Ice Fall Speed Research Articles

Assessment of a Microphysical Ensemble Used to Investigate the OWLeS IOP4 Lake-Effect Storm

AbstractMicrophysical processes within mixed-phase convective clouds can have cascading impacts on cloud properties and resultant precipitation. This paper investigates the role of microphysics in the lake-effect storm (LES) observed during intensive observing period 4 of the Ontario Winter Lake-effect Systems field campaign. A microphysical ensemble is composed of 24 simulations that differ in the microphysics scheme used (e.g., Weather Research and Forecasting Model microphysics options or a choice of two bulk adaptive habit models) along with changes in the representation of aerosol and potential ice nuclei concentrations, ice nucleation parameterizations, rain and ice fall speeds, spectral indices, ice habit assumptions, and the number of moments used for modeling ice-phase hydrometeors in each adaptive habit model. Each of these changes to microphysics resulted in varied precipitation types at the surface; 15 members forecast a mixture of snow, ice, and graupel, 7 members forecast only snow and ice, and the remaining 2 members forecast a combination of snow, ice, graupel, and rain. Observations from an optical disdrometer positioned to the south of the LES core indicate that 92% of the observed particles were snow and ice, 5% were graupel, and 3% were rain and drizzle. Analysis of observations spanning more than a point location, such as polarimetric radar observations and aircraft measurements of liquid water content, provides insight into cloud composition and processes leading to the differences at the surface. Ensemble spread is controlled by hydrometeor type differences spurred by processes or parameters (e.g., ice fall speed) that affect graupel mass.

Microphysical properties and fall speed measurements of snow ice crystals using the Dual Ice Crystal Imager (D-ICI)

Abstract. Accurate predictions of snowfall require good knowledge of the microphysical properties of the snow ice crystals and particles. Shape is an important parameter as it strongly influences the scattering properties of the ice particles, and thus their response to remote sensing techniques such as radar measurements. The fall speed of ice particles is another important parameter for both numerical forecast models as well as representation of ice clouds and snow in climate models, as it is responsible for the rate of removal of ice from these models. We describe a new ground-based in situ instrument, the Dual Ice Crystal Imager (D-ICI), to determine snow ice crystal properties and fall speed simultaneously. The instrument takes two high-resolution pictures of the same falling ice particle from two different viewing directions. Both cameras use a microscope-like setup resulting in an image pixel resolution of approximately 4 µm pixel−1. One viewing direction is horizontal and is used to determine fall speed by means of a double exposure. For this purpose, two bright flashes of a light-emitting diode behind the camera illuminate the falling ice particle and create this double exposure, and the vertical displacement of the particle provides its fall speed. The other viewing direction is close-to-vertical and is used to provide size and shape information from single-exposure images. This viewing geometry is chosen instead of a horizontal one because shape and size of ice particles as viewed in the vertical direction are more relevant than these properties viewed horizontally, as the vertical fall speed is more strongly influenced by the vertically viewed properties. In addition, a comparison with remote sensing instruments that mostly have a vertical or close-to-vertical viewing geometry is favoured when the particle properties are measured in the same direction. The instrument has been tested in Kiruna, northern Sweden (67.8∘ N, 20.4∘ E). Measurements are demonstrated with images from different snow events, and the determined snow ice crystal properties are presented.

Impact of Cloud Ice Particle Size Uncertainty in a Climate Model and Implications for Future Satellite Missions

AbstractIce particle size is pivotal to determining ice cloud radiative effect and precipitating rate. However, there is a lack of accurate ice particle effective radius (Rei) observation on the global scale to constrain its representation in climate models. In support of future mission design, here we present a modeling assessment of the sensitivity of climate simulations to Rei and quantify the impact of the proposed mission concept on reducing the uncertainty in climate sensitivity. We perturb the parameters pertaining to ice fall speed parameter and Rei in radiation scheme, respectively, in National Center for Atmospheric Research CESM1 model with a slab ocean configuration. The model sensitivity experiments show that a settling velocity increase due to a larger Rei results in a longwave cooling dominating over a shortwave warming, a global mean surface temperature decrease, and precipitation suppression. A similar competition between longwave and shortwave cloud forcing changes also exists when perturbing Rei in the radiation scheme. Linearity generally holds for the climate response for Rei related parameters. When perturbing falling snow particle size (Res) in a similar way, we find much less sensitivity of climate responses. Our quadrupling CO2 experiments with different parameter settings reveal that Rei and Res can account for changes in climate sensitivity significantly from +12.3% to −6.2%. By reducing the uncertainty ranges of Rei and Res from a factor of 2 to ±25%, a future satellite mission under design is expected to improve the climate state simulations and reduce the climate sensitivity uncertainty pertaining to ice particle size by approximately 60%. Our results highlight the importance of better observational constraints on Rei by satellite missions.

The Relative Impact of Ice Fall Speeds and Microphysics Parameterization Complexity on Supercell Evolution

Abstract The use of bin or bulk microphysics schemes in model simulations frequently produces large changes in the simulated storm and precipitation characteristics, but it is still unclear which aspects of these schemes give rise to these changes. In this study, supercell simulations using either a bin or a double-moment bulk microphysics scheme are conducted with the Regional Atmospheric Modeling System (RAMS). The two simulations produce very different storm morphologies. An additional simulation is run for each scheme in which the diameter–fall speed relationships for ice hydrometeors are modified to be similar to those used by the other scheme. When fall speed relationships are homogenized, the two parameterization schemes simulate similar storm morphology. Therefore, despite the use of largely dissimilar approaches to parameterizing microphysics, the difference in storm morphology is found to be related to the choice of diameter–fall speed relationships for ice hydrometeors. This result is investigated further to understand why. Higher fall speeds lead to higher mixing ratios of hydrometeors at low levels and thus more melting. Consequently, stronger downdrafts and cold pools exist in the high fall speed storms, and these stronger cold pools lead to storm splitting and the intensification of a left mover. The results point to the importance of hydrometeor fall speed on the evolution of supercells. It is also suggested that caution be used when comparing the response of a cloud model to different classes of microphysics schemes since the assumptions made by the schemes may be more important than the scheme class itself.

Insensitivity of the Cloud Response to Surface Warming Under Radical Changes to Boundary Layer Turbulence and Cloud Microphysics: Results From the Ultraparameterized CAM

AbstractWe study the cloud response to a +4K surface warming in a new multiscale climate model that uses enough interior resolution to begin explicitly resolving boundary layer turbulence (i.e., ultraparameterization or UP). UP's predictions are compared against those from standard superparameterization (SP). The mean cloud radiative effect feedback turns out to be remarkably neutral across all of our simulations, despite some radical changes in both cloud microphysical parameter settings and cloud‐resolving model grid resolution. The overall low cloud response to warming is a positive low cloud feedback over land, a negative feedback (driven by cloud optical depth increase) at high latitudes, and weak feedback over the low‐latitude oceans. The most distinct effects of UP result from tuning decisions impacting high‐latitude cloud feedback. UP's microphysics is tuned to optimize the model present‐day, top‐of‐atmosphere radiation fluxes against CERES observations, by lowering the cloud ice‐liquid phase shift temperature ramp, adjusting the ice/liquid autoconversion rate, and increasing the ice fall speed. This reduces high‐latitude low cloud amounts and damps the optical depth feedback at high latitudes, leading to a slightly more positive global cloud feedback compared to SP. A sensitivity test that isolates these microphysical impacts from UP's grid resolution confirms that the microphysical settings are mostly responsible for the differences between SP and UP cloud feedback.

Modified NAM Microphysics for Forecasts of Deep Convective Storms

Abstract The Ferrier–Aligo (FA) microphysics scheme has been running operationally in the National Centers for Environmental Prediction (NCEP) North American Mesoscale Forecast System (NAM) since August 2014. It was developed to improve forecasts of deep convection in the NAM contiguous United States (CONUS) nest, and it replaces previous versions of the NAM microphysics. The FA scheme is the culmination of extensive microphysical scheme sensitivity experiments made over nearly a dozen warm- and cool-season severe weather cases, as well as an extensive real-time testing in a full, system-wide developmental version of the NAM. While the FA scheme advects each hydrometeor species separately, it was the mass-weighted rime factor (RF) that allowed rimed ice to be advected to very cold temperatures aloft and improved the vertical structure of deep convection. Rimed ice fall speeds were reduced in order to offset an increase in bias of heavy precipitation as a consequence of the mass-weighted RF advection. The FA scheme also incorporated findings from 3-km model runs using the Thompson scheme, including 1) improved closure assumptions for large precipitating ice that targeted the convective and anvil regions of storms, 2) a new diagnostic calculation of radar reflectivity from rimed ice in association with intense convection, and 3) a variable rain intercept parameter that reduced widespread spurious weak reflectivity from shallow boundary layer clouds and increased stratiform rainfall.

Sensitivity of summer ensembles of fledgling superparameterized U.S. mesoscale convective systems to cloud resolving model microphysics and grid configuration

AbstractThe sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global‐scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger‐scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS‐like events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP‐CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS‐like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five‐summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one‐moment and two‐moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP‐GCMs. These results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.

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.

Quantitative Sensitivity Analysis of Physical Parameterizations for Cases of Deep Convection in the NASA GEOS-5

Abstract Parameterization of processes that occur on length scales too small to resolve on a computational grid is a major source of uncertainty in global climate models. This study investigates the relative importance of a number of parameters used in the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model, focusing on cloud, convection, and boundary layer parameterizations. Latin hypercube sampling is used to generate a few hundred sets of 19 candidate physics parameters, which are subsequently used to generate ensembles of single-column model realizations of cloud content, precipitation, and radiative fluxes for four different field campaigns. A Gaussian process model is then used to create a computationally inexpensive emulator for the simulation code that can be used to determine a measure of relative parameter sensitivity by sampling the response surface for a very large number of input parameter sets. Parameter sensitivities are computed for different geographic locations and seasons to determine whether the intrinsic sensitivity of the model parameterizations changes with season and location. The results indicate the same subset of parameters collectively control the model output across all experiments, independent of changes in the environment. These are the threshold relative humidity for cloud formation, the ice fall speeds, convective and large-scale autoconversion, deep convection relaxation time scale, maximum convective updraft diameter, and minimum ice effective radius. However, there are differences in the degree of parameter sensitivity between continental and tropical convective cases, as well as systematic changes in the degree of parameter influence and parameter–parameter interaction.

Perturbed physics ensemble simulations of cirrus on the cloud system‐resolving scale

In this study, the effect of uncertainties in the parameterization of ice microphysical processes and initial conditions on the variability of cirrus microphysical and radiative properties are investigated in a series of cloud system‐resolving perturbed physics ensemble (PPE) and initial condition ensemble (ICE) simulations. Three cirrus cases representative of midlatitude, subtropical, and tropical anvil cirrus are examined. The variability in cirrus properties induced by perturbing uncertain parameters in ice microphysics parameterizations outweighs the variability induced by perturbing the initial conditions in midlatitude and subtropical cirrus. However, in tropical anvil cirrus the variability spanned by the PPE and ICE simulations is on the same order of magnitude. Uncertainties in the parameterization of ice microphysical processes affect the vertical distribution of cloud fraction, ice water content, and cloud thickness, whereas cirrus cloud cover is only marginally affected. The top three uncertainties controlling the microphysical variability and radiative impact of cirrus clouds are the mode of ice nucleation, the number concentrations of ice nuclei available for heterogeneous freezing, and the threshold size of the parameterized ice autoconversion process. Uncertainties in ice fall speeds are of minor importance. Changes in the ice deposition coefficient induce only transient effects on the microphysical properties and radiative impacts of cirrus except in cases of very low ice deposition coefficients of about 0.05. Changes in the sulfate aerosol number concentration available for homogeneous freezing have virtually no effect on the microphysical properties and radiative impact of midlatitude and subtropical cirrus but a minor effect on tropical anvil cirrus.

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.

Ice Cloud Particle Size Distributions and Pressure-Dependent Terminal Velocities from In Situ Observations at Temperatures from 0° to −86°C

Abstract The primary goal of this study is to derive ice particle terminal velocities from micron to centimeter sizes and for atmospheric pressures covering the range 200–1000 hPa from data spanning a wide range of locations, temperatures, and altitudes and to parameterize the results for use in cloud through cloud models. The study uses data from 10 field programs spanning the temperature range −86° to 0°C and encompassing a total of about 800 000 km of cloud horizontal pathlengths and includes measurements of ice particle size distributions (PSDs) and direct measurements of the ice water content (IWC). The necessary ice particle variables are derived using variables that are interconnected rather than varying independently from observations reported in the literature. A secondary goal of the study is to quantify the properties of ice cloud particle ensembles over a wide range of temperatures to further the understanding of how ice particle ensembles and ice clouds develop. Functional forms for the PSDs and mass– and area–dimensional relationships are developed from the observations and summarized in a table. The PSDs are found to be nearly exponential at temperatures from about −40° to −10°C although deviations from exponentiality are noted outside of this range. It is demonstrated that previous pressure-dependent corrections to ice fall speeds lead to overestimated terminal velocities for particles smaller than 1 mm, particularly so for sizes below 100 μm, with consequent effects on modeled lifetimes of cold ice clouds.

Evaluation of clouds in ACCESS using the satellite simulator package COSP: Global, seasonal, and regional cloud properties

Cloud properties from the Australian Community Climate and Earth System Simulator (ACCESS1.3) are evaluated using the Cloud Feedback Model Intercomparison Project (CFMIP) Observational Simulator Package (COSP). CloudSat, CALIPSO, and International Satellite Cloud Climatology Project (ISCCP) observations are used to evaluate the modeled cloud cover, condensate properties, and cloud optical depths for two seasons. The global distribution of cloud in the model is generally well represented with maximum high cloud in the tropics and low cloud over the eastern edges of the ocean basins. The model captures the observed position of the midlatitude storm track clouds and the modeled cloud top heights compare well with the observations in the upper troposphere. However, there is a lack of modeled midlevel cloud in the tropics and midlatitudes. The average high cloud cover in the Tropical Warm Pool region shows good agreement with CALIPSO. However, the modeled radar reflectivities and lidar scattering ratios are biased toward lower values, suggesting that the ice water contents and particles sizes of these clouds in the model are too small. Over the Southern Ocean the modeled cloud cover is underestimated due to a lack of mid‐ and low‐level cloud. The low clouds over the Southern Ocean and the California stratocumulus clouds in the model have too little condensate and optical thickness and too much rain and drizzle. A sensitivity experiment showed that reducing the ice fall speeds improves aspects of the modeled cloud properties by increasing the frequency of occurrence of high clouds with large scattering ratios and optically thick low clouds. ACCESS1.3 has a reasonable representation of cloud. However, the underestimate of ice water content and particles sizes in high clouds and the too frequent occurrence of drizzle may impact the modeled cloud feedbacks and regional precipitation associated with current and perturbed climates.

A FIRE-ACE/SHEBA Case Study of Mixed-Phase Arctic Boundary Layer Clouds: Entrainment Rate Limitations on Rapid Primary Ice Nucleation Processes

Abstract Observations of long-lived mixed-phase Arctic boundary layer clouds on 7 May 1998 during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)–Arctic Cloud Experiment (ACE)/Surface Heat Budget of the Arctic Ocean (SHEBA) campaign provide a unique opportunity to test understanding of cloud ice formation. Under the microphysically simple conditions observed (apparently negligible ice aggregation, sublimation, and multiplication), the only expected source of new ice crystals is activation of heterogeneous ice nuclei (IN) and the only sink is sedimentation. Large-eddy simulations with size-resolved microphysics are initialized with IN number concentration NIN measured above cloud top, but details of IN activation behavior are unknown. If activated rapidly (in deposition, condensation, or immersion modes), as commonly assumed, IN are depleted from the well-mixed boundary layer within minutes. Quasi-equilibrium ice number concentration Ni is then limited to a small fraction of overlying NIN that is determined by the cloud-top entrainment rate we divided by the number-weighted ice fall speed at the surface υf. Because wc < 1 cm s−1 and υf > 10 cm s−1, Ni/NIN ≪ 1. Such conditions may be common for this cloud type, which has implications for modeling IN diagnostically, interpreting measurements, and quantifying sensitivity to increasing NIN (when we/υf < 1, entrainment rate limitations serve to buffer cloud system response). To reproduce observed ice crystal size distributions and cloud radar reflectivities with rapidly consumed IN in this case, the measured above-cloud NIN must be multiplied by approximately 30. However, results are sensitive to assumed ice crystal properties not constrained by measurements. In addition, simulations do not reproduce the pronounced mesoscale heterogeneity in radar reflectivity that is observed.

Assessing the performance of a prognostic and a diagnostic cloud scheme using single column model simulations of TWP–ICE

AbstractSingle column model simulations using the UK Met Office Unified Model, as used in the Australian Community Climate Earth System Simulator, are presented for the Tropical Warm Pool–International Cloud Experiment (TWP–ICE) field study. Two formulations for the representation of clouds are compared with the extensive observations taken during the campaign, giving insight into the ability of the model to simulate tropical cloud systems. During the active monsoon phase the modelled cloud cover has a stronger dependence on relative humidity than the observations. Observed ice cloud properties during the suppressed monsoon period show that the ice water content is significantly underestimated in the simulations. The profiles of modelled ice fall speeds are faster than those observed in the levels above 12 km, implying that the observations have smaller sized particles in larger concentrations than the models. Both simulations show similar errors in the diurnal cycle of relative humidity during the active monsoon phase, suggesting that the error is less sensitive to the choice of cloud scheme and rather is driven by the convection scheme. However, during the times of suppressed convection the relative humidity error is different between the simulations, with congestus convection drying the environment too much, particularly in the prognostic cloud‐scheme simulation. This result shows that the choice of cloud scheme and the way that the cloud and convection schemes interact plays a role in the temperature and moisture errors during the suppressed monsoon phase, which will impact the three‐dimensional model simulations of tropical variability. Copyright © 2011 Royal Meteorological Society

Reducing the Biases in Simulated Radar Reflectivities from a Bulk Microphysics Scheme: Tropical Convective Systems

Abstract A well-known bias common to many bulk microphysics schemes currently being used in cloud-resolving models is the tendency to produce excessively large reflectivity values (e.g., 40 dBZ) in the middle and upper troposphere in simulated convective systems. The Rutledge and Hobbs–based bulk microphysics scheme in the Goddard Cumulus Ensemble model is modified to reduce this bias and improve realistic aspects. Modifications include lowering the efficiencies for snow/graupel riming and snow accreting cloud ice; converting less rimed snow to graupel; allowing snow/graupel sublimation; adding rime splintering, immersion freezing, and contact nucleation; replacing the Fletcher formulation for activated ice nuclei with that of Meyers et al.; allowing for ice supersaturation in the saturation adjustment; accounting for ambient RH in the growth of cloud ice to snow; and adding/accounting for cloud ice fall speeds. In addition, size-mapping schemes for snow/graupel were added as functions of temperature and mixing ratio, lowering particle sizes at colder temperatures but allowing larger particles near the melting level and at higher mixing ratios. The modifications were applied to a weakly organized continental case and an oceanic mesoscale convective system (MCS). Strong echoes in the middle and upper troposphere were reduced in both cases. Peak reflectivities agreed well with radar for the weaker land case but, despite improvement, remained too high for the MCS. Reflectivity distributions versus height were much improved versus radar for the less organized land case but not for the MCS despite fewer excessively strong echoes aloft due to a bias toward weaker echoes at storm top.

Representing the ice fall speed in climate models: Results from Tropical Composition, Cloud and Climate Coupling (TC4) and the Indirect and Semi-Direct Aerosol Campaign (ISDAC)

[1] Ice fall velocity has a strong impact on climate feedback, influencing cirrus cloud coverage and radiative forcing as well as upper troposphere relative humidity. This study aims to provide the atmospheric modeling community with better parameterizations of the ice fall speed in cirrus clouds on the basis of aircraft measurements from recent field campaigns, especially the Tropical Composition, Cloud and Climate Coupling (TC4) campaign in 2007 and the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in 2008. These campaigns provide improved measurements of the ice particle size distribution (PSD) where the concentrations of artifact small ice particles (due to shattering of ice particles on the probe inlet tube) are greatly reduced. In addition to the PSD, the mass-weighted fall velocity (Vm) depends on the ice particle projected area and mass. The calculation of Vm was based on improved direct measurements of the PSD number and area concentration and improved estimates of ice particle mass. The effective diameter (De) was calculated in a similar way. The TC4 analysis has provided a diagnostic relationship that relates Vm to both cloud temperature (T) and ice water content (IWC) with an r2 of 0.78. A similar relationship for De was also obtained with an r2 of 0.82. The Vm relationship and associated Vm-IWC-T measurements were found to agree well with a Vm scheme based on T and cloud radar retrievals of Vm and IWC in tropical cirrus clouds. However, a critical climate-influencing parameter like the ice fall speed needs to be coupled with the cloud microphysics and radiation in climate models. This is made possible through strong correlations between De and Vm regarding TC4 and ISDAC cirrus. Finally, TC4 satellite retrievals of De and Vm are found to be consistent with corresponding observations.

Parameterization of Riming Intensity and Its Impact on Ice Fall Speed Using ARM Data

Abstract Riming within mixed-phase clouds can have a large impact on the prediction of clouds and precipitation within weather and climate models. The increase of ice particle fall speed due to riming has not been considered in most general circulation models (GCMs), and many weather models only consider ice particles that are either unrimed or heavily rimed (not a continuum of riming amount). Using the Atmospheric Radiation Measurement (ARM) Program dataset at the Southern Great Plains (SGP) site of the United States, a new parameterization for riming is derived, which includes a diagnosed rimed mass fraction and its impact on the ice particle fall speed. When evaluated against a vertical-pointing Doppler radar for stratiform mixed-phase clouds, the new parameterization produces better ice fall speeds than a conventional parameterization. The new parameterization is tested in the recently developed Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model (AM3) using prescribed sea surface temperature (SST) simulations. Compared with the standard (CTL) simulation, the new parameterization increases ice amount aloft by ∼20%–30% globally, which reduces the global mean outgoing longwave radiation (OLR) by ∼2.8 W m−2 and the top-of-atmosphere (TOA) shortwave absorption by ∼1.5 W m−2. Global mean precipitation is also slightly reduced, especially over the tropics. Overall, the new parameterization produces a comparable climatology with the CTL simulation and it improves the physical basis for using a fall velocity larger than a conventional parameterization in the current AM3.

Climate feedbacks determined using radiative kernels in a multi-thousand member ensemble of AOGCMs

The use of radiative kernels to diagnose climate feedbacks is a recent development that may be applied to existing climate change simulations. We apply the radiative kernel technique to transient simulations from a multi-thousand member perturbed physics ensemble of coupled atmosphere-ocean general circulation models, comparing distributions of model feedbacks with those taken from the CMIP-3 multi GCM ensemble. Although the range of clear sky longwave feedbacks in the perturbed physics ensemble is similar to that seen in the multi-GCM ensemble, the kernel technique underestimates the net clear-sky feedbacks (or the radiative forcing) in some perturbed models with significantly altered humidity distributions. In addition, the compensating relationship between global mean atmospheric lapse rate feedback and water vapor feedback is found to hold in the perturbed physics ensemble, but large differences in relative humidity distributions in the ensemble prevent the compensation from holding at a regional scale. Both ensembles show a similar range of response of global mean net cloud feedback, but the mean of the perturbed physics ensemble is shifted towards more positive values such that none of the perturbed models exhibit a net negative cloud feedback. The perturbed physics ensemble contains fewer models with strong negative shortwave cloud feedbacks and has stronger compensating positive longwave feedbacks. A principal component analysis used to identify dominant modes of feedback variation reveals that the perturbed physics ensemble produces very different modes of climate response to the multi-model ensemble, suggesting that one may not be used as an analog for the other in estimates of uncertainty in future response. Whereas in the multi-model ensemble, the first order variation in cloud feedbacks shows compensation between longwave and shortwave components, in the perturbed physics ensemble the shortwave feedbacks are uncompensated, possibly explaining the larger range of climate sensitivities observed in the perturbed simulations. Regression analysis suggests that the parameters governing cloud formation, convection strength and ice fall speed are the most significant in altering climate feedbacks. Perturbations of oceanic and sulfur cycle parameters have relatively little effect on the atmospheric feedbacks diagnosed by the kernel technique.

Radar reflectivity as a proxy for convective mass transport

More observations of vertical mass transport in deep convection are needed to improve dynamical understanding of detrainment processes and for verification of transport models. A methodology for using radar reflectivity as a direct observation of vertical transport of mass from the boundary layer to the upper troposphere and lower stratosphere is investigated, and the “level of maximum detrainment” (LMD) is proposed. The case investigated is the 26 January 1999 squall line from the Tropical Rainfall Measuring Mission Large‐Scale Biosphere‐Atmosphere field campaign. Echo top heights and dual‐Doppler derived divergence profiles are used to define the mass detrainment range. Over 10% of anvil echo tops occurred above the sounding‐derived level of neutral buoyancy of 15.4 km during the mature stage of the storm, and convective tops reached above 18 km. Anvil ice water content, with a simple correction for ice fall speed, is found to be a good proxy for both the LMD, which for the storm analyzed is 11.25 km, and for the detrainment range of 6 to 17 km. More cases need to be analyzed to confirm the strength of this methodology, but the case study presented shows a strong correlation between anvil properties determined from radar reflectivity and the mass detrainment profile. Thus, radar reflectivity can be used as an indicator of the LMD to test model convective and transport parameterizations.