• Anthes, R. A., 1984: Enhancement of convective precipitation by mesoscale variations in vegetative covering in semiarid regions. J. Climate Appl. Meteor., 23, 541554.

    • Search Google Scholar
    • Export Citation
  • Boyles, R., , Raman S. , , and Sims A. , 2007: Sensitivity of mesoscale precipitation dynamics to surface soil and vegetation contrasts over the Carolina Sandhills. Pure Appl. Geophys., 164, 15471576.

    • Search Google Scholar
    • Export Citation
  • Brown, M. E., , and Arnold D. L. , 1998: Land-surface–atmosphere interactions associated with deep convection in Illinois. Int. J. Climatol., 18, 16371653.

    • Search Google Scholar
    • Export Citation
  • Brown, M. E., , and Wax C. L. , 2007: Temperature as an indicator of the influence of landforms on atmospheric processes. Phys. Geogr., 28, 148157.

    • Search Google Scholar
    • Export Citation
  • Chen, C., , Lin Y. , , Peng W. , , and Liu C. , 2010: Investigation of a heavy rainfall event over southwestern Taiwan associated with a subsynoptic cyclone during the 2003 mei-yu season. Atmos. Res., 95, 235254.

    • Search Google Scholar
    • Export Citation
  • Chen, F., , and Dudhia J. , 2001: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569585.

    • Search Google Scholar
    • Export Citation
  • Clark, A. J., , Gallus W. A. Jr., , and Chen T.-C. , 2007: Comparison of the diurnal precipitation cycle in convection-resolving and non-convection-resolving mesoscale models. Mon. Wea. Rev., 135, 34563473.

    • Search Google Scholar
    • Export Citation
  • Done, J., , Davis C. , , and Weisman M. , 2004: The next generation of NWP: Explicit forecasts of convection using the Weather Research and Forecast (WRF) model. Atmos. Sci. Lett., 5, 110117.

    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107.

    • Search Google Scholar
    • Export Citation
  • Dyer, J. L., 2008: Basin-scale precipitation analysis for southeast U.S. watersheds using high-resolution radar precipitation estimates. Phys. Geogr., 29, 320340.

    • Search Google Scholar
    • Export Citation
  • Dyer, J. L., 2010: Influences of land surface characteristics on precipitation over the lower Mississippi River alluvial plain. Proc. 2009 Mississippi Water Resources Conf., Tunica, MS, Mississippi Water Resources Research Institute 54–67.

    • Search Google Scholar
    • Export Citation
  • Fitzpatrick, P. J., , Li Y. , , Hill C. , , Karan H. , , Lim E. , , and Xiao Q. , 2008: The impact of radar data assimilation on a squall line in Mississippi. Preprints, 24th Conf. on IIPS, New Orleans, LA, Amer. Meteor. Soc., 9A.11. [Available online at http://ams.confex.com/ams/88Annual/techprogram/paper_130773.htm.]

    • Search Google Scholar
    • Export Citation
  • Fulton, R. A., 2002: Activities to improve WSR-88D radar rainfall estimation in the National Weather Service. Proc. Second Federal Interagency Hydrologic Modeling Conf., Las Vegas, NV, Subcommittee on Hydrology, Interagency Advisory Committee on Water Data. [Available online at http://www.weather.gov/oh/hrl/presentations/fihm02/pdfs/qpe_hydromodelconf_web.pdf.]

    • Search Google Scholar
    • Export Citation
  • Hong, X., , Leach M. J. , , and Raman S. , 1995: Role of vegetation in generation of mesoscale circulation. Atmos. Environ., 29, 21632176.

  • Koch, S. E., , and Ray K. A. , 1997: Mesoanalysis of summertime convective zones in central and eastern North Carolina. Wea. Forecasting, 12, 5677.

    • Search Google Scholar
    • Export Citation
  • Kusaka, H., , Crook A. , , Dudhia J. , , and Wada K. , 2005: Comparison of the WRF and MM5 models for simulation of heavy rainfall along the Baiu front. SOLA, 1, 197200.

    • Search Google Scholar
    • Export Citation
  • Lin, Y.-L., , Farley R. D. , , and Orville H. D. , 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., 22, 10651092.

    • Search Google Scholar
    • Export Citation
  • Lowrey, M., , and Yang Z.-L. , 2008: Assessing the capability of a regional-scale weather model to simulate extreme precipitation patterns and flooding in central Texas. Wea. Forecasting, 23, 11021126.

    • Search Google Scholar
    • Export Citation
  • Mahfouf, J.-F., , Richard E. , , and Mascart P. , 1987: The influence of soil and vegetation on the development of mesoscale circulations. J. Climate Appl. Meteor., 26, 14831495.

    • Search Google Scholar
    • Export Citation
  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343360.

  • Miller, L. J., , and Weisman M. L. , 2002: Comparison of radar-observed and WRF-modeled structures of two STEPS storms. Preprints, 21st Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., 299–302.

    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., , Taubman S. J. , , Brown P. D. , , Iacono M. J. , , and Clough S. A. , 1997: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102 (D14), 16 66316 682.

    • Search Google Scholar
    • Export Citation
  • Ookouchi, Y., , Segal M. , , Kessler R. C. , , and Pielke R. A. , 1984: Evaluation of soil moisture effects on the generation and modification of mesoscale circulations. Mon. Wea. Rev., 112, 22812292.

    • Search Google Scholar
    • Export Citation
  • Rabin, R. M., , Stadler S. , , Wetzel P. J. , , Stensrud D. J. , , and Gregory M. , 1990: Observed effects of landscape variability on convective clouds. Bull. Amer. Meteor. Soc., 71, 272280.

    • Search Google Scholar
    • Export Citation
  • Raymond, W. H., , Rabin R. M. , , and Wade G. S. , 1994: Evidence of an agricultural heat island in the lower Mississippi River floodplain. Bull. Amer. Meteor. Soc., 75, 10191025.

    • Search Google Scholar
    • Export Citation
  • Schumacher, R. S., , and Johnson R. H. , 2005: WRF model simulations of a quasi-stationary, extreme-rain-producing mesoscale convective system. Preprints, 11th Conf. on Mesoscale Processes, Albuquerque, NM, Amer. Meteor. Soc., P2M.3. [Available online at http://ams.confex.com/ams/pdfpapers/96608.pdf.]

    • Search Google Scholar
    • Export Citation
  • Segal, M., , Avissar R. , , McCumber M. C. , , and Pielke R. A. , 1988: Evaluation of vegetation effects on the generation and modification of mesoscale circulations. J. Atmos. Sci., 45, 22682292.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., , Klemp J. B. , , Dudhia J. , , Gill D. O. , , Barker D. M. , , Wang W. , , and Powers J. G. , 2005: A description of the Advanced Research WRF Version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp.

    • Search Google Scholar
    • Export Citation
  • Trier, S. B., , Davis C. A. , , Ahijevych D. A. , , Weisman M. L. , , and Bryan G. H. , 2006: Mechanisms supporting long-lived episodes of propagating nocturnal convection within a 7-day WRF model simulation. J. Atmos. Sci., 63, 24372461.

    • Search Google Scholar
    • Export Citation
  • Trier, S. B., , LeMone M. A. , , Chen F. , , and Manning K. W. , 2011: Effects of surface heat and moisture exchange on ARW-WRF warm-season precipitation forecasts over the central United States. Wea. Forecasting, 26, 325.

    • Search Google Scholar
    • Export Citation
  • U.S. Department of Agriculture, cited 2010: Soil Climate Analysis Network (SCAN). [Available online at http://www.wcc.nrcs.usda.gov/scan.]

    • Search Google Scholar
    • Export Citation
  • View in gallery

    (top) Vegetation type and (bottom) soil type over the southeastern United States derived from U.S. Geological Survey 1-km spatial fields. The white box denotes the extent of the 3-km WRF domain used for analysis. The white triangles denote Mississippi SCAN sites used for verification, with station labels as follows: 1—Goodwin Creek Timber, 2—Vance, and 3—Beasley Lake.

  • View in gallery

    (left) GOES visible imagery and (right) WRF-simulated cloud cover [shading scale goes from 0% (lightest) to 100% (darkest) in 10% increments] at (a),(b) 1000, (c),(d) 1200, (e),(f) 1400, and (g),(h) 1600 LST.

  • View in gallery

    (left) Multisensor estimates and (right) WRF-simulated values of precipitation (shading increments from lightest to darkest: 0, 2, 4, 6, 8, 10, 15, 20, 25, 30, 40, and 50 mm) at (a),(b) 1000, (c),(d) 1200, (e),(f) 1400, and (g),(h) 1600 LST.

  • View in gallery

    WRF-simulated (dashed lines) and observations from the SCAN network (solid lines) at Goodwin Creek Timber (dark gray), Beasley Lake (black), and Vance (light gray) for (a) 2-m temperature, (b) 2-m dewpoint, (c) soil temperature at 2-cm depth (0–10-cm average for simulated values), and (d) soil moisture at 2-cm depth (0–10-cm average for simulated values).

  • View in gallery

    The 300-hPa heights (gpm; solid lines), wind magnitude (m s−1; dotted lines and shading), and wind vectors at (a)–(d) 1800 UTC 6–9 Sep 2006, respectively, calculated from the NARR data.

  • View in gallery

    As in Fig. 5, but for 850 hPa and showing temperature (K; dotted lines and shading) in place of wind magnitude.

  • View in gallery

    Mean sea level pressure (hPa; solid lines), wind vectors (m s−1), and (a),(c) temperature (K; dotted lines and shading) or (b),(d) specific humidity (g kg−1; dotted lines and shading) for (left) 1800 UTC 8 and (b) 1800 UTC 9 Sep 2006, calculated from the NARR data.

  • View in gallery

    WRF-simulated (a),(c),(e) temperature (K) and (b),(d),(f) specific humidity (g kg−1) over the study area for1400 LST 9 Sep 2006 at (a),(b) 1000, (c),(d) 850, and (e),(f) 700 hPa. Shading ranges are 295–306 K, 7–16 g kg−1, 288–292.5 K, 7.0–12.5 g kg−1, 276.5–280.5 K, and 2–9 g kg−1 in (a)–(f), respectively.

  • View in gallery

    WRF-simulated surface (left) latent and (right) sensible heat fluxes (W m−2) at (from top to bottom) 0800, 1000, 1200, 1400, and 1600 LST 9 Sep 2006.

  • View in gallery

    Cross section at 34°N latitude showing WRF-simulated specific humidity (g kg−1; shaded) and temperature (K; contours) for (a) 1000 and (b) 1400 LST.

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Analysis of a Warm-Season Surface-Influenced Mesoscale Convective Boundary in Northwest Mississippi

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  • 1 Department of Geosciences, Mississippi State University, Mississippi State, Mississippi
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Abstract

The lower Mississippi River alluvial valley in southeastern Arkansas, northeastern Louisiana, and northwestern Mississippi is characterized by widespread agriculture with few urban areas. Land use is predominantly cultivated cropland with minimal topographic variation; the eastern edge of the alluvial valley is defined by a rapid, although small, change in elevation into a heavily forested landscape, however. This change in land use/land cover has been shown to potentially enhance precipitation through generation of a weak mesoscale convective boundary. This project defines the influence of the land surface on associated precipitation processes by simulating a convective rainfall event that was influenced by regional surface features. Analysis was conducted using a high-resolution simulated dataset generated by the Weather Research and Forecasting Model (WRF). Results show that the strongest uplift coincides with an abrupt low-level thermal boundary, developed primarily by a rapid change from sensible to latent heat flux relative to the agricultural and forested areas, respectively. In addition, surface heating over the cultivated landscape appears to destabilize the boundary layer, with precipitation occurring as air is advected across the land cover boundary and the associated thermal gradient. This information can be used to define and predict surface-influenced convective precipitation along agricultural boundaries in other regions where the synoptic environment is weak.

Corresponding author address: Jamie Dyer, Dept. of Geosciences, Mississippi State University, 355 E. Lee Blvd., 108 Hilbun Hall, Mississippi State, MS 39762-5448.E-mail: jdyer@geosci.msstate.edu

Abstract

The lower Mississippi River alluvial valley in southeastern Arkansas, northeastern Louisiana, and northwestern Mississippi is characterized by widespread agriculture with few urban areas. Land use is predominantly cultivated cropland with minimal topographic variation; the eastern edge of the alluvial valley is defined by a rapid, although small, change in elevation into a heavily forested landscape, however. This change in land use/land cover has been shown to potentially enhance precipitation through generation of a weak mesoscale convective boundary. This project defines the influence of the land surface on associated precipitation processes by simulating a convective rainfall event that was influenced by regional surface features. Analysis was conducted using a high-resolution simulated dataset generated by the Weather Research and Forecasting Model (WRF). Results show that the strongest uplift coincides with an abrupt low-level thermal boundary, developed primarily by a rapid change from sensible to latent heat flux relative to the agricultural and forested areas, respectively. In addition, surface heating over the cultivated landscape appears to destabilize the boundary layer, with precipitation occurring as air is advected across the land cover boundary and the associated thermal gradient. This information can be used to define and predict surface-influenced convective precipitation along agricultural boundaries in other regions where the synoptic environment is weak.

Corresponding author address: Jamie Dyer, Dept. of Geosciences, Mississippi State University, 355 E. Lee Blvd., 108 Hilbun Hall, Mississippi State, MS 39762-5448.E-mail: jdyer@geosci.msstate.edu

1. Introduction

Soil type and vegetation play a key role in determining the dynamics of energy and moisture transport into the atmospheric boundary layer through spatial variations in evapotranspiration, albedo, and surface heat fluxes (Hong et al. 1995; Segal et al. 1988; Ookouchi et al. 1984; Rabin et al. 1990; Mahfouf et al. 1987; Boyles et al. 2007). These effects are well documented and can occur in various climate zones given benign synoptic forcing. Research has shown that anthropogenic modification of spatial boundaries in land use/land cover through agricultural practices can have an influence on regional weather variability through these processes (Brown and Arnold 1998). In addition, agricultural land use can influence the dynamics of the boundary layer through variations in surface roughness over the growing season, effectively modifying existing subsynoptic and mesoscale flow regimes by varying the intensity of turbulent mixing through the radix layer.

The energy, moisture, and turbulent fluxes all have strong influences on the generation and strength of mesoscale circulations, which can affect precipitation generation. As a result, variations in land use and/or soil type can lead to changes in regional precipitation patterns and associated water resources (Anthes 1984). For soil-type interfaces, several studies have demonstrated the role of the sand–clay soil boundary in eastern North Carolina (i.e., the “sandhill effect”) on mesoscale surface convergence and convective precipitation (Boyles et al. 2007; Koch and Ray 1997). Similar soil contrasts, along with distinct vegetation boundaries, exist within the lower Mississippi River alluvial valley in northwest Mississippi (known locally as the Mississippi Delta), and results from Dyer (2008) indicate that precipitation patterns in and around the Mississippi Delta may be influenced by distinct horizontal boundaries in soil type and/or land cover. In addition, studies have shown that abnormal temperature variations in the region exist as a result of spatial variations in soil and vegetation (Raymond et al. 1994; Brown and Wax 2007). These temperature effects could be an indicator of possible boundary layer modification through surface influences, resulting in the generation of mesoscale circulations and related localized precipitation.

Although the modification of atmospheric properties through surface characteristics occurs on a diurnal scale, seasonal variations in land cover and synoptic conditions play a role in the strength and extent of the influence. As a result, it is necessary to study the daily evolution of mesoscale convective processes while keeping in context the seasonal conditions of the region of interest. In general, the spatial extent of surface-influenced atmospheric processes is of the same scale as the land cover discontinuity driving the circulation, with the advection of atmospheric features (cloud cover, precipitation, etc.) dependent on the regional synoptic wind field conditions. The modification of rainfall patterns over northern Mississippi is on the order of 100 km downwind of the Mississippi Delta boundary (Dyer 2008), which indicates that local influences play a dominant role in determining the circulation patterns related to the convective development. To better define the local variability in surface and atmospheric properties, however, it is necessary to determine the characteristic spatial and temporal scale of the land cover boundary and regional meteorological conditions.

The primary objective of this study is to identify the surface influences on mesoscale convective precipitation generation in northwestern Mississippi during the warm season, especially along the eastern boundary of the lower Mississippi River alluvial valley (i.e., the Mississippi Delta). Because of the highly agricultural characteristic of the landscape in this region and the associated sensitivity to water resources, it is important to identify potential causes for precipitation modification due to land surface characteristics during the warm season when mesoscale processes dominate and water availability is critical. The study employs numerical weather model simulations to identify surface and lower-atmospheric processes related to convective precipitation generation. Results of this project provide detailed information regarding precipitation patterns over the Mississippi Delta during the warm season, allowing agriculture and water resource managers to make more accurate local-scale predictions and assessments of water supply and availability.

2. Data and methods

To better understand the influence of land cover and/or soil boundaries on rainfall distribution in the Mississippi Delta, it is necessary to perform an analysis of convective forcing mechanisms and the associated precipitation generation. Because of the lack of high-resolution observation data in the region, this type of study is best performed through numerical modeling; therefore, this project utilizes the Weather Research and Forecasting Model (WRF; Skamarock et al. 2005) to simulate regional surface and atmospheric mechanisms and processes related to rainfall generation. WRF has been used in various research applications dealing with convective systems and initiation (Done et al. 2004; Schumacher and Johnson 2005; Trier et al. 2006; Clark et al. 2007; Fitzpatrick et al. 2008) as well as precipitation distribution and prediction (Miller and Weisman 2002; Kusaka et al. 2005). Research applications using WRF to simulate heavy precipitation related to flooding have also been conducted in various regions around the world, including Taiwan (Chen et al. 2010) and Texas (Lowrey and Yang 2008). In addition, modeling studies have been carried out in various locations to examine the sensitivity of mesoscale circulations to surface characteristics (Mahfouf et al. 1987; Boyles et al. 2007; Hong et al. 1995).

Dyer (2010), using observed and remotely sensed cloud and precipitation data, showed that precipitation over the southeastern United States, and over the Mississippi Delta in particular, shows a distinct seasonal pattern such that the warm season is dominated by surface-initiated convection driven by small-scale thermodynamic boundaries. The regional variations in precipitation patterns were on the order of 100 km relative to the Mississippi Delta, with convective initiation and rainfall generation occurring on a diurnal temporal scale. The surface discontinuity and related convective circulation is on the order of 10 km, however; therefore, high-spatial-resolution data are required to assess the influence of surface properties on atmospheric processes.

To analyze the atmospheric mechanisms associated with this pattern, a day was chosen (9 September 2006) that displayed regional convective precipitation generation and weak synoptic conditions (details on related atmospheric conditions are included in section 4a), indicating that the precipitation was a result of near-surface thermodynamic forcing mechanisms. For the study day, WRF was run for a 24-h period beginning at 0000 local standard time (LST) with 30-min temporal resolution over a domain centered on the eastern boundary of the Mississippi Delta (Fig. 1). The model surface and atmospheric horizontal resolutions were set at 3 km, with 60 vertical atmospheric levels (logarithmic from 1013 to 100 hPa) and a 16-s advection time step, which allowed for adequate simulation of convective processes without the need for a convective parameterization scheme. A single 3-km domain was used instead of a nested setup since synoptic-scale advective processes were considered to be minimal over the study period, minimizing the need for higher-resolution boundary conditions. Atmospheric initial and boundary conditions were provided by the North American Regional Reanalysis (NARR) dataset, which has a 32-km horizontal resolution, 50-hPa vertical resolution, and 3-h temporal resolution (Mesinger et al. 2006). The land and soil states were initialized by the WRF preprocessing system using the default NARR surface data, which are climatological values on a 32-km spatial grid.

Fig. 1.
Fig. 1.

(top) Vegetation type and (bottom) soil type over the southeastern United States derived from U.S. Geological Survey 1-km spatial fields. The white box denotes the extent of the 3-km WRF domain used for analysis. The white triangles denote Mississippi SCAN sites used for verification, with station labels as follows: 1—Goodwin Creek Timber, 2—Vance, and 3—Beasley Lake.

Citation: Journal of Hydrometeorology 12, 5; 10.1175/2011JHM1326.1

Subsequent WRF parameterizations were chosen to best simulate warm-season, surface-based, mesoscale processes. These include the Lin et al. (1983) microphysics scheme, the Mellor–Yamada–Janjic boundary layer scheme, the four-layer Noah land surface model (Chen and Dudhia 2001), the Rapid Radiative Transfer Model scheme for longwave radiation (Mlawer et al. 1997), and the Dudhia (1989) scheme for shortwave radiation. The time step for the radiation schemes was set at 5 min.

Although other parameterization schemes may lead to different model responses, a sensitivity analysis using various parameterizations was beyond the scope of this study. Trier et al. (2011) showed that considerable uncertainty exists in the strength and timing of convective precipitation generation within the WRF during events influenced by surface–atmosphere energy and moisture exchanges. This uncertainty is based on the turbulent surface exchange strength, which is related to vegetation height and surface roughness; therefore, future research plans include an investigation of WRF using a parameter ensemble approach to verify which schemes and surface exchanges coefficients are most applicable for simulation of convective precipitation in the southeastern United States.

Verification of the WRF simulation was accomplished through use of a variety of observed and estimated data sources. Precipitation data are verified against 4 × 4 km2 precipitation estimates from the Multisensor Precipitation Estimator algorithm, which are derived from hourly Weather Surveillance Radar-1988 Doppler (WSR-88D) data and hourly surface-based observations from the Hydrometeorological Automated Data System network (Fulton 2002). Simulated cloud cover is compared with visible imagery from the Geostationary Operational Environmental Satellite (GOES) platform, and surface meteorological characteristics and soil properties from Soil Climate Analysis Network (SCAN) stations in and adjacent to the Mississippi Delta are used to verify related WRF-simulated variables (U.S. Department of Agriculture 2010; Fig. 1).

3. Verification of WRF simulation

Cloud cover patterns over the study area for the morning of 9 September 2006 (1000 LST) initially showed generally clear conditions over Arkansas and northern Louisiana with an increase in convective cloud cover to the south and east (Fig. 2a). In addition, a thin line of convective clouds was apparent along the southeastern boundary of the Mississippi Delta. The WRF-simulated cloud cover reflects this pattern well, showing an increase in cloud cover to the southeast of the study area and a line of clouds along the eastern boundary of the Mississippi Delta (Fig. 2b).

Fig. 2.
Fig. 2.

(left) GOES visible imagery and (right) WRF-simulated cloud cover [shading scale goes from 0% (lightest) to 100% (darkest) in 10% increments] at (a),(b) 1000, (c),(d) 1200, (e),(f) 1400, and (g),(h) 1600 LST.

Citation: Journal of Hydrometeorology 12, 5; 10.1175/2011JHM1326.1

As the day progresses, observed cloud cover becomes more pronounced along the eastern boundary of the Mississippi Delta and east along the Mississippi–Alabama border, with the extent of the cloud area increasing as convection strengthens (Figs. 2c,e). This pattern is maintained through the day, such that by late afternoon (1600 LST; Fig. 2g), the most dense cloud cover roughly exists along the eastern edge of the Mississippi Delta and northwestern Alabama. Although the WRF-simulated cloud patterns show some variability relative to the observed cloud cover, the same general patterns exist. At 1200 LST (Fig. 2d), the most dense cloud cover follows a line roughly parallel to the Mississippi–Alabama border. As the day progresses, a secondary line of convective cloud cover is apparent along the eastern edge of the Mississippi Delta, with a definite clear area becoming more defined through the afternoon (Figs. 2f,h).

The agreement in the observed and simulated cloud cover over the Mississippi–Alabama border and the eastern edge of the Mississippi Delta indicates that WRF is able to recognize and produce reliable convective cloud patterns over the study period. This is critical because of the importance of the cloud cover in the recognition of a convective mesoscale boundary over the study area, as well as the importance of cloud location and extent in association with the simulated surface heat fluxes.

With regard to precipitation patterns, early in the day on 9 September 2006, both the observed and simulated precipitation patterns agree well, despite the minimal amount and extent of rainfall (Figs. 3a,b). Since the rainfall associated with the mesoscale convective boundary initiated along the eastern boundary of the Mississippi Delta is of primary interest in this study, it is critical that the initial timing and location of the precipitation be simulated well. By noon on the study day, the observed precipitation changes little; the WRF-simulated precipitation patterns begin to show some deviation (Figs. 3c,d), however. Although the rainfall along the Mississippi Delta boundary is maintained, scattered rainfall is generated toward the east that is not mirrored in the observed record. The reason for the region of enhanced rainfall may be associated with false convective initiation in the region of maximum low-level moisture advection, which is reflected in the simulated cloud cover at the same time period (Fig. 2d).

Fig. 3.
Fig. 3.

(left) Multisensor estimates and (right) WRF-simulated values of precipitation (shading increments from lightest to darkest: 0, 2, 4, 6, 8, 10, 15, 20, 25, 30, 40, and 50 mm) at (a),(b) 1000, (c),(d) 1200, (e),(f) 1400, and (g),(h) 1600 LST.

Citation: Journal of Hydrometeorology 12, 5; 10.1175/2011JHM1326.1

As the afternoon progresses, the region of enhanced simulated rainfall to the east of the study area is maintained, although the extent continually decreases (Figs. 3f,h). More important, however, are the continuation of rainfall along the eastern boundary of the Mississippi Delta and the lack of rainfall to the west of the study area. The multisensor precipitation estimates show an enhancement of rainfall intensity and extent along the eastern boundary of the study area through the day, with additional precipitation in northwestern Alabama late in the afternoon (Figs. 3e,g). Although the WRF simulation indicates a precipitation boundary along the Mississippi Delta boundary, the rainfall in northeastern Mississippi and northwestern Alabama is maintained throughout the day. The exact reason for this early initiation of precipitation to the east of the study area is likely the early initiation of convection through enhanced low-level moisture inflow within the model domain. The agreement between simulated and observed precipitation patterns along the eastern boundary of the Mississippi Delta is strong enough to accept the WRF-simulated atmospheric conditions and continue with further analysis.

The high level of organization of observed precipitation along the Mississippi Delta boundary provides a good indication of the importance of surface energy and moisture conditions on convective processes during synoptically weak warm-season conditions. Under such conditions, it is the surface boundary that provides the trigger for convective development; therefore, one should expect the generation of organized convection. The fact that the WRF-simulated precipitation patterns do not show the same level of organization, despite a clear indication of surface influence along the Mississippi Delta boundary, gives credence to the inherent difficulty in accurately portraying surface conditions and their impact on local-scale atmospheric conditions.

Verification of WRF-simulated meteorological and surface conditions at select points over the study region using information from SCAN stations shows that near-surface conditions are relatively well resolved (Figs. 4a,b). Although the agreement between the observed and modeled time series of temperature and dewpoint do not match exactly, the relative pattern and magnitude of the variables is maintained over the course of the study period. Specifically, the slightly lower temperature and higher dewpoint over the forested site relative to the sites within the Mississippi Delta indicate that the simulated surface energy and moisture fluxes are representative of actual conditions.

Fig. 4.
Fig. 4.

WRF-simulated (dashed lines) and observations from the SCAN network (solid lines) at Goodwin Creek Timber (dark gray), Beasley Lake (black), and Vance (light gray) for (a) 2-m temperature, (b) 2-m dewpoint, (c) soil temperature at 2-cm depth (0–10-cm average for simulated values), and (d) soil moisture at 2-cm depth (0–10-cm average for simulated values).

Citation: Journal of Hydrometeorology 12, 5; 10.1175/2011JHM1326.1

An examination of soil temperature and moisture shows that although the relative patterns between the simulated and observed data are in agreement, there is some discrepancy in the magnitude (Figs. 4c,d). Note, however, that the values used for verification are not the same, such that the observed values from the SCAN sites are for soil conditions at 2 cm while the WRF-simulated values reflect average soil conditions from 0 to 10 cm. As a result, the general patterns of the time series should match while the magnitudes may be substantially different. The graph of soil temperature (Fig. 4c) shows that both the observed and simulated time series show the same relative minimum in the early morning and maximum at sundown, which is reasonable. In addition, despite the difference in magnitude, neither data source shows much variation in soil moisture over the time period (Fig. 4d). These results provide verification that the WRF is satisfactorily representing soil temperature and moisture patterns over the study period; because of the difference in values being compared (2- vs 0–10-cm average), however, the magnitude of the simulated values cannot be readily verified.

4. Results and analysis

a. Synoptic overview

The day used in this study, 9 September 2006, was previously defined as synoptically benign by Dyer (2010) based on low-level and midlevel wind speeds from regional sounding data. Under conditions in which dynamic lifting mechanisms are negligible, convective precipitation is expected to be generated primarily by mesoscale thermodynamic boundaries set up by differential energy and moisture fluxes at the surface. The ability for preexisting boundaries, such as outflow boundaries or drylines, to trigger convection can make analysis of surface influences on atmospheric properties difficult, however. As such, even when synoptic forcing mechanisms are weak, the complexity and limited scale of mesoscale convective processes make it difficult to accurately define the location and timing of precipitation in response to surface energy fluxes.

To verify that the study period was characterized by weak regional dynamic forcing mechanisms with no preexisting moisture or thermal boundaries, it is necessary to diagnose the general atmospheric conditions over the region. Using the 32-km NARR dataset, meteorological characteristics at the surface, 850 hPa, and 300 hPa were analyzed to show that conditions on and prior to 9 September 2006 over the lower Mississippi River valley were susceptible to surface energy and moisture influences, especially along the eastern edge of the Mississippi Delta.

Although surface and atmospheric conditions over the study region show considerable variability during the warm season, 9 September 2006 showed minimal influence from synoptic or preexisting mesoscale forcing mechanisms. Several days prior to the study period, an upper-level trough moved across the study region (Figs. 5a,b), followed by a zonal flow pattern over the lower Mississippi river valley on 8–9 September (Figs. 5c,d). Near the end of the study period, a weak jet max developed to the west of the Mississippi Delta (Fig. 5d). Although the dynamic lifting mechanisms associated with this upper-level pattern on 9 September 2006 are not strong enough to generate low-level vertical motion (not shown), the upper-level divergence pattern could help to enhance surface-based convection by helping to remove mass from the atmospheric column. As a result, the upper-level synoptic features during the study period do not appear to be the source of the surface-based convection but may play a role in the maintenance of convective cells generated through other mechanisms.

Fig. 5.
Fig. 5.

The 300-hPa heights (gpm; solid lines), wind magnitude (m s−1; dotted lines and shading), and wind vectors at (a)–(d) 1800 UTC 6–9 Sep 2006, respectively, calculated from the NARR data.

Citation: Journal of Hydrometeorology 12, 5; 10.1175/2011JHM1326.1

Low-level synoptic conditions prior to the study period are roughly barotropic, with flow from the northeast on 6 September (Fig. 6a) weakening through 7 September (Fig. 6b). Wind and temperature patterns from 8 to 9 September (Figs. 6c,d) show a gradual transition to south–southeasterly flow over the study region, leading to low-level warm-air advection over the lower Mississippi River valley. By the evening of 9 September, a slight zonal temperature gradient was in place along the eastern edge of the Mississippi Delta (Fig. 6d) as a result of the advection of warm air to the west over Arkansas and northern Louisiana. It is possible that the low-level temperature gradient is the cause of the surface-based convection during the study period; the orientation of this gradient along the eastern boundary of the Mississippi Delta could be a result of surface energy and/or moisture fluxes influencing atmospheric conditions, however. Although the cause and effect of this pattern are difficult to define using the 32-km synoptic data, it is necessary to look at regional surface conditions to verify that surface and low-level patterns coincide.

Fig. 6.
Fig. 6.

As in Fig. 5, but for 850 hPa and showing temperature (K; dotted lines and shading) in place of wind magnitude.

Citation: Journal of Hydrometeorology 12, 5; 10.1175/2011JHM1326.1

As with the wind field at 850 hPa, surface flow on 8–9 September is south–southeasterly across the lower Mississippi River valley (Fig. 7). Despite the southerly flow, however, there is an area of relatively warm, dry air to the northwest of the Mississippi Delta on 8 September (Figs. 7a,c) that decreases in extent into 9 September (Figs. 7b,d). This area is evident at 850 hPa on 9 September (Fig. 6d), where the eastern edge of the moisture and temperature gradient closely follows the edge of the Mississippi Delta at the surface. Interestingly, although the spatial extent of the warm, dry low-level air mass changes considerably from 8 to 9 September, the gradient at the surface remains relatively fixed along the eastern boundary of the Mississippi Delta. This implies that surface conditions along the boundary of the Mississippi Delta are influencing atmospheric conditions on and prior to 9 September, and that preexisting synoptic and/or mesoscale boundaries are most likely not responsible for the generation of convective precipitation during the study period.

Fig. 7.
Fig. 7.

Mean sea level pressure (hPa; solid lines), wind vectors (m s−1), and (a),(c) temperature (K; dotted lines and shading) or (b),(d) specific humidity (g kg−1; dotted lines and shading) for (left) 1800 UTC 8 and (b) 1800 UTC 9 Sep 2006, calculated from the NARR data.

Citation: Journal of Hydrometeorology 12, 5; 10.1175/2011JHM1326.1

Precipitation patterns for the days leading up to 9 September 2006 show normal warm-season scattered rainfall over the study region (not shown); none of the rainfall appears to be of a high enough magnitude to modify soil moisture conditions along the Mississippi Delta boundary, however. As a result, the modification of surface soil moisture gradients based on rainfall leading up to 9 September 2006 is considered to be minimal. It is interesting to note, however, that precipitation patterns for the days leading up to 9 September show a general lack of rainfall over the Mississippi Delta and a regional maximum directly to the east along the Mississippi–Alabama border. This supports the argument that convective boundaries developing because of surface heterogeneities in northwestern Mississippi are influencing local precipitation generation.

b. Analysis of WRF simulation

Analysis of meteorological conditions using the 32-km NARR dataset indicates that surface characteristics within the Mississippi Delta may be influencing low-level atmospheric properties; therefore, it is necessary to utilize the 3-km WRF simulation to identify and analyze the local-scale factors causing this influence. Specifically, atmospheric factors related to vertical thermodynamic stability over the study region must be investigated to define the mechanisms responsible for the initiation of convection and precipitation generation.

The first indication of surface influences on lower-atmospheric processes over northwestern Mississippi on 9 September 2006 occurs as differential surface heating within the lower Mississippi River valley causes near-surface (1000 hPa) air temperatures to increase relative to adjacent regions in the early afternoon (1400 LST; Fig. 8a). At the same time, moisture advection from southeasterly surface winds lead to a relatively tight low-level humidity gradient along the eastern boundary of the Mississippi Delta (Fig. 8b). The same general thermal and moisture pattern exists at 850 hPa (Figs. 8c,d); the area of highest temperatures at this level covers a smaller area over the Mississippi–Louisiana border and west–central Mississippi, however. As a result, the thermal gradient to the east becomes weaker but is more confined to the central Mississippi Delta. Likewise, the moisture gradient becomes more clearly defined along the eastern border of the Mississippi Delta.

Fig. 8.
Fig. 8.

WRF-simulated (a),(c),(e) temperature (K) and (b),(d),(f) specific humidity (g kg−1) over the study area for1400 LST 9 Sep 2006 at (a),(b) 1000, (c),(d) 850, and (e),(f) 700 hPa. Shading ranges are 295–306 K, 7–16 g kg−1, 288–292.5 K, 7.0–12.5 g kg−1, 276.5–280.5 K, and 2–9 g kg−1 in (a)–(f), respectively.

Citation: Journal of Hydrometeorology 12, 5; 10.1175/2011JHM1326.1

Farther aloft at the 700-hPa level, the thermal pattern over the study region is reversed, such that there is a temperature minimum over the lower Mississippi River valley with a rapid increase to the east and west (Fig. 8e). This change in horizontal temperature gradient—where the relative position of the gradient remains stationary while the direction of the gradient changes with height—implies that there is a surface influence over the region driving the low-level energy flux and associated thermal patterns. If advective processes were the cause of the temperature gradient, there would most likely be a change in position with height dependent on the velocity of the horizontal winds, while the relative strength of the gradient would be based on upwind thermal features.

Regarding the moisture patterns over the study region, the gradient at 700 hPa is shifted to the west relative to the lower levels (Fig. 8f), being roughly positioned along the western edge of the region of cooler air over the lower Mississippi River valley. In fact, the thermal and moisture gradients at 700 hPa are closely aligned in southeast Arkansas, which could indicate that the strength of the surface influence on lower-atmospheric properties is beginning to weaken while the influence of the southeasterly flow and moisture advection is beginning to dominate. Note that convective cloud cover was observed and simulated to the east of the Mississippi Delta by 1400 LST on the study day (Figs. 2e,f), indicating that convective processes caused surface moisture to be moved vertically, thereby increasing the lower-level humidity values and horizontal moisture advection over the Mississippi Delta.

The warm, dry conditions at the surface over the Mississippi Delta on 9 September 2006 along with warm, moist air aloft indicates a statically stable atmospheric column; therefore, convective initiation required either an external triggering mechanism or a change in surface and/or low-level atmospheric conditions. For the study period of 9 September 2006, both of these conditions likely come about as a result of modification of atmospheric properties through surface heat fluxes. In general, the lower Mississippi River alluvial valley is characterized by dark, fertile clay soils and low cropland while vegetation to the east consists of relatively dense broadleaf and evergreen forests in loamy soils (Fig. 1). September is near the end of the growing season in the region; therefore, there is a mix of harvested and nonharvested crops. In addition, local water resource management requires an end to agricultural irrigation in August (D. Pennington, Yazoo Mississippi Delta Joint Water Management District, 2008, personal communication). As a result, the amount of evapotranspiration over the Mississippi Delta is much lower than that over the surrounding forested land, leading to considerable variations in the surface heat fluxes.

Figure 9 shows the relatively stark contrast in the sensible and latent heat flux between the lower Mississippi River valley and adjacent regions during the course of the day on 9 September 2006. Even in the morning hours, there is a noticeable minimum in the latent heat flux over the valley, which becomes more pronounced through the afternoon. The opposite is true with the sensible heat flux, which shows a general maximum over the lower Mississippi River valley from late morning through early afternoon when solar heating is greatest. The relatively cloud-free conditions over the Mississippi Delta exacerbate this pattern by maximizing the surface heating over the area, thereby strengthening the gradient along the eastern border of the Mississippi Delta where scattered cloud cover exists beginning in the early afternoon.

Fig. 9.
Fig. 9.

WRF-simulated surface (left) latent and (right) sensible heat fluxes (W m−2) at (from top to bottom) 0800, 1000, 1200, 1400, and 1600 LST 9 Sep 2006.

Citation: Journal of Hydrometeorology 12, 5; 10.1175/2011JHM1326.1

The ramifications of a higher sensible heat flux in the Mississippi Delta relative to surrounding areas are that surface temperatures will increase faster since there is less evapotranspiration to offset the radiation flux. As a result, lower-atmospheric temperatures over the cultivated alluvial valley will increase relative to surrounding areas, causing a dome of warm air to develop because of decreased evapotranspiration over the agricultural surfaces relative to the forested lands to the east. This phenomenon is minimized in the morning when differential surface heating is minimized (Fig. 10a) but is easily recognized in the early afternoon once the surface heat fluxes have intensified (Fig. 10b).

Fig. 10.
Fig. 10.

Cross section at 34°N latitude showing WRF-simulated specific humidity (g kg−1; shaded) and temperature (K; contours) for (a) 1000 and (b) 1400 LST.

Citation: Journal of Hydrometeorology 12, 5; 10.1175/2011JHM1326.1

This dome of warm air can act to destabilize near-surface air advected from outside the region, as is the case for the 9 September 2006 study period where southeasterly flow exists in the lower levels. The relatively warm air over the alluvial valley has a dominant influence during the late morning and early afternoon, as seen by the elevated low-level temperatures (Figs. 8a,c). As convection initiates along this boundary, low-level moisture within the boundary layer from the east is utilized for latent heat release and precipitation generation, leading to deeper convection and, eventually, localized convective rainfall.

In addition to convective uplift due to moisture advection and low-level thermal boundaries, small-scale dynamic forcing is evident along the eastern edge of the Mississippi Delta in the form of near-surface speed confluence (see wind vectors in Fig. 8b). The confluence is strongest in late morning, which is likely a result of a deepening of the boundary layer over the Mississippi Delta region through the early afternoon causing a decrease in local winds due to turbulent mixing. The combination of the thermodynamic and dynamic factors causes low-level convection to intensify along the eastern Mississippi Delta interface before the initiation of a convective precipitation boundary in the afternoon.

While the southeasterly low-level flow causes near-surface air to become unstable along the eastern boundary of the Mississippi Delta where the positive thermal gradient is strongest, westerly flow aloft acts to advect the convective cells and associated precipitation to the east (Fig. 8f). The westerly flow also augments the export of mass from the study area as the convective boundary develops, helping to strengthen and maintain the localized convection and vertical energy and moisture transport. This indirectly leads to an easterly transport of moisture from the study area, which can be considered a source of interbasin water transport.

5. Conclusions

The lower Mississippi River alluvial valley, known regionally as the Mississippi Delta, is characterized by widespread agricultural vegetation and clayey soils, whereas adjacent areas are heavily forested with loamy soils (Fig. 1). The abrupt transition between the surface types leads to high spatial variations in the local energy and moisture balance, which plays a role in the intensity of the sensible and latent heat fluxes because of variations in evapotranspiration and albedo. On days when synoptic-scale wind speeds are weak, vertical development is largely driven by low-level thermodynamic mechanisms related to these heat fluxes; therefore, the influence of surface conditions on atmospheric processes is substantial.

As shown in this project, local discontinuities in near-surface atmospheric properties during periods of benign synoptic forcing can lead to the development of mesoscale convective boundaries and localized precipitation. The specific role of surface conditions in the timing and extent of the convection and convective precipitation over the Mississippi Delta is not well understood, however. Using the Weather Research and Forecasting Model, a high-resolution simulation was done for 9 September 2006, a day characterized as having weak synoptic conditions and development of convective precipitation along the eastern boundary of the Mississippi Delta. This information was used to define and describe the surface characteristics responsible for modification of lower-atmospheric properties and the associated influence on the development of a mesoscale convective boundary.

Results of the WRF simulation indicate that spatial variations in the sensible and latent heat fluxes relative to areas inside and adjacent to the Mississippi Delta are primarily responsible for atmospheric modification through surface processes. To be specific, a relatively high sensible heat flux inside the Mississippi Delta led to the development of a low-level region of warm air while high latent heat values to the east over the forested regions helped to maintain a thermal gradient along the boundary of the study area. The thermal gradient was most intense in the early afternoon near the surface (1400 LST), covering most of the lower Mississippi River alluvial valley in northwestern Mississippi and southeastern Arkansas. The spatial extent of the dome of warm air decreased with height before reversing direction at 700 hPa, at which point the atmospheric temperatures were lower over the Mississippi Delta relative to adjacent regions.

Low-level southeasterly flow interacting with the horizontal thermal gradient near the surface caused a decrease in the vertical static stability over the region, which was augmented by the rapid decrease in atmospheric temperatures with height over the study area. Increased moisture advection along with the development of a mesoscale convergence boundary strengthened the convection along the eastern edge of the Mississippi Delta, leading to deep convection and the generation of convective rainfall. Subsequent westerly flow in the midlevels during the study period acted to transport the convective cloud cover and associated precipitation to the east, effectively leading to dry conditions over the study area as the moisture was transported eastward.

The direct implications of the surface-based modification of atmospheric properties shown in this study include an indication of regional climate modification due to local anthropogenic causes. The transition from forest to agricultural vegetation over the Mississippi Delta directly affects the energy and moisture fluxes into the lower atmosphere, leading to variations in the patterns of warm-season precipitation generation. In essence, the development of a mesoscale convective boundary along the eastern edge of the Mississippi Delta allows for an atmospheric pathway for interbasin water transport. This leads to a net removal of moisture from the agricultural region through increased evapotranspiration and decreased precipitation. Although the use of a single day to study the influence of surface characteristics on convective rainfall generation does not take into account seasonal or annual variations in land cover or atmospheric properties, the fact that warm-season surface conditions can modify local precipitation patterns introduces an area of future research that is critically important to agricultural and water resource managers.

The results of this study show that land surface incongruities, such as soil and vegetation boundaries, can cause horizontal variations in the latent and sensible heat fluxes that are large enough to influence surface-based atmospheric convection. Such is the case over the lower Mississippi River alluvial plain, where low-level moisture advection from the southeast, combined with an increased sensible heat flux over the Mississippi Delta, leads to convective precipitation initiation. This process is similar to that of the urban heat island, although it is often of a larger extent because of the greater extent of rural and agricultural areas throughout the United States. Such precipitation modifications, although minimal relative to mean annual precipitation, could lead to variations in warm-season rainfall distribution. This may potentially lead to water resource issues because of the sensitivity of agriculture to local-scale precipitation patterns during the warm season.

Acknowledgments

The author thanks the Mississippi Water Resources Research Institute and the U.S. Geological Survey for funding to complete this research through Grant 2009MS85B.

REFERENCES

  • Anthes, R. A., 1984: Enhancement of convective precipitation by mesoscale variations in vegetative covering in semiarid regions. J. Climate Appl. Meteor., 23, 541554.

    • Search Google Scholar
    • Export Citation
  • Boyles, R., , Raman S. , , and Sims A. , 2007: Sensitivity of mesoscale precipitation dynamics to surface soil and vegetation contrasts over the Carolina Sandhills. Pure Appl. Geophys., 164, 15471576.

    • Search Google Scholar
    • Export Citation
  • Brown, M. E., , and Arnold D. L. , 1998: Land-surface–atmosphere interactions associated with deep convection in Illinois. Int. J. Climatol., 18, 16371653.

    • Search Google Scholar
    • Export Citation
  • Brown, M. E., , and Wax C. L. , 2007: Temperature as an indicator of the influence of landforms on atmospheric processes. Phys. Geogr., 28, 148157.

    • Search Google Scholar
    • Export Citation
  • Chen, C., , Lin Y. , , Peng W. , , and Liu C. , 2010: Investigation of a heavy rainfall event over southwestern Taiwan associated with a subsynoptic cyclone during the 2003 mei-yu season. Atmos. Res., 95, 235254.

    • Search Google Scholar
    • Export Citation
  • Chen, F., , and Dudhia J. , 2001: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569585.

    • Search Google Scholar
    • Export Citation
  • Clark, A. J., , Gallus W. A. Jr., , and Chen T.-C. , 2007: Comparison of the diurnal precipitation cycle in convection-resolving and non-convection-resolving mesoscale models. Mon. Wea. Rev., 135, 34563473.

    • Search Google Scholar
    • Export Citation
  • Done, J., , Davis C. , , and Weisman M. , 2004: The next generation of NWP: Explicit forecasts of convection using the Weather Research and Forecast (WRF) model. Atmos. Sci. Lett., 5, 110117.

    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107.

    • Search Google Scholar
    • Export Citation
  • Dyer, J. L., 2008: Basin-scale precipitation analysis for southeast U.S. watersheds using high-resolution radar precipitation estimates. Phys. Geogr., 29, 320340.

    • Search Google Scholar
    • Export Citation
  • Dyer, J. L., 2010: Influences of land surface characteristics on precipitation over the lower Mississippi River alluvial plain. Proc. 2009 Mississippi Water Resources Conf., Tunica, MS, Mississippi Water Resources Research Institute 54–67.

    • Search Google Scholar
    • Export Citation
  • Fitzpatrick, P. J., , Li Y. , , Hill C. , , Karan H. , , Lim E. , , and Xiao Q. , 2008: The impact of radar data assimilation on a squall line in Mississippi. Preprints, 24th Conf. on IIPS, New Orleans, LA, Amer. Meteor. Soc., 9A.11. [Available online at http://ams.confex.com/ams/88Annual/techprogram/paper_130773.htm.]

    • Search Google Scholar
    • Export Citation
  • Fulton, R. A., 2002: Activities to improve WSR-88D radar rainfall estimation in the National Weather Service. Proc. Second Federal Interagency Hydrologic Modeling Conf., Las Vegas, NV, Subcommittee on Hydrology, Interagency Advisory Committee on Water Data. [Available online at http://www.weather.gov/oh/hrl/presentations/fihm02/pdfs/qpe_hydromodelconf_web.pdf.]

    • Search Google Scholar
    • Export Citation
  • Hong, X., , Leach M. J. , , and Raman S. , 1995: Role of vegetation in generation of mesoscale circulation. Atmos. Environ., 29, 21632176.

  • Koch, S. E., , and Ray K. A. , 1997: Mesoanalysis of summertime convective zones in central and eastern North Carolina. Wea. Forecasting, 12, 5677.

    • Search Google Scholar
    • Export Citation
  • Kusaka, H., , Crook A. , , Dudhia J. , , and Wada K. , 2005: Comparison of the WRF and MM5 models for simulation of heavy rainfall along the Baiu front. SOLA, 1, 197200.

    • Search Google Scholar
    • Export Citation
  • Lin, Y.-L., , Farley R. D. , , and Orville H. D. , 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., 22, 10651092.

    • Search Google Scholar
    • Export Citation
  • Lowrey, M., , and Yang Z.-L. , 2008: Assessing the capability of a regional-scale weather model to simulate extreme precipitation patterns and flooding in central Texas. Wea. Forecasting, 23, 11021126.

    • Search Google Scholar
    • Export Citation
  • Mahfouf, J.-F., , Richard E. , , and Mascart P. , 1987: The influence of soil and vegetation on the development of mesoscale circulations. J. Climate Appl. Meteor., 26, 14831495.

    • Search Google Scholar
    • Export Citation
  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343360.

  • Miller, L. J., , and Weisman M. L. , 2002: Comparison of radar-observed and WRF-modeled structures of two STEPS storms. Preprints, 21st Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., 299–302.

    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., , Taubman S. J. , , Brown P. D. , , Iacono M. J. , , and Clough S. A. , 1997: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102 (D14), 16 66316 682.

    • Search Google Scholar
    • Export Citation
  • Ookouchi, Y., , Segal M. , , Kessler R. C. , , and Pielke R. A. , 1984: Evaluation of soil moisture effects on the generation and modification of mesoscale circulations. Mon. Wea. Rev., 112, 22812292.

    • Search Google Scholar
    • Export Citation
  • Rabin, R. M., , Stadler S. , , Wetzel P. J. , , Stensrud D. J. , , and Gregory M. , 1990: Observed effects of landscape variability on convective clouds. Bull. Amer. Meteor. Soc., 71, 272280.

    • Search Google Scholar
    • Export Citation
  • Raymond, W. H., , Rabin R. M. , , and Wade G. S. , 1994: Evidence of an agricultural heat island in the lower Mississippi River floodplain. Bull. Amer. Meteor. Soc., 75, 10191025.

    • Search Google Scholar
    • Export Citation
  • Schumacher, R. S., , and Johnson R. H. , 2005: WRF model simulations of a quasi-stationary, extreme-rain-producing mesoscale convective system. Preprints, 11th Conf. on Mesoscale Processes, Albuquerque, NM, Amer. Meteor. Soc., P2M.3. [Available online at http://ams.confex.com/ams/pdfpapers/96608.pdf.]

    • Search Google Scholar
    • Export Citation
  • Segal, M., , Avissar R. , , McCumber M. C. , , and Pielke R. A. , 1988: Evaluation of vegetation effects on the generation and modification of mesoscale circulations. J. Atmos. Sci., 45, 22682292.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., , Klemp J. B. , , Dudhia J. , , Gill D. O. , , Barker D. M. , , Wang W. , , and Powers J. G. , 2005: A description of the Advanced Research WRF Version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp.

    • Search Google Scholar
    • Export Citation
  • Trier, S. B., , Davis C. A. , , Ahijevych D. A. , , Weisman M. L. , , and Bryan G. H. , 2006: Mechanisms supporting long-lived episodes of propagating nocturnal convection within a 7-day WRF model simulation. J. Atmos. Sci., 63, 24372461.

    • Search Google Scholar
    • Export Citation
  • Trier, S. B., , LeMone M. A. , , Chen F. , , and Manning K. W. , 2011: Effects of surface heat and moisture exchange on ARW-WRF warm-season precipitation forecasts over the central United States. Wea. Forecasting, 26, 325.

    • Search Google Scholar
    • Export Citation
  • U.S. Department of Agriculture, cited 2010: Soil Climate Analysis Network (SCAN). [Available online at http://www.wcc.nrcs.usda.gov/scan.]

    • Search Google Scholar
    • Export Citation
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