The Impact of Variable Land‐Atmosphere Coupling on Convective Cloud Populations Observed During the 2016 HI‐SCALE Field Campaign

Fast, Jerome D.; Berg, Larry K.; Feng, Zhe; Mei, Fan; Newsom, Rob; Sakaguchi, Kôichi; Xiao, Heng

doi:10.1029/2019ms001727

Cited by 29 publications

(78 citation statements)

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“…However, those small patches, along with water grids, suggest the water grid cells tend to delay convection. Fast, Berg, Feng, et al (2019) also observed that lakes and their downwind regions are virtually "cloud-free." Cluster analysis confirms this finding.…”

Section: 1029/2020jd032550mentioning

confidence: 96%

“…To isolate the effects of these factors, a sensitivity simulation is designed where large-scale winds and advection of heat and moisture are removed by forcing horizontal winds to be zero and homogenizing thermal and water vapor fields in the initial and lateral boundary conditions. The sensitivity simulation with isolated local effects is first compared with the realistic simulation discussed in Fast, Berg, Feng, et al (2019) to illustrate the comparative roles of both local and large-scale effects in cloud populations and land-atmosphere interactions. Then, the detailed characteristics of land-atmospheric interaction under the idealized conditions of no advection are investigated using a cluster analysis approach.…”

Section: Journal Of Geophysical Research: Atmospheresmentioning

confidence: 99%

“…Some of those shallow cumuli transitioned to cumulus congestus and deep convection during the afternoon. Fast, Berg, Feng, et al (2019) conducted LES with Weather Forecasting and Research (WRF) model with interactive land surface parameterization to simulate the complex population of shallow clouds on this day. Three simulations were conducted in that study including (1) default WRF setup that uses large-scale analysis data, (2) inclusion of more spatially variable soil properties and land use type obtained by combining in situ measurements and satellite data and modified initial meteorological profiles, and (3) modification of the initial meteorological profiles.…”

Section: Overview Of the Case Studymentioning

confidence: 99%

“…The default WRF settings are polished by modifying the soil moisture, soil temperature, and land use type. The spatial distribution of the top-layer soil moisture shown in Figure 1a is the same as Figure 2b in Fast, Berg, Feng, et al (2019). Both ARM and Oklahoma Mesonet stations and Global Land Evaporation Amsterdam Model satellite data are used to construct the spatial variations of soil moisture.…”

Section: Design Of the Control Simulationmentioning

confidence: 99%

“…Surface heterogeneity was reported to produce more realistic cloud distributions than uniform surface conditions (Fast, Berg, Feng, et al, 2019;Garcia-Carreras et al, 2011;Wu et al, 2015). Fast, Berg, Feng, et al (2019) conducted LES simulations coupled with an interactive land model to examine the impacts of variations in soil property and finer-scale vertical variations in initial atmospheric state on the complex 10.1029/2020JD032550…”

Section: Introductionmentioning

confidence: 99%

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Characterization of Surface Heterogeneity‐Induced Convection Using Cluster Analysis

et al. 2020

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Land-atmosphere interactions and boundary layer processes often control the formation of shallow clouds and subsequently deep convective precipitation over the U.S. Southern Great Plains. In this study, we examine the impacts of large-scale advection on the cloud populations and land-atmospheric coupling observed during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems field campaign in 2016. We performed two large eddy simulations using the Weather Research and Forecasting Model for a day in which the transition from clear-sky to shallow precipitating clouds and isolated deep convection was observed. The control simulation reproduced the overall distribution of cloud populations by using realistic soil conditions with an interactive land model. In the sensitivity simulation where large-scale advection is removed, a strong relationship between the land and boundary layer is found. To study the timing, location, and intensity of convective initiation and the relationship of clouds with land surface properties, a cluster analysis of equivalent potential temperature is performed for the simulation without large-scale advection. That analysis shows that convective clouds first form over regions with higher surface sensible heat flux. Precipitation from those convective clouds likely triggers new updrafts nearby about 2 hr later through the lifting associated with cold pools. The cluster analysis also shows that in addition to the spatial pattern of soil moisture, land use and soil texture in western Oklahoma also influence the location of convective initiation. Plain Language Summary Accurately predicting the timing, location, and intensities of convection over midlatitude land is extremely important. Yet, complete answers to the related questions such as how the land properties impact the atmosphere and cloud properties remain lacking. Models that resolve boundary layer turbulence and clouds have been used extensively to understand processes controlling land-atmosphere interactions, but computational expense limits the employment of realistic land properties. In this study, we employ a more realistic modeling approach to study abovementioned question. First, we examined the relative role of large-scale advection and the local effects of land properties in convection and cloud formation. A comparison of two sensitivity studies shows that large-scale advection is vital in the characterization of land-atmosphere interactions not only in terms of the magnitude but also the types of relationships. Then, we analyzed the simulation with only local effects by cluster analysis. We found that convection initiates over the regions with high surface sensible heat flux. Precipitation from the earliest convection likely triggers new convection around about 2 hr later by forming a cold surface area due to evaporating cooling. Moreover, soil moisture, land use type, and soil texture play roles in determining the surface heat fluxes.

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Section: 1029/2020jd032550mentioning

confidence: 96%

Section: Journal Of Geophysical Research: Atmospheresmentioning

confidence: 99%

Section: Overview Of the Case Studymentioning

confidence: 99%

Section: Design Of the Control Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Characterization of Surface Heterogeneity‐Induced Convection Using Cluster Analysis

et al. 2020

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Global Surface Soil Moisture Drydown Patterns

Mohanty¹,

Sehgal²

2020

Preprint

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Modeling Spatial Heterogeneity in Surface Turbulent Heat Flux in the U.S. Southern Great Plains

et al. 2020

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Advances in numerical modeling of cloud dynamics are driving a need for improved land model prediction at convective storm scales. In this study, satellite and ground‐based vegetation remote sensing data were combined with land model experiments to more accurately characterize land surface spatial heterogeneity in the Community Land Model (CLM4.0). The new subgrid classification of plant functional types (PFT) and leaf area index (LAI) enables consistent comparison between models and ground‐based flux measurements in the U.S. southern Great Plains. Errors in vegetation data sets (inferred from comparison between 250 m satellite and ground‐based LAI), while large, had less impact on the simulated characteristics of spatial heterogeneity compared to errors in model representation of surface energy partitioning (between latent and sensible heat flux) and its relationship to LAI. Predicted spatial heterogeneity in surface energy partitioning was enhanced after replacing soil and stomatal resistance parameters with a new set that better predicts the observed relationship to LAI. These modifications increase the number of smaller (mesoscale) dry land patches having higher sensible heat flux. The parameter experiments suggest that vegetation state and processes (transpiration) act to broaden the size spectrum of surface heat flux heterogeneity, which can influence clouds and convective initiation. Moreover, improvements in vegetation input data and model parameters had partially compensating effects on surface flux heterogeneity, indicating the importance of evaluating input data and parameterizations together to improve prediction at higher spatial resolutions.

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The Impact of Variable Land‐Atmosphere Coupling on Convective Cloud Populations Observed During the 2016 HI‐SCALE Field Campaign

Cited by 29 publications

References 93 publications

Characterization of Surface Heterogeneity‐Induced Convection Using Cluster Analysis

Characterization of Surface Heterogeneity‐Induced Convection Using Cluster Analysis

Global Surface Soil Moisture Drydown Patterns

Modeling Spatial Heterogeneity in Surface Turbulent Heat Flux in the U.S. Southern Great Plains

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