Tropical Warm Pool International Cloud Experiment Research Articles

The Impacts of Single-Scattering and Microphysical Properties of Ice Particles Smaller Than 100 µm on the Bulk Radiative Properties of Tropical Cirrus

There are large uncertainties in the single-scattering (i.e., morphologies) and microphysical (i.e., concentrations) properties of ice particles whose size are less than ~100 µm. Insufficient resolutions of the most advanced cloud probes (e.g., cloud particle imager) cannot resolve the micrometer-scale morphologies of small ice particles. Further, the shattering of large ice particles on probes’ inlets or tips causes uncertainties in the measurement of the concentrations of small ice particles. These uncertainties have large impacts on the single-scattering and microphysical properties of small ice particles that are utilized to quantify the bulk radiative properties of cirrus. In this study, the impacts of uncertainties in the morphologies and concentrations of small ice particles on the bulk radiative properties of tropical cirrus were calculated using measurements acquired during the Tropical Warm Pool-International Cloud Experiment. Five different models (i.e., budding Buckyball, Chebyshev particle, droxtal, Gaussian random sphere, and sphere) that represent the shapes of small ice particles were used to calculate the single-scattering properties. The bulk radiative properties, average phase-function (P11¯), and average asymmetry parameter (g¯) were computed by combining the measured size/habit distributions and the calculated single-scattering properties of ice particles. The impacts of the selection of varying morphologies of small particles on the bulk radiative properties were quantified. For these calculations, the possible range of the concentrations of small ice particles which depend on the degree of shattered large particles were also used. The impacts of varying the single-scattering properties of small ice particles on the bulk radiative properties were the largest in the upper parts of cirrus (T < −60 °C), while they were the smallest in the lower parts of cirrus (−45 < T < −30 °C). The impacts of uncertainties in the concentrations of small ice particles on the bulk radiative properties were largest in the lower parts of cirrus (−45 < T < −30 °C), whereas they were smallest in the upper parts of cirrus (T < −60 °C). The effect of shattering was maximum in the lower parts of cirrus, whilst it was minimum in the upper parts of cirrus. The combined impacts of uncertainties in the single-scattering (i.e., morphologies) and microphysical (i.e., concentrations) properties of small ice particles revealed variations of up to 11.2% (127.1%; 67.3%) of the integrated intensity in the forward (sideward; backward) angles in P11¯ and a corresponding change in g¯ by up to 12.61%.

Integrated cloud macro- and micro-physics schemes with kinetic treatment of condensation processes for global models

A new parameterization scheme was developed to remove the saturation adjustment assumption and resolve the condensation process in the grid-scale cloud macrophysics scheme to build an integrated cloud microphysics scheme for global climate models. By applying a saturation prediction equation with calculations based on cloud hydrometeor properties, supersaturation or subsaturation can be determined within the macrophysics scheme. This treatment provides the basis for condensation calculation and allows the Wegener–Bergeron–Findeisen process to be resolved explicitly to render a realistic liquid–ice partition in mixed-phase clouds. The cloud fraction scheme was modified based on physics principles to complement the condensation scheme. The new scheme's performance was examined by incorporating it into the Community Atmosphere Model version 5 (CAM5) single-column model to simulate a Tropical Warm Pool–International Cloud Experiment (TWP–ICE) case. The results revealed that grid-scale cloud properties are sensitive to the condensation process's treatment, and the new scheme can produce a more reasonable cloud fraction and liquid–ice partition than the original CAM5. The theory-based scheme developed in this study may provide insight for addressing consistency between the macrophysical and microphysical schemes in global climate models.

Evaluation of a Flexible Single Ice Microphysics and a Gaussian Probability-Density-Function Macrophysics Scheme in a Single Column Model

Scale-aware parameterizations of subgrid scale physics are essentials for multiscale atmospheric modeling. A single-ice (SI) microphysics scheme and Gaussian probability-density-function (Gauss-PDF) macrophysics scheme were implemented in the single-column Global-to-Regional Integrated forecast System model (SGRIST) and they were tested using the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) and the Atmospheric Radiation Measurement Southern Great Plains Experiment in 1997 (ARM97). Their performance was evaluated against observations and other reference schemes. The new schemes simulated reasonable precipitation with proper fluctuations and peaks, ice, and liquid water contents, especially in lower levels below 650 hPa during the wet period in the TWP-ICE. The root mean square error (RMSE) of the simulated cloud fraction was below 200 hPa was 0.10/0.08 in the wet/dry period, which showed an obvious improvement when compared to that, i.e., 0.11/0.11 of original scheme. Accumulated ice water content below the melting level decreased by 21.57% in the SI. The well-matched average liquid water content displayed between the new scheme and observations, which was two times larger than those with the referencing scheme. In the ARM97 simulations, the SI scheme produced considerable ice water content, especially when convection was active. Low-level cloud fraction and precipitation extremes were improved using the Gauss-PDF scheme, which displayed the RMSE of cloud fraction of 0.02, being only half of the original schemes. The study indicates that the SI and Gauss-PDF schemes are promising approaches to simplify the microphysics process and improve the low-level cloud modeling.

Improved Convective Ice Microphysics Parameterization in the NCAR CAM Model

AbstractPartitioning deep convective cloud condensates into components that sediment and detrain, known to be a challenge for global climate models, is important for cloud vertical distribution and anvil cloud formation. In this study, we address this issue by improving the convective microphysics scheme in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 (CAM5.3). The improvements include: (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, “rimed ice,” to the original four‐class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. Results from the default and modified CAM5.3 models were evaluated against observations from the U.S. Department of Energy Tropical Warm Pool‐International Cloud Experiment (TWP‐ICE) field campaign. The default model overestimates ice amount, which is largely attributed to the underestimation of convective ice particle sedimentation. By considering cloud ice sedimentation and rimed ice particles and applying a new convective snow terminal velocity parameterization, the vertical distribution of ice amount is much improved in the midtroposphere and upper troposphere when compared to observations. The vertical distribution of ice condensate also agrees well with observational best estimates upon considering snow detrainment. Comparison with observed convective updrafts reveals that current bulk model fails to reproduce the observed updraft magnitude and occurrence frequency, suggesting spectral distributions be required to simulate the subgrid updraft heterogeneity.

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.

Simulation of High-Resolution Precipitable Water Data by a Stochastic Model with a Random Trigger

We use a stochastic differential equation (SDE) model with a random precipitation trigger for mass balance to simulate the 20 s temporal resolution column precipitable water vapor (PWV) data during the tropical warm pool international cloud experiment (TWP-ICE) period of January 20 to February 15, 2006 at Darwin, Australia. The trigger is determined by an exponential cumulative distribution function, the time step size in the SDE simulation, and a random precipitation indicator uniformly distributed over [0, 1]. Compared with the observed data, the simulations have similar means, extremes, skewness, kurtosis, and overall shapes of probability distribution, and are temporally well synchronized for increasing and decreasing, but have about 20% lower standard deviation. Based on a 1000-day run, the correlations between the model data and the observations in TWP-ICE period were computed in a moving time window of 25 days and show quasi-periodic variations between (−0.675, 0.697). This shows that the results are robust for the stochastic model simulation of the observed PWV data, whose fractal dimension is 1.9, while the dimension of the simulated data is also about 1.9. This agreement and numerous sensitivity experiments form a test on the feasibility of using an SDE model to simulate precipitation processes in more complex climate models.

Estimation of convective entrainment properties from a cloud-resolving model simulation during TWP-ICE

The fractional entrainment rate in convective clouds is an important parameter in current convective parameterization schemes of climate models. In this paper, it is estimated using a 1-km-resolution cloud-resolving model (CRM) simulation of convective clouds from TWP-ICE (the Tropical Warm Pool-International Cloud Experiment). The clouds are divided into different types, characterized by cloud-top heights. The entrainment rates and moist static energy that is entrained or detrained are determined by analyzing the budget of moist static energy for each cloud type. Results show that the entrained air is a mixture of approximately equal amount of cloud air and environmental air, and the detrained air is a mixture of ~80 % of cloud air and 20 % of the air with saturation moist static energy at the environmental temperature. After taking into account the difference in moist static energy between the entrained air and the mean environment, the estimated fractional entrainment rate is much larger than those used in current convective parameterization schemes. High-resolution (100 m) large-eddy simulation of TWP-ICE convection was also analyzed to support the CRM results. It is shown that the characteristics of entrainment rates estimated using both the high-resolution data and CRM-resolution coarse-grained data are similar. For each cloud category, the entrainment rate is high near cloud base and top, but low in the middle of clouds. The entrainment rates are best fitted to the inverse of in-cloud vertical velocity by a second order polynomial.

Parameterization of the Spatial Variability of Rain for Large-Scale Models and Remote Sensing

AbstractThe spatial variability of rain rate R is evaluated by using both radar observations and cloud-resolving model output, focusing on the Tropical Warm Pool–International Cloud Experiment (TWP-ICE) period. In general, the model-predicted rain-rate probability distributions agree well with those estimated from the radar data across a wide range of spatial scales. The spatial variability in R, which is defined according to the standard deviation of R (for R greater than a predefined threshold Rmin) σ(R), is found to vary according to both the average of R over a given footprint μ(R) and the footprint size or averaging scale Δ. There is good agreement between area-averaged model output and radar data at a height of 2.5 km. The model output at the surface is used to construct a scale-dependent parameterization of σ(R) as a function of μ(R) and Δ that can be readily implemented into large-scale numerical models. The variability in both the rainwater mixing ratio qr and R as a function of height is also explored. From the statistical analysis, a scale- and height-dependent formulation for the spatial variability of both qr and R is provided for the analyzed tropical scenario. Last, it is shown how this parameterization can be used to assist in constraining parameters that are often used to describe the surface rain-rate distribution.

Dimensions and aspect ratios of natural ice crystals

Abstract. During the 2006 Tropical Warm Pool International Cloud Experiment (TWP-ICE) in the tropics, the 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC) in the Arctic, and the 2010 Small PARTicles In CirrUS (SPARTICUS) campaign at mid-latitudes, high-resolution images of ice crystals were recorded by a Cloud Particle Imager at temperatures (T) between −87 and 0 °C. The projected maximum dimension (D'), length (L'), and width (W') of pristine columns, plates, and component bullets of bullet rosettes were measured using newly developed software, the Ice Crystal Ruler. The number of bullets in each bullet rosette was also measured. Column crystals were further distinguished as either horizontally oriented columns or columns with other orientations to eliminate any orientation effect on the measured dimensions. The dimensions and aspect ratios (AR, the dimension of the major axis divided by the dimension of the minor axis) of crystals were determined as functions of temperature, geophysical location, and type of cirrus. Dimensions of crystals generally increased with temperature. Columns and bullets had larger dimensions (i.e., W') of the minor axis (i.e., a axis) for a given dimension (i.e., D' orL') of the major axis (i.e., c axis), and thus smaller AR, as T increased, whereas this trend did not occur for plate crystals. The average number of branches in bullet rosettes was 5.50 ± 1.35 during three campaigns and 6.32 ± 1.34 (5.46 ± 1.34; 4.95 ± 1.01) during TWP-ICE (SPARTICUS; ISDAC). The AR of bullets increased with the number of branches in bullet rosettes. Most dimensions of crystals and ARs of columnar crystals measured during SPARTICUS were larger than those measured during TWP-ICE and ISDAC at −67 < T < -35 °C and at −40 < T < −15 °C, respectively. The relative occurrence of varying pristine habits depended strongly on cirrus type (i.e., anvil or non-anvil clouds), with plates especially occurring more frequently in anvils. The L–W relationships of columns derived using current data exhibited a strong dependence on temperature; similar relationships determined in previous studies were within the range of the current data.

Self‐consistency tests of large‐scale dynamics parameterizations for single‐column modeling

AbstractLarge‐scale dynamics parameterizations are tested numerically in cloud‐resolving simulations, including a new version of the weak‐pressure‐gradient approximation (WPG) introduced by Edman and Romps (2014), the weak‐temperature‐gradient approximation (WTG), and a prior implementation of WPG. We perform a series of self‐consistency tests with each large‐scale dynamics parameterization, in which we compare the result of a cloud‐resolving simulation coupled to WTG or WPG with an otherwise identical simulation with prescribed large‐scale convergence. In self‐consistency tests based on radiative‐convective equilibrium (RCE; i.e., no large‐scale convergence), we find that simulations either weakly coupled or strongly coupled to either WPG or WTG are self‐consistent, but WPG‐coupled simulations exhibit a nonmonotonic behavior as the strength of the coupling to WPG is varied. We also perform self‐consistency tests based on observed forcings from two observational campaigns: the Tropical Warm Pool International Cloud Experiment (TWP‐ICE) and the ARM Southern Great Plains (SGP) Summer 1995 IOP. In these tests, we show that the new version of WPG improves upon prior versions of WPG by eliminating a potentially troublesome gravity‐wave resonance.

Evaluation of cloud‐resolving and limited area model intercomparison simulations using TWP‐ICE observations: 2. Precipitation microphysics

AbstractTen 3‐D cloud‐resolving model (CRM) simulations and four 3‐D limited area model (LAM) simulations of an intense mesoscale convective system observed on 23–24 January 2006 during the Tropical Warm Pool–International Cloud Experiment (TWP‐ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, colocated UHF and VHF vertical profilers, and a Joss‐Waldvogel disdrometer in an attempt to explain a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One‐moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rainwater contents (RWCs) that are similar to observed. Two‐moment rain schemes with a gamma shape parameter (μ) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one‐moment schemes but lower RWCs. Two‐moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and, thus, may have issues balancing raindrop formation, collision‐coalescence, and raindrop breakup. Assuming a μ of 2.5 rather than 0 for the raindrop size distribution improves one‐moment scheme biases, and allowing μ to have values greater than 0 may improve excessive size sorting in two‐moment schemes. Underpredicted stratiform rain rates are associated with underpredicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. A limited domain size also prevents a large, well‐developed stratiform region like the one observed from developing in CRMs, although LAMs also fail to produce such a region.

Evaluation of cloud‐resolving and limited area model intercomparison simulations using TWP‐ICE observations: 1. Deep convective updraft properties

AbstractTen 3‐D cloud‐resolving model simulations and four 3‐D limited area model simulations of an intense mesoscale convective system observed on 23–24 January 2006 during the Tropical Warm Pool‐International Cloud Experiment (TWP‐ICE) are compared with each other and with observed radar reflectivity fields and dual‐Doppler retrievals of vertical wind speeds in an attempt to explain published results showing a high bias in simulated convective radar reflectivity aloft. This high‐bias results from ice water content being large, which is a product of large, strong convective updrafts, although hydrometeor size distribution assumptions modulate the size of this bias. Making snow mass more realistically proportional to D2 rather than D3 eliminates unrealistically large snow reflectivities over 40 dBZ in some simulations. Graupel, unlike snow, produces high biased reflectivity in all simulations, which is partly a result of parameterized microphysics but also partly a result of overly intense simulated updrafts. Peak vertical velocities in deep convective updrafts are greater than dual‐Doppler‐retrieved values, especially in the upper troposphere. Freezing of liquid condensate, often rain, lofted above the freezing level in simulated updraft cores greatly contributes to these excessive upper tropospheric vertical velocities. The strongest simulated updraft cores are nearly undiluted, with some of the strongest showing supercell characteristics during the multicellular (presquall) stage of the event. Decreasing horizontal grid spacing from 900 to 100 m slightly weakens deep updraft vertical velocity and moderately decreases the amount of condensate aloft but not enough to match observational retrievals. Therefore, overly intense simulated updrafts may additionally be a product of unrealistic interactions between convective dynamics, parameterized microphysics, and large‐scale model forcing that promote different convective strengths than observed.

Convectively generated gravity waves simulated by NAM‐SCA

AbstractConvectively generated gravity waves are an unresolved process in global models. However, parameterization of their effects is difficult because the parameterized wave spectrum must be linked to the convective source, which is itself parameterized. Here we use the NAM‐SCA model (nonhydrostatic anelastic model with segmentally constant approximation), which is midway between a cloud‐resolving model and convection parameterization. Unlike conventional convection parameterizations, NAM‐SCA is built directly upon a nonhydrostatic anelastic model, and thus it describes dynamical processes consistently but in a “compressed” manner (i.e., with truncation via a spatiotemporal adaptive mesh) that facilitates its potential use as a parameterization. As a result, under the dynamical framework of NAM‐SCA, convection generates a spectrum of gravity waves in a physically consistent manner without any additional assumptions or simplifications. The present study examines the capacity of NAM‐SCA for generating gravity waves from convection under varying degree of “compression” and assesses its viability as a physically consistent convective gravity wave source parameterization. By taking the TWP‐ICE (Tropical Warm Pool‐International Cloud Experiment) period for the case study, NAM‐SCA successfully represents the convectively generated gravity waves even down to the compression rate of 0.1. Analysis in the wave number frequency space shows that the compression behaves as a weak low‐pass filter in wave number, but higher‐frequency components generated by dynamic adaptation partially compensate the filtering effect making the net Reynolds stress relatively insensitive to compression.

Gravity waves generated by convection during TWP‐ICE: 2. High‐frequency gravity waves

AbstractHigh‐frequency gravity waves are analyzed using radiosonde soundings taken during the Tropical Warm Pool‐International Cloud Experiment (TWP‐ICE). The intrinsic periods of these waves are estimated to be between 10 and 50 min. The high‐frequency wave activity in the stratosphere, defined by mass‐weighted variance of the vertical motion of the sonde, has a maximum following the afternoon local convection indicating that these waves are generated by local convection. The wave activity is the strongest in the lower stratosphere below 22 km and, during the suppressed monsoon period, is modulated with a 3–4 day period. The concentration of the wave activity in the lower stratosphere is consistent with the properties of the environment in which these waves propagate, whereas its 3–4 day modulation is explained by the variation of the convection activity in the TWP‐ICE domain. For shallow convection, the wave activity has a weak tendency to increase as the rainfall intensity increases. The wave activity associated with deep convection, which typically occurs at high rainfall intensities, is larger and has more spread than that associated with shallow convection.

Gravity waves generated by convection during TWP‐ICE: I. Inertia‐gravity waves

AbstractGravity waves are analyzed in radiosonde soundings taken during the Tropical Warm Pool‐International Cloud Experiment (TWP‐ICE) campaign. The properties of the inertia‐gravity waves are analyzed in Part I, whereas Part II focuses on high‐frequency gravity waves. Two groups of inertia‐gravity waves are detected: group L (Long vertical wavelength) in the middle stratosphere during the suppressed monsoon period and group S (Short vertical wavelength) in the lower stratosphere during the monsoon break period. Waves belonging to group L propagate to the southeast with a mean intrinsic period of 35 h and have vertical and horizontal wavelengths of about 5–6 km and 3000–6000 km, respectively. Ray‐tracing calculations indicate that these waves originate from a deep convective region near Indonesia. Waves belonging to group S propagate to the south‐southeast with an intrinsic period, vertical wavelength, and horizontal wavelength of about 45 h, 2 km, and 2000–4000 km, respectively. These waves appear to originate from convection in the vicinity of New Guinea.

Ground‐based observations of overshooting convection during the Tropical Warm Pool‐International Cloud Experiment

This study uses gridded radar data to investigate the properties of deep convective storms that penetrate the tropical tropopause layer (TTL) and overshoot the cold‐point tropopause during the Tropical Warm Pool‐International Cloud Experiment (TWP‐ICE). Overshooting convection during the observed break period is relatively more intense and exhibits lesser diurnal variability than severe monsoonal storms in terms of mean overshooting area in the TTL (as covered by >20 dBZ echoes). However, ground‐based radar has geometrical constraints and sampling gaps at high altitude that lead to biases in the final radar product. Using synthetic observations derived from model‐based data, ground‐based radar is shown to underestimate the mean overshooting area in the TTL across both TWP‐ICE regimes. Differences range from ∼180 km2 (∼100 km2) to ∼14 km2 (∼8 km2) between 14 and 18 km for the active (break) period. This implies that the radar is underestimating the transport of water and ice mass into the TTL by convective overshoots during TWP‐ICE. The synthetic data is also used to correct profiles of the mean observed overshooting area. These are shown to differ only marginally between the two sampled regimes once the influence of a large mesoscale convective system, considered as a departure from normal monsoon behavior, was removed from the statistics. The results of our study provide a useful cross‐validation comparison for satellite‐based detections of overshooting top areas over Darwin, Australia.

Response of Tropical Deep Convection to Localized Heating Perturbations: Implications for Aerosol-Induced Convective Invigoration

Abstract A cloud-system-resolving model is used to investigate the effects of localized heating/cooling perturbations on tropical deep convection, in the context of the aerosol “invigoration effect.” This effect supposes that a reduction of droplet collision–coalescence in polluted conditions leads to lofting of cloud water in convective updrafts and enhanced freezing, latent heating, and buoyancy. To specifically isolate and test this mechanism, heating perturbations were applied to updrafts with corresponding cooling applied in downdrafts. Ensemble simulations were run with either perturbed or unperturbed conditions and large-scale forcing from a 7.5-day period of active monsoon conditions during the 2006 Tropical Warm Pool–International Cloud Experiment. In the perturbed simulations there was an initial invigoration of convective updrafts and surface precipitation, but convection returned to its unperturbed state after about 24 h because of feedback with the larger-scale environment. This feedback led to an increase in the horizontally averaged mid-/upper-tropospheric temperature of about 1 K relative to unperturbed simulations. When perturbed conditions were applied to only part of the domain, gravity waves rapidly dispersed buoyancy anomalies in the perturbed region to the rest of the domain, allowing convective invigoration from the heating perturbations to be sustained over the entire simulation period. This was associated with a mean mesoscale circulation consisting of ascent (descent) at mid-/upper levels in the perturbed (unperturbed) region. In contrast to recent studies, it is concluded that the invigoration effect is intimately coupled with larger-scale dynamics through a two-way feedback, and in the absence of alterations in the larger-scale circulation there is limited invigoration beyond the convective adjustment time scale.

Statistics of Storm Updraft Velocities from TWP-ICE Including Verification with Profiling Measurements

AbstractComparisons between direct measurements and modeled values of vertical air motions in precipitating systems are complicated by differences in temporal and spatial scales. On one hand, vertically profiling radars more directly measure the vertical air motion but do not adequately capture full storm dynamics. On the other hand, vertical air motions retrieved from two or more scanning Doppler radars capture the full storm dynamics but require model constraints that may not capture all updraft features because of inadequate sampling, resolution, numerical constraints, and the fact that the storm is evolving as it is scanned by the radars. To investigate the veracity of radar-based retrievals, which can be used to verify numerically modeled vertical air motions, this article presents several case studies from storm events around Darwin, Northern Territory, Australia, in which measurements from a dual-frequency radar profiler system and volumetric radar-based wind retrievals are compared. While a direct comparison was not possible because of instrumentation location, an indirect comparison shows promising results, with volume retrievals comparing well to those obtained from the profiling system. This prompted a statistical analysis of an extended period of an active monsoon period during the Tropical Warm Pool International Cloud Experiment (TWP-ICE). Results show less vigorous deep convective cores with maximum updraft velocities occurring at lower heights than some cloud-resolving modeling studies suggest.

A single‐column model ensemble approach applied to the TWP‐ICE experiment

Single‐column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large‐scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large‐scale data for the Tropical Warm Pool International Cloud Experiment (TWP‐ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud‐resolving models (CRM). Best estimate simulations are also performed. All models show that moisture‐related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only.

A Comparison of the Water Budgets between Clouds from AMMA and TWP-ICE

AbstractTwo field campaigns, the African Monsoon Multidisciplinary Analysis (AMMA) and the Tropical Warm Pool–International Cloud Experiment (TWP-ICE), took place in 2006 near Niamey, Niger, and Darwin, Northern Territory, Australia, providing extensive observations of mesoscale convective systems (MCSs) near a desert and a tropical coast, respectively. Under the constraint of their observations, three-dimensional cloud-resolving model simulations are carried out and presented in this paper to replicate the basic characteristics of the observed MCSs. All of the modeled MCSs exhibit a distinct structure having deep convective clouds accompanied by stratiform and anvil clouds. In contrast to the approximately 100-km-scale MCSs observed in TWP-ICE, the MCSs in AMMA have been successfully simulated with a scale of about 400 km.These modeled AMMA and TWP-ICE MCSs offer an opportunity to understand the structure and mechanism of MCSs. Comparing the water budgets between AMMA and TWP-ICE MCSs suggests that TWP-ICE convective clouds have stronger ascent while the mesoscale ascent outside convective clouds in AMMA is stronger. A case comparison, with the aid of sensitivity experiments, also suggests that vertical wind shear and ice crystal (or dust aerosol) concentration can significantly impact stratiform and anvil clouds (e.g., their areas) in MCSs. In addition, the obtained water budgets quantitatively describe the transport of water between convective, stratiform, and anvil regions as well as water sources/sinks from microphysical processes, providing information that can be used to help determine parameters in the convective and cloud parameterizations in general circulation models (GCMs).