A Case Study Investigating the Low Summertime CAPE Behavior in the Global Forecast System
[1];
- a Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado; b National Oceanic and Atmospheric Administration/Global Systems Laboratory, Boulder, Colorado; d Developmental Testbed Center, Boulder, Colorado
- b National Oceanic and Atmospheric Administration/Global Systems Laboratory, Boulder, Colorado
- c National Center for Atmospheric Research, Boulder, Colorado; d Developmental Testbed Center, Boulder, Colorado
Convective available potential energy (CAPE) is an important index for storm forecasting. Recent versions (v15.2 and v16) of the Global Forecast System (GFS) predict lower values of CAPE during summertime in the continental United States than analysis and observation. We conducted an evaluation of the GFS in simulating summertime CAPE using an example from the Unified Forecast System Case Study collection to investigate the factors that lead to the low CAPE bias in GFS. Specifically, we investigated the surface energy budget, soil properties, and near-surface and upper-level meteorological fields. Results show that the GFS simulates smaller surface latent heat flux and larger surface sensible heat flux than the observations. This can be attributed to the slightly drier-than-observed soil moisture in the GFS that comes from an offline global land data assimilation system. The lower simulated CAPE in GFS v16 is related to the early drop of surface net radiation with excessive boundary layer cloud after midday when compared with GFS v15.2. A moisture-budget analysis indicates that errors in the large-scale advection of water vapor does not contribute to the dry bias in the GFS at low levels. Common Community Physics Package single-column model (SCM) experiments suggest that with realistic initial vertical profiles, SCM simulations generate a larger CAPE than runs with GFS IC. SCM runs with an active LSM tend to produce smaller CAPE than that with prescribed surface fluxes. Note that the findings are only applicable to this case study. Including more warm-season cases would enhance the generalizability of our findings.
- Research Organization:
- ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Contributing Organization:
- PNNL, BNL, ANL, ORNL
- Grant/Contract Number:
- AC05-76RL01830
- OSTI ID:
- 2274752
- Journal Information:
- Weather and Forecasting, Journal Name: Weather and Forecasting Journal Issue: 1 Vol. 39; ISSN 0882-8156
- Publisher:
- American Meteorological SocietyCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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