Short range numerical weather prediction for the Gulf Coast region during the NOAA/ARL-JSU meteorological field experiment of summer 2009

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Tuesday, 19 January 2010: 9:15 AM
B302 (GWCC)
William Pendergrass, NOAA/OAR/ARL/ATDD, Oak Ridge, TN; and L. Myles, C. A. Vogel, V. B. R. Dodla, H. P. Dasari, Y. Anjaneyulu, J. M. Baham, R. Hughes, C. Patrick, J. H. Young, and S. Swanier

Numerical weather prediction experiments using a high resolution mesoscale atmospheric model for the Gulf Coast region were performed for the period of 16-19 June, 2009 so as to validate the model output with the special observations collected as a part of joint NOAA-ARL and JSU-TLGVRC meteorological field study of summer-2009. This study has become necessary as the atmospheric fields are being produced at a desired high resolution of 4 km, which are being used to run the air quality models such as HYSPLIT and CMAQ as a part of the ongoing NOAA sponsored Atmospheric Dispersion Program at Jackson State University. The model produced atmospheric fields play an important role in deriving the spatial distribution of pollutants from an observation stations and in producing forward and trajectories to understand the characteristics of atmospheric dispersion. In this study, altogether eight predictions were obtained and the model derived 3-dimensional atmospheric fields were compared with 40 km and 12 km regional analysis and weather observations from National Weather Service and the special observations at two locations on the Gulf Coast during this period.

ARW (Advanced Research WRF) model was adopted for the Gulf Coast region to have nested two-way interactive three domains with 36, 12 and 4 km resolutions, with the inner most domain covering the entire Gulf Coast region. The model vertical levels were taken to be 63, of which 42 levels were chosen to be below 800 hPa level so as to fine resolve the boundary layer features. This vertical resolution has been chosen as the simulation of boundary layer characteristics is crucial for determining the atmospheric dispersion under different atmospheric stability conditions and associated the influence of coastal land and sea breeze circulations. The initial and boundary conditions were provided from NCEP FNL data available at 1 degree interval and the boundary conditions were updated at every 6 hours. The parameterization schemes of RUC and YSU were chosen for the surface and planetary boundary layer processes respectively for all the prediction experiments. High resolution terrain and land use data at 0.9 km resolution was used to describe the 4 km inner most domain region. The model was integrated for 48 hours starting from 00 and 12 UTC of each day starting from 15 June up to 00 UTC of 18 June 2009.

The model predicted atmospheric fields below 850 hPa level were compared with the corresponding regional analyses at 40 km and 12 km resolution. The model outputs were analyzed to retrieve the vertical profiles of temperature, humidity, wind direction and speed at four locations, of which two are from National Weather Service and two are from the NOAA-JSU meteorological field study program of summer 2009. The short range weather predictions were validated up to 48 hours and the model errors were computed. Some specific parameters such as LCL, CCL, LFC, CAPE, Richardson Number, Depth of Mixed Layer were computed from the model produced fields and observations and were compared for validation of model predictions.

Analyses of model validation show that the ARW model could predict many of the atmospheric features agreeing with the observations. The model could predict the diurnal variations of the coastal circulations, the height of the mixed layer, inversion at the top of the PBL as indicated by sudden increase of temperature and dryness with height. The model derived parameters also agree with corresponding observation derived values to a large extent. The model produced regional circulation features agree with the 40 and 12 km analyses and the model indicates the mesoscale circulation features that could not be obtained in the other analyses. This study indicates the advantages of using high resolution ARW model for short range prediction of atmospheric variables which will be useful for deriving atmospheric dispersion fields.