A statistical-dynamical approach to parameterize subgrid-scale land-surface heterogeneity in climate models

1991 ◽  
Vol 12 (1-3) ◽  
pp. 155-178 ◽  
Author(s):  
Roni Avissar
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Surface Heterogeneity ◽  
Subgrid Scale ◽  
Dynamical Approach ◽  
Land Surface Heterogeneity

Impact of Land Surface Heterogeneity on Mesoscale Atmospheric Dispersion

2009 ◽  
Vol 133 (3) ◽  
Author(s):  
Yuling Wu ◽  
Udaysankar S. Nair ◽  
Roger A. Pielke ◽  
Richard T. McNider ◽  
Sundar A. Christopher ◽  
...  
Keyword(s):  
Land Surface ◽  
Atmospheric Dispersion ◽  
Surface Heterogeneity ◽  
Land Surface Heterogeneity

Land surface heterogeneity on surface energy and water fluxes

2002 ◽  
Author(s):  
David L. Toll ◽  
Jared K. Entin ◽  
Paul R. Houser
Keyword(s):  
Surface Energy ◽  
Land Surface ◽  
Surface Heterogeneity ◽  
Water Fluxes ◽  
Land Surface Heterogeneity

scholarly journals Land Surface Heterogeneity Signature in Tornado Climatology? An Illustrative Analysis over Indiana, 1950–2012*

2014 ◽  
Vol 18 (10) ◽  
pp. 1-32 ◽  
Author(s):  
Olivia Kellner ◽  
Dev Niyogi
Keyword(s):  
Land Use ◽  
Population Density ◽  
Land Cover ◽  
Land Surface ◽  
Strong Relationship ◽  
Surface Heterogeneity ◽  
Temporal Analysis ◽  
Antecedent Rainfall ◽  
Land Surface Heterogeneity ◽  
Tornado Climatology

Abstract Land surface heterogeneity affects mesoscale interactions, including the evolution of severe convection. However, its contribution to tornadogenesis is not well known. Indiana is selected as an example to present an assessment of documented tornadoes and land surface heterogeneity to better understand the spatial distribution of tornadoes. This assessment is developed using a GIS framework taking data from 1950 to 2012 and investigates the following topics: temporal analysis, effect of ENSO, antecedent rainfall linkages, population density, land use/land cover, and topography, placing them in the context of land surface heterogeneity. Spatial analysis of tornado touchdown locations reveals several spatial relationships with regard to cities, population density, land-use classification, and topography. A total of 61% of F0–F5 tornadoes and 43% of F0–F5 tornadoes in Indiana have touched down within 1 km of urban land use and land area classified as forest, respectively, suggesting the possible role of land-use surface roughness on tornado occurrences. The correlation of tornado touchdown points to population density suggests a moderate to strong relationship. A temporal analysis of tornado days shows favored time of day, months, seasons, and active tornado years. Tornado days for 1950–2012 are compared to antecedent rainfall and ENSO phases, which both show no discernible relationship with the average number of annual tornado days. Analysis of tornado touchdowns and topography does not indicate any strong relationship between tornado touchdowns and elevation. Results suggest a possible signature of land surface heterogeneity—particularly that around urban and forested land cover—in tornado climatology.

Using Spatial Eddy Covariance to Investigate Energy Balance Closure over a Heterogeneous Ecosystem

2020 ◽  
Author(s):  
Brian Butterworth ◽  
Ankur Desai ◽  
Sreenath Paleri ◽  
Stefan Metzger ◽  
David Durden ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Energy Balance ◽  
Surface Energy ◽  
Atmospheric Boundary Layer ◽  
Eddy Covariance ◽  
Land Surface ◽  
Surface Heterogeneity ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Land Surface Heterogeneity

<p>Land surface heterogeneity influences patterns of sensible and latent heat flux, which in turn affect processes in the atmospheric boundary layer. However, gridded atmospheric models often fail to incorporate the influence of land surface heterogeneity due to differences between the temporal and spatial scales of models compared to the local, sub-grid processes. Improving models requires the scaling of surface flux measurements; a process made difficult by the fact that surface measurements usually find an imbalance in the energy budget.</p><p>The Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors (CHEESEHEAD19) was an observational experiment designed to investigate how the atmospheric boundary layer responds to scales of spatial heterogeneity in surface-atmosphere heat and water exchanges. The campaign was conducted from June – October 2019, measuring surface energy fluxes over a heterogeneous forest ecosystem as fluxes transitioned from latent heat-dominated summer through sensible heat-dominated fall. Observations were made by ground, airborne, and satellite platforms within the 10 x 10 km study region, which was chosen to match the scale of a typical model grid cell. The spatial distribution of energy fluxes was observed by an array of 20 eddy covariance towers and a low-flying aircraft. Mesoscale atmospheric properties were measured by a suite of LiDAR and sounding instruments, measuring winds, water vapor, temperature, and boundary layer development. Plant phenology was measured in-situ and mapped remotely using hyperspectral imaging.</p><p>The dense set of multi-scale observations of land-atmosphere exchange collected during the CHEESEHEAD field campaign permits combining the spatial and temporal distribution of energy fluxes with mesoscale surface and atmospheric properties. This provides an unprecedented data foundation to evaluate theoretical explanations of energy balance non-closure, as well as to evaluate methods for scaling surface energy fluxes for improved model-data comparison. Here we show how fluxes calculated using a spatial eddy covariance technique across the 20-tower network compare to those of standard temporal eddy covariance fluxes in order to characterize of the spatial representativeness of single tower eddy covariance measurements. Additionally, we show how spatial EC fluxes can be used to better understand the energy balance over heterogeneous ecosystems.</p>

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