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Title: Introduction to CAUSES: Description of Weather and Climate Models and Their Near-Surface Temperature Errors in 5 day Hindcasts Near the Southern Great Plains

Journal Article · · Journal of Geophysical Research: Atmospheres
DOI:https://doi.org/10.1002/2017JD027199· OSTI ID:1426306
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  1. Met Office, Exeter UK
  2. Lawrence Livermore National Laboratory, Livermore CA USA
  3. European Centre for Medium-Range Weather Forecasts, Reading UK
  4. CNRM, Météo-France/CNRS, Toulouse France
  5. Pacific Northwest National Laboratory, Richland WA USA
  6. NASA Langley Research Center, Hampton VA USA
  7. Laboratoire de Météorologie Dynamique, Paris France
  8. Environment and Climate Change Canada, Victoria British Columbia Canada
  9. Academia Sinica, Taipei Taiwan
+ Show Author Affiliations

We introduce the Clouds Above the United States and Errors at the Surface (CAUSES) project with its aim of better understanding the physical processes leading to warm screen temperature biases over the American Midwest in many numerical models. In this first of four companion papers, 11 different models, from nine institutes, perform a series of 5 day hindcasts, each initialized from reanalyses. After describing the common experimental protocol and detailing each model configuration, a gridded temperature data set is derived from observations and used to show that all the models have a warm bias over parts of the Midwest. Additionally, a strong diurnal cycle in the screen temperature bias is found in most models. In some models the bias is largest around midday, while in others it is largest during the night. At the Department of Energy Atmospheric Radiation Measurement Southern Great Plains (SGP) site, the model biases are shown to extend several kilometers into the atmosphere. Finally, to provide context for the companion papers, in which observations from the SGP site are used to evaluate the different processes contributing to errors there, it is shown that there are numerous locations across the Midwest where the diurnal cycle of the error is highly correlated with the diurnal cycle of the error at SGP. This suggests that conclusions drawn from detailed evaluation of models using instruments located at SGP will be representative of errors that are prevalent over a larger spatial scale.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Met Office, Exeter (United Kingdom)
Sponsoring Organization:
Office of Science (SC), Biological and Environmental Research (BER). Earth and Environmental Systems Science Division
Contributing Organization:
Met Office (UK), LLNL (USA), PNNL (USA), ECMWF (UK), Meteofrance/CNRM/CNRS (France), LMD (France), Academia Sinica (Taiwan)
Grant/Contract Number:
AC52-07NA27344; SC0014122; SC0005259; AC05-76RL01830; AC02-05CH11231; DARI-0292
OSTI ID:
1426306
Alternate ID(s):
OSTI ID: 1426307; OSTI ID: 1429920; OSTI ID: 1438772; OSTI ID: 1501543
Report Number(s):
PNNL-SA-126058; LLNL-JRNL-732218
Journal Information:
Journal of Geophysical Research: Atmospheres, Journal Name: Journal of Geophysical Research: Atmospheres Vol. 123 Journal Issue: 5; ISSN 2169-897X
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 55 works
Citation information provided by
Web of Science

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Related Subjects

54 ENVIRONMENTAL SCIENCES
systematic errors
surface temperature bias
ARM
SGP
58 GEOSCIENCES
Atmospheric modelling
climate simulations
surface temperature
warm bias
clouds
land-surface