CMAQ - can I include (actual) observations to improve the meteo fields?

Hi,

I am doing a research on obtaining high-resolution meteorological fields over complex terrain. After reading the documentation, I still have some open questions which I would prefer to have answered before i dig into the deployment.

I am NOT at all interested in the dispersion of air pollutants or any kind of chemical reaction. I am only interested in the high-resolution meteo fields (temperature, wind, solar irradiation and rain).

  1. So, can I use CMAQ to obtain high-resolution fields of all mentioned variables?
  2. Correct me if I am wrong, CMAQ uses mesoscopic models as initial values.
  3. Can actual observations from several meteo stations be used to improve the accuracy of the downscalling procedure?
  4. Are there any limitations (other than computational complexity) to the spatial resolution of output fields?

I thank you in advance!

The CCTM component of the CMAQ modeling system is a chemistry transport model that does not compute the meteorological fields it needs to simulate the effects of meteorology on the chemical species it represents (i.e. the effects of transport, chemistry, and deposition on these species). Instead, the required meteorological fields are obtained from a meteorological model like WRF, either by first running the meteorological model, saving and processing the outputs, and then passing them to the CCTM (offline mode) or by running the WRF/CMAQ two-way model in which the meteorological fields calculated by WRF are directly passed to CCTM and (optionally) aerosol fields simulated by the CCTM are passed back to WRF to be taken into account in the WRF radiation calculations.

Since you state that you are only interested in simulating meteorological fields, the CMAQ CCTM does not appear to be the correct tool for your plans. Instead, you would want to use a meteorological model such as WRF for your project. WRF has the option to use four-dimensional data assimilation (FDDA) incorporating analysis fields and various observational datasets (surface and upper air) to provide observational constraints on model simulations. Some relevant information may be found here and here, though I am not a WRF modeler so this is just based on a quick websearch to get you started should you decide to pursue the WRF option.

@hogrefe.christian Your help is much appreciated. Thank you for the helpful links towards WRF.