<p>Mesoscale processes, dictated by surface characteristics, play adominant role in the development of the planetary boundary layer (PBL)structure and the formation of convection. The effect of mesoscale processeson the boundary layer structure also has significant implications in theunderstanding of circulation patterns and regional scale predictability. Largegeographical variability in North Carolina (NC) provides a wide variety ofweather events and climatological regimes.There are many challenges for numerical modeling in NC due to theheterogeneity in topography, land use, and soil type, presence of the oceanand the Gulf Stream. These heterogeneous attributes feature an excellentlocation for simulations and validation of the MM5 numerical modeling systemwith observations of high spatial and temporal resolution.MM5 is utilized for a non-precipitation case and a convective caseincluding precipitation with a 5-km domain centered over the Carolinas.Model integration is for 72 hours from 0000Z August 15, 2000 to 0000ZAugust 18, 2000. Simulated hourly surface and sub-surface values areevaluated against in-situ surface observations. These simulations consist ofreal case studies involving MM5 Version 3 with the MRF PBL schemecoupled to the Oregon State University (OSU) land surface model (LSM).The OSU LSM uses 1 km resolution land-use and soil data as input into MM5for capturing the dynamics of land-surface forcing.The acquisition and combination of different agro-meteorological dataacross NC provides high-resolution observations used for validation atmultiple model grid points. For the case studies, these data incorporate hourlyobservation sites throughout North Carolina including 19 ASOS (AutomatedSurface Observing Sites / owned and operated by the NWS and FAA) sitesand 15 ECONet (Environmental and Climate Observing Network: maintainedby State Climate Office of North Carolina) sites. Multiple parameterscompared and investigated using this network of observations include:ECONet: Air Temperature (2m), Relative Humidity (2m), Wind Speed (10m),Wind Direction (10m), Soil Temperature (10 cm), Soil Moisture (10cm), HourlyPrecipitation rate; ASOS: Air Temperature (2m), Dewpoint (2m), Wind Speed(10m), Wind Direction (10m), Hourly Precipitation, Weather Conditions, andCloud Layers.The approach involves examination of simulated horizontal and verticalwind patterns across the coast, piedmont, and mountainous regions in NorthCarolina. These simulated wind fields are used to investigate local land-seainteractions near the coast, effects of land surface processes in the piedmont,and pollution transport potential over complex terrain in the mountains of North Carolina. Precipitation patterns generated by the model are alsocompared with daily observations of precipitation amounts in conjunction withthe hourly stations across the central portion of the 5 km domain, particularlyNorth and South Carolina.Following a graphical comparison of 2D and 3D fields, statisticalmethods are applied to provide quantitative relationships for errors and biasesin the simulations. The analyses give additional insight into modelperformance. This is especially important when validating complex andcomprehensive interactions and processes that occur in North Carolina.Statistical measures used include: absolute correlation, root mean squareerror (RMSE), bias, normalized mean square error (NMSE), weightednormalized mean square error of the normalized ratios (WNNR), normalizedmean square error of the distribution of the normalized ratios (NNR), and theindex of agreement.Diurnal variation is handled well by the model indicating that thethermodynamic structure of the atmosphere is well simulated. Nocturnalboundary layer processes are poorly simulated, particularly in western NC,and heterogeneous surface features have significant effects on regional scaleprocesses including boundary layer structure and precipitation patterns.Model performance degrades over regions with complex terrain signifying thatmore observations are needed to develop regionally consistent flow patterns.Precipitation patterns are simulated with a fair amount of accuracy whenincluding the Kain-Fritsch cumulus parameterization scheme.<P>
| Identifer | oai:union.ndltd.org:NCSU/oai:NCSU:etd-20011031-181856 |
| Date | 01 November 2001 |
| Creators | Sims, Aaron Paul |
| Contributors | Sethu Raman, Kiran Alapaty, Gerald Watson, Dev dutta S. Niyogi |
| Publisher | NCSU |
| Source Sets | North Carolina State University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://www.lib.ncsu.edu/theses/available/etd-20011031-181856 |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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