Regional CO2and latent heat surface fluxes in the Southern Great Plains: Measurements, modeling, and scaling

Abstract This paper is Part I of a two-part study that uses high-resolution Regional Atmospheric Modeling System (RAMS) simulations to investigate mesoscale land–atmosphere interactions in the summertime U.S. Southern Great Plains. The focus is on the atmospheric dynamics associated with mesoscale heterogeneity in the underlying surface fluxes: how shifts in meteorological regimes modulate these diurnal, mesoscale processes, and their overall impact at larger scales and over multiple diurnal cycles. Part I examines individual case study time periods drawn from the simulations that illustrate general points about the key land–atmosphere interactions. The main findings are as follows: The mesoscale processes are embedded within a synoptic-scale organization that controls the background meteorological regime at a given location. During the clear, dry days in the simulated months, heterogeneity in the surface fluxes forces strong, lower-tropospheric, mesoscale circulations that exhibit a characteristic dynamical life cycle over diurnal time scales. In general, the background large-scale flow does not affect the overall intensity of these coherent roll structures, though strong large-scale subsidence can sometimes dampen them. In addition, depending on the thermodynamic profile, the strong vertical motions associated with these circulations are sufficient to trigger shallow or even deep convection, with associated clouds and precipitation. Furthermore, surface heterogeneity sufficient to force such circulations can arise even without heterogeneity in preexisting land cover characteristics such as vegetation, for example, solely as a result of spatial variability in rainfall and other atmospheric processes. In Part II the mesoscale land–atmosphere interactions in these case study periods are placed in the larger context of the full, monthlong simulations.

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A technique for determining the spatial and temporal distributions of surface fluxes of heat and moisture over the Southern Great Plains Cloud and Radiation Testbed

Journal of Geophysical Research Atmospheres ◽

10.1029/97jd03427 ◽

1998 ◽

Vol 103 (D6) ◽

pp. 6109-6121 ◽

Cited By ~ 25

Author(s):

J. C. Doran ◽

J. M. Hubbe ◽

J. C. Liljegren ◽

W. J. Shaw ◽

G. J. Collatz ◽

...

Keyword(s):

Great Plains ◽

Surface Fluxes ◽

Southern Great Plains ◽

Spatial And Temporal Distributions ◽

Heat And Moisture

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Estimating Clear-Sky Regional Surface Fluxes in the Southern Great Plains Atmospheric Radiation Measurement Site with Ground Measurements and Satellite Observations

Journal of Applied Meteorology ◽

10.1175/1520-0450(1998)037<0005:ecsrsf>2.0.co;2 ◽

1998 ◽

Vol 37 (1) ◽

pp. 5-22 ◽

Cited By ~ 33

Author(s):

W. Gao ◽

R. L. Coulter ◽

B. M. Lesht ◽

J. Qiu ◽

M. L. Wesely

Keyword(s):

Great Plains ◽

Surface Fluxes ◽

Satellite Observations ◽

Atmospheric Radiation ◽

Radiation Measurement ◽

Southern Great Plains ◽

Clear Sky ◽

Measurement Site ◽

Atmospheric Radiation Measurement

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A Modeling Study of Irrigation Effects on Surface Fluxes and Land–Air–Cloud Interactions in the Southern Great Plains

Journal of Hydrometeorology ◽

10.1175/jhm-d-12-0134.1 ◽

2013 ◽

Vol 14 (3) ◽

pp. 700-721 ◽

Cited By ~ 90

Author(s):

Yun Qian ◽

Maoyi Huang ◽

Ben Yang ◽

Larry K. Berg

Keyword(s):

Soil Moisture ◽

Great Plains ◽

Mixed Layer ◽

Mixed Layer Depth ◽

Surface Fluxes ◽

Specific Humidity ◽

Surface Model ◽

Layer Depth ◽

Near Surface ◽

Southern Great Plains

Abstract In this study, the authors incorporate an operational-like irrigation scheme into the Noah land surface model as part of the Weather Research and Forecasting Model (WRF). A series of simulations, with and without irrigation, is conducted over the Southern Great Plains (SGP) for an extremely dry (2006) and wet (2007) year. The results show that including irrigation reduces model bias in soil moisture and surface latent heat (LH) and sensible heat (SH) fluxes, especially during a dry year. Irrigation adds additional water to the surface, leading to changes in the planetary boundary layer. The increase in soil moisture leads to increases in the surface evapotranspiration and near-surface specific humidity but decreases in the SH and surface temperature. Those changes are local and occur during daytime. There is an irrigation-induced decrease in both the lifting condensation level (ZLCL) and mixed-layer depth. The decrease in ZLCL is larger than the decrease in mixed-layer depth, suggesting an increasing probability of shallow clouds. The simulated changes in precipitation induced by irrigation are highly variable in space, and the average precipitation over the SGP region only slightly increases. A high correlation is found among soil moisture, SH, and ZLCL. Larger values of soil moisture in the irrigated simulation due to irrigation in late spring and summer persist into the early fall, suggesting that irrigation-induced soil memory could last a few weeks to months. The results demonstrate the importance of irrigation parameterization for climate studies and improve the process-level understanding on the role of human activity in modulating land–air–cloud interactions.

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Factors Controlling the Vertical Extent of Fair-Weather Shallow Cumulus Clouds over Land: Investigation of Diurnal-Cycle Observations Collected at the ARM Southern Great Plains Site

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-12-0131.1 ◽

2013 ◽

Vol 70 (4) ◽

pp. 1297-1315 ◽

Cited By ~ 49

Author(s):

Yunyan Zhang ◽

Stephen A. Klein

Keyword(s):

Heat Flux ◽

Great Plains ◽

Diurnal Cycle ◽

Sensible Heat Flux ◽

Surface Fluxes ◽

Cloud Base ◽

Fair Weather ◽

Southern Great Plains ◽

Vertical Extent ◽

Thin Cloud

Abstract Summertime observations for 13 yr at the Atmospheric Radiation Measurement Southern Great Plains site are used to study fair-weather shallow cumuli (ShCu). To roughly separate forced from active ShCu, days are categorized into “thin-” or “thick-” ShCu days according to whether the daytime-average cloud depth exceeds 300 m. By comparing diurnal-cycle composites of these two regimes, the authors document differences in cloud properties and their radiative impacts. The differences in environmental conditions provide clues as to what controls ShCu vertical extent. Higher boundary layer (BL) relative humidity (RH) is found on thick-cloud days, associated with large-scale moisture advection before sunrise. This higher BL RH not only contributes to a lower cloud base but also to the penetrating ability of an air parcel to reach higher levels, and thus leads to larger cloud vertical extent. Although not as significant as BL RH, ShCu vertical extent also varies with thermal stability and surface fluxes. Enhanced stability above cloud on thin-cloud days may limit cloud vertical extent. A larger sensible heat flux on thin-cloud days encourages greater entrainment of dry air into the BL, whereas a larger latent heat flux on thick-cloud days helps sustain higher afternoon BL RH. These heat flux differences help maintain the BL RH differences that appear to control cloud vertical extent. This study provides observational evidence that forced clouds are related to BL large-eddy overshoots limited by a stronger inversion whereas higher moisture and a weaker stability above favor active cumuli with greater vertical extent.

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Biases in regional carbon budgets from covariation of surface fluxes and weather in transport model inversions

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-19051-2013 ◽

2013 ◽

Vol 13 (7) ◽

pp. 19051-19083 ◽

Cited By ~ 1

Author(s):

I. N. Williams ◽

W. J. Riley ◽

M. S. Torn ◽

S. C. Biraud ◽

M. L. Fischer

Keyword(s):

Boundary Layer ◽

Time Scales ◽

Great Plains ◽

Seasonal Cycle ◽

Transport Model ◽

Surface Flux ◽

Growing Season ◽

Surface Fluxes ◽

Southern Great Plains ◽

Annual Variability

Abstract. Recent advances in transport model inversions could significantly reduce uncertainties in land carbon uptake through assimilation of high frequency CO2 concentration measurements. The impact of these measurements depends on the strength of covariation between surface fluxes and atmospheric transport and mixing at weekly and shorter time-scales, and on how well transport models represent this covariation. A stochastic boundary layer model was developed to quantify the effects of synoptic covariation on surface flux inversions at daily to season time-scales, and to compare covariation in transport model simulations to observations at the US Southern Great Plains Atmospheric Radiation Measurement Climate Research Facility. The most significant covariation of surface fluxes and transport occurred on weekly and longer time-scales, suggesting that surface flux inversions would benefit most from improved simulations of dynamics at the lower-frequency end of the synoptic spectrum. Biases in these rectifier effects contributed to surface flux biases of 13% of the seasonal cycle amplitude, estimated from differences between observations and a data assimilation system (CarbonTracker). Biases in simulated covariation of transport and surface fluxes resulted in overestimated boundary layer concentrations during the growing season over the Southern Great Plains, by up to 0.3 ppm CO2. Though small relative to the seasonal cycle, the strength of synoptic rectifier effects strongly varies on inter-annual time-scales, with some years having negligible and others having large vertical concentration gradients during the growing season, due only to differences in covariation of surface fluxes and transport. Inter-annual variability in vertical gradients due to synoptic rectifier effects is of similar magnitude to the inter-annual variability due to carbon sinks alone.

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Spatiotemporal Variations in Growing Season Exchanges of CO2, H2O, and Sensible Heat in Agricultural Fields of the Southern Great Plains

Earth Interactions ◽

10.1175/ei231.1 ◽

2007 ◽

Vol 11 (17) ◽

pp. 1-21 ◽

Cited By ~ 117

Author(s):

Marc L. Fischer ◽

David P. Billesbach ◽

Joseph A. Berry ◽

William J. Riley ◽

Margaret S. Torn

Keyword(s):

Regression Model ◽

Great Plains ◽

Ecosystem Respiration ◽

Gross Primary Production ◽

Growing Season ◽

Temporal Variations ◽

Surface Fluxes ◽

Heat Fluxes ◽

Agricultural Fields ◽

Southern Great Plains

Abstract Climate, vegetation cover, and management create finescale heterogeneity in unirrigated agricultural regions, with important but not well-quantified consequences for spatial and temporal variations in surface CO2, water, and heat fluxes. Eddy covariance fluxes were measured in seven agricultural fields—comprising winter wheat, pasture, and sorghum—in the U.S. Southern Great Plains (SGP) during the 2001–03 growing seasons. Land cover was the dominant source of variation in surface fluxes, with 50%–100% differences between fields planted in winter–spring versus fields planted in summer. Interannual variation was driven mainly by precipitation, which varied more than twofold between years. Peak aboveground biomass and growing season net ecosystem exchange (NEE) of CO2 increased in rough proportion to precipitation. Based on a partitioning of gross fluxes with a regression model, ecosystem respiration increased linearly with gross primary production, but with an offset that increased near the time of seed production. Because the regression model was designed for well-watered periods, it successfully retrieved NEE and ecosystem parameters during the peak growing season and identified periods of moisture limitation during the summer. In summary, the effects of crop type, land management, and water limitation on carbon, water, and energy fluxes were large. Capturing the controlling factors in landscape-scale models will be necessary to estimate the ecological feedbacks to climate and other environmental impacts associated with changing human needs for agricultural production of food, fiber, and energy.

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