The Diurnal Cycle of Land–Atmosphere Interactions across Oklahoma’s Winter Wheat Belt

Matthew J. Haugland Oklahoma Climatological Survey, University of Oklahoma, Norman, Oklahoma

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Kenneth C. Crawford Oklahoma Climatological Survey, University of Oklahoma, Norman, Oklahoma

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Abstract

This manuscript documents the impact of Oklahoma’s winter wheat belt (WWB) on the near-surface atmosphere by comparing the diurnal cycle of meteorological conditions within the WWB relative to conditions in adjacent counties before and after the wheat harvest.

To isolate the impact of the winter wheat belt on the atmosphere, data from several meteorological parameters were averaged to create a diurnal cycle before and after the wheat harvest. Observations from 17 Oklahoma Mesonet sites within the WWB (during a period of 9 yr) were compared with observations from 22 Mesonet sites in adjacent counties outside the winter wheat belt.

The average diurnal cycles of dewpoint, temperature, and surface pressure exhibited patterns that revealed a distinct mesoscale impact of the wheat fields. The diurnal patterns were consistent with the status of the wheat crop and the grassland in adjacent counties. The impact of the WWB was shown to be more significant during a month when soil moisture was abundant, and minimal during a month when soil moisture was limited. Statistically significant, hydrostatically consistent afternoon surface pressure anomalies suggest that there is a strong possibility of weak mesoscale circulations induced by the WWB.

Corresponding author address: Matthew J. Haugland, Oklahoma Climatological Survey, 100 E. Boyd St., Suite 1210, Norman, OK, 73019. Email: haugland@ou.edu

Abstract

This manuscript documents the impact of Oklahoma’s winter wheat belt (WWB) on the near-surface atmosphere by comparing the diurnal cycle of meteorological conditions within the WWB relative to conditions in adjacent counties before and after the wheat harvest.

To isolate the impact of the winter wheat belt on the atmosphere, data from several meteorological parameters were averaged to create a diurnal cycle before and after the wheat harvest. Observations from 17 Oklahoma Mesonet sites within the WWB (during a period of 9 yr) were compared with observations from 22 Mesonet sites in adjacent counties outside the winter wheat belt.

The average diurnal cycles of dewpoint, temperature, and surface pressure exhibited patterns that revealed a distinct mesoscale impact of the wheat fields. The diurnal patterns were consistent with the status of the wheat crop and the grassland in adjacent counties. The impact of the WWB was shown to be more significant during a month when soil moisture was abundant, and minimal during a month when soil moisture was limited. Statistically significant, hydrostatically consistent afternoon surface pressure anomalies suggest that there is a strong possibility of weak mesoscale circulations induced by the WWB.

Corresponding author address: Matthew J. Haugland, Oklahoma Climatological Survey, 100 E. Boyd St., Suite 1210, Norman, OK, 73019. Email: haugland@ou.edu

1. Introduction

The interaction between the land and the atmosphere has become a subject of great interest and speculation. The interaction has been modeled and observed by many, but relatively little is known about the complex and nonlinear relationship between land surface features and the atmosphere (André et al. 1990; Pielke et al. 1991). Previous studies of land–atmosphere interactions have been limited by a lack of long-term, high quality mesoscale data. The purpose of this manuscript is to document the impact of Oklahoma’s winter wheat belt on the atmosphere using 9 yr of quality-assured mesoscale observations from the Oklahoma Mesonetwork (hereafter referred to as Mesonet; Brock et al. 1995; Shafer et al. 2000; Fiebrich and Crawford 2001).

The winter wheat belt (WWB) is defined, as by McPherson et al. (2004), as the swath of land across Oklahoma and Kansas that was characterized by either winter wheat or a winter wheat/grassland mix as the land use type designated by the U.S. Geological Survey. A small part of the WWB extends into north Texas. This study focuses on the portion of the winter wheat belt within the boundaries of Oklahoma. The WWB is approximately 100–150 km wide and stretches from north-central to southwest Oklahoma (Fig. 1). It is a near-ideal outdoor laboratory for the study of land–atmosphere interactions. Winter wheat is a cold-season crop planted during the fall. It grows until December and then becomes dormant. The winter wheat begins growing again by the end of winter and flourishes during the spring months. Winter wheat is harvested during late May or early June. By mid-June, only bare soil and dead wheat stubble remain in the winter wheat fields (McPherson et al. 2004).

The winter wheat belt is surrounded by mixed vegetation that is primarily grassland. While the amount of green vegetation across most of Oklahoma increases from April to June, vegetation across the WWB is greatly reduced by the harvest. During the months preceding the harvest, the WWB is a strip of anomalously abundant green vegetation (Fig. 2). After the harvest, the WWB is a strip of anomalously sparse green vegetation (Fig. 3).

This manuscript documents the impact of the WWB by comparing meteorological conditions within the WWB relative to conditions in adjacent counties before and after the wheat harvest. Because land–atmosphere interactions are driven by physical processes represented by components in the surface energy balance equation, the interactions are shown to exhibit a well-defined diurnal cycle. Archives of Mesonet data are analyzed to determine the impact of the winter wheat fields on the diurnal cycle of temperature, dewpoint, and surface air pressure.

2. Scientific background

Entekhabi (1995) recognized that an accurate representation of land–atmosphere interactions would be essential to model small-scale atmospheric phenomena realistically. Thus, detailed land cover data have been incorporated into mesoscale forecast models by many scientists (Avissar and Pielke 1989; Xue et al. 1991; Wetzel and Boone 1995; Mahfouf et al. 1995; Manning and Davis 1997; Chen et al. 1997; Wen et al. 2000; Slater et al. 2001). The collective results have shown significant sensitivity to differences in land cover and how it has been parameterized within the mesoscale models. In some cases, land cover data significantly improved the mesoscale forecasts (Crawford et al. 2001). In other cases, the land cover parameterization reduced the accuracy of mesoscale forecasts (Crawford et al. 2001). It seems clear that the full potential of mesoscale models will not be realized until a better understanding is attained regarding how land cover impacts the atmosphere. This study uses mesoscale observations to demonstrate and help explain the impact of a specific land cover on the atmosphere.

Harvested wheat fields during summer months cause an increased Bowen ratio (ratio of sensible to latent heat flux), which results in a warm anomaly over the winter wheat belt. Rabin et al. (1990) determined that the warm surface anomaly was a favorable area for convective cloud development on relatively dry days when synoptic-scale forcing was weak. Using satellite imagery, they observed that clouds had a tendency to develop first over the harvested wheat fields. Unfortunately, their study, conducted during the late 1980s, did not have access to long-term data from a mesoscale observation network. Thus, they were unable to quantify the impact of the wheat fields on the local atmosphere.

McPherson et al. (2004) used data from the Oklahoma Mesonet to measure the impact of Oklahoma’s winter wheat belt on the mesoscale environment. They documented a well-defined cool anomaly that existed across the wheat belt during the winter and early spring while a well-defined warm anomaly existed across the wheat belt during the late spring and into the summer. These anomalies were focused on only five–six counties in northwest Oklahoma. Their comprehensive analysis demonstrated that Oklahoma’s winter wheat belt has a dramatic impact on the near-surface, mesoscale environment during its growth and after its harvest.

Markowski and Stensrud (1998) used a small mesoscale network of surface sites to observe large horizontal variations in the mean diurnal cycle of temperature and specific humidity across western Oklahoma during May and June of 1985. They concluded that those variations were caused by convective clouds and inhomogeneous land cover. Soil moisture also was found to be an important influence on the diurnal cycle of dewpoint. Basara and Crawford (2002) discovered a linear relationship between latent heat flux and root-level soil moisture. Based on those discoveries, one can infer that the diurnal cycle also is influenced by antecedent precipitation. For example, significant spatial variations in the diurnal cycle of temperature and dewpoint have been observed across tight gradients of antecedent rainfall in northern Oklahoma (Arndt and Crawford 2002).

Large heterogeneous surfaces have been shown to produce mesoscale solenoidal circulations (Segal et al. 1989; Mahrt et al. 1994; Rife et al. 2002). Yan and Anthes (1988) developed a numerical model to simulate inland “sea breezes.” Using this model, they documented how a dry strip of land surrounded by moist land produced a soleniodal circulation that was effective in generating precipitation. They found dry strips on the order of 100 km wide were particularly effective. Thus, they documented how inhomogeneous surface moisture conditions could produce inland “sea breeze” circulations with a magnitude equal to that of a coastal sea breeze when synoptic-scale forcing was insignificant. A similar geometric and dynamic configuration is created in western Oklahoma during the months following the winter wheat harvest.

Segal and Arritt (1992) concluded that an emphasis on observations would be essential for further progress in the quantification of real-world inland sea-breeze circulations. This manuscript presents observational evidence that an inland sea-breeze circulation is induced by differential heating across the WWB. It also documents the impact of external influences such as antecedent precipitation on the diurnal cycle of temperature, dewpoint, and pressure across the WWB.

3. Methodology

a. Dataset and averaging

The Oklahoma Mesonet is a statewide network of 114 automated weather stations. At least one Mesonet site is located in each county of the state, and the average distance between sites is 32 km (Brock et al. 1995). The data used in this study are Mesonet observations averaged over the last 5 min of each hour. During the spring and summer months (1 March to 31 August) of 1994–2002, approximately 40 000 hourly observations per variable per Mesonet site were acquired; they serve as the basis for this study. Temperature, relative humidity, and surface pressure were directly measured. Dewpoint was derived from measurements of temperature and relative humidity.

Some 15 Mesonet sites are located within the heart of the winter wheat belt where winter wheat is the primary vegetation type. Two sites in close proximity to (but not within) the winter wheat belt were considered WWB sites because they are located within 2 km of large winter wheat fields. The remaining sites within the winter wheat belt were not included because the primary vegetation type near those sites was not winter wheat.

Atmospheric conditions in adjacent counties (AC) outside the WWB are represented by 22 sites. Eleven of the AC sites are east of the WWB and 11 are west of the WWB. The geographic centroid of the 17 WWB sites is 2.01 km south and 0.23 km west of the geographic centroid of the 22 AC sites. The average elevation of the WWB sites is 42.1 m below the average elevation of the AC sites (Table 1; Fig. 4). Because the average latitude, longitude, and elevation of the 17 WWB sites is almost identical to that of the 22 AC sites, the relative differences in atmospheric parameters across this region of Oklahoma must be created by features in the landscape.

Observed values of meteorological parameters at a particular hour of the day were averaged during each spring and summer month from 1994 to 2002. This methodology was extended such that parameter averages were computed for each hour of the 24-h day, thereby producing an average diurnal cycle of each meteorological parameter used in this study. The 9-yr averaging minimized the effects of small-scale atmospheric variability unrelated to the land surface pattern.

b. Significance testing

Statistical quantities were computed using the bootstrap method for spatial variances (Efron 1979). The purpose of these computations was to determine whether differences in the diurnal means between the WWB and AC sites were greater than what could be expected from random selections of the 39 Mesonet sites used in this study. For a given month, diurnal averages of parameters at each site were computed using 9 yr of observations. These diurnal averages were pooled into a group of 39 different averages representing the 39 Mesonet sites. Two groups were randomly selected from the pool. One group was drawn from 17 randomly selected sites, and the other group included the remaining 22 sites. The difference between the means of the two groups was calculated. The process was repeated 10 000 times (each time using new groups of randomly selected sites) and yielded a normal distribution of mean diurnal differences that was used to compute confidence intervals.

A difference between the WWB and AC sites for a given parameter is said to be statistically significant if the 90% confidence range is entirely above or below zero. Significance in this case means the observed difference between the WWB and AC is significant compared to the differences that would be expected from averaging parameters at random sites in western Oklahoma.

c. Normalized solar time

For each parameter, the average diurnal cycle, average difference between the diurnal cycle at the WWB and AC sites, and 90% confidence intervals were plotted as a function of normalized solar hours after sunrise. Normalized solar hours are obtained by dividing the 24-h day into 12 equal daytime “hours” and 12 equal nighttime “hours.” The relative duration of normalized daytime and nighttime hours depends on the relative duration of daylight. Thus, sunset is always 12 normalized solar hours after sunrise, regardless of the season. Likewise, solar noon is always 6 normalized solar hours after sunrise.

d. Surface air pressure normalization

The average elevation difference between the WWB and AC sites caused surface air pressure differences of approximately 4 hPa. To compare the diurnal cycle of pressure between sites within the WWB and AC, it was desirable to reduce pressure to sea level or to a particular reference height. However, a temperature-dependent reduction of pressure was not used because the expected error was the same order of magnitude as were regional differences in the reduced pressure. To eliminate this error, a normalized surface pressure was computed by subtracting a constant value, the average nighttime pressure observed at each site, from the station pressure at each site. The average nighttime pressure was subtracted because surface temperature inhomogeneities were expected to cause much smaller pressure differences at night compared to daytime. Because of the relatively shallow depth of the boundary layer at night, surface inhomogeneities were considered to have a minimal impact. If a spatial pressure anomaly is defined as the relative difference in surface pressure between the WWB and AC sites from sunrise to midafternoon, the normalization of pressure in the manner outlined would have no effect on the results. However, the normalized pressure was plotted because it was considered to give a clearer illustration of the physical processes involved.

4. Results

a. Dewpoint

The diurnal cycle of dewpoint across the WWB and AC sites revealed processes that impact near-surface moisture (Fig. 5). At sunrise, evapotranspiration (ET) increased as morning dew was quickly evaporated, causing a sharp increase of the dewpoint during the first 2–4 h after sunrise. The stable low-level atmosphere during this postsunrise period forced ground-based moisture to remain near the surface without being mixed to higher levels. As surface temperature increased during the day and low-level stability decreased, drier air above the morning boundary layer mixed down to the surface. That process is known as dry air entrainment (DAT). The result was a decrease of the surface dewpoint during the course of the day. During the afternoon hours, evapotranspiration was at a maximum because the vapor pressure deficit (i.e., the difference in vapor pressure between the vegetation and the surrounding atmosphere) was at a maximum. However, the surface-based moisture gained from ET usually did not offset the DAT across western Oklahoma. As a result, surface moisture decreased during the afternoon; a minimum value of dewpoint usually occurred during the late-afternoon hours.

By sunset, decreasing surface temperatures led to increased near-surface stability and a reduction in vertical mixing and DAT. The result was an increase in the surface dewpoint that began a few hours before sunset because continuous ET finally exceeded the diminishing DAT. At sunset, solar heating ended, the low-level atmosphere became stable, and DAT ended. The stable atmosphere trapped moisture from ET near the surface. Without DAT to offset ET, the dewpoint across Oklahoma reached a maximum value after sunset. During the nighttime, temperature decreased and approached the dewpoint. As the relative humidity near the surface reached 100%, water vapor near the ground was converted to dew through condensation. Thereafter, a steady decrease of the dewpoint signaled a steady increase in dew until sunrise.

During the growing season of winter wheat, the amount of green vegetation across the winter wheat belt was greater than observed in adjacent counties. The result was a larger ET influence on near-surface atmospheric water vapor across the WWB relative to that in adjacent counties during the late-winter and early-spring months. During March, a west–east average dewpoint gradient was observed at sunrise (not shown), which was most likely created by the average precipitation and elevation gradients across western Oklahoma. However, these gradients were effectively cancelled out by the selection of AC sites, which included an equal number of stations east and west of the WWB. Thus, the average dewpoint at sunrise across the winter wheat belt was nearly the same as that observed across adjacent counties (Fig. 6). During the day, dry air entrainment reduced the surface dewpoint across most of Oklahoma. However, the average March dewpoint within the winter wheat belt increased throughout the day because of greater evapotranspiration (Fig. 7). From noon to sunset, the average dewpoint across the winter wheat belt was approximately 1.2°–1.6°C higher than those observed in adjacent counties (Fig. 8). During most of the day and the first half of the night, average dewpoint differences between the WWB and AC sites were statistically significant compared to a random selection of sites in western Oklahoma. On clear days with light winds, the impact of the WWB on the diurnal cycle of dewpoint was even more significant (not shown). Afternoon dewpoint differences (between the WWB and AC) of up to 4°C were observed on individual days (not shown).

The late-spring wheat harvest reduced the wheat fields to bare soil and dead wheat stubble. As a result, evapotranspiration was greatly reduced across the WWB. While the diurnal cycle of dewpoint outside the WWB changed very little from spring to summer, dramatic changes occurred in this diurnal cycle within the WWB (Figs. 6 and 9).

As observed before the harvest, the average dewpoints within and outside the WWB were approximately equal at sunrise (i.e., the average dewpoint difference between the two zones was zero). However, the reduction of dewpoint values by DAT within the WWB occurred earlier in the day than that within the AC. During the afternoon, the average dewpoint outside the WWB decreased, but remained higher than observed at sunrise. Within the WWB, the afternoon dewpoint was lower than that observed at sunrise (Figs. 9 and 10). The average dewpoint difference reached a maximum of −0.6°C during the midafternoon, the only period in which the difference was statistically significant (Figs. 9 and 11). On clear days with light winds, afternoon dewpoint differences of up to −3°C have been observed. One can infer that after the harvest, the diurnal cycle of dewpoint across the WWB is dominated by DAT, but during the spring it is dominated by ET.

The diurnal cycle of dewpoint illustrates the combined interaction of soil moisture, vegetation, and the atmosphere. Oklahoma received above-average rainfall during June 2000 (evenly distributed across the WWB and AC), and there was therefore abundant soil moisture during the month of July. As a result, the average diurnal cycle of dewpoint observed at Mesonet sites during July 2000 revealed significant differences between sites within the WWB and sites in adjacent counties (Fig. 12). These differences were more pronounced than during a typical July represented by 9 yr of archived Mesonet data (not shown). During the late-morning hours of July 2000, the dewpoint across the winter wheat belt (mostly bare soil and dead wheat stubble) decreased more quickly than observed in surrounding areas. This is apparently because the vegetation within the AC was very effective in transporting ground moisture to the atmosphere (counteracting the effects of DAT). By midafternoon, the average dewpoint across the WWB was 1°C lower than observed across adjacent counties.

During a drought when soil moisture is minimal, the amount of water transported to the atmosphere by vegetation is reduced. During the spring of 1998, very little rainfall occurred across Oklahoma. As a result, Oklahoma experienced drought conditions by July. Shortly after sunrise during an average day in July 1998, evapotranspiration was quickly overcome by dry air entrainment. As a result, the dewpoint across both regions (Fig. 12) decreased sharply until midafternoon. The average dewpoint across western Oklahoma during the afternoon was approximately 1.5°C lower than the average dewpoint shortly before sunrise (Fig. 12). The dewpoint increased during the late afternoon as solar heating and vertical mixing decreased. However, the average dewpoint reached a broad plateau near sunset, which indicated minimal ET. The dewpoint remained steady from sunset to sunrise, which indicated minimal condensation at night. Unlike in July 2000, the diurnal cycle of dewpoint during July 1998 was nearly identical within the WWB and AC.

One can conclude that, without sufficient soil moisture, the impact of inhomogeneous vegetation (i.e., the harvested wheat fields contrasted with the native vegetation to the east and west) on the atmosphere is minimal. However, the impact is amplified when soil moisture is abundant, as occurred during July 2000.

The vertical profile of moisture is another important factor that influences the diurnal cycle of dewpoint. On days when the dewpoint near the top of the boundary layer decreased sharply with height, such as 8 June 2000 (Fig. 13), the harvested wheat fields had their greatest impact on the diurnal cycle of dewpoint (not shown). It is hypothesized that if the winter wheat belt were located in a region with deeper moisture, such as near the Gulf Coast, dry air entrainment would be a smaller factor and the WWB’s impact on the diurnal cycle of dewpoint during spring and summer would be less dramatic.

b. Temperature and pressure

Evapotranspiration also has a major impact on temperature. Before harvest, the increased ET across the WWB causes more incoming solar radiation to be partitioned into latent heat flux (evaporation) relative to sensible heat flux (Rabin et al. 1990). As a result, the surface air temperature across the WWB is moderated during the afternoon hours of the wheat-growing season (compared to air temperature in the AC). If these surface temperature anomalies are distributed through a deep enough portion of the boundary layer, they create weak pressure gradients at the surface. In turn, a solenoidal circulation known as an “inland sea breeze” should result (Yan and Anthes 1988). During the growing season of winter wheat, the average afternoon temperature across the winter wheat belt is lower than observed in adjacent counties (Fig. 14). In turn, the temperature anomaly over the WWB hydrostatically should create a collocated surface high pressure anomaly.

Before harvest, the average difference in the surface potential temperature between the WWB and the AC reaches a maximum during the midafternoon hours. As a result, the normalized surface pressure difference reaches a maximum (i.e., a relative high pressure anomaly is collocated over the cool anomaly of the WWB). The phenomenon is clearly observed during March, when the WWB is most green compared to adjacent counties (Fig. 15). The average difference in the midafternoon potential temperature is − 0.9 K while the average normalized pressure difference is + 0.09 hPa.1 During the late-afternoon and early-evening hours, the average potential temperature and normalized pressure differences are almost eliminated and spatial gradients become relaxed. The potential temperature and normalized pressure differences are statistically significant during the midafternoon hours. One can infer that this vegetation-induced pressure gradient should cause a response in the wind field (an inland sea-breeze circulation). Thus, the equalization of pressure between the WWB and AC signals the end of this circulation.

After the winter wheat harvest, the green vegetation across the WWB significantly decreased, which causes evapotranspiration to be minimal. As a result, most of the incoming solar energy is partitioned into sensible heat flux (Rabin et al. 1990). Average afternoon temperatures across the WWB during the summer months are higher than those observed in adjacent counties (Fig. 16). The maximum temperature difference between the WWB and AC occurs during the late-afternoon hours (Fig. 17). Consequently, a surface low pressure anomaly develops across the WWB relative to adjacent counties.

The average differences in the midafternoon potential temperature between the WWB and AC is +0.4 K, while the average normalized pressure difference is −0.11 hPa (Fig. 17). During the late-afternoon and early-evening hours, the average temperature and pressure gradients are almost eliminated. The normalized pressure difference is significant during most of the afternoon. However, the potential temperature difference is not statistically significant at the 90% confidence level (although it is significant at the 80% confidence level). The relatively large variance in the potential temperature difference between the WWB and AC is most likely caused by microscale surface inhomogeneities within the WWB after the harvest (i.e., other crops, trees, and grassland near some WWB sites). The surface pressure hardly seems affected by microscale surface features but, instead, responds to the larger-scale impact of the WWB.

The change in the sign of differences in the normalized surface pressure from before harvest to after harvest strongly suggests that the wheat fields caused the differences. One can infer that the pressure gradient resulted in an inland sea-breeze circulation that is opposite to the direction of the inferred circulation before the harvest.

Significant normalized pressure differences were observed during and after the growing season of winter wheat (Fig. 18). The average differences in normalized pressure were +0.11 hPa during December, +0.13 hPa during April, −0.12 hPa during July, and −0.09 hPa during August. May is a transition month when the greenness of the WWB is approximately equal to the greenness of the warm-season grassland in adjacent counties. As a result, statistically significant pressure differences were not observed during May. The internal consistency of these results provides compelling evidence that the wheat fields created the differences observed in the average diurnal cycle of surface pressure.

The inferred inland sea-breeze circulations induced by the WWB were not discernable in the Mesonet wind observations. Perhaps the local variability of the wind field created by terrain features and the exposure at Mesonet sites had a greater influence on the wind observations at those sites than did the inland sea breeze. Thus, an inland sea-breeze circulation might not be evident in the observed wind field until the “correct” mean wind was subtracted and Mesonet siting biases were considered. Likewise, the meteorological “noise” in surface pressure observations created by gravity waves and other mesoscale meteorological phenomena limit the usefulness of surface pressure observations for detecting inland sea-breeze circulations on a case study basis. However, the long-term average difference in diurnal pressure provides compelling evidence that the forcing processes for such circulations did occur.

Although the Oklahoma Mesonet only measures temperature at 1.5 and 9 m above the surface, the vertical depth of the spatial temperature anomalies associated with the WWB can be inferred by the internally consistent surface pressure anomalies. This inference begins with the fact that the average temperature and pressure anomalies observed before and after the harvest were hydrostatically consistent. By vertically integrating the hydrostatic equation, it can be shown that the surface temperature anomalies observed during the afternoon must extend at least 200–300 m above ground during March and 600–700 m above ground during June to create the observed pressure anomalies. If the spatial temperature anomaly weakens with height, this wheat-induced feature must extend even higher to create the same pressure anomaly. Therefore, it is likely that the spatial temperature anomaly created by the WWB extends to the top of the planetary boundary layer. A temperature anomaly extending to the top of the boundary layer is particularly important because it could have implications concerning convective initiation.

5. Conclusions

The diurnal cycle of dewpoint clearly revealed land–atmosphere interactions across the winter wheat belt. The wheat fields created a moist anomaly during the growing season, especially during the late-afternoon hours. The impact of winter wheat on the diurnal cycle of dewpoint was shown to be reversed following the harvest. The impact was shown to be more significant during a month when soil moisture was abundant, and minimal during a month when soil moisture was limited.

Average diurnal temperature and surface pressure differences across the winter wheat belt were consistent with the theoretical model of inland “sea breeze” circulations. Statistically significant, hydrostatically consistent afternoon surface temperature and pressure differences were observed during every spring and summer month, except during the transition month of May.

The internal consistency of the results in relation to observed vegetation patterns before and after the wheat harvest clearly indicates that the observed differences in the diurnal cycle of meteorological parameters resulted from the vegetation character over the WWB.

Acknowledgments

The first author holds an AMS Graduate Fellowship sponsored by NASA’s Earth Science Enterprise. Special thanks are due the staff of the Oklahoma Climatological Survey and meteorology faculty members Dr. Charles A. Doswell III, Dr. Evgeni Fedorovich, and Dr. Peter Lamb for their help in improving this manuscript.

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  • Wen, L., W. Yu, C. A. Lin, M. Beland, R. Benoit, and Y. Delage, 2000: The role of land surface schemes in short-range, high spatial resolution forecasts. Mon. Wea. Rev., 128 , 36053617.

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  • Wetzel, P. J., and A. Boone, 1995: A Parameterization for Land–Atmosphere–Cloud Exchange (PLACE): Documentation and testing of a detailed process model of the partly cloudy boundary layer over heterogeneous land. J. Climate, 8 , 18101837.

    • Search Google Scholar
    • Export Citation
  • Xue, Y., P. J. Sellers, J. L. Kinter, and J. Shukla, 1991: A simplified biosphere model for climate studies. J. Climate, 4 , 345364.

  • Yan, H., and R. A. Anthes, 1988: The effect of variations in surface moisture on mesoscale circulations. Mon. Wea. Rev., 116 , 192208.

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Fig. 1.
Fig. 1.

The location of the WWB within Oklahoma, as defined in this study.

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 2.
Fig. 2.

Visual greenness during the week ending on 8 Apr 2000, showing the WWB strip of anomalously abundant green vegetation. The black outline represents the boundary of Oklahoma’s winter wheat belt, as defined in this study.

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 3.
Fig. 3.

Visual greenness during the week ending on 15 Jun 2000, showing the WWB strip of anomalously sparse green vegetation.

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 4.
Fig. 4.

Locations of WWB and AC Mesonet sites within Oklahoma. County boundaries are shown in gray.

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 5.
Fig. 5.

Diurnal cycle of dewpoint (°C) across the WWB and AC (all months; 1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 6.
Fig. 6.

Diurnal cycle of dewpoint (°C) within the WWB and AC during Mar (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 7.
Fig. 7.

Dewpoint change (°C) between 1300 and 0000 UTC during Mar (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 8.
Fig. 8.

Diurnal cycle of dewpoint difference (°C) between WWB and AC sites along with 90% confidence interval (see text) during Mar (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 9.
Fig. 9.

Diurnal cycle of dewpoint (°C) within the WWB and AC during Jun (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 10.
Fig. 10.

Dewpoint change (°C) from 1100 until 2300 UTC during Jun (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 11.
Fig. 11.

Diurnal cycle of dewpoint difference (°C) between WWB and AC sites along with 90% confidence interval (see text) during Jun (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 12.
Fig. 12.

Diurnal cycle of dewpoint (°C) within the WWB and AC, averaged for all days during (left) Jul 2000 and (right) Jul 1998.

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 13.
Fig. 13.

The 0000 UTC sounding at Norman, OK, on 9 Jun 2000, a typical day with a large dewpoint difference between the WWB and AC.

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 14.
Fig. 14.

Air temperature (°C) at 1900 UTC during Mar (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 15.
Fig. 15.

Diurnal cycle of (left) potential temperature difference (K) and (right) normalized surface pressure difference (hPa) between WWB and AC sites along with the 90% confidence interval (see text) during Mar (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 16.
Fig. 16.

Air temperature (°C) at 2100 UTC during Jun (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 17.
Fig. 17.

Diurnal cycle of (left) potential temperature difference (K) and (right) normalized surface pressure difference (hPa) between WWB and AC sites along with the 90% confidence interval (see text) during Jun (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Fig. 18.
Fig. 18.

Diurnal cycle of normalized surface pressure difference (hPa) between WWB and AC sites during Mar–Jun (1994–2002 average).

Citation: Monthly Weather Review 133, 1; 10.1175/MWR-2842.1

Table 1.

Geographic statistics of WWB and AC mesonet sites.

Table 1.

1

The value 0.09 hPa is below the accuracy of the Mesonet’s pressure sensors (which are accurate to within 0.4 hPa). However, pressure measurement errors should be random, hence, near zero in the mean. The consistent negative difference in potential temperature during the day is internally consistent with the positive pressure anomaly that appears at the same time.

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    • Search Google Scholar
    • Export Citation
  • Wetzel, P. J., and A. Boone, 1995: A Parameterization for Land–Atmosphere–Cloud Exchange (PLACE): Documentation and testing of a detailed process model of the partly cloudy boundary layer over heterogeneous land. J. Climate, 8 , 18101837.

    • Search Google Scholar
    • Export Citation
  • Xue, Y., P. J. Sellers, J. L. Kinter, and J. Shukla, 1991: A simplified biosphere model for climate studies. J. Climate, 4 , 345364.

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    • Export Citation
  • Fig. 1.

    The location of the WWB within Oklahoma, as defined in this study.

  • Fig. 2.

    Visual greenness during the week ending on 8 Apr 2000, showing the WWB strip of anomalously abundant green vegetation. The black outline represents the boundary of Oklahoma’s winter wheat belt, as defined in this study.

  • Fig. 3.

    Visual greenness during the week ending on 15 Jun 2000, showing the WWB strip of anomalously sparse green vegetation.

  • Fig. 4.

    Locations of WWB and AC Mesonet sites within Oklahoma. County boundaries are shown in gray.

  • Fig. 5.

    Diurnal cycle of dewpoint (°C) across the WWB and AC (all months; 1994–2002 average).

  • Fig. 6.

    Diurnal cycle of dewpoint (°C) within the WWB and AC during Mar (1994–2002 average).

  • Fig. 7.

    Dewpoint change (°C) between 1300 and 0000 UTC during Mar (1994–2002 average).

  • Fig. 8.

    Diurnal cycle of dewpoint difference (°C) between WWB and AC sites along with 90% confidence interval (see text) during Mar (1994–2002 average).

  • Fig. 9.

    Diurnal cycle of dewpoint (°C) within the WWB and AC during Jun (1994–2002 average).

  • Fig. 10.

    Dewpoint change (°C) from 1100 until 2300 UTC during Jun (1994–2002 average).

  • Fig. 11.

    Diurnal cycle of dewpoint difference (°C) between WWB and AC sites along with 90% confidence interval (see text) during Jun (1994–2002 average).

  • Fig. 12.

    Diurnal cycle of dewpoint (°C) within the WWB and AC, averaged for all days during (left) Jul 2000 and (right) Jul 1998.

  • Fig. 13.

    The 0000 UTC sounding at Norman, OK, on 9 Jun 2000, a typical day with a large dewpoint difference between the WWB and AC.

  • Fig. 14.

    Air temperature (°C) at 1900 UTC during Mar (1994–2002 average).

  • Fig. 15.

    Diurnal cycle of (left) potential temperature difference (K) and (right) normalized surface pressure difference (hPa) between WWB and AC sites along with the 90% confidence interval (see text) during Mar (1994–2002 average).

  • Fig. 16.

    Air temperature (°C) at 2100 UTC during Jun (1994–2002 average).

  • Fig. 17.

    Diurnal cycle of (left) potential temperature difference (K) and (right) normalized surface pressure difference (hPa) between WWB and AC sites along with the 90% confidence interval (see text) during Jun (1994–2002 average).

  • Fig. 18.

    Diurnal cycle of normalized surface pressure difference (hPa) between WWB and AC sites during Mar–Jun (1994–2002 average).

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