Cloud Ice Number Concentration Research Articles

Implementation of Prognostic Cloud Ice Number Concentrations for the Weather Research and Forecasting (WRF) Double‐Moment 6‐Class (WDM6) Microphysics Scheme

AbstractThe ice microphysical processes in the Weather Research and Forecasting (WRF) Double‐Moment 6‐class (WDM6) microphysics scheme are treated as a single‐moment approach, in which the number concentration of cloud ice is diagnosed based on its mixing ratio. This study develops the revised WDM6 scheme through the implementation of prognostic cloud ice number concentrations. The effect of the prognostic number concentration on the simulated precipitation is verified through simulations of short‐term winter snowfall cases during International Collaborative Experiments for the Pyeongchang 2018 Olympics and Paralympics (ICE‐POP 2018) winter games and a 1‐month regional climate case during the summer season, July 2009. For all cases, the revised WDM6 simulates higher cloud ice number concentrations and lower cloud ice mixing ratios than the original WDM6. The microphysics budget analysis for the snowfall cases shows that the inefficient deposition and vapor freezing nucleation processes of cloud ice reduce the available cloud ice mixing ratio. Consequently, the accretion processes with cloud ice decrease and the deposition into snow increases due to the surplus water vapor. The revised WDM6 alleviates the positive bias of surface precipitation consisting of snow over the region where the original WDM6 simulates excessive precipitation, compared to the observed data. For the regional climate case, the reduced cloud ice amount strengthens the Western North Pacific high‐pressure system by allowing more solar radiation to reach the surface, leading to simulated precipitation bands and synoptic environments that are more comparable with the observed data.

Improvements of the Double-Moment Bulk Cloud Microphysics Scheme in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM)

Abstract This study revises the collisional growth, heterogeneous ice nucleation, and homogeneous ice nucleation processes in a double-moment bulk cloud microphysics scheme implemented in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM). The revised cloud microphysical processes are tested by 10-day global simulations with a horizontal resolution of 14 km. It is found that both the aggregation of cloud ice with smaller diameters and the graupel production by riming are overestimated in the current schemes. A new method that numerically integrates the collection kernel solves this issue, and consequently, the lifetime of cloud ice is reasonably extended in reference to satellite observations. In addition, the results indicate that a reduction in graupel modulates the convective intensity, particularly in intense rainfall systems. The revision of both heterogeneous and homogeneous ice nucleation significantly increases the production rate of cloud ice number concentration. With these revisions, the new version of the cloud microphysics scheme successfully improves outgoing longwave radiation, particularly over the intertropical convergence zone, in reference to satellite observations. Therefore, the revisions are beneficial for both long-term climate simulations and representing the structure of severe storms. Significance Statement Very high-resolution global atmospheric models have been developed to simultaneously address global climate and regional weather. In general, cloud microphysics schemes used in such global models are introduced from regional weather forecasting models to realistically represent mesoscale cloud systems. However, a cloud microphysics scheme that was originally developed with the aim of weather forecasting can cause unexpected errors in global climate simulations because such a cloud microphysics scheme is not designed for interdisciplinary usage across spatiotemporal scales. This study focuses on systematic model biases in evaluating the terminal velocity of ice cloud particles and proposes a method to accurately calculate the growth rate of ice cloud particles. Improvements in ice cloud modeling successfully reduce model biases in the global energy budget. In addition, the internal structure of intense rainfall systems is modified using the new cloud model. Therefore, improvements in ice cloud modeling could further increase the reliability of weather forecasting, seasonal prediction, and climate projection.

Code for JAMES publication - Implementation of prognostic cloud ice number concentrations for the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme.

Code for JAMES publication - Implementation of prognostic cloud ice number concentrations for the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme.

Code for JAMES publication - Implementation of prognostic cloud ice number concentrations for the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme.

Code for JAMES publication - Implementation of prognostic cloud ice number concentrations for the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme.

Dependence of the effect of aerosols on cirrus clouds on background vertical velocity

Cirrus clouds cover approximately 20–25% of the globe and thus play an important role in the Earth's radiation budget. This important role in the radiation budget played by cirrus clouds indicates that aerosol effects on cirrus clouds can have a substantial impact on the variation of global radiative forcing if the ice–water path (IWP) changes. This study examines the aerosol indirect effect (AIE) through changes in the IWP for cirrus cloud cases. This study also examines the dependence of aerosol–cloud interactions in cirrus clouds on the large-scale vertical motion. We use a cloud-system resolving model (CSRM) coupled with a double-moment representation of cloud microphysics.Intensified interactions among the cloud ice number concentration (CINC), deposition and dynamics play a critical role in the IWP increases due to aerosol increases from the preindustrial (PI) level to the present-day (PD) level with a low large-scale vertical velocity. Increased aerosols lead to an increased CINC, providing an increased surface area for water vapor deposition. The increased surface area leads to increased deposition despite decreased supersaturation with increasing aerosols. The increased deposition causes an increased depositional heating which produces stronger updrafts, and these stronger updrafts lead to the increased IWP. However, with a high large-scale vertical velocity, the effect of increased CINC on deposition was not able to offset the effect of decreasing supersaturation with increasing aerosols. The effect of decreasing supersaturation on deposition dominant over that of increasing CINC leads to smaller deposition and IWP at high aerosol with the PD aerosol than at low aerosol with the PI aerosol.The conversion of ice crystals to aggregates through autoconversion and accretion plays a negligible role in the IWP responses to aerosols, as does the sedimentation of aggregates. The sedimentation of ice crystals plays a more important role in the IWP response to aerosol increases than the sedimentation of aggregates, but, not more important than the interactions among the CINC, supersaturation, deposition and dynamics. These interactions not only determine the effect of aerosols on IWP but also control how this effect varies with varying large-scale vertical velocities.

Aerosol effects on ice clouds: can the traditional concept of aerosol indirect effects be applied to aerosol-cloud interactions in cirrus clouds?

Abstract. Cirrus clouds cover approximately 20–25% of the globe and thus play an important role in the Earth's radiation budget. Therefore the effect of aerosols on cirrus clouds can have a substantial impact on global radiative forcing if either the ice-water path (IWP) and/or the cloud ice number concentration (CINC) changes. This study examines the aerosol indirect effect (AIE) through changes in the CINC and IWP for a cirrus cloud case. We use a cloud-system resolving model (CSRM) coupled with a double-moment representation of cloud microphysics. Intensified interactions among CINC, deposition and dynamics play a critical role in increasing the IWP as aerosols increase. Increased IWP leads to a smaller change in the outgoing LW radiation relative to that for the SW radiation for increasing aerosols. Increased aerosols lead to increased CINC, providing increased surface area for water vapor deposition. The increased deposition causes depositional heating which produces stronger updrafts, and leads to the increased IWP. The conversion of ice crystals to aggregates through autoconversion and accretion plays a negligible role in the IWP response to aerosols, and the sedimentation of aggregates is negligible. The sedimentation of ice crystals plays a more important role in the IWP response to aerosol increases than the sedimentation of aggregates, but not more than the interactions among the CINC, deposition and dynamics.

Relationships of Biomass-Burning Aerosols to Ice in Orographic Wave Clouds

Abstract Ice concentrations in orographic wave clouds at temperatures between −24° and −29°C were shown to be related to aerosol characteristics in nearby clear air during five research flights over the Rocky Mountains. When clouds with influence from colder temperatures were excluded from the dataset, mean ice nuclei and cloud ice number concentrations were very low, on the order of 1–5 L−1. In this environment, ice number concentrations were found to be significantly correlated with the number concentration of larger particles, those larger than both 0.1- and 0.5-μm diameter. A variety of complementary techniques was used to measure aerosol size distributions and chemical composition. Strong correlations were also observed between ice concentrations and the number concentrations of soot and biomass-burning aerosols. Ice nuclei concentrations directly measured in biomass-burning plumes were the highest detected during the project. Taken together, this evidence indicates a potential role for biomass-burning aerosols in ice formation, particularly in regions with relatively low concentrations of other ice nucleating aerosols.

Ice nuclei characteristics from M-PACE and their relation to ice formation in clouds

This paper presents airborne measurements of ice nuclei (IN) number concentration and elemental composition from the mixed-phase Arctic cloud experiment (M-PACE) in northern Alaska during October 2004. Although the project average IN concentration was low, less than 1 L -1 STP, there was significant spatial and temporal variability, with local maximum concentrations of nearly 60 L -1 STP. Immersion and/or condensation freezing appear to be the dominant freezing mechanisms, whereas mechanisms that occur below water saturation played a smaller role. The dominant particle types identified as IN were metal oxides/dust (39%), carbonaceous particles (35%) and mixtures of metal oxides/dust with either carbonaceous components or salts/sulphates (25%), although there was significant variability in elemental composition. Trajectory analysis suggests both local and remote sources, including biomass burning and volcanic ash. Seasonal variability of IN number concentrations based on this study and data from SHEBA/FIRE-ACE indicates that fall concentrations are depleted relative to spring by about a factor of five. Average IN number concentrations from both studies compare favorably with cloud ice number concentrations of cloud particles larger than 125 μ m, for temperatures less than −10 °C. Cloud ice number concentrations also were enhanced in spring, by a factor of ∼2, but only over a limited temperature range. DOI: 10.1111/j.1600-0889.2009.00415.x

Ice nuclei characteristics from M-PACE and their relation to ice formation in clouds

This paper presents airborne measurements of ice nuclei (IN) number concentration and elemental composition from the mixed-phase Arctic cloud experiment (M-PACE) in northern Alaska during October 2004. Although the project average IN concentration was low, less than 1 L-1 STP, there was significant spatial and temporal variability, with local maximum concentrations of nearly 60 L-1 STP. Immersion and/or condensation freezing appear to be the dominant freezing mechanisms, whereas mechanisms that occur below water saturation played a smaller role. The dominant particle types identified as IN were metal oxides/dust (39%), carbonaceous particles (35%) and mixtures of metal oxides/dust with either carbonaceous components or salts/sulphates (25%), although there was significant variability in elemental composition. Trajectory analysis suggests both local and remote sources, including biomass burning and volcanic ash. Seasonal variability of IN number concentrations based on this study and data from SHEBA/FIREACE indicates that fall concentrations are depleted relative to spring by about a factor of five. Average IN number concentrations from both studies compare favorably with cloud ice number concentrations of cloud particles larger than 125 μm, for temperatures less than -10°C. Cloud ice number concentrations also were enhanced in spring, by a factor of ˜2, but only over a limited temperature range.

Simulations of Arctic mixed‐phase clouds in forecasts with CAM3 and AM2 for M‐PACE

Simulations of mixed‐phase clouds in forecasts with the NCAR Atmosphere Model version 3 (CAM3) and the GFDL Atmospheric Model version 2 (AM2) for the Mixed‐Phase Arctic Cloud Experiment (M‐PACE) are performed using analysis data from numerical weather prediction centers. CAM3 significantly underestimates the observed boundary layer mixed‐phase cloud fraction and cannot realistically simulate the variations of liquid water fraction with temperature and cloud height due to its oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer cloud fraction while its clouds contain much less cloud condensate than CAM3 and the observations. The simulation of the boundary layer mixed‐phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used (CAM3LIU). The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes. Sensitivity tests show that these results are not sensitive to the analysis data used for model initialization. Increasing model horizontal resolution helps capture the subgrid‐scale features in Arctic frontal clouds but does not help improve the simulation of the single‐layer boundary layer clouds. AM2 simulated cloud fraction and LWP are sensitive to the change in cloud ice number concentrations used in the Wegener‐Bergeron‐Findeisen process while CAM3LIU only shows moderate sensitivity in its cloud fields to this change. This paper shows that the Wegener‐Bergeron‐Findeisen process is important for these models to correctly simulate the observed features of mixed‐phase clouds.

Assessment of the dehydration‐greenhouse feedback over the Arctic during February 1990

AbstractThe effect of pollution‐derived sulfuric acid aerosols on the aerosol‐cloud‐radiation interactions is investigated over the Arctic for February 1990. Observations suggest that acidic aerosols can decrease the heterogeneous nucleation rate of ice crystals and lower the homogeneous freezing temperature of haze droplets. On the basis of these observations, we hypothesize that the cloud thermodynamic phase is modified in polluted air mass (Arctic haze). Cloud ice number concentration is reduced, thus promoting further ice crystal growth by the Bergeron–Findeisen process. Hence, ice crystals reach larger sizes and low‐levkel ice crystal precipitation from mixed‐phase clouds increases. Enhanced dehydration of the lower troposphere contributes to decreased water vapour greenhouse effect and cools the surface. A positive feedback is created between surface cooling and air dehydration, accelerating cold air production. This process is referred to as the dehydration‐greenhouse feedback (DGF).Simulations performed using an Arctic regional climate model for February 1990 are used to assess the potential effect of the DGF on the Arctic climate during February. Results show that the DGF has an important effect on cloud, atmospheric dehydration, and temperature over the Central and Eurasian Arctic, which is the coldest part of the Arctic. Cloud ice is significantly reduced and the total atmospheric water path is decreased by as much as 12%. This results in a surface cooling ranging between 0 and − 3 K. Moreover, the lower tropospheric cooling over the Eurasian and Central Arctic strengthens the atmospheric circulation at the upper level, thus increasing the aerosol transport from the mid‐latitudes and enhancing the DGF. Over warmer areas, the increased aerosol concentration (caused by the DGF) leads to longer cloud lifetime, which contributes to warm these areas. Copyright © 2006 Royal Meteorological Society

A New Double-Moment Microphysics Parameterization for Application in Cloud and Climate Models. Part II: Single-Column Modeling of Arctic Clouds

Abstract The new double-moment microphysics scheme described in Part I of this paper is implemented into a single-column model to simulate clouds and radiation observed during the period 1 April–15 May 1998 of the Surface Heat Budget of the Arctic (SHEBA) and First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment–Arctic Clouds Experiment (FIRE–ACE) field projects. Mean predicted cloud boundaries and total cloud fraction compare reasonably well with observations. Cloud phase partitioning, which is crucial in determining the surface radiative fluxes, is fairly similar to ground-based retrievals. However, the fraction of time that liquid is present in the column is somewhat underpredicted, leading to small biases in the downwelling shortwave and longwave radiative fluxes at the surface. Results using the new scheme are compared to parallel simulations using other microphysics parameterizations of varying complexity. The predicted liquid water path and cloud phase is significantly improved using the new scheme relative to a single-moment parameterization predicting only the mixing ratio of the water species. Results indicate that a realistic treatment of cloud ice number concentration (prognosing rather than diagnosing) is needed to simulate arctic clouds. Sensitivity tests are also performed by varying the aerosol size, solubility, and number concentration to explore potential cloud–aerosol–radiation interactions in arctic stratus.