The Impact of Aerosol Vertical Distribution on a Deep Convective Cloud

This study investigates the effects of aerosol vertical distribution on a deep convective cloud system. We intend to elucidate the mechanisms for aerosols entering the cloud from different heights, and how they affect cloud microphysics and precipitation. A thermal bubble is released at 1.5 km initially to run an idealized case using the Weather Research and Forecast (WRF) model. The aerosol layer with high concentration was initially put at different altitudes in the model to study the mechanisms and the number of aerosols entering the cloud. It was found that there are three mechanisms for aerosols from different heights to enter the cloud, depending on their relative height with the thermal bubble. Aerosols from lower altitudes (below 1 km) enter the cloud through pumping, while aerosols from higher altitudes (2–3 km, 3–5 km) enter the cloud through entrainment. Both mechanisms lead to low cloud condensation nuclei (CCN) concentration in the cloud. Only aerosols from intermediate altitudes (1–2 km), which is the same as the initial height of the thermal bubble, enter the cloud mainly by ascending with the bubble and lead to high CCN concentration in the cloud. The differences in activated CCN concentration affect the microphysical processes and precipitation remarkably. For the simulations with an initial aerosol layer at 1–2 km and 0–5 km, aerosols can enter the cloud more efficiently than the other four simulations. More activated CCNs in these two simulations lead to more graupels with smaller sizes at higher altitudes, which delays the precipitation but makes the precipitation last longer. However, the accumulated precipitation is similar in all six simulations, no matter what aerosol vertical distribution is like. The results in this study indicate that the altitude of aerosol layers determines the mechanisms for aerosols entering clouds, CCN concentration in the cloud, and to what extent the cloud microphysical processes and precipitation are affected.

Radiometric Performance Evaluation of FY-4A/AGRI Based on Aqua/MODIS

Fengyun-4A (FY-4A) is the first satellite of the Chinese second-generation geostationary orbit meteorological satellites (FY-4). The Advanced Geostationary Radiation Imager (AGRI), onboard FY-4A does not load with high-precision calibration facility in visible and near infrared (VNIR) channel. As a consequence, it is necessary to comprehensively evaluate its radiometric performance and quantitatively describe the attenuation while using its VNIR data. In this paper, the radiometric performance at VNIR channels of FY-4A/AGRI is evaluated based on Aqua/MODIS data using the deep convective cloud (DCC) target. In order to reduce the influence of view angle and spectral response difference, the bi-directional reflectance distribution function (BRDF) correction and spectral matching have been performed. The evaluation result shows the radiometric performance of FY-4A/AGRI: (1) is less stable and with obvious fluctuations; (2) has a lower radiation level because of 24.99% lower compared with Aqua/MODIS; 3) has a high attenuation with 9.11% total attenuation over 2 years and 4.0% average annual attenuation rate. After the evaluation, relative radiometric normalization between AGRI and MODIS in VNIR channel is performed and the procedure is proved effective. This paper proposed a more reliable reference for the quantitative applications of FY-4A data.

Impacts of Varying Concentrations of Cloud Condensation Nuclei On Deep Convective Cloud Updrafts – A Multimodel Assessment

This study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations amongst seven, state-of-the-art, cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced, updraft changes.The models show several consistent trends. In general, the changes between the High-CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5-15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~-5-0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone.

Theoretical Analysis of the Entrainment–Mixing Process at Cloud Boundaries. Part II: Motion of Cloud Interface

The entrainment–mixing process leads to formation of a cloud–environment interface zone, consisting of the cloud dilution zone, where the liquid water content decreases as the distance from the cloud interior increases, and a humid shell with higher humidity in comparison with the dry environment. The time evolution of the location and width of these zones is analyzed by solving the diffusion–evaporation equation for the open region in the vicinity of the cloud–dry air interface. Upon normalization, the problem is reduced to a one-parametric one, the governing parameter being the potential evaporation parameter R < 0, which is proportional to the ratio of saturation deficit in the dry air to the available liquid water content in the cloud air. It is shown that the widths of the dilution zone and the humid shell increase with time. At R < −1, the interface between the dilution zone and the humid shell (i.e., the cloud edge) moves toward the cloud interior (i.e., the cloud dissipates). If R > −1, the cloud edge moves outward; that is, the mixing leads to an increase in the cloud volume. It is shown that the relative humidity remains high within most of the cloud dilution zone, and the effective radius changes only slightly, especially in growing clouds, where the effective radius changes by less than 10% within more than 80% of the cloud dilution zone. The strong decrease in the LWC is accompanied by a corresponding decrease in the droplet concentration. The study is illustrated by means of two examples of clouds: a small cumulus (Cu) typical of the trade wind zone and a deep convective cloud typical of the monsoon period over India. It is shown that while the small Cu tends to dissipate, the deep convective cloud expands. The characteristic sizes of the dilution zone and the humid shell are several tens of meters for the small Cu and several hundred meters for the deep convective cloud.

The Inter-Calibration of the DSCOVR EPIC Imager with Aqua-MODIS and NPP-VIIRS

The Deep Space Climate Observatory (DSCOVR) through the earth polychromatic imaging camera (EPIC) continuously observes the illuminated disk from the Lagrange-1 point. The EPIC sensor was designed to monitor the diurnal variation of ozone, clouds, aerosols, and vegetation, especially those features that benefit from observation near-backscatter conditions. The EPIC sensor does not contain any onboard calibration systems. This study describes the inter-calibration of EPIC channels 5 (0.44 µm), 6 (0.55 µm), 7 (0.68 µm), and 10 (0.78 µm) with respect to Aqua-MODIS and NPP-VIIRS. The calibration is transferred using coincident ray-matched reflectance pairs over all-sky tropical ocean (ATO) and deep convective cloud (DCC) targets. A robust and automated image-alignment technique based on feature matching was formulated to improve the navigation quality of the EPIC images. The EPIC V02 dataset exhibits improved navigation over V01. As the visible channels display similar spatial features, a single visible channel can be used to co-register the remaining visible bands. The VIIRS-referenced EPIC ATO and DCC ray-matched calibration coefficients are within 0.3%. The EPIC four-year calibration trends based on VIIRS are within 0.15%/year. The MODIS-based EPIC calibration coefficients were compared against the Geogdzhayev and Marshak 2018 published calibration coefficients and were found to be within 1.6%.