to combine observations from multiple fields, such as the intermittent passive microwave observations, precipitation propagated in time using motion vectors, and geosynchronous infrared observations. These separate precipitation fields can be combined through weighted averaging, which produces estimates that are generally superior to the individual parent fields. However, the process of averaging changes the distribution of the precipitation values, leading to an increase in precipitating area and a decrease in the values of high precipitation rates, a phenomenon observed in IMERG. To mitigate this issue, we introduce a new scheme called SHARPEN (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood), which recovers the distribution of the averaged precipitation field based on the idea of quantile mapping applied to the local environment. When implemented in IMERG, precipitation estimates from SHARPEN exhibit a distribution that resembles that of the original instantaneous observations, with matching precipitating area and peak precipitation rates. Case studies demonstrate its improved ability in bridging between the parent precipitation fields. Evaluation against ground observations reveals a distinct improvement in precipitation detection skill, but also a slightly reduced correlation likely because of a sharper precipitation field. The increased computational demand of SHARPEN can be mitigated by striding over multiple grid boxes, which has only marginal impacts on the accuracy of the estimates. SHARPEN can be applied to any precipitation algorithm that produces an average from multiple input precipitation fields and is being considered for implementation in IMERG V07.

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