Identification

Title

On the correspondence between mean forecast errors and climate errors in CMIP5 models

Abstract

The present study examines the correspondence between short- and long-term systematic errors in five atmospheric models by comparing the 16 five-day hindcast ensembles from the Transpose Atmospheric Model Intercomparison Project II (Transpose-AMIP II) for July-August 2009 (short term) to the climate simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and AMIP for the June-August mean conditions of the years of 1979-2008 (long term). Because the short-term hindcasts were conducted with identical climate models used in the CMIP5/AMIP simulations, one can diagnose over what time scale systematic errors in these climate simulations develop, thus yielding insights into their origin through a seamless modeling approach. The analysis suggests that most systematic errors of precipitation, clouds, and radiation processes in the long-term climate runs are present by day 5 in ensemble average hindcasts in all models. Errors typically saturate after few days of hindcasts with amplitudes comparable to the climate errors, and the impacts of initial conditions on the simulated ensemble mean errors are relatively small. This robust bias correspondence suggests that these systematic errors across different models likely are initiated by model parameterizations since the atmospheric large-scale states remain close to observations in the first 2-3 days. However, biases associated with model physics can have impacts on the large-scale states by day 5, such as zonal winds, 2-m temperature, and sea level pressure, and the analysis further indicates a good correspondence between short- and long-term biases for these large-scale states. Therefore, improving individual model parameterizations in the hindcast mode could lead to the improvement of most climate models in simulating their climate mean state and potentially their future projections.

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document

Resource locator

Unique resource identifier

code

https://n2t.org/ark:/85065/d77945km

codeSpace

Dataset language

eng

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Classification of spatial data and services

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geoscientificInformation

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title

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reference date

date type

publication

effective date

2016-01-01T00:00:00Z

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publication

effective date

2014-02-15T00:00:00Z

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Copyright 2014 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or amspubs@ametsoc.org. Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

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