Details:

Journal Title:
Journal of Hydrometeorology
Personal Author:
Nguyen, Phu ; Ombadi, Mohammed ; Gorooh, Vesta Afzali ; Shearer, Eric J. ; Sadeghi, Mojtaba ; ... More +
Nguyen, Phu ; Ombadi, Mohammed ; Gorooh, Vesta Afzali ; Shearer, Eric J. ; Sadeghi, Mojtaba ; Sorooshian, Soroosh ; Hsu, Kuolin ; Bolvin, David ; Ralph, Martin F. Less -
NOAA Program & Office:
NOAA General Documents
Description:
This study presents the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR-Now) near-real-time precipitation dataset. This dataset provides hourly, quasi-global, infrared-based precipitation estimates at 0.04° × 0.04° spatial resolution with a short latency (15–60 min). It is intended to supersede the PERSIANN–Cloud Classification System (PERSIANN-CCS) dataset previously produced as the near-real-time product of the PERSIANN family. We first provide a brief description of the algorithm’s fundamentals and the input data used for deriving precipitation estimates. Second, we provide an extensive evaluation of the PDIR-Now dataset over annual, monthly, daily, and subdaily scales. Last, the article presents information on the dissemination of the dataset through the Center for Hydrometeorology and Remote Sensing (CHRS) web-based interfaces. The evaluation, conducted over the period 2017–18, demonstrates the utility of PDIR-Now and its improvement over PERSIANN-CCS at all temporal scales. Specifically, PDIR-Now improves the estimation of rain/no-rain days as demonstrated by a critical success index (CSI) of 0.53 compared to 0.47 of PERSIANN-CCS. In addition, PDIR-Now improves the estimation of seasonal and diurnal cycles of precipitation as well as regional precipitation patterns erroneously estimated by PERSIANN-CCS. Finally, an evaluation is carried out to examine the performance of PDIR-Now in capturing two extreme events, Hurricane Harvey and a cluster of summer thunderstorms that occurred over the Netherlands, where it is shown that PDIR-Now adequately represents spatial precipitation patterns as well as subdaily precipitation rates with a correlation coefficient (CORR) of 0.64 for Hurricane Harvey and 0.76 for the Netherlands thunderstorms.
Keywords:
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Atmospheric Science
Source:
Journal of Hydrometeorology, 21(12), 2893-2906
DOI:
https://doi.org/10.1175/jhm-d-20-0177.1
ISSN:
1525-755X;1525-7541;
Format:
PDF
Publisher:
American Meteorological Society
Document Type:
Journal Article
Rights Information:
Other
Compliance:
Library
Main Document Checksum:
[+]
urn:sha256:98291ab708c982fc258cccc86546b0bfdcb835a018e25585bfa242dfb96b8e6d
Download URL:
https://repository.library.noaa.gov/view/noaa/60070/noaa_60070_DS1.pdf
File Type:

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