Single-column Model Research Articles

Constraining stochastic parametrisation schemes using high‐resolution simulations

AbstractStochastic parametrisations can be used in weather and climate models to improve the representation of unpredictable unresolved processes. When compared with a deterministic model, a stochastic model represents “model uncertainty”, that is, sources of error in the forecast due to the limitations of the forecast model. A technique is presented for systematically deriving new stochastic parametrisations or constraining existing stochastic approaches. A high‐resolution model simulation is coarse‐grained to the desired forecast model resolution. This provides the initial conditions and forcing data needed to drive a single‐column model (SCM). Comparing the SCM parametrised tendencies with the evolution of the high‐resolution model provides an estimate of the error in the SCM tendencies that a stochastic parametrisation seeks to represent. This approach is used to assess the physical basis of the widely used stochastically perturbed parametrisation tendencies (SPPT) scheme. Justification is found for the multiplicative nature of SPPT, along with some evidence for the use of spatio‐temporally correlated stochastic perturbations. Evidence that the stochastic perturbation should be positively skewed is found, indicating that occasional large‐magnitude positive perturbations are physically realistic. However, other key assumptions of SPPT are less well justified, including coherency of the stochastic perturbations with height, coherency of the perturbations for different physical parametrisation schemes, and coherency for different prognostic variables. Relaxing these SPPT assumptions allows for an error model that explains a larger fractional variance than traditional SPPT. In particular, it is suggested that independently perturbing the tendencies associated with different parametrisation schemes is justifiable and would improve the realism of the SPPT approach.

A prototype stochastic parameterization of regime behaviour in the stably stratified atmospheric boundary layer

Abstract. Recent research has demonstrated that hidden Markov model (HMM) analysis is an effective tool to classify atmospheric observations of the stably stratified nocturnal boundary layer (SBL) into weakly stable (wSBL) and very stable (vSBL) regimes. Here we consider the development of explicitly stochastic representations of SBL regime dynamics. First, we analyze whether HMM-based SBL regime statistics (the occurrence of regime transitions, subsequent transitions after the first, and very persistent nights) can be accurately represented by “freely running” stationary Markov chains (FSMCs). Our results show that despite the HMM-estimated regime statistics being relatively insensitive to the HMM transition probabilities, these statistics cannot all simultaneously be captured by a FSMC. Furthermore, by construction a FSMC cannot capture the observed non-Markov regime duration distributions. Using the HMM classification of data into wSBL and vSBL regimes, state-dependent transition probabilities conditioned on the bulk Richardson number (RiB) or the stratification are investigated. We find that conditioning on stratification produces more robust results than conditioning on RiB. A prototype explicitly stochastic parameterization is developed based on stratification-dependent transition probabilities, in which turbulence pulses (representing intermittent turbulence events) are added during vSBL conditions. Experiments using an idealized single-column model demonstrate that such an approach can simulate realistic-looking SBL regime dynamics.

A Preliminary Impact Study of Wind on Assimilation and Forecast Systems into the One-Dimensional Fog Forecasting Model COBEL-ISBA over Morocco

The assimilation impact of wind data from aircraft measurements (AMDAR), surface synoptic observations (SYNOP) and 3D numerical weather prediction (NWP) mesoscale model, on short-range numerical weather forecasting (up to 12 h) and on the assimilation system, using the one-dimensional fog forecasting model COBEL-ISBA (Code de Brouillard à l’Échelle Locale-Interactions Soil Biosphere Atmosphere), is studied in the present work. The wind data are extracted at Nouasseur airport, Casablanca, Morocco, over a winter period from the national meteorological database. It is the first time that wind profiles (up to 1300 m) are assimilated in the framework of a single-column model. The impact is assessed by performing NWP experiments with data denial tests, configured to be close to the operational settings. The assimilation system estimates the flow-dependent background covariances for each run of the model and takes the cross-correlations between temperature, humidity and wind components into account. When assimilated into COBEL-ISBA with an hourly update cycle, the wind field has a positive impact on temperature and specific humidity analysis and forecasts accuracy. Thus, a superior fit of the analysis background fields to observations is found when assimilating AMDAR without NWP wind data. The latter has shown a detrimental impact in all experiments. Besides, wind assimilation gave a clear improvement to short-range forecasts of near-surface thermodynamical parameters. Although, assimilation of SYNOP and AMDAR wind measurements slightly improves the probability of detection of fog but also increases the false alarms ratio by a lower magnitude.

Formation of Arctic Stratocumuli Through Atmospheric Radiative Cooling

AbstractStratocumulus clouds are important to the Arctic climate because they are prevalent and exert a strong radiative forcing on the surface. However, relatively little is known about how stratocumulus clouds form in the Arctic. In this study, radiative transfer calculations are used to show that the timescale over which stably stratified Arctic temperature and water vapor profiles cool to saturation is less than typical residence times for individual air parcels in the Arctic. This result is consistent with previous studies in suggesting that elevated stratocumulus can form naturally through clear‐sky radiative cooling during all seasons, without assistance from frontal lifting or other atmospheric forcing. Single column model simulations of the cloud formation process, after radiative cooling has resulted in saturation in a stably stratified profile, suggest that stratocumulus cloud properties are sensitive to the characteristics of the environment in which the formation process takes place. For example, sensitivity tests suggest that clouds may attain liquid water paths of over 50 g/m2 if they form in moist environments but may become locked in a low‐liquid water path quasi steady state or dissipate within hours if they form in dry environments. A potential consequence of these sensitivities is that when an Arctic stratocumulus layer forms by radiative cooling, it is more likely to become optically thick, optically thin, or dissipate than it is to obtain an intermediate optical thickness. This could help explain why the cloudy and radiatively clear atmospheric states are so prevalent across the Arctic.

A Novel Framework for Evaluating and Improving Parameterized Subtropical Marine Boundary Layer Cloudiness

AbstractA single-column model (SCM) is used to simulate a variety of environmental conditions between Los Angeles, California, and Hawaii in order to identify physical elements of parameterizations that are required to reproduce the observed behavior of marine boundary layer (MBL) cloudiness. The SCM is composed of the JPL eddy-diffusivity/mass-flux (EDMF) mixing formulation and the RRTMG radiation model. Model forcings are provided by the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2). Simulated low cloud cover (LCC), rain rate, albedo, and liquid water path are compared to collocated pixel-level observations from A-Train satellites. This framework ensures that the JPL EDMF is able to simulate a continuum of real-world conditions. First, the JPL EDMF is shown to reproduce the observed mean LCC as a function of lower-tropospheric stability. Joint probability distributions of lower-tropospheric cloud fraction, height, and lower-tropospheric stability (LTS) show that the JPL EDMF improves upon its MERRA2 input but struggles to match the frequency of observed intermediate-range LCC. We then illustrate the physical roles of plume lateral entrainment and eddy-diffusivity mixing length in producing a realistic behavior of LCC as a function of LTS. In low-LTS conditions, LCC is mostly sensitive to the ability of convection to mix moist air out of the MBL. In high-LTS conditions, LCC is also sensitive to the turbulent mixing of free-tropospheric air into the MBL. In the intermediate LTS regime typical of stratocumulus–cumulus transition there is proportional sensitivity to both mixing mechanisms, emphasizing the utility of a combined eddy-diffusivity/mass-flux approach for representing mixing processes.

Simulation Study of Cloud Properties Affected by Heterogeneous Nucleation Using the GRAPES_SCM during the TWP-ICE Campaign

This study used the Global/Regional Assimilation and PrEdiction System Single-Column Model (GRAPES_SCM) to simulate monsoon precipitation with deep convective cloud and associated cirrus during the Tropical Warm Pool International Cloud Experiment (TWP-ICE), especially during the active and suppressed monsoon periods. Four cases with different heterogeneous nucleation parameterizations were simulated by using the ensemble method. All simulations clearly separated the active and suppressed monsoon periods, and they reproduced the major characteristics of monsoonal cloud such as the total cloud hydrometeor mixing ratio distribution, and precipitation and radiation properties. The results showed that the number concentration production rate of different heterogeneous nucleation parameterizations varied substantially under the given temperature and water vapor mixing ratio. However, ice formation and precipitation during the monsoon period were affected only slightly by the different heterogeneous nucleation parameterizations. This study also captured clear competition between different ice formation processes.

A Unified Eddy-Diffusivity/Mass-Flux Approach for Modeling Atmospheric Convection

Abstract A fully unified parameterization of boundary layer and moist convection (shallow and deep) is presented. The new parameterization is based on the stochastic multiplume eddy-diffusivity/mass-flux (EDMF) approach, which distinguishes between convective plumes and nonconvective mixing. The convective plumes represent both surface-forced updrafts and evaporatively driven downdrafts. The type of convection (i.e., dry, shallow, or deep) represented by the updrafts is not defined a priori, but rather depends on the near-surface updraft properties and the stochastic interactions between the plumes and the environment through lateral entrainment. Consequently, some updrafts may contribute only to the nonlocal transport within the subcloud layer, while others may condense and form shallow or even deep convection. Such a formulation is void of trigger functions and additional closures typical of modular parameterizations. The updrafts are coupled to relatively simple warm-, mixed-, and ice-phase microphysics. Each precipitating updraft forms a downdraft driven by the evaporation of detrained precipitation. The downdrafts control the development of cold pools near the surface that can invigorate convection. The new parameterization is tested in a single-column model against large-eddy simulations (LESs) for cases representing weakly precipitating marine convection and the diurnal cycle of continental deep convection. The results of these EDMF experiments compare well with the LES reference simulations. In particular, the transitions between the different dominant convection regimes are realistically simulated.

Effect of Wind Speed and Leads on Clear-Sky Cooling over Arctic Sea Ice during Polar Night

Abstract A simple analytical model of the atmospheric boundary layer (ABL) coupled to sea ice is presented. It describes clear-sky cooling over sea ice during polar night in the presence of leads. The model solutions show that the sea ice concentration and wind speed have a strong impact on the thermal regime over sea ice. Leads cause both a warming of the ABL and an increase of stability over sea ice. The model describes a sharp ABL transition from a weakly stable coupled state to a strongly stable decoupled state when wind speed is decreasing. The threshold value of the transition wind speed is a function of sea ice concentration. The decoupled state is characterized by a large air–surface temperature difference over sea ice, which is further increased by leads. In the coupled regime, air and surface temperatures increase almost linearly with wind speed due to warming by leads and also slower cooling of the ABL. The cooling time scale shows a nonmonotonic dependency on wind speed, being lowest for the threshold value of wind speed and increasing for weak and strong winds. Theoretical solutions agree well with results of a more realistic single-column model and with observations performed at the three Russian “North Pole” drifting stations (NP-35, -37, and -39) and at the Surface Heat Budget of the Arctic Ocean ice camp. Both modeling results and observations show a strong implicit dependency of the net longwave radiative flux at the surface on wind speed.

TKE-Based Moist Eddy-Diffusivity Mass-Flux (EDMF) Parameterization for Vertical Turbulent Mixing

Abstract A new turbulent kinetic energy (TKE)-based moist eddy-diffusivity mass-flux (EDMF) vertical turbulence mixing scheme (EDMF-TKE) is developed, where the nonlocal transport by large turbulent eddies is represented by a mass-flux (MF) scheme while the local transport by small turbulent eddies is represented by an eddy-diffusivity (ED) scheme, which is given by a function of a prognostic TKE. In the scheme, an MF approach is employed for the stratocumulus-top-driven downdrafts as well as for the thermals in the daytime unstable boundary layer. The scheme includes parameterizations for enhanced buoyancy due to moist adiabatic processes in condensation and for TKE interaction with cumulus convection. A scale-aware parameterization is proposed for the grid sizes where the large turbulent eddies are partially resolved. The single-column model (SCM) tests show that both the EDMF-TKE and the current operational NCEP GFS hybrid EDMF scheme (EDMF-CTL) simulate a daytime dry-convective boundary layer well and agree with a benchmark large-eddy simulation (LES). For a marine stratocumulus-topped boundary layer case, the EDMF-TKE better simulates the liquid water and wind speed profiles than the EDMF-CTL compared to the LES. For a stable boundary layer (SBL) case, the EDMF-TKE also agrees better with the LES than the EDMF-CTL, although it tends to produce a deeper SBL compared to the LES. On the other hand, three-dimensional medium-range forecast experiments show that the EDMF-TKE slightly improves forecast skill in the 500-hPa height anomaly correlation and wind vector, while it has a neutral impact on precipitation forecasts over the continental United States.

Quantifying the aerosol effect on droplet size distribution at cloud top

Abstract. This work uses the number concentration-effective diameter phase-space to test cloud sensitivity to variations in the aerosol population characteristics, such as the aerosol size distribution, number concentration and hygroscopicity. It is based on the information from the top of a cloud simulated by a bin-microphysics single-column model, for initial conditions typical of the Amazon, using different assumptions regarding the entrainment and the aerosol size distribution. It is shown that the cloud-top evolution can be very sensitive to aerosol properties, but the relative importance of each parameter is variable. The sensitivity to each aerosol characteristic varies as a function of the parameter tested and is conditioned by the base values of the other parameters, showing a specific dependence for each configuration of the model. When both the entrainment and the bin treatment of the aerosol are allowed, the largest influence on the droplet size distribution sensitivity was obtained for the median radius of the aerosols and not for the total number concentration of aerosols. Our results reinforce that the cloud condensation nuclei activity can not be predicted solely on the basis of the w∕Na supersaturation-based regimes.

Competition between atmospheric and surface parameterizations for the control of air-sea latent heat fluxes in two single-column models

Competition between atmospheric and surface parameterizations for the control of air-sea latent heat fluxes in two single-column models

The Single Column Atmosphere Model Version 6 (SCAM6): Not a Scam but a Tool for Model Evaluation and Development

AbstractThe Single Column Atmosphere Model (SCAM) is a single column model version of the Community Atmosphere Model (CAM). Here we describe the functionality and features of SCAM6, available as part of CAM6 in the Community Earth System Model, version 2 (CESM2). SCAM6 features a wide selection of standard cases, as well as the ability to easily configure a case specified by the user based on a particular point in a CAM 3‐D simulation. This work illustrates how SCAM6 reproduces CAM6 results for physical parameterizations, mostly of moisture and clouds. We demonstrate how SCAM6 can be used for model development through different physics selections, as well as with parameter sweep experiments to highlight the sensitivity of cloud properties to the specification of the vapor deposition process in the cloud microphysics. Furthermore, we use SCAM6 to illustrate the sensitivity of CAM6 cloud radiative properties and precipitation to variable drop number (cloud microphysics properties). Finally, we illustrate how SCAM6 can be used to explore critical emergent processes such as cloud feedbacks and show that CAM6 cloud responses to surface warming in stratus and stratocumulus regimes are similar to those in CAM5. CAM6 has a larger response in the shallow cumulus regime than CAM5. CAM6 cloud feedbacks in the shallow cumulus regime are sensitive to turbulence parameters. SCAM6 is thus a valuable tool for model development, evaluation, and scientific analy sis and an important part of the model hierarchy in Community Earth System Model, version 2.

A New TKE‐Based Parameterization of Atmospheric Turbulence in the Canadian Global and Regional Climate Models

AbstractA new semi‐empirical turbulence parameterization is presented. Key features of the scheme include representation of turbulent diffusivities in terms of the turbulent kinetic energy that is determined by solving a quasi‐equilibrium form of the equation representing the turbulent kinetic energy budget. The new parameterization is innovative in the treatment of turbulent transfer in stably stratified conditions and the representation of nonlocal contributions to the vertical transport of heat, moisture, and scalar prognostic variables in convectively active boundary layers. A key element in the modeling of turbulence in stably stratified conditions is the formulation of the turbulent Prandtl number based on the results of recently published theoretical, modeling, and observational studies of stratified turbulence in the atmospheric boundary layer. The new parameterization has been implemented in the CanAM4 single column model. Its performance in comparison with that of the operational CanAM4 turbulence parameterization is documented in terms of selected results from case studies for clear‐sky conditions based on meteorological observations from the KNMI‐mast at Cabauw, Netherlands, and the Second Dynamics and Chemistry of Marine Stratocumulus case study of stratocumulus‐topped marine boundary layers. The performance of the new and operational schemes is qualitatively similar in clear‐sky conditions in both convective and stable boundary layer regimes. However, they perform differently for the extended simulations for the Second Dynamics and Chemistry of Marine Stratocumulus case study. The new scheme maintains an elevated stratocumulus layer throughout a 30‐hr simulation, but peak liquid water contents are larger than large eddy simulations.

Turbulent Collapse and Recovery in the Stable Boundary Layer Using an Idealized Model of Pressure-Driven Flow with a Surface Energy Budget

Abstract The evolution of the stable boundary layer is simulated using an idealized single-column model of pressure-driven flow coupled to a surface energy budget. Several commonly used parameterizations of turbulence are examined. The agreement between the simulated wind and temperature profiles and tower observations from the Cabauw tower is generally good given the simplicity of the model. The collapse and recovery of turbulence is explored in the presence of a large-scale pressure gradient, but excluding transient submesoscale atmospheric forcings such as internal waves and density-driven currents. The sensitivity tests presented here clarify the role of both rotation and the surface energy budget in the collapse and recovery of turbulence for the pressure-driven dry stable boundary layer (SBL). Conditions of stability are affected strongly by the geostrophic winds, the cloud cover, and the thermal conductivity of the surface. Inertial oscillations and the subsurface temperature have a weaker influence. Particularly noteworthy is the relationship between SBL regime and the relative importance of the terms in the surface energy budget.

Optimization of vertical grid setting for air quality modelling in China considering the effect of aerosol-boundary layer interaction

The feedback between ambient aerosols and planetary boundary layer (PBL) meteorology has been proven to play a critical role in the enhancement of haze pollution. Vertical distribution of aerosols as well as temperature stratification are vital to understand aerosol – boundary layer interaction (ABI) and its impact on air quality deterioration. In current regional air quality models, the default vertical grid setting is relatively coarse and decreases progressively with altitude. However, the ABI is sensitive to aerosol layer at specific altitudes, i.e. around the top of PBL. This work aims to explore optimized vertical grid setting for better characterizing ABI and its role in air quality degradation. A single column model (SCM) is used for sensitivity tests considering the balance between model performance and computational cost. This optimized grid setting is then applied in three-dimensional air quality modelling in eastern China. Compared with default configuration, the optimized one is demonstrated to perform much better in characterizing temperature stratification and extreme fine particle (PM2.5) concentration as well as its diurnal variation during haze episodes. Specifically, the averaged decrease in PBL height and increment in surface PM2.5 concentration are about 5% and 20% while applying optimized setting, thereby reducing the mean bias from 30 to 5 μg/m3 in PM2.5 concentration. The improvements could be attributed mainly to more accurate profiles of aerosol and its heating effect, and thus stabilized lower atmosphere. The optimization of vertical grid setting could be applied to areas with high concentration of absorbing aerosols such as eastern China and India, which could help better predict extreme near-surface pollution episodes.

Using the ECMWF OpenIFS model and state-of-the-art training techniques in meteorological education

Abstract. The OpenIFS programme of the European Centre for Medium-Range Weather Forecasts (ECMWF) maintains a version of the ECMWF forecast model (IFS; Integrated Forecasting System) for use in education and research at universities, national meteorological services and other institutes. The OpenIFS model can be run on high-performance computing systems, desktop or laptop computers to produce weather forecasts in a similar way to the operational forecasts at ECMWF. Application of OpenIFS as a training tool is wide ranging. At several universities, masters students are taught modelling aspects via sensitivity studies, such as numerical stability, impact of spatial resolution and physical parameterisation settings on the forecast quality. The OpenIFS single column model is used to study a subset of physical processes in the atmosphere. Participants of the OpenIFS user workshops are trained through selected weather events on interpretation of different forecasts, for example ensemble forecasts, probabilistic information, seasonal forecasts. The OpenIFS user meetings and training events demonstrate advanced and easy-to-use graphical tools and training technologies. Metview is developed to analyse, visualise and evaluate the forecast outputs. OpenIFS and Metview “virtual machines” relieve the tutors from the difficulties often found in installing this software on the local computing environment. They provide data, applications and documents in a package tested in-house and deployed easily to another site. A further step on virtualisation is utilising cloud servers, ensuring the computational resources demanded by model runs are available in the cloud space. This paper shows the education activity in the OpenIFS programme with some examples.

Transitions in the wintertime near-surface temperature inversion at Dome C, Antarctica.

In this work we study the dynamics of the surface‐based temperature inversion over the Antarctic Plateau during the polar winter. Using 6 years of observations from the French–Italian Antarctic station Concordia at Dome C, we investigate sudden regime transitions in the strength of the near‐surface temperature inversion. Here we define “near‐surface” as being within the domain of the 45‐m measuring tower. In particular, we consider the strongly nonlinear relation between the 10‐m inversion strength (T 10m – T s) and the 10‐m wind speed.To this end, all individual events for which the 10‐m inversion strength increases or decreases continuously by more than 15 K in time are considered. Composite time series and vertical profiles of wind and temperature reveal specific characteristics of the transition from weak to very strong inversions and vice versa. In contrast to midlatitudes, the largest variations in temperature are not found at the surface but at a height of 10 m.A similar analysis was performed on results from an atmospheric single‐column model (SCM). Overall, the SCM results reproduce the observed characteristics of the transitions in the near‐surface inversion remarkably well. Using model output, the underlying mechanisms of the regime transitions are identified. The nonlinear relation between inversion strength and wind speed at a given level is explained by variations in the geostrophic wind speed, changes in the depth of the turbulent layer and the vertical divergence of turbulent fluxes. Moreover, the transitions between different boundary layer regimes cannot be explained without considering the contribution of subsidence heating.

Nonuniqueness in a Single-Column Model for Moist Convection

Abstract We investigate a moist atmospheric column convection model by considering the atmosphere as a single vertical column of air parcels, each of which contains water vapor. The moist convective adjustment of both air and water mass in the column is considered from an (unstable) initial state to a statically stable final configuration of parcels. Two variations of an algorithm based upon swapping neighboring parcels are compared: after swapping, no parcels remain supersaturated. The results of these algorithms are compared directly with those of the adjustment algorithm of Cheng et al., which adjusts an atmospheric column to achieve the global maximum of a relevant cost functional. Two examples are considered: in the first, the algorithms adjust to similar arrangements, showing that the global maximum of the functional is the dynamically preferred state, while in the second, the algorithms adjust to significantly different states. Thus, we identify a nonuniqueness to the solution to the adjustment problem in terms of local and global cost functional maximizers. We then discuss the relevance of this nonuniqueness to numerical prediction in weather and climate models.

A single-column ocean biogeochemistry model (GOTM–TOPAZ) version 1.0

Abstract. Recently, Earth system models (ESMs) have begun to consider the marine ecosystem to reduce errors in climate simulations. However, many models are unable to fully represent the ocean-biology-induced climate feedback, which is due in part to significant bias in the simulated biogeochemical properties. Therefore, we developed the Generic Ocean Turbulence Model–Tracers of Phytoplankton with Allometric Zooplankton (GOTM–TOPAZ), a single-column ocean biogeochemistry model that can be used to improve ocean biogeochemical processes in ESMs. This model was developed by combining GOTM, a single-column model that can simulate the physical environment of the ocean, and TOPAZ, a biogeochemical module. Here, the original form of TOPAZ has been modified and modularized to allow easy coupling with other physical ocean models. To demonstrate interactions between ocean physics and biogeochemical processes, the model was designed to allow ocean temperature to change due to absorption of visible light by chlorophyll in phytoplankton. We also added a module to reproduce upwelling and the air–sea gas transfer process for oxygen and carbon dioxide, which are of particular importance for marine ecosystems. The simulated variables (e.g., chlorophyll, oxygen, nitrogen, phosphorus, silicon) of GOTM–TOPAZ were evaluated by comparison against observations. The temporal variability in the observed upper-ocean (0–20 m) chlorophyll is well captured by the GOTM–TOPAZ with a correlation coefficient of 0.53 at point 107 in the Sea of Japan. The surface correlation coefficients among GOTM–TOPAZ oxygen, nitrogen, phosphorus, and silicon are 0.47, 0.31, 0.16, and 0.19, respectively. We compared the GOTM–TOPAZ simulations with those from MOM–TOPAZ and found that GOTM–TOPAZ showed relatively lower correlations, which is most likely due to the limitations of the single-column model. Results also indicate that source–sink terms may contribute to the biases in the surface layer (<60 m), while initial values are important for realistic simulations in the deep sea (>250 m). Despite this limitation, we argue that our GOTM–TOPAZ model is a good starting point for further investigation of key biogeochemical processes and is also useful to couple complex biogeochemical processes with various oceanic global circulation models.

Shallow-to-Deep Transition of Continental Moist Convection: Cold Pools, Surface Fluxes, and Mesoscale Organization

Abstract Large-eddy simulation is used to investigate the effects of cold pools driven by rain evaporation on the shallow-to-deep convection transition over land. The physically consistent methodologies are developed to obtain a time-dependent reference ensemble without cold pools and to apply interactive surface heat fluxes without modeling of surface energy and water budgets. Three different simulation ensembles are contrasted. The reference ensemble, in the spirit of one-dimensional single-column models, eliminates cold pools by horizontally homogenizing negative buoyancy production due to rain evaporation. The additional ensembles complement the reference cold-pool-free ensemble by including cold pools and by applying either interactive or prescribed surface fluxes. Contrasting these ensembles suggests possible improvements of convection parameterization in large-scale models of weather and climate. Without cold pools, the reference ensemble preserves key features of buoyancy-driven cellular convection associated with a field of convective plumes, as assumed in a typical convection parameterization. With cold pools, a significant enhancement of surface heat and moisture fluxes and about an hour delay of their daily maximum is simulated. Cold pools enhance near-surface temperature and moisture standard deviations as well as maxima of the near-surface updraft velocity. They also lead to the reduction of cloud lateral entrainment, deeper vertical development of the cloud layer, and a few-times-larger accumulated surface precipitation. Interactive surface fluxes provide a damping mechanism that noticeably suppresses all these effects. Perhaps surprisingly, cold pools do not significantly change the cloud-base convective mass flux that approximately follows the evolution of surface heat fluxes.