Autoconversion Threshold Research Articles

The Role of Cloud-Radiative Interaction in Tropical Circulation and the Madden–Julian Oscillation

Abstract Cloud-radiative interaction (CRI) is a fundamental process that modulates tropical circulation and intraseasonal variability, including the Madden–Julian oscillation (MJO). In this study, we investigate how the mean state of the tropical atmosphere and the MJO respond to CRI intensity changes and provide insights into the underlying mechanisms, using the aquaplanet configuration in the Community Earth System Model, version 2 (CESM2). By enhancing CRI through tuning the DCS parameter (an autoconversion threshold size in the Morrison and Gettelman cloud microphysics scheme), we demonstrate that DCS-induced CRI intensification is linked to a warmer troposphere, increased tropical moisture, strengthened Hadley cell (HC), stronger trade winds, and a stronger equatorward intertropical convergence zone (ITCZ) with more clouds and precipitation, reflecting stronger cloud–radiation–circulation feedback. The intensified CRI also leads to the intensification and slower propagation of the simulated MJO-like mode despite the MJO-like signals becoming less distinguishable from the background due to the influence of other waves. The MJO intensification is likely associated with the mean state changes that support the development of deep convection. Moreover, the CRI itself, especially the interaction with the longwave radiation, also directly influences the MJO’s maintenance and propagation, more contributing to the maintenance of column moist static energy (MSE) and deceleration of its eastward propagation on intraseasonal time scales.

ВЛИЯНИЕ СИЛЬНОГО АЭРОЗОЛЬНОГО ЗАГРЯЗНЕНИЯ ВОЗДУХА НА ЭВОЛЮЦИЮ КОНВЕКТИВНЫХ ОБЛАКОВ ВО ВРЕМЯ ГРОЗЫ В КИТАЕ ПО РЕЗУЛЬТАТАМ ТРЕХМЕРНОГО ЧИСЛЕННОГО МОДЕЛИРОВАНИЯ

Numerical simulation of evolution of a convective cloud and precipitation during a thunderstorm event that took place on August 11, 2017 in Beijing (China) against a background of high aerosol air pollution was performed using a numerical nonstationary three-dimensional model. Different microphysical parameters of drops and ice particles which depend on aerosol pollution of the atmosphere, were varied: an autoconversion threshold for cloud droplets and raindrops and parameters of raindrop and hailstone size distribution. It was found for this case that liquid drops do not play a significant role in the convective cloud evolution. The effect of aerosol pollution both on the raindrop size spectrum and on the transition of cloud droplets to raindrops does not influence significantly dynamic, microphysical and electrical properties of the cloud. At the same time, the change in the ice particle spectrum towards the size decrease that happens under the influence of increased aerosol pollution, has a significant impact on the evolution of the cloud and precipitation. The amount of precipitation decreases both within the cloud and on the underlying surface. However, the lightning activity of the cloud changes little

A Two-Moment Bulk Parameterization of the Drop Collection Growth in Warm Clouds

Abstract To improve the modeling of warm rain initiation, a two-moment bulk parameterization of the drop collection growth in warm clouds is developed by two steps: (i) its prototype is first derived based on the analytic solution of the stochastic collection equation (SCE) with the Golovin kernel, and (ii) the prototype is then revamped empirically to fit the numerical solution of SCE with the real hydrodynamic collection kernel, reaching the final version of the parameterization. Since the final version represents the self-collection of cloud drops explicitly, it replicates warm rain initiation well even when liquid water content (cloud-drop number concentration) is very low (high). It also replicates the autoconversion threshold and time delay of rain initiation via a small autoconversion rate.

Sensitivity Experiments of Rainfall to Warm Cloud Auto-Conversion Threshold and Relative Humidity Threshold of Cloudiness in RegCM4.6 over the Maritime Continent

ABSTRACTIn the present work, sensitivity experiments for two parameter schemes are conducted using the Regional Climate Model System, version 4.6, to improve the model capability for reproducing rainfall over the Maritime Continent (MC). One parameter is the warm cloud auto-conversion threshold in the Emanuel convective scheme, and the other parameter is the relative humidity threshold of cloudiness in the subgrid explicit moisture microphysics scheme. Our results show that using the optimized values of these two parameters can reduce the rainfall bias over land in the western MC. In addition, we also show that the choice of the sea surface temperature forcing data is important in improving the model's performance. The improvement is confirmed from extreme year simulations and the long-run simulation in both spatial and temporal characteristics. The optimized simulation shows improved model performance in both wet and dry seasons. The underestimation of the annual and interannual rainfall variability is alleviated in the optimized simulation. This indicates the model's ability to reproduce the MC's rainfall under the appropriate parameterization schemes. We expect that our optimized parameterization can be used to reproduce more reliable downscaled rainfall data to support various climate research activities over the MC.

On the Relative Sensitivity of a Tropical Deep Convective Storm to Changes in Environment and Cloud Microphysical Parameters

Abstract Monte Carlo and Morris screening techniques are used to examine the relative sensitivity of deep convective simulations to changes in initial conditions (IC) versus changes to microphysical parameters (MP). IC are perturbed using a set of empirical orthogonal function–principal component pairs obtained from a database of tropical soundings, while MP are perturbed consistent with their range of realistic values. Monte Carlo experiments provide a broad overview of parameter–output response, while Morris screening techniques identify the most significant influences on specific model output variables. Changes to MP produce a similar order-of-magnitude response in convective hydrologic cycle, dynamics, and latent heating as changes to IC. Changes in IC appear to have a larger effect on radiative fluxes than perturbations to MP. The distribution of low-level latent heating reveals that changes in MP have a larger influence on cold pool properties than changes to the environment. The dominant effects are produced by a subset of cloud MP and thermodynamic structure functions, indicating perturbation of a subset of the control factors may be used to produce most of the variability in a short-term convective-scale ensemble forecast. The most influential MP are the autoconversion threshold, the rain particle size distribution intercept, and the ice particle fall speed parameters. The most influential EOFs are those that correspond to variability in lower- to midtropospheric temperature and water vapor, as well as zonal low-level shear. The results have implications for both the understanding of what influences convective development and the design of ensemble-based prediction and data assimilation systems.

An attempt to improve Kessler-type parameterization of warm cloud microphysical conversion processes using CloudSat observations

Improvements to the Kessler-type parameterization of warm cloud microphysical conversion processes (also called autoconversion) are proposed based on a large number of CloudSat observations between June 2006 and April 2011 over Asian land areas. The emphasis is given to the vertical distribution of liquid water content (LWC), particularly, the threshold values of LWC for autoconversion. The results warrant a new approach to the numerical parameterization of autoconversion in warm clouds. One feature of this new approach is that the autoconversion threshold, which has been treated as a constant in previous parameterization schemes, is diagnosed as a function of altitude by using a relationship between LWC and height (H) derived from CloudSat observations: $$LWC_{dig} = - 500.0\ln \left( {\frac{H} {{9492.2}}} \right)$$ . Under this framework, the threshold LWC decreases with increasing H, allowing autoconversion to occur in clouds with low LWC (approximately 0.3 g m−3) at levels above 5.5 km. Autoconversion rates calculated based on the new parameterization are compared to those calculated based on several commonly used parameterization schemes over a range of LWCs from 0.01 to 1.0 g m−3. The new scheme provides reasonable simulations of autoconversion at various vertical levels.

Examination of microphysical relationships and corresponding microphysical processes in warm fogs

In this paper, the microphysical relationships of 8 dense fog events collected from a comprehensive fog observation campaign carried out at Pancheng (32.2°N, 118.7°E) in the Nanjing area, China in the winter of 2007 are investigated. Positive correlations are found among key microphysical properties (cloud droplet number concentration, droplet size, spectral standard deviation, and liquid water content) in each case, suggesting that the dominant processes in these fog events are likely droplet nucleation with subsequent condensational growth and/or droplet deactivation via complete evaporation of some droplets. The abrupt broadening of the fog droplet spectra indicates the occurrence of the collision-coalescence processes as well, although not dominating. The combined effects of the dominant processes and collision-coalescence on microphysical relationships are further analyzed by dividing the dataset according to visibility or autoconversion threshold in each case. The result shows that the specific relationships of number concentration to volume-mean radius and spectral standard deviation depend on the competition between the compensation of small droplets due to nucleation-condensation and the loss of small droplets due to collision-coalescence. Generally, positive correlations are found for different visibility or autoconversion threshold ranges in most cases, although negative correlations sometimes appear with lower visibility or larger autoconversion threshold. Therefore, the compensation of small droplets is generally stronger than the loss, which is likely related to the sufficient fog condensation nuclei in this polluted area.

Sensitivity of the Aerosol Indirect Effect to Subgrid Variability in the Cloud Parameterization of the GFDL Atmosphere General Circulation Model AM3

AbstractThe recently developed GFDL Atmospheric Model version 3 (AM3), an atmospheric general circulation model (GCM), incorporates a prognostic treatment of cloud drop number to simulate the aerosol indirect effect. Since cloud drop activation depends on cloud-scale vertical velocities, which are not reproduced in present-day GCMs, additional assumptions on the subgrid variability are required to implement a local activation parameterization into a GCM.This paper describes the subgrid activation assumptions in AM3 and explores sensitivities by constructing alternate configurations. These alternate model configurations exhibit only small differences in their present-day climatology. However, the total anthropogenic radiative flux perturbation (RFP) between present-day and preindustrial conditions varies by ±50% from the reference, because of a large difference in the magnitude of the aerosol indirect effect. The spread in RFP does not originate directly from the subgrid assumptions but indirectly through the cloud retuning necessary to maintain a realistic radiation balance. In particular, the paper shows a linear correlation between the choice of autoconversion threshold radius and the RFP.Climate sensitivity changes only minimally between the reference and alternate configurations. If implemented in a fully coupled model, these alternate configurations would therefore likely produce substantially different warming from preindustrial to present day.

Analysis of the microphysical structure of heavy fog using a droplet spectrometer: A case study

The microphysical properties of a long-lasting heavy fog event are examined based on the results from a comprehensive field campaign conducted during the winter of 2006 at Pancheng (32.2 ◦ N, 118.7 ◦ E), Jiangsu Province, China. It is demonstrated that the key microphysical properties (liquid water content, fog droplet concentration, mean radius and standard deviation) exhibited positive correlations with one another in general, and that the 5-min-average maximum value of fog liquid water content was sometimes greater than 0.5 g m −3 . Further analysis shows that the unique combination of positive correlations likely arose from the simultaneous supply of moist air and fog condensation nuclei associated with the advection of warm air, which further led to high liquid water content. High values of liquid water content and droplet concentration conspired to cause low visibility (<50 m) for a prolonged period of about 40 h. Examination of the microphysical relationships conditioned by the corresponding autoconversion threshold functions shows that the collision-coalescence process was sometimes likely to occur, weakening the positive correlations induced by droplet activation and condensational growth. Statistical analysis shows that the observed droplet size distribution can be described well by the Gamma distribution.

Parameterization of the Autoconversion Process. Part II: Generalization of Sundqvist-Type Parameterizations

Abstract Existing Sundqvist-type parameterizations, which only consider dependence of the autoconversion rate on cloud liquid water content, are generalized to explicitly account for the droplet concentration and relative dispersion of the cloud droplet size distribution as well. The generalized Sundqvist-type parameterization includes the more commonly used Kessler-type parameterization as a special case, unifying the two different types of parameterizations for the autoconversion rate. The generalized Sundqvist-type parameterization is identical with the Kessler-type parameterization presented in Part I beyond the autoconversion threshold, but exhibits a more realistic, smooth transition in the vicinity of the autoconversion threshold (threshold behavior) in contrast to the discontinuously abrupt transition embodied in the Kessler-type parameterization. A new Sundqvist-type parameterization is further derived by applying the expression for the critical radius derived from the kinetic potential theory to the generalized Sundqvist-type parameterization. The new parameterization eliminates the need for defining the driving radius and for prescribing the critical radius associated with Kessler-type parameterizations. The two-part structure of the autoconversion process raises questions regarding model-based empirical parameterizations obtained by fitting simulation results from detailed collection models with a single function.

Validation of a cirrus parameterization with Meteosat Second Generation observations

A brightness temperature difference (BTD) technique is used to constrain the ice to snow autoconversion threshold, a tunable parameter of a bulk microphysical cloud scheme in a regional meteorological model. The technique based on a contrasted absorption property of ice crystals at two wavelengths within the atmospheric infrared window is applied to 3‐hourly Meteosat Second Generation (MSG) observations in the 8.7‐ and 10.8‐μm bands over southern Brazil. The cirrus coverage presents a diurnal cycle associated with tropical deep convection peaking at 1800 local solar time (LST). A similar signal is obtained from the regional model when the ice to snow autoconversion threshold is reevaluated using the BTD data. The improved diurnal cycle furthermore better captures the observed upper‐tropospheric humidity (UTH) maximum that lags the cirrus cover by 12 hours.

A smaller global estimate of the second indirect aerosol effect

Global estimates of the indirect aerosol effect much larger than 1 W m−2 in magnitude are difficult to reconcile with observations, yet climate models give estimates between −1 and −4.4 W m−2. We use a climate model with a new treatment of autoconversion to reevaluate the second indirect aerosol effect. We obtain a global‐mean value of −0.28 W m−2, compared to −0.71 W m−2 with the autoconversion treatment most often used in climate models. The difference is due to (1) the new scheme's smaller autoconversion rate, and (2) an autoconversion threshold that increases more slowly with cloud droplet concentration. The impact of the smaller autoconversion rate shows the importance of accurately modeling this process. Our estimate of the total indirect aerosol effect on liquid‐water clouds changes from −1.63 to −1.09 W m−2.

Mesoscale model cloud scheme assessment using satellite observations

An exploratory evaluation of the explicit cloud scheme of the mesoscale nonhydrostatic (Meso‐NH) model has been conducted by comparing synthetic METEOSAT brightness temperatures (BT) to the observed ones. Three different meteorological situations are examined to illustrate the expected degree of accuracy in simulating realistic synthetic BTs in the midlatitude and in the subtropics, with a horizontal grid length ranging from 75 to 12 km. It is shown that the model to satellite approach, which combines the output from a bulk explicit cloud scheme routinely used in mesoscale simulations with a detailed radiative transfer code, offers the possibility of tuning a critical parameter. For instance, tests made with three different values of an ice to snow autoconversion threshold reveal a profound impact on the synthetic BT maps which results in unbiased differences with satellite observations when the appropriate value is selected. The main discrepancies that remain are partly due to errors in the vertical or horizontal placement of the cloud layer or in the amount of condensates, but also due to the lack of subgrid‐scale cloudiness in the model. A similar test conducted on the ice water and the liquid water paths confirms the fairly good agreement with retrievals from microwave observations. The paper concludes by discussing the need not only to extend the model to satellite approach to other well‐documented cases but also to derive diagnostics from deep convection scheme characteristics in order to include the radiative effect of the convective towers in the generation of synthetic BT maps.

On the “tuning” of autoconversion parameterizations in climate models

Autoconversion is a highly nonlinear process, which is usually evaluated in global climate models (GCMs) from the mean in‐cloud value of the liquid‐water mixing ratio q′l. This biases the calculated autoconversion rate, and may explain why it usually seems to be necessary to reduce the autoconversion threshold to an unrealistically low value to obtain a realistic simulation in a GCM. Two versions of a threshold‐dependent autoconversion parameterization are compared in the CSIRO GCM. In the standard (“OLD”) treatment, autoconversion occurs in a grid box whenever the mean in‐cloud q′l exceeds the threshold qcrit, which is derived from a prescribed threshold cloud‐droplet radius rcrit. In the modified (“NEW”) version, the assumed subgrid moisture distribution from the model's condensation scheme is applied in each grid box to determine the fraction of the cloudy area in which q′l &gt; qcrit, and autoconversion occurs in this fraction only. Simulations are performed using both treatments, for present‐day and preindustrial distributions of cloud‐droplet concentration, and using different values for rcrit. Changing from the OLD to the NEW treatment means that rcrit can be increased from 7.5 μm to a more realistic 9.3 μm, while maintaining the global‐mean liquid‐water path at about the same value. Simulations for preindustrial and present‐day conditions are compared, to see whether the change of scheme alters the modeled cloud‐lifetime effect. It is found that the NEW scheme with rcrit = 9.3 μm gives a 0.5 W m−2 (62%) stronger cloud‐lifetime effect than the OLD scheme with rcrit = 7.5 μm.

Indirect forcing by anthropogenic aerosols: A global climate model calculation of the effective‐radius and cloud‐lifetime effects

A global climate model (GCM) that includes a physically based cloud scheme is used to calculate the indirect radiative forcing due to the modification of liquid‐water cloud properties by anthropogenic aerosols. The distribution of cloud‐droplet number concentration Nd required by the cloud scheme is estimated empirically from monthly mean fields of sulfate mass generated by a chemical transport model. The effects of anthropogenic changes in Nd are considered in the calculation of precipitation (the “cloud‐lifetime” effect) and of the droplet effective radius used in the shortwave and longwave radiation schemes (the “effective‐radius” effect). The modeled cloud‐droplet effective radii for present‐day conditions agree quite well with satellite‐retrieved values, although the land‐ocean and hemispheric contrasts are weaker in the model than in the observations. The total indirect forcing is −2.1 W m−2, including a small longwave forcing of +0.1 W m−2. The forcing results from a 1% increase in cloudiness, a 6% increase in liquid water path, and a 7% decrease in droplet effective radius. The breakdown of the total indirect forcing into the effective‐radius and cloud‐lifetime effects is estimated by performing separate GCM experiments in which each effect is included individually. The estimated forcings due to the effective‐radius and cloud‐lifetime effects are −1.2 and −1.0 W m−2, respectively. The calculated forcings show some sensitivity to the autoconversion threshold, the sulfate‐Nd relation, and the vertical distribution of sulfate, but in each case the cloud‐lifetime forcing is at least 25% of the total indirect forcing. These results suggest that the cloud‐lifetime effect should not be ignored in future calculations of the indirect forcing due to anthropogenic aerosols.