Online coupled chemical weather forecasting based on HIRLAM - overview and prospective of Enviro-HIRLAM

However, the handling of high resolution data in this manner is highly cumbersome and time consuming and therefore, not suited for operational chemical weather forecasting. Alternatively, an online coupled model may be generated by integrating a CTM in the meteorological driver, thereby, reducing the external data handling to a minimum. This should be done in such a way that all transport, dispersion and transformation of the chemical and aerosol species are done on the grid used by the meteorological model using the same numerical solution methods. We believe that this approach contains a number of advantages that makes it convenient. These include the use of the same parameterizations and numerical solution schemes for the chemical and aerosol species and the meteorological driving fields eliminating this type of inconsistency as well as the removal of spatial and temporal interpolation of the meteorological forcing fields. Comparing to offline models the online approach takes full advantage of the variability of the meteorological fields, it may include feedbacks and has shorter execution time. One might say that when using an offline model the computational resources are spread out over a longer time span, since, the meteorological forecast, the pre-processing (spatial and temporal interpolation) of the driving fields and the execution of the CTM are done separately, whereas with an online model, as advocated above, it is all done in during one run. It should be noted that, if it is assumed that feedbacks are not of importance, offline models have advantages in other disciplines such as sensitivity studies, including air quality impact studies, where meteorology is kept constant and emissions are varied. According to the definition given above chemical weather forecasting is not a new discipline, since offline air quality models have been used for several decades. However, if one wishes to simulate the short term variability (below one hour), present in chemical and aerosol fields, which is important for feedbacks (see Feedback section later) online coupled models are needed.

[1]  Ana Isabel Miranda,et al.  Air Pollution Modeling and Its Application XIX , 2008 .

[2]  A. Bott.  A positive definite advection scheme obtained by nonlinear renormalization of the advective fluxes , 1989 .

[3]  J. Kristjánsson,et al.  Condensation and Cloud Parameterization Studies with a Mesoscale Numerical Weather Prediction Model , 1989 .

[4]  Jason Ching,et al.  Simulation of Meteorological Fields Within and Above Urban and Rural Canopies with a Mesoscale Model , 2004 .

[5]  A. Wexler,et al.  Post-fog nucleation of H2SO4H2O particles in smog , 1994 .

[6]  Steven E. Peckham,et al.  Online versus offline air quality modeling on cloud‐resolving scales , 2004 .

[7]  E. Kaas.  A simple and efficient locally mass conserving semi-Lagrangian transport scheme , 2008 .

[8]  M. Jacobson.  Development and application of a new air pollution modeling system-part I: Gas-phase simulations , 1997 .

[9]  Hilding Sundqvist,et al.  Parameterization of Condensation and Associated Clouds in Models for Weather Prediction and General Circulation Simulation , 1988 .

[10]  A. Clappier,et al.  An Urban Surface Exchange Parameterisation for Mesoscale Models , 2002 .

[11]  Approaches for urbanization of DMI-HIRLAM NWP model , 2005 .

[12]  Georg A. Grell,et al.  Fully coupled “online” chemistry within the WRF model , 2005 .

[13]  K. Sattler,et al.  Large eddy simulation of urban features for Copenhagen metropolitan area , 2005 .

[14]  Jerome D. Fast,et al.  Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) , 2008 .

[15]  Alexander Baklanov,et al.  Pollutant transport schemes integrated in a numerical weather prediction model: model description and verification results , 2004 .

[16]  L. Pirjola,et al.  Parameterizations for sulfuric acid/water nucleation rates , 1998 .

[17]  Robert E. Dickinson,et al.  How Can We Advance Our Weather and Climate Models as a Community , 2002 .

[18]  K. Sattler,et al.  Verifi cation of long-term DMI-HIRLAM NWP model runs using urbanization and building effect parameterization modules , 2008 .

[19]  William R. Goodin,et al.  Numerical solution of the atmospheric diffusion equation for chemically reacting flows , 1982 .

[20]  Sven-Erik Gryning,et al.  Air pollution modeling and its application , 1981 .

[21]  I. J. Ackermann,et al.  Modeling the formation of secondary organic aerosol within a comprehensive air quality model system , 2001 .

[22]  M. Memmesheimer,et al.  Modal aerosol dynamics model for Europe: development and first applications , 1998 .

[23]  Guriĭ Ivanovich Marchuk,et al.  Mathematical Models in Environmental Problems , 1986 .

[24]  Mark Z. Jacobson,et al.  Fundamentals of Atmospheric Modeling: Preface , 2005 .

[25]  H. Sundqvist.  Inclusion of ice phase of hydrometeors in cloud parameterization for mesoscale and largescale models , 1993 .

[26]  B. Albrecht.  Aerosols, Cloud Microphysics, and Fractional Cloudiness , 1989, Science.

[27]  Alexander Baklanov,et al.  Parameterisation of radionuclide deposition in atmospheric long-range transport modelling , 2001 .

[28]  Lennart Thaning,et al.  On the Settling Velocity in a Nonstationary Atmosphere , 1991 .

[29]  M. Fraser.  Atmospheric Pollution: History, Science and Regulation , 2003 .

[30]  J. Seinfeld.  Atmospheric Chemistry and Physics of Air Pollution , 1986 .

[31]  Philip J. Rasch,et al.  A Comparison of the CCM3 Model Climate Using Diagnosed and Predicted Condensate Parameterizations , 1998 .

[32]  G. Sehmel.  Particle and gas dry deposition: A review , 1980 .

[33]  Francis S. Binkowski,et al.  AEROSOLS IN MODELS-3 CMAQ , 1999 .

[34]  Mark Lawrence,et al.  The chemical weather , 2005 .

[35]  J. Redelsperger,et al.  A turbulence scheme allowing for mesoscale and large‐eddy simulations , 2000 .

[36]  M. Wesely.  Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical models , 1989 .

[37]  Bent Hansen Sass.  A research version of the STRACO cloud scheme , 2002 .

[38]  S. Twomey.  Pollution and the Planetary Albedo , 1974 .

[39]  J. Chenevez.  Advection Experiments with DMI-HIRLAM-TRACER , 2002 .

[40]  Peter H. Lauritzen,et al.  A mass-conservative version of the semi-implicit semi-Lagrangian HIRLAM , 2008 .

[41]  Patrice G. Mestayer,et al.  Parameterization of the Urban Water Budget with the Submesoscale Soil Model , 2006 .

[42]  Peter H. McMurry,et al.  Modal Aerosol Dynamics Modeling , 1997 .