Ice Microphysics Scheme Research Articles

Evaluating Ice Phase Microphysics in the Simulation of a Snowstorm Over Northern China

AbstractThe complexity of ice particles in the atmosphere makes it difficult to model microphysical growth processes accurately. In this study, we simulated a snowfall case over Northern China Plain using two different microphysics schemes, that is, Thompson and Morrison schemes, in the Advanced Research WRF (Weather Research and Forecasting) model. Both schemes are able to reproduce the event, albeit with a slightly weaker precipitation compared with the surface observation. However, the radar reflectivity factor in Morrison simulation is higher than the radar observation to ∼10 dBZ. Further analysis reveals that such stronger radar reflectivity in the Morrison simulation might be caused by larger collection efficiency, which would lead to more active self‐aggregation process in prediction of snow number concentration and then larger snow particle size. Sensitivity tests show that using an alternative formula of collection efficiency produces smaller radar reflectivity that is in better agreement with observations. This study highlights the accurate representation of self‐aggregation process and underscores the needs of further improvement of ice microphysics schemes for the better snowfall simulations.

Interactions between Gravity Waves and Cirrus Clouds: Asymptotic Modeling of Wave-Induced Ice Nucleation

Abstract We present an asymptotic approach for the systematic investigation of the effect of gravity waves (GWs) on ice clouds formed through homogeneous nucleation. In particular, we consider high- and midfrequency GWs in the tropopause region driving the formation of ice clouds, modeled with a double-moment bulk ice microphysics scheme. The asymptotic approach allows for identifying reduced equations for self-consistent description of the ice dynamics forced by GWs including the effects of diffusional growth and nucleation of ice crystals. Further, corresponding analytical solutions for a monochromatic GW are derived under a single-parcel approximation. The results provide a simple expression for the nucleated number of ice crystals in a nucleation event. It is demonstrated that the asymptotic solutions capture the dynamics of the full ice model and accurately predict the nucleated ice crystal number. The present approach is extended to allow for superposition of GWs, as well as for variable ice crystal mean mass in the deposition. Implications of the results for an improved representation of GW variability in cirrus parameterizations are discussed.

An application of the boundary element method (BEM) to the calculation of the single-scattering properties of very complex ice crystals in the microwave and sub-millimetre regions of the electromagnetic spectrum

To improve the prediction of weather and climate models there is a need for the accurate computation of the single-scattering properties of randomly oriented complex atmospheric ice crystals. Here, we apply BEM to calculate these properties in the microwave and sub-millimetre region of the electromagnetic spectrum for the purposes of all-sky data assimilation. The properties are calculated at the frequencies of 50, 183, 243 and 664 GHz for the temperatures of −83 °C, −43 °C, and −3 °C. The particles are assumed to be complex aggregates of bullet rosettes with maximum dimensions that vary between 10 and 10,000μm. Moreover, the rosette-aggregates are constructed to follow an observed mass-dimension power law that is consistent with an ice microphysics scheme in a weather model. To solve efficiently the BEM linear matrix equation, random orientation is simulated by fixing the particle with respect to the incident plane wave with the latter rotated about the particle. This representation is shown to replicate T-matrix solutions found for hexagonal columns to within a few percent for size parameters between 0.05 and 10. We further show that we can simulate the single-scattering properties with errors less than a few percent, using only 14 and up to 302 incident waves for the smallest and largest size parameters respectively. The errors grow larger only for some of the largest size parameters considered. We find that BEM can be applied to compute accurately the scattering properties of complex ice aggregates of importance to weather and climate models.

A Lagrangian Perspective of Microphysical Impact on Ice Cloud Evolution and Radiative Heating

AbstractWe generate trajectories in storm‐resolving simulations in order to quantify the effect of ice microphysics on tropical upper‐tropospheric cloud‐radiative heating. The pressure and flow field tracked along the trajectories are used to run different ice microphysical schemes, both one‐ and two‐moment formulations within the Icosahedral Non‐hydrostatic Model model and a separate offline box microphysics model (CLaMS‐Ice). This computational approach allows us to isolate purely microphysical differences in a variant of “microphysical piggybacking;” feedbacks of microphysics onto pressure and the flow field, for example, via latent heating, are suppressed. Despite these constraints, we find about a 5‐fold difference in median cloud ice mass mixing ratios (qi) and ice crystal number (Ni) between the microphysical schemes and very distinct qi distributions versus temperature and relative humidity with respect to ice along the trajectories. After investigating microphysical formulations for nucleation, depositional growth, and sedimentation, we propose three cirrus lifecycles: a weak source‐strong sink lifecycle whose longwave and shortwave heating are smallest due to short lifetime and low optical depth, a strong source‐weak sink lifecycle whose longwave and shortwave heating are largest due to long lifetime and high optical depth, and a strong source‐strong sink lifecycle with intermediate radiative properties.

Cirrus cloud thinning using a more physically based ice microphysics scheme in the ECHAM-HAM general circulation model

Abstract. Cirrus cloud thinning (CCT) is a relatively new radiation management proposal to counteract anthropogenic climate warming by targeting Earth's terrestrial radiation balance. The efficacy of this method was presented in several general circulation model (GCM) studies that showed widely varied radiative responses, originating in part from the differences in the representation of cirrus ice microphysics between the different GCMs. The recent implementation of a new, more physically based ice microphysics scheme (Predicted Particle Properties, P3) that abandons ice hydrometeor size class separation into the ECHAM-HAM GCM, coupled to a new approach for calculating cloud fractions that increases the relative humidity (RH) thresholds for cirrus cloud formation, motivated a reassessment of CCT efficacy. In this study, we first compared CCT sensitivity between the new cloud fraction approach and the original ECHAM-HAM cloud fraction approach. Consistent with previous approaches using ECHAM-HAM, with the P3 scheme and the higher RH thresholds for cirrus cloud formation, we do not find a significant cooling response in any of our simulations. The most notable response from our extreme case is the reduction in the maximum global-mean net top-of-atmosphere (TOA) radiative anomalies from overseeding by about 50 %, from 9.9 W m−2 with the original cloud fraction approach down to 4.9 W m−2 using the new cloud fraction RH thresholds that allow partial grid-box coverage of cirrus clouds above ice saturation, unlike the original approach. Even with this reduction with the updated cloud fraction approach, the TOA anomalies from overseeding far exceed those reported in previous studies. We attribute the large positive TOA anomalies to seeding particles overtaking both homogeneous nucleation and heterogeneous nucleation on mineral dust particles within cirrus clouds to produce more numerous and smaller ice crystals. This effect is amplified by longer ice residence times in clouds due to the slower removal of ice via sedimentation in the P3 scheme. In an effort to avoid this overtaking effect of seeding particles, we increased the default critical ice saturation ratio (Si,seed) for ice nucleation on seeding particles from the default value of 1.05 to 1.35 in a second sensitivity test. With the higher Si,seed we drastically reduce overseeding, which suggests that Si,seed is a key factor to consider for future CCT studies. However, the global-mean TOA anomalies contain high uncertainty. In response, we examined the TOA anomalies regionally and found that specific regions only show a small potential for targeted CCT, which is partially enhanced by using the larger Si,seed. Finally, in a seasonal analysis of TOA responses to CCT, we find that our results do not confirm the previous finding that high-latitude wintertime seeding is a feasible strategy to enhance CCT efficacy, as seeding in our model enhances the already positive cirrus longwave cloud radiative effect for most of our simulations. Our results also show feedbacks on lower-lying mixed-phase and liquid clouds through the reduction in ice crystal sedimentation that reduces cloud droplet depletion and results in stronger cloud albedo effects. However, this is outweighed by stronger longwave trapping from cirrus clouds with more numerous and smaller ice crystals. Therefore, we conclude that CCT is unlikely to act as a feasible climate intervention strategy on a global scale.

Ice microphysical processes exert a strong control on the simulated radiative energy budget in the tropics

Simulations of the global climate system at storm-resolving resolutions of 2 km are now becoming feasible and show promising realism in clouds and precipitation. However, shortcomings in their representation of microscale processes, like the interaction of cloud droplets and ice crystals with radiation, can still restrict their utility. Here, we illustrate how changes to the ice microphysics scheme dramatically alter both the vertical profile of cloud-radiative heating and top-of-atmosphere outgoing longwave radiation (terrestrial infrared cooling) in storm-resolving simulations over the Asian monsoon region. Poorly-constrained parameters in the ice nucleation scheme, overactive conversion of ice to snow, and inconsistent treatment of ice crystal effective radius between microphysics and radiation alter cloud-radiative heating by a factor of four and domain-mean infrared cooling by 30 W m−2. Vertical resolution, on the other hand, has a very limited impact. Even in state-of-the-art models then, uncertainties in microscale cloud properties exert a strong control on the radiative budget that propagates to both atmospheric circulation and regional climate. These uncertainties need to be reduced to realize the full potential of storm-resolving models.

How Does Riming Affect Dual‐Polarization Radar Observations and Snowflake Shape?

AbstractAs an ice particle grows by riming its shape is expected to change, resulting in a more spherical particle at the later stages of riming. This conceptual model is at the core of the current ice microphysical schemes and used for dual‐polarization radar observation based classification of hydrometeors. A quantitative relation between riming and shapes of snowflake aggregates, however, has not been established yet. This study aims to derive this relation by using surface‐based precipitation and coinciding dual‐polarization radar observations. The observations were collected during four winter seasons, 49 snowstorms, at University of Helsinki measurement station in Hyytiälä, Finland. Results show that relation between the differential reflectivity and reflectivity‐weighted rime mass fraction is not monotonic and depends on reflectivity‐weighted mean diameter. This behavior can be explained by the opposing effects of riming on dual‐polarization radar observations. Riming increases particle bulk density, which leads to more pronounced dual‐polarization radar signatures. As riming progresses the aspect ratio of snowflake increases slowly until the rime mass fraction value reaches a certainty value after which the aspect ratio increases more rapidly. Finally, coutilization of Ze, Zdr, and Kdp for inferring riming fraction is analyzed.

Evaluation of Cloud Microphysical Schemes for a Warm Frontal Snowband during the GPM Cold Season Precipitation Experiment (GCPEx)

Detailed observations from the Global Precipitation Measurement (GPM) mission Cold Season Precipitation Experiment (GCPEx) of an intense warm frontal band on 18 February 2012 were used to evaluate several bulk microphysical parameterizations within the NASA-Unified Weather Research and Forecasting (NU-WRF) Model. These included the Predicted Particle Properties (P3), Morrison (MORR), Stony Brook University (SBU), and Goddard four-class ice (4ICE) microphysics schemes. All schemes were able to predict the snowband, but the simulated intensities varied because of various assumptions in these schemes. The saturation adjustment scheme within MORR promoted excessive amounts of cloud water evaporational cooling in the warm sector, which contributed to a decrease in midlevel instability approaching the frontal band and thus a weaker band. In contrast, the explicit calculation of cloud water condensation/evaporation in the P3 scheme produced limited amounts of evaporational cooling, which allowed for greater midlevel instability to support band development. The P3 and SBU schemes produced moderate rime/graupel mass within the band that was confirmed by observations, while the MORR and 4ICE schemes drastically underpredicted the graupel mass. The high-density, fast-falling rimed particles in P3 underwent weak sublimation and melting, which helped promote a stronger horizontal temperature gradient and greater low-level instability along the frontal band compared to the other schemes. Overall, the schemes that use specified thresholds for converting between the predefined ice-phase categories of cloud ice, snow, and graupel had the most unrepresentative hydrometeor types. These results highlight the advantage of predicting ice particle properties and explicitly calculating cloud water condensation/evaporation in the P3 scheme.

Evaluating the Effect of Physics Schemes in WRF Simulations of Summer Rainfall in North West Iran

The numerical weather forecast model Weather Research and Forecasting (WRF) has a range of applications because it offers multiple physical options, enabling the users to optimizing WRF for specific scales, geographical locations and applications. Summer rainfall cannot be predicted well in North West of Iran (NWI). Most of them are convective. Sometimes rainfall is heavy, so that it causes flash flood. In this research, some configurations of WRF were tested with four summer rainfall events in NWI to find the best configuration. Five cumulus, four planetary boundary layers (PBL) and two microphysical schemes were combined. Twenty-six different configurations (models) were implemented at two resolutions of 5 and 15 km for duration of 48 h. Four events, with over 20 mm convective daily rainfall total, were selected at NWI during summer season between 2010 and 2015. These events were tested by developing 26 unique models. Results were verified using several methods. The aim was to find the best results during the first 24 h. Although no single configuration can be introduced for all times, thresholds, and atmospheric system to provide reliable and accurate forecast, the best configuration for WRF can be identified. Kain-Fritsch (new Eta), Betts-Miller-Janjic, Modified Kain-Fritsch, Multi-scale Kain-Fritsch and newer Tiedtke cumulus schemes and Mellor-Yamada-Janjic, Shin-Hong ‘scale-aware’, Medium Range Forecast (MRF) and Yonsei University (YSU) Planetary Boundary Layer schemes and Kessler, WRF Single Moment 3 class simple ice (WSM3) microphysics schemes were selected. The result show that Cumulus schemes are the most sensitive and Microphysics schemes are the less sensitive. The comparison of 15 km and 5 km resolution simulations do not show obvious advantages in downscaling the results. Configuration with newer Tiedtke cumulus, Mellor-Yamada-Janjic PBL, WSM3 and Kessler microphysics schemes give the best results for the 5 and 15 km resolutions. The output image of models and statistical methods verification indexes show that WRF could not accurately simulate convective rainfall in the NWI in summer.

Performance of the Goddard multiscale modeling framework with Goddard ice microphysical schemes

AbstractThe multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud‐resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM‐based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long‐term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one‐moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four‐class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three‐class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long‐term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size‐mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.

Insights into low-latitude cloud feedbacks from high-resolution models.

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: 'thermodynamic' cloudiness reduction from warming of the atmosphere-ocean column, 'radiative' cloudiness reduction from CO2- and H2O-induced increase in atmospheric emissivity aloft, 'stability-induced' cloud increase from increased lower tropospheric stratification, and 'dynamical' cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes.

Identifying sensitivities for cirrus modelling using a two-moment two-mode bulk microphysics scheme

Cirrus cloud genesis is an inherently multiscale and non-linear problem. The synoptic scale provides the environment, the mesoscale determines the forcing and the actual nucleation events occur on a microscopic scale. This makes the parameterisation in numerical weather prediction models a challenging task. In order to improve the prediction of cirrus clouds and ice supersaturation formation in the German Weather Service (DWD) model chain, the controlling physical processes are investigated and parameterised in a new cloud ice microphysics scheme. The new scheme is an extended version of the ice-microphysical scheme operational in the numerical weather prediction models of DWD. The developed two-moment two-mode cloud ice scheme includes state-of-the-art parameterisations for the two main processes for ice formation, namely homogeneous and heterogeneous nucleation. Homogeneous freezing of supercooled liquid aerosols is triggered in regions with high atmospheric ice supersaturations (145–160%) and high cooling rates. Atmospheric small-scale fluctuations are accounted for by use of the turbulent kinetic energy. Heterogeneous nucleation depends mostly on the existence of ice nuclei in the atmosphere and occurs primarily at lower ice supersaturations. Thus, heterogeneously nucleated ice crystals deplete ice supersaturation via depositional growth and can therefore inhibit subsequent homogeneous freezing. The new cloud ice scheme accounts for pre-existing ice crystals, contains a prognostic budget variable for activated ice nuclei and includes cloud ice sedimentation. Furthermore, a consistent treatment of the depositional growth of the two-ice particle modes and the larger snowflakes is applied by using a relaxation time scale method which ensures a physical representation for depleting ice supersaturation. The new cloud ice scheme is used to identify the relative roles of heterogeneous and homogeneous nucleation in the formation of cirrus clouds and ice supersaturation. A parcel model is used in order to investigate the differences between the operational and new cloud ice scheme. The time scales for the homogeneous nucleation event and for the depositional growth are emphasised. The importance of the new ice nucleation scheme is demonstrated by conducting idealised simulations of orographic cirrus in the COSMO (Consortium for Small-Scale Modeling) model environment.

Parameterization of ice fall speeds in midlatitude cirrus: Results from SPartICus

AbstractThe climate sensitivity predicted in general circulation models can be sensitive to the treatment of the ice particle fall velocity. In this study, the mass‐weighted ice fall speed (Vm) and the number concentration ice fall speed (Vn) in midlatitude cirrus clouds are computed from in situ measurements of ice particle area and number concentration made by the two‐dimensional stereo probe during the Small Particles In Cirrus field campaign. For single‐moment ice microphysical schemes, Vm and the ice particle size distribution effective diameter De were parameterized in terms of cloud temperature (T) and ice water content (IWC). For two‐moment schemes, Vm and Vn were related to De and the mean maximum dimension¯D, respectively. For single‐moment schemes, although the correlations of Vm and De with T were higher than the correlations of Vm and De with IWC, it is demonstrated that Vm and De are better predicted by using both T and IWC. The parameterization relating Vm to T and IWC is compared with another scheme relating Vm to T and IWC, with the latter based on millimeter cloud radar measurements. Regarding two‐moment ice microphysical schemes, a strong correlation was found between De and Vm and between¯D and Vn owing to their similar weightings by ice particle mass and number concentration, respectively. Estimating Vm from De makes Vm a function of IWC and projected area, realistically coupling Vm with both the cloud microphysics and radiative properties.

The effective density of small ice particles obtained from in situ aircraft observations of mid‐latitude cirrus

AbstractThe effective ice‐particle density, parametrized through a mass–dimension relation, is widely used in ice microphysical schemes for weather and climate models. In this study, we use aircraft‐based observations in mid‐latitude cirrus taken during the Constrain field programme in 2010. The low temperatures and a humidity often close to ice saturation meant that the typical ice particles observed were small (maximum dimension 20–800 µm) and ice water contents were low (0.001–0.05 g m−3). Two new instruments are included in this study: the Small Ice Detector Mark‐2 (SID‐2) and the deep‐cone Nevzorov Total Water Content probe. SID‐2 is a new single‐particle light‐scattering instrument and was used to identify and size small ice particles (10–150 µm). The deep‐cone Nevzorov probe is shown to be able to collect small ice masses with sufficient sensitivity. The focus of this article is on the effective density of small ice particles (both pristine ice crystals and small aggregates up to 600 µm maximum dimension). Due to instrument limitations in previous studies, the effective density of small ice particles is questionable.Aircraft flights in six cirrus cases provided ice‐particle measurements throughout the depth of the cirrus. The particle size distribution (PSD) was mostly bimodal. The smaller ice‐crystal mode dominated the PSD near cloud top and the larger ice‐aggregate mode dominated near cloud base. A mass–dimension relation valid for both ice crystals and aggregates was found that provided a best fit to the observations. For small ice particles (less than 70 µm diameter) the density is constant (700 kg m−3), while for larger ice crystals or aggregates the mass–dimension relation is m(D) = 0.0257D2.0. These measurements allow testing of the diagnostic split between ice crystals and aggregates used in the Met Office Unified Model.

Impact of the Environmental Low-Level Wind Profile on Ensemble Forecasts of the 4 May 2007 Greensburg, Kansas, Tornadic Storm and Associated Mesocyclones

The early tornadic phase of the Greensburg, Kansas, supercell on the evening of 4 May 2007 is simulated using a set of storm-scale (1-km horizontal grid spacing) 30-member ensemble Kalman filter (EnKF) data assimilation and forecast experiments. The Next Generation Weather Radar (NEXRAD) level-II radar data from the Dodge City, Kansas (KDDC), Weather Surveillance Radar-1988 Doppler (WSR-88D) are assimilated into the National Severe Storms Laboratory (NSSL) Collaborative Model for Multiscale Atmospheric Simulation (COMMAS). The initially horizontally homogeneous environments are initialized from one of three reconstructed soundings representative of the early tornadic phase of the storm, when a low-level jet (LLJ) was intensifying. To isolate the impact of the low-level wind profile, 0–3.5-km AGL wind profiles from Vance Air Force Base, Oklahoma (KVNX), WSR-88D velocity-azimuth display (VAD) analyses at 0130, 0200, and 0230 UTC are used. A sophisticated, double-moment bulk ice microphysics scheme is employed. For each of the three soundings, ensemble forecast experiments are initiated from EnKF analyses at various times prior to and shortly after the genesis of the Greensburg tornado (0200 UTC). Probabilistic forecasts of the mesocyclone-scale circulation(s) are generated and compared to the observed Greensburg tornado track. Probabilistic measures of significant rotation and observation-space diagnostic statistics are also calculated. It is shown that, in general, the track of the Greensburg tornado is well predicted, and forecasts improve as forecast lead time decreases. Significant variability is also seen across the experiments using different VAD wind profiles. Implications of these results regarding the choice of initial mesoscale environment, as well as for the “Warn-on-Forecast” paradigm for probabilistic numerical prediction of severe thunderstorms and tornadoes, are discussed.

Indirect Impact of Atmospheric Aerosols in Idealized Simulations of Convective–Radiative Quasi Equilibrium. Part II: Double-Moment Microphysics

AbstractThis paper extends the previous cloud-resolving modeling study concerning the impact of cloud microphysics on convective–radiative quasi equilibrium (CRQE) over a surface with fixed characteristics and prescribed solar input, both mimicking the mean conditions on earth. The current study applies sophisticated double-moment warm-rain and ice microphysics schemes, which allow for a significantly more realistic representation of the impact of aerosols on precipitation processes and on the coupling between clouds and radiative transfer. Two contrasting cloud condensation nuclei (CCN) characteristics are assumed, representing pristine and polluted conditions, as well as contrasting representations of the effects of entrainment and mixing on the mean cloud droplet size. In addition, four sets of sensitivity simulations are also performed with changes that provide a reference for the main simulation set.As in the previous study, the CRQE mimics the estimates of globally and annually averaged water and energy fluxes across the earth’s atmosphere. There are some differences from the previous study, however, consistent with the slightly lower water vapor content in the troposphere and significantly reduced lower-tropospheric cloud fraction in current simulations. There is also a significant reduction of the difference between the pristine and polluted cases, from ∼20 to ∼4 W m−2 at the surface from ∼20 to ∼9 W m−2 at the top of the atmosphere (TOA). The difference between the homogeneous and extremely inhomogeneous mixing scenarios, ∼20 W m−2 in the previous study, is reduced to a mere 2 (1) W m−2 at the surface (TOA). An unexpected difference between the previous and current simulations is the lower Bowen ratio of the surface heat flux, the partitioning of the total flux into sensible and latent components. It is shown that most of the change comes from the difference in the representation of rain evaporation in the subcloud layer in the single- and double-moment microphysics schemes. The difference affects the mean air temperature and humidity near the surface, and thus the Bowen ratio. The differences between the various simulations are discussed, contrasting the process-level approach with the impact of cloud microphysics on the quasi-equilibrium state with a more appropriate system dynamics approach. The key distinction is that the latter includes the interactions among all the processes in the modeled system.

Exploring the Land–Ocean Contrast in Convective Vigor Using Islands

Abstract Moist convection is well known to be generally more intense over continental than maritime regions, with larger updraft velocities, graupel, and lightning production. This study explores the transition from maritime to continental convection by comparing the trends in Tropical Rainfall Measuring Mission (TRMM) radar and microwave (37 and 85 GHz) observations over islands of increasing size to those simulated by a cloud-resolving model. The observed storms were essentially maritime over islands of <100 km2 and continental over islands >10 000 km2, with a gradual transition in between. Equivalent radar and microwave quantities were simulated from cloud-resolving runs of the Weather Research and Forecasting model via offline radiation codes. The model configuration was idealized, with islands represented by regions of uniform surface heat flux without orography, using a range of initial sounding conditions without strong horizontal winds or aerosols. Simulated storm strength varied with initial sounding, as expected, but also increased sharply with island size in a manner similar to observations. Stronger simulated storms were associated with higher concentrations of large hydrometeors. Although biases varied with different ice microphysical schemes, the trend was similar for all three schemes tested and was also seen in 2D and 3D model configurations. The successful reproduction of the trend with such idealized forcing supports previous suggestions that mesoscale variation in surface heating—rather than any difference in humidity, aerosol, or other aspects of the atmospheric state—is the main reason that convection is more intense over continents and large islands than over oceans. Some dynamical storm aspects, notably the peak rainfall and minimum surface pressure low, were more sensitive to surface forcing than to the atmospheric sounding or ice scheme. Large hydrometeor concentrations and simulated microwave and radar signatures, however, were at least as sensitive to initial humidity levels as to surface forcing and were more sensitive to the ice scheme. Issues with running the TRMM simulator on 2D simulations are discussed, but they appear to be less serious than sensitivities to model microphysics, which were similar in 2D and 3D. This supports the further use of 2D simulations to economically explore modeling uncertainties.

Cirrus clouds triggered by radiation, a multiscale phenomenon

Abstract. In this study, the influence of radiative cooling and small eddies on cirrus formation is investigated. For this purpose the non-hydrostatic, anelastic model EULAG is used with a recently developed and validated ice microphysics scheme (Spichtinger and Gierens, 2009a). Additionally, we implemented a fast radiative transfer code (Fu et al., 1998). Using idealized profiles with high ice supersaturations up to 144% and weakly stable stratifications with Brunt-Vaisala frequencies down to 0.0018 s−1 within a supersaturated layer, the influence of radiation on the formation of cirrus clouds is remarkable. Due to the radiative cooling at the top of the ice supersaturated layer with cooling rates down to −3.5 K/d, the stability inside the ice supersaturated layer decreases with time. During destabilization, small eddies induced by Gaussian temperature fluctuations start to grow and trigger first nucleation. These first nucleation events then induce the growth of convective cells due to the radiative destabilization. The effects of increasing the local relative humidity by cooling due to radiation and adiabatic lifting lead to the formation of a cirrus cloud with IWC up to 33 mg/m3 and mean optical depths up to 0.36. In a more stable environment, radiative cooling is not strong enough to destabilize the supersaturated layer within 8 h; no nucleation occurs in this case. Overall triggering of cirrus clouds via radiation works only if the supersaturated layer is destabilized by radiative cooling such that small eddies can grow in amplitude and finally initialize ice nucleation. Both processes on different scales, small-scale eddies and large-scale radiative cooling are necessary.

An Improved Representation of Rimed Snow and Conversion to Graupel in a Multicomponent Bin Microphysics Scheme

Abstract This paper describes the development of a new multicomponent detailed bin ice microphysics scheme that predicts the number concentration of ice as well as the rime mass mixing ratio in each mass bin. This allows for local prediction of the rime mass fraction. In this approach, the ice particle mass size, projected area size, and terminal velocity–size relationships vary as a function of particle mass and rimed mass fraction, based on a simple conceptual model of rime accumulation in the crystal interstices that leads to an increase in particle mass, but not in its maximum size, until a complete “filling in” with rime and conversion to graupel occurs. This approach allows a natural representation of the gradual transition from unrimed crystals to rimed crystals and graupel during riming. The new ice scheme is coupled with a detailed bin representation of the liquid hydrometeors and applied in an idealized 2D kinematic flow model representing the evolution of a mixed-phase precipitating cumulus. Results using the bin scheme are compared with simulations using a two-moment bulk scheme employing the same approach (i.e., separate prediction of bulk ice mixing ratio from vapor deposition and riming, allowing for local prediction of bulk rime mass fraction). The bin and bulk schemes produce similar results in terms of ice and liquid water paths and optical depths, as well as the timing of the onset and peak surface precipitation rate. However, the peak domain-average surface precipitation rate produced by the bulk scheme is about 4 times that in the bin simulation. The bin scheme is also compared with simulations that assume the ice particles consist entirely of either unrimed snow or graupel. While overall results are fairly similar, the onset and timing of the peak domain-average surface precipitation rate are substantially delayed in the simulations that treat the ice particles as either unrimed snow or graupel. These results suggest the importance of representing different ice types, including partially rimed crystals, for this case.

The impact of atmospheric aerosols on precipitation from deep organized convection: A prescribed-flow model study using double-moment bulk microphysics

This note discusses the results of numerical simulations in which a prescribed-flow model is merged with a double-moment warm-rain and ice microphysics scheme to investigate the impact of microphysical processes on precipitation from deep organized convection. The prescribed two-dimensional flow mimics an idealized squall line, with a narrow region of strong convective updraft and much wider region of weak stratiform updraft overlaying a stratiform downdraft. To cover the broad range of conditions that are possible for a squall line as well as to explore precipitation dependence on different parameters, 25 pairs of simulations are performed. Simulated cases differ in the dynamics (e.g. changing the updraft strength or large-scale shear), thermodynamics (e.g. changing the inflow sounding) or microphysics (e.g. changing the collision efficiencies). Each pair features cloud condensation nuclei (CCN) in either a pristine or polluted environment. Total surface precipitation and partitioning between convective and stratiform precipitation in each pair appears to be almost the same, with the difference being typically a few tenths of 1%. However, the dynamical and thermodynamical parameters do affect the precipitation significantly. It follows that the surface precipitation from organized convection can differ between pristine and polluted environments only through the feedback of CCN on cloud dynamics. In this feedback, small differences in the latent heating for the same flow pattern lead to different flow patterns in subsequent squall-line evolution. Details of this feedback need to be investigated using a dynamical model. Copyright © 2009 Royal Meteorological Society