The Effect of Land Surface Heterogeneity and Background Wind on Shallow Cumulus Clouds and the Transition to Deeper Convection

2019 ◽  
Vol 76 (2) ◽  
pp. 401-419 ◽  
Author(s):  
Jungmin M. Lee ◽  
Yunyan Zhang ◽  
Stephen A. Klein
Keyword(s):  
Wind Speed ◽  
Land Surface ◽  
Surface Heterogeneity ◽  
Secondary Circulation ◽  
Length Scale ◽  
Background Wind ◽  
Cumulus Clouds ◽  
Shallow Cumulus ◽  
Land Surface Heterogeneity ◽  
The Impact

Abstract Idealized large-eddy simulations (LESs) with prescribed heterogeneous land surface heat fluxes are performed to study the impact of the heterogeneity length scale and background wind speed on the development of shallow cumulus and the subsequent transition to congestus/deep convection. We study the impact of land surface heterogeneity in an atmosphere that favors shallow convection but is also conditionally unstable with respect to deeper convection. We find that before the convection transition, larger and thicker shallow cumulus clouds are attached to moisture pools near the PBL top over patches with low evaporative fraction (referred to as “DRY”). This feature is attributable to a surface-induced secondary circulation whose development depends on the heterogeneity size and the background wind speed. With large patches (≥5 km) under zero ambient wind, the secondary mesoscale circulation promotes the vertical transport of moisture forming a moisture pool over DRY patches, while with smaller patches, no such circulation develops. The influence of the background wind on the secondary circulation is strong such that any wind stronger than 2 m s−1 effectively eliminates the impact of surface heterogeneity on the PBL and brings no secondary circulation. This is because the triggered secondary circulation is not strong enough to withstand the imposed background wind. Based on these, we propose two criteria for the convection transition, namely, that the heterogeneity length scale is greater than 5 km and that the background wind speed is less than Uc0, where Uc0 is the near-surface cross-patch wind speed of the secondary circulation under zero background wind for a given patch size and is about 1.5 m s−1 in our cases.

Modelling multi-scale atmosphere and land-surface interactions

2020 ◽  
Author(s):  
Zahra Parsakhoo ◽  
Cedrick Ansorge ◽  
Yaping Shao
Keyword(s):  
Water Vapor ◽  
Soil Type ◽  
Land Surface ◽  
Dynamic Effect ◽  
Surface Heterogeneity ◽  
Original Data ◽  
Length Scale ◽  
Atmospheric State ◽  
Land Surface Heterogeneity ◽  
Thermodynamic Coupling

<p>As land-surface properties are heterogeneous over a broad range of length-scales, surface-induced fluxes are heterogeneous too. Representing land-surface heterogeneity and the corresponding fluxes is a challenging task in numerical prediction of weather and projection of climate. </p><p>In this work, we introduce the approach of <em>'para-real' ensemble modelling</em> to investigate the dynamic effect of land-surface heterogeneity. We perform a large ensemble of high-resolution simulations using the Weather research and forecast model (WRF-ARW-LSM). The para-real simulation ensembles are externally forced by a reanalysis of a real case in spring 2013, but become exposed to different synthesized surface patterns (SP) generated as quasi-fractal Brownian surfaces (quasi-fBs) with exact control of the dominant wave length and fractal persistence.</p><p>The focus of this study is on the three inter-related land-surface and atmosphere coupling mechanisms--the <em>thermodynamic coupling</em>, <em>aerodynamic coupling</em>, and <em>hydrological coupling</em>. For each mechanism, a corresponding surface property is identified, namely surface albedo (α) for thermodynamic coupling, roughness length (z<sub>0</sub>) for aerodynamic coupling, and soil type (s<sub>t</sub>) for hydrological coupling. For each surface property, we generate a set of quasi-fBs with different dominant length scale and fractal persistence. In our para-real ensembles, the original fields of the surface properties are replaced by the quasi-fBs, for which we estimate the control parameters from the original data, i.e., the probability density distribution of the original data matches that of the quasi-fBs which eliminates the flux aggregation effect and allows us to focus on the dynamic effect. </p><p>We find, first, a strong impact of the length scale of the surface forcing on the intensity of coupling: while the dynamic effect of surface heterogeneity significantly impacts the state of the atmospheric boundary layer for all cases investigated,  the impact of the surface signal on the atmospheric state  grows with the length-scale of the surface heterogeneity. Second, we demonstrate that larger fractal persistence of the surface signal also strengthens the atmosphere--surface coupling. Third, the qualitative impact of the surface forcing is shown to depend on time, which eliminates the possibility of a simple linear forward propagation of the surface signal; there is strong sensitivity to the diurnal cycle, in particular with respect to the horizontal wind components: The maximum intensity of atmosphere--surface coupling (measured in terms of correlation) is found around noon for the atmospheric temperature, and some hours later (in the early afternoon) for water vapor. Fourth, among the different surface forcing investigated, we find that the heterogeneity of soil type is the most important to the atmospheric state--surface exchanges and its signal are detected in the atmospheric water-vapor up to 2km height; in particular, the soil-type pattern with the smallest length-scale causes a doubling of cloud-water above 500m height  whereas no impact on the bulk atmospheric state is found for patterns with other length-scales and fractal persistence or forcing of other surface variables. This illustrates the key part that hydrological coupling plays in connecting the atmosphere to the surface, and it underlines the relevance of improved hydrological process-level representation for improved parameterization of the coupled land--atmosphere system.</p>

An Analysis of the Importance of a Fully-Coupled Atmosphere and Land-Surface When Considering the Impact of Multi-Scale Land Spatial Heterogeneity on Cloud Development

2021 ◽  
Author(s):  
Jason Simon ◽  
Tyler Waterman ◽  
Finley Hay-Chapman ◽  
Paul Dirmeyer ◽  
Andrew Bragg ◽  
...  
Keyword(s):  
Land Surface ◽  
Wrf Model ◽  
Surface Heterogeneity ◽  
Land Surface Models ◽  
Bottom Boundary ◽  
Surface Models ◽  
Land Surface Heterogeneity ◽  
Land Surfaces ◽  
The Impact ◽  
Fully Coupled

<p><span>Land-surface heterogeneity is known to play an important role in land-surface hydrology, which drives the bottom boundary condition for atmospheric models in numerical weather prediction (NWP) applications. However, the ultimate impact of land-surface heterogeneity on atmospheric boundary layer (ABL) development is still an open problem with implications for sub-grid scale (SGS) parameterizations for both NWP and climate modeling. Large-eddy simulation (LES) is often used to study the effects of land-surface heterogeneity on ABL development, most typically via specified surface fields which are not influenced by the atmosphere (i.e. semi-coupled). Heterogeneous land surfaces have been seen in previous studies to have a significant influence on ABL dynamics, particularly cloud production, in certain cases when semi-coupled to the atmosphere. </span></p><p><span>Here we use the Weather Research and Forecasting (WRF) model as an LES with both semi-coupled and fully-coupled land surfaces to investigate the impact of two-way coupling on the interaction between heterogeneous land surfaces and daytime ABLs. For semi-coupled simulations, the HydroBlocks land-surface model is run offline, drive</span><span>n by 4-km NLDAS-2 meteorology with Stage-IV radar rainfall data, and then used to specify the bottom boundary in WRF. The WRF-Hydro model is used for cases where the land surface is fully coupled to the WRF model. Both land-surface models use the Noah-MP model as their underlying physics package and add both subsurface and overland flow routing. </span><span>The WRF model uses a 100-m horizontal resolution, and the land-surface models use </span><span>high resolution (30 m) datasets that were upscaled to match the LES resolution for elevation, landcover, and soil type using NED, NLCD, and POLARIS respectively. </span><span>These LES experiments are performed over the ARM Southern Great Plains Site</span><span> atmospheric observatory in Oklahoma during the Summer of 2017 with a grid size of 100 km x 100 km to imitate a single cell in a modern climate model. </span><span>The impact of land-surface heterogeneity on the atmosphere is evaluated by comparing simulations using the fully heterogeneous land surfaces with simulations where the land surface is homogenized at each timestep, taking a domain-wide spatial mean value at every grid cell. </span><span>Results are evaluated primarily by the differences in the development of clouds and evolution of turbulent kinetic energy in the ABL. </span></p>

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

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.

Evaluating the Impact of Free-Stream Turbulence on Convective Cooling of Overhead Conductors Using Large Eddy Simulations

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Mohamed Abdelhady ◽  
David H. Wood
Keyword(s):  
Wind Speed ◽  
Real Time ◽  
Turbulence Intensity ◽  
Free Stream ◽  
Diameter Ratio ◽  
Weather Data ◽  
Length Scale ◽  
Free Stream Turbulence ◽  
Large Eddy ◽  
The Impact

The international trend of using renewable energy sources for generating electricity is increasing, partly through harvesting energy from wind turbines. Increasing electric power transmission efficiency is achievable through using real-time weather data for power line rating, known as real-time thermal rating (RTTR), instead of using the worst case scenario weather data, known as static rating. RTTR is particularly important for wind turbine connections to the grid, as wind power output and overhead conductor rating both increase with increasing wind speed, which should significantly increase real-time rated conductor from that of statically rated. Part of the real-time weather data is the effect of free-stream turbulence, which is not considered by the commonly used overhead conductor codes, Institute of Electrical and Electronics Engineers (IEEE) 738 and International Council on Large Electric Systems (CIGRÉ) 207. This study aims to assess the effect free-stream turbulence on IEEE 738 and CIGRÉ 207 forced cooling term. The study uses large eddy simulation (LES) in the ANSYS fluent software. The analysis is done for low wind speed, corresponding to Reynolds number of 3000. The primary goal is to calculate Nusselt number for cylindrical conductors with free-stream turbulence. Calculations showed an increase in convective heat transfer from the low turbulence value by ∼30% at turbulence intensity of 21% and length scale to diameter ratio of 0.4; an increase of ∼19% at turbulence intensity of 8% and length scale to diameter ratio of 0.4; and an increase of ∼15% at turbulence intensity of 6% and length scale to diameter ratio of 0.6.

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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