Improvement and evaluation of the mesoscale meteorological model MM5 for air-quality applications in Southern California and the San Joaquin Valley: Final Report
Bornstein, Robert D.
Seaman, Nelson L.
Stauffer, David R.
Hunter, Glenn K.
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The objective of the Penn State University (PSU) part of the study was to investigate the MM5's ability to simulate wintertime fog in the San Joaquin Valley (SJV) and summertime sea breeze flows in the South Coast Air Basin (SoCAB). For the SJV work the MM5 was configured with four nested grid and an advanced turbulence sub-model. Applied to the event of 7-12 December 1995, observed during the IMS-95 program, the model's innermost domain used 40 vertical layers and a 4-km mesh. Several experiments were performed to improve the turbulence sub-model for saturated conditions and to provide more accurate initial conditions for soil temperature and moisture. Results showed the MM5 correctly predicted the type of visibility obscuration (fog, haze, status or clear) in 14 out of the 18 events. For depth was estimated by the MM5 with a mean absolute error of only 92 m and a mean error of -41 m. Mean errors for both the surface temperature and dew point were within +1C, while the mean absolute errors were ~1.5-2.0 C. As a consequence, the mean error for dew-point depression is very small. Thus, the MM5 was shown to simulate fog and haze in the SJV with considerable accuracy. Extensions of the turbulence sub-model to include saturation effects and the specification of accurate soil temperature and moisture were important for simulating fog characteristics in the case. Additionally, MM5 was able to simulate the light and variable winds in the Sacramento and San Joaquin Valleys that prevailed during this event. Moreover, the winds responded quite well to the slowly changing synoptic-scale weather, as well, as confirmed by the observations. the objective for the San Jose State University (SJSU) work included use of SCOS97 data and MM5 simulations to understand meteorological factors in the formation of high ozone concentrations during 4-7 August 1997. Meteorological data for the case study included observations at 110 SCOS97 surface sites and upper air measurements from 12 rawinsonde and 26 RWP/RASS profilers. the MM5 version contained the PSU Marine Boundary Layer Initialization (MBLI) scheme, quadruple nested grids (horizontal resolutions of 135, 45, 15, and 5 km), 30 vertical layers, minimum sigma level of 46 m, USGS global land-use, GDAS global gridded model analyses and SSTs, analysis nudging, observational nudging, force-restore surface temperature, 1.5 order TKE, one-way continuous nesting, and a MAPS statistical evaluation. Analysis showed the ozone episode resulting from a unique combination of large-scale upper level synoptic forcings that included a weak local coastal 700 mb anticyclone. Its movement around SoCAB rotated the upper level synoptic background flow from its normal westerly onshore direction to a less common offshore easterly flow during the nighttime period preceding the episode. The resulting easterly upper level synoptic background winds influenced surface flow direction at inland sites, so that a surface frontal convergence zone resulted where the easterly flow met the westerly onshore sea breeze flow. The maximum inland penetration of the convergence zone was about to the San Gabriel Mountain peaks, the location of daytime maximum ozone-episode concentrations. The current MM5 simulations reproduced the main qualitative features of the evolution of the diurnal sea breeze cycle in the SoCAB with reasonable accuracy. The position of the sea breeze front during its daytime inland penetration and nighttime retreat could be determined from the simulated wind fields. the accuracy of predicted MM5 surface winds and temperatures over SoCAB were improved by the modifications of its deep-soil temperatures, interpolation of predicted temperatures and winds to SCOS97 observational levels, use of updated urban land-use patterns, and use of corrected input values for ocean and urban surface roughness parameter values.
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