A Simplified Land Model (SLM) for use in cloud‐resolving models: Formulation and evaluation

Lee, Jungmin M.; Khairoutdinov, Marat

doi:10.1002/2014ms000419

Cited by 11 publications

(13 citation statements)

References 77 publications

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“…The Simplified Land Model (SLM) 49 is coupled to SAM version 6.11 and is used to represent land-atmosphere interactions. SLM currently has 17 land surface types, including water and snow/ice.…”

Section: Methodsmentioning

confidence: 99%

Midwinter Arctic leads form and dissipate low clouds

Krueger

Strong

et al. 2020

Nat Commun

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Leads are a key feature of the Arctic ice pack during the winter owing to their substantial contribution to the surface energy balance. According to the present understanding, enhanced heat and moisture fluxes from high lead concentrations tend to produce more boundary layer clouds. However, described here in our composite analyses of diverse surface-and satellite-based observations, we find that abundant boundary layer clouds are associated with low lead flux periods, while fewer boundary layer clouds are observed for high lead flux periods. Motivated by these counterintuitive results, we conducted threedimensional cloud-resolving simulations to investigate the underlying physics. We find that newly frozen leads with large sensible heat flux but low latent heat flux tend to dissipate low clouds. This finding indicates that the observed high lead fractions likely consist of mostly newly frozen leads that reduce any pre-existing low-level cloudiness, which in turn decreases downwelling infrared flux and accelerates the freezing of sea ice.

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Section: Methodsmentioning

confidence: 99%

Midwinter Arctic leads form and dissipate low clouds

Krueger

Strong

et al. 2020

Nat Commun

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“…Other studies have simulated cloud populations over entire countries, including Netherlands (Schalkwijk et al, 2012(Schalkwijk et al, , 2015 and Germany (Heinze et al, 2017). The ability to include simulations of soil properties and surface fluxes via a land model coupled with the System for Atmospheric Modeling LES model has also been demonstrated by Lee and Kariroutdinov (2015).…”

Section: Introductionmentioning

confidence: 99%

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

Fast

Berg

Feng

et al. 2019

J Adv Model Earth Syst

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We use a large‐eddy simulation model with a nested domain configuration (297 and 120 km wide) and an interactive land surface parameterization to simulate the complex population of shallow clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land‐Ecosystems campaign conducted in north‐central Oklahoma. Shallow convective clouds first formed over southeast Oklahoma and then spread toward the northwest into southern Kansas. By the early afternoon, the relatively uniform shallow cloud field became more complex in which some regions became nearly cloud free and in other regions larger shallow clouds developed with some transitioning to deeper, precipitating convection. We show that the model reproduces the observed heterogeneity in the cloud populations only when realistic variations in soil moisture are used to initialize the model. While more variable soil moisture and to a lesser extent cool lake temperatures drive the initial spatial heterogeneity in the cloud populations, precipitation‐driven cold pools become an important factor after 1300 CST. When smoother soil moisture variations are used in the model, more uniform shallow cloud populations are predicted with far fewer clouds that transition to deeper, precipitating convection that produce cold pools. An algorithm that tracks thousands of individual cumulus show that the more realistic soil moisture distributions produces clouds that are larger and have a longer lifetime. The results suggest that shallow and deep convection parameterizations used by mesoscale models need to account for the effects of variable land‐atmosphere interactions and cold pools.

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Section: Methodsmentioning

confidence: 99%

“…We use coupled simulations of the land surface model described by Lee and Khairoutdinov (2015) and the System for Atmospheric Modeling (SAM; version 6.11.1) originally introduced in Khairoutdinov and Randall (2003). The land surface model solves energy and moisture balance equations to determine atmospheric surface fluxes (Lee and Khairoutdinov 2015). The cloud-resolving model SAM solves the anelastic continuity, momentum, and scalar conservation equations, with prognostic thermodynamic variables being the liquid water/ice moist static energy, total nonprecipitating water, and total precipitating water (Khairoutdinov and Randall 2003).…”

Section: Methodsmentioning

confidence: 99%

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Soil Moisture Control of Precipitation Reevaporation over a Heterogeneous Land Surface

Cheng

Chan

Wei

et al. 2021

Journal of the Atmospheric Sciences

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Soil moisture heterogeneity can induce mesoscale circulations due to differential heating between dry and wet surfaces, which can, in turn, trigger precipitation. In this work, we conduct cloud-permitting simulations over a 100 km × 25 km idealized land surface, with the domain split equally between a wet and dry region, each with homogeneous soil moisture. In contrast to previous studies that prescribed initial atmospheric profiles, each simulation is run with fixed soil moisture for 100 days to allow the atmosphere to equilibrate to the given land surface rather than prescribing the initial atmospheric profile. It is then run for one additional day, allowing the soil moisture to freely vary. Soil moisture controls the resulting precipitation over the dry region through three different mechanisms: as the dry domain gets drier, (1) the mesoscale circulation strengthens, increasing water vapor convergence over the dry domain, (2) surface evaporation declines over the dry domain, decreasing water vapor convergence over the dry domain and (3) precipitation efficiency declines due to increased re-evaporation, meaning proportionally less water vapor over the dry domain becomes surface precipitation. We find that the third mechanism dominates when soil moisture is small in the dry domain: drier soils ultimately lead to less precipitation in the dry domain due to its impact on precipitation efficiency. This work highlights an important new mechanism by which soil moisture controls precipitation, through its impact on precipitation re-evaporation and efficiency.

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A Simplified Land Model (SLM) for use in cloud‐resolving models: Formulation and evaluation

Cited by 11 publications

References 77 publications

Midwinter Arctic leads form and dissipate low clouds

Midwinter Arctic leads form and dissipate low clouds

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

Soil Moisture Control of Precipitation Reevaporation over a Heterogeneous Land Surface

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