Meteorological observations and model

Data assimilation (DA) is important for daily chemistry forecasts, but it also is a challenge. At the moment there are much fewer stations with chemistry observations than meteorological observations, and the observations from these stations may not always be available in real time. Also, the gradients in chemical species often are very sharp, which the current observation network and data assimilation schemes are not capable of representing. And last but not least, it is difficult to determine the assimilation increments with so many possible species and so few detailed observations. This is why ECMWF has limited the chemistry in their model and data assimilation to five species (in addition to the cost in computer power). 

ADAPT-LODI, developed at Lawrence Livermore National Laboratory. The ADAPT model assimilates meteorological data provided by observations and models (in particular, by Coupled Ocean/Atmosphere Mesoscale Prediction System [COAMPS ]) to construct the wind and turbulence fields. Particle positions are updated using a Lagrangian particle approach that uses a skewed (non-Gaussian) probability density function (Nasstrom et al. 1999 Ermak and Nasstrom 2000). 

Figure 3.3 and Table 3.1 are shown here to indicate the spread of available observations for model evaluation. Figure 3.3 shows a comparison of water vapor mixing ratio as predicted by WRF/Chem for the same time period, but compared to aircraft observations. Similar comparisons are available for other meteorological parameters as well as many chemical constituents, including Ozone, PM species and ozone precursors (Table 3.1). Detailed results are displayed on the WEB at http //www.al.noaa.gov/lCARTT/modeleval. 

Gedzelman and Arnold (1994) built on this isotopic approach, but with a more realistic two-dimensional, non-steady-state, cloud model. The model was mn for several idealized, classical stratiform and convective storm situations and the resulting isotope ratios of precipitation and water vapor estimated and compared to observations. The model reproduces many of the salient features of isotope meteorology when applied to snowstorms, stratiform rain, and convective precipitation. Also noticeable is the fact that isotope ratios are particularly low when the rain derives from a recirculation process in which air previously charged by vapor from falling rain subsequently rises. This provides a reasonable explanation for extraordinary low isotope ratios observed in some hurricanes and organized thunderstorms. 

Air parcel trajectories were computed on a two-dimensional horizontal grid using numerically analyzed meteorological data. The trajectory model has been described in detail by Nordlund et al. (1985). The meteorological data analyses are based on simultaneous synoptical surface observations and sounding and satellite data from the whole of the northern hemisphere. These data are numerically analyzed onto constant pressure levels on a rectangular mesh system. The mesh is about 150 km wide, and the values within each grid square are comput by linear interpolation procedures. 

---