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Jiwen Fan, Yuan Wang, Daniel Rosenfeld, and Xiaohong Liu

Abstract

Over the past decade, the number of studies that investigate aerosol–cloud interactions has increased considerably. Although tremendous progress has been made to improve the understanding of basic physical mechanisms of aerosol–cloud interactions and reduce their uncertainties in climate forcing, there is still poor understanding of 1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, 2) the feedbacks between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and 3) the significance of cloud–aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoretical studies and important mechanisms on aerosol–cloud interactions and discusses the significances of aerosol impacts on radiative forcing and precipitation extremes associated with different cloud systems. The authors summarize the main obstacles preventing the science from making a leap—for example, the lack of concurrent profile measurements of cloud dynamics, microphysics, and aerosols over a wide region on the observation side and the large variability of cloud microphysics parameterizations resulting in a large spread of modeling results on the modeling side. Therefore, large efforts are needed to escalate understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties and cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed.

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Wenjun Cui, Xiquan Dong, Baike Xi, Zhe Feng, and Jiwen Fan

Abstract

Mesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs’ rainfall is therefore crucial in understanding their impact on the climate system. The V06B Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) half-hourly precipitation final product is a useful tool to study the precipitation characteristics of MCSs because of its global coverage and fine spatiotemporal resolutions. However, errors and uncertainties in IMERG should be quantified before applying it to hydrology and climate applications. This study evaluates IMERG performance on capturing and detecting MCSs’ precipitation in the central and eastern United States during a 3-yr study period against the radar-based Stage IV product. The tracked MCSs are divided into four seasons and are analyzed separately for both datasets. IMERG shows a wet bias in total precipitation but a dry bias in hourly mean precipitation during all seasons due to the false classification of nonprecipitating pixels as precipitating. These false alarm events are possibly caused by evaporation under the cloud base or the misrepresentation of MCS cold anvil regions as precipitating clouds by the algorithm. IMERG agrees reasonably well with Stage IV in terms of the seasonal spatial distribution and diurnal cycle of MCSs precipitation. A relative humidity (RH)-based correction has been applied to the IMERG precipitation product, which helps reduce the number of false alarm pixels and improves the overall performance of IMERG with respect to Stage IV.

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Guang J. Zhang, Jiwen Fan, and Kuan-Man Xu
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Damao Zhang, Zhien Wang, Andrew Heymsfield, Jiwen Fan, and Tao Luo

Abstract

Measurements of ice number concentration in clouds are important but still pose problems. The pattern of ice development in stratiform mixed-phase clouds (SMCs) offers an opportunity to use cloud radar reflectivity (Z e) measurements and other cloud properties to retrieve ice number concentrations. To quantify the strong temperature dependencies of ice crystal habits and growth rates, a one-dimensional (1D) ice growth model has been developed to calculate ice diffusional growth and riming growth along ice particle fallout trajectories in SMCs. The radar reflectivity and fallout velocity profiles of ice crystals calculated from the 1D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high-vertical-resolution radar measurements. A method has been developed to retrieve ice number concentrations in SMCs at a specific cloud-top temperature (CTT) and liquid water path (LWP) by combining Z e measurements and 1D ice growth model simulations. The retrieved ice number concentrations in SMCs are evaluated using integrated airborne in situ and remote sensing measurements and three-dimensional cloud-resolving model simulations with a bin microphysical scheme. The statistical evaluations show that the retrieved ice number concentrations in the SMCs are within an uncertainty of a factor of 2.

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Jong-Hoon Jeong, Jiwen Fan, Cameron R. Homeyer, and Zhangshuan Hou

Abstract

Hailstones are a natural hazard that pose a significant threat to property and are responsible for significant economic losses each year in the United States. Detailed understanding of their characteristics is essential to mitigate their impact. Identifying the dynamic and physical factors contributing to hail formation and hailstone sizes is of great importance to weather and climate prediction and policymakers. In this study, we have analyzed the temporal and spatial variabilities of severe hail occurrences over the U.S. southern Great Plains (SGP) states from 2004 to 2016 using two hail datasets: hail reports from the Storm Prediction Center and the newly developed radar-retrieved maximum expected size of hail (MESH). It is found that severe and significant severe hail occurrences have a considerable year-to-year temporal variability in the SGP region. The interannual variabilities have a strong correspondence with sea surface temperature anomalies over the northern Gulf of Mexico and there is no outlier. The year 2016 is identified as an outlier for the correlations with both El Niño–Southern Oscillation (ENSO) and aerosol loading. The correlations with ENSO and aerosol loading are not statistically robust to inclusion of the outlier 2016. Statistical analysis without the outlier 2016 shows that 1) aerosols that may be mainly from northern Mexico have the largest correlation with hail interannual variability among the three factors and 2) meteorological covariation does not significantly contribute to the high correlation. These analyses warrant further investigations of aerosol impacts on hail occurrence.

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Yunyan Zhang, Stephen A. Klein, Jiwen Fan, Arunchandra S. Chandra, Pavlos Kollias, Shaocheng Xie, and Shuaiqi Tang

Abstract

Based on long-term observations by the Atmospheric Radiation Measurement program at its Southern Great Plains site, a new composite case of continental shallow cumulus (ShCu) convection is constructed for large-eddy simulations (LES) and single-column models. The case represents a typical daytime nonprecipitating ShCu whose formation and dissipation are driven by the local atmospheric conditions and land surface forcing and are not influenced by synoptic weather events. The case includes early morning initial profiles of temperature and moisture with a residual layer; diurnally varying sensible and latent heat fluxes, which represent a domain average over different land surface types; simplified large-scale horizontal advective tendencies and subsidence; and horizontal winds with prevailing direction and average speed. Observed composite cloud statistics are provided for model evaluation.

The observed diurnal cycle is well reproduced by LES; however, the cloud amount, liquid water path, and shortwave radiative effect are generally underestimated. LES are compared between simulations with an all-or-nothing bulk microphysics and a spectral bin microphysics. The latter shows improved agreement with observations in the total cloud cover and the amount of clouds with depths greater than 300 m. When compared with radar retrievals of in-cloud air motion, LES produce comparable downdraft vertical velocities, but a larger updraft area, velocity, and updraft mass flux. Both observations and LES show a significantly larger in-cloud downdraft fraction and downdraft mass flux than marine ShCu.

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Yi-Chin Liu, Jiwen Fan, Kuan-Man Xu, and Guang J. Zhang

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We use 3D cloud-resolving model (CRM) simulations of two mesoscale convective systems at midlatitudes and a simple statistical ensemble method to diagnose the scale dependency of convective momentum transport (CMT) and CMT-related properties and evaluate a parameterization scheme for the convection-induced pressure gradient (CIPG) developed by Gregory et al. Gregory et al. relate CIPG to a constant coefficient multiplied by mass flux and vertical mean wind shear. CRM results show that mass fluxes and CMT exhibit strong scale dependency in temporal evolution and vertical structure. The upgradient–downgradient CMT characteristics for updrafts are generally similar between small and large grid spacings, which is consistent with previous understanding, but they can be different for downdrafts across wide-ranging grid spacings. For the small to medium grid spacings (4–64 km), Gregory et al. reproduce some aspects of CIPG scale dependency except for underestimating the variations of CIPG as grid spacing decreases. However, for large grid spacings (128–512 km), Gregory et al. might even less adequately parameterize CIPG because it omits the contribution from either the nonlinear-shear or the buoyancy forcings. Further diagnosis of CRM results suggests that inclusion of nonlinear-shear forcing in Gregory et al. is needed for the large grid spacings. For the small to median grid spacings, a modified Gregory et al. with the three-updraft approach help better capture the variations of CIPG as grid spacing decreases compared to the single updraft approach. Further, the optimal coefficients used in Gregory et al. seem insensitive to grid spacings, but they might be different for updrafts and downdrafts, for different MCS types, and for zonal and meridional components.

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Xiang Ni, Andreas Muehlbauer, John T. Allen, Qinghong Zhang, and Jiwen Fan

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Hail size records are analyzed at 2254 stations in China and a hail size climatology is developed based on gridded hail observations for the period 1960–2015. It is found that the annual percentiles of hail size records changed sharply and national-wide after 1980, therefore two periods, 1960–79 and 1980–2015, are studied. There are some similarities between the two periods in terms of the characteristics of hail size such as the spatial distribution patterns of mean annual maximum hail size and occurrence week of annual maximum hail size. The 1980–2015 period had higher observation density than the 1960–79 period, but showed smaller mean annual maximum hail size, especially in northern China. In the majority of grid boxes, the annual maximum hail size experienced a decreasing trend during the 1980–2015 period. A Gumbel extreme value model is fitted to each grid box to estimate the return periods of maximum hail size. The scale and location parameter of the fitted Gumbel distributions are higher in eastern China than in western China, thereby reflecting a greater likelihood of large hail in eastern China. In southern China, the maximum hail size exceeds 127 mm for a 10-yr return period, whereas in northern China maximum hail size exceeds this threshold for a 50-yr return period. The Gumbel model is found to potentially underestimate the maximum hail size for certain return periods, but provides a more informed picture of the spatial distribution of extreme hail size and the regional differences.

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Yan Yang, Jiwen Fan, L. Ruby Leung, Chun Zhao, Zhanqing Li, and Daniel Rosenfeld

Abstract

A significant reduction in precipitation in the past decades has been documented over many mountain ranges such as those in central and eastern China. Consistent with the increase of air pollution in these regions, it has been argued that the precipitation trend is linked to the aerosol microphysical effect on suppressing warm rain. Rigorous quantitative investigations on the reasons responsible for the precipitation reduction are lacking. In this study, an improved Weather Research and Forecasting (WRF) Model with online coupled chemistry (WRF-Chem) is applied and simulations are conducted at the convection-permitting scale to explore the major mechanisms governing changes in precipitation from orographic clouds in the Mt. Hua area in central China. It is found that anthropogenic pollution contributes to a ~40% reduction of precipitation over Mt. Hua during the 1-month summertime period. The reduction is mainly associated with precipitation events associated with valley–mountain circulation and a mesoscale cold-front event. In this paper (Part I), the mechanism leading to a significant reduction for the cases associated with valley–mountain circulation is scrutinized. It is found that the valley breeze is weakened by aerosols as a result of absorbing aerosol-induced warming aloft and cooling near the surface as a result of aerosol–radiation interaction (ARI). The weakened valley breeze and the reduced water vapor in the valley due to reduced evapotranspiration as a result of surface cooling significantly reduce the transport of water vapor from the valley to mountain and the relative humidity over the mountain, thus suppressing convection and precipitation in the mountain.

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Zachary J. Lebo, Ben J. Shipway, Jiwen Fan, Istvan Geresdi, Adrian Hill, Annette Miltenberger, Hugh Morrison, Phil Rosenberg, Adam Varble, and Lulin Xue
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