Prediction and predictability of land and atmosphere initialized CCSM4 climate forecasts over North America

Infanti, Johnna M.; Kirtman, Ben P.

doi:10.1002/2016JD024932

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Prediction and predictability of land and atmosphere initialized CCSM4 climate forecasts over North America

2016
By Infanti, Johnna M. ; Kirtman, Ben P.
Source: J. Geophys. Res. Atmos., 121, 12,690– 12,701

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Details:

Journal Title:

Journal of Geophysical Research: Atmospheres
Personal Author:

Infanti, Johnna M. ; Kirtman, Ben P.

Infanti, Johnna M. ; Kirtman, Ben P. Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; CPO (Climate Program Office) ; CIMAS (Cooperative Institute for Marine and Atmospheric Studies)

OAR (Oceanic and Atmospheric Research) ; CPO (Climate Program Office) ; CIMAS (Cooperative Institute for Marine and Atmospheric Studies) Less -
Description:

Subseasonal‐to‐seasonal prediction is influenced by slowly varying surface fields such as sea surface temperature (SST) and soil moisture. Fully coupled hindcasts were recently completed in the Community Climate System Model version 4.0 (CCSM4) as part of the North American Multi‐Model Ensemble project. Using similar land and atmosphere initialization strategies, but with prescribed climatological SSTs, we attempt to determine the isolated impact of combined observed atmosphere and land initialization and of observed atmosphere initialization on monthly precipitation and 2 m temperature prediction‐estimated skill (i.e., skill assessed without SST variability) and predictability on monthly time scales. CCSM4 has been cited as having low land‐atmosphere coupling, and while combined land and atmosphere initialization significantly increases the estimated skill of precipitation and temperature in the first month after initialization (lead 0), land initialization influence is weak, consistent with low land‐atmosphere coupling in CCSM4. In contrast, atmosphere initialization is a stronger contributor to prediction skill and predictability. We find stronger influence of land and atmosphere initialization on precipitation in CCSM4 versus results from CCSM3. Predictability results show that there is potential skill to be gained for both precipitation and temperature should model errors, atmosphere or land initial state errors, and/or land‐atmosphere coupling improve.
Keywords:

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Atmosphere Forecasting Climatology Forecasting Land Use Precipitation
Source:

J. Geophys. Res. Atmos., 121, 12,690– 12,701
DOI:

https://doi.org/10.1002/2016JD024932
Document Type:

Journal Article
Funding:

Grant no. NA15OAR4320064 ; Grant no. NA10OAR4320143 ; GC15-210A

Grant no. NA15OAR4320064 ; Grant no. NA10OAR4320143 ; GC15-210A Less -
Place as Subject:

North America
Rights Information:

Other
Compliance:

Submitted
Main Document Checksum:

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urn:sha256:3ca0bca9ad7e592fcb12e1ec8cc767af859cb9ea41e9e17d53e872e706c9235e
Download URL:

https://repository.library.noaa.gov/view/noaa/28358/noaa_28358_DS1.pdf
File Type:

	NMME	htm
	ccsm4.0	htm

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