Single-column Model Research Articles

Stochasticity of convection in Giga-LES data

The poor representation of tropical convection in general circulation models (GCMs) is believed to be responsible for much of the uncertainty in the predictions of weather and climate in the tropics. The stochastic multicloud model (SMCM) was recently developed by Khouider et al. (Commun Math Sci 8(1):187–216, 2010) to represent the missing variability in GCMs due to unresolved features of organized tropical convection. The SMCM is based on three cloud types (congestus, deep and stratiform), and transitions between these cloud types are formalized in terms of probability rules that are functions of the large-scale environment convective state and a set of seven arbitrary cloud timescale parameters. Here, a statistical inference method based on the Bayesian paradigm is applied to estimate these key cloud timescales from the Giga-LES dataset, a 24-h large-eddy simulation (LES) of deep tropical convection (Khairoutdinov et al. in J Adv Model Earth Syst 1(12), 2009) over a domain comparable to a GCM gridbox. A sequential learning strategy is used where the Giga-LES domain is partitioned into a few subdomains, and atmospheric time series obtained on each subdomain are used to train the Bayesian procedure incrementally. Convergence of the marginal posterior densities for all seven parameters is demonstrated for two different grid partitions, and sensitivity tests to other model parameters are also presented. A single column model simulation using the SMCM parameterization with the Giga-LES inferred parameters reproduces many important statistical features of the Giga-LES run, without any further tuning. In particular it exhibits intermittent dynamical behavior in both the stochastic cloud fractions and the large scale dynamics, with periods of dry phases followed by a coherent sequence of congestus, deep, and stratiform convection, varying on timescales of a few hours consistent with the Giga-LES time series. The chaotic variations of the cloud area fractions were captured fairly well both qualitatively and quantitatively demonstrating the stochastic nature of convection in the Giga-LES simulation.

Attributing the behavior of low‐level clouds in large‐scale models to subgrid‐scale parameterizations

AbstractThis study explores ways of establishing the characteristic behavior of boundary layer schemes in representing subtropical marine low‐level clouds in climate models. To this purpose, parameterization schemes are studied in both isolated and interactive mode with the larger‐scale circulation. Results of the EUCLIPSE/GASS intercomparison study for Single‐Column Models (SCM) on low‐level cloud transitions are compared to General Circulation Model (GCM) results from the CFMIP‐2 project at selected grid points in the subtropical eastern Pacific. Low cloud characteristics are plotted as a function of key state variables for which Large‐Eddy Simulation results suggest a distinct and reasonably tight relation. These include the Cloud Top Entrainment Instability (CTEI) parameter and the total cloud cover. SCM and GCM results are thus compared and their resemblance is quantified using simple metrics. Good agreement is reported, to such a degree that SCM results are found to be uniquely representative of their GCM, and vice versa. This suggests that the system of parameterized fast boundary layer physics dominates the model state at any given time, even when interactive with the larger‐scale flow. This behavior can loosely be interpreted as a unique “fingerprint” of a boundary layer scheme, recognizable in both SCM and GCM simulations. The result justifies and advocates the use of SCM simulation for improving weather and climate models, including the attribution of typical responses of low clouds to climate change in a GCM to specific parameterizations.

Near-Surface Effects of Free Atmosphere Stratification in Free Convection

The effect of a linear stratification in the free atmosphere on near-surface properties in a free convective boundary layer (CBL) is investigated by means of direct numerical simulation. We consider two regimes: a neutral stratification regime, which represents a CBL that grows into a residual layer, and a strong stratification regime, which represents the equilibrium (quasi-steady) entrainment regime. We find that the mean buoyancy varies as $$z^{-1/3}$$ , in agreement with classical similarity theory. However, the root-mean-square (r.m.s.) of the buoyancy fluctuation and the r.m.s. of the vertical velocity vary as $$z^{-0.45}$$ and $$\ln z$$ , respectively, both in disagreement with theory. These scaling laws are independent of the stratification regime, but the depth over which they are valid depends on the stratification. In the strong stratification regime, this depth is about 20 to 25 % of the CBL depth instead of the commonly used 10 %, which we only observe under neutral conditions. In both regimes, the near-surface flow structure can be interpreted as a hierarchy of circulations attached to the surface. Based on this structure, we define a new near-surface layer in free convection, the plume-merging layer, that is conceptually different from the constant-flux layer. The varying depth of the plume-merging layer depending on the stratification accounts for the varying depth of validity of the scaling laws. These findings imply that the buoyancy transfer law needed in mixed-layer and single-column models is well described by the classical similarity theory, independent of the stratification in the free atmosphere, even though other near-surface properties, such as the r.m.s. of the buoyancy fluctuation and the r.m.s. of the vertical velocity, are inconsistent with that theory.

An improvement in mass flux convective parameterizations and its impact on seasonal simulations using a coupled model

A new closure and a modified detrainment for the simplified Arakawa–Schubert (SAS) cumulus parameterization scheme are proposed. In the modified convective scheme which is named as King Abdulaziz University (KAU) scheme, the closure depends on both the buoyancy force and the environment mean relative humidity. A lateral entrainment rate varying with environment relative humidity is proposed and tends to suppress convection in a dry atmosphere. The detrainment rate also varies with environment relative humidity. The KAU scheme has been tested in a single column model (SCM) and implemented in a coupled global climate model (CGCM). Increased coupling between environment and clouds in the KAU scheme results in improved sensitivity of the depth and strength of convection to environmental humidity compared to the original SAS scheme. The new scheme improves precipitation simulation with better representations of moisture and temperature especially during suppressed convection periods. The KAU scheme implemented in the Seoul National University (SNU) CGCM shows improved precipitation over the tropics. The simulated precipitation pattern over the Arabian Peninsula and Northeast African region is also improved.

Intercomparison of methods of coupling between convection and large-scale circulation: 1. Comparison over uniform surface conditions.

As part of an international intercomparison project, a set of single‐column models (SCMs) and cloud‐resolving models (CRMs) are run under the weak‐temperature gradient (WTG) method and the damped gravity wave (DGW) method. For each model, the implementation of the WTG or DGW method involves a simulated column which is coupled to a reference state defined with profiles obtained from the same model in radiative‐convective equilibrium. The simulated column has the same surface conditions as the reference state and is initialized with profiles from the reference state. We performed systematic comparison of the behavior of different models under a consistent implementation of the WTG method and the DGW method and systematic comparison of the WTG and DGW methods in models with different physics and numerics. CRMs and SCMs produce a variety of behaviors under both WTG and DGW methods. Some of the models reproduce the reference state while others sustain a large‐scale circulation which results in either substantially lower or higher precipitation compared to the value of the reference state. CRMs show a fairly linear relationship between precipitation and circulation strength. SCMs display a wider range of behaviors than CRMs. Some SCMs under the WTG method produce zero precipitation. Within an individual SCM, a DGW simulation and a corresponding WTG simulation can produce different signed circulation. When initialized with a dry troposphere, DGW simulations always result in a precipitating equilibrium state. The greatest sensitivities to the initial moisture conditions occur for multiple stable equilibria in some WTG simulations, corresponding to either a dry equilibrium state when initialized as dry or a precipitating equilibrium state when initialized as moist. Multiple equilibria are seen in more WTG simulations for higher SST. In some models, the existence of multiple equilibria is sensitive to some parameters in the WTG calculations.

A Hybrid Evolutionary–Deterministic Optimization Approach for Conceptual Design

Most optimization-based approaches in conceptual process design either focus on global optimization using simplified process models or utilize some kind of metaheuristic to optimize by means of repetitive runs of a detailed simulation model. Because the design of even a single distillation column model results in a nonconvex large-scale and mixed-integer optimization problem, if rigorous thermodynamic models are applied, deterministic optimization is still mostly limited to local optimization. In order to investigate and improve the solution quality of previously developed efficient local optimization approaches, this paper proposes a hybrid evolutionary–deterministic optimization approach. The resulting memetic algorithm not only allows the optimization of the initial process structure but also facilitates discrete decision making that severely complicates a deterministic optimization due to the resulting discontinuities. The proposed approach not only eases the application by reducing the necessary user...

Ion exchange recovery of rhenium from industrially relevant sulfate solutions: Single column separations and modeling

In this study, phenomena behind recovery of Re by weak anion exchangers from sulfate solutions containing Mo and As as impurities were investigated. All the metals exist as different kinds of oxyanions or, at some conditions, cations, meaning that several phenomena need to be taken into account. Batch uptake kinetics and dynamic breakthrough experiments were conducted with three commercial resins, and a model based on competitive Langmuir isotherm and an approximate diffusion equation was used to describe competitive sorption of the oxyacids. The separation systems are also discussed in relation to thermodynamic properties of the related oxyanions.The ability of the anion exchangers to adsorb Re from concentrated sulfate solutions is related to the size and degree of hydration of perrhenate anion, ReO4−. Especially high Re equilibrium capacities of the Purolite A170 and gel-type A172 resins are related to their complex amine functional group, which favors less charged and more hydrophobic anions. However, the functionality did not explain the superior Re/Mo selectivity of the A172 resin detected especially in dynamic column experiments. Diffusion coefficients of all components were remarkably low in A172, and the measured moisture content of the resin was also low. These observations lead to a conclusion that the physical structure of the A172 is so dense that Mo species can only enter near the surface of the resin particle, which is the cause to a low uptake. Both of the Purolite resins also had a good Re/As selectivity, and are well suited for recovering Re from acidic sulfate solutions not containing Mo that are common in industrial applications.

Revisiting the Bulk Relation for Heat Flux in the Free Convection Limit

We modify the velocity applied to the bulk relation for surface heat flux using turbulent kinetic energy, such that the effect of horizontal flow induced by unresolved free convection is incorporated. Numerical experiments with a large-eddy simulation (LES) and a single-column model (SCM) are examined for an ideal convective boundary layer. The surface fluxes obtained from both models are compared to investigate the effect of the velocity correction. It is confirmed that the surface heat flux calculated with the velocity correction is relatively consistent between the LES and SCM, even for a free convection case. Furthermore, the proposed method provides an evaluation of the surface heat flux that is insensitive to the model resolution, unlike the conventional method.

Constraints on Cumulus Parameterization from Simulations of Observed MJO Events

Abstract Two recent activities offer an opportunity to test general circulation model (GCM) convection and its interaction with large-scale dynamics for observed Madden–Julian oscillation (MJO) events. This study evaluates the sensitivity of the Goddard Institute for Space Studies (GISS) GCM to entrainment, rain evaporation, downdrafts, and cold pools. Single Column Model versions that restrict weakly entraining convection produce the most realistic dependence of convection depth on column water vapor (CWV) during the Atmospheric Radiation Measurement MJO Investigation Experiment at Gan Island. Differences among models are primarily at intermediate CWV where the transition from shallow to deeper convection occurs. GCM 20-day hindcasts during the Year of Tropical Convection that best capture the shallow–deep transition also produce strong MJOs, with significant predictability compared to Tropical Rainfall Measuring Mission data. The dry anomaly east of the disturbance on hindcast day 1 is a good predictor of MJO onset and evolution. Initial CWV there is near the shallow–deep transition point, implicating premature onset of deep convection as a predictor of a poor MJO simulation. Convection weakly moistens the dry region in good MJO simulations in the first week; weakening of large-scale subsidence over this time may also affect MJO onset. Longwave radiation anomalies are weakest in the worst model version, consistent with previous analyses of cloud/moisture greenhouse enhancement as the primary MJO energy source. The authors’ results suggest that both cloud-/moisture-radiative interactions and convection–moisture sensitivity are required to produce a successful MJO simulation.

Three‐dimensional constrained variational analysis: Approach and application to analysis of atmospheric diabatic heating and derivative fields during an ARM SGP intensive observational period

AbstractAtmospheric vertical velocities and advective tendencies are essential large‐scale forcing data to drive single‐column models (SCMs), cloud‐resolving models (CRMs), and large‐eddy simulations (LESs). However, they cannot be directly measured from field measurements or easily calculated with great accuracy. In the Atmospheric Radiation Measurement Program (ARM), a constrained variational algorithm (1‐D constrained variational analysis (1DCVA)) has been used to derive large‐scale forcing data over a sounding network domain with the aid of flux measurements at the surface and top of the atmosphere (TOA). The 1DCVA algorithm is now extended into three dimensions (3DCVA) along with other improvements to calculate gridded large‐scale forcing data, diabatic heating sources (Q1), and moisture sinks (Q2). Results are presented for a midlatitude cyclone case study on 3 March 2000 at the ARM Southern Great Plains site. These results are used to evaluate the diabatic heating fields in the available products such as Rapid Update Cycle, ERA‐Interim, National Centers for Environmental Prediction Climate Forecast System Reanalysis, Modern‐Era Retrospective Analysis for Research and Applications, Japanese 55‐year Reanalysis, and North American Regional Reanalysis. We show that although the analysis/reanalysis generally captures the atmospheric state of the cyclone, their biases in the derivative terms (Q1 and Q2) at regional scale of a few hundred kilometers are large and all analyses/reanalyses tend to underestimate the subgrid‐scale upward transport of moist static energy in the lower troposphere. The 3DCVA‐gridded large‐scale forcing data are physically consistent with the spatial distribution of surface and TOA measurements of radiation, precipitation, latent and sensible heat fluxes, and clouds that are better suited to force SCMs, CRMs, and LESs. Possible applications of the 3DCVA are discussed.

Development of a toy column model and its application in testing cumulus convection parameterizations

A single-column model is constructed based on parameterizations inherited from the Finite-volume/Spectral Atmospheric Model F/SAMIL and tested in simulations of tropical convective systems. Two representative convection schemes are compared in terms of their performances on precipitation types, individual physical tendencies, and temperature and moisture fields. The main difference between the two selected schemes is in their representation of entraining/detraining process. The Tiedtke scheme assumes bulk entrainment, while the Zhang-McFarlane scheme parameterizes entrainment/detrainment rates under the spectrum concept. Large-scale forcing and verification data are taken from the GATE phase III field campaign, during which abundant convective events were observed. Given the same triggering function and closure assumption, results show that entrainment/detrainment representation remains the dominant factor on the simulation of cumulus mass flux and of temperature and moisture fields. By analyzing sources and sinks of heat and moisture, this study reveals how parameterization components compensate for each other and make model results insensitive to parameterization changes in certain fields, thus suggesting the need to treat parameterizations as systems rather than individual components.

Improved Low-Cloud Simulation from the Community Atmosphere Model with an Advanced Third-Order Turbulence Closure

Abstract In this study, a simplified intermediately prognostic higher-order turbulence closure (IPHOC) is implemented in the Community Atmosphere Model, version 5 (CAM5), to provide a consistent treatment of subgrid-scale cloud processes, except for deep convection. The planetary boundary layer (PBL) height is prognosticated to better resolve the discontinuity of temperature and moisture above the PBL top. Single-column model tests show that fluxes of liquid water potential temperature and total water, cloud fraction, and liquid water content are improved with this approach. The simplified IPHOC package replaces the boundary layer dry and moist turbulence parameterizations, the shallow convection parameterization, and the liquid-phase part of the cloud macrophysics parameterization in CAM5. CAM5-IPHOC improves the simulation of the low-level clouds off the west coasts of continents and the storm track region in the Southern Hemisphere (SH). The transition from stratocumulus to cumulus clouds is more gradual. There are also improvements on the cloud radiative forcing, especially shortwave, in the subsidence regime. The improvements in the relationships among low cloud amount, surface relative humidity, lower tropospheric stability, and PBL depth are seen in some stratocumulus regions. CAM5-IPHOC, however, produces weaker precipitation at the South Pacific convergence zone than CAM5 because of less energy flux into the SH atmosphere. The more downward surface shortwave radiative cooling and the less top-of-the-atmosphere longwave cloud radiative heating in the SH relative to the Northern Hemisphere explains the anomalous cooling and the lesser energy flux into the SH, which is related to the underestimate of extratropical middle/high clouds in the SH.

Large-Eddy Simulation and Single-Column Modeling of Thermally Stratified Wind Turbine Arrays for Fully Developed, Stationary Atmospheric Conditions

AbstractEffects of atmospheric thermal stratification on the asymptotic behavior of very large wind farms are studied using large-eddy simulations (LES) and a single-column model for vertical distributions of horizontally averaged field variables. To facilitate comparisons between LES and column modeling based on Monin–Obukhov similarity theory, the LES are performed under idealized conditions of statistical stationarity in time and fully developed conditions in space. A suite of simulations are performed for different thermal stratification levels and the results are used to evaluate horizontally averaged vertical profiles of velocity, potential temperature, vertical turbulent momentum, and heat flux. Both LES and the model show that the stratification significantly affects the atmospheric boundary layer structure, its height, and the surface fluxes. However, the effects of the wind farm on surface heat fluxes are found to be relatively small in both LES and the single-column model. The surface fluxes are the result of two opposing trends: an increase of mixing in wakes and a decrease in mixing in the region below the turbines due to reduced momentum fluxes there for neutral and unstable cases, or relatively unchanged shear stresses below the turbines in the stable cases. For the considered cases, the balance of these trends yields a slight increase in surface flux magnitude for the stable and near-neutral unstable cases, and a very small decrease in flux magnitude for the strongly unstable cases. Moreover, thermal stratification is found to have a negligible effect on the roughness scale as deduced from the single-column model, consistent with the expectations of separation of scale.

How Climate Model Complexity Influences Sea Ice Stability

AbstractRecord lows in Arctic sea ice extent have been making frequent headlines in recent years. The change in albedo when sea ice is replaced by open water introduces a nonlinearity that has sparked an ongoing debate about the stability of the Arctic sea ice cover and the possibility of Arctic “tipping points.” Previous studies identified instabilities for a shrinking ice cover in two types of idealized climate models: (i) annual-mean latitudinally varying diffusive energy balance models (EBMs) and (ii) seasonally varying single-column models (SCMs). The instabilities in these low-order models stand in contrast with results from comprehensive global climate models (GCMs), which typically do not simulate any such instability. To help bridge the gap between low-order models and GCMs, an idealized model is developed that includes both latitudinal and seasonal variations. The model reduces to a standard EBM or SCM as limiting cases in the parameter space, thus reconciling the two previous lines of research. It is found that the stability of the ice cover vastly increases with the inclusion of spatial communication via meridional heat transport or a seasonal cycle in solar forcing, being most stable when both are included. If the associated parameters are set to values that correspond to the current climate, the ice retreat is reversible and there is no instability when the climate is warmed. The two parameters have to be reduced by at least a factor of 3 for instability to occur. This implies that the sea ice cover may be substantially more stable than has been suggested in previous idealized modeling studies.

Development and application of a weather data service client for preparation of weather input files to a crop model

Crop yield prediction has been made using a crop growth model that relies on four categories of input data including soil, crop, management, and weather. Most crop models are single column models, which require individual weather inputs for each site of interest. The objectives of this study were to develop a weather data service client that prepares weather input files for a crop growth model and to examine its application to yield prediction at a national scale. The weather data service client downloads daily weather data from the web-based weather data service portal operated by the Korea Meteorological Administration (KMA). The client also prepares weather input files for the ORYZA 2000 model at minimum effort. In total, 4950 input files were prepared to predict rice yield in 2011 and 2012 using the weather data service client. To prepare nearly 5000 weather input files, it would take more than a month for a skilled person to download weather data from the KMA database and to reorganize those data to the input data format for the ORYZA 2000 model manually. Using the weather data service client, several hours were enough to prepare all the input files without error associated with manual preparation as well as with minimum effort and labor.

A single‐column model intercomparison on the stratocumulus representation in present‐day and future climate

AbstractSix Single‐Column Model (SCM) versions of climate models are evaluated on the basis of their representation of the dependence of the stratocumulus‐topped boundary layer regime on the free tropospheric thermodynamic conditions. The study includes two idealized experiments corresponding to the present‐day and future climate conditions in order to estimate the low‐cloud feedback. Large‐Eddy Simulation (LES) results are used as a benchmark and GCM outputs are included to assess whether the SCM results are representative of their 3‐D counterparts. The SCMs present a variety of dependencies of the cloud regime on the free tropospheric conditions but, at the same time, several common biases. For all the SCMs the stratocumulus‐topped boundary layer is too shallow, too cool, and too moist as compared to the LES results. Moreover, they present a lack of clouds and liquid water and an excess of precipitation. The disagreement among SCMs is even more distinct for the response to a climate perturbation. Even though the overall feedback is positive for all the models, in line with the LES results, the SCMs show a rather noisy behavior, which depends irregularly on the free tropospheric conditions. Finally, the comparison with the host GCM outputs demonstrates that the considered approach is promising but needs to be further generalized for the SCMs to fully capture the behavior of their 3‐D counterparts.

Representing Richardson Number Hysteresis in the NWP Boundary Layer

Abstract Turbulence in the planetary boundary layer (PBL) transports heat, momentum, and moisture in eddies that are not resolvable by current NWP systems. Numerical models typically parameterize this process using vertical diffusion operators whose coefficients depend on the intensity of the expected turbulence. The PBL scheme employed in this study uses a one-and-a-half-order closure based on a predictive equation for the turbulent kinetic energy (TKE). For a stably stratified fluid, the growth and decay of TKE is largely controlled by the dynamic stability of the flow as represented by the Richardson number. Although the existence of a critical Richardson number that uniquely separates turbulent and laminar regimes is predicted by linear theory and perturbation analysis, observational evidence and total energy arguments suggest that its value is highly uncertain. This can be explained in part by the apparent presence of turbulence regime-dependent critical values, a property known as Richardson number hysteresis. In this study, a parameterization of Richardson number hysteresis is proposed. The impact of including this effect is evaluated in systems of increasing complexity: a single-column model, a forecast case study, and a full assimilation cycle. It is shown that accounting for a hysteretic loop in the TKE equation improves guidance for a canonical freezing rain event by reducing the diffusive elimination of the warm nose aloft, thus improving the model’s representation of PBL profiles. Systematic enhancements in predictive skill further suggest that representing Richardson number hysteresis in PBL schemes using higher-order closures has the potential to yield important and physically relevant improvements in guidance quality.

Aerosol specification in single-column Community Atmosphere Model version 5

Abstract. Single-column model (SCM) capability is an important tool for general circulation model development. In this study, the SCM mode of version 5 of the Community Atmosphere Model (CAM5) is shown to handle aerosol initialization and advection improperly, resulting in aerosol, cloud-droplet, and ice crystal concentrations which are typically much lower than observed or simulated by CAM5 in global mode. This deficiency has a major impact on stratiform cloud simulations but has little impact on convective case studies because aerosol is currently not used by CAM5 convective schemes and convective cases are typically longer in duration (so initialization is less important). By imposing fixed aerosol or cloud-droplet and crystal number concentrations, the aerosol issues described above can be avoided. Sensitivity studies using these idealizations suggest that the Meyers et al. (1992) ice nucleation scheme prevents mixed-phase cloud from existing by producing too many ice crystals. Microphysics is shown to strongly deplete cloud water in stratiform cases, indicating problems with sequential splitting in CAM5 and the need for careful interpretation of output from sequentially split climate models. Droplet concentration in the general circulation model (GCM) version of CAM5 is also shown to be far too low (~ 25 cm−3) at the southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site.

Representation of daytime moist convection over the semi‐arid Tropics by parametrizations used in climate and meteorological models

A case of daytime development of deep convection over tropical semi‐arid land is used to evaluate the representation of convection in global and regional models. The case is based on observations collected during the African Monsoon Multidisciplinary Analysis (AMMA) field campaign and includes two distinct transition phases, from clear sky to shallow cumulus and from cumulus to deep convection. Different types of models, run with identical initial and boundary conditions, are intercompared: a reference large‐eddy simulation (LES), single‐column model (SCM) version of four different Earth system models that participated in the Coupled Model Intercomparison Project 5 exercise, the SCM version of the European Centre for Medium‐range Weather Forecasts operational forecast model, the SCM version of a mesoscale model and a bulk model. Surface fluxes and radiative heating are prescribed preventing any atmosphere–surface and cloud–radiation coupling in order to simplify the analyses so that it focuses only on convective processes. New physics packages are also evaluated within this framework.As the LES correctly reproduces the observed growth of the boundary layer, the gradual development of shallow clouds, the initiation of deep convection and the development of cold pools, it provides a basis to evaluate in detail the representation of the diurnal cycle of convection by the other models and to test the hypotheses underlying convective parametrizations. Most SCMs have difficulty in representing the timing of convective initiation and rain intensity, although substantial modifications to boundary‐layer and deep‐convection parametrizations lead to improvements. The SCMs also fail to represent the mid‐level troposphere moistening during the shallow convection phase, which we analyse further. Nevertheless, beyond differences in timing of deep convection, the SCM models reproduce the sensitivity to initial and boundary conditions simulated in the LES regarding boundary‐layer characteristics, and often the timing of convection triggering.

Clear‐sky stable boundary layers with low winds over snow‐covered surfaces. Part 1: WRF model evaluation

In this article, we evaluate the Weather Research and Forecasting (WRF) mesoscale meteorological model for stable conditions in clear skies with low wind speeds. Three contrasting terrains with snow‐covered surfaces are considered, namely Cabauw (Netherlands, snow over grass), Sodankylä (Finland, snow over a needle‐leaf forest) and Halley (Antarctica, snow over an ice shelf). We used the full three‐dimensional (3D) model and the single‐column versions of the WRF model. The single‐column model (SCM) was driven by realistic forcings of the WRF–3D field. Several sets of SCM forcings were tested: A, no advection; B, varying geostrophic wind in time; C, momentum advection in addition to B; D, temperature and moisture advection in addition to C; E, forcing the SCM field to the 3D field above a threshold height.The WRF–3D model produced good results overall for wind speed, but the near‐surface temperatures and specific humidity were overestimated for Cabauw and Sodankylä and underestimated for Halley. Prescribing advection for momentum, temperature and moisture gave the best results for the WRF–SCM and simulations deviated strongly from reality without advection. Nudging the SCM field to the 3D field above a threshold height led to an unrealistic behaviour of the variables below this height and is not recommended. Detailed prescription of the surface characteristics, e.g. adjusting the snow cover and vegetation fraction, improved the 2 m temperature simulation. For all three sites, the simulated temperature and moisture inversion were underestimated, though this improved when prescribing advection.Overall, in clear‐sky conditions, the stable boundary layer over snow and ice can be modelled to a good approximation if all processes are taken into account at high resolution and if land surface properties are carefully prescribed.