ARM-Funded Algorithms Lead to Marked Improvements in Global Weather Forecast Model
Morcrette, J. J., European Centre for Medium-Range Weather Forecasts
General Circulation and Single Column Models/Parameterizations
Morcrette, J.-J., H.W. Barker, J.N.S. Cole, M.J. Iacono, and R. Pincus, 2007: Impact of a new radiation package, McRad, in the ECMWF Integrated Forecasting System. Mon. Wea. Rev., Submitted.
Figure 1a. Black contours are for ERA-40 mean-annual, zonally-averaged tempreatures, while colored controus correspond to differences between ERA-40 and the ECMWF model without the new routines.
Figure 1b. Same as Fig. 1a, except colored contours correspond to differences between ERA-40 and the ECMWF model with the new routines.
Additional Key Contacts: Howard Barker, Jason Cole, Mike Iacono, Eli Mlawer, Robert Pincus, and Petri Räisänen.
One of the world's foremost weather forecast models is showing dramatic improvements thanks to the pairing of two recent advancements in the representation of atmospheric radiative transfer. Developed with the help of funding from the Atmospheric Radiation Measurement (ARM) Program, the new components simulate atmospheric absorption and scattering of sunlight ("solar radiation") and better represent the interaction between radiation and clouds.
These new components helped remedy several long-standing problems in the forecast model of the European Centre for Medium-Range Weather Forecasts (ECMWF). In long runs, the model is now in better agreement with the observationally-based ERA-40 reanalysis. Figure 1 shows that zonally-averaged temperature biases in previous simulations (Figure 1a) are improved through much of the atmosphere by the new components (Figure 1b). Better agreement with observations is also seen in 10-day forecasts and, remarkably, the better agreement persists for the entire 10-day cycle of forecasts. Improvements in the simulated temperature structure affect other aspects of the simulation. For instance, the new configuration has curbed the model's previous tendency to over-predict convective thunderstorms over the ocean relative to those over nearby land areas.
The two ARM-funded components introduced into the European Centre model are a treatment of atmospheric radiative transfer and a method for treating interactions between radiation and clouds. The first component is a rapid radiative transfer model called RRTMG, which is a version of the column model, RRTM. Modified for use in global models, RRTMG was developed by scientists at Atmospheric and Environmental Research (AER) Inc. (Clough et al., 2005). RRTMG-shortwave features include state-of-the-art representations of absorption and scattering of sunlight by atmospheric gases such as carbon dioxide, ozone, and water vapor (Iacono et al., 2004). ECMWF has used the longwave version of RRTM (Mlawer et al., 1997) since summer 2000. Both the longwave and shortwave versions are based on detailed observations from the ARM Program.
The new ECMWF model pairs RRTMG and the "Monte Carlo Independent Column Approximation" (McICA), an efficient and unbiased statistical technique for representing the interaction between radiation and small-scale variations in cloud geometry and cloud properties. McICA was developed by researchers at Environment Canada, the University of Colorado, and ECMWF. McICA is attractive because it is a simple solution to a long-standing, difficult problem. It is now a standard option in RRTMG, and it has been incorporated into climate models in Finland, Canada, and the United States (Pincus et al., 2006) in addition to the European Centre's.
After careful testing and rigorous evaluation, ECMWF began operational use of McICA and RRTMG-shortwave in its forecast model on June 5, 2007 (Morcrette et al., 2007). The new components provide the flexibility necessary to incorporate future advances in cloud and radiation physics resulting from the ARM Program and other research organizations.
Additional References: Barker, H. W., R. Pincus, and J.-J Morcrette, 2002: The Monte Carlo Independent Column Approximation: Application within Large-Scale Models. In proceedings of the GCSS-ARM Workshop on the Representation of Cloud Systems in Large-Scale Models, May 2002, Kananaskis, AB, Canada. Available at http://www.met.utah.edu/skrueger/gcss-2002/Extended-Abstracts.pdf.
Clough, S.A., M.W. Shephard, E.J. Mlawer, J.S. Delamere, M.J. Iacono, K. Cady-Pereira, S. Boukabara, P.D. Brown, 2005: Atmospheric radiative transfer modeling: a summary of the AER codes, J. Quant. Spectrosc. Radiat. Transfer, 91, 233-244.
Iacono, M. J., J. S. Delamere, E. J. Mlawer, S. A. Clough, J.-J. Morcrette, and Y.-T. Hou, 2004: Development and evaluation of RRTMG_SW, a shortwave radiative transfer model for GCM applications, in Proceedings of the Fourteenth ARM Science Team Meeting, Albuquerque, New Mexico, March 22-26, 2004.
Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102D, 16,663–16,682.
Pincus, R., H. W. Barker, and J. J. Morcrette, 2003: A fast, flexible, approximate technique for computing radiative transfer in inhomogeneous cloud fields. J. Geophys. Res., 108, 4376, doi:10.1029/2002JD003322.
Pincus, R., R. Hemler, and S. A. Klein, 2006: Using Stochastically Generated Subcolumns to Represent Cloud Structure in a Large-Scale Model. Mon. Wea. Rev., 134, 3644-3656.
Räisänen, P., H. W. Barker, M. F. Khairoutdinov, J. Li, and D. A. Randall, 2004: Stochastic generation of subgrid-scale cloudy columns for large-scale models. Quart. J. Roy. Meteor. Soc., 130, 2047–2067.