A Hybrid Dynamic-Statistical Approach to Link Predictive Understanding to Improve Seasonal Prediction of Rainfall Anomalies at the Regional Scale

Fu, Rong; Erfanian, Amir; Fernando, Nelun

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A Hybrid Dynamic-Statistical Approach to Link Predictive Understanding to Improve Seasonal Prediction of Rainfall Anomalies at the Regional Scale

2019
By Fu, Rong ; Erfanian, Amir ; Fernando, Nelun
Source: Climate Prediction S&T Digest

[PDF-598.15 KB]

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Details:

Journal Title:

Climate Prediction S&T Digest
Personal Author:

Fu, Rong ; Erfanian, Amir ; Fernando, Nelun

Fu, Rong ; Erfanian, Amir ; Fernando, Nelun Less -
NOAA Program & Office:

NWS (National Weather Service) ; OSTI (Office of Science and Technology Integration) ; OAR (Oceanic and Atmospheric Research) ; CPO (Climate Program Office)

NWS (National Weather Service) ; OSTI (Office of Science and Technology Integration) ; OAR (Oceanic and Atmospheric Research) ; CPO (Climate Program Office) Less -
Description:

Seasonal prediction of summer rainfall anomalies over the United State (US) Great Plains (GP) is central for drought early warning and society preparedness. Yet, current dynamic models’ predictions have failed to predict recent extreme droughts in 2011 and 2012 and shown virtually no skills for seasonal prediction of the summer rainfall anomalies (e.g. Quan et al. 2012; Hoerling et al. 2014).
Keywords:

[+]

Long-range Weather Forecasting Precipitation Forecasting Rain And Rainfall
Source:

Climate Prediction S&T Digest
Document Type:

Journal Article
Rights Information:

CC 0
Compliance:

Submitted
Main Document Checksum:

[+]

urn:sha256:0ebcb457cc7868aa7eca484ae69373fadb581baae0fd025922976b471e3925fd
Download URL:

https://repository.library.noaa.gov/view/noaa/36781/noaa_36781_DS1.pdf
File Type:

NOAA Annual Climate Diagnostics & Prediction Workshop Index

htm

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